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Issue Cover

Article Contents

1. introduction, 2. green logistics and sustainability, 3. city logistics, 4. vehicle routing problems, 5. current trends and business and social innovations, 6. conclusion and recommendations, acknowledgements, last mile logistics: research trends and needs.

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Emrah Demir, Aris Syntetos, Tom van Woensel, Last mile logistics: Research trends and needs, IMA Journal of Management Mathematics , Volume 33, Issue 4, October 2022, Pages 549–561, https://doi.org/10.1093/imaman/dpac006

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Aspiring green agendas in conjunction with tremendous economic pressures are resulting in an increased attention to the environment and technological innovations for improving existing logistics systems. Last mile logistics, in particular, are becoming much more than a consumer convenience necessity and a transportation optimization exercise. Rather, this area presents a true opportunity to foster both financial and environmental sustainability. This paper investigates recent technological advancements and pending needs related to business and social innovations, emphasizing green logistics and city logistics concepts. We discuss various pertinent aspects, including drones, delivery robots, truck platooning, collection and pickup points, collaborative logistics, integrated transportation, decarbonization and advanced transport analytics. From a mathematical perspective, we focus on the basic features of the vehicle routing problem and some of its variants. We provide recommendations around strategies that may facilitate the adoption of new effective technologies and innovations.

In recent years, the vulnerability of supply chains and transportation networks was exposed at a time when the demand for last mile logistics services soared. While COVID-19 has been a significant threat to almost everything as part of modern life, relevant operational responses have been almost exclusively reactive than proactive. Similarly, the logistics networks connecting us to goods have been under immense pressure due to increased online shopping. The value of public and private partnerships for the environment and technology integration has never been more crucial for the transport industry. As customers ask for fast and reliable last mile delivery, bringing technological innovation into sustainable transportation systems is urgently needed. Before the pandemic, the logistics industry was under pressure to improve their operations for cost reduction and profit making in a highly competitive market while dealing with unending requirements of their customers. For example, in their research, Gevaers et al. (2014) investigated the cost characteristics of last mile delivery services. In order to quantify the costs, their proposed simulation model considered the level of customer service, type of delivery, geographical area, market, density, fleet and the environment. It is highlighted that the last mile-related costs can differ greatly depending on these factors.

Environmental sustainability has never attracted equal focus compared with the economic priorities of retailers and logistics service providers (LSPs). It is now time to consider both financial and environmental sustainability in an attempt to escape from the disastrous impact of the pandemic and be ready for the future. There is an excellent opportunity to make changes and improve the design and operations of freight transportation soon as discussed in Meersman & Van de Voorde (2019) . Looking at the vulnerability of the logistics systems, the logistics industry needs to make the best use of available resources to ensure a sustainable future for all. Green logistics has been one of the most studied topics in the last decade, and it has brought various ideas and algorithms for tackling emissions, particularly greenhouse gases (GHGs) ( Dekker et al. , 2012 ; Demir et al. , 2014 ; Marrekchi et al. , 2021 ; Moghdani et al. , 2021 ). We can extend this area of research by looking at the latest technological, social and business innovations as a remedy to last mile problem.

Freight transportation manages the complete operation of the movement of freight and related resources from a starting location to a final destination by paying particular attention to customers’ requirements ( Ghiani et al. , 2013 ; Toth & Vigo, 2014 ). In practice, traditional LSPs aim to manage these activities at the lowest possible logistics cost and risk to be a preferable option for shippers and customers. Therefore, it is essential to optimize the whole logistics network, considering the characteristics of each component used in freight transportation. As noted in the literature, there are two main areas in freight transportation based on the coverage area of distribution/collection services. These two types of transportation are called long-haul and short-haul transportation. In long-haul transportation, freight is transported over a long distance (i.e. minimum hundreds of kilometres). Short-haul transportation is referred to as a small distance delivery within a city or region. This paper focuses on short-haul transportation as it is the most crucial part of the supply networks and the most relevant one for last mile logistics.

Due to the unprecedented increase in e-commerce and accessibility of goods via the Internet, the role of LSPs has become more critical in the supply network. The Swiss Reinsurance company estimates that the population living in areas classified as urban will increase by approximately 1.4 billion to 5 billion from 2011 to 2030 ( DHL, 2014 ). This will make the logistics systems more complicated than before. The cheapest delivery to satisfy customers’ needs has been the top priority for the logistics industry. Nowadays, the commitments for on-time delivery and reduced or net-zero emission (GHGs and air pollutants) are also becoming very important targets in a competitive and cost-driven logistics market ( Savelsbergh & Van Woensel, 2016 ).

As the most crucial part of the supply network, the road transportation mode is the most used and preferred option by the logistics industry. The whole process in road freight needs to deal with several decision-making stages. At the lowest level (operational-level) of planning, the Vehicle Routing Problem (VRP) has been extensively studied since the original work by Dantzig & Ramser (1959) . The main objective in this problem is to obtain a set of routes for vehicles starting and ending at a depot to visit customers’ locations. The problem also considers several practical operational constraints. These may include vehicle capacity or compartment volume, distance or duration, customers’ time windows (i.e. hard or soft), and other related customer, product, resource or LSP-related specific requirements.

Traditionally, the minimization of the travelled distance was considered as the main objective in the VRP literature. With the increasing emphasis on the environment, the interaction of operational research with automotive engineering highlighted various factors to accurately estimate fuel consumption. This interaction has to lead to the development of green logistics (and green vehicle routing as a sub-category) topic in the operational research literature ( Demir et al. , 2014 ; Moghdani et al. , 2021 ).

Another positive impact on freight transportation from the effects of increased e-commerce sales is the acceleration of the adoption of technological innovation for the industry. Seamless delivery and the use of new alternative resources, such as drones, delivery robots and truck platooning have led to new opportunities for the logistics industry. This paper presents a brief discussion on how the last mile logistics have evolved around green logistics (or sustainability) and technological innovations in recent years. This discussion will highlight the current achievements and the outlook of future needs on last mile logistics. We note that our focus is mostly on vehicle routing optimization and related developments in the context of last mile logistics. Other aspects of last mile logistics, such as the location problems and humanitarian logistics, are not covered in this paper.

The scientific and visionary contributions of this paper is threefold: (i) to discuss the importance of green vehicle routing and city logistics for the last mile delivery, (ii) to briefly introduce the VRP and some of its variants, (iii) to review the latest technological developments in last mile logistics. The remainder of this ‘positioning’ paper is organized into five sections. Section 2 presents a brief review on green vehicle routing, whereas section 3 discusses recent research in city logistics. Section 4 provides relevant VRPs along with an example of VRP mathematical formulation. In section 5 , we discuss contemporary topics related to last mile logistics. Conclusions and the outlook of future research needs on last mile logistics are provided in section 6 .

This section discusses how green logistics (and sustainability) is shaping the planning of vehicle routing activities from the last mile perspective.

Green logistics is an area that focuses on manufacturing and delivering freight to avoid the depletion of scarce natural resources. We focus only on the distribution part of green logistics in this paper. From this standpoint, green vehicle routing is a specific research domain in green logistics that studies VRPs and related negative externalities. In this research domain, vehicles running on petroleum-based fuels (petrol or diesel) or alternative cleaner fuels are explicitly considered for a better and more efficient route planning.

The most studied negative externalities are GHG emissions. They are primarily generated from power stations, transportation and industrial processes. As the primary reference metric, the CO |$_2$| -equivalent (CO |$_2$| e) is used to compare emissions based on their global warming potential by translating other gases to the equivalent amount of CO |$_2$|⁠ . More specifically, all gaseous emissions from transportation can be converted to the amount of CO |$_2$| needed to create the same effect as CO |$_2$| e. The reduction of emissions is an essential topic for obvious reasons, and governments are trying to tackle this problem. Since 2016, transportation has become the largest emitting sector in the UK. The UK’s transportation sector was accountable for 27% of the total-generated emissions in 2019. Of the total emissions, a large share of emissions (91%) came from road transport vehicles in the same year ( BEIS, 2021 ). With regards to freight transportation, heavy goods vehicles were responsible for 18% of road transport emissions (equivalent to 19.5 MtCO |$_2$| e), and delivery vans were responsible for 17% of emissions (equivalent to 19 MtCO |$_2$| e). While road transportation was one of the sectors most affected by the pandemic, emissions are likely to increase as transport demand increases. Next to the generation of GHGs, the logistics industry also generates large amounts of air pollutants. These include particulate matter, CO (carbon monoxide), ozone (O |$_3$|⁠ ) and hazardous air pollutants.

As CO |$_2$| or CO |$_2$| e is directly proportional to fuel consumption, the generated (on-road) emissions can be calculated by looking at the fuel consumption rate. The ultimate goal in green vehicle routing is to produce greener transportation plans (or routes) based on fuel consumption estimation. However, the methodology for calculating emissions can be in different forms than each other. For example, vehicle-generated emissions depend on various factors, including vehicle occupancy and age, fuel type, engine temperature, vehicle speed and load. However, from an operational planning perspective, vehicle payload and speed are the more relevant and controllable factors in routing. Such discussions have started the green vehicle routing domain as various factors and methodologies are available in the literature. Significantly, the interest in fuel consumption modelling within routing domain has created a great deal of research in the operational research domain.

Next to emissions, the literature has also focused on other types of negative externalities. The other negative externalities of freight transportation include noise pollution, traffic congestion, road accidents and excessive land use. We refer the interested readers to literature on (see, e.g. Brons & Christidis, 2012 ; McAuley, 2010 ) for more details. Later, Demir et al. (2015) has also developed a comprehensive framework for negative externalities of road freight transportation as shown in Figure 1 .

The most common negative externalities of road transportation. Source: Demir et al. (2015).

The most common negative externalities of road transportation. Source: Demir et al. (2015) .

Figure 1 presents the details of negative externalities of road transportation. As highlighted in the figure, the focus should be on emissions, and all other externalities of transportation should be carefully considered through better and more efficient transport planning. We note that there is good progress on GHGs-related studies in the literature, but more research is needed for other types of negative externalities. From the supply chain management perspective, there is also good progress on sustainability. For example, Luis et al. (2021) developed an optimization model for a sustainable closed-loop supply chain network with conflicting objectives (i.e. the minimization of the total logistic costs and the total amount of carbon emissions). The authors provided a mathematical model and matheuristic algorithm to investigate the trade-offs between conflicting objectives.

The birth of green VRPs in the operational research domain has created various analytical methods for making better decisions in last mile logistics. Various authors have proposed mathematical formulations and solution algorithms tailored specifically for the reduction of emissions. Next to distance-minimization in routing problems, authors in this domain have proposed more comprehensive objective functions and dealt with more practical constraints. For example, vehicle speed and payload have become the most important decision variables for reducing emissions. Using different type of emissions modelling for the calculation of emissions required more complex and advanced analytical techniques. In their study, Leenders et al. (2017) investigated the allocation of emissions to a specific shipment in routing by considering more advanced fuel consumption formulae. The authors looked at terrain, distance, payload and the fuel consumption rates of empty and loaded vehicle. Their research highlights the importance of considering more holistic approach for estimating emissions and fuel consumption. Considering the complexity of fuel consumption modelling, there is still need for in-depth research for developing advanced methodologies, including exact and approximations methods.

This section briefly discusses how city logistics became an essential area of research in the logistics literature.

Logistics management is a complex but crucial activity. It includes supply, distribution, production and reverse logistics. Each of these dimensions looks at a different aspect of the supply network. The focus of our paper is the distribution of goods to customers. The e-commerce hype in the last decade has fundamentally changed the way customers purchase and consume products, and the expectations for delivery has also similarly changed over the years. Before the pandemic, 35% of industrial leasing could be attributed to the e-commerce business. In 2020, the e-commerce logistics market had grown more than 27%. To sustain profitable and environmental last mile delivery in urban areas, the topic of city logistics has gained more popularity in the transport industry. In simple terms, city logistics is considered the delivery and/or collection of parcels in cities. It also promotes cleaner transportation modes (i.e. rail, maritime), new handling and storage processes, reduced inventories and waste, reverse logistics, attended delivery, next-day, same-day and instant delivery services. From an operational perspective, the performance of city logistics requires seamless planning of vehicle routes to reduce empty miles, unnecessary driving and idling. In addition, city logistics operations require more efficient, light and modular vehicles that run on alternative or cleaner energy.

Similar to green vehicle routing, city logistics also pay attention to the environmental impact of all logistical operations in an urban environment. Savelsbergh & Van Woensel (2016) discuss the importance of city logistics for urban development. The authors also pointed out the requirements of city logistics, such as connectivity, big data and analytics, automation and automotive technology. Other aspects of city logistics are discussed by Taniguchi & Thompson (2018) , who particularly look at the impacts of city logistics on the environment.

One of the main tasks in city logistics is to establish coordination and consolidation opportunities between different stakeholders and it is a crucial success factor for the city logistics. Next to finding the right location decision, there is also need for zero and low-emission zones within urban areas (see, e.g. Lurkin et al. , 2021 ). The classic approach of running smooth city logistics activities is to consolidate freight volumes outside the city without creating unnecessary trips. Normally, the term urban distribution centres is used to refer these specific locations outside the city. From these locations, the handled freight is then moved into the cities using cleaner and alternative vehicle technologies or services. This two-level problem is also known as two-echelon distribution problem in the literature. By adding more distribution centres closer the cities, the supply chain can be extended to improve efficiency of both upstream and downstream ( Savelsbergh & Van Woensel, 2016 ). For a recent review paper we refer to Sluijk et al. (2022) . In the next section, we define the most applicable VRP formulation for the last mile logistics.

A fundamental last mile problem is to find a set of routes to serve a set of customers located in a geographical region. As the problem has many dimensions, such as a vehicle, operation, driver and fuel type, many studies focus on various dimensions of routing.

The VRP deals with designing vehicle routes subject to various constraints. The basic assumptions of the VRP can be listed as follows: (i) vehicle(s) must start and end at the same depot; (ii) each customer must be visited only once by a vehicle and (iii) the total payload in a vehicle must not surpass the available vehicle capacity. These assumptions are the basic features of the standard VRP. Due to customers’ requirements and operational challenges in last mile logistics, various VRPs and mathematical formulations have been proposed in the literature. We refer to studies on VRP and its variants for more details, see e.g. Toth & Vigo (2014) ; Vidal et al. (2020) . There are also other studies that look at more several practical constraints. For example, Derigs & Pullmann (2016) studied different strategies for the solution of a variety of rich VRPs with regards to solution quality and speed. The authors proposed variable neighbourhood search algorithm by considering several modules for different types of VRP features.

The standard VRP with distance minimization is known as the capacitated VRP (CVRP) and it can be defined mathematically as follows. We assume that a complete graph |${G} = ({N}, {A})$| includes node set |${N} = \{0, 1, 2,..., n\}$| and arc set |$\in{A} = \{{i,j}: {i,j} \in{N}, i \neq j\}$|⁠ . Each node (customer) |$i \in{N} \backslash \{0\}$| is defined with a demand q |$_i$|⁠ . The depot is considered as node |$0$|⁠ . All homogeneous vehicles ( m ) are located and available at the depot. Each arc ( i , j ) |$\in{A}$| is quantified with a distance d |$_{ij}$| between nodes |$i$| and |$j$|⁠ . Moreover, the vehicle capacity is denoted with |${Q}$|⁠ . The objective in the CVRP is to obtain a set of vehicle routes with the lowest total travelling distance. The closest CVRP variant is the distance constrained VRP (DVRP). In the DVRP, capacity-related constraints are changed with other constraints such that the length of a route must not surpass the defined distance range.

Another practical VRP variant is known as the VRP with pickup and delivery (VRPPD). This problem is finding a set of vehicle routes for a group of requests. This can be very relevant for LSPs who wish to simultaneously or subsequently serve pickup and delivery customers in the same route. There are also other variants of the VRPPD available in the literature. In the case of real-time vehicle routing optimization, dynamic VRP formulations can be used for dispatching vehicles to serve customers. Some parts of the transport plan must be decided beforehand, and the plans may need to be revised regularly in practice. This makes the routing problem more complex but practical for the logistics industry.

Another important variant is known as the production routing problem in the literature. This problem considers a more complex but practical planning problem that jointly optimizes production, inventory, distribution and routing. In the study of Shahrabi et al. (2021) , the authors studied the same problem with time windows, deterioration and split delivery. The authors specifically looked at the bi-objective (i.e. economic and social sustainability) model for a single product. They also proposed an interval robust approach and extensive analysis are conducted on a real-life case on a food factory.

The most relevant extension of the VRP in last mile logistics is the VRP with time windows (VRPTW). Next to customer’s demand, each customer should also be served within predefined time intervals. For all locations (a set of customers and depot) |$i (i \in{N}_0)$|⁠ , a time window |$[{a}_i, {b}_i]$| is defined. In this delivery problem, each customer has to be served within this interval. The delivery should begin at customer |$i (i \in{N}_0)$| just after the lower bound of time window a |$_i$| but not later than the upper bound of time window b |$_i$|⁠ . Also, if the vehicle arrives at customer |$i$| location before the start a |$_i$|⁠ , the vehicle should wait the time a |$_i$| to commence delivery.

As an example VRP model formulation, a mixed-integer linear programming model for the VRPTW is presented below. The following decision variables are used for the model.

The objective function ( 4.1 ) is the minimization of the total distance. Constraints ( 4.2 ) ensure that a vehicle must departure from the depot. Constraints ( 4.3 ) and ( 4.4 ) are the degree constraints to ensure each customer is visited one time only. Constraints ( 4.5 ) and ( 4.6 ) state the flows of payload on each arc chosen in a solution. Constraints ( 4.7 )–( 4.9 ), where |$K$| and |$L$| are large numbers. They also ensure the time window features of the problem. Constraints ( 4.10 )–( 4.12 ) define non-negativity conditions.

This section provides a discussion on recent trends and developments in the last mile logistics. More specifically, we discuss how these contemporary topics affect last mile logistics practices.

When considering new technological instruments for adoption, one may consider the ‘Law of Disruption’ model, which is proposed by Downes (2009) . The author explains how digital life has changed and how technology develops exponentially while social, economic and legal systems change incrementally. This law presents a pattern of how different types of change manifest themselves. The author also points out that technological innovations are generally ahead of social and political change. As in other industries, we can also expect regulatory barriers or negative public perception to remain in effect in the next 5–10 years for the logistics sector. This is more or less the case for all technologies and innovations discussed here. Especially, there is a need for mathematical proofs and evidence before the actual implementation. Mathematical modelling and optimization can help promoting these technologies and innovations by providing quantitative justification. More research can aid policy makers and governments to take action for greener transportation, especially within populated urban areas. We will now discuss some of these latest developments to attract more attention to current technologies and environmental concerns.

5.1 Unmanned aerial vehicles (drone)

An unmanned aerial vehicle (UAV) is an aircraft without any pilot. It can be fully or partially autonomous. This new technology is available for use in freight transportation, and a wide range of research is available in the literature. Interested readers are referred to original review papers on UAVs by Macrina et al. (2020) ; Rojas Viloria et al. (2021) and Rovira-Sugranes et al. (2022) .

In a recent study, Kundu et al. (2021) studied a variant of the travelling salesman problem (TSP) as denoted flying sidekick TSP. In this variant, the authors consider a single vehicle case using only one drone to serve customers. In this problem setting, drone can be launched from the vehicle at customer location. The driver and drone can simultaneously deliver packages. The authors propose a novel split algorithm and heuristic method to the studied problem. Freight transportation can benefit from UAVs as they can be used to deliver goods in the last mile ( DHL, 2014 ). Primarily, customers are interested in receiving their orders with the use of UAVs. Even though there are several advantages, it will not be easy to replace traditional road vehicle-only transportation soon. However, we have seen various small applications or trials of UAVs used in recent years. During the pandemic, companies have successfully deployed UAVs for last mile delivery. UAV technologies can be a sustainable option in the context of the last mile. These resources are already utilized by logistics and retailer companies, such as DHL International, United Parcel Service and Amazon.

From an operational perspective, UAVs can play a vital role in last mile logistics as they are fast and capable of carrying multiple packages in different weights. However, legal challenges and public perception need to be addressed before utilizing them in urban areas.

5.2 Unmanned ground vehicles (delivery robot)

An unmanned ground vehicle (UGV) is a type of vehicle that is operated on the ground without an onboard human presence. They can be used for transportation in urban areas to minimize delivery times. As a practical solution, the integration of UGVs with delivery vans can offer greener solutions than using only delivery vans. As UGVs are powered by clean electricity, they do not produce emissions themselves. As a successful trial, Starship Technologies had been experimenting with the delivery system with UGVs in London in 2020. Chen et al. (2021) studied an urban delivery problem using robots as assistants. In their delivery system, the traditional delivery van serves the customer and acts as a mothership for its robots in the meantime. When the van is parked, robots can be dispatched to their target customer(s) and return to the same place where they depart from to rendezvous with the mothership van. This is a very realistic example of UGVs’ use in practice.

From an operational perspective, UGVs have particular advantages over UAVs. Since most UAVs are powered by small-capacity batteries that last less than half an hour (on average), their capacities and flying ranges are quite limited. However, UGVs have more loading capacity, and their range is much more than UAVs. With an integrated delivery van and UGVs, drivers can also supervise UGVs in certain areas, which is not the case for UAVs.

5.3 Collection and delivery points

As an alternative solution in urban areas, collection and delivery points can improve the logistics efficiency and reduce emissions. Especially, in populated city centres or in the proximity of heavy footfall areas, these points can be preferred by customers. In the study of Janjevic et al. (2019) , the authors proposed a new method for the integration of collection and delivery points in the design of multi-echelon logistics systems based on a real-life case study. The benefits of using these systems are quantified by showing significant cost benefits for companies involved in last mile logistics.

Weltevreden (2008) studied collection and delivery points in the Netherlands and its consequences for other stakeholders. The author showed that these locations are most used for returning online orders. For retailers operating a service point may lead to additional revenues. In recent study, Kedia et al. (2020) looked at to identify the optimal density and locations for establishing collection and delivery points in New Zealand. The authors modelled the problem as a set covering problem by considering city demographics and travel distance between population centres and potential facility locations. New type of points such as dairies and supermarkets were found to be more accessible than traditional post shops.

5.4 Truck platooning

The arrival of autonomous vehicles is an opportunity to improve people’s lives and protect the environment. These vehicles also contribute to advancing the sustainable development agenda. One of the application areas of autonomous vehicles is platooning, which links two or more vehicles (trucks) together to create a form of train. Generally, LSPs aim to make their operations more efficient by utilizing their resources (i.e. fleet, labour etc.) ( Ghiani et al. , 2013 ). These companies are also paying close attention to their environmental footprint. Early adopters of truck platooning can bring a competitive advantage amongst LSPs. Countries are also interested in automation and, more particularly, truck platooning. Most of the autonomous vehicle projects in Europe are done by collaborating with different organizations and countries. Cooperation of actors, especially in the European Union (EU), is progressing well since EU countries have similar legislation.

Truck platooning will contribute to the transport industry, including improved traffic management, reduced operational costs and operations ( Tavasszy & Janssen, 2016 ). Next to these advantages, truck platooning will also make the logistic operations more efficient and optimize the labour market. Platooning will also optimize the supply network from a higher perspective. This will eventually reduce CO |$_2$| e emissions and minimize congestion by improving traffic flows with reduced tailbacks. Truck platooning can be more efficient for longer distances and heavy good vehicles. The possibility to platoon with different trucks or multi-brand platooning is also needed to form vehicles in a platoon successfully.

5.5 Collaborative logistics

Generally, last mile delivery solutions are individually managed by retailers and LSPs. Due to competitiveness of the last mile delivery market, there is little room for joint and synchronized solutions. Collaborative logistics can address the challenges of last mile by increasing cost efficiency and utilization. The major challenge in last mile logistics is that the demand points are often located in highly congested urban areas and they are quite far from distribution centres. In the study of De Souza et al. (2014) , the authors looked at industry alignment through a synchronized marketplace concept by using clusters of customers, suppliers and service providers in Singapore.

Park et al. (2016) studied the collaborative delivery problem to measure the effects of collaboration for apartment complexes in Korea. Potential benefits are also quantified in this study and the role of the public sector is considered to be essential.

5.6 Integrated transport

As a promising business model, integrating freight flows with public scheduled transportation can be a viable option for freight transportation. A successful synchronization of delivery vehicles with scheduled public transport is directly related to coordination, which is the critical factor for seamless movement of freight in the last mile ( Ghilas et al. , 2016 ).

As public transportation systems have particular coverage, specific delivery trips of delivery vans may overlap with the scheduled line services. Using public transportation instead of delivery vans may reduce transportation cost and create environmental benefits. Due to the shorter driving time of their delivery vans, LSPs may reduce their operational costs. Less travel time also leads to reduced amount of CO |$_{2}$| e emissions. It is not an easy task to coordinate both delivery vans and public scheduled lines from an operational perspective. However, this system can be a viable option for the industry, especially in rural areas.

5.7 Decarbonization

By definition, decarbonization in road freight reduces transportation-related activities’ carbon footprint (GHGs). Reducing emissions in every industry is essential to ensure global temperature standards set by the Paris Agreement and governments. As the share of last mile increases due to e-commerce sales, more research and green thinking are needed for the industry.

In 2021, the Department for Transport of the UK published a policy plan on decarbonizing transport to meet the UK’s net-zero targets ( Department for Transport, 2021 ). Some of the proposed initiatives include: phasing out the sale of all new non-zero emission HGVs; demonstrating zero emission HGV technology on UK roads; stimulating demand for zero-emission trucks with financial and other incentives; supporting efficiency improvements and emission reductions in the current fleet; and also taking new measures to transform last mile deliveries. From this perspective, two technologies look prominent for last mile logistics. These include electric vehicles and green hydrogen, and these options could help reduce the environmental impact of last mile logistics.

5.8 Towards transport analytics: the role of data and information

The Internet of Things is known as the network of physical objects to enable data and information exchange between different physical and virtual objects. Last mile logistics and transportation can also benefit from information sharing on inventory, supply chain, resources and people. However, although promising, it is a great challenge to change the logistics systems and its related overwhelming daily operations. It requires the involvement of various stakeholders to act together for all types of operations.

It is important to consider different analytical approaches with information sharing capability for the last mile logistics. In the study of Krushynskyi et al. (2021) , the authors investigate two policies to improve the efficiency of the LSP by allowing more flexibility in choosing the delivery locations. The considered policies include roaming vehicle routing and the second policy allows the possibility of aggregating certain locations. The problem is modelled as TSP real-life parcel delivery data are analyzed. The authors points out that the two proposed policies can lead to significant improvements in the route length.

In order to improve the efficiency of last mile logistics, all processes during the transportation should be improved. Such improvement can be achieved by using advanced analytics, artificial intelligence (AI) and blockchain systems. Historical logistics data can be utilized to proactively reduce the vulnerability of traffic networks and improve the communication between transport users with real-time data. For example, AI-enhanced decision-making capabilities can provide real-time information and actionable suggestions for the planning of vehicle routes. In a related study, Ozarik et al. (2021) studied VRP in which customer presence probability data are explicitly considered in the planning of routes. As the unavailability of customers is a major problem for the logistics industry, the real-time location information of customers can improve the delivery service and reduce the unnecessarily generated emissions.

The last mile delivery is the most complicated part of the supply network. It deals with the movement of goods from a hub to their final destination. This is normally the customer’s doorstep. It is essential to make the delivery as efficient as possible while minimizing all operational costs. Due to urbanization and population growth, this final step of transportation is becoming increasingly important. Customers prefer to have on-time delivery, and this might be a challenge for the industry because of various uncertainties. Because of these challenges, there is a growing need to provide LSPs with relevant evidence, strategies and decision-making tools to help them plan better.

Academic research in last mile logistics has successfully considered new trends and technological developments in scientific investigations. However, there is a need for more research focusing on more operational and tactical issues related to routing optimization. Our short positioning paper has looked at various dimensions of last mile logistics and discussed the outlook of future research needs by the industry.

The future of last mile logistics will be shaped by technology, innovation and customer requirements. There is already good progress for using advanced technology in logistics. Digitization, automation and robotic systems will help LSPs to handle last mile operations more efficiently. The industry will also pay more attention to sustainability and decarbonization as the share of emissions from transportation must be reduced sharply in the next 10 years in many countries.

Building upon findings of our research, we can make the following recommendations for the adoption of the latest technologies and innovations in the last mile logistics.

The unending customer requirements must be addressed by promoting greener last mile delivery services through the use of advanced mathematical optimization techniques. In particular, there is a need for developing proactive and robust algorithms specifically designed for dynamic traffic environments.

The negative externalities of freight transportation and social indicators must also be considered within route optimization along with economic indicators. There is good progress on the environmental sustainability, but more research is needed to tackle social sustainability.

The barriers influencing the adoption of the latest technological solutions and innovations must be dealt with using quantitative data generated with the help of operational research techniques.

AI-enhanced decision-making approaches should be used based on the available data for creating vehicle routes and schedules. The algorithms should be suitable for processing large amounts of data within reasonable solution times.

Sincere thanks are due to the Operations Area Editor of IMAMAN for the opportunity to organize this special issue. We also thank two anonymous reviewers for their useful comments and for raising interesting points for discussion.

BEIS ( 2021 ) 2019 UK Greenhouse Gas Emissions, Technical report . Department of Business, Energy & Industrial Strategy , London: United Kingdom.

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  • Original article
  • Open access
  • Published: 22 September 2021

Assessment of logistics service quality dimensions: a qualitative approach

  • Gamze Arabelen 1 &
  • Hasan Tolga Kaya   ORCID: orcid.org/0000-0003-0150-4182 2  

Journal of Shipping and Trade volume  6 , Article number:  14 ( 2021 ) Cite this article

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Globalization and complex supply chain networks have been affecting Logistics Services Providers’ (LSPs) service delivery and service expectations. Logistics Service Quality (LSQ) is becoming a more important aspect for LSPs and logistics service customers. In recent years, there has been an increase in the studies on service quality in logistics. Researchers have been trying to identify aspects of LSQ and its dimensions in order to create a measurement model that could be used in overall logistics services. However, there is still neither a unified nor agreed LSQ measurement model in the literature and researchers have been debating continuously on the proposed models. This paper targets to investigate and suggest LSQ measurement dimensions obtained from previous studies by analyzing the findings within a systematic approach and improving the findings with semi-structured interviews. In this study, systematic literature analysis has been conducted to research papers published in selected academic databases with specific keyword and keyword cluster searches to identify the related articles published within a specified period. Papers have been selected in accordance with the predefined criteria. As a result, a total of 59 articles have been determined for the search criteria and the findings obtained were analyzed. Most frequently used research trends and methods on service quality in logistics have been identified. In addition, the most frequently used LSQ dimensions and factors have been reviewed. Moreover, the most frequently used service quality approaches and measurement models have been analyzed. The results received from systematic literature review have been composed and dimensions have been identified. Semi-structured interviews with LSPs and customers of LSPs in Germany-based companies have been conducted to strengthen the findings gained from systematic literature review. 5 LSQ dimensions and 24 factors have been formed with the help of semi-structured interviews. This paper represents the basis for further research for empirical studies and can be used as a guideline for quality management practices in logistics applications and transport.

Introduction

Globalization and growing supply chain networks have been pushing logistics service providers to focus on the provided logistics practices. Simultaneously, service types offered by logistics service providers have increased quickly. Importance of logistics services also has been increased universally; hence, service quality has become an important driver for LSPs. The importance of logistics services is known by practitioners and academics. Significance and interest in Logistics service quality (LSQ) have been also increasing. The concept of LSQ is equally important for customers and LSPs (Mentzer et al. 1999 ; Thai 2013 ). High level of LSQ increases logistics providers’ competitive advantage among compelling business environments (Wang and Hu 2016 ). Good service quality offered to customers generates customer satisfaction as well as customer loyalty for the service provider (Franceschini and Rafele 2000 ; Davis and Mentzer 2006 ; Baki et al. 2009 ).

There has not been any clear understanding of the LSQ concept despite the increasing number of research papers. Major focus of the researchers has been on the concept of the LSQ and its quality attributes, how to analyze and measure the quality of the services (Bienstock et al. 1997 ; Mentzer et al. 1999 ; Franceschini and Rafele 2000 ; Rafele 2004 ). Nonetheless, researchers have developed different ideas on logistics concept and service quality dimensions over time. There have been very few studies with the holistic approach on the LSQ to analyze overall developed dimensions and the attributes along with the general framework. Therefore, a comprehensive LSQ model that would incorporate different sectors is not available at present.

General approach of the researchers developing a study in LSQ has kept the literature review part very short and directed it to particular approaches without critically viewing the literature. This paper is aiming to address the previously mentioned issue by analyzing papers related to LSQ with a systematic approach. This will ensure that previous findings from scientific papers are systematically analyzed and presented and findings can be used in future studies to develop scientific or practical LSQ studies. Additionally, this study is anticipating LSQ attributes by analyzing research trends and general usage of LSQ dimensions, research methods, and fields of sectors. Furthermore, it is aiming to conduct a semi-structured interview with logistics professionals in order to confirm and enhance the outcome of the systematic literature review.

This paper has been developed through multiple sections. In the first section, research methodology has been explained. General approach in the systematic literature review, paper selection criteria, keywords, databases, and preliminary paper classification have been described in the second section. In the third section, descriptive analysis of the selected papers has been carried out. In the fourth section, LSQ dimensions and attributes have been analyzed and the LSQ measurement model has been created to discuss the findings in semi-structured interviews. In the fourth section, semi-structured interviews and findings from business professionals’ contributions have been explained. In the fifth section, a brief overview of this study has been presented and in addition notes on future works have been provided.

Research methodology

Systematic literature review methodology has been used in this study to have a holistic approach towards LSQ studies and interpret the findings obtained from previous papers. Systematic literature analysis method has been considered a technique of systematic, qualitative, objective, and quantitative description in the research area (Berelson 1952 ). A systematic content analysis methodology has been considered a very powerful and an explicit tool because of its ability to combine qualitative approaches retaining rich meaning with quantitative analyses (Duriau et al. 2007 ; Fink 2005 ). Additionally, the main difference between systematic literature review and traditional literature review has been considered the first comprehensive search section (Crossan and Apaydin 2010 ). In order the follow a structured method with valid results, a systematic literature review approach from the literature has been applied (Seuring and Gold 2012 ). In this regard, a systematic literature review has been planned in this study with several steps as: material collection, descriptive analysis, category selection, material evaluation. Material collection reflects gathering all necessary papers from previously created criteria. Collection of materials has been the most crucial step in systematic literature reviews. In the study, literature regarding the LSQ has been selected from peer-reviewed journals and literature databases, Web of Science, ScienceDirect, Emerald, Taylor and Francis, JSTOR, Business Source Premier, and the web. Second part of the systematic literature review has been descriptive analysis. Only studies in English language and published between 1995 and 2020 have been selected for the future classification. The formal characteristics of the selected papers have been set out in the descriptive analysis section to provide background for the content. Consequently, publication years, research methods and research fields of reviewed journals have been documented. Structural dimensions and related categories for future analytics have been selected in category selection. In the material evaluation section, all analyses have been presented according to determined categories and parameters.

Semi-structured interviews have been used in this study to consolidate the LSQ dimension findings from systematic literature analysis, as it is the most frequently used interview method (Taylor 2005 ; Dicocco-Bloom and Crabtree 2006 ). Flexibility and reciprocity of semi-structured interviews have benefited the LSQ discussion. Questions regarding service quality in logistics have been prepared prior to meetings, which were shaped around the systematic literature review findings and perceptions of the participants. In semi-structured interviews, following a strict structure is not advised (Kallio et al. 2016 ). Definite resolution on logistics quality and definition of quality dimensions have not been agreed upon for LSQ, therefore a semi-structured interview qualitative approach is considered more convenient in order to allow participants to express themselves. In order to create successful semi-structured interviews, a five-step model has been utilized (Kallio et al. 2016 ). Firstly, prerequisites of the interviews have been decided. Due to the coronavirus pandemic situation, related global restrictions and organizations, new working models such as online meeting method have been selected. Second step is gathering previous knowledge on data by using the systematic literature review. This has allowed the interviewer to gain knowledge and confidence in regular spontaneous follow-up questions. In the third step, guidelines of the interview have been developed. Questions have been prepared regarding participants’ understanding of LSQ, participants’ perception of the identified LSQ dimensions and follow-up questions regarding examples for the in-depth analysis of the topic. In the fourth step, a pilot has been conducted with one logistics business professional to test the clarity of the developed approach. In the final step, semi-structured interviews have been performed with five logistics professionals.

Systematic literature review

Systematic literature review is advised to be applied to a specified period of time. Therefore, materials have been selected from research papers that were published between 1995 and 2020. Specific keywords related to service quality in logistics have been used in literature databases such as Web of Science, ScienceDirect, Emerald, Taylor and Francis, JSTOR, Business Source Premier, and the web to identify the first step. Only papers that have been peer-reviewed in English language have been selected for further analysis for systematic review. Table 1 provides a summary of sample paper selection. In literature databases with keyword matches in their titles, 221 papers that are fit for the search criteria have been found. Furthermore, the suitability of the sample has been checked by applying a two-stage screening process. First screening has been applied to the abstracts of the selected papers. After analyzing the abstracts of 221 papers, sources that were irrelevant or with little relevance to the topic have been excluded from further analysis. However, studies with no abstract or with unclear information have been directly transferred to the second stage. In the second screening process, full paper review has been applied to enforce the relevance of the selected literature sample. Additionally, papers that have been cited multiple times and fit to the criteria of this research have been included in the samples. As a result, final sample has consisted of 59 papers.

After collecting the sample based on criteria, descriptive analysis has been followed, as it would create a framework for the systematic analysis. In this context, formal characteristics have been analyzed. Consequently, publication years and service fields have been analyzed to identify the preliminary framework of the selected literature sample. Publication years of the selected studies have shown that the trend towards the research topic of LSQ had been increasing. Findings of the study have shown that the LSQ is still a discussion subject among researchers. In order to show the academic interest in the LSQ topic, selected timeline of 25 years has been divided into five years of periods. The results have shown that 23 papers were published between 2015 and 2020, which clearly shows the increasing relevancy and interest in the research topic. Furthermore, search fields of selected papers have been analyzed and results reflected that 49% of the studies have been conducted in the logistics field and the second most popular research field groups have indicated the industrial management field with 20% of the total sample.

After analyzing the descriptive specifications of the selected research paper samples, analytic categories have been selected including research methods, data analysis methods, LSQ dimensions, service quality measurement models, approach of the studies. In the last part of the systematic literature analysis, selected categories have been analyzed and categorized to create some practical guidance on the LSQ research question. According to Avenier (2010), decontextualized evaluation of the literature analysis’ results brings out the possibility of proposing a certain degree of generalization for the findings. Therefore, systematic literature review findings have been used to identify the first design of the LSQ dimensions and later discussed in semi-structured interviews.

Analysis of the Categories

Previously founded categories have been analyzed to create further research design with transparency. Therefore, used data analysis and research method of selected literature sample have been analyzed. Table 2 provides an overview of the used researched methodology. According to the results, linear usage of qualitative, quantitative, and multiple data analysis known as triangulation has been used among 51% of the studies and 76% of the studies have had empirical approach.

There is an increase in empirical studies about the LSQ topic in addition to using existing created models and trying to validate the quality measurement models. Besides, many researchers have been searching the relationship between the LSQ and other attributes such as loyalty and satisfaction. Consequently, this increase in validation studies may refer to a reaction to unconformity on the search field and in search of study and generalized LSQ measurement model. Moreover, qualitative LSQ dimensions developing studies have been mainly observed in early periods and most researchers preferred to create an LSQ model and validate its reliability by quantitative methods throughout the time. Details of the research approach method with corresponding publications has been presented in Table 3 . From triangulation, Mentzer et al. ( 1999 ), created a nine-dimension service quality measurement model which is broadly used, Feng et al. ( 2007 ), Gil-Saura et al. ( 2008 ) and Thai ( 2013 ) also developed different models which were created for the need of the search in LSQ with different approaches.

Table 4 provides an overview of the ratio of used LSQ measurement models and, it is clear that most of the researchers preferred to create a unique service quality measurement model for logistics or preferred to add a modification to generally used methods instead of directly using developed and proved reliable methods. Logistics services have been always a chain of multiple services and findings may show differences among supply field, region or service expertise. For instance, Zailani et al. ( 2018 ) focused on LSQ considering halal logistics network and developed an individual service quality model. Thai ( 2008 ) has provided a service quality method for port operations and defined six brand new dimensions: resources, outcome, process, management, image or reputation and social responsibility. Despite having specialized service quality measurement models for logistics operations, most of the researchers have used the classical model of SERVQUAL in quantitative research. This approach also provides an insight into the inefficient LSQ measurement model for general usage.

In addition, the LSQ scale created by Mentzer et al. ( 1999 , 2001 ) has been used by researchers particularly. Rafiq and Jaafar ( 2007 ) had used the LSQ scale to measure customer perception on 3PL service providers, authors suggested generalizability of the LSQ scale on a similar sample model. Bouzaabia et al. ( 2013 ) has utilized the LSQ scale to compare the LSQ perception between Romania and Tunisia in retail logistics. Yumurtaci Huseyinoglu et al. ( 2018 ) has investigated the service quality scale model on Omni-channel capability. Table 5 provides an overview of LSQ dimensions and how often they are used in literature. The publication list has been submitted in chronological order to provide an overview of the development of LSQ dimensions that have been used throughout the period of the systematic research analysis. Due to different naming conventions on similar meanings, LSQ dimensions have been grouped by their relevance to each other. As a result, most frequently used LSQ measurement dimensions have been identified. Dimensions related to communication have been used 27 times in total, which have been mentioned under different names such as personal contact quality; responsiveness; customer focus etc. Second most frequently used LSQ dimensions are process-related and have been mentioned 20 times in the selected sample publications. Process related dimensions have been mentioned as order release quantities, order accuracy, order discrepancy handling, order quality and correctness, etc. Third but not least used dimensions are time-related and have been used 19 times in publications throughout the period. Time-related dimensions have been named in different forms such as timeliness, on-time delivery, lead time, etc. Over time, it has become clearly visible that while the focus of the operational quality has lost its importance and significance, communication-related dimensions and empathy dimension usage and their relation to quality have gained importance due to factors such as, responsiveness, empathy, personnel contact quality, etc.

The findings have indicated that the LSQ research area has remained incomplete in the literature. Thus, tailored service quality with hierarchical dimensions for logistics services are more applicable to analyze LSQ. Dimensions have been selected based on their relevance and frequency of use. As it has been noticed from the studies, focus on customer-related services in logistics operations is increasing, therefore, dimensions related to customer focus quality have been selected as the first dimension for this study to analyze further in the interviews. Additionally, by the image of the company and social responsibility acts investigated under a total of six LSQ dimensions and twenty sub-factors have been identified by their relevancy on logistics and the frequency of the use: Information quality, customer focus quality, order fulfillment quality, timeliness quality, corporate image and social responsibility were selected.

Semi-structured interviews

Semi-structured interviews allow participants and the interviewer to interchange knowledge within mutual benefit and, allow the interviewer to ask follow-up questions to participants based on the development of the answers (Rubin and Rubin 2005 ). In order to benefit from the professional view of the participants, semi-structured interview method has been selected. Semi-structured interview method is considered more fit for further investigation on LSQ dimensions because the topic is broadly discussed and has no consensus has been reached either on the definition or on the quality dimensions. Semi-structured interview has allowed participants to roam freely around the topic, and follow-up questions have provided preferable inputs and modifications on developed LSQ dimensions and sub-factors. As shown in Table 6 , interviews were carried out with five logistics business professionals. Two of the participants were logistics managers in retail business, one was the logistics service provider team lead and two of them were logistics specialists for logistics service providers. All interview participants and their companies were located in Germany and companies have the scope of working in global logistics and supply chain businesses. All interviews have been conducted through online calls, and meetings have been recorded. Five interviews lasted average of thirty minutes for each participant.

Semi-structured interview questions have been designed according to the outcome of the systematic literature review. Open-ended questions have invited participants to follow-up the topic. Open-ended questions have been designed for each participant and their companies. Next set of questions have been designed for each quality dimension that has been identified in the systematic literature analysis and the said questions asked participants their point of view to validate and modify the proposed model. In general, participants have been directed with general questions to understand their personal quality perceptions and followed-up with prompt questions.

As a result, construction of the preliminary proposed quality dimensions has changed. All participants have expressed the importance of their customer value and its relation with quality perception, also they have highlighted that quality dimension is in fact a customer obsession. Therefore, naming has been changed to ‘ customer obsession quality’ from ‘ customer focus quality’ . Additionally, all participants have highlighted and agreed on the social responsibility activities are related to companies’ image; therefore, LSQ dimensions have merged under one quality dimension: social responsibility and company image. Additionally, LSQ factors have also been discussed and modified as a consequence of the interviews. Sub-dimensional quality factors have raised to 24 from 20 in total. Final LSQ dimensions and factors have been defined as shown in Table 7 .

After the final evaluation of semi-structured reviews, shipment tracing capability, innovative solutions in logistics services; reliability, regularity, flexibility and availability of service, company’s reputation for reliability have been added to the LSQ factors and LSQ scale has been developed with five quality dimensions and 24 factors in total.

Research findings

Research findings have been developed with qualitative research techniques. Firstly, systematic literature analysis has been applied to the LSQ related papers with specified criteria between 1995 and 2020. Samples have been analyzed with systematically created filtering and descriptive analysis. Results have been analyzed and shown that researchers have not reached a consensus either on the LSQ perception or the measurement method. Additionally, a paradigm shift towards customer-oriented services from the natural physical movement of the cargoes has been observed in recent years. As a result, logistics service customers are giving more importance to business-to-business or business-to-customer communication and empathy. This change has been seen in the recent LSQ publications as well. As a consequence of the initial analysis, six dimensions and twenty logistics factors have been developed. Preliminary findings have been discussed in five semi-structured interviews. Logistics professionals’ contributions have been included in this study to ensure that literature key findings are in line with actual business and quality dimensions have improved by the outcome of the results.

As a result, systematic literature analysis has shown that SERVQUAL quality measurement method is still broadly used; however, there have been great contributions from many authors towards LSQ and the creation of logistics specific quality measurement model. Despite these improvements, there has been no consensus on the singular quality measurement model. This research proposes LSQ dimensions and factors created from systematic literature analysis and semi-structured interviews. Firstly, six-dimensional twenty factors have been developed and findings have been improved after the semi-structured interviews. Final model proposes five LSQ dimensions with twenty-four factors.

Conclusion and recommendations for further researches

Logistics services have been continuously growing around the world. These improvements and developments have increased the competition among service providers. There has been an increment in the number of research papers exploring this area. Service providers are trying to leverage operational excellence with high quality of services to maintain customer satisfaction, loyalty, and market competition. A regularly dynamic environment requires dynamic solutions, therefore, logistics services are constantly in development. Consequently, the perception of LSQ has been changing.

It has been found that LSQ understanding and applications have been evolving around the business focus of LSPs. Throughout the development of the quality dimensions in logistics, there have been different approaches from different authors. In the literature, the focus of the LSQ dimensions has been differing among different periods of the samples and it clearly shows the change in the focus on the quality. After observing a period of twenty years, early developed LSQ dimensions have shown that quality focus is mainly on the physical attributes of the operations, such as physical distribution and timeliness related dimensions. Over time, logistics services have accumulated more customer-oriented operations hence, in later periods customer-related LSQ dimensions have been observed, such as personal service/contact, empathy. The dimensional switch has also been accepted in semi-structured interviews and recorded as the most important dimension of the LSPs. Therefore, currently keeping positive relations with customers by providing emphatic continuous relationship has been more important for LSPs.

Despite having a high rate in empirical studies, findings suggest that researchers used repeatedly SERVQUAL model in LSQ measurement even though there have been measurement models created specifically for logistics services. This indicates that the search of the LSQ dimensions and measurement methods have not been completed; hence, it is open for improvement and eventually reaching the recognized LSQ measurement method. This study is providing a framework for service quality in logistics for researchers and logistics professionals by systematically analyzing the previously developed studies and measurement models. Primary quality dimensions have been developed from systematic literature analysis by systemizing and organizing the existing literature. Then, additional interviews have been conducted with service professionals. As a result, framework of LSQ has been developed with five dimensions with customer obsession quality, order fulfillment quality, timeliness quality, information quality, corporate image and social responsibility and twenty-four factors. The holistic approach of the research model has asserted LSQ dimensions for further measurement models.

Proposed model may be used as a framework for further studies and can be strengthened by empirically testing in multiple regions of the world. LSQ dimensions may be improved by conducting focus group meetings and additional interviews with logistics professionals from different regions of the world. Additionally, professionals may use these LSQ dimensions as an internal quality indicator and use factors and dimensions as quality key performance metrics. Managers may benefit from the findings to create quality-oriented logistics services or improve existing service models.

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

  • Logistics service quality

Logistics Services providers

  • Service quality

Service performance

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The author HTK analyzed and interpreted the historical research data regarding Logistics Service Quality and conducted descriptive analysis. HTK conducted interviews with business professionals. The author GA, analyzed historical service quality dimensions, developed inferences between historical findings and periodic trends among service quality dimensions, and is a major contributor in writing the manuscript. All authors read and approved the final manuscript.

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Arabelen, G., Kaya, H.T. Assessment of logistics service quality dimensions: a qualitative approach. J. shipp. trd. 6 , 14 (2021). https://doi.org/10.1186/s41072-021-00095-1

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Big data analytics in logistics and supply chain management

The International Journal of Logistics Management

ISSN : 0957-4093

Article publication date: 14 May 2018

Fosso Wamba, S. , Gunasekaran, A. , Papadopoulos, T. and Ngai, E. (2018), "Big data analytics in logistics and supply chain management", The International Journal of Logistics Management , Vol. 29 No. 2, pp. 478-484. https://doi.org/10.1108/IJLM-02-2018-0026

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Introduction

In recent years, big data analytics (BDA) capability has attracted significant attention from academia and management practitioners. We are living in an era where there has been an explosion of data ( Choi et al. , 2017 ). Kiron et al. (2014) argued that a majority of fortune 1,000 firms is pursuing BDA-related development projects. Chen and Zhang (2014) argued that big data (BD) has enough potential to revolutionize many fields including business, scientific research and public administration and so on. The use of BDA in the field of marketing and finance is on the rise. However, the operations and supply chain professionals are yet to exploit the true potential of the BDA capability in order to improve the supply chain operational decision-making skills ( Srinivasan and Swink, 2017 ). Operations and supply chain professionals have access not only to data, which is continuously generated by traditional devices such as POS, RFID, but also GPS to a vast amount of data generated from unstructured data sources such as digital clickstreams, camera and surveillance footage, imagery, social media postings, blog/wiki entries and forum discussions ( Sanders and Ganeshan, 2015 ). Today, supply chains are highly supported by advanced networking technologies – sensors, tags, tracks and other smart devices, which are gathering data on real-time basis ( Wang et al. , 2016 ; Gunasekaran et al. , 2017 ), which provides end to end demand and supply visibility ( Gunasekaran et al. , 2017 ; Srinivasan and Swink, 2017 ). Schoenherr and Speier-Pero (2015) argued that supply chain managers need to process a large amount of data to make decisions that may help reduce costs and increase the product availability to the customers.

The extant literature defines a BDA capability as a technologically enabled ability which can help process large volume, high velocity and several varieties of data to extract meaningful and useful insights; hereby enabling the organizations to gain competitive advantage ( Fosso Wamba et al. , 2015, 2017 ). Galbraith (2014) further noted that historically, supply chain managers used to analyze data gathered from traditional data warehouses to gain insights. Moreover, Hazen et al. (2014) argued that the effectiveness of decision making in supply chains often hinges upon the quality of the data processed via organizational infrastructure, which enables the supply chain managers to quickly acquire, process and analyze data. Papadopoulos et al. (2017) argued that insights gained via increased information processing capability can reduce uncertainty, especially when operational tasks such as disaster relief operations are highly complex. However, despite increasing efforts from the operations and supply chain community to understand the associations between different types of operational visibility and analytics capabilities, the theory-driven research is limited. Hazen et al. (2016) further outlined how the use of organizational theories can help explain the complexity associated with the use of BDA capability to explain supply chain sustainability. Waller and Fawcett (2013a) noted that the intersection of logistics and supply chain management field with data science, predictive analytics and BD can provide numerous opportunities for research. However, in the absence of adequate skills, the supply chain managers often face a myriad of challenges to extract information from BD to take effective supply chain operational decisions (Waller and Fawcett, 2013a; Dubey and Gunasekaran, 2015a ; Gupta and George, 2016 ). The role of contextual factors in developing BDA capability is well discussed in the information systems literature. What is less understood is how BDA under the effect of contextual factors affect logistics and supply chain processes. Waller and Fawcett (2013b) argued that recent experience with BD may help to explain some of the complex phenomena and unanswered questions in logistics and supply chain management.

The main objective of this special issue (SI) is to provide a significant opportunity to the logistics and supply chain management community to affect practice through fundamental research on how BDA capability can be exploited by the organizations to provide logistics and supply chain insights.

Review of articles included in the SI

Our SI attracted 44 submissions. Each manuscript was examined to ensure that it was in line with our stated objectives in the published call for papers. We desk rejected some of the papers which failed to meet our objectives or the objectives of the International Journal of Logistics Management (IJLM). Next, the manuscripts which were in line with our SI and IJLM objectives, as well as fit for the next round, were submitted for review to two or more experts per manuscript. Based on the reviewers’ and guest editors’ review, we rejected or invited the authors to undertake substantial revision based on the reviewers’ inputs. Finally, after multiple rounds of review, we finally accepted 13 papers for our SI. All accepted papers in this SI are in line with our and IJLM objectives. The papers that are included in this: Dubey et al. (2018) , Jeble et al. (2017) , Song et al. (2018) , Brinch et al. (2018) , Hopkins and Hawking (2018) , Gravili et al. (2018) , Lamba and Singh (2018) , Gupta et al. (2018) , Lai et al. (2018) , Hoehle et al. (2018) , Bhattacharjya et al. (2018) , Hofmann and Rutschmann (2018) and Queiroz and Telles (2018) .

The first paper in this SI is on the application of big data and predictive analytics (BDPA) on humanitarian supply chains by Dubey et al. (2018) . This paper examines what the antecedents of BDPA are. Second, how the BDPA can improve the visibility of humanitarian supply chains and coordination among the actors in humanitarian supply chains. Third, the authors examine the moderating role of swift trust on the path joining BDPA and visibility/coordination. To answer these research questions, the authors have grounded their model in contingent resource-based view (CRBV). In addition, the authors have tested their theoretical model using survey data gathered from informants at international NGOs that are engaged in disaster relief operations. The findings of the study offer some interesting contributions to BD, predictive analytics literature and swift-trust theory. Furthermore, it offers numerous directions to the managers who are engaged in disaster relief operations.

The second paper in this SI is on the application of BDPA on supply chain sustainability by Jeble et al. (2017) . This paper examines what the resources needed to build BDPA capability are. Second, the paper examines how BDPA affects the supply chain sustainability under the moderating effect of supply base complexity. To answer these research questions, the authors grounded their model in the CRBV. The authors also tested their model using data gathered via the single-informant instrument. The findings of the study contribute to the growing debate surrounding BD, predictive analytics and supply chain sustainability.

The third paper in this SI is on the use of large data sets to examine the impact of financial restrictions on green innovation capability in the context of the global supply chain by Song et al. (2018) . In this study, the authors have proposed a linear relationship between green innovation as a dependent variable; green supply chain integration and financial restriction as dependent variables. The study utilized customs, import and export data from 222,773 Chinese enterprises to test their proposed model. The findings suggest that greater supply chain integration and relaxation in financial restriction will boost the green innovation initiative of these firms. The study contributes to the prior research calls of scholars (see Waller and Fawcett, 2013a ; Wang et al. , 2016 ), and how BDPA can be used to advance existing debates surrounding SCM.

The fourth paper in this SI is an exploratory study which aims to understand how supply chain practitioners view BD and its application in supply chain management by Brinch et al. (2018). In this study, the authors have used mixed research methods to address their research questions. First, the authors used the Delphi technique to understand the extent to which the supply chain practitioners were familiar with the application of BD in SCM. They further ranked the applications of BD in the SCOR process framework. The authors also supported the Delphi study via cross-sectional data gathered using the survey-based instrument. The study provides an in-depth understanding of the various applications of BD in SCM. Second, the authors explore how BD applications in various stages in the supply chain can help the firm gain a competitive advantage. The study provides numerous directions for further research, which may help to expand logistics and supply chain management literature.

The fifth paper in this SI investigates the application of BDA and IoT in logistics by Hopkins and Hawking (2018) . In this study, the authors have tried to develop a theoretical framework using a case study approach to understanding how logistics firms use BDA and IoT to support strategies to improve driver safety, reduce operating costs and reduce the negative effects of automobiles on the environment. The study provides directions for the logistics companies on how effective deployment of BDA and IoT can address some of the perennial problems of the logistics industry.

The sixth paper in this SI is on the influence of digital divide (DD) and digital alphabetization (DA) on the BD generation in supply chain management by Gravili et al. (2018) . In this study, the authors have investigated the influence of the DD and DA on the BD generation process in order to gain insight into how BD could become a useful tool in the decision-making process of SCM. In addition, the authors have used a systematic literature review to understand the relationship between the literature on BDA, DD and SCM. The authors also explored the vector autoregressive, which is a stochastic technique to capture the linear interdependence between DD (as a part of internet usage) and trade in the context of the European Union. By examining the association between DD and internet acquisitions, a positive and long-lasting impulse response function was revealed, followed by an ascending trend. The findings suggest that a self-multiplying effect is being generated, and it is, in effect, reasonable to assume that the more individuals use the internet, the more electronic acquisitions occur. Thus, the improvement of the BD and SCM process is strongly dependent on the quality of the human factor.

The seventh paper in this SI attempts to develop a theoretical model, which tries to explain how the enablers of BD in operations and supply chain management are associated with each other by Lamba and Singh (2018) . In this study, the authors have used fuzzy TISM to develop a theoretical model and have further examined the causality of the linkages using the DEMATEL technique. These techniques are grounded in graph theory. The current contribution of the authors makes significant strides toward the theoretical advancement of BDA and its application in the operations and supply chain management context. In the future, the proposed model may be tested using longitudinal data.

The eighth paper in this SI examines the role of cloud ERP on organizational performance by Gupta et al. (2018) . Cloud-based ERP enables an organization to pay for the services they need and removes the need to maintain information technology infrastructure. In this paper, the authors have grounded their model in a CRBV and have further tested the role of cloud-based ERP services on supply chain performance and organizational performance, with cross-sectional data collected via a single-informant questionnaire. The findings of the study indicate that cloud ERP has a positive influence on supply chain performance and organizational performance measured in terms of market and financial performance. Furthermore, the study indicates that the supply base complexity has a significant moderating influence on the path joining cloud ERP and market/financial performance. The study contributes to the extant literature and further provides direction to the management practitioners.

The ninth paper in this SI examines the determinants of BDA in logistics and supply chain management by Lai et al. (2018) . The authors have undertaken an extensive literature review of extant literature on BDA and SCM and have further classified the factors into four constructs: technological factors, organizational factors, environmental factors and supply chain characteristics. Furthermore, drawing from the innovation diffusion theory, the authors have proposed their theoretical model using the four constructs, and have further tested the process using single-informant survey data from 210 organizations. The findings of the study suggest that perceived benefits and top management support have a significant influence on the adoption intention. Subsequently, environmental factors such as competitors’ adoption, government policy and supply chain connectivity have a significant moderating effect on the direct relationship between driving factors and the adoption intention. The results offer some interesting contributions to the BDA and SCM literature.

The tenth paper in this SI examines the customer’s tolerance in the context of omnichannel retail stores via logistics and supply chain analytics by Hoehle et al. (2018) . In this study, the authors argued that mobile technologies are increasingly being used as a data source to enable BDA. These BDA enable inventory control and logistics planning for omnichannel businesses. First, the authors in this study introduced three emerging mobile shopping checkout processes in the retail store. Second, they suggested that new validation procedures (i.e. exit inspections) necessary for implementation of mobile technology-enabled checkout processes may disrupt traditional retail service processes. Third, the authors have proposed a construct labeled “tolerance for validation” defined as customer reactions to checkout procedures. The authors have also developed a measurement scale for the proposed construct and gathered data using a structured questionnaire from 239 customers. The statistical analyses suggest that customers have a higher tolerance for validation under scenarios in which mobile technologies are used in the checkout processes, as compared to the traditional self-service scenario in which no mobile technology is used. The customers do not particularly show a clear preference for specific mobile shopping scenarios. Hence, these findings contribute to our understanding of the challenges that omnichannel businesses may face as they leverage data from digital technologies to enhance collaborative planning, forecasting and replenishment processes. The proposed construct and measurement scales can be used in future work on omnichannel retailing.

The 11th paper of this SI examines how unstructured data in the form of tweets can be exploited to improve customer service by Bhattacharjya et al. (2018) . In this study, the authors argued that in recent days, the interaction between firms and their customers in the form of tweets have increased. However, these tweets often constitute a large volume and the extraction of valuable information from these unstructured data may offer unique opportunities to understand their customers’ need. The authors have demonstrated the need for tweet analytics via parcel shipping companies and their interactions with customers in Australia, the UK and the USA. The findings from the study contribute to the customer engagement theory. The research provides a unique opportunity for the practitioners, confirming that tweet analytics can be exploited to address other logistics and supply chain activities.

The 12th paper of this SI examines how BDA can be used for forecasting in supply chains by Hofmann and Rutschmann (2018) . In this study, the authors argued that BD can minimize the forecast errors, thereby improving the forecast accuracy. The authors have proposed a conceptual structure based on the design-science paradigm via three steps: description of conceptual elements of the framework utilizing justifiable knowledge; specification of the principles of the theoretical framework to explain the interplay between elements; and creation of a matching framework by conducting investigations within the retail industry. The developed framework could serve as the first guide for meaningful BDA initiatives in the supply chain. This study attempts to offer unique contributions to the forecasting technique via BDA.

The 13th paper of this SI examines the role of BDA in logistics and supply chain by Queiroz and Telles (2018) . In this study, the authors have investigated the role of supply chain partnerships, human knowledge and innovation culture on supply chains in BD environments. The authors have further tested their proposed BDA-SCM triangle using data gathered via single-informant instrument from Brazilian corporations. The study provides an understanding of the barriers related to BDA adoption and the relationship between supply chain levels and BDA knowledge. The authors have further noted their limitations, which offer unique opportunities to the BDA and SCM scholars to build upon current findings.

Limitations and future research directions

When should we use BDPA in SCM?

Under what context can BDPA in SCM be used?

How can predictive analytics be used to advance theory in SCM?

How does BDPA in SCM affect organizational performance and under what circumstances?

How can BDPA be used in inventory planning?

How can BDPA improve information sharing?

How can BDPA be used for facility layout design?

How can BDPA be used in vehicle routing problems?

How can BDPA help to minimize environmental uncertainties?

Hence, we can argue that we need strong predictive analytics capability because consumer behavior has become an integral part of the supply chain ( Waller and Fawcett, 2013b ). Thus, the ability to predict the consumer behavior has implications for product innovation, product manufacturing, distribution, design and demand.

Concluding remarks

The BDA is one of the most promising topics which can provide numerous opportunities for academic and management practitioners. It can be used for building theories which is one of the untapped potentials of the BDPA; even though many scholars often term BDA as one of the management fads. Despite criticisms, we believe that BDA have immense potential to revolutionize existing supply chain theories.

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Chae , B.K. ( 2015 ), “ Insights from hashtag♯ supplychain and Twitter analytics: considering Twitter and Twitter data for supply chain practice and research ”, International Journal of Production Economics , Vol. 165 , pp. 247 - 259 .

Dubey , R. and Gunasekaran , A. ( 2015b ), “ The role of truck driver on sustainable transportation and logistics ”, Industrial and Commercial Training , Vol. 47 No. 3 , pp. 127 - 134 .

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Freight Traffic Impacts and Logistics Inefficiencies in India: Policy Interventions and Solution Concepts for Sustainable City Logistics

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  • Published: 07 July 2022
  • Volume 8 , article number  31 , ( 2022 )

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logistics research paper pdf

  • Prasanta K. Sahu   ORCID: orcid.org/0000-0002-4309-5631 1 ,
  • Agnivesh Pani   ORCID: orcid.org/0000-0002-0136-8224 2 &
  • Georgina Santos   ORCID: orcid.org/0000-0002-8446-8297 3  

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Freight traffic fulfils not only the business needs of a region to move goods between producers, manufacturers, and end consumers, but also creates a host of unintended environmental, social, and economic impacts. Despite its importance, freight traffic impacts and associated logistic inefficiencies are largely overlooked in the urban transport discussions in developing economies like India. This paper addresses this research gap by outlining the research progress related to freight transport in India and discusses the key problems related to freight system performance. The published literature in the last three decades (1990–2020), policy briefs and institutional reports are explored to summarize key findings and uncover thematic linkages. We categorize the inefficiencies in the freight system into four aspects: (i) long-haul trucking, (ii) last-mile logistics, (iii) freight distribution (inventory level), and (iv) policies and regulations. Apart from identifying the limitations in policy discourse, this paper also explores the possible solution concepts to improve efficiency in freight transport and mitigate the unintended negative externalities in urban areas. The overall conclusion is that increasing and improving infrastructure and equipment, technology and operations, and policy and regulations will go some way towards making freight more efficient in India and reducing congestion and emissions of air pollutants and GHG. The present paper can be expected to promote further freight research and effective policy instrument design in India.

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Introduction

Currently, more than a third of global transport energy consumption (39%) is generated by freight movements [ 1 ]; trucking is responsible for 23%, followed by marine vessels, which are responsible for 12%, and rail and pipelines, which are responsible for 4%. It is therefore an imperative research need to investigate how to ensure that freight activities fulfil their role in economic transaction of goods, while mitigating the associated negative externalities. It is also critically important to understand why, how and where freight activity takes place and what kind of infrastructure and policies need to be provided to respond effectively to the growing logistical requirements of businesses and households [ 2 , 3 , 4 ]. The practical requirements to improve the logistics competency and operational efficiency of freight transport have been acting as strong catalysts to stimulate a number of studies towards understanding freight activity at both national and local scales. However, a data-driven summary of the freight system performance in India, expanding on the logistics inefficiencies and negative externalities of freight traffic, are evident gaps in the literature. This discernible research need triggered the present comprehensive review. This review specifically outlines the progress that has been made in freight research, along with possible future research directions and policy guidelines.

The objectives of this review paper are therefore threefold: (1) to investigate the various aspects of freight system performance, logistics inefficiencies, and freight traffic negative externalities in India; (2) to discuss the potential solution concepts and prepare a research agenda for future research on sustainable city logistics in India; and (3) to develop insights for policy and practice based on the empirical evidence in the literature and the emerging trends in the logistics market. These objectives are motivated by the lack of practice- and policy-based discussions on improving freight mobility in India and enhancing the ease in moving goods across cities and states in a geographically diverse country like India. Reviewing the inefficiencies and externalities of freight in India will help to provide solution concepts and mitigation strategies to improve the freight system performance. This paper, therefore, addresses the need for a comprehensive review focusing on Indian freight studies and aims to draw inferences from the existing literature and provide guidance for future research in India. The review findings are expected to promote freight research and effective policy instrument design to meet the growing needs to reduce the overall logistics cost for moving goods.

Method Adopted for the Review and Data Collection

Research questions.

The primary aim of this paper is to present a comprehensive review of the freight traffic impacts and logistics inefficiencies in India, which is an area of significant practical and research interest in the context of coordinated global efforts to reduce transport emissions. The following are the specific research questions explored in this review:

What is the extent of literature relevant to freight transport planning in India and what is the emerging trend?

Are there any deficiencies of freight performance in India relative to global benchmarks?

What are the logistics inefficiencies in India and what are the underlying reasons contributing to them?

What are the environmentally negative externalities of freight movements and how can they be quantified in India?

What are the potential solution concepts that can be derived from the literature for addressing the issues related to freight system performance, logistics inefficiencies, and negative externalities of freight movements in India?

An overview of the review questions, methodology and the discussion structure adopted in this paper is presented in Fig.  1 . As can be seen, the first research question (RQ1) is designed to map the extent of literature related to freight transport planning in India through a review of published literature, policy documents, and reports. The second research question (RQ2) follows from the previous question as it is to analyse and discuss the freight system performance in India based on the papers identified and screened as a part of RQ1. The third research question (RQ3) is to discover the underlying reasons contributing to logistics inefficiencies in India as a logical extension of RQ2. The fourth research question (RQ4) is to assess the environmentally negative externalities of freight transport, going beyond the operational efficiency focus in RQ3. The final research question (RQ5) is aimed at discussing the potential solution concepts in practice across the world to improve the freight system performance (RQ2), logistics inefficiencies (RQ3), and negative externalities (RQ4) in India.

figure 1

Overview of the review questions, method, and discussion structure

Identifying and Screening of Literature

To ensure the review covered the most recent published literature on freight in India, Scopus, Web of Science, and TRID were combined with Google Scholar. The initial search used the general keywords ‘freight transportation/transport’ but this was later narrowed down to ‘India’, and subject areas ‘engineering’, ‘social sciences’, ‘environmental science’, and ‘decision science’. The search process was repeated using additional keywords of interest to this study, such as ‘logistics inefficiencies’, ‘freight traffic’, and ‘freight system performance’. Only peer-reviewed articles (including both review and original papers) were considered but these were combined with grey literature reports and government (e.g. Government of India) and international organizations (e.g. the World Bank) publications. The initial 290 unique records published between 1990 and 2020 were screened and purged down to 49. Many papers were irrelevant to the present study, as they dealt with issues unrelated to the research questions posed, despite having come up in the search exercise. The limited number of relevant papers found in the published literature underline the urgent need to focus on these research problems.

Review Approach and Data

The papers that survived the pruning were papers published in the following journals: Transportation Research (TR) Part A, TR Part B, TR Part C, TR Part D, Transport Policy, Transportation, Transport Geography, Transportation Research Record, Research in Transportation Economics, Travel Behaviour and Society, Sustainable Cities and Society, Transport Reviews, Journal of Cleaner Production, Energy Policy, Transportation Research Procedia, KSCE Journal of Civil Engineering, Transportation Letters, and Research in Transportation Business and Management. To quantify the extent of literature relevant to freight transportation in India (RQ1), the number of papers published in each of these journals is presented in Fig.  2 and the total number of publications in each year is presented in Fig.  3 . As can be seen in Fig.  3 , there has been substantial growth in freight studies since 2018. This jump in the number of papers underlines the increased research attention given to this topic area in recent years. Out of the 49 papers, 41 were published in Elsevier journals (83.67%), 3 were published in Springer journals (6.12%), 3 were published in Taylor and Francis journals (6.12%), and 2 were published in SAGE journals (4.08%). The 49 papers can be categorized into four areas: (1) development of disaggregate-level freight demand estimations at seaports [ 5 , 6 ] or urban establishments [ 7 , 8 , 9 , 10 , 11 ], (2) development of aggregate-level freight generation [ 12 , 13 ] or distribution models [ 14 ], (3) design of establishment-based freight surveys [ 15 , 16 ] and zoning systems [ 17 , 18 , 19 , 20 ], (4) analysis of freight transport parking practices [ 21 ], emissions [ 22 , 23 ], expenditure patterns [ 9 , 24 , 25 ], and logistics sprawl [ 26 ]. Since the relevant statistics on freight system performance (e.g. modal share, logistics cost) or specific logistics inefficiencies related to India were missing in these publications, the review scope was also extended to collect aggregate-level data from publicly available sources, such as the Logistics Performance Index from the World Bank [ 39 ] and the Freight Transport Indicators from the OECD [ 38 ]. Additionally, policy briefs and reports published by government agencies in India were also referred to gain insights into the status of freight transport policies. The Indian Government National Transport Development Policy Report [ 27 ] was reviewed with the aim of capturing the policy discourse. The discussion derived from the identified literature follows the structure shown in Fig.  1 . The thematic discussions on three specific topic areas are provided in the next three sections: freight system performance in India (RQ2), logistics inefficiencies in India (RQ3), and negative externalities of freight traffic in India (RQ4). The solution concepts for the issues identified in the thematic discussions are discussed in the penultimate section. The final section concludes this paper.

figure 2

Number of papers reviewed from the literature and their respective journals

figure 3

Number of papers published each year between 1990 and 2020

Freight System Performance in India

In line with the rest of the world, freight transport is undergoing important changes in India, most of which are simply a result of market trends, and most of which are already shaping and will continue to significantly shape the way freight transport performs in the future. This section is devoted to scrutinizing these trends, putting them in context, and understanding their potential impact in the short and medium term.

Unbalanced Modal Mix and Growth in Road Freight

The Indian economy is growing rapidly, partly thanks to its ongoing industrialization. One of the consequences of this is that freight movements are growing exponentially—both in the last-mile and long-haul trucking sector [ 27 ]. A major share of this demand is carried by road transport due to the flexibility provided for first-mile and last-mile logistics. The freight transport sector in India, as a result, is heavily skewed towards road transport with a modal share of 64% [ 28 ]. This compares with 75% in Europe [ 29 ] and 63% in the USA [ 30 ]. The historical trend of modal share between road, railways and inland waterways is presented in Fig.  4 using secondary data publicly available from a report published by the “Sustainable Urban Transport Project”, an organization devoted to the study and promotion of sustainable transport in urban areas [ 31 ]. The rail market share, as it can be seen, has gradually declined over the years. This trend is concerning because the economies of scale for bulk cargoes can be better achieved using a combination of railway, inland waterways, and coastal shipping. In 2018–2019, freight mode share in India stood at 27% rail, 64% road, 5% coastal shipping, 2% inland waterways, and less than 1% air (plus a 2% via pipelines for gas, water sewerage, etc.) [ 28 ]. Considering the less than optimal rail share, Indian Railways, a government entity under the Ministry of Railways that operates India’s national rail system, has set a target of having at least a 50% share of the country’s freight traffic by 2030 [ 32 ]. To achieve this, Indian Railways is investing heavily on network expansion projects and dedicated freight corridors. The strategic planning of these large-scale projects requires accurate freight demand models [ 24 , 25 , 33 , 34 ].

figure 4

Source: Urban Freight and Logistics: The State of Practices in India [ 31 ]

Variation in freight modal share in India over time.

Achieving an efficient modal share is important for a country and the environmental impacts of different transport modes are evaluated in several studies [ 35 ]. An efficient modal share is one that maximizes volumes transported and does so at the minimum social cost, to include not just time and vehicle operating costs, but also externalities, especially noise, air pollution, climate change, caused by greenhouse gas (GHG) emissions, and accidents. For example, large, regular flows of goods with low-value density are historically suited for transport by railways, because: (i) origin/destination points tend to remain the same; (ii) commodity fragmentation can be avoided, and (iii) emissions can be minimized. Medium-valued goods are also increasingly transported by railways due to the availability of modern intermodal services around the world [ 36 ]. Due to significant economies of scale, railway or inland waterways have the potential to move these goods at a much lower unit cost than trucks with far lower GHG emissions and cost variability. A recent comparison of freight mode performance in India [ 37 ] suggests that the unit costs of moving goods is highest for road transport (2.58 INR/ton-km or 3.4 US cents/ton-km at April 2022 exchange rates), followed by railway (1.41 INR/ton-km or 1.86 US cents/ton-km at April 2022 exchange rates) and waterways (1.06 INR/ton-km or 1.40 US cents/ton-km at April 2022 exchange rates), respectively. Despite the high unit costs and road freight externalities, freight transport is road dominated in India (and other regions of the world such as Europe and the USA, as already highlighted above) because it offers greater delivery flexibility and shipment size. This trend is reflected in the growth of (road) freight transport in emerging Asian countries, such as China and India, as shown on Fig.  5 . The data were collected from the OECD Freight Transport Indicators Database [ 38 ]. The figure shows a clear growth of road freight in emerging economies, in line with the growth of the freight sector in those countries, and of the economy in general. Freight flows in OECD countries of North America and Europe, on the other hand, have reached a steady-state.

figure 5

Source: OECD Freight Transport Indicators Database [ 38 ]

Growth of road freight transport in India and other major OECD countries.

Road freight transport offers lower transit times and higher reliability, making it better suited for transport of perishable goods and commodities with high value density [ 17 ]. The other operational advantages of using trucks include saving in packaging costs, ability to track and trace cargoes, door-to-door serviceability, and ability to schedule the delivery. An effective mode share of a country should thus concomitantly satisfy two criteria: (i) minimizing transport costs and (ii) meeting the operational requirements of shippers. While there is no consensus on the “ideal” modal mix for freight transport, India’s geographical features (extensive coastlines, predominance of hinterland economic activity, longer length of hauls) and the need to reduce freight emissions point in favour of rail transport.

Logistics Cost, Performance and Global Benchmarks

Logistics costs are a significant component of total trade costs. The high logistics costs constrain the competitiveness of the economy and are often the result of shortcomings (physical, regulatory, or institutional) in the transport sector. Nearly one-third of India’s logistics costs (~ 4% of GDP) are attributed to inefficiencies in infrastructure. An important logistics measure that can be used to compare the performance of India’s logistics system against its competitors is the Logistics Performance Index (LPI) produced by the World Bank [ 39 ]. The LPI scores are based on data on six dimensions of trade: customs efficiency, infrastructure quality, ease of transporting international shipments, logistics quality and competence, trackability of consignments (also called tracking and tracing), and delivery timeliness [ 39 ]. The World Bank uses the LPI to rank countries [ 39 ], and a summary of this ranking, relevant to the present paper, is presented in Fig.  6 . As it can be seen in Fig.  6 , the logistics infrastructure in India lags behind that in Germany, the USA, the UK, and China. Jumping up the LPI rank, as currently proposed [ 40 ], will require a fundamental reorientation in the way logistics infrastructure caters to freight demand in India.

figure 6

Source: Logistics Performance Index [ 39 ]

Global variation in logistics performance index.

Pairwise comparisons of LPI scores between major OECD countries and India are given in Fig.  7 , to highlight the deficiencies across different aspects of logistics.

figure 7

Pairwise comparison of LPI between OECD countries and India.

Changes in Logistics Strategies and Freight Needs

One important challenge in the freight sector is linked to the changes that have taken place and continue to take place in the context of E-commerce [ 41 ]. The purchasing options of consumers in the past were limited to retailers in the city centre, whereas these are now competing with wide-ranging options provided by online retailers. To maintain a competitive edge in the market, shops are increasingly adopting just-in-time inventory practices, which result in stocks being kept to a minimum. Another noticeable change is the increased requirement for better logistics outsourcing service levels [ 9 ]. Many customers expect delivery within 24 h after placing an order [ 10 ]. Retailers are forced to respond and adapt to changing consumer requirements or risk losing them to the nearest competitor. Compounding this challenge is the consumer experience, which has become highly personalized and specialized, thanks to the digital transformation that has taken place since the early 2000s. This implies more customized orders, stricter quality controls, tighter compliance standards, shorter delivery windows and an overall intolerance to delays in shipments. The role of “fulfilment centres” became increasingly important over the first two decades of the 2000s, and is now a component in many supply chains, with a prime example being Amazon. The changes in logistic strategies of many stores (and warehouses) and the expectations from end consumers have had significant impacts on the demand for freight transport as follows: (i) there is a higher demand for goods, (ii) there are higher service levels, and (iii) shipment sizes tend to be smaller than they used to be.

Diversification of Freight Flows

There are different types of freight flows. These are depicted in Fig.  8 , based on the typology suggested in a report by the Ministry of Housing and Urban Affairs and Rocky Mountain published in 2019 [ 42 ]. As shown in Fig.  8 , there are four different types of shipments: (i) low-value, bulk freight (LVBF), (ii) medium-value, medium-density freight (MVDF), (iii) business-to-business freight (B2BF) for urban consumption, and (iv) business-to-consumers freight (B2CF) for urban residents. LVBF refers to shipments of construction materials (concrete, sand, gravel) and industrial goods (oil and petrochemicals). LVBF accounts for a significant share of freight shipments, especially in cities where the majority of the infrastructure is still in the process of being built. These low-value shipments tend to be shipped in large quantities (and heavy-duty vehicles), which cause high external costs. The next spectrum of shipments refers to MVDF, which are inputs or outputs of light industry (raw material oriented and less capital intensive), such as, for example, paper products, plastic products, leather, and textile products. The B2BF shipments are typically directed towards retailers so that they can be sold to urban residents. These shipments include fast-moving consumer goods, such as, for example, food products, beverages and pharmaceuticals, and they are typically stocked on the shelves of consumer stores. B2BF shipments are characterized by a high frequency of trips, although they are typically transported in light or medium-duty vehicles. Restricting the movement of B2BF shipments is generally contentious, because B2BF shipments directly cater to the needs of urban residents. Instead of reducing the freight volume, restrictions are typically found to force the shippers to move freight in less efficient ways. B2CF shipments typically are of high value and have specialized handling and delivery requirements (e.g. food deliveries, document packages, parcels). These types of freight are transported in light-duty vehicles, vans, two wheelers or even by foot, directly to the end consumer. Formerly a relatively small segment of urban freight travel market, B2CF shipments have become critical in urban logistics with the rise of E-commerce. Much like B2BF shipments, B2CF shipments cater to urban residents and policy interventions should focus on efficiency rather than demand management. While these diversifications are unique in each supply chain, a general conceptualization of urban supply chains is presented in Fig.  9 .

figure 8

Source: authors’ own conceptualization based on freight flow categories discussed in the report by the Ministry of Housing and Urban Affairs and Rocky Mountain Institute [ 42 ]

Type of shipments transported by urban freight.

figure 9

Source: authors’ own conceptualization, extending the layout in Pani and Sahu (2019b)

Conceptual layout of urban supply chains.

B2CF shipments have experienced an important growth in the last few years, mainly due to increased Internet penetration. In the organized retail market, the share of online purchases was 25% in 2019, with forecasts predicting it could reach 37% by 2030 [ 43 ]. The presence of online platforms also enables consumer-to-consumer online markets; this form of E-commerce is rising in popularity [ 44 ]. Due to the influx of online platforms, many traditional retailers feel the need to participate in E-commerce as well, further increasing the urban freight flow levels. Many retailers are choosing to sell goods held in their inventory through E-commerce and Omni-channel delivery systems to offer better options to consumers [ 45 ]. In the context of increasing B2CF flows, reverse logistics of goods are also becoming more important. These streams involve not only the return and exchange of goods purchased online, but also services such as waste collection. As it can be seen in Fig.  9 , shippers also produce additional freight activity in the form of waste and “reverse logistics” of returns and exchanges. Policymakers should therefore customize policy interventions to different types of freight traffic. For instance, shippers or retailers can offer customers (end node of supply chains) unique value by incentivizing reuse of raw or finished materials through a seamless “return” policy. By creating these feedback loops in supply chains, cities can transition towards a circular economy with significant societal and economic benefits [ 46 ]. Classifying the type of goods entering the city through different supply chains can be the first step for understanding the diverse needs of the freight market segments and, in turn, examining what challenges they present. Existing freight studies in India have largely focused on freight flow, and limited attention has been given to reverse logistics and service activities [ 9 , 16 , 47 ].

Infrastructure Investment and Mobility Studies

Productive investment on freight transport infrastructure is vital for improving the freight system performance and, in turn, enabling seamless deliveries and pick-ups of goods in urban areas [ 48 ]. An integrated approach to infrastructure spending, with investment schemes driven by transport policy goals that are coordinated with land-use and industrial development objectives, is critical for India. Since much of the freight movements have a destination in cities where ports or airports are located, infrastructure investment needs to be prioritized in those cities and regions, especially as freight vehicles share road space with passenger traffic. A comparison of infrastructure investment in India over the period 2004–2017 is presented in Fig.  10 .

figure 10

Source: OECD Infrastructure Investment Database [ 49 ]

Growth in infrastructure investment.

There have been several initiatives for increasing capacity, such as for example, the construction of dedicated freight corridors (DFCs). DFCs are expected to ensure that long-haul freight demand is catered efficiently in existing trunk routes on the eastern and western corridors (Howrah-Delhi and Mumbai-Delhi), which are currently saturated with line capacity utilization of 115%–150% [ 27 ]. The diversion of freight traffic from the long-haul trucking sector to DFCs on truck routes is expected to decongest the existing highway network for passenger movement. However, appropriate transport supply improvements require a demand assessment toolkit which is still missing for India [ 18 ].

Logistics Inefficiencies in India

There are a number of inefficiencies in both freight transport and freight policies in India. These inefficiencies can be broadly categorized into four areas: (i) long-haul trucking, (ii) last-mile logistics, (iii) freight distribution (inventory level), and (iv) policies and regulations. Reducing these inefficiencies will reduce the generalized cost of moving goods and the externalities of road transport. It will also improve the satisfaction of urban residents.

Inefficiencies in Long-Haul Trucking

The inefficiencies in trucking costs are driven by three factors: (i) avoidable running costs created by empty backhaul of trucks, (ii) usage of trucks with reduced fuel economy and (iii) insufficient fleet size and mix of logistics providers, which lead to inefficient utilization of trucks for forwarding shipments. The root cause of these inefficiencies is related to the inability of trucking firms to achieve economies of scale, thereby resulting in low productivity and efficiency. This is partially linked to the rise of small trucking firms, which attempt to reduce logistics costs through overloading, service violations and poor maintenance. These unlawful logistic operations artificially lower the price of trucking services and make the traditional carriers with large efficient fleets unable to continue operations. Large trucking firms, on the other hand, can achieve economies of scale through efficient dispatching and scheduling, which is critical to increasing fleet utilization and reducing empty running. Another important contributor towards inefficiency is the suboptimal load size observed in emerging countries [ 37 ]. The highways in India are also inadequately maintained, inconsistent in road width and heavily congested [ 27 ]. These infrastructure shortfalls underline the need for targeted capacity increase to improve the inefficiencies in long-haul trucking.

Inefficiencies in Last-Mile Logistics

Last-mile logistics involves delivering packages to end consumers or retail shops in urban centres. It typically follows different trip patterns, uses different vehicle types and has a different spatial extent of travel, compared to long-distance trucking. Due to the nature of multi-stop delivery tours carried out in last-mile operations, priority is given to maximizing the amount of freight delivered in an average tour. This is in contrast with the priorities given to achieving improved shipment size in long-distance trucking. The importance of last-mile logistics, despite being the shortest link in supply chains, stems from the fact that it constitutes up to up to 13%–72% of total logistics costs in many supply chains [ 50 ], and up to 55% in supply chains involving E-commerce [ 37 ]. The variation in costs is because of several potential causes of inefficiencies that exist in last mile, as explained below.

Fragmentation of receivers: In India, as in many emerging markets, the demand for freight can be somewhat fragmented. The reason for this fragmentation is the informal, even impulsive, ordering behaviour of “nano stores” [ 51 ]. This ordering behaviour affects the performance of the whole supply chain, as it triggers actions upstream in the supply chain [ 51 ].

Fragmentation of carriers: Planning delivery tours is a complex optimization problem, which needs to maximize delivery quantities, minimize time and distance whilst reaching all destinations, considering delivery windows and traffic patterns/congestion . Logistic providers in developing countries like India often lack the fleet size and technical tools to dispatch delivery trucks on optimal tours.

Fragmentation of delivery points: In the era of E-commerce and highly personalized freight orders, fragmentation of delivery points is an important barrier to last-mile logistics efficiency. The discretization of delivery points is a more pronounced issue in urban areas than the fragmentation of receivers. This is a problem common to both developed and developing countries, but in countries like India, the impacts are more evident, probably because of the higher traffic congestion levels that prevail in most cities.

Logistics sprawl: Due to high land values in cities, warehouses and distribution centres tend to migrate towards the suburbs. This phenomenon, known as “logistics sprawl”, increases the duration of delivery tours and the resultant traffic increases congestion levels, both going into and out of the cities [ 52 ]. Transportation is intrinsically linked to the urban growth phenomenon and the associated logistics sprawl [ 53 , 54 ]. Another implication of logistics sprawl is that it reduces the number of delivery points accomplished in a single tour. The evidence for logistics sprawl in major Indian cities is already available for industry sectors such as the timber market [ 26 ].

Inefficiencies in Freight Distribution

Inventory is a critical element of logistics costs, as it requires facilities for storage and holds up the working capital of firms (i.e. receivers) in a freight system [ 55 ]. To reduce these costs, firms typically attempt to minimize inventory levels without compromising their ability to serve end consumers. Due to uncertainty in lead times (i.e. time taken by shipper to deliver goods), excess inventory costs are typically incurred by shippers in the freight system, thereby increasing the overall logistics costs. The reduced reliability in transit times leads to higher buffer stocks to guard against uncertainty. The highly fragmented and inefficient distribution system poses major challenges to buffer stock reductions. Another challenge is the limited digitization of links connecting the stakeholders in a freight system, which restricts the ability of retailers to reduce cycle stock (i.e. the inventory held in shelves to satisfy normal sales demand). The ability to implement just-in-time (JIT) ordering practices that can accomplish reductions in cycle stock hinges on two factors: (i) digital capabilities to track inventory drawdown and (ii) digital links to distribution centres and supplies to avail dynamic replenishment of products. Due to limited advances in JIT systems in India, efforts to reduce the total amount of inventory in the distribution system and the amount of inventory lost have not been very successful [ 37 ].

Inefficiencies in Policy Framework

Policies intended to reduce the negative externalities or inefficiencies from freight can actually backfire and yield the opposite result. The National Urban Transport Policy (NUTP) in India acknowledges that freight traffic will grow substantially [ 31 , 56 ]. Timely and seamless freight movements are also mentioned as a priority for the economic development of the country [ 31 , 56 ]. The freight-related policy measures recommended in the NUTP report can be summarized as follows: (i) using off-peak hours for freight deliveries, (ii) restricting the entry of heavy-duty trucks into cities during daytime, (iii) building bypasses through public–private partnerships so that long-haul trucks can go around the city, instead of adding to the city traffic, (iv) reorganizing land use by locating wholesale activities in the periphery of cities, along the interstate highways, rather than in city centres, (v) building truck terminals and parking facilities outside the city limits to encourage the shifting of wholesale activities, (vi) provisioning parking space at appropriate locations for on/off street with the use of intelligent transport systems, (vii) planning ring roads to relieve traffic congestion in central areas, and (viii) implementing auto-fuel policies that call for tighter emission regulations and fleet upgrades [ 31 , 56 ]. Following the recommendations of the NUTP report [ 31 , 56 ], some cities, including Ahmedabad, Bangalore, Hyderabad, and Kochi, have set up committees, known as Unified Metropolitan Transport Authorities (UMTAs), charged with the mission of integrating the functioning of agencies associated with passenger and freight mobility. These top-down policies may deliver positive impacts and help achieve more efficient freight movements in urban areas.

Another policy that has been suggested is the implementation of time-based or cordon-based restrictions. These restrictions have been introduced in some cities in India [ 7 ]. They can entail, for example, banning vehicles exceeding 7.5 tons during specific time periods of the year or specific times of the day [ 7 ]. Delhi has also banned non-destined transiting trucks (heavy, medium or light-duty vehicles) from passing through certain regions in Delhi [ 23 ] and has imposed entry time restrictions to freight destined for Delhi. Shifting freight travel into times of minimum residential use can force deliveries at night, greatly increasing the share of last-mile cost in total logistics cost. Furthermore, it can, and it has, resulted in good deliveries by vans or three wheelers, which are not subject to bans, and this can, and indeed has, in turn, increased overall traffic.

In addition to the above, the imposition of pollution taxes can help freight face the environmental costs they cause. Delhi, for example, introduced a pollution tax in 2015, payable by trucks passing through Delhi [ 23 ]. The tax is 700 INR and 1400 INR (USD 9.24 and USD 18.49 at April 2022 exchange rates) for light-duty vehicles and heavy-duty vehicles, respectively. Reorganizing land use by moving wholesale markets to outer town suburbs or satellite towns can help reduce the pressure from freight movements. Mumbai did exactly this to reduce traffic levels in the congested south part of the city. Another initiative is that of Urban Consolidation Centres (UCCs) [ 57 ]. These schemes aim to reduce the number of goods delivery vehicles in urban areas by consolidating multiple shipments at centres located in the city periphery [ 58 ]. There are several informal examples of such centres in India, especially in the perishable product sector (e.g. Azadpur vegetable market, sabzi mandi in Delhi). Another example of consolidation is the ITC e-Choupal project in which internet-based kiosks reach out directly to farmers and eliminate the middleman in agri-business supply chains [ 31 ]. Finally, many cities, such as for example Chennai, are planning to have truck terminals and parking zones on the city periphery [ 31 ]. However, there are several institutional, practical and legal barriers for long-term success in UCCs implementation, as reported in some European cities like Oslo [ 57 ].

Despite the publication of the NUTP and the setup of UMTAs in some cities, freight transport policy in India is still in nascent stage [ 42 ], in contrast with passenger transport policy. Save for the policy initiatives aimed at increasing capacity and building facilities (truck terminals, consolidation centres), freight policies in India have largely been restrictive in nature [ 23 ]. A scenario building approach, perhaps taking into account individual perspectives [ 59 ], has the potential to yield participatory decision-making outcomes related to freight policies.

Negative Externalities of Freight Traffic in Indian Cities

The negative externalities from freight traffic in India are only expected to increase in magnitude, bearing in mind the trends mentioned in previous sections. Negative externalities from freight can be defined as the costs imposed by freight on freight and other traffic, and society in general. These costs are not borne by those causing them, and are not reflected in any economic transaction (i.e. when the good is produced, transported or consumed). These external costs can be broadly categorized into three [ 60 , 61 ]: (i) environmental impacts, (ii) social impacts and (iii) economic impacts, as explained below.

Environmental Impacts

The environmental impacts from freight transport include air pollution, climate change caused by GHG emissions, noise, and water pollution. A multimodal emission assessment shows that the emissions from transport are expected to grow by 4.1–6.1% per year, leading to an increase of seven times by 2050 [ 62 ]. Air pollution is caused by emissions of particulate matter (i.e. microscopic solid or liquid particles in air), carbon monoxide, ozone and hazardous air pollutants such as benzene, which causes cancer and other serious health effects. Most trucks run on diesel, which is more polluting than petrol. Climate change is caused by GHGs. Excessive noise can negatively impact human health, disturb sleep, and cause cardiovascular and psychophysiological problems [ 63 ]. Most of the external costs from trucks in Europe come from noise [ 64 , 65 ]. Water pollution can result from freight transport when there are spills, leakages, or disposal of cargo material in water bodies. Although freight traffic constitutes merely 3% to 15% of total traffic in urban arterials and expressways [ 66 , 67 ], it is estimated to be responsible for up to 50% of road transport emissions [ 68 ]. In the case of noise pollution and vibration hindrance, in general, road freight has a much larger impact than cars [ 64 , 65 ]. Compounding these impacts is the fact that freight trucks used for urban deliveries are generally older and more polluting than trucks used for long-haul shipments [ 69 ]. Finally, land-use changes associated with freight flow and transport infrastructure development are an increasing source of concern as they can cause visual intrusion on environmental landscape, and destruction of habitats and species loss.

Social Impacts

The main negative externality from freight with social impacts is accidents. A significant share of road accidents can be attributed to trucks, as shown in Fig.  11 , based on crash data published by the Transportation Research and Injury Prevention Programme at the Indian Institute of Technology in Delhi [ 70 ]. The vehicle types include motorized two wheelers (MTWs), three wheel scooter taxis (TSTs), buses, cars, trucks, and others. As it can be seen in Fig.  11 , 72% and 65% of fatal crashes in six-lane national highways and urban highways are associated with trucks as one of the impacting vehicles.

figure 11

Source: Transportation Research and Injury Prevention Report, Table 10 [ 70 ]

Proportion of impacting vehicle type in fatal crashes (2015–2018).

Economic Impacts

The main externality from road freight that has economic impacts is congestion. Congestion caused by road freight has become a common problem in cities around the world [ 71 ]. In Europe, most of the external cost from trucks comes from congestion (and noise) [ 64 ]. Trucks take between two and four times the road space that cars take, and their speeds also tend to be lower. In addition, due to scarcity or inadequate configuration of loading or unloading bays/zones, freight trucks often double park during their delivery tours [ 72 ], thereby blocking the road for other vehicles. Traffic congestion has substantial negative impacts in terms of reduced productivity and wasted fuel. A high-level estimate of the economic loss resulting from congestion in major cities in India is over 22 billion USD per year [ 61 ]. Two conflicting interests emerge regarding congestion—public authorities aim to reduce freight traffic to improve the attractiveness of their city to residents as well as tourists, while private companies seek to operate at lowest cost with quick deliveries to satisfy consumers’ expectations in a highly competitive market [ 61 ]. The regulations and restrictions brought by public authorities can cause “detour” of delivery vehicles through narrow streets and unsafe delivery areas with low vertical clearance, further exacerbating traffic congestion [ 73 ].

Solution Concepts for Sustainable City Logistics

Considering the past trends, future projections of freight movement in India, a portfolio of solution concepts needs to be proposed and implemented to address negative externalities and inefficiencies in freight transport. We provide a broad overview of these solution concepts in this section and do so under four categories: (i) physical assets such as infrastructure and equipment, (ii) technology and operations, (iii) policy and regulations, and (iv) logistics-driven changes. The first two classes of solution concepts are part of long-term planning and require significant investment and changes to transport infrastructure. The latter two classes are part of short-term planning and they aim to reduce the impact of freight transport within the existing expanse of transport infrastructure. These categories of solution concepts are explained in the next subsections.

Infrastructure Solutions

These solutions include improving the quality and capacity of the road and railway networks and providing multimodal hubs and warehouses. Analyses of commodity movements and freight demand are critical decision-making tools for provision of infrastructure solutions. These solutions are imperative for developing a balanced modal mix and reducing the overall logistics cost, as explained below.

Improving freight distribution and last-mile logistics: The infrastructure facilities that need to be provided to improve freight distribution and last-mile logistics in urban areas are: (i) curb-level parking infrastructure and loading bays, (ii) exclusive truck lanes and dedicated routes, (iii) urban freight consolidation centres, and (iv) urban logistics spaces and (v) smart lockers. Parking and loading bays are critical for reducing the cruising time for truck traffic since delivery locations in urban areas often lack parking infrastructure. As a result, the inability to find an unloading spot or off-street parking lot leads to double parking and congestion [ 74 ]. Development of reversible lanes (off-peak reorganization of lanes in dense business districts), developmental lines and land-use ordinances are some of the effective solutions for improving parking efficiency [ 72 ]. Exclusive truck routes help for “detouring” freight deliveries away from residential areas in urban areas. These routes need to be designed for anticipated truck traffic levels in terms of vertical clearance, turning radii, sight distances and gradients. Provision of exclusive truck routes helps to streamline freight traffic in such a manner that the operational efficiency of other roads can also be improved. UCCs allow for greatly enhanced loading and routing efficiency in last-mile logistics efficiency. UCCs implementation can reduce freight travel by up to 50% in urban areas [ 37 ]. Urban logistics spaces (ULS) present a less intrusive way of achieving shipment consolidation than UCCs. Logistics operators and shippers typically welcome ULS compared to UCCs since the former are perceived to cause less disruption to lead times and delivery frequency. Smart lockers, or pack stations, are banks of lockers placed in activity centres such as transit stations, malls, grocery stores, to allow end consumers to collect their orders during their daily activity travel pattern, instead of taking delivery at home locations.

Achieving a balanced modal mix: There are two complementary targets in the roadmap for achieving a balanced modal mix in a country like India where rail freight is having a suboptimal share. One is to look at potential solutions that can foster a modal shift towards rail transport and the other is to facilitate better intermodal transfer between road and rail [ 75 ]. The former category of solutions includes the following: (i) increasing rail network capacity, and (ii) resolving gaps in rail network connectivity. The latter category of solutions includes developing intermodal logistic parks in tandem with dedicated freight corridors, and/or promoting double-stack clearance (stack containers one above the other) of intermodal corridors.

Reducing inventory costs: Two major solutions exist for reducing inventory costs, a major component of total logistics costs. The first is to improve the quality of warehousing, and the second is to reorganize warehouses to optimal locations. As for the first solution, the quality of warehousing can be improved by investing on automation, cross-docking facilities and refrigeration systems.

Improving trucking efficiency and productivity: The most important solution to improve trucking efficiency is to ensure that the current highway network keeps in pace with growing freight demand. Another avenue is to standardize logistic practices (e.g. harmonization of pallet and truck standards) and inventory data (e.g. inventory management for better dispatching of trucks).

Technological Solutions

To enable logistics chains, reduce costs, and improve services for customers, freight systems need to be enriched in various technologies. Digitization, coupled with adequate technological support and targeted investment schemes, can integrate the supply chain from demand forecasting stage to shipment consolidation, truck routing and dispatch scheduling [ 76 ]. The potential solutions through these technological, digital and operational advancements can be explained on seven fronts: (i) developing more accurate demand forecasting models through enhanced inventory visibility, (ii) automation of warehouse processes, (iii) deploying inventory data insights in distribution network design to deal with demand volatility, (iv) implementation of just-in-time inventory systems and fostering lean ordering behaviour among establishments, (v) achieving efficiency in truck routing and dispatch through real-time information, (vi) implementing intelligent transport systems (ITS), such as weigh-in-motion systems, delivery space booking systems, and route planning systems, and (vii) promoting carrier collaboration and accomplishing higher levels of operational efficiency through “Internet of Things” applications. These technological solutions are increasingly explored by the new third-party logistics providers, freight forwarders, and trucking companies emerging in the Indian market. For instance, driver relay models are increasingly adopted to reduce the continuous driving time of truck drivers to less than a day, and in turn reduce the turnaround time on long-haul routes (eliminating the driver idling time in the prior operational models). Increased adoption of location tracking solutions and growing presence of fulfilment centres in Indian cities have been helping the emerging logistics companies to eliminate the inefficiencies in the traditional hub-and-spoke model of delivering parcels. By utilizing distributed delivery models (i.e. each arc in the network acting as a hub and a processing centre by itself), the delays in routing the shipments through a hub before reaching the spoke can be avoided with the help of technology. As a result, most of the emerging logistics companies are positioning themselves as supply chain enablers with their own in-house order management systems. The challenges faced by small fleet owners have also come to the focus of the emerging market players in the logistics space with a vast number of software-as-a-service (SAAS) companies working towards hassle-free truck bookings and real-time vehicle tracking. The ongoing efforts as a part of Government of India’s Gati-Shakti national master plan to develop a unified logistic interface platform (ULIP) are expected to further accelerate the efforts of trucking companies and SAAS providers to reduce the overall costs of logistics and time in India.

Policy Interventions

Policy interventions play a crucial role in translating the first two solution classes into action, both in terms of energy demand and economic consequences [ 77 ]. Government departments, such as the Ministry of Shipping and Logistics, can employ a wide-range of policy measures, ranging from taxation instruments (e.g. fuel taxes, excise taxes and tolls) to financial incentives (e.g. tax rebates for supporting greener modes, capital grants) and regulation orders (e.g. vehicle design, entry time, emission standards), as explained below.

Taxation: Apart from the typical taxes levied on petroleum products (24–25% by the central government and 20–25% by state governments), additional charges such as the ‘green surcharge’ (up to INR 2/litre, or US cents 2.6/litre at April 2022 exchange rates) exist in India, although they do not include diesel vehicles. Introducing such differential charges for trucks can favour a switch to alternate modes, such as electric trucks or rail and water. The political challenges of introducing a carbon tax in developing countries are well known [ 78 ] and require more coordinated efforts in the future to foster a nationwide change to low carbon logistics.

Financial incentives: The financial support provided by the government varies from initiatives such as off-hour deliveries to incentives for shifting to greener freight modes such as electric trucks. The extent of financial support depends on external factors such as (i) differences in service and infrastructure ownership, (ii) competition policy, (iii) nature of freight market, and (iv) regulations governing financial aid from governments. Incentives also include capital grants to develop rolling stock or vessels for intermodal transfer and terminal development. Depending on the contribution to achieving government-level goals of sustainability, many services and infrastructure provisions can avail discounted infrastructure payments, operating subsidies or revenue supporting grants.

Supply chain digitization: As discussed in the previous section, digitization of supply chains and enforcement strategies can improve trucking efficiency. For instance, weigh-in-motion (WIM) implementation helps to penalize shipments that are exceeding the allowable limits and helps to identify the defaulters in the freight system; this also allows for effective checkpost clearance since trucks do not need to stop for inspections. The introduction of the electronic way (e-way) bill under tax-reforms like GST has improved clearance times across various states in India.

Zoning for freight operations: Land-use planning needs to develop designated locations for intermodal facilities such as inland container terminals, which can reduce urban congestion and foster a shift towards smaller commercial vehicles [ 18 ]. For this purpose, premium city space may need to be made available for logistical development near significant freight generating areas [ 19 ]. Another important aspect of land-use planning is to encourage spatial clustering of manufacturing firms that can achieve economies of density, which can lower transport costs down and improve delivery efficiency.

Zoning for logistic sprawl: Due to increasing land values in city cores, logistic land uses tend to locate farther from the city centre [ 79 ]. This sprawl of logistic facilities increases daily truck kilometres travelled, as well as congestion on urban arterials. By developing an efficient zoning policy for reserving suitable land uses in city centres (e.g. creation of urban logistics spaces or ULS near major retailing chains), logistics sprawl can be reversed. By bringing ULS to city centres, urban residents can also benefit in terms of superior access to goods and services.

Low emission zones: Low emission zones (LEZ) are geographic areas that limit access to those vehicles meeting certain emission standards [ 80 ]. The purpose of LEZs is to restrict or put a price on the most polluting vehicles if they enter areas in close proximity to urban residents. LEZs are typically proposed in areas where air quality levels are hazardous to society.

Delivery vehicle restrictions: These are among the most common policy responses taken by public authorities when freight traffic is sharing the same right of way with passenger traffic [ 81 ]. Implementation of these restrictions without the provision of ULS or UCCs are found to have negatives impacts on the regional economy. Besides, these restrictions often turn counterproductive due to increased delivery activity using small vans and three-wheelers. In the aftermath of the COVID-19 pandemic, delivery vehicle restrictions have received increased attention due to the rising delivery activity in residential areas, largely driven by the emergence of grocery and food delivery companies. As the delivery start-ups are primarily focusing on faster deliveries and increased convenience for consumers, fulfilment/distribution centres are being deployed in the middle of dense urban neighbourhoods and delivery drivers are incentivized to achieve 10-min or 15-min delivery windows. The traffic safety concerns resulting from these delivery vehicles have thus been receiving notable coverage in the newspapers, underlining the requirement of data-driven delivery vehicle restrictions and centralized self-service delivery lockers as a mitigating solution.

Market-Driven Solutions

The final class of solution concepts is related to the market-driven changes that can be implemented in the freight transport sector. These solutions include three broad categories: (i) technological advances, (ii) crowd shipping on transit (COT) programs, and (ii) planning and cooperation initiatives, as explained below.

Electric and autonomous freight vehicles: A number of technological advances in the freight transport sector have been made in the field of vehicle technology [ 82 , 83 , 84 ]. These advances are increasing the fuel efficiency of trucks and reducing emissions through emission filters. Continuous improvements are being made with respect to noise reduction and safety hazards. Furthermore, electric trucks (ETs) and connected and autonomous trucks (CATs) are becoming more scalable and viable alternatives relative to diesel powered trucks [ 85 , 86 , 87 ]. Analysis of the passenger transport sector already shows that the policy push for e-vehicles will only reduce GHG emissions if the electricity generated to power these vehicles is produced in a clean manner, i.e. the electricity generation mix needs to have a large share of renewables [ 88 ]. Fostering the replacement of traditional truck fleets with ETs and CATs through incentive schemes and tax reductions will significantly reduce the negative externalities of freight transport. Autonomous delivery robots (ADRs) are another emerging technology in retail and are projected to be a crucial step towards low-carbon last-mile deliveries [ 89 ]. With various tests underway, researchers believe that ADRs could revolutionize the system and reduce delivery costs by 80% to 90%. Although the current state of autonomous delivery still faces substantial challenges, the capabilities of the technology are promising for a country like India, with a fragmented delivery system. There has also been conclusive evidence that autonomous delivery robots (ADRs) can bring carbon emissions down compared to traditional van deliveries, especially when the delivery areas are near to the depot [ 90 ]. The existing policy framework in India, however, does not allow testing of autonomous technology and significant research is required to assess the implementation challenges in enabling CATs, ETs, and ADRs in India. Recent policy initiatives by the Indian government, such as ‘Faster Adoption and Manufacturing of Hybrid and Electric Vehicles’ (FAME), are a valuable step towards fostering technology advancements in freight transport.

Crowdshipping on transit: Crowdshipping on transit (COT) is a concept that incorporates the underutilized passenger transport mode capacity and related infrastructure to cover the last mile and deliver freight packages [ 91 ]. Packages are delivered with the help of commuters and other trip makers, who drop the packages off at designated places on their way, for the packages to then be picked up by another trip maker and delivered to the customer at the final destination. While large-scale formal crowdshipping programmes have been missing in Indian cities, the ongoing COVID-19 pandemic has put a sudden spotlight on introducing COT for enhancing non-ticket revenue of transit systems [ 92 ]. For instance, the public transit agency in Kerala, a Southern state in India, has recently initiated COT programs for parcel service in an attempt to overcome the fall in revenue following the pandemic-induced lockdowns and heightened risk perceptions [ 93 ]. Further research is required to scale up COT programs with the required infrastructure and operational efficiency for last-mile delivery.

Planning and cooperation initiatives: Business establishments can achieve higher logistic performance by cooperating with other stakeholders in the freight system, utilizing resources more efficiently [ 94 ]. This cooperation can either be horizontal (between same types of establishments active in the same stage of supply chain, such as carriers) or vertical (between different establishments positioned upstream and downstream of a supply chain, such as shippers and carriers). Despite the potential benefits of collaboration among logistics service providers, there is little effective collaboration in practice. In the era of the sharing economy, logistics collaborations have great potential in a country like India towards on-demand logistics, freight consolidation, facility sharing, and warehousing.

Conclusions

This paper has reviewed Indian freight transport research and policies in terms of logistic performance and solution approach for mitigating externalities. What emerges from the discussion is that freight transport is growing substantially in India, mainly due to its growing economy. However, like in Europe and the USA, the share of road transport seems too high, especially bearing in mind the higher negative externalities that road freight causes relative to its main competitor, rail freight. Decreasing this share is not easy because of the fragmentation of receivers and carriers in India. The penetration of the Internet has also triggered, like in most developed and many developing countries, an increase in B2CF, which only increases air pollutant and GHG emissions, and congestion. To make matters worse, some of the policies intended to reduce the externalities from road freight in India are proving counterproductive. Restricting areas or hours of freight deliveries, or banning big trucks, has increased, rather than decreased some externalities. The response has often been to fragment deliveries even further by, for example, using smaller vehicles and making more trips, or delivering during the night when time restrictions do not apply.

A portfolio of solution concepts to overcome the inefficiencies has also been presented. Although there is no one solution that will solve all the problems discussed, the following policy interventions have the potential to make freight more efficient in India and reduce emissions of air pollutants and GHG. Long-term planning and significant investment in infrastructure, including parking and loading bays, exclusive truck routes, consolidation centres, urban logistics spaces and pack stations, increasing road and rail network quality and capacity, could go some way towards integrating road and rail freight and reducing traffic congestion. Short-term planning to reduce the impact of freight transport within the existing expanse of transport infrastructure, including the development of intermodal logistic parks in tandem with dedicated freight corridors, and the promotion of double-stack clearance (stack containers one above the other) of intermodal corridors, would also help to increase the efficiency of the freight transport system in India. Additional interventions could entail developing more accurate demand forecasting models, automating warehouse processes, deploying inventory data insights in distribution network design to deal with demand volatility, implementing just-in-time inventory systems and fostering lean ordering behaviour among establishments, achieving efficiency in truck routing and dispatching through real-time information, implementing intelligent transport systems (ITS), delivering space booking systems, and route planning systems, and promoting electric delivery trucks.

The coordination and implementation of these actions are likely to require financial and time resources, and to encounter some degree of stakeholder backlash. This review has outlined the progress in freight research related to India and provided a framework of solution concepts. India is in a position to leapfrog and make important advances in policy implementation and doing so will increase the efficiency of freight transport, with consequent positive impacts on the economy and the environment.

Data Availability

The data that support the findings of this study are available from Prasanta Sahu ( [email protected] ) upon reasonable request.

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Funding was provided by the Research Initiation Grant (RIG Head 06/03/302), Birla Institute of Technology and Science (BITS) Pilani, Hyderabad, India.

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Sahu, P.K., Pani, A. & Santos, G. Freight Traffic Impacts and Logistics Inefficiencies in India: Policy Interventions and Solution Concepts for Sustainable City Logistics. Transp. in Dev. Econ. 8 , 31 (2022). https://doi.org/10.1007/s40890-022-00161-8

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The state of AI in early 2024: Gen AI adoption spikes and starts to generate value

If 2023 was the year the world discovered generative AI (gen AI) , 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey  on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year , with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.

About the authors

This article is a collaborative effort by Alex Singla , Alexander Sukharevsky , Lareina Yee , and Michael Chui , with Bryce Hall , representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.

Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.

AI adoption surges

Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in any region; however, this year more than two-thirds of respondents in nearly every region say their organizations are using AI. 1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption. Looking by industry, the biggest increase in adoption can be found in professional services. 2 Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.

Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).

Gen AI adoption is most common in the functions where it can create the most value

Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which previous research  determined that gen AI adoption could generate the most value 3 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. —as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.

Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.

Investments in gen AI and analytical AI are beginning to create value

The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.

Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found last year —as well as meaningful revenue increases from AI use in marketing and sales.

Inaccuracy: The most recognized and experienced risk of gen AI use

As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.

Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).

Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.

In fact, inaccuracy— which can affect use cases across the gen AI value chain , ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.

Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.

Our previous research has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place. 4 “ Implementing generative AI with speed and safety ,” McKinsey Quarterly , March 13, 2024. For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.

Bringing gen AI capabilities to bear

The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found three archetypes for implementing gen AI solutions : takers use off-the-shelf, publicly available solutions; shapers customize those tools with proprietary data and systems; and makers develop their own foundation models from scratch. 5 “ Technology’s generational moment with generative AI: A CIO and CTO guide ,” McKinsey, July 11, 2023. Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.

Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.

Gen AI high performers are excelling despite facing challenges

Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.

To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.

What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.

Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “ shift left .” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.

In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.

About the research

The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

Alex Singla and Alexander Sukharevsky  are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; Lareina Yee  is a senior partner in the Bay Area office, where Michael Chui , a McKinsey Global Institute partner, is a partner; and Bryce Hall  is an associate partner in the Washington, DC, office.

They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.

This article was edited by Heather Hanselman, a senior editor in McKinsey’s Atlanta office.

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Title: hallucination-free assessing the reliability of leading ai legal research tools.

Abstract: Legal practice has witnessed a sharp rise in products incorporating artificial intelligence (AI). Such tools are designed to assist with a wide range of core legal tasks, from search and summarization of caselaw to document drafting. But the large language models used in these tools are prone to "hallucinate," or make up false information, making their use risky in high-stakes domains. Recently, certain legal research providers have touted methods such as retrieval-augmented generation (RAG) as "eliminating" (Casetext, 2023) or "avoid[ing]" hallucinations (Thomson Reuters, 2023), or guaranteeing "hallucination-free" legal citations (LexisNexis, 2023). Because of the closed nature of these systems, systematically assessing these claims is challenging. In this article, we design and report on the first preregistered empirical evaluation of AI-driven legal research tools. We demonstrate that the providers' claims are overstated. While hallucinations are reduced relative to general-purpose chatbots (GPT-4), we find that the AI research tools made by LexisNexis (Lexis+ AI) and Thomson Reuters (Westlaw AI-Assisted Research and Ask Practical Law AI) each hallucinate between 17% and 33% of the time. We also document substantial differences between systems in responsiveness and accuracy. Our article makes four key contributions. It is the first to assess and report the performance of RAG-based proprietary legal AI tools. Second, it introduces a comprehensive, preregistered dataset for identifying and understanding vulnerabilities in these systems. Third, it proposes a clear typology for differentiating between hallucinations and accurate legal responses. Last, it provides evidence to inform the responsibilities of legal professionals in supervising and verifying AI outputs, which remains a central open question for the responsible integration of AI into law.

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Why the Pandemic Probably Started in a Lab, in 5 Key Points

logistics research paper pdf

By Alina Chan

Dr. Chan is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of “Viral: The Search for the Origin of Covid-19.”

This article has been updated to reflect news developments.

On Monday, Dr. Anthony Fauci returned to the halls of Congress and testified before the House subcommittee investigating the Covid-19 pandemic. He was questioned about several topics related to the government’s handling of Covid-19, including how the National Institute of Allergy and Infectious Diseases, which he directed until retiring in 2022, supported risky virus work at a Chinese institute whose research may have caused the pandemic.

For more than four years, reflexive partisan politics have derailed the search for the truth about a catastrophe that has touched us all. It has been estimated that at least 25 million people around the world have died because of Covid-19, with over a million of those deaths in the United States.

Although how the pandemic started has been hotly debated, a growing volume of evidence — gleaned from public records released under the Freedom of Information Act, digital sleuthing through online databases, scientific papers analyzing the virus and its spread, and leaks from within the U.S. government — suggests that the pandemic most likely occurred because a virus escaped from a research lab in Wuhan, China. If so, it would be the most costly accident in the history of science.

Here’s what we now know:

1 The SARS-like virus that caused the pandemic emerged in Wuhan, the city where the world’s foremost research lab for SARS-like viruses is located.

  • At the Wuhan Institute of Virology, a team of scientists had been hunting for SARS-like viruses for over a decade, led by Shi Zhengli.
  • Their research showed that the viruses most similar to SARS‑CoV‑2, the virus that caused the pandemic, circulate in bats that live r oughly 1,000 miles away from Wuhan. Scientists from Dr. Shi’s team traveled repeatedly to Yunnan province to collect these viruses and had expanded their search to Southeast Asia. Bats in other parts of China have not been found to carry viruses that are as closely related to SARS-CoV-2.

logistics research paper pdf

The closest known relatives to SARS-CoV-2 were found in southwestern China and in Laos.

Large cities

Mine in Yunnan province

Cave in Laos

South China Sea

logistics research paper pdf

The closest known relatives to SARS-CoV-2

were found in southwestern China and in Laos.

philippines

logistics research paper pdf

The closest known relatives to SARS-CoV-2 were found

in southwestern China and Laos.

Sources: Sarah Temmam et al., Nature; SimpleMaps

Note: Cities shown have a population of at least 200,000.

logistics research paper pdf

There are hundreds of large cities in China and Southeast Asia.

logistics research paper pdf

There are hundreds of large cities in China

and Southeast Asia.

logistics research paper pdf

The pandemic started roughly 1,000 miles away, in Wuhan, home to the world’s foremost SARS-like virus research lab.

logistics research paper pdf

The pandemic started roughly 1,000 miles away,

in Wuhan, home to the world’s foremost SARS-like virus research lab.

logistics research paper pdf

The pandemic started roughly 1,000 miles away, in Wuhan,

home to the world’s foremost SARS-like virus research lab.

  • Even at hot spots where these viruses exist naturally near the cave bats of southwestern China and Southeast Asia, the scientists argued, as recently as 2019 , that bat coronavirus spillover into humans is rare .
  • When the Covid-19 outbreak was detected, Dr. Shi initially wondered if the novel coronavirus had come from her laboratory , saying she had never expected such an outbreak to occur in Wuhan.
  • The SARS‑CoV‑2 virus is exceptionally contagious and can jump from species to species like wildfire . Yet it left no known trace of infection at its source or anywhere along what would have been a thousand-mile journey before emerging in Wuhan.

2 The year before the outbreak, the Wuhan institute, working with U.S. partners, had proposed creating viruses with SARS‑CoV‑2’s defining feature.

  • Dr. Shi’s group was fascinated by how coronaviruses jump from species to species. To find viruses, they took samples from bats and other animals , as well as from sick people living near animals carrying these viruses or associated with the wildlife trade. Much of this work was conducted in partnership with the EcoHealth Alliance, a U.S.-based scientific organization that, since 2002, has been awarded over $80 million in federal funding to research the risks of emerging infectious diseases.
  • The laboratory pursued risky research that resulted in viruses becoming more infectious : Coronaviruses were grown from samples from infected animals and genetically reconstructed and recombined to create new viruses unknown in nature. These new viruses were passed through cells from bats, pigs, primates and humans and were used to infect civets and humanized mice (mice modified with human genes). In essence, this process forced these viruses to adapt to new host species, and the viruses with mutations that allowed them to thrive emerged as victors.
  • By 2019, Dr. Shi’s group had published a database describing more than 22,000 collected wildlife samples. But external access was shut off in the fall of 2019, and the database was not shared with American collaborators even after the pandemic started , when such a rich virus collection would have been most useful in tracking the origin of SARS‑CoV‑2. It remains unclear whether the Wuhan institute possessed a precursor of the pandemic virus.
  • In 2021, The Intercept published a leaked 2018 grant proposal for a research project named Defuse , which had been written as a collaboration between EcoHealth, the Wuhan institute and Ralph Baric at the University of North Carolina, who had been on the cutting edge of coronavirus research for years. The proposal described plans to create viruses strikingly similar to SARS‑CoV‑2.
  • Coronaviruses bear their name because their surface is studded with protein spikes, like a spiky crown, which they use to enter animal cells. T he Defuse project proposed to search for and create SARS-like viruses carrying spikes with a unique feature: a furin cleavage site — the same feature that enhances SARS‑CoV‑2’s infectiousness in humans, making it capable of causing a pandemic. Defuse was never funded by the United States . However, in his testimony on Monday, Dr. Fauci explained that the Wuhan institute would not need to rely on U.S. funding to pursue research independently.

logistics research paper pdf

The Wuhan lab ran risky experiments to learn about how SARS-like viruses might infect humans.

1. Collect SARS-like viruses from bats and other wild animals, as well as from people exposed to them.

logistics research paper pdf

2. Identify high-risk viruses by screening for spike proteins that facilitate infection of human cells.

logistics research paper pdf

2. Identify high-risk viruses by screening for spike proteins that facilitate infection of

human cells.

logistics research paper pdf

In Defuse, the scientists proposed to add a furin cleavage site to the spike protein.

3. Create new coronaviruses by inserting spike proteins or other features that could make the viruses more infectious in humans.

logistics research paper pdf

4. Infect human cells, civets and humanized mice with the new coronaviruses, to determine how dangerous they might be.

logistics research paper pdf

  • While it’s possible that the furin cleavage site could have evolved naturally (as seen in some distantly related coronaviruses), out of the hundreds of SARS-like viruses cataloged by scientists, SARS‑CoV‑2 is the only one known to possess a furin cleavage site in its spike. And the genetic data suggest that the virus had only recently gained the furin cleavage site before it started the pandemic.
  • Ultimately, a never-before-seen SARS-like virus with a newly introduced furin cleavage site, matching the description in the Wuhan institute’s Defuse proposal, caused an outbreak in Wuhan less than two years after the proposal was drafted.
  • When the Wuhan scientists published their seminal paper about Covid-19 as the pandemic roared to life in 2020, they did not mention the virus’s furin cleavage site — a feature they should have been on the lookout for, according to their own grant proposal, and a feature quickly recognized by other scientists.
  • Worse still, as the pandemic raged, their American collaborators failed to publicly reveal the existence of the Defuse proposal. The president of EcoHealth, Peter Daszak, recently admitted to Congress that he doesn’t know about virus samples collected by the Wuhan institute after 2015 and never asked the lab’s scientists if they had started the work described in Defuse. In May, citing failures in EcoHealth’s monitoring of risky experiments conducted at the Wuhan lab, the Biden administration suspended all federal funding for the organization and Dr. Daszak, and initiated proceedings to bar them from receiving future grants. In his testimony on Monday, Dr. Fauci said that he supported the decision to suspend and bar EcoHealth.
  • Separately, Dr. Baric described the competitive dynamic between his research group and the institute when he told Congress that the Wuhan scientists would probably not have shared their most interesting newly discovered viruses with him . Documents and email correspondence between the institute and Dr. Baric are still being withheld from the public while their release is fiercely contested in litigation.
  • In the end, American partners very likely knew of only a fraction of the research done in Wuhan. According to U.S. intelligence sources, some of the institute’s virus research was classified or conducted with or on behalf of the Chinese military . In the congressional hearing on Monday, Dr. Fauci repeatedly acknowledged the lack of visibility into experiments conducted at the Wuhan institute, saying, “None of us can know everything that’s going on in China, or in Wuhan, or what have you. And that’s the reason why — I say today, and I’ve said at the T.I.,” referring to his transcribed interview with the subcommittee, “I keep an open mind as to what the origin is.”

3 The Wuhan lab pursued this type of work under low biosafety conditions that could not have contained an airborne virus as infectious as SARS‑CoV‑2.

  • Labs working with live viruses generally operate at one of four biosafety levels (known in ascending order of stringency as BSL-1, 2, 3 and 4) that describe the work practices that are considered sufficiently safe depending on the characteristics of each pathogen. The Wuhan institute’s scientists worked with SARS-like viruses under inappropriately low biosafety conditions .

logistics research paper pdf

In the United States, virologists generally use stricter Biosafety Level 3 protocols when working with SARS-like viruses.

Biosafety cabinets prevent

viral particles from escaping.

Viral particles

Personal respirators provide

a second layer of defense against breathing in the virus.

DIRECT CONTACT

Gloves prevent skin contact.

Disposable wraparound

gowns cover much of the rest of the body.

logistics research paper pdf

Personal respirators provide a second layer of defense against breathing in the virus.

Disposable wraparound gowns

cover much of the rest of the body.

Note: ​​Biosafety levels are not internationally standardized, and some countries use more permissive protocols than others.

logistics research paper pdf

The Wuhan lab had been regularly working with SARS-like viruses under Biosafety Level 2 conditions, which could not prevent a highly infectious virus like SARS-CoV-2 from escaping.

Some work is done in the open air, and masks are not required.

Less protective equipment provides more opportunities

for contamination.

logistics research paper pdf

Some work is done in the open air,

and masks are not required.

Less protective equipment provides more opportunities for contamination.

  • In one experiment, Dr. Shi’s group genetically engineered an unexpectedly deadly SARS-like virus (not closely related to SARS‑CoV‑2) that exhibited a 10,000-fold increase in the quantity of virus in the lungs and brains of humanized mice . Wuhan institute scientists handled these live viruses at low biosafet y levels , including BSL-2.
  • Even the much more stringent containment at BSL-3 cannot fully prevent SARS‑CoV‑2 from escaping . Two years into the pandemic, the virus infected a scientist in a BSL-3 laboratory in Taiwan, which was, at the time, a zero-Covid country. The scientist had been vaccinated and was tested only after losing the sense of smell. By then, more than 100 close contacts had been exposed. Human error is a source of exposure even at the highest biosafety levels , and the risks are much greater for scientists working with infectious pathogens at low biosafety.
  • An early draft of the Defuse proposal stated that the Wuhan lab would do their virus work at BSL-2 to make it “highly cost-effective.” Dr. Baric added a note to the draft highlighting the importance of using BSL-3 to contain SARS-like viruses that could infect human cells, writing that “U.S. researchers will likely freak out.” Years later, after SARS‑CoV‑2 had killed millions, Dr. Baric wrote to Dr. Daszak : “I have no doubt that they followed state determined rules and did the work under BSL-2. Yes China has the right to set their own policy. You believe this was appropriate containment if you want but don’t expect me to believe it. Moreover, don’t insult my intelligence by trying to feed me this load of BS.”
  • SARS‑CoV‑2 is a stealthy virus that transmits effectively through the air, causes a range of symptoms similar to those of other common respiratory diseases and can be spread by infected people before symptoms even appear. If the virus had escaped from a BSL-2 laboratory in 2019, the leak most likely would have gone undetected until too late.
  • One alarming detail — leaked to The Wall Street Journal and confirmed by current and former U.S. government officials — is that scientists on Dr. Shi’s team fell ill with Covid-like symptoms in the fall of 2019 . One of the scientists had been named in the Defuse proposal as the person in charge of virus discovery work. The scientists denied having been sick .

4 The hypothesis that Covid-19 came from an animal at the Huanan Seafood Market in Wuhan is not supported by strong evidence.

  • In December 2019, Chinese investigators assumed the outbreak had started at a centrally located market frequented by thousands of visitors daily. This bias in their search for early cases meant that cases unlinked to or located far away from the market would very likely have been missed. To make things worse, the Chinese authorities blocked the reporting of early cases not linked to the market and, claiming biosafety precautions, ordered the destruction of patient samples on January 3, 2020, making it nearly impossible to see the complete picture of the earliest Covid-19 cases. Information about dozens of early cases from November and December 2019 remains inaccessible.
  • A pair of papers published in Science in 2022 made the best case for SARS‑CoV‑2 having emerged naturally from human-animal contact at the Wuhan market by focusing on a map of the early cases and asserting that the virus had jumped from animals into humans twice at the market in 2019. More recently, the two papers have been countered by other virologists and scientists who convincingly demonstrate that the available market evidence does not distinguish between a human superspreader event and a natural spillover at the market.
  • Furthermore, the existing genetic and early case data show that all known Covid-19 cases probably stem from a single introduction of SARS‑CoV‑2 into people, and the outbreak at the Wuhan market probably happened after the virus had already been circulating in humans.

logistics research paper pdf

An analysis of SARS-CoV-2’s evolutionary tree shows how the virus evolved as it started to spread through humans.

SARS-COV-2 Viruses closest

to bat coronaviruses

more mutations

logistics research paper pdf

Source: Lv et al., Virus Evolution (2024) , as reproduced by Jesse Bloom

logistics research paper pdf

The viruses that infected people linked to the market were most likely not the earliest form of the virus that started the pandemic.

logistics research paper pdf

  • Not a single infected animal has ever been confirmed at the market or in its supply chain. Without good evidence that the pandemic started at the Huanan Seafood Market, the fact that the virus emerged in Wuhan points squarely at its unique SARS-like virus laboratory.

5 Key evidence that would be expected if the virus had emerged from the wildlife trade is still missing.

logistics research paper pdf

In previous outbreaks of coronaviruses, scientists were able to demonstrate natural origin by collecting multiple pieces of evidence linking infected humans to infected animals.

Infected animals

Earliest known

cases exposed to

live animals

Antibody evidence

of animals and

animal traders having

been infected

Ancestral variants

of the virus found in

Documented trade

of host animals

between the area

where bats carry

closely related viruses

and the outbreak site

logistics research paper pdf

Infected animals found

Earliest known cases exposed to live animals

Antibody evidence of animals and animal

traders having been infected

Ancestral variants of the virus found in animals

Documented trade of host animals

between the area where bats carry closely

related viruses and the outbreak site

logistics research paper pdf

For SARS-CoV-2, these same key pieces of evidence are still missing , more than four years after the virus emerged.

logistics research paper pdf

For SARS-CoV-2, these same key pieces of evidence are still missing ,

more than four years after the virus emerged.

  • Despite the intense search trained on the animal trade and people linked to the market, investigators have not reported finding any animals infected with SARS‑CoV‑2 that had not been infected by humans. Yet, infected animal sources and other connective pieces of evidence were found for the earlier SARS and MERS outbreaks as quickly as within a few days, despite the less advanced viral forensic technologies of two decades ago.
  • Even though Wuhan is the home base of virus hunters with world-leading expertise in tracking novel SARS-like viruses, investigators have either failed to collect or report key evidence that would be expected if Covid-19 emerged from the wildlife trade . For example, investigators have not determined that the earliest known cases had exposure to intermediate host animals before falling ill. No antibody evidence shows that animal traders in Wuhan are regularly exposed to SARS-like viruses, as would be expected in such situations.
  • With today’s technology, scientists can detect how respiratory viruses — including SARS, MERS and the flu — circulate in animals while making repeated attempts to jump across species . Thankfully, these variants usually fail to transmit well after crossing over to a new species and tend to die off after a small number of infections. In contrast, virologists and other scientists agree that SARS‑CoV‑2 required little to no adaptation to spread rapidly in humans and other animals . The virus appears to have succeeded in causing a pandemic upon its only detected jump into humans.

The pandemic could have been caused by any of hundreds of virus species, at any of tens of thousands of wildlife markets, in any of thousands of cities, and in any year. But it was a SARS-like coronavirus with a unique furin cleavage site that emerged in Wuhan, less than two years after scientists, sometimes working under inadequate biosafety conditions, proposed collecting and creating viruses of that same design.

While several natural spillover scenarios remain plausible, and we still don’t know enough about the full extent of virus research conducted at the Wuhan institute by Dr. Shi’s team and other researchers, a laboratory accident is the most parsimonious explanation of how the pandemic began.

Given what we now know, investigators should follow their strongest leads and subpoena all exchanges between the Wuhan scientists and their international partners, including unpublished research proposals, manuscripts, data and commercial orders. In particular, exchanges from 2018 and 2019 — the critical two years before the emergence of Covid-19 — are very likely to be illuminating (and require no cooperation from the Chinese government to acquire), yet they remain beyond the public’s view more than four years after the pandemic began.

Whether the pandemic started on a lab bench or in a market stall, it is undeniable that U.S. federal funding helped to build an unprecedented collection of SARS-like viruses at the Wuhan institute, as well as contributing to research that enhanced them . Advocates and funders of the institute’s research, including Dr. Fauci, should cooperate with the investigation to help identify and close the loopholes that allowed such dangerous work to occur. The world must not continue to bear the intolerable risks of research with the potential to cause pandemics .

A successful investigation of the pandemic’s root cause would have the power to break a decades-long scientific impasse on pathogen research safety, determining how governments will spend billions of dollars to prevent future pandemics. A credible investigation would also deter future acts of negligence and deceit by demonstrating that it is indeed possible to be held accountable for causing a viral pandemic. Last but not least, people of all nations need to see their leaders — and especially, their scientists — heading the charge to find out what caused this world-shaking event. Restoring public trust in science and government leadership requires it.

A thorough investigation by the U.S. government could unearth more evidence while spurring whistleblowers to find their courage and seek their moment of opportunity. It would also show the world that U.S. leaders and scientists are not afraid of what the truth behind the pandemic may be.

More on how the pandemic may have started

logistics research paper pdf

Where Did the Coronavirus Come From? What We Already Know Is Troubling.

Even if the coronavirus did not emerge from a lab, the groundwork for a potential disaster had been laid for years, and learning its lessons is essential to preventing others.

By Zeynep Tufekci

logistics research paper pdf

Why Does Bad Science on Covid’s Origin Get Hyped?

If the raccoon dog was a smoking gun, it fired blanks.

By David Wallace-Wells

logistics research paper pdf

A Plea for Making Virus Research Safer

A way forward for lab safety.

By Jesse Bloom

The Times is committed to publishing a diversity of letters to the editor. We’d like to hear what you think about this or any of our articles. Here are some tips . And here’s our email: [email protected] .

Follow the New York Times Opinion section on Facebook , Instagram , TikTok , WhatsApp , X and Threads .

Alina Chan ( @ayjchan ) is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of “ Viral : The Search for the Origin of Covid-19.” She was a member of the Pathogens Project , which the Bulletin of the Atomic Scientists organized to generate new thinking on responsible, high-risk pathogen research.

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Grassy Narrows First Nation files lawsuit against Ontario, federal governments over mercury contamination

Superior court challenge alleges governments fail to protect first nation treaty rights.

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A First Nation in northwestern Ontario that has faced decades of mercury poisoning is suing the provincial and federal governments, arguing they've failed to protect its treaty rights.

Asubpeeschoseewagong Netum Anishinabek First Nation — known as Grassy Narrows — filed the lawsuit in Ontario's Superior Court of Justice on Tuesday morning.

It argues the governments have violated their duties under Treaty 3 by failing to protect against or remedy the effects of mercury contamination in the English-Wabigoon River system.

The allegations in this lawsuit haven't been tested in court.

Contamination of the river system dates back to the 1960s and '70s  when Dryden's paper mill in northwestern Ontario dumped an estimated nine tonnes of mercury into the water.

Generations of people have consumed fish from the river. According to a previously reported study by medical specialists, about 90 per cent of the community of roughly 1,000 people experience symptoms of mercury poisoning. They include Chief Rudy Turtle.

"Our mercury nightmare should have ended long ago, but it has been longer and worse because of the government's failure to live up to its obligations," Turtle said in a news release on Tuesday.

'A test of ... commitment to truth'

For years, environmental advocates have called for the river to be cleaned up and the mill to be shut down.

In late May, a new study from Western University in London, Ont., revived these demands with a report suggesting mercury contamination in the river system has been made worse by ongoing industrial pollution.

"Dryden Fibre Canada took over operations for the mill last August. We operate in compliance with extensive environmental regulatory requirements," said Dianne Loewen, a spokesperson for Dryden Fibre Canada, in an email to CBC News late Tuesday afternoon. "Regarding this morning's announcement by Grassy Narrows — we have not yet seen the filing and will not be commenting."

logistics research paper pdf

Grassy Narrows lawsuit targets 'environmental racism' of mercury poisoning

"The government has egregiously violated its obligations to Grassy Narrows by failing to ensure that Grassy Narrows people could safely practise their right to fish — a cornerstone of Grassy Narrows' sustenance and Indigenous way of life," says a statement from the First Nation that was also issued Tuesday.

"This case will be a test of Ontario's and Canada's commitment to truth, reconciliation and justice following one of Canada's worst environmental and human rights catastrophes." 

Calls to end environmental racism

During a news conference in Toronto on Tuesday morning, Kiiwetinoong MPP Sol Mamakwa said the lack of government action is perpetuating the effects of colonialism on Grassy Narrows people.

"When we talk about environmental genocide, this is what it looks like," Mamakwa said.

Judy Da Silva is a Grassy Narrows grandmother and the community's environmental health co-ordinator. She says she also experiences symptoms of mercury poisoning, which include loss of co-ordination, trouble swallowing, and a loss of sensation in her hands and feet. 

A person stands at a podium set up outside a building and speaks into a microphone. Four people are standing behind them.

"Our people were proud fishermen and land users and hunters, and then this poison came and took all that away," Da Silva said in an interview with CBC News.

She thinks back to summer 2000, when the Walkerton water crisis made national headlines after seven people died and about 2,300 others became ill from Canada's worst E. coli contamination.

"They got compensated so quickly and then Grassy's been going through this for decades, and still there's no resolution," she said. "I think it's environmental racism."

Federal leaders respond

In 2017, the federal government committed to building a Mercury Care Home in Grassy Narrows. The same year, the Ontario government committed $85 million to fund mercury cleanup and remediation efforts in the English-Wabigoon River system.

About seven years later, the river remains toxic. Construction on the Mercury Care Home is expected to start this summer and take two to three years to complete.

In Ottawa on Tuesday, Minister of Indigenous Services Patty Hajdu told reporters she understands the frustration that has led Grassy Narrows to go through the courts.

"I'm sure they're seeing it as a part of a broader effort to ensure that this kind of environmental racism doesn't continue," Hajdu said.

logistics research paper pdf

Minister acknowledges frustration of Grassy Narrows First Nation following launch of lawsuit

Ottawa has now committed $146 million for the construction and operation of the Mercury Care Home, she said. While the protection of water falls under provincial jurisdiction, Hajdu did point to Bill C-61,  an act respecting water, source water, drinking water, wastewater and related infrastructure on First Nation lands , as a key way of preventing future harm.

CBC News reached out to the Ontario government for comment on the lawsuit and received an emailed response from Keesha Seaton, spokesperson for the Ministry of the Attorney General, late Tuesday afternoon.

"As this matter is subject to litigation, it would be inappropriate to comment," Seaton said.

A spokesperson for the federal Office of the Minister of the Environment and Climate Change also provided CBC News with an emailed statement on behalf of Hajdu and Minister of the Environment and Climate Change Steven Guilbeault.

  • Mercury poisoning near Grassy Narrows First Nation worsened by industrial pollution, study suggests
  • First Nations Land Defence Alliance says no nuclear waste facility without First Nations consent

"We cannot comment on the legal case as it is before the courts. It is extremely important to the government of Canada to do its part in responding to this crisis, and we will be there to work with Grassy Narrows and Wabaseemong Independent Nations every step of the way," wrote spokesperson Kaitlin Power.

Federal NDP Leader Jagmeet Singh also reacted to the Grassy Narrows lawsuit while addressing reporters on Parliament Hill.

"It's an ongoing example of Indigenous communities receiving second-class treatment," Singh said of the persisting mercury poisoning.

"This is Canada's fault and Canada must step up."

Lawsuit seeks to restore 'way of life'

Grassy Narrows, about 150 kilometres from Dryden near the Ontario-Manitoba border, is being represented by both Toronto-based firm Cavalluzzo LLP and Ratcliff LLP out of Vancouver.

At this point, there is no set dollar amount for how much compensation the First Nation is seeking. However, the types of remedies relate to restoring the environment, "upon which their health, and their livelihoods and their treaty rights depend," Adrienne Telford, co-lead legal counsel with Cavalluzzo LLP, said in an interview with CBC News.

A boat is shown on a scenic river picture.

"Grassy Narrows is a community in crisis," Telford said. "They require significant financial, and socioeconomic and health supports to allow community members to restore their health, and their well-being and their way of life."

"If this was Ontario cottage country, the river would have been cleaned up decades ago, the pollution would have stopped and the harms properly compensated."

Ontario commits to 'correcting this historic wrong'

When pressed by Kiiwetinoong MPP Sol Mamakwa during Monday's question period in the Ontario Legislature, the minister of the environment, conservation and parks, Andrea Khanjin, said the government is committed to remediating the mercury contamination.

Technical experts with the ministry have met with First Nations leaders and those who led the Western University study — though additional work is needed before the researchers' report is finalized, Khanjin said.

logistics research paper pdf

Is Ontario doing enough to address mercury contamination in the English-Wabigoon River system?

Sandy Shaw, MPP for Hamilton West—Ancaster—Dundas and NDP environment, conservation and parks critic, called that answer "disappointing."

"This is a human and ecological disaster and it has been going on for generations. For heaven's sake, Speaker, the time for studies has well passed," Shaw said.

  • Grassy Narrows chief announces candidacy for Ontario regional chief
  • Grassy Narrows chief calls out Ottawa for 'ridiculous' delays to mercury treatment centre construction

Khanjin responding by pointing to the work being done with Ontario's English and Wabigoon Rivers Remediation Panel .

"We're taking the politics out of this and referring to the science because this government remains committed to correcting this historic wrong."

ABOUT THE AUTHOR

logistics research paper pdf

Sarah Law is a CBC News reporter based in Thunder Bay, Ont., and has also worked for newspapers and online publications elsewhere in the province. Have a story tip? You can reach her at [email protected]

With files from Philip Lee-Shanok and Chris Glover

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    stead, the paper focuses on research methodologies applied in SCM research. 110 Á. Halldórsson, J. S. Arlbjørn 3 On Research Methods in Logistics and SCM ... program in logistics includes "methods in logistics research," and suggests fur-thermore that such a course may "…stimulate the innovativeness of logistics ...

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    The STF on integrative literature reviews4 offers an ave-nue to synthesize important L&SCM research streams that create novel empirical, theoretical, or managerial insights. The papers published in 2021 also reflect a variety of data sources and the application of rigorous methodologi-cal approaches. Because of the novelty of many of the phe ...

  9. Integrated transport and logistics for sustainable global trade

    This context is equally applicable in providing equitable access to an integrated and sustainable transport and logistics network for remote and peripheral regions to facilitate unrestricted yet fair global traded (Lee and Song 2023 ). This special issue therefore compiles a set of research papers that probe transport and logistics integration ...

  10. Operations management of smart logistics: A literature review and

    The global collaboration and integration of online and offline channels have brought new challenges to the logistics industry. Thus, smart logistics has become a promising solution for handling the increasing complexity and volume of logistics operations. Technologies, such as the Internet of Things, information communication technology, and artificial intelligence, enable more efficient ...

  11. Last mile logistics: Research trends and needs

    Green logistics is an area that focuses on manufacturing and delivering freight to avoid the depletion of scarce natural resources. We focus only on the distribution part of green logistics in this paper. From this standpoint, green vehicle routing is a specific research domain in green logistics that studies VRPs and related negative ...

  12. Assessment of logistics service quality dimensions: a qualitative

    Papers have been selected in accordance with the predefined criteria. As a result, a total of 59 articles have been determined for the search criteria and the findings obtained were analyzed. Most frequently used research trends and methods on service quality in logistics have been identified.

  13. The International Journal of Logistics Management

    Issue 2 2019. Issue 1 2019. Volume 29. Issue 4 2018 22nd International Symposium in Logistics, 2017. Issue 3 2018 Cold chain supply chain management. Issue 2 2018 Big data analytics in logistics and supply chain management. Issue 1 2018. Volume 28. Issue 4 2017.

  14. PDF Impact of Technology on Logistics and Supply Chain Management

    7th International Business Research Conference 19 | Page Indian Education Society's Management College and Research Centre Impact of Technology on Logistics and Supply Chain Management Rajiv Bhandari F-303, Arenja Complex, Sector 8, C.B.D Belapur Navi Mumbai 400614, 9819884293 ... paper is to determine the various technology used in logistics ...

  15. Big data analytics in logistics and supply chain management

    The ninth paper in this SI examines the determinants of BDA in logistics and supply chain management by Lai et al.. The authors have undertaken an extensive literature review of extant literature on BDA and SCM and have further classified the factors into four constructs: technological factors, organizational factors, environmental factors and ...

  16. Freight Traffic Impacts and Logistics Inefficiencies in ...

    The objectives of this review paper are therefore threefold: (1) to investigate the various aspects of freight system performance, logistics inefficiencies, and freight traffic negative externalities in India; (2) to discuss the potential solution concepts and prepare a research agenda for future research on sustainable city logistics in India ...

  17. PDF Analysis of the Logistics Research in India White Paper

    Analysis of the Logistics Research in India - White Paper 4/11 3. Focus and cooperation practices of logistics research in India 3.1 Prevailing topics and institutions of logistics research in India In this section, we provide an overview of the most active institutions and their main specializations in logistics research.

  18. Multi-objective location-routing model and algorithm study of material

    @article{Zhu2024MultiobjectiveLM, title={Multi-objective location-routing model and algorithm study of material reserve bases for large-scale railway engineering construction projects}, author={Hongxing Zhu and Jin Zhang and Hao Shen and Wenguang Yang and Wenjie Sun and Yan Zhang}, journal={International Journal of Systems Science: Operations ...

  19. Navigating the labor mismatch in US logistics and supply chains

    The transportation and logistics sector has been particularly hard hit, with the impact of worker-retention challenges and rising labor costs being felt across the entire value chain. The labor mismatch has pushed private-sector wages to increase at more than double the long-term pre-COVID-19 growth rates, yet positions remain unfilled.

  20. The state of AI in early 2024: Gen AI adoption spikes and starts to

    About the research. The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and ...

  21. [2405.20362] Hallucination-Free? Assessing the Reliability of Leading

    View a PDF of the paper titled Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools, by Varun Magesh and 5 other authors ... making their use risky in high-stakes domains. Recently, certain legal research providers have touted methods such as retrieval-augmented generation (RAG) as "eliminating" (Casetext, 2023) or ...

  22. Why the Pandemic Probably Started in a Lab, in 5 Key Points

    Dr. Chan is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of "Viral: The Search for the Origin of Covid-19." This article has been updated to reflect news ...

  23. Grassy Narrows First Nation files lawsuit against Ontario, federal

    A First Nation that has faced decades of mercury poisoning is suing the provincial and federal governments, arguing they've failed to protect its treaty rights.The lawsuit by Grassy Narrows First ...