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Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

• Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
• Fifty four percent of raw case users came from outside the U.S..
• The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
• Twenty-six of the cases in the list are raw cases.
• A third of the cases feature a woman protagonist.
• Orders for Yale SOM case studies increased by almost 50% compared to 2020.
• The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

Cracking the code to smarter B2B technology sales

A multinational tech company unlocks big revenues with a rapid pilot approach to selling cloud services across segments, regions & partner channels.

• Call for Change
• When Tech Meets Human Ingenuity
• A Valuable Difference
• Related Capabilities

Call for change

This tech platform company carved out a top spot in the cloud market with its easy-to-use products and services. But while its solutions were designed for simplicity, the company found selling in the B2B space was getting more complex.  

With an expanding array of cloud solutions and millions of prospects and customers, the company must coordinate across countless channels, global regions, and segments, including small- and medium-sized businesses (SMB), corporate, enterprise, public sector, and education.

The tech platform company knew if it could better manage these moving parts, it stood to capture a greater piece of the B2B market. It set out an ambitious plan to make more effective use of channels, rapidly test and deploy fresh go-to-market strategies, and scale sales processes to better serve its growing customer base.

When tech meets human ingenuity

With Accenture’s help, the tech platform company has reinvented its inside sales strategy to a scalable, human + machine model that rapidly tests new products and segments and optimizes existing ones.

The program has three key areas of focus:

Sales development

Scaling up inbound and outbound demand for the United States, Canada, and Latin America, covering enterprise, corporate, SMB, and public sector segments. Accenture helped the company

• Enrich & prioritize leads across all product categories.
• Qualify leads into new revenue opportunities. 

Partner enablement

Providing enablement and demand and account development services to channel partners across North America and Latin America. This includes:

• Onboarding support
• Ongoing consulting
• Lead generation

Full-cycle SMB sales

Shaping a highly efficient and connected experience for SMBs in Latin America through the full customer journey:

• Acquisition
• Customer success

The result: a scalable, human + machine model that rapidly tests new products and segments and optimizes existing ones—and drives revenue.

A valuable difference

With a new ability to quickly test and optimize go-to-market strategies, the company is seeing pipeline, revenue, and partner satisfaction soar to new heights. Key results to date include:

in new pipeline

in upsell, cross-sell, and net-new revenue

increase in lead-to-pipeline conversion rate

In addition to the sales impacts, Accenture’s SMB team has outperformed their expected revenue goal by 28%, and Accenture’s partner team has helped the client achieve a partner satisfaction score of 95%, a 20% increase over previous programs.

The tech platform company now hopes to build on these impressive results by expanding programs in North America and Latin America, and establishing similar programs in Europe, and Asia-Pacific—setting the company on course for even greater growth in sales opportunities and revenues.

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How a Global Management and IT Firm Saved $47M on Contingent Workforce Management (Case Study)

By MBO Partners | June 4, 2022

With a program in place to handle the entire independent talent lifecycle, organizations can increase their control over compliance risk, realize significant cost savings, and achieve greater spend visibility.

Enterprises have a lot to gain from developing a centralized engagement program that encompasses finding, sourcing, engaging, paying, and managing independent workers.

By providing flexible engagement options that appeal to a wide range of independent talent, organizations can strategically manage independent contractor spend with insight and data while increasing worker satisfaction.

Vertical: Professional Services | Type: Workforce Management

Managing various groups of independent professionals in a streamlined, compliant manner is a difficult thing for enterprises to do without the right infrastructure in place. While the rise of new collaboration technology makes it easier for companies to expand their national or global presence for less cost and administrative overhead, it is important to make sure these tools work together and are efficient and easy to use.

With a program in place to handle the entire independent talent lifecycle , organizations can increase their control over compliance risk, realize significant cost savings, and achieve greater spend visibility. These three tangible benefits can help organizations remain both legally compliant and competitive among peers.

3 Benefits of a Contingent Workforce Management Program

• A comprehensive program can help minimize the risk of worker misclassification. By working with a company like MBO, organizations can gain access to valuable strategies, tools, and advice to steer clear of misclassification and legal risk.
• A defined program can help minimize costs from both a compliance and engagement perspective. By providing flexible engagement options that appeal to a wide range of independent talent, organizations can strategically manage independent contractor spend with insight and data while increasing worker satisfaction.
• Enterprises can increase visibility into expenses and profitability with a defined program in place. Over time, this visibility can help organizations better manage costs, and alleviate administrative burdens by giving managers the tools they need to find, engage, and manage independent talent.

5 Ways a Global IT Firm Saved $47M on Contingent Workforce Management

A global management and information technology consulting firm needed assistance with proposal support and contract administration for their independent workforce. They also needed to revamp their internal compliance review process and streamline the way they engaged independent talent. They decided to partner with MBO to develop an infrastructure to support the firm’s entire talent lifecycle.

What We Did:

• Consolidated the firm’s population of independent contractors under one program
• Developed processes to engage independent talent easier and faster
• Implemented a simple way for independents to track time as well as billable and non-billable expenses
• Improved the proposal process, helping independent contractors qualify for small business certifications when applicable to meet federal contract requirements
• Expanded program to six business units, saving the firm $47 million since program inception

View the case study to learn more about how the consulting firm saved $47M since program inception.

You can also contact our team of experts today, or view our case study library to see more success stories.

The information provided in the MBO Blog does not constitute legal, tax or financial advice. It does not take into account your particular circumstances, objectives, legal and financial situation or needs. Before acting on any information in the MBO Blog you should consider the appropriateness of the information for your situation in consultation with a professional advisor of your choosing.  

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Case Studies 3 MINs READ

Case studies | [rt_reading_time label='' postfix="mins read" postfix_singular="min read"], 5 ways a healthcare company streamlined contractor onboarding (case study), april 22, 2022.

4 Ways an American Bank Saved $13.2M through Direct Sourcing (Case Study)

April 15, 2022.

4 Ways a Leading Cloud-Based Software Company Optimized their Workforce (Case Study)

March 25, 2022, misclassification & compliance 3 mins read, misclassification & compliance | [rt_reading_time label='' postfix="mins read" postfix_singular="min read"], 3 ways to stay compliant when hiring independent contractors, by mbo partners | may 15, 2024, direct sourcing 5 mins read, direct sourcing | [rt_reading_time label='' postfix="mins read" postfix_singular="min read"], 5 ways direct sourcing helps overcome challenges using independent professionals, by mbo partners | may 11, 2024, workforce management 4 mins read, workforce management | [rt_reading_time label='' postfix="mins read" postfix_singular="min read"], benefits and challenges of building an international contingent workforce, by jessica soler | may 9, 2024, subscribe to our blog, get a weekly email of our latest posts sent straight to your inbox, learn more about the mbo platform, for independent professionals, start, run, and grow.

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47 case interview examples (from McKinsey, BCG, Bain, etc.)

One of the best ways to prepare for   case interviews  at firms like McKinsey, BCG, or Bain, is by studying case interview examples. 

There are a lot of free sample cases out there, but it's really hard to know where to start. So in this article, we have listed all the best free case examples available, in one place.

The below list of resources includes interactive case interview samples provided by consulting firms, video case interview demonstrations, case books, and materials developed by the team here at IGotAnOffer. Let's continue to the list.

• McKinsey examples
• BCG examples
• Bain examples
• Deloitte examples
• Other firms' examples
• Case books from consulting clubs
• Case interview preparation

Click here to practise 1-on-1 with MBB ex-interviewers

1. mckinsey case interview examples.

• Beautify case interview (McKinsey website)
• Diconsa case interview (McKinsey website)
• Electro-light case interview (McKinsey website)
• GlobaPharm case interview (McKinsey website)
• National Education case interview (McKinsey website)
• Talbot Trucks case interview (McKinsey website)
• Shops Corporation case interview (McKinsey website)
• Conservation Forever case interview (McKinsey website)
• McKinsey case interview guide (by IGotAnOffer)
• McKinsey live case interview extract (by IGotAnOffer) - See below

2. BCG case interview examples

• Foods Inc and GenCo case samples  (BCG website)
• Chateau Boomerang written case interview  (BCG website)
• BCG case interview guide (by IGotAnOffer)
• Written cases guide (by IGotAnOffer)
• BCG live case interview with notes (by IGotAnOffer)
• BCG mock case interview with ex-BCG associate director - Public sector case (by IGotAnOffer)
• BCG mock case interview: Revenue problem case (by IGotAnOffer) - See below

3. Bain case interview examples

• CoffeeCo practice case (Bain website)
• FashionCo practice case (Bain website)
• Associate Consultant mock interview video (Bain website)
• Consultant mock interview video (Bain website)
• Written case interview tips (Bain website)
• Bain case interview guide   (by IGotAnOffer)
• Digital transformation case with ex-Bain consultant
• Bain case mock interview with ex-Bain manager (below)

4. Deloitte case interview examples

• Engagement Strategy practice case (Deloitte website)
• Recreation Unlimited practice case (Deloitte website)
• Strategic Vision practice case (Deloitte website)
• Retail Strategy practice case  (Deloitte website)
• Finance Strategy practice case  (Deloitte website)
• Talent Management practice case (Deloitte website)
• Enterprise Resource Management practice case (Deloitte website)
• Footloose written case  (by Deloitte)
• Deloitte case interview guide (by IGotAnOffer)

5. Accenture case interview examples

• Case interview workbook (by Accenture)
• Accenture case interview guide (by IGotAnOffer)

6. OC&C case interview examples

• Leisure Club case example (by OC&C)
• Imported Spirits case example (by OC&C)

7. Oliver Wyman case interview examples

• Wumbleworld case sample (Oliver Wyman website)
• Aqualine case sample (Oliver Wyman website)
• Oliver Wyman case interview guide (by IGotAnOffer)

8. A.T. Kearney case interview examples

• Promotion planning case question (A.T. Kearney website)
• Consulting case book and examples (by A.T. Kearney)
• AT Kearney case interview guide (by IGotAnOffer)

9. Strategy& / PWC case interview examples

• Presentation overview with sample questions (by Strategy& / PWC)
• Strategy& / PWC case interview guide (by IGotAnOffer)

10. L.E.K. Consulting case interview examples

• Case interview example video walkthrough   (L.E.K. website)
• Market sizing case example video walkthrough  (L.E.K. website)

11. Roland Berger case interview examples

• Transit oriented development case webinar part 1  (Roland Berger website)
• Transit oriented development case webinar part 2   (Roland Berger website)
• 3D printed hip implants case webinar part 1   (Roland Berger website)
• 3D printed hip implants case webinar part 2   (Roland Berger website)
• Roland Berger case interview guide   (by IGotAnOffer)

12. Capital One case interview examples

• Case interview example video walkthrough  (Capital One website)
• Capital One case interview guide (by IGotAnOffer)

13. Consulting clubs case interview examples

• Berkeley case book (2006)
• Columbia case book (2006)
• Darden case book (2012)
• Darden case book (2018)
• Duke case book (2010)
• Duke case book (2014)
• ESADE case book (2011)
• Goizueta case book (2006)
• Illinois case book (2015)
• LBS case book (2006)
• MIT case book (2001)
• Notre Dame case book (2017)
• Ross case book (2010)
• Wharton case book (2010)

Practice with experts

Using case interview examples is a key part of your interview preparation, but it isn’t enough.

At some point you’ll want to practise with friends or family who can give some useful feedback. However, if you really want the best possible preparation for your case interview, you'll also want to work with ex-consultants who have experience running interviews at McKinsey, Bain, BCG, etc.

If you know anyone who fits that description, fantastic! But for most of us, it's tough to find the right connections to make this happen. And it might also be difficult to practice multiple hours with that person unless you know them really well.

Here's the good news. We've already made the connections for you. We’ve created a coaching service where you can do mock case interviews 1-on-1 with ex-interviewers from MBB firms . Start scheduling sessions today!

The IGotAnOffer team

• FARO Sphere Login

Technology Transformation

Before adopting 3D reality capture hardware and software, JFD Engineering relied on a total station. Their traditional approach involved two people working in the field. After surveying, these two people would return to the office to create drawings. This method worked well in terms of accuracy — but during a labor shortage in the construction industry, it resulted in prolonged working hours for the company.

As such, they made the switch to a 3D laser scanner. Their old total station required two people to do the job; the FARO ® Focus Premium Laser Scanner required only one operator.

For JFD Engineering, this immediately doubled their work efficiency and operational efficiency.

Download the full case study to read how this surveying firm solved construction industry labor shortage issues and tackled 3D (“dirty, difficult, and dangerous”) challenges on their jobsites by switching to 3D scanners.

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40 Detailed Artificial Intelligence Case Studies [2024]

In this dynamic era of technological advancements, Artificial Intelligence (AI) emerges as a pivotal force, reshaping the way industries operate and charting new courses for business innovation. This article presents an in-depth exploration of 40 diverse and compelling AI case studies from across the globe. Each case study offers a deep dive into the challenges faced by companies, the AI-driven solutions implemented, their substantial impacts, and the valuable lessons learned. From healthcare and finance to transportation and retail, these stories highlight AI’s transformative power in solving complex problems, optimizing processes, and driving growth, offering insightful glimpses into the potential and versatility of AI in shaping our world.

Related: How to Become an AI Thought Leader?

1. IBM Watson Health: Revolutionizing Patient Care with AI

Task/Conflict: The healthcare industry faces challenges in handling vast amounts of patient data, accurately diagnosing diseases, and creating effective treatment plans. IBM Watson Health aimed to address these issues by harnessing AI to process and analyze complex medical information, thus improving the accuracy and efficiency of patient care.

Solution: Utilizing the cognitive computing capabilities of IBM Watson, this solution involves analyzing large volumes of medical records, research papers, and clinical trial data. The system uses natural language processing to understand and process medical jargon, making sense of unstructured data to aid medical professionals in diagnosing and treating patients.

Overall Impact:

• Enhanced accuracy in patient diagnosis and treatment recommendations.
• Significant improvement in personalized healthcare services.

Key Learnings:

• AI can complement medical professionals’ expertise, leading to better healthcare outcomes.
• The integration of AI in healthcare can lead to significant advancements in personalized medicine.

2. Google DeepMind’s AlphaFold: Unraveling the Mysteries of Protein Folding

Task/Conflict: The scientific community has long grappled with the protein folding problem – understanding how a protein’s amino acid sequence determines its 3D structure. Solving this problem is crucial for drug discovery and understanding diseases at a molecular level, yet it remained a formidable challenge due to the complexity of biological structures.

Solution: AlphaFold, developed by Google DeepMind, is an AI model trained on vast datasets of known protein structures. It assesses the distances and angles between amino acids to predict how a protein folds, outperforming existing methods in terms of speed and accuracy. This breakthrough represents a major advancement in computational biology.

• Significant acceleration in drug discovery and disease understanding.
• Set a new benchmark for computational methods in biology.
• AI’s predictive power can solve complex biological problems.
• The application of AI in scientific research can lead to groundbreaking discoveries.

3. Amazon: Transforming Supply Chain Management through AI

Task/Conflict: Managing a global supply chain involves complex challenges like predicting product demand, optimizing inventory levels, and streamlining logistics. Amazon faced the task of efficiently managing its massive inventory while minimizing costs and meeting customer demands promptly.

Solution: Amazon employs sophisticated AI algorithms for predictive inventory management, which forecast product demand based on various factors like buying trends, seasonality, and market changes. This system allows for real-time adjustments, adapting swiftly to changing market dynamics.

• Reduced operational costs through efficient inventory management.
• Improved customer satisfaction with timely deliveries and availability.
• AI can significantly enhance supply chain efficiency and responsiveness.
• Predictive analytics in inventory management leads to reduced waste and cost savings.

4. Tesla’s Autonomous Vehicles: Driving the Future of Transportation

Task/Conflict: The development of autonomous vehicles represents a major technological and safety challenge. Tesla aimed to create self-driving cars that are not only reliable and safe but also capable of navigating complex traffic conditions without human intervention.

Solution: Tesla’s solution involves advanced AI and machine learning algorithms that process data from various sensors and cameras to understand and navigate the driving environment. Continuous learning from real-world driving data allows the system to improve over time, making autonomous driving safer and more efficient.

• Leadership in the autonomous vehicle sector, enhancing road safety.
• Continuous improvements in self-driving technology through AI-driven data analysis.
• Continuous data analysis is key to advancing autonomous driving technologies.
• AI can significantly improve road safety and driving efficiency.

Related: High-Paying AI Career Options

5. Zara: Fashioning the Future with AI in Retail

Task/Conflict: In the fast-paced fashion industry, predicting trends and managing inventory efficiently are critical for success. Zara faced the challenge of quickly adapting to changing fashion trends while avoiding overstock and meeting consumer demand.

Solution: Zara employs AI algorithms to analyze fashion trends, customer preferences, and sales data. The AI system also assists in managing inventory, ensuring that popular items are restocked promptly and that stores are not overburdened with unsold products. This approach optimizes both production and distribution.

• Increased sales and profitability through optimized inventory.
• Enhanced customer satisfaction by aligning products with current trends.
• AI can accurately predict consumer behavior and trends.
• Effective inventory management through AI can significantly impact business success.

6. Netflix: Personalizing Entertainment with AI

Task/Conflict: In the competitive streaming industry, providing a personalized user experience is key to retaining subscribers. Netflix needed to recommend relevant content to each user from its vast library, ensuring that users remained engaged and satisfied.

Solution: Netflix developed an advanced AI-driven recommendation engine that analyzes individual viewing habits, ratings, and preferences. This personalized approach keeps users engaged, as they are more likely to find content that interests them, enhancing their overall viewing experience.

• Increased viewer engagement and longer watch times.
• Higher subscription retention rates due to personalized content.
• Personalized recommendations significantly enhance user experience.
• AI-driven content curation is essential for success in digital entertainment.

7. Airbus: Elevating Aircraft Maintenance with AI

Task/Conflict: Aircraft maintenance is crucial for ensuring flight safety and operational efficiency. Airbus faced the challenge of predicting maintenance needs to prevent equipment failures and reduce downtime, which is critical in the aviation industry.

Solution: Airbus implemented AI algorithms for predictive maintenance, analyzing data from aircraft sensors to identify potential issues before they lead to failures. This system assesses the condition of various components, predicting when maintenance is needed. The solution not only enhances safety but also optimizes maintenance schedules, reducing unnecessary inspections and downtime.

• Decreased maintenance costs and reduced aircraft downtime.
• Improved safety with proactive maintenance measures.
• AI can predict and prevent potential equipment failures.
• Predictive maintenance is essential for operational efficiency and safety in aviation.

8. American Express: Securing Transactions with AI

Task/Conflict: Credit card fraud is a significant issue in the financial sector, leading to substantial losses and undermining customer trust. American Express needed an efficient way to detect and prevent fraudulent transactions in real-time.

Solution: American Express utilizes machine learning models to analyze transaction data. These models identify unusual patterns and behaviors indicative of fraud. By constant learning from refined data, the system becomes increasingly accurate in detecting fraudulent activities, providing real-time alerts and preventing unauthorized transactions.

• Minimized financial losses due to reduced fraudulent activities.
• Enhanced customer trust and security in financial transactions.
• Machine learning is highly effective in fraud detection.
• Real-time data analysis is crucial for preventing financial fraud.

Related: Is AI a Good Career Option for Women?

9. Stitch Fix: Tailoring the Future of Fashion Retail

Task/Conflict: In the competitive fashion retail industry, providing a personalized shopping experience is key to customer satisfaction and business growth. Stitch Fix aimed to offer customized clothing selections to each customer, based on their unique preferences and style.

Solution: Stitch Fix uses AI and algorithms analyze customer feedback, style preferences, and purchase history to recommend clothing items. This personalized approach is complemented by human stylists, ensuring that each customer receives a tailored selection that aligns with their individual style.

• Increased customer satisfaction through personalized styling services.
• Business growth driven by a unique, AI-enhanced shopping experience.
• AI combined with human judgment can create highly effective personalization.
• Tailoring customer experiences using AI leads to increased loyalty and business success.

10. Baidu: Breaking Language Barriers with Voice Recognition

Task/Conflict: Voice recognition technology faces the challenge of accurately understanding and processing speech in various languages and accents. Baidu aimed to enhance its voice recognition capabilities to provide more accurate and user-friendly interactions in multiple languages.

Solution: Baidu employs deep learning algorithms for voice and speech recognition, training its system on a diverse range of languages and dialects. This approach allows for more accurate recognition of speech patterns, enabling the technology to understand and respond to voice commands more effectively. The system continuously improves as it processes more voice data, making technology more accessible to users worldwide.

• Enhanced user interaction with technology in multiple languages.
• Reduced language barriers in voice-activated services and devices.
• AI can effectively bridge language gaps in technology.
• Continuous learning from diverse data sets is key to improving voice recognition.

11. JP Morgan: Revolutionizing Legal Document Analysis with AI

Task/Conflict: Analyzing legal documents, such as contracts, is a time-consuming and error-prone process. JP Morgan sought to streamline this process, reducing the time and effort required while increasing accuracy.

Solution: JP Morgan implemented an AI-powered tool, COIN (Contract Intelligence), to analyze legal documents quickly and accurately. COIN uses NLP to interpret and extract relevant information from contracts, significantly reducing the time required for document review.

• Dramatic reduction in time required for legal document analysis.
• Increased accuracy and reduced human error in contract interpretation.
• AI can efficiently handle large volumes of data, offering speed and accuracy.
• Automation in legal processes can significantly enhance operational efficiency.

12. Microsoft: AI for Accessibility

Task/Conflict: People with disabilities often face challenges in accessing technology. Microsoft aimed to create AI-driven tools to enhance accessibility, especially for individuals with visual, hearing, or cognitive impairments.

Solution: Microsoft developed a range of AI-powered tools including applications for voice recognition, visual assistance, and cognitive support, making technology more accessible and user-friendly. For instance, Seeing AI, an app developed by Microsoft, helps visually impaired users to understand their surroundings by describing people, texts, and objects.

• Improved accessibility and independence for people with disabilities.
• Creation of more inclusive technology solutions.
• AI can significantly contribute to making technology accessible for all.
• Developing inclusive technology is essential for societal progress.

Related: How to get an Internship in AI?

13. Alibaba’s City Brain: Revolutionizing Urban Traffic Management

Task/Conflict: Urban traffic congestion is a major challenge in many cities, leading to inefficiencies and environmental concerns. Alibaba’s City Brain project aimed to address this issue by using AI to optimize traffic flow and improve public transportation in urban areas.

Solution: City Brain uses AI to analyze real-time data from traffic cameras, sensors, and GPS systems. It processes this information to predict traffic patterns and optimize traffic light timing, reducing congestion. The system also provides data-driven insights for urban planning and emergency response coordination, enhancing overall city management.

• Significant reduction in traffic congestion and improved urban transportation.
• Enhanced efficiency in city management and emergency response.
• AI can effectively manage complex urban systems.
• Data-driven solutions are key to improving urban living conditions.

14. Deep 6 AI: Accelerating Clinical Trials with Artificial Intelligence

Task/Conflict: Recruiting suitable patients for clinical trials is often a slow and cumbersome process, hindering medical research. Deep 6 AI sought to accelerate this process by quickly identifying eligible participants from a vast pool of patient data.

Solution: Deep 6 AI employs AI to sift through extensive medical records, identifying potential trial participants based on specific criteria. The system analyzes structured and unstructured data, including doctor’s notes and diagnostic reports, to find matches for clinical trials. This approach significantly speeds up the recruitment process, enabling faster trial completions and advancements in medical research.

• Quicker recruitment for clinical trials, leading to faster research progress.
• Enhanced efficiency in medical research and development.
• AI can streamline the patient selection process for clinical trials.
• Efficient recruitment is crucial for the advancement of medical research.

15. NVIDIA: Revolutionizing Gaming Graphics with AI

Task/Conflict: Enhancing the realism and performance of gaming graphics is a continuous challenge in the gaming industry. NVIDIA aimed to revolutionize gaming visuals by leveraging AI to create more realistic and immersive gaming experiences.

Solution: NVIDIA’s AI-driven graphic processing technologies, such as ray tracing and deep learning super sampling (DLSS), provide highly realistic and detailed graphics. These technologies use AI to render images more efficiently, improving game performance without compromising on visual quality. This innovation sets new standards in gaming graphics, making games more lifelike and engaging.

• Elevated gaming experiences with state-of-the-art graphics.
• Set new industry standards for graphic realism and performance.
• AI can significantly enhance creative industries, like gaming.
• Balancing performance and visual quality is key to gaming innovation.

16. Palantir: Mastering Data Integration and Analysis with AI

Task/Conflict: Integrating and analyzing large-scale, diverse datasets is a complex task, essential for informed decision-making in various sectors. Palantir Technologies faced the challenge of making sense of vast amounts of data to provide actionable insights for businesses and governments.

Solution: Palantir developed AI-powered platforms that integrate data from multiple sources, providing a comprehensive view of complex systems. These platforms use machine learning to analyze data, uncover patterns, and predict outcomes, assisting in strategic decision-making. This solution enables users to make informed decisions in real-time, based on a holistic understanding of their data.

• Enhanced decision-making capabilities in complex environments.
• Greater insights and efficiency in data analysis across sectors.
• Effective data integration is crucial for comprehensive analysis.
• AI-driven insights are essential for strategic decision-making.

Related: Surprising AI Facts & Statistics

17. Blue River Technology: Sowing the Seeds of AI in Agriculture

Task/Conflict: The agriculture industry faces challenges in increasing efficiency and sustainability while minimizing environmental impact. Blue River Technology aimed to enhance agricultural practices by using AI to make farming more precise and efficient.

Solution: Blue River Technology developed AI-driven agricultural robots that perform tasks like precise planting and weed control. These robots use ML to identify plants and make real-time decisions, such as applying herbicides only to weeds. This targeted approach reduces chemical usage and promotes sustainable farming practices, leading to better crop yields and environmental conservation.

• Significant reduction in chemical usage in farming.
• Increased crop yields through precision agriculture.
• AI can contribute significantly to sustainable agricultural practices.
• Precision farming is key to balancing productivity and environmental conservation.

18. Salesforce: Enhancing Customer Relationship Management with AI

Task/Conflict: In the realm of customer relationship management (CRM), personalizing interactions and gaining insights into customer behavior are crucial for business success. Salesforce aimed to enhance CRM capabilities by integrating AI to provide personalized customer experiences and actionable insights.

Solution: Salesforce incorporates AI-powered tools into its CRM platform, enabling businesses to personalize customer interactions, automate responses, and predict customer needs. These tools analyze customer data, providing insights that help businesses tailor their strategies and communications. The AI integration not only improves customer engagement but also streamlines sales and marketing efforts.

• Improved customer engagement and satisfaction.
• Increased business growth through tailored marketing and sales strategies.
• AI-driven personalization is key to successful customer relationship management.
• Leveraging AI for data insights can significantly impact business growth.

19. OpenAI: Transforming Natural Language Processing

Task/Conflict: OpenAI aimed to advance NLP by developing models capable of generating coherent and contextually relevant text, opening new possibilities in AI-human interaction.

Solution: OpenAI developed the Generative Pre-trained Transformer (GPT) models, which use deep learning to generate text that closely mimics human language. These models are trained on vast datasets, enabling them to understand context and generate responses in a conversational and coherent manner.

• Pioneered advancements in natural language understanding and generation.
• Expanded the possibilities for AI applications in communication.
• AI’s ability to mimic human language has vast potential applications.
• Advancements in NLP are crucial for improving AI-human interactions.

20. Siemens: Pioneering Industrial Automation with AI

Task/Conflict: Industrial automation seeks to improve productivity and efficiency in manufacturing processes. Siemens faced the challenge of optimizing these processes using AI to reduce downtime and enhance output quality.

Solution: Siemens employs AI-driven solutions for predictive maintenance and process optimization to reduce downtime in industrial settings. Additionally, AI optimizes manufacturing processes, ensuring quality and efficiency.

• Increased productivity and reduced downtime in industrial operations.
• Enhanced quality and efficiency in manufacturing processes.
• AI is a key driver in the advancement of industrial automation.
• Predictive analytics are crucial for maintaining efficiency in manufacturing.

Related: Top Books for Learning AI

21. Ford: Driving Safety Innovation with AI

Task/Conflict: Enhancing automotive safety and providing effective driver assistance systems are critical challenges in the auto industry. Ford aimed to leverage AI to improve vehicle safety features and assist drivers in real-time decision-making.

Solution: Ford integrated AI into its advanced driver assistance systems (ADAS) to provide features like adaptive cruise control, lane-keeping assistance, and collision avoidance. These systems use sensors and cameras to gather data, which AI processes to make split-second decisions that enhance driver safety and vehicle performance.

• Improved safety features in vehicles, minimizing accidents and improving driver confidence.
• Enhanced driving experience with intelligent assistance features.
• AI can highly enhance safety in the automotive industry.
• Real-time data processing and decision-making are essential for effective driver assistance systems.

22. HSBC: Enhancing Banking Security with AI

Task/Conflict: As financial transactions increasingly move online, banks face heightened risks of fraud and cybersecurity threats. HSBC needed to bolster its protective measures to secure user data and prevent scam.

Solution: HSBC employed AI-driven security systems to observe transactions and identify suspicious activities. The AI models analyze patterns in customer behavior and flag anomalies that could indicate fraudulent actions, allowing for immediate intervention. This helps in minimizing the risk of financial losses and protects customer trust.

• Strengthened security measures and reduced incidence of fraud.
• Maintained high levels of customer trust and satisfaction.
• AI is critical in enhancing security in the banking sector.
• Proactive fraud detection can prevent significant financial losses.

23. Unilever: Optimizing Supply Chain with AI

Task/Conflict: Managing a global supply chain involves complexities related to logistics, demand forecasting, and sustainability practices. Unilever sought to enhance its supply chain efficiency while promoting sustainability.

Solution: Unilever implemented AI to optimize its supply chain operations, from raw material sourcing to distribution. AI algorithms analyze data to forecast demand, improve inventory levels, and minimize waste. Additionally, AI helps in selecting sustainable practices and suppliers, aligning with Unilever’s commitment to environmental responsibility.

• Enhanced efficiency and reduced costs in supply chain operations.
• Better sustainability practices, reducing environmental impact.
• AI can highly optimize supply chain management.
• Integrating AI with sustainability initiatives can lead to environmentally responsible operations.

24. Spotify: Personalizing Music Experience with AI

Task/Conflict: In the competitive music streaming industry, providing a personalized listening experience is crucial for user engagement and retention. Spotify needed to tailor music recommendations to individual tastes and preferences.

Solution: Spotify utilizes AI-driven algorithms to analyze user listening habits, preferences, and contextual data to recommend music tracks and playlists. This personalization ensures that users are continually engaged and discover new music that aligns with their tastes, enhancing their overall listening experience.

• Increased customer engagement and time spent on the platform.
• Higher user satisfaction and subscription retention rates.
• Personalized content delivery is key to user retention in digital entertainment.
• AI-driven recommendations significantly enhance user experience.

Related: How can AI be used in Instagram Marketing?

25. Walmart: Revolutionizing Retail with AI

Task/Conflict: Retail giants like Walmart face challenges in inventory management and providing a high-quality customer service experience. Walmart aimed to use AI to optimize these areas and enhance overall operational efficacy.

Solution: Walmart deployed AI technologies across its stores to manage inventory levels effectively and enhance customer service. AI systems predict product demand to optimize stock levels, while AI-driven robots assist in inventory management and customer service, such as guiding customers in stores and handling queries.

• Improved inventory management, reducing overstock and shortages.
• Enhanced customer service experience in stores.
• AI can streamline retail operations significantly.
• Enhanced customer service through AI leads to better customer satisfaction.

26. Roche: Innovating Drug Discovery with AI

Task/Conflict: The pharmaceutical industry faces significant challenges in drug discovery, requiring vast investments of time and resources. Roche aimed to utilize AI to streamline the drug development process and enhance the discovery of new therapeutics.

Solution: Roche implemented AI to analyze medical data and simulate drug interactions, speeding up the drug discovery process. AI models predict the effectiveness of compounds and identify potential candidates for further testing, significantly minimizing the time and cost related with traditional drug development procedures.

• Accelerated drug discovery processes, bringing new treatments to market faster.
• Reduced costs and increased efficiency in pharmaceutical research.
• AI can greatly accelerate the drug discovery process.
• Cost-effective and efficient drug development is possible with AI integration.

27. IKEA: Enhancing Customer Experience with AI

Task/Conflict: In the competitive home furnishings market, enhancing the customer shopping experience is crucial for success. IKEA aimed to use AI to provide innovative design tools and improve customer interaction.

Solution: IKEA introduced AI-powered tools such as virtual reality apps that allow consumers to visualize furniture before buying. These tools help customers make more informed decisions and enhance their shopping experience. Additionally, AI chatbots assist with customer service inquiries, providing timely and effective support.

• Improved customer decision-making and satisfaction with interactive tools.
• Enhanced efficiency in customer service.
• AI can transform the retail experience by providing innovative customer interaction tools.
• Effective customer support through AI can enhance brand loyalty and satisfaction.

28. General Electric: Optimizing Energy Production with AI

Task/Conflict: Managing energy production efficiently while predicting and mitigating potential issues is crucial for energy companies. General Electric (GE) aimed to improve the efficiency and reliability of its energy production facilities using AI.

Solution: GE integrated AI into its energy management systems to enhance power generation and distribution. AI algorithms predict maintenance needs and optimize energy production, ensuring efficient operation and reducing downtime. This predictive maintenance approach saves costs and enhances the reliability of energy production.

• Increased efficiency in energy production and distribution.
• Reduced operational costs and enhanced system reliability.
• Predictive maintenance is crucial for cost-effective and efficient energy management.
• AI can significantly improve the predictability and efficiency of energy production.

Related: Use of AI in Sales

29. L’Oréal: Transforming Beauty with AI

Task/Conflict: Personalization in the beauty industry enhances customer satisfaction and brand loyalty. L’Oréal aimed to personalize beauty products and experiences for its diverse customer base using AI.

Solution: L’Oréal leverages AI to assess consumer data and provide personalized product suggestions. AI-driven tools assess skin types and preferences to recommend the best skincare and makeup products. Additionally, virtual try-on apps powered by AI allow customers to see how products would look before making a purchase.

• Enhanced personalization of beauty products and experiences.
• Increased customer engagement and satisfaction.
• AI can provide highly personalized experiences in the beauty industry.
• Data-driven personalization enhances customer satisfaction and brand loyalty.

30. The Weather Company: AI-Predicting Weather Patterns

Task/Conflict: Accurate weather prediction is vital for planning and safety in various sectors. The Weather Company aimed to enhance the accuracy of weather forecasts and provide timely weather-related information using AI.

Solution: The Weather Company employs AI to analyze data from weather sensors, satellites, and historical weather patterns. AI models improve the accuracy of weather predictions by identifying trends and anomalies. These enhanced forecasts help in better planning and preparedness for weather events, benefiting industries like agriculture, transportation, and public safety.

• Improved accuracy in weather forecasting.
• Better preparedness and planning for adverse weather conditions.
• AI can enhance the precision of meteorological predictions.
• Accurate weather forecasting is crucial for safety and operational planning in multiple sectors.

31. Cisco: Securing Networks with AI

Task/Conflict: As cyber threats evolve and become more sophisticated, maintaining robust network security is crucial for businesses. Cisco aimed to leverage AI to enhance its cybersecurity measures, detecting and responding to threats more efficiently.

Solution: Cisco integrated AI into its cybersecurity framework to analyze network traffic and identify unusual patterns indicative of cyber threats. This AI-driven approach allows for real-time threat detection and automated responses, thus improving the speed and efficacy of security measures.

• Strengthened network security with faster threat detection.
• Reduced manual intervention by automating threat responses.
• AI is essential in modern cybersecurity for real-time threat detection.
• Automating responses can significantly enhance network security protocols.

32. Adidas: AI in Sports Apparel Manufacturing

Task/Conflict: To maintain competitive advantage in the fast-paced sports apparel market, Adidas sought to innovate its manufacturing processes by incorporating AI to improve efficiency and product quality.

Solution: Adidas employed AI-driven robotics and automation technologies in its factories to streamline the production process. These AI systems optimize manufacturing workflows, enhance quality control, and reduce waste by precisely cutting fabrics and assembling materials according to exact specifications.

• Increased production efficacy and reduced waste.
• Enhanced consistency and quality of sports apparel.
• AI-driven automation can revolutionize manufacturing processes.
• Precision and efficiency in production lead to higher product quality and sustainability.

Related: How can AI be used in Disaster Management?

33. KLM Royal Dutch Airlines: AI-Enhanced Customer Service

Task/Conflict: Enhancing the customer service experience in the airline industry is crucial for customer satisfaction and loyalty. KLM aimed to provide immediate and effective assistance to its customers by integrating AI into their service channels.

Solution: KLM introduced an AI-powered chatbot, which provides 24/7 customer service across multiple languages. The chatbot handles inquiries about flight statuses, bookings, and baggage policies, offering quick and accurate responses. This AI solution helps manage customer interactions efficiently, especially during high-volume periods.

• Improved customer service efficiency and responsiveness.
• Increased customer satisfaction through accessible and timely support.
• AI chatbots can highly improve user service in high-demand industries.
• Effective communication through AI leads to better customer engagement and loyalty.

34. Novartis: AI in Drug Formulation

Task/Conflict: The pharmaceutical industry requires rapid development and formulation of new drugs to address emerging health challenges. Novartis aimed to use AI to expedite the drug formulation process, making it faster and more efficient.

Solution: Novartis applied AI to simulate and predict how different formulations might behave, speeding up the lab testing phase. AI algorithms analyze vast amounts of data to predict the stability and efficacy of drug formulations, allowing researchers to focus on the most promising candidates.

• Accelerated drug formulation and reduced time to market.
• Improved efficacy and stability of pharmaceutical products.
• AI can significantly shorten the drug development lifecycle.
• Predictive analytics in pharmaceutical research can lead to more effective treatments.

35. Shell: Optimizing Energy Resources with AI

Task/Conflict: In the energy sector, optimizing exploration and production processes for efficiency and sustainability is crucial. Shell sought to harness AI to enhance its oil and gas operations, making them more efficient and less environmentally impactful.

Solution: Shell implemented AI to analyze geological data and predict drilling outcomes, optimizing resource extraction. AI algorithms also adjust production processes in real time, improving operational proficiency and minimizing waste.

• Improved efficiency and sustainability in energy production.
• Reduced environmental impact through optimized resource management.
• Automation can enhance the effectiveness and sustainability of energy production.
• Real-time data analysis is crucial for optimizing exploration and production.

36. Procter & Gamble: AI in Consumer Goods Production

Task/Conflict: Maintaining operational efficiency and innovating product development are key challenges in the consumer goods industry. Procter & Gamble (P&G) aimed to integrate AI into their operations to enhance these aspects.

Solution: P&G employs AI to optimize its manufacturing processes and predict market trends for product development. AI-driven data analysis helps in managing supply chains and production lines efficiently, while AI in market research informs new product development, aligning with consumer needs.

• Enhanced operational efficacy and minimized production charges.
• Improved product innovation based on consumer data analysis.
• AI is crucial for optimizing manufacturing and supply chain processes.
• Data-driven product development leads to more successful market introductions.

Related: Use of AI in the Navy

37. Disney: Creating Magical Experiences with AI

Task/Conflict: Enhancing visitor experiences in theme parks and resorts is a priority for Disney. They aimed to use AI to create personalized and magical experiences for guests, improving satisfaction and engagement.

Solution: Disney utilizes AI to manage park operations, personalize guest interactions, and enhance entertainment offerings. AI algorithms predict visitor traffic and optimize attractions and staff deployment. Personalized recommendations for rides, shows, and dining options enhance the guest experience by leveraging data from past visits and preferences.

• Enhanced guest satisfaction through personalized experiences.
• Improved operational efficiency in park management.
• AI can transform the entertainment and hospitality businesses by personalizing consumer experiences.
• Efficient management of operations using AI leads to improved customer satisfaction.

38. BMW: Reinventing Mobility with Autonomous Driving

Task/Conflict: The future of mobility heavily relies on the development of safe and efficient autonomous driving technologies. BMW aimed to dominate in this field by incorporating AI into their vehicles.

Solution: BMW is advancing its autonomous driving capabilities through AI, using sophisticated machine learning models to process data from vehicle sensors and external environments. This technology enables vehicles to make intelligent driving decisions, improving safety and passenger experiences.

• Pioneering advancements in autonomous vehicle technology.
• Enhanced safety and user experience in mobility.
• AI is crucial for the development of autonomous driving technologies.
• Safety and reliability are paramount in developing AI-driven vehicles.

39. Mastercard: Innovating Payment Solutions with AI

Task/Conflict: In the digital age, securing online transactions and enhancing payment processing efficiency are critical challenges. Mastercard aimed to leverage AI to address these issues, ensuring secure and seamless payment experiences for users.

Solution: Mastercard integrates AI to monitor transactions in real time, detect fraudulent activities, and enhance the efficiency of payment processing. AI algorithms analyze spending patterns and flag anomalies, while also optimizing authorization processes to reduce false declines and improve user satisfaction.

• Strengthened security and reduced fraud in transactions.
• Improved efficiency and user experience in payment processing.
• AI is necessary for securing and streamlining expense systems.
• Enhanced transaction processing efficiency leads to higher customer satisfaction.

40. AstraZeneca: Revolutionizing Oncology with AI

Task/Conflict: Advancing cancer research and developing effective treatments is a pressing challenge in healthcare. AstraZeneca aimed to utilize AI to revolutionize oncology research, enhancing the development and personalization of cancer treatments.

Solution: AstraZeneca employs AI to analyze genetic data and clinical trial results, identifying potential treatment pathways and personalizing therapies based on individual genetic profiles. This approach accelerates the development of targeted treatments and improves the efficacy of cancer therapies.

• Accelerated innovation and personalized treatment in oncology.
• Better survival chances for cancer patients.
• AI can significantly advance personalized medicine in oncology.
• Data-driven approaches in healthcare lead to better treatment outcomes and innovations.

Related: How can AI be used in Tennis?

Closing Thoughts

These 40 case studies illustrate the transformative power of AI across various industries. By addressing specific challenges and leveraging AI solutions, companies have achieved remarkable outcomes, from enhancing customer experiences to solving complex scientific problems. The key learnings from these cases underscore AI’s potential to revolutionize industries, improve efficiencies, and open up new possibilities for innovation and growth.

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Case study on adoption of new technology for innovation: Perspective of institutional and corporate entrepreneurship

Asia Pacific Journal of Innovation and Entrepreneurship

ISSN : 2398-7812

Article publication date: 7 August 2017

This paper aims at investigating the role of institutional entrepreneurship and corporate entrepreneurship to cope with firm’ impasses by adoption of the new technology ahead of other firms. Also, this paper elucidates the importance of own specific institutional and corporate entrepreneurship created from firm’s norm.

Design/methodology/approach

The utilized research frame is as follows: first, perspective of studies on institutional and corporate entrepreneurship are performed using prior literature and preliminary references; second, analytical research frame was proposed; finally, phase-based cases are conducted so as to identify research objective.

Kumho Tire was the first tire manufacturer in the world to exploit the utilization of radio-frequency identification for passenger carâ’s tire. Kumho Tire takes great satisfaction in lots of failures to develop the cutting edge technology using advanced information and communication technology cultivated by heterogeneous institution and corporate entrepreneurship.

Originality/value

The firm concentrated its resources into building the organization’s communication process and enhancing the quality of its human resources from the early stages of their birth so as to create distinguishable corporate entrepreneurship.

• Corporate entrepreneurship
• Institutional entrepreneurship

Han, J. and Park, C.-m. (2017), "Case study on adoption of new technology for innovation: Perspective of institutional and corporate entrepreneurship", Asia Pacific Journal of Innovation and Entrepreneurship , Vol. 11 No. 2, pp. 144-158. https://doi.org/10.1108/APJIE-08-2017-031

Emerald Publishing Limited

Copyright © 2017, Junghee Han and Chang-min Park.

Published in the Asia Pacific Journal of Innovation and Entrepreneurship . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licenses/by/4.0/legalcode

1. Introduction

Without the entrepreneur, invention and new knowledge possibly have lain dormant in the memory of persons or in the pages of literature. There is a Korean saying, “Even if the beads are too much, they become treasure after sewn”. This implies importance of entrepreneurship. In general, innovativeness and risk-taking are associated with entrepreneurial activity and, more importantly, are considered to be important attributes that impact the implementation of new knowledge pursuing.

Implementation of cutting edge technology ahead of other firms is an important mechanism for firms to achieve competitive advantage ( Capon et al. , 1990 ; D’Aveni, 1994 ). Certainly, new product innovation continues to play a vital role in competitive business environment and is considered to be a key driver of firm performance, especially as a significant form of corporate entrepreneurship ( Srivastava and Lee, 2005 ). Corporate entrepreneurship is critical success factor for a firm’s survival, profitability and growth ( Phan et al. , 2009 ).

The first-mover has identified innovativeness and risk-taking as important attributes of first movers. Lumpkin and Dess (1996) argued that proactiveness is a key entrepreneurial characteristic related to new technology adoption and product. This study aims to investigate the importance of corporate and institutional entrepreneurship through analyzing the K Tire’s first adaptation of Radio-frequency identification (RFID) among the world tire manufactures. Also, this paper can contribute to start ups’ readiness for cultivating of corporate and institutional entrepreneurship from initial stage to grow and survive.

K Tire is the Korean company that, for the first time in the world, applied RFID to manufacturing passenger vehicle tires in 2013. Through such efforts, the company has built an innovation model that utilizes ICTs. The adoption of the technology distinguishes K Tire from other competitors, which usually rely on bar codes. None of the global tire manufacturers have applied the RFID technology to passenger vehicle tires. K Tire’s decision to apply RFID to passenger vehicle tires for the first time in the global tire industry, despite the uncertainties associated with the adoption of innovative technologies, is being lauded as a successful case of innovation. In the global tire market, K Tire belongs to the second tier, rather than the leader group consisting of manufacturers with large market shares. Then, what led K Tire to apply RFID technology to the innovation of its manufacturing process? A company that adopts innovative technologies ahead of others, even if the company is a latecomer, demonstrates its distinguishing characteristics in terms of innovation. As such, this study was motivated by the following questions. With regard to the factors that facilitate innovation, first, what kind of the corporate and institutional situations that make a company more pursue innovation? Second, what are the technological situations? Third, how do the environmental situations affect innovation? A case study offers the benefit of a closer insight into the entrepreneurship frame of a specific company. This study has its frame work rooted in corporate entrepreneurship ( Guth and Ginsberg, 1990 ; Shane and Venkataraman, 2000 ) and institutional entrepreneurship ( Battilana, 2006 ; Fligstein, 1997 ; Rojas, 2010 ). As mentioned, we utilized qualitative research method ( Yin, 2008 ). This paper is structured as follows. Section two presents the literature review, and section three present the methodology and a research case. Four and five presents discussion and conclusions and implications, respectively.

2. Theoretical review and analysis model

RFID technology is to be considered as not high technology; however, it is an entirely cutting edged skills when combined with automotive tire manufacturing. To examine why and how the firm behaves like the first movers, taking incomparable high risks to achieve aims unlike others, we review three kinds of prior literature. As firms move from stage to stage, they have to revamp innovative capabilities to survive and ceaseless stimulate growth.

2.1 Nature of corporate entrepreneurship

Before reviewing the corporate entrepreneurship, it is needed to understand what entrepreneurship is. To more understand the role that entrepreneurship plays in modern economy, one need refer to insights given by Schumpeter (1942) or Kirzner (1997) . Schumpeter suggests that entrepreneurship is an engine of economic growth by utilization of new technologies. He also insists potential for serving to discipline firms in their struggle to survive gale of creative destruction. While Schumper argued principle of entrepreneurship, Kirzner explains the importance of opportunities. The disruptions generated by creative destruction are exploited by individuals who are alert enough to exploit the opportunities that arise ( Kirzner, 1997 ; Shane and Venkataraman, 2000 ).

Commonly all these perspectives on entrepreneurship is an appreciation that the emergence of novelty is not an easy or predictable process. Based on literature review, we note that entrepreneurship is heterogeneous interests and seek “something new” associated with novel outcomes. Considering the literature review, we can observe that entrepreneurship is the belief in individual autonomy and discretion, and a mindset that locates agency in individuals for creating new activities ( Meyer et al. ,1994 ; Jepperson and Meyer, 2001 ).

the firm’s commitment to innovation (including creation and introduction of products, emphasis on R&D investments and commitment to patenting);

the firm’s venturing activities, such as entry into new business fields by sponsoring new ventures and creating new businesses; and

strategic renewal efforts aimed at revitalizing the firm’s ability to compete.

developing innovation an organizational tool;

allowing the employees to propose ideas; and

encouraging and nurturing the new knowledge ( Hisrich, 1986 ; Kuratko, 2007 ).

Consistent with the above stream of research, our paper focuses on a firm’s new adaptation of RFID as a significant form of corporate entrepreneurial activity. Thus, CE refers to the activities a firm undertakes to stimulate innovation and encourage calculated risk taking throughout its operations. Considering prior literature reviews, we propose that corporate entrepreneurship is the process by which individuals inside the organization pursuing opportunities without regards to the resources they control.

If a firm has corporate entrepreneurship, innovation (i.e. transformation of the existing firm, the birth of new business organization and innovation) happens. In sum, corporate entrepreneurship plays a role to pursue to be a first mover from a latecomer by encompassing the three phenomena.

2.2 Institution and institutional entrepreneurship

Most literature regarding entrepreneurship deals with the attribute of individual behavior. More recently, scholars have attended to the wider ecosystem that serves to reinforce risk-taking behavior. Institution and institutional entrepreneurship is one way to look at ecosystem that how individuals and groups attempt to try to become entrepreneurial activities and innovation.

Each organization has original norm and intangible rules. According to the suggestion by Scott (1995) , institutions constrain behavior as a result of processes associated with institutional pillars. The question how actors within the organizations become motivated and enabled to transform the taken-for-granted structures has attracted substantial attention for institutionalist. To understand why some firms are more likely to seek innovation activities despite numerous difficulties and obstacles, we should take look at the institutional entrepreneurship.

the regulative, which induces worker’s action through coercion and formal sanction;

the normative, which induces worker’s action through norms of acceptability and ethics; and

the cognitive, which induces worker’s action through categories and frames by which actors know and interpret their world.

North (1990) defines institutions as the humanly devised constraints that structure human action. Actors within some organization with sufficient resources have intend to look at them an opportunity to realize interests that they value highly ( DiMaggio, 1988 ).

It opened institutional arguments to ideas from the co-evolving entrepreneurship literature ( Aldrich and Fiol, 1994 ; Aldrich and Martinez, 2001 ). The core argument of the institutional entrepreneurship is mechanisms enabling force to motivate for actors to act difficult task based on norm, culture and shared value. The innovation, adopting RFID, a technology not verified in terms of its effectiveness for tires, can be influenced by the institution of the society.

A firm is the organizations. An organization is situated within an institution that has social and economic norms. Opportunity is important for entrepreneurship. The concept of institutional entrepreneurship refer to the activities of worker or actor who have new opportunity to realize interest that they values highly ( DiMaggio, 1988 ). DiMaggio (1988) argues that opportunity for institutional entrepreneurship will be “seen” and “exploited” by within workers and not others depending on their resources and interests respectively.

Despite that ambiguity for success was given, opportunity and motivation for entrepreneurs to act strategically, shape emerging institutional arrangements or standards to their interests ( Fligstein and Mara-Drita, 1996 ; Garud et al. , 2002 ; Hargadon and Douglas, 2001 ; Maguire et al. , 2004 ).

Resource related to opportunity within institutional entrepreneurship include formal or informal authority and power ( Battilana, 2006 ; Rojas, 2010 ). Maguire et al. (2004) suggest legitimacy as an important ingredient related to opportunity for institutional entrepreneurship. Some scholars suggest opportunity resources for institutional entrepreneurship as various aspects. For instance, Marquire and Hardy (2009) show that knowledge and expertise is more crucial resources. Social capital, including market leadership and social network, is importance resource related to opportunity ( Garud et al. , 2002 ; Lawrence et al. , 2005 ; Townley, 2002 ). From a sociological perspective, change associated with entrepreneurship implies deviations from some norm ( Garud and Karnøe, 2003 ).

Institutional entrepreneurship is therefore a concept that reintroduces agency, interests and power into institutional analyses of organizations. Based on the previous discussion, this study defines institution as three processes of network activity; coercion and formal sanction, normative and cognitive, to acquire the external knowledge from adopting common goals and rules inside an organization. It would be an interesting approach to look into a specific company to see whether it is proactive towards adopting ICTs (e.g. RFID) and innovation on the basis of such theoretical background.

2.3. Theoretical analysis frame

Companies innovate themselves in response to the challenges of the ever-changing markets and technologies, so as to ensure their survival and growth ( Tushman and Anderson, 1986 ; Tidd and Bessant, 2009 ; Teece, 2014 ). As illustrated above, to achieve the purpose of this study, the researcher provides the following frames of analyses based on the theoretical background discussed above ( Figure 1 ).

3. Case study

3.1 methodology.

It is a highly complicated and tough task to analyze the long process of innovation at a company. In this paper, we used analytical approach rather than the problem-oriented method because the case is examined to find and understand what has happened and why. It is not necessary to identify problems or suggest solutions. Namely, this paper analyzes that “why K Tire becomes a first mover from a late comer through first adoption of RFID technology for automotive tire manufacture with regards to process and production innovations”.

To study the organizational characteristics such as corporate entrepreneurship, institutional entrepreneurship, innovation process of companies, the qualitative case study is the suitable method. This is because a case study is a useful method when verifying or expanding well-known theories or challenging a specific theory ( Yin, 2008 ). This study seeks to state the frame of analysis established, based on previously established theories through a single case. K Tire was selected as the sample because it is the first global tire manufacturer, first mover to achieve innovation by developing and applying RFID.

The data for the case study were collected as follows. First, this study was conducted from April 2015 to the end of December 2015. Additional expanded data also were collected from September 12 to November 22, 2016, to pursue the goal of this paper. Coauthor worked for K Tire for more than 30 year, and currently serves as the CEO of an affiliate company. As such, we had the most hands-on knowledge and directed data in the process of adoption RFID. This makes this case study a form of participant observation ( Yin, 2008 ). To secure data on institutional entrepreneurship, in-depth interviews were conducted with the vice president of K Tire. The required data were secured using e-mail, and the researchers accepted the interviewees’ demand to keep certain sensitive matters confidential. The interviewees agreed to record the interview sessions. In this way, a 20-min interview data were secured for each interviewee. In addition, apart from the internal data of the subject company, other objective data were obtained by investigating various literatures published through the press.

3.2 Company overview

In September 1960, K Tire was established in South Korea as the name of Samyang Tire. In that time, the domestic automobile industry in Korea was at a primitive stage, as were auto motive parts industries like the tire industry. K Tire products 20 tires a day, depending on manual labor because of our backward technology and shortage of facilities.

The growth of K Tire was astonishment. Despite the 1974 oil shock and difficulties in procuring raw materials, K Tire managed to achieve remarkable growth. In 1976, K Tire became the leader in the tire sector and was listed on the Korea Stock Exchange. Songjung plant II was added in 1977. Receiving the grand prize of the Korea Quality Control Award in 1979, K Tire sharpened its corporate image with the public. The turmoil of political instability and feverish democratization in the 1980s worsened the business environment. K Tire also underwent labor-management struggles but succeeded in straightening out one issue after another. In the meantime, the company chalked up a total output of 50 million tires, broke ground for its Koksung plant and completed its proving ground in preparation for a new takeoff.

In the 1990s, K Tire expanded its research capability and founded technical research centers in the USA and the United Kingdom to establish a global R&D network. It also concentrated its capabilities in securing the foundation as a global brand, by building world-class R&D capabilities and production systems. Even in the 2000s, the company maintained its growth as a global company through continued R&D efforts by securing its production and quality capabilities, supplying tires for new models to Mercedes, Benz, Volkswagen and other global auto manufacturers.

3.3 Implementation of radio-frequency identification technology

RFID is radio-frequency identification technology to recognize stored information by using a magnetic carrier wave. RFID tags can be either passive, active or battery-assisted passive (BAP). An active tag has an on-board battery and periodically transmits its ID signal. A BAP has a small battery on board and is activated when in the presence of an RFID reader. A passive tag is cheaper and smaller because it has no battery; instead, the tag uses the radio energy transmitted by the reader. However, to operate a passive tag, it must be illuminated with a power level roughly a thousand times stronger than for signal transmission. That makes a difference in interference and in exposure to radiation.

an integrated circuit for storing and processing information, modulating and demodulating a radio frequency signal, collecting DC power from the incident reader signal, and other specialized functions; and

an antenna for receiving and transmitting the signal.

capable of recognizing information without contact;

capable of recognizing information regardless of the direction;

capable of reading and saving a large amount of data;

requires less time to recognize information;

can be designed or manufactured in accordance with the system or environmental requirements;

capable of recognizing data unaffected by contamination or the environment;

not easily damaged and cheaper to maintain, compared with the bar code system; and

tags are reusable.

3.3.1 Phase 1. Background of exploitation of radio-frequency identification (2005-2010).

Despite rapid growth of K Tire since 1960, K Tire ranked at the 13th place in the global market (around 2 per cent of the global market share) as of 2012. To enlarge global market share is desperate homework. K Tire was indispensable to develop the discriminated technologies. When bar code system commonly used by the competitors, and the industry leaders, K Tire had a decision for adoption of RFID technology instead of bar code system for tires as a first mover strategy instead of a late comer with regard to manufacture tires for personal vehicle. In fact, K Tire met two kinds of hardship. Among the top 20, the second-tier companies with market shares of 1-2 per cent are immersed in fiercer competitions to advance their ranks. The fierceness of the competition is reflected in the fact that of the companies ranked between the 11th and 20th place, only two maintained their rank from 2013.

With the demand for stricter product quality control and manufacture history tracking expanding among the auto manufacturers, tire manufacturers have come to face the need to change their way of production and logistics management. Furthermore, a tire manufacturer cannot survive if it does not properly respond to the ever stricter and exacting demand for safe passenger vehicle tires of higher quality from customers and auto manufacturers. As mentioned above, K Tire became one of the top 10 companies in the global markets, recording fast growth until the early 2000. During this period, K Tire drew the attention of the global markets with a series of new technologies and innovative technologies through active R&D efforts. Of those new products, innovative products – such as ultra-high-performance tires – led the global markets and spurred the company’s growth. However, into the 2010s, the propriety of the UHP tire technology was gradually lost, and the effect of the innovation grew weaker as the global leading companies stepped forward to take the reign in the markets. Subsequently, K Tire suffered from difficulties across its businesses, owing to the failure to develop follow-up innovative products or market-leading products, as well as the aggressive activities by the company’s hardline labor union. Such difficulties pushed K Tire down to the 13th position in 2014, which sparked the dire need to bring about innovative changes within the company.

3.3.2 Phase 2. Ceaseless endeavor and its failure (2011-2012).

It needs to be lightweight : An RFID tag attached inside a vehicle may adversely affect the weight balance of the tires. A heavier tag has greater adverse impact on the tire performance. Therefore, a tag needs to be as light as possible.

It needs to be durable : Passenger vehicle tires are exposed to extensive bending and stretching, as well as high levels of momentum, which may damage a tag, particularly causing damage to or even loss of the antenna section.

It needs to maintain adhesiveness : Tags are attached on the inner surface, which increase the possibility of the tags falling off from the surface while the vehicle is in motion.

It needs to be resistant to high temperature and high pressure : While going through the tire manufacture process, a tag is exposed to a high temperature of around 200°C and high pressure of around 30 bars. Therefore, a tag should maintain its physical integrity and function at such high pressure and temperature.

It needs to be less costly : A passenger vehicle tire is smaller, and therefore cheaper than truck/bus tires. As a result, an RFID tag places are greater burden on the production cost.

Uncountable tag prototypes, were applied to around 200 test tires in South Korea for actual driving tests. Around 150 prototypes were sent to extremely hot regions overseas for actual driving tests. However, the driving tests revealed damage to the antenna sections of the tags embedded in tires, as the tires reached the end of their wear life. Also, there was separation of the embedded tags from the rubber layers. This confirmed the risk of tire separation, resulting in the failure of the tag development attempt.

3.3.3 Phase 3. Success of adoption RFID (2013-2014).

Despite the numerous difficulties and failures in the course of development, the company ultimately emerged successful, owing to its institutional entrepreneurship and corporate entrepreneurship the government’s support. Owing to the government-led support project, K Tire resumed its RFID development efforts in 2011. This time, the company discarded the idea of the embedded-type tag, which was attempted during the first development. Instead, the company turned to attached-type tag. The initial stages were marked with numerous failures: the size of a tag was large at 20 × 70 mm, which had adverse impact on the rotation balance of the tires, and the attached area was too large, causing the attached sections to fall off as the tire stretched and bent. That was when all personnel from the technical, manufacturing, and logistics department participated in creating ideas to resolve the tag size and adhesiveness issues. Through cooperation across the different departments and repeated tests, K Tire successfully developed its RFID tag by coming up with new methods to minimize the tag size to its current size (9 × 45 mm), maintain adhesiveness and lower the tag price. Finally, K Tire was success the adoption RFID.

3.3.4 Phase 4. Establishment of the manufacture, logistics and marketing tracking system.

Whenever subtle and problematic innovation difficulties arise, every worker and board member moves forward through networking and knowledge sharing within intra and external.

While a bar code is only capable of storing the information on the nationality, manufacturer and category of a product, an RFID tag is capable of storing a far wider scope of information: nationality, manufacturer, category, manufacturing date, machines used, lot number, size, color, quantity, date and place of delivery and recipient. In addition, while the data stored in a bar code cannot be revised or expanded once the code is generated, an RFID tag allows for revisions, additions and removal of data. As for the recognition capability, a bar code recognizes 95per cent of the data at the maximum temperature of 70°C. An RFID tag, on the other hand, recognizes 99.9 per cent of the data at 120°C.

The manufacture and transportation information during the semi-finished product process before the shaping process is stored in the RFID tags, which is attached to the delivery equipment to be provided to the MLMTS;

Logistics Products released from the manufacture process are stored in the warehouses, to be released and transported again to logistics centers inside and outside of South Korea. The RFID tags record the warehousing information, as the products are stored into the warehouses, as well as the release information as the products are released. The information is instantly delivered to the MLMTS;

As a marketing, the RFID tags record the warehousing information of the products supplied and received by sales branches from the logistics centers, as well as the sales information of the products sold to consumers. The information is instantly delivered to the MLMTS; and

As a role of integrative Server, MLM Integrative Server manages the overall information transmitted from the infrastructures for each section (production information, inventory status and release information, product position and inventory information, consumer sales information, etc.).

The MLMTS provides the company with various systemic functions to integrate and manage such information: foolproof against manufacture process errors, manufacture history and quality tracking for each individual product, warehousing/releasing and inventory status control for each process, product position control between processes, real-time warehouse monitoring, release control and history information tracking across products of different sizes, as well as link/control of sales and customer information. To consumers, the system provides convenience services by providing production and quality information of the products, provision of the product history through full tracking in the case of a claim, as well as a tire pressure monitoring system:

“South korea’s K Tire Co. Inc. has begun applying radio-frequency identification (RFID) system tags on: half-finished” tire since June 16. We are now using an IoT based production and distribution integrated management system to apply RFID system on our “half-finished products” the tire maker said, claiming this is a world-first in the industry. The technology will enable K Tire to manage products more efficiently than its competitors, according to the company. RFID allows access to information about a product’s location, storage and release history, as well as its inventory management (London, 22, 2015 Tire Business).

4. Discussions

Originally, aims of RFID adoption for passenger car “half-finished product” is to chase the front runners, Hankook Tire in Korea including global leading companies like Bridgestone, Michaelin and Goodyear. In particular, Hankook Tire, established in 1941 has dominated domestic passenger tire market by using the first mover’s advantage. As a late comer, K Tire needs distinguishable innovation strategy which is RFID adoption for passenger car’s tire, “half-finished product” to overcome shortage of number of distribution channels. Adoption of RFID technology for passenger car’s tire has been known as infeasible methodologies according to explanation by Changmin Park, vice-CTO (chief technology officer) until K Tire’s success.

We lensed success factors as three perspectives; institutional entrepreneurship, corporate entrepreneurship and innovation. First, as a corporate entrepreneurship perspective, adopting innovative technologies having uncertainties accompanies by a certain risk of failure. Corporate entrepreneurship refers to firm’s effort that inculcate and promote innovation and risk taking throughout its operations ( Burgelman, 1983 ; Guth and Ginsberg, 1990 ). K Tire’s success was made possible by overcome the uncountable difficulties based on shared value and norms (e.g. Fligstein and Mara-Drita, 1996 ; Garud et al. , 2002 ; Hargadon and Douglas, 2001 ; Maguire et al. , 2004 ).

An unsuccessful attempt at developing innovative technologies causes direct loss, as well as loss of the opportunity costs. This is why many companies try to avoid risks by adopting or following the leading companies’ technologies or the dominant technologies. Stimulating corporate entrepreneurship requires firms to acquire and use new knowledge to exploit emerging opportunities. This knowledge could be obtained by joining alliances, selectively hiring key personnel, changing the composition or decision-making processes of a company’s board of directors or investing in R&D activities. When the firm uses multiple sources of knowledge ( Branzei and Vertinsky, 2006 ; Thornhill, 2006 ), some of these sources may complement one another, while others may substitute each other ( Zahra and George, 2002 ). Boards also provide managers with appropriate incentives that better align their interests with those of the firm. Given the findings, K Tire seeks new knowledge from external organizations through its discriminative corporate entrepreneurship.

When adopting the RFID system for its passenger vehicle tires, K Tire also had to develop new RFID tags suitable for the specific type of tire. The company’s capabilities were limited by the surrounding conditions, which prevented the application of existing tire RFID tag technologies, such as certain issues with the tire manufacturing process, the characteristic of its tires and the price of RFID tags per tire. Taking risks and confronting challenges are made from board member’s accountability. From the findings, we find that entrepreneurship leadership can be encouraged in case of within the accountability frame work.

Despite its status as a second-tier company, K Tire attempted to adopt the RFID system to its passenger vehicle tires, a feat not achieved even by the leading companies. Thus, the company ultimately built and settled the system through numerous trials and errors. Such success was made possible by the entrepreneurship of K Tire’s management, who took the risk of failure inherent in adopting innovative technologies and confronting challenges head on.

Second, institutional entrepreneurship not only involves the “capacity to imagine alternative possibilities”, it also requires the ability “to contextualize past habits and future projects within the contingencies of the moment” if existing institutions are to be transformed ( Emirbayer and Mische, 1998 ). New technologies, the technical infrastructure, network activities to acquire the new knowledge, learning capabilities, creating a new organization such as Pioneer Lab and new rules to create new technologies are the features. To qualify as institutional entrepreneurs, individuals must break with existing rules and practices associated with the dominant institutional logic(s) and institutionalize the alternative rules, practices or logics they are championing ( Garud and Karnøe, 2003 ; Battilana, 2006 ). K Tire established new organization, “Special lab” to obtain the know technology and information as CEO’s direct sub-committees. Institutional entrepreneurship arise when actors, through their filed position, recognize the opportunity circumstance so called “norms” ( Battilana et al. , 2009 ). To make up the deficit of technologies for RFID, knowledge stream among workers is more needed. Destruction of hierarch ranking system is proxy of the institutional entrepreneurship. Also, K Tire has peculiar norms. Namely, if one requires the further study such as degree course or non-degree course education services, grant systems operated via short screen process. Third, as innovation perspectives, before adopting the RFID system, the majority of K Tire’s researchers insisted that the company use the bar code technology, which had been widely used by the competitors. Such decision was predicated on the prediction that RFID technology would see wider use in the future, as well as the expected effect coming from taking the leading position, with regard to the technology.

Finally, K Tire’s adoption of the RFID technology cannot be understood without government support. The South Korean government has been implementing the “Verification and Dissemination Project for New u-IT Technologies” since 2008. Owing to policy support, K Tire can provide worker with educational service including oversea universities.

5. Conclusions and implications

To cope with various technological impasses, K Tire demonstrated the importance of institutional and corporate entrepreneurship. What a firm pursues more positive act for innovation is a research question.

Unlike firms, K Tire has strongly emphasized IT technology since establishment in 1960. To be promotion, every worker should get certification of IT sectors after recruiting. This has become the firm’s norm. This norm was spontaneously embedded for firm’s culture. K Tire has sought new ICT technology become a first mover. This norm can galvanize to take risk to catch up the first movers in view of institutional entrepreneurship.

That can be cultivated both by corporate entrepreneurship, referred to the activities a firm undertakes to stimulate innovation and encourage calculated risk taking throughout its operations within accountabilities and institutional entrepreneurship, referred to create its own peculiar norm. Contribution of our paper shows both importance of board members of directors in cultivating corporate entrepreneurship and importance of norm and rules in inducing institutional entrepreneurship.

In conclusion, many of them were skeptical about adopting RFID for its passenger vehicle tires at a time when even the global market and technology leaders were not risking such innovation, citing reasons such as risk of failure and development costs. However, enthusiasm and entrepreneurship across the organization towards technical innovation was achieved through the experience of developing leading technologies, as well as the resolve of the company’s management and its institutional entrepreneurship, which resulted in the company’s decision to adopt the RFID technology for small tires, a technology with unverified effects that had not been widely used in the markets. Introduction of new organization which “Special lab” is compelling example of institutional entrepreneurship. Also, to pursue RFID technology, board members unanimously agree to make new organization in the middle of failing and unpredictable success. This decision was possible since K Tire’s cultivated norm which was to boost ICT technologies. In addition, at that time, board of director’s behavior can be explained by corporate entrepreneurship.

From the findings, this paper also suggests importance of firms’ visions or culture from startup stage because they can become a peculiar norm and become firm’s institutional entrepreneurship. In much contemporary research, professionals and experts are identified as key institutional entrepreneurs, who rely on their legitimated claim to authoritative knowledge or particular issue domains. This case study shows that authoritative knowledge by using their peculiar norm, and culture as well as corporate entrepreneurship.

This paper has some limitations. Despite the fact that paper shows various fruitful findings, this study is not free from that our findings are limited to a single exploratory case study. Overcoming such limitation requires securing more samples, including the group of companies that attempt unprecedented innovations across various industries. In this paper, we can’t release all findings through in-depth interview and face-to-face meetings because of promise for preventing the secret tissues.

Nevertheless, the contribution of this study lies in that it shows the importance of corporate entrepreneurship and institutional entrepreneurship for firm’s innovative capabilities to grow ceaselessly.

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Acknowledgements

 This work was supported by 2017 Hongik University Research Fund.

Corresponding author

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2. Prioritize partnerships over transactional relationships.

Founders must be mindful of every expense, but when partnering with a technology consulting firm, the least expensive option upfront can be a costly decision in the long run.

Seek firms genuinely interested in your business and willing to collaborate as partners rather than just vendors. Boutique firms will want your business for several reasons. They may want to feature your company’s logo on their website and use the network effect. They may believe your work will be an interesting case study for their team. They may also find cultural alignment with your company and feel the day-to-day collaboration would be meaningful and inspiring for both teams.

That typically makes boutique technology consulting firms great partners for starting enterprises; they can co-market your brand for free and help boost your overall PR and awareness. In order to maintain these relationships, I find that these partners are also usually more willing to jump in and help out when "fires" emerge, giving you access to a lifeline you can use as needed.

3. Negotiation is more than price.

If you want to negotiate hard on price, you should be more flexible in other areas, such as payment terms, providing a project advance or additional co-marketing rights. If you're looking at a longer-term partnership, consider prioritizing terms that are better for you in the long run and have a better impact—like sustained discounts or offering equity to allow the firm to invest in your outcomes.

Ensure your technology consultancy is giving you all of the IP related to your project, but also try to avoid paying them to recreate the basics. There should be some flexibility to leverage and reuse their processes, frameworks and tools so they aren't rebilling you for repetitive effort. You don't need to pay for that to be created from scratch every time, and you don't want to.

4. Expect the honeymoon to end.

After signing and starting a project strong, challenges will inevitably arise, especially when the risks and rewards are high. That’s true whether a project is in-house or uses an external partner. One way founders can mitigate this is by hosting a bi-weekly "showcase" where the team shares progress, highlights from completed work and feedback from the broader group. Creating space for both sides of the partnership to ask questions and correct course prevents either side from being caught by a surprise development or being out of sync.

You’ve hired smart people to help you, so you want them to say something if they see an issue—and vice versa. Both sides need to be able to share when they see problems on the horizon or advise on opportunities to get you to that deadline soon. I urge leaders to lean into establishing a safe and trusting environment as soon as possible so they can get the most out of their investment. Aligning goals and incentive structures can help both parties proactively deal with challenges in ways that further strengthen the partnership.

5. Think long term.

Beyond individual projects, startups should aim to cultivate a long-term relationship with their technology consultants. By nurturing these relationships, over time, startups can access a reliable network of expertise, referrals and support to fill in the gaps or validate the hiring needs of their business. With these strengthened relationships, partners are also more likely to prioritize you within their portfolio.

In my experience, access to this repository of professional expertise enables tech founders to use their capital to hit milestones ahead of schedule, find better revenue paths and keep teams and efforts running while they search for that perfect hire or invest in developing capacity and skills internally.

Every founder can’t be everything, so my recommendation is don’t waste time trying to. With the right mindset and due diligence, a technology consultant can be the best tool in your toolkit for quickly getting your board, investors and team the outcomes you’re looking for.

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In the tech world and beyond, new 5G applications are being discovered every day. From driverless cars to smarter cities, farms, and even shopping experiences, the latest standard in wireless networks is poised to transform the way we interact with information, devices and each other. What better time to take a closer look at how humans are putting 5G to use to transform their world.

What is 5G?

5G (fifth-generation mobile technology  is the newest standard for cellular networks. Like its predecessors, 3G, 4G and 4G LTE, 5G technology uses radio waves for data transmission. However, due to significant improvements in latency, throughput and bandwidth, 5G is capable of faster download and upload speeds than previous networks.

Since its release in 2019, 5G broadband technology has been hailed as a breakthrough technology with significant implications for both consumers and businesses. Primarily, this is due to its ability to handle large volumes of data that is generated by complex devices that use its networks.

As mobile technology has expanded over the years, the number of data users generate every day has increased exponentially. Currently, other transformational technologies like  artificial intelligence (AI),  the  Internet of Things (IoT ) and  machine learning (ML)  require faster speeds to function than 3G and 4G networks offer. Enter 5G, with its lightning-fast data transfer capabilities that allow newer technologies to function in the way they were designed to.

Here are some of the biggest differences between 5G and previous wireless networks.

• Physical footprint : The transmitters that are used in 5G technology are smaller than in predecessors’ networks, allowing for discrete placement in out-of-the-way places. Furthermore, “cells”—geographical areas that all wireless networks require for connectivity—in 5G networks are smaller and require less power to run than in previous generations.
• Error rates : 5G’s adaptive Modulation and Coding Scheme (MCS), a schematic that wifi devices use to transmit data, is more powerful than ones in 3G and 4G networks. This makes 5G’s Block Error Rate (BER)—a metric of error frequency—much lower. 
• Bandwidth : By using a broader spectrum of radio frequencies than previous wireless networks, 5G networks can transmit on a wider range of bandwidths. This increases the number of devices that they can support at any given time.
• Lower latency : 5G’s low  latency , a measurement of the time it takes data to travel from one location to another, is a significant upgrade over previous generations. This means that routine activities like downloading a file or working in the cloud is going to be faster with a 5G connection than a connection on a different network.

Like all wireless networks, 5G networks are separated into geographical areas that are known as cells. Within each cell, wireless devices—such as smartphones, PCs, and IoT devices—connect to the internet via radio waves that are transmitted between an antenna and a base station. The technology that underpins 5G is essentially the same as in 3G and 4G networks. But due to its lower latency, 5G networks are capable of delivering faster download speeds—in some cases as high as 10 gigabits per second (Gbps).

As more and more devices are built for 5G speeds, demand for 5G connectivity is growing. Today, many popular Internet Service Providers (ISPs), such as Verizon, Google and AT&T, offer 5G networks to homes and businesses. According to Statista,  more than 200 million homes  and businesses have already purchased it with that number expected to at least double by 2028 (link resides outside ibm.com).

Let’s take a look at three areas of technological improvement that have made 5G so unique.

New telecom specifications

The 5G NR (New Radio) standard for cellular networks defines a new radio access technology (RAT) specification for all 5G mobile networks. The 5G rollout began in 2018 with a global initiative known as the 3rd Generation Partnership Project (3FPP). The initiative defined a new set of standards to steer the design of devices and applications for use on 5G networks.

The initiative was a success, and 5G networks grew swiftly in the ensuing years. Today, 45% of networks worldwide are 5G compatible, with that number forecasted to rise to 85% by the end of the decade according to  a recent report by Ericsson  (link resides outside ibm.com).

Independent virtual networks (network slicing)

On 5G networks, network operators can offer multiple independent virtual networks (in addition to public ones) on the same infrastructure. Unlike previous wireless networks, this new capability allows users to do more things remotely with greater security than ever before. For example, on a 5G network, enterprises can create use cases or business models and assign them their own independent virtual network. This dramatically improves the user experience for their employees by adding greater customizability and security.

Private networks

In addition to network slicing, creating a 5G private network can also enhance personalization and security features over those available on previous generations of wireless networks. Global businesses seeking more control and mobility for their employees increasingly turn to private 5G network architectures rather than public networks they’ve used in the past.

Now that we better understand how 5G technology works, let’s take a closer look at some of the exciting applications it’s enabling.

Autonomous vehicles

From taxi cabs to drones and beyond, 5G technology underpins most of the next-generation capabilities in autonomous vehicles. Until the 5G cellular standard came along, fully autonomous vehicles were a bit of a pipe dream due to the data transmission limitations of 3G and 4G technology. Now, 5G’s lightning-fast connection speeds have made transport systems for cars, trains and more, faster than previous generations, transforming the way systems and devices connect, communicate and collaborate.

Smart factories

5G, along with AI and ML, is poised to help factories become not only smarter but more automated, efficient, and resilient. Today, many mundane but necessary tasks that are associated with equipment repair and optimization are being turned over to machines thanks to 5G connectivity paired with AI and ML capabilities. This is one area where 5G is expected to be highly disruptive, impacting everything from fuel economy to the design of equipment lifecycles and how goods arrive at our homes.

For example, on a busy factory floor, drones and cameras that are connected to smart devices that use the IoT can help locate and transport something more efficiently than in the past and prevent theft. Not only is this better for the environment and consumers, but it also frees up employees to dedicate their time and energy to tasks that are more suited to their skill sets.

Smart cities

The idea of a hyper-connected urban environment that uses 5G network speeds to spur innovation in areas like law enforcement, waste disposal and disaster mitigation is fast becoming a reality. Some cities already use 5G-enabled sensors to track traffic patterns in real time and adjust signals, helping guide the flow of traffic, minimize congestion, and improve air quality.

In another example, 5G power grids monitor supply and demand across heavily populated areas and deploy AI and ML applications to “learn” what times energy is in high or low demand. This process has been shown to significantly impact energy conservation and waste, potentially reducing carbon emissions and helping cities reach sustainability goals.

Smart healthcare

Hospitals, doctors, and the healthcare industry as a whole already benefit from the speed and reliability of 5G networks every day. One example is the area of remote surgery that uses robotics and a high-definition live stream that is connected to the internet via a 5G network. Another is the field of mobile health, where 5G gives medical workers in the field quick access to patient data and medical history. This enables them to make smarter decisions, faster, and potentially save lives.

Lastly, as we saw during the pandemic, contact tracing and the mapping of outbreaks are critical to keeping populations safe. 5G’s ability to deliver of volumes of data swiftly and securely allows experts to make more informed decisions that have ramifications for everyone.

5G paired with new technological capabilities won’t just result in the automation of employee tasks, it will dramatically improve them and the overall  employee experience . Take virtual reality (VR) and augmented reality (AR), for example. VR (digital environments that shut out the real world) and AR (digital content that augments the real world) are already used by stockroom employees, transportation drivers and many others. These employees rely on wearables that are connected to a 5G network capable of high-speed data transfer rates that improve several key capabilities, including the following:

• Live views : 5G connectivity provides live, real-time views of equipment, events, and even people. One way in which this feature is being used in professional sports is to allow broadcasters to remotely call a sporting event from outside the stadium where the event is taking place.
• Digital overlays : IoT applications in a warehouse or industrial setting allow workers that are equipped with smart glasses (or even just a smartphone) to obtain real-time insights from an application. This includes repair instructions or the name and location of a spare part.
• Drone inspections : Right now, one of the leading causes of employee injury is inspection of equipment or project sites in remote and potentially dangerous areas. Drones, which are connected via 5G networks, can safely monitor equipment and project sites and even take readings from hard-to-reach gauges.

Edge computing , a computing framework that allows computations to be done closer to data sources, is fast becoming the standard for enterprises. According to  this Gartner white paper  (link resides outside ibm.com), by 2025, 75% of enterprise data will be processed at the edge (compared to only 10% today). This shift saves businesses time and money and enables better control over large volumes of data. It would be impossible without the new speed standards that are generated by 5G technology. 

Ultra-reliable edge computing and 5G enable the enterprise to achieve faster transmission speeds, increased control and greater security over massive volumes of data. Together, these twin technologies will help reduce latency while increasing speed, reliability and bandwidth, resulting in faster, more comprehensive data analysis and insights for businesses everywhere.

5G solutions with IBM Cloud Satellite  

5G presents significant opportunities for the enterprise, but first, you need a platform that can handle its speed. IBM Cloud Satellite® lets you deploy and run apps consistently across on-premises, edge computing and public cloud environments on a 5G network. And it’s all enabled by secure and auditable communications within the IBM Cloud®.

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How effective boards approach technology governance

Across industries and regions, the evidence is clear: technology is increasingly a key part of every organization’s business strategy. Yet boards often struggle with the best way to engage in technology, and there continues to be discontinuity between the board and management when it comes to major technology initiatives.

One management team, for example, came to its board with a proposal to purchase an expensive, cutting-edge new technology system, which they believed would help them outperform their competition. The board, however, lacked a clear mechanism to provide effective guidance on technology topics, and so it wasn’t able to ask probing questions about the system’s true value to the business, push for a practical governance model to manage such a complex implementation, or establish meaningful key performance indicators (KPIs) to track progress. After months of costly implementation work, the vendor failed to deliver significant value. Only later did the management team and the board realize a standard, low-cost solution would have been just as effective in meeting the goals of the project.

Stories like this are becoming more common as boards increasingly need to weigh in on crucial technology strategies. Digital transformations , IT transformations , and large initiatives such as cloud adoption have become fundamental business for the board and can determine a company’s ability to drive inclusive and sustainable growth. It’s not that boards don’t recognize the importance of technology; our analysis shows a steady 33 percent increase since 2010 in board directors who have experience in technical leadership roles. 1 Using data provided by BoardEx, we analyzed the profiles of all S&P 500 board directors from 2010–21, identifying those with technical leadership experience based on their previous titles. We identified directors whose current or historic employment role included one of the following keywords: analytics, cloud, cyber, data, digital, CIO, CISO, CTO, digital, engineering, infrastructure, IT, network, security, software, tech. The issue, however, is that despite the increasing recognition of technology’s importance to the business, boards still tend to deal with technology on the periphery or as a subtopic within the risk and audit committee. Across interviews with board members and executives on the topic of technology and boards, there was broad agreement that boards need to give structure and priority to their technology engagement, but it is not always clear how best to do so. 2 Over the past year, we interviewed more than 12 board directors and executives serving public and private for-profit companies and leading nonprofit organizations.

Boards have clear roles in helping leadership navigate technological waters: posing the right fundamental questions , 3 Celia Huber, Alex Sukharevsky, and Rodney Zemmel, “Five questions boards should be asking about digital transformation,” Harvard Business Review , June 21, 2021. challenging the organization to become more “ tech forward ,” and providing oversight through KPIs and metrics. Precisely because technology now cuts across so many organizational and strategic areas of the business—strategy definition, capability building, partner selection, business integration—clear leadership from the board is crucial to help management coalesce a coherent and practicable strategy across these interdependencies.

The most common engagement model: The technology committee

The most clearly defined form of board engagement with technology is a board committee dedicated to understanding and supporting the organization’s technology strategy, investments, and risk profile and to sharing its insights with the full board. Among the Global Fortune 500, industries with a notable number of tech committees were finance, consumer, and industrials (Exhibit 1). 4 2021 Global Fortune 500 financial statements and reporting. Our research shows that, in 2020 and 2021, companies in these industries that had a board tech committee had operating margins 100–600 basis points higher than their peers that did not have tech committees. Companies’ most common hesitations for not having a tech committee were that they couldn’t find the right members to serve on the committee, the board would become too operational, they might create too many committees, or a committee would crowd out technology discussions within the broader boardroom’s discussion of business strategy.

As a result, only 12 percent of Global Fortune 500 companies have standing tech committees, up from 11 percent two years ago (as of March 2022). Industries with a stronger reliance on technology or digital transformation for their competitive strategy, such as telecom, healthcare, and finance, are most likely to have technology committees. While a formal tech committee is not necessarily the right model for every company (depending on industry, importance of technology, and board expertise), having some form of structured engagement could be beneficial for most.

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Models for board engagement with technology.

Research identifies four effective models through which boards engage with management on technology issues (Exhibit 2):

• regular, full-board engagement as a recurring agenda item
• formal, standing technology committees
• temporary and/or advisory tech committees
• informal engagement on select topics

Regular, full-board engagement

For companies in industries where technology is a core business driver or most business units are impacted by digital strategy, regular, full-board engagement has been the norm. Common examples include software businesses, consumer internet, and telecom. In this model, all directors need to fully understand technology’s implications for the business and have the expertise to navigate wide-ranging issues connected to technology, including corporate strategy, operating models, and governance. Even with full-board engagement, however, an additional board tech committee can be helpful for structured examinations of specific issue areas—talent strategy, for example—or for assisting management teams in pinpointing issues and decisions that require discussion with the broader board.

A board director at a major global bank noted the value of regular, full-board engagement when her company was developing a cloud-based offering. The management team presented the board with three infrastructure options—public, private, or hybrid cloud—with the corresponding resource and risk implications of each and management’s initial recommendation. Board directors scrutinized management’s recommendation by applying their own expertise to weigh trade-offs such as business value and risk across the option set, surfacing to management the most important decision factors and helping to narrow down the options to the final choice.

Standing technology committees

As referenced earlier, where technology may not be related to the core business but nonetheless represents a leading, long-term source of competitive advantage, boards and management teams may seek additional guidance on technology’s relationship to other strategic topics.

This model has been used successfully in financial institutions that rely on digital infrastructure, traditional retailers with substantial and growing e-commerce channels, and pharmaceutical companies that depend on digital systems to optimize R&D.

For these organizations, a standing technology committee helps directors see the interdependencies between corporate strategy and digital. For example, these committees could help the broader board prioritize technology decisions appropriately by surfacing and contextualizing key metrics that have risk, finance, or talent implications. Key risk areas, such as cybersecurity, might require persistent and periodic board oversight, with technology committees providing guidance and transparency for decision making. Additionally, a standing committee on technology with focused board expertise signals an organization’s commitment to technology as a core source of differentiation.

The CIO of a leading insurance enterprise shared that the primary purpose of its board’s technology committee was to help articulate how technology could serve the broader corporate strategy and generate competitive advantage. Monthly meetings with the CEO and CTO also provided the committee with a chance to shape the broader board’s discussions around cyberrisk and other relevant topics ranging from digital resiliency to AI, machine learning, and the path to value from technology.

When setting up a formal, standing technology committee, it is crucial to define the right charter and regular meeting agenda (Exhibit 3). Charters should consider focus areas and the outcomes for the broader board (such as oversight for management reporting). Tech committees also need to define the extent to which they should evaluate technology decisions and status updates as part of the broader corporate strategy, and which form this evaluation should take. This role definition could include overseeing major technology transitions, monitoring commercially important industry or technical trends, or developing, implementing, and monitoring the corporate cyberrisk framework.

Temporary committees and third-party expertise

Some organizations have recently dedicated major strategic or financial resources to technology, typically in the form of a major technology transition or strategic digital investment. Examples include cloud transitions, new digital-business builds, postmortems for major cyber events, and mergers with substantial IT ramifications. These circumstances will nearly always have far-reaching implications for board-level issues related to the operating model, business strategy, and risk. In this case, and especially because these organizations are usually less mature technologically, temporary committees and third-party validation could offer a reliable source of oversight, expertise, and confirmation with the right level of transparency. They could comprise experienced practitioners who bring prior expertise and broader business context to the oversight of a major investment or project—for example, a former CTO or CISO during a transition to the cloud.

Temporary committees draw members from the broader board, while third-party expertise involves external advisors who bring supplemental strategic technical proficiency to specific areas. In both cases, it is important to ensure such resources have a clearly stated mandate, such as overseeing the decision to move to the cloud, and provide guidance on the anticipated impact of considered technologies on the business. As such, prior to forming such committees, there should be detailed discussion around the time and resources needed to support them.

An infrastructure company’s management had been struggling for years to use technology to enable its business goals. At a transformative moment in the company’s history, a board member helped management convene a temporary task force of industry experts to support management and the board in jointly envisioning a strategy for an entirely new type of technologically enabled smart city. The management team led the effort with board oversight, providing regular progress updates together to select directors over the course of several months. Management then used the new strategy to attract and sign a major contract with a marquee customer, which helped revitalize the business and give it a competitive edge.

Four ways boards can shape the cloud agenda

Informal board engagement.

This last engagement model helps a subset of the management team gain frequent and highly focused guidance, including coaching and mentorship, from an experienced board director on high-priority topics. Our interviews with directors showed that this model can take many forms, such as offline mentorship of technical executives, pointed engagement on technical but commercially transformative topics, such as computer vision and blockchain, or periodic input on how to position technical progress updates to the full board. Informal engagement is best suited for boards where one or two directors, rather than a critical mass, have extensive expertise in broader technology or specialized technical areas and management needs additional technical guidance and support. In this model, it’s particularly important for board members to resist the natural inclination to become entangled in management’s operational decisions, while ensuring there is sufficient full-board visibility to underscore the strategic importance of technology discussions. Additionally, formal and full-board engagement, often led by the board’s subset of experts, is often necessary to ensure that technology decisions inform and support the company’s overall business strategy.

Informal engagement may also be helpful for organizations lacking or just developing a forward-thinking technology strategy. In these cases, select, experienced board directors can guide management in thinking through and communicating the concrete technology agenda. Once that agenda is better defined, the board may begin engaging on technology issues more formally. For one pension fund undergoing a cloud transition, board and management determined the incumbent operating model was unsuitable for maximizing the benefits from the investment in the cloud transition. The CEO and chair nominated a director to serve as an informal advisor to the CTO. The pair convened monthly to discuss their agenda for the broader board, with the board member testing the CTO’s road map against his prior experience in such transitions. In another example, a consumer-facing company was digitizing its service operations to increase chatbot-based support. A director helped the head of HR navigate broader board communications on the complicated workforce decisions required for the transition.

The preceding models are not mutually exclusive. In some cases, depending on the topic or need, multiple, simultaneous engagement methods may be expedient. For example, the boards of certain companies may find it helpful to have a formal standing committee to help management assess new technology investments and broad technology strategy, alongside third-party experts, who are able to provide deep analysis of investment decisions, cyberrisk mitigation, and product strategies. Conversely, not all engagement models may be immediately viable choices for any given board. In many cases, boards may find they require new expertise or education before they can contribute meaningfully to certain strategically relevant technical discussions.

Given these considerations, boards should annually reassess their approach to calibrate the best level of engagement with their companies’ executives.

Initial steps for boards and directors

With few standardized methods for assessing major technology decisions and investments, as well as the sheer complexity of managing technology transitions, boards have their work cut out for them. In all cases, boards should follow topic-agnostic best practices for any type of technology work, posing the right questions and determining meaningful metrics and governance to put in place to track progress. For technology specifically, continuous education, the right balance of technical expertise, and targeted engagement with external technology leaders are all prerequisites for board effectiveness. But without an effective technology engagement model, boards will still struggle to have the right level of impact.

An important place to start is to take stock of the flexibility boards have to adapt their technology engagement approach depending on their own level of expertise, corporate strategy, competitive positioning, and management needs. Answering the following questions can help boards and management determine the engagement model best suited to their company:

• How important is technology to my organization’s and any competitors’ corporate strategy?
• What kind of technical expertise do I have on my board, and how relevant is it to my company’s business model?
• What is the pace of technological change or transformation in my company and among its peers?
• What are the three largest technology risks that could disrupt or endanger our operating model and business?
• How effectively is management addressing the key technology issues today?

Boards can create value by understanding connections between technology and their business, determining a clear vision and goals for their technology transformation, and anticipating and minimizing potential risks and threats. Every director should ask whether the board’s current approach to technology sufficiently addresses these issues, and which engagement model might best serve their specific goals.

Will Forrest is a senior partner in McKinsey’s Chicago office, Sidney Li is an alumnus of the Boston office, Isabelle Tamburro is a consultant in the Casablanca office, and Steve Van Kuiken is a senior partner in the New Jersey office.

The authors wish to thank James Kaplan for his contributions to this article.

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Research: Technology is changing how companies do business

By sarah mangus-sharpe.

A new study from the Cornell SC Johnson College of Business advances understanding of the U.S. production chain evolution amidst technological progress in information technology (IT), shedding light on the complex connections between business IT investments and organizational design. Advances in IT have sparked significant changes in how companies design their production processes. In the paper " Production Chain Organization in the Digital Age: Information Technology Use and Vertical Integration in U.S. Manufacturing ," which published April 30 in Management Science, Chris Forman , the Peter and Stephanie Nolan Professor in the Dyson School of Applied Economics and Management , and his co-author delved into what these changes mean for businesses and consumers.

Forman and Kristina McElheran, assistant professor of strategic management at University of Toronto, analyzed U.S. Census Bureau data of over 5,600 manufacturing plants to see how the production chains of businesses were affected by the internet revolution. Their use of census data allowed them to look inside the relationships among production units within and between companies and how transaction flows changed after companies invested in internet-enabled technology that facilitated coordination between them. The production units of many of the companies in their study concurrently sold to internal and external customers, a mix they refer to as plural selling. They found that the reduction in communication costs enabled by the internet shifted the mix toward more sales outside of the firm, or less vertical integration.

The research highlights the importance of staying ahead of the curve in technology. Companies that embrace digital technologies now are likely to be the ones that thrive in the future. And while there are still many unanswered questions about how these changes will play out, one thing is clear: The relationship between technology and business is only going to become more and more intertwined in the future.

Read the full story on the Cornell SC Johnson College of Business news site, BusinessFeed.

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Navigating the future of work: A case for a robot tax in the age of AI

Subscribe to the center for technology innovation newsletter, michael j. ahn michael j. ahn associate professor, department of public policy and public affairs - university of massachusetts boston.

May 13, 2024

• Artificial intelligence and robotics promise unprecedented efficiency while creating a risk of job loss for human workers.
• A specific tax on companies that deploy AI and robotics that are capable of autonomous decision-making could provide economic support for displaced workers as well as an incentive for strategic decision-making about automation, particularly when the benefits are marginal.
• Implementing this tax may require extending legal personhood to robots, not in order to grant robots human rights but to create a structured basis for interactions between robots, individuals, and the state.

In an era characterized by declining birthrates and the urgent need for enhanced productivity, the advent of artificial intelligence (AI) and robotics stands as a dual-edged sword, promising unprecedented efficiency while posing challenges to the economic and social structure through the potential displacement of human workers across both manual and professional fields. As we navigate this new technological revolution, the integration of automation into our workforce and economy moves to an imminent and practical concern.

At this pivotal moment, the proposal of a robot tax is introduced not merely as a knee-jerk governmental response to tax new and unknown technologies, but as a deliberate strategy aimed at enhancing the equity and fairness of technological advances. This approach seeks to sustain humanity and needed social services in this newly automated landscape, aiming to ensure the benefits of technological progress are broadly shared, thus facilitating a smoother, less disruptive transition for society and the economy. As the capabilities of AI continue to advance, the time is approaching to define the appropriate relationship between humans and AI/robots—a critical step towards harmonizing our coexistence.

Strategizing a robot tax: Economic buffers and ethical considerations

A robot tax, targeting companies that deploy AI and robotics that are capable of autonomous decision-making, fulfills two pivotal roles. Initially, it provides economic support for individuals affected by automation, bolstering unemployment benefits and ensuring the market’s demand for goods and services remains steady. Additionally, it prompts businesses to weigh the advantages of human labor against the efficiencies of automation, especially in cases where the benefits of either option are closely matched. This strategic decision-making is crucial for maintaining a dynamic market and healthy consumer demand, essential components of economic vitality.

For the robot tax to be implemented effectively, it’s imperative to clarify the legal relationship between humans and robots/AI. Assigning legal personality to robots would create a structured basis for taxation, responsibility, and ethical guidelines, reflecting discussions like those about autonomous vehicles. Like legal personality granted to corporations, it involves recognizing robots and AI systems as entities with a set of legal rights and obligations enabling them to enter contracts, potentially be held accountable for certain actions (to sue and to be sued), and become subject to taxation as separate entities . In essence, this implies recognizing that AI machines can create added value. Until now, economics has adhered to the labor theory of value, which sees only human labor as creating added value. Acknowledging that intelligent machines are also key players in value creation enables the imposition of taxes on the added value they generate. This legal framework is not about granting robots citizenship or human rights but establishing a structured basis for interactions between robots, individuals, and the state, particularly in contexts where autonomous decision-making by robots impacts the public domain.

The process of granting legal personality to robots would likely involve future legislative action to define the scope of rights and responsibilities associated with different categories of AI and robotics. For instance, a distinction could be made between simple automated machines and advanced AI systems capable of learning and making autonomous decisions. The limits of this legal personality would be carefully outlined to avoid attributing undue rights or moral considerations to robots. The focus would be on creating clear guidelines for how robots can be held responsible for their actions (liability), how they can be integrated into the existing tax systems (taxation), and how they can be controlled or governed by laws (regulation).

Then why the need for legal rights to tax robots when all kinds of equipment can be taxed without legal personality? This arises from the need for clarity and fairness in taxation policy. While it is true that equipment and property can be taxed without legal personhood, the unique nature of AI and robots—particularly their autonomous decision-making capabilities and the potential for generating income or performing tasks traditionally done by humans—presents new challenges for taxation frameworks. Assigning legal personality, in this context, helps to clarify the basis on which taxes are levied, ensuring that the economic benefits derived from the use of advanced AI and robotics are shared equitably within society. It’s not about giving robots rights akin to humans or animals but about adapting our legal and fiscal systems to the realities of an increasingly automated world. Such legal acknowledgment facilitates the tax’s logistical aspects and initiates a wider debate on the ethical considerations of relying on autonomous systems.

Recognizing the legal status of robots and AI transcends mere financial considerations, prompting a deeper exploration of the ethical dimensions involved in embedding autonomous systems into our daily existence. This step could facilitate the creation of regulations aimed at ensuring these technologies serve the public good while addressing any potential adverse effects or biases. Additionally, affording AI and robots legal personality simplifies issues of liability, similar to the discussions surrounding autonomous vehicles. Such recognition not only facilitates the implementation of a robot tax but also enriches the conversation about our evolving dependency on autonomous systems, compelling us to reconsider notions of agency, responsibility, and our interactions with these technological entities.

Key considerations for a robot tax

As we contemplate the future of a robot tax, several key considerations emerge. Firstly, the scope of taxation—identifying which industries and functions of AI to tax—is important. Secondly, the responsibility for the tax, whether it lies with the manufacturers or the employers of robots, requires clarification. Thirdly, given the global nature of technology and business, international cooperation is essential to prevent competitive disadvantages for countries adopting the tax. Lastly, we must establish an ethical baseline for the creation and employment of robots, contemplating the long-term possibility of AI developing or emulating consciousness and how this would redefine our relationship with them.

The determination of which industries and AI functions to tax involves a nuanced analysis to identify sectors where automation plays a critical role in productivity and employment dynamics. For instance, manufacturing, where robots have long been integral, and emerging fields like health care and finance, where AI’s impact is rapidly growing, are prime candidates. The goal is to develop a tax framework that acknowledges the varied contributions of AI and robotics across the economic spectrum, ensuring the tax is both fair and focused on areas with the most significant displacement potential.

Clarifying who bears the fiscal responsibility for the robot tax—manufacturers of the technology or the businesses that employ these automated systems—is essential. This decision influences the broader economic impact of the tax, potentially affecting innovation and investment in the sector. If manufacturers are taxed, it could slow down technological advancement by potentially increasing the development costs associated with such a tax. Conversely, taxing employers might lead to higher operational costs but encourage more thoughtful integration of automation. A balanced approach could involve considerations of the robot’s or AI system’s complexity, usage, and the economic context of its deployment.

Given the borderless nature of technology and commerce, international collaboration would be necessary in implementing a robot tax. Without a coordinated approach, countries adopting the tax might face economic disadvantages, such as loss of foreign investment or technology firms relocating to tax-friendly jurisdictions. Establishing international guidelines and agreements can help create a level playing field, ensuring that the robot tax supports global economic stability and fairness. This requires dialogue and partnership between nations, international bodies, and stakeholders in the tech industry. Effectively governing AI, including measures like taxation or establishing ethical standards, would likely necessitate some form of enforceable international agreement. Without widespread international cooperation, the impact of unilateral actions could be significantly diminished. This poses a challenge that needs to be addressed. As a country with considerable influence, the U.S. should take a leadership role in fostering and enforcing such agreements, ensuring that initiatives do not undermine its competitiveness or incentivize firms to relocate their robot operations abroad.

The development of robots and AI challenges us to consider not just the economic implications but also the ethical boundaries of our relationship with these technologies. Establishing an ethical baseline for the creation and employment of robots is essential, especially as we approach the frontier of AI potentially developing or emulating consciousness. This involves grappling with questions of rights, responsibilities, and the societal role of AI entities, ensuring that technological advancement aligns with human values and ethics. As we chart the course for a future intertwined with AI, these ethical considerations will shape not only tax policies but also the broader framework of human-machine coexistence.

The introduction of a robot tax emerges as a forward-thinking solution to the complex challenges brought about by automation and AI. This tax not only promises to redistribute the economic gains from technological progress by supporting workers displaced by automation, but it also plays a crucial role in enhancing societal equity. By reallocating wealth generated from the use of robots and AI, the robot tax aims to fund essential public services and initiatives—ranging from supporting elder care and social welfare to education and retraining—thereby addressing disparities and ensuring that the benefits of the AI revolution are shared across the entire spectrum of society. As we move forward, engaging in comprehensive discussions that span legal, ethical, and economic domains is crucial for developing policies that are both just and visionary. The trajectory of the future of work remains in our collective hands, offering us the opportunity to ensure that advancements in AI and robotics serve to uplift rather than undermine human welfare, making the case for a robot tax a pivotal step towards achieving a more equitable future for all.

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Managing firm risk: supply chain board members and the contingent effects of firm network architectures

• Published: 15 May 2024

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• Yue Fang 1 , 2 , 3 , 4 ,
• Tianyu Hou 5 ,
• Qin Su   ORCID: orcid.org/0000-0001-5003-125X 1 , 3 , 4 &
• Raymond Y.K. Lau 2  

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Demand-supply mismatch is considered one of the most important factors that drives firm risk. Nevertheless, the difficulties in quantifying firms’ capability and ambition to deal with demand-supply mismatch drive external investors to seek valuable signals to guide investment decisions. Drawing on signaling theory, we identified supply chain board members (SCBMs) – the presence of directors of customer and supplier organizations in a focal firm’s boardroom as an effective approach to attenuate demand-supply mismatch, and accordingly indicate lower firm risk. Through a panel dataset of 1681 manufacturing firms listed in the North American market from 2010 to 2020, we empirically analyzed the effects of supply chain board members on firm idiosyncratic volatility. We found that firms with supply chain members in their boardrooms are accompanied by lower idiosyncratic volatility than those without SCBMs. We further discussed the effects of supply chain network architectures as critical signaling environments on SCBMs. The regression results indicated that the signal of SCBMs is strengthened under high eigenvector centrality, but weakened by a high level of structural holes. This study extends conventional risk evaluation literature by theorizing one type of inter-organizational relationship, SCBMs, as an effective signal of collaborative intention and commitment, which proxies a focal firm’s capability and ambition to build collective strength with external investors and stakeholders to lower firm risk. Our findings are robust under several additional tests, e.g., propensity scores matching, instrument variable regression, and Heckman’s two-stage regression.

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Note that we don’t limit the measurement of SCBMs to the manufacturing industry to avoid sample selection bias issues. Interlocked directors could come from other industries. For the same reason, we also use the entire listed companies supply chain networks to calculate focal firms’ supply chain architectures, e.g. (eigenvector centrality and structural holes).

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This study was funded by Ministry of Science and Technology of the People’s Republic of China (Grant Number 2019YFB170078), China Postdoctoral Science Foundation (Grant Number 2023M731901), Research Grants Council of the Hong Kong Special Administrative Region, China (Grant Number CityU 11507323), and City University of Hong Kong SRG (Grant Number 7005780).

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Yue Fang & Qin Su

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State Key Laboratory for Manufacturing Systems Engineering, Xi’an, China

The Key Laboratory of the Ministry of Education for Process Control & Efficiency Engineering, Xi’an, China

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Fang, Y., Hou, T., Su, Q. et al. Managing firm risk: supply chain board members and the contingent effects of firm network architectures. Inf Technol Manag (2024). https://doi.org/10.1007/s10799-024-00426-1

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Published : 15 May 2024

DOI : https://doi.org/10.1007/s10799-024-00426-1

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