literature review on impact of technology on consumer behaviour

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 15 March 2022

The impact of digital technology on changing consumer behaviours with special reference to the home furnishing sector in Singapore

• Easwaramoorthy Rangaswamy   ORCID: orcid.org/0000-0003-0222-4764 1 ,
• Nishad Nawaz   ORCID: orcid.org/0000-0003-4781-7993 2 &
• Zhou Changzhuang 3  

Humanities and Social Sciences Communications volume  9 , Article number:  83 ( 2022 ) Cite this article

39k Accesses

17 Citations

1 Altmetric

Metrics details

• Business and management
• Information systems and information technology

The impact of digital technology has altered consumers’ choices for decades, which has fostered large amounts of eCommerce, including in the home furnishing business. Furthermore, due to the Coronavirus disease (COVID-19) pandemic, consumer behaviours have changed, with consumer satisfaction influencing purchasing initiatives and decision-making online. There is insufficient research on online purchasing behaviours in the home furnishing sector in the context of Singapore. The advent of digitisation and the emergence of marketing through digital platforms compared to offline marketing have changed purchasing behaviours regarding home furnishing in Singapore. Research designs and methods, including realism philosophies, deductive approaches, a quantitative research method, a cross-sectional analysis in a descriptive research design and a questionnaire research instrument, were applied to the current study. The findings show a critical trend: consumers prefer an omnichannel approach when purchasing furniture, thereby enhancing competitive costs and personalisation designs and services. Consumers expect advantages both online and offline to maximise the benefits of their purchasing.

Similar content being viewed by others

Impact of smart locker use on customer satisfaction of online shoppers in Vietnam

Modeling the intention to consume and willingness to pay premium price for 3D-printed food in an emerging economy

The impact of perceived risk of online takeout packaging and the moderating role of educational level

Introduction.

According to the Singapore Economic Development Board ( 2018 ), due to an increase in the intensity of the competition in the global market, the ways in which retail markets operate have been changing rapidly. The rate of change from offline to online markets has been so alarming that offline retail stores or traditional markets are now greatly threatened. Furthermore, with the disruption of the COVID-19 pandemic, the existing online retailers have become worried about the sudden influx of competitors who have turned to eCommerce. There has been a 50% increase in online shopping over the last 10 years, while the average purchasing value has decreased significantly, especially that for prices above 200 Singapore dollars, which has been reduced by 20% (Data.gov.sg, 2020 ). Unfortunately, home furnishing (furniture) products average a value above $200; thus, it is crucial to research Singapore’s local online shopping characteristics in terms of the bulky home furnishing category to analyse the market and provide strategic advice for local furniture partners. Neither the Singapore Furniture Industries Council (SFIC) nor the Singapore Furniture Association can help local furniture partners adapt to innovation activities. Unfortunately, there is not enough information in terms of market trends or local consumer behaviours; thus, the gap analysis would involve both external and internal investigations to aid in filling the gaps for higher business potentials (Miller et al., 1998 ; Booth et al., 2003 ; Novy and Colomb, 2016 ).

Research problems have been recognised due to steady improvements, and advances in technologies have fostered market changes from traditional brick and mortar companies towards more click and mortar options, if not click-only options. Online and offline retail players are concerned about user experiences, including both online and offline experiences. Assumptions that the traditional physical retail store design will never be disrupted in regard to home furnishing products may therefore be reconsidered. While local consumers’ attitudes will affect the business model in terms of home furnishings, it is important to research purchasing concerns regarding the pros and cons of both online and offline shopping. Additionally, it is crucial to analyse the current buyers’ intentions and behaviours with regard to the changing COVID-19 situation. Furthermore, possibilities with regard to omnichannel feasibility analysis have led to this study, which focuses on the impact of digital technology on changing consumer behaviours, especially concerning home furnishing in Singapore as an essential sector.

Moreover, the COVID-19 pandemic has accelerated digitalisation trends and the possibility of the swift development of new digital technologies; thus, it is crucial for organisations to review their overarching digital transformation (Trenerry et al., 2021 ). Additionally, Singapore, which is one of the top smart cities in the world, has adopted such technology in most business sectors and applications and in almost all the projects led and supported by the government (Huseien and Shah, 2022 ). Furthermore, for businesses in Singapore, it is crucial that they apply digital technologies in their organisation, as was reported in a study on the application of digital technology (Whitelaw Sera, 2020 ). This argument was supported by Skare and Riberio Soriano ( 2021 ), who argued that globalisation influences the adoption of digital technologies. Considering the minimal research available regarding digital technology’s impact on the changing consumer behaviours related to home furnishing in Singapore, there is an urgent and important need to conduct the present study. To analyse the problem mentioned previously and to achieve a positive result regarding the current research, the following research questions were asked in this study, which range from general online shopping to furniture eCommerce and focus on various concerns or variables that can alter consumers’ decisions.

Have there been any changes made in regard to consumer behaviours and attitudes towards furniture, especially regarding vertical eCommerce?

What are the advantages and disadvantages of both offline and online furniture stores?

Is the omnichannel (both online and offline) the most consumer-acceptable home furnishing (furniture) business model?

The benefit of conducting the present research is to enable stakeholders to better understand the impact of digital technology on the changing purchasing behaviours towards home furnishing in Singapore. The study reveals customers’ expectations towards future home furnishing services, which can be used to alter the furniture industry’s strategies. The aim of the current study is to evaluate the digital characteristics that alter buyers’ behaviours, i.e., to reveal the underlying demands that analyse the changing needs and desires regarding the purchase of furniture. Furthermore, the study aims to evaluate buyers’ preferences for combining both online and offline advantages and to evaluate a potential successful model for the home furnishing business. The COVID-19 pandemic has led to the integration of both the offline and online approaches, which has created an omnichannel as a new competitive advantage that is now seen as the norm. Thus, the objectives of the present research are as follows:

To evaluate consumer behaviour trends towards home furnishing (furniture) expansion, especially concerning vertical eCommerce in Singapore.

To compare the advantages and disadvantages of traditional (offline) versus online home furnishing stores (furniture) in Singapore.

To examine the future omnichannel (online + offline) of the home furnishing business model.

Literature review and conceptual gap

This research used a deductive approach. In doing so, the research reviewed the existing literature and determined the research gap in the existing conceptual models; it also determined the best business model/theory to be used to examine home furnishing (furniture) eCommerce, i.e., applying a quantitative approach involving purchasing frequency, attitudes and so on (Cleveland and McCutcheon, 2022 ; Bell et al., 2018 ; Creswell, 2014 ). Important reviews related to the research are presented in this section.

It is crucial to investigate the components or variables, such as features, attitudes, behaviours, and involvement, in the context of their impact on buyer behaviour (O’leary, 2017 ). With such research variables influencing different components, such as advanced technology, the digital revolution, ageing, income levels, lifestyle changes, environmental concern, etc., there are changes made to consumer behaviours. Consumers are influenced by various factors that exert varying degrees of power on their decision to purchase furniture (Zwierzyński, 2018 ). In Poland, the main factors in such a decision are the buyer’s family and financial situations. However, Singapore presents a different economic stage, in which the buyer’s household income influences his or her desire for home furnishing purchase intentions, as confirmed by research conducted in 2012–2014 (Studio, 2012 ) in Poland.

As online shopping has become more prevalent and attractive, home furnishing has presented itself as one of the potential sectors; however, the lack of data regarding the related research, especially concerning Singapore, raises the importance of conducting a questionnaire based on the literature review. The current research ranges from macro digital impacts to consumer buying behaviours to evaluate the pros and cons of both online and offline businesses by analysing the factors of the attitudes affected by specific home furnishing categories. A previous study (Moreno-Llamas et al., 2020 ) argued that digital technology development encourages higher levels of sedentary behaviour; however, this argument has not yet been confirmed. However, it was previously found that the ownership of an e-device (either a DVD player, CD player, desk computer, laptop, or an internet connection) was associated with a longer sitting time (>4.5 h/day) for the overall population, with slight differences by gender. Another study (Hoyer et al., 2020 ) highlighted that new technologies, such as the Internet of Things (IoT), augmented reality (AR), virtual reality (VR), mixed reality (MR), virtual assistants, chatbots and robots, which are typically powered by artificial intelligence (AI), are dramatically transforming the customer experience. This study also argued that the role of new technologies on the customer/shopper journey is crucial at each broad stage of the shopping journey (pretransaction, transaction, and posttransaction).

As highlighted by previous research, the local market for online furniture in Singapore has been changing and evolving (Lee, 2020 ). This study presented various drivers of change in the context of local markets in Singapore. The first of the market-changing drivers highlighted was the availability of retail space, which has been supported by the ongoing COVID-19 situation. Second, the local market has always supported the idea that there should be some form of a physical presence presented rather than only a fully online presence. This support, in turn, influences the value and recognition of retailers. Additionally, having a physical presence shows that the local retailers are better than the overseas retailers, who only have an online presence from whom customers may choose to import. Third, there has been a fundamental shift in consumer perception towards physical experiences in the context of the brand value of a product. Similarly, another previous study (Zwierzyński, 2018 ) highlighted that due to the COVID-19 pandemic, there would be significant ongoing innovations made throughout society during the pandemic, with many of these innovations having the possibility of long-term societal impacts. Digital technologies are seen as part of these large-scale systemic shifts.

In the literature (Jafari-Sadeghi et al., 2021 ), researchers have studied the digital transformation, which has been broken into three categories, namely, technology readiness (e.g., ICT investments), digital technology exploration (e.g., research and development) and digital technology exploitation (e.g., patents and trademarks). Several significant relationships between constructs have been identified. The digital transformation of value creation has contributed to technology entrepreneurship and technological market expansion. Digital transformation assists as an innovative network in which the digital supply chain helps organisations establish an ecosystem and enhance the supply chain. These changes in the digital systems of an organisation help management make better tactical decisions and maximise the value for the organisation (Choudhury et al., 2021 ). This argument was agreed to and supported by Cruz-Cárdenas et al. ( 2021 ), who highlighted that the technology and measures adopted by governments and social media stand out as external factors that affect organisations. Furthermore, the authors argued that organisations should work on varied marketing strategies that reflect the technological changes made to consumer behaviour. As such, organisations must work on creating digital transformations that address such changes in the consumer and market.

Similar to earlier studies, Matarazzo et al. ( 2021 ) examined the impact of digital transformation on customer value creation and highlighted that digital channels contribute to the innovation of an organisation’s business model. Such transformation also helps to create new distribution channels and new ways to create and deliver value to customer segments. Additionally, digital transformation impacts technological market expansion when organisations are seen as embracing digital innovation (Jafari-Sadeghi et al., 2021 ). Such conclusions and arguments indicate that the enhanced use of digital technologies increases an organisation’s innovation performance (Usai et al., 2021 ). Another study (Jessen et al., 2020 ) empirically demonstrated the sequential mediation process connecting the use of technological advances with customer engagement, customer creativity and anticipated satisfaction. The study highlighted that such use was better in the early stages of customers’ purchase journeys. Additionally, it has been emphasised that consumer involvement plays a central role in explaining the intention to participate in online buying (Sharma and Klein, 2020 ). Furthermore, it has been argued that consumer perceived value, trust, and susceptibility to interpersonal influence are significantly correlated with consumer involvement (Cruz-Cárdenas et al., 2021 ).

Customer involvement also depends on the level of convenience offered by organisations; when retailers enhance their level of service convenience, this affects the consumers’ channel switching behaviour. When looking at the omnichannel retailing industry, both offline search convenience and online purchase convenience have impacts on motivating consumers’ showroom behaviour (Shankar et al., 2021 ). Furthermore, these elements of convenience can also help identify motives, barriers, personality traits, and the role of culture in consumer adoption, which helps one recognise enablers and inhibitors (Jain et al., 2022 ). A meta-analysis conducted by Jayawardena et al. ( 2022 ) indicated that online engagement strategies based on gamification assist retailers in improving the engagement of customers and their level of involvement. This approach can further assist in enhancing online education, online brand engagement, and information system engagement.

Another study (Mims, 2017 ) argued that a company should work on enhancing their brand visibility before planning an overseas venture through an online presence. This study also stated that a lack of brand visibility may affect the company’s physical and emotional connection with customers. It is crucial for Singapore firms to address these concerns locally before moving towards options of internationalisation or exploring the regional markets. Furthermore, the debates related to the waning efficacy of offline and online media advertising channels, especially in the context of increasing advertising budgets, cannot be ignored. As such, in the home furnishing industry, the role of the offline retail experience and the way in which the industry operates is different. With increasing levels of internet penetration, online shopping has maintained a competitive position since the 21st century, and the high risk of cybercrime has made it difficult to choose (Davis, 1989 ). Therefore, a vertical eCommerce approach could change the retail game for a sector such as home furnishing. Home furnishing, especially furniture purchasing, requires personally tailored products with a modern value. Simultaneously, cost sensitivity characteristics are another main factor of purchasing decisions (Bednarik and Pakainé Kováts, 2010 ). Personal relations with counselling are used to obtain a market share in Hungary; this approach may also be used in markets such as Singapore.

In the US, according to a study by Cisco ( 2012 ), 74% of customers conduct online research before they make an in-store purchasing decision; furthermore, it is stated that nearly 40% of American respondents use mobile phones to obtain onsite digital content information, while another 35% use tablets for the same purpose. In addition, research by Furniture Today has shown that nearly 50% of furniture store consumers use smartphones before their visit to look up information, which means that customers hop from one single information channel to another. Such a “cross-channel” shopping experience demands a new approach to retain and win consumers for most retailers. For example, using in-store kiosks to provide potential buyers with fully displayed information provides a unique competitive advantage.

Another previous study (Ponder, 2013 ) also suggested that a significant shift, which includes shopping attitudes and online furniture purchasing, is occurring quite gradually. This study shows that the number of people who bought furniture online doubled to 21.6% within a span of only five years. Additionally, it shows that nearly 52% of people would be willing to order home furnishings, including bulky furniture, through the internet in the future; this means that “the retailer’s standalone website” is the most crucial element of online home furnishing purchase consideration for the majority of such shoppers (78.31%). Furthermore, it is highlighted that the COVID-19 pandemic and the subsequent lockdown have disrupted consumer buying and shopping habits (Sheth, 2020 ). Consumers are learning to improvise and learn new habits, which also emerge from technological advances and the supply chain (Chowdhury et al., 2021 ).

The existing research highlights that there is a lack of data concerning Singapore furniture authorities; the related reviews that are used as references for further localisation verification come from either the US or Poland. All of the data indications reveal the development of successful local furniture models from end users’ opinions, which can help guide local players to meet the existing demands. It is crucial in a research study to review the available literature to understand the research topic more clearly, and a further in-depth literature review is needed to identify the research gaps; the valuable data gathered during these processes have made this research more relevant to the current requirements of stakeholders and market players. Thus, researching the local market for home furnishing online purchasing in terms of consumer behaviours is in high demand, especially for local furniture dealers.

A conceptual framework has been developed to address these research gaps with the aim of also studying local consumer behaviours with a digital lifestyle to better understand the local market by utilising analogies. Other studies (Moreno et al., 2014 ; Berman and Pollack, 2021 ) have analysed changing factors to help formalise the omnichannel strategy with adopted consumer attitudes, thereby enhancing the strengths from both online and offline models to a new vertical eCommerce business model. This framework (Fig. 1 ) has been developed with two main factors, namely, external technology’s impact on digital life and internal customers’ attitudes and behaviours. These factors have been analysed mostly in demographic segments to evaluate the final hypotheses regarding the omnichannel for home furnishing in Singapore. Hypotheses derived from this conceptual model need to address the demographic characteristics of the consumers that contribute to their behaviours and attitudes in regard to purchasing furniture either online or offline. Online shopping frequency and purchasing time duration are also seen as contributing factors. Keeping in mind the limited resources available to analyse these purchasing behaviours in regard to how they change along with the digital life, especially in the home furnishing sector, the following hypotheses are tested using the data collected:

Conceptual framework for a study on the impact of digital technology on changing consumer behaviours.

H1: There is no significant relationship between gender and consumer behaviours towards purchasing furniture either online or offline.

H2: There is no significant relationship between gender and consumer attitudes towards having either a showroom or a purely online presence.

H3: There is no significant relationship between marital status and consumer attitudes towards having either a showroom or a purely online presence.

H4: There is no significant relationship between income levels and consumer behaviours regarding online shopping frequency.

H5: There is no significant relationship between income levels and consumer attitudes towards having either a showroom or a purely online presence.

H6: There is no significant relationship between education and consumer behaviours regarding purchasing time duration.

The present study about home furnishing in Singapore is examined in the context of the impact of digital technology, changes in home furnishings and changes in buyer behaviours. Impact in digital technology is studied in both offline and online store impact strengths. Changes in buyer behaviours lead to the study of the attitudes and factors that affect these changes. These changes are, in turn, studied along with the omnichannel strategy of adopted consumer behaviours concerning vertical eCommerce and business model changes. Various demographic characteristics, such as age, gender, income and education, are also studied along with the hypotheses that are developed and tested.

The present quantitative research used a deductive approach based on the literature (Bell et al., 2018 ; Creswell, 2014 ). The research also applied realism to the study process, which is a philosophy based on the scientific approach to developing knowledge (Saunders et al., 2009 ). A cross-sectional analysis was applied, with participants being arranged in different groups; this approach did not require an extended monitoring period of longitudinal research (Jackson, 2015 ). The research design used in this study was descriptive in manner, which means that it aimed to accurately portray the character of a group or situation.

The primary data (Corbin and Strauss, 2014 ) were collected using convenience sampling as the technique method. The research instrument used was a questionnaire consisting of four parts: sociodemographic information, buying behaviour, behavioural intention to purchase furniture, and external influences of purchasing. Eighty-four respondents were selected to participate in the study. The participants were aged 18–75, with miscellaneous income and education levels and specified sexes and marital statuses. To minimise the discrepancy of the sample, the research was carried out using nonprobability sampling, in which everyone had an equal chance of being selected and selection was based on the individual’s availability and having enough time to complete the questionnaire (Bryman, 2016 ).

Data were collected from the respondents, who were members of the general public in Singapore who had internet access. The survey questionnaire was posted on social media and responded to anonymously via Google Forms between October and November 2020. Validity tests were conducted for the research instrument. Content validity was assessed by seeking feedback from two information technology professionals, two marketing professionals and two experts in the home furnishing industry. Construct validity was assessed by consulting a statistician to ensure that appropriate variable types, such as nominal, ordinal and categorical, as well as appropriate intervals, were chosen. Reliability analysis was performed using Cronbach’s alpha measure, where a score of at least 0.73 or above is considered reliable (Bell et al., 2018 ). The Cronbach’s alpha reliability score for the current research instrument is 0.749. As this score is >0.73, the research instrument used in the study is considered to be reliable.

Although various nonparametric tests exist, such as the 1-sample sign test, 1-sample Wilcoxon signed-rank test, Friedman test, Goodman–Kruska gamma test, Mann–Whitney test, and Spearman rank correlation test, the present study used chi-square tests in conjunction with descriptive-analytical tools. Chi-square tests were performed to better understand the relationships between the variables used in this study. In the present study, chi-square tests were used as nonparametric tests, as such tests help to determine whether there is an association between categorical variables (i.e., whether the variables are independent or related). Demographic variables were tested, including variables that were related to consumer behaviours in terms of online and offline furniture purchases, consumer attitudes towards showrooms, consumer behaviours regarding online shopping frequency, consumer behaviours in terms of purchasing time duration and consumer attitudes towards purchasing furniture both offline and online. Such analysis assisted with the hypothesis testing. In chi-square test results, if the p value is greater than the chosen significance level ( α  = 0.05), then the null hypothesis is not rejected.

The research revealed trends related to home furnishing in terms of offline stores and online platforms. The data showed that omnichannel and standalone furniture websites accounted for two-thirds of the overall shopping behaviour. As such, consumers who are willing to spend money on home furnishings will both satisfy their physical needs and value them. Thus, the omnichannel approach has a significant favourable influence on consumer behaviours regarding home furnishings in Singapore. Figure 2 indicates the importance of an online plus offline combination, with consumers preferring a more omnichannel approach (35%). This preference is followed by new standalone branded furniture websites (33%).

Consumer shopping behaviour on home furnishings.

This section studies the relationships between demographic characteristics and purchasing online structure characteristics. Table 1 shows that gender significantly influences the choice of online or offline shopping in terms of furniture. The first hypothesis is that online shopping with physical viewing ability is the most appealing shopping method (71%). In contrast, the second hypothesis is translated as a positive relation of the two variables (0.029), with males intending to purchase more when using the omnichannel approach.

Hypothesis 1: There is no significant relationship between gender and consumer behaviours towards purchasing furniture either online or offline.

Hypothesis 1 is rejected, as Table 2 shows a positive relationship between the variables.

The results of Table 3 indicate that gender significantly impacts consumer attitudes towards showroom-only retailers and purely online shopping retailers in terms of furniture. The first hypothesis indicated that offline shopping (90%) is still mainstream. In contrast, the second hypothesis indicates to a positive relationship between the two variables (0.04), with males intending to more easily accept purely online shopping compared to females; in other words, females prefer physical stores.

Hypothesis 2: There is no significant relationship between gender and consumer attitudes towards having either a showroom or a purely online presence

Hypothesis 2 is rejected, as Table 4 shows a positive relationship between these variables.

Table 5 shows a significant positive relationship between marital status and preferring either a showroom or a purely online presence. The results of the first hypothesis indicate that visiting a showroom is still the most attractive method for purchasing (90%). The second hypothesis indicates that couples display more purchasing intention when visiting a showroom than do single individuals, and these variables are statistically significantly associated (0.004).

Hypothesis 3: There is no significant relationship between marital status and consumer attitudes towards having either a showroom or a purely online presence.

Hypothesis 3 is rejected, as Table 6 shows a positive relationship between these variables.

Table 7 shows a significant positive relationship between income and frequency of online shopping. The results of the first hypothesis indicate that the most common online shopping occurs between one week and one month for all income groups. Furthermore, the second hypothesis indicates that those with lower incomes purchase by online shopping more frequently than do those with higher incomes.

Hypothesis 4: There is no significant relationship between income levels and consumer behaviours regarding online shopping frequency.

Hypothesis 4 is rejected, as Table 8 shows a positive relationship between these variables.

Table 9 results indicate that income has a significant association with both online and offline shopping methods in terms of furniture, which leads to a positive relationship between the two variables. The high-income group has a higher level of intention to order furniture online, and purchasing online with a physical view available is the most attractive scenario, especially for the high-end income group.

Hypothesis 5: There is no significant relationship between income levels and consumer attitudes towards having either a showroom or a purely online presence.

Hypothesis 5 is rejected, as Table 10 shows a positive relationship between these variables.

Table 11 shows a significant positive relationship between education and research time allowed for online purchasing. The results indicate that the more education a group has, the more time they spend researching online shopping. This outcome is evident in the results, as bachelor’s degree holders account for 37% of the total. There is a significant relationship between education and purchasing time duration (0.009).

Hypothesis 6: There is no significant relationship between education and consumer behaviours regarding purchasing time duration.

Hypothesis 6 is rejected, as Table 12 shows a positive relationship between these variables.

Digital technology has changed lifestyles, while the COVID-19 pandemic has accelerated the pace of consumer behaviours. The trend of eCommerce is a popular way of shopping that is driven by the benefits of both offline stores and online platforms, while consumer behaviours demonstrate a massive push towards the omnichannel strategy (Wilmarth and Milstead, 2020 ), especially the need for brands. Gender has a significant influence on online or offline shopping choices in terms of furniture. The first hypothesis suggests that online shopping with physical viewing available is the most appealing shopping method. In contrast, the second hypothesis suggests a positive relation between these two variables, with males intending to purchase more with regard to the omnichannel approach. Gender also has a significant impact on the preference between visiting a showroom versus engaging in purely online shopping in terms of furniture. The first hypothesis indicates that offline shopping is still mainstream, while the second hypothesis suggests a positive relationship between the two variables. Males seem to more easily accept purely online shopping compared to females; in other words, females prefer visiting a physical store.

There is a significant positive relationship between visiting a showroom and engaging in purely online purchasing in terms of marital status. The results of the first hypothesis indicate that visiting a showroom is still the most attractive method for purchasing. In contrast, the second hypothesis suggests that couples are statistically significantly more likely to visit a showroom compared to single individuals. Couples are the most attractive group for shopping for home furnishings, especially with a showroom experience. Thus, local furniture sellers should be encouraged to focus more on the demands of couples while also developing goods for and attracting single individuals. Such results align with the results of previous research (Zwierzyński, 2018 ), which highlights that decision-making is influenced by various factors with degrees of power. Similarly, O’leary ( 2017 ) also agrees that the relationship of the variables affects the behaviour of consumers.

There is a significant positive relationship between education and research times for online purchasing. The results indicate that those with a higher education spend more time researching online shopping; there is a significant relationship between education and research time. Those with a higher education were more prudent regarding purchasing; thus, a piece of sufficient information was displayed in these results, the effective oh which has a massive impact on targeting, with tremendous sales initiatives. It is also crucial, as highlighted, that such relationships are important to and aid in online shopping (Wiśniewska and Paginowska, 2006 ), which can also be further observed in the future (Gauri et al., 2021 ).

Income has a significant association with both online and offline shopping methods in terms of furniture, which suggests a positive relationship between the two variables. The high-income group has a higher level of intention to order furniture online, and purchasing online with a physical view available is the most attractive scenario, especially for the high-end income group. The higher-income groups are the target population segment for existing sales growth, while the low-to-medium income groups represent the basis of the home furnishing business. The study by Studio also supports and agrees with the impact of finances on one’s purchase decision (Studio, 2012 ). This includes the intention to purchase home furnishings. The most frequent range for engaging in home furnishing shopping is one to ten years, and consumers prefer the omnichannel approach and supporting a branded standalone website due to their reputation. A similar study (Ponder, 2013 ) also showed that the frequency of online furniture purchases using newly available mediums doubled to 21,6% within five years compared to the growth of traditional options, and it is suggested that such growth will continue in the postpandemic period (Al Mansoori and Ahmad, 2021 ).

Implications of the study

The impact of digital technology has altered consumers’ choices for decades, which has, in turn, fostered large amounts of eCommerce, including in the home furnishing sector. With limited literature available in the present research area, especially in regard to the home furnishing sector, the present study is quite significant for decision-makers and stakeholders in the industry. Furthermore, in addition to the COVID-19 pandemic, consumer behaviours have changed during the movement control period, and consumer satisfaction will continue to influence purchasing initiatives and decision-making online. Therefore, there has been a need for the current study to address the present conditions of the market. Additionally, this study shows that consumers expect advantages from both online and offline purchasing to maximise their benefits of purchasing, which is also key for the home furnishing industry to consider in their strategies. The current study also highlights that the home furnishing business does need to adapt to changing consumer attitudes and behaviours. Clarity regarding the impact of demographic variables has also been shown for those in the home furnishing business to reflect upon. By helping to fill the research gap, which is present due to the limited amount of literature on eCommerce studies focused on home furnishing, the present study’s contribution to the literature is important.

The current research was conducted using limited respondents and a time loop, which could be improved by expanding the sample size and spreading the study period to either 9–12 months or a longer period of longitudinal research. Furthermore, future research questions should be modified to focus on the details or specific categories of the home furnishing sector. Such findings would help guide Singapore home furnishing companies to plan for offline and online campaigns to better ensure a successful business. Additionally, convenience sampling was used in the current study due to time and cost constraints, as the study was self-sponsored. The results would have provided different dimensions if the study has accommodated the probability sampling method with a larger sample size. Future research can also include other critical success factors, such as branding recognition, existing reviews, and decision-making processes. These outcomes would also help guide Singapore home furnishing companies to plan offline and online campaigns to better ensure a successful business. Future studies can also study online engagement strategies such as gamification with reference to digital channel marketing in the home furnishing business. Although there is a scope for future study, the current results can help lead the home furnishing industry to more positive strategic implications.

The present study has evaluated consumer behaviour trends in home furnishing (furniture) expansion in eCommerce in Singapore. It has also compared the advantages and disadvantages of traditional (offline) versus online home furnishing stores (furniture) in Singapore. A further examination of the home furnishing business model’s future omnichannel (online plus offline) approach has also been presented. With the options of omnichannel options, retailers would ideally manage their issues on the level of consumers’ product involvement; offering such conveniences helps with regard to customer retention and managing consumers’ channel switching behaviours (Shankar et al., 2021 ). Additionally, such an approach would assist organisations in recognising the main enablers of and inhibitors to adopting (Jain et al., 2022 ). Additionally, organisations must use an appropriate engagement strategy to improve their involvement. Such approaches include online education, online brand engagement, and information system engagement (Jayawardena et al., 2022 ). As Singapore is a developed society, traditional brick and mortar stores have occupied most of the market share; however, vertical eCommerce is a fast-growing industry due to the effects of the COVID-19 pandemic. The results of the current study show that consumers are motivated if they are engaged online, which helps to change their behaviour and attitudes. It has also been reinforced that an exciting offline experience is one way to cater to consumer needs and enhance consumer buying behaviours. This research is crucial, as the business community needs to capture and retain customers’ attention, while at the same time, the need to brand a home furnishing is a stimulus. Such a unique value proposition will distinguish competitors. In return, the brand’s image will create positive reinforcement. As using the internet has become the norm for almost everyone, an alternate target market strategy is recommended for gender, education and income level differences, with reinforced consultation and customisation and enhanced content marketing to attract an audience. To retain existing customers, more emphasis should be placed on the postsale period, as the concerns of buyers include showroom location and quality and design.

Data availability

The authors confirm that all data generated or analysed during this study are included in this published article.

Al Mansoori MS, Ahmad SZ (2021) Adapting to the “new normal” post-pandemic consumer behavior: the case of Rafeeg’s strategy of service marketing. Emerald Emerg Markets Case Stud 11(3):1–17. https://doi.org/10.1108/EEMCS-08-2020-0311

Article   Google Scholar  

Bednarik E, Pakainé Kováts J (2010) Consumer behaviour model on the furniture market = Vásárlói magatartásmodell a bútorpiacon. Acta Silvatica Lignaria Hung 6:75–88

Google Scholar  

Bell E, Bryman A, Harley B (2018) Business research methods. Oxford University Press.

Berman B, Pollack D (2021) Strategies for the successful implementation of augmented reality. Bus Horiz 64(5):621–630. https://doi.org/10.1016/j.bushor.2021.02.027

Booth WC, Booth WC, Colomb GG, Colomb GG, Williams JM, Williams JM (2003) The raft of research. University of Chicago Press.

Bryman A (2016) Social research methods, 4th edn. Oxford university press.

Choudhury A, Behl A, Sheorey PA, Pal A (2021) Digital supply chain to unlock new agility: a TISM approach. Benchmarking 28:2075–2109. https://doi.org/10.1108/BIJ-08-2020-0461 .

Chowdhury P, Paul SK, Kaisar S, Moktadir MA (2021) COVID-19 pandemic related supply chain studies: a systematic review. Transp Res Part E 148, 102271. https://doi.org/10.1016/j.tre.2021.102271

Cisco (2012) Annual report 2012. https://www.cisco.com/c/dam/assets/cdc_content_elements/docs/annualreports/ar2012.pdf

Cleveland M, McCutcheon G (2022) ‘Antiglobalscapes’: a cross-national investigation of the nature and precursors of consumers’ apprehensions towards globalization. J Bus Res 138:170–184. https://doi.org/10.1016/j.jbusres.2021.09.011

Corbin J, Strauss A (2014) Basics of qualitative research: techniques and procedures for developing grounded theory. Sage publications.

Creswell JW (2014) Qualitative, quantitative and mixed methods approaches. Sage.

Cruz-Cárdenas J, Zabelina E, Guadalupe-Lanas J, Palacio-Fierro A, Ramos-Galarza C (2021) COVID-19, consumer behavior, technology, and society: a literature review and bibliometric analysis. Technol Forecast Soc Change 173:121179. https://doi.org/10.1016/j.techfore.2021.121179

Article   PubMed   PubMed Central   Google Scholar  

Data.gov.sg. (2020) Online shoppers. https://data.gov.sg/dataset/online-shoppers

Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 319–340.

Gauri DK, Jindal RP, Ratchford B, Fox E, Bhatnagar A, Pandey A, Navallo JR, Fogarty J, Carr S, Howerton E (2021) Evolution of retail formats: past, present, and future. J Retail 97(1):42–61. https://doi.org/10.1016/j.jretai.2020.11.002

Hoyer WD, Kroschke M, Schmitt B, Kraume K, Shankar V (2020) Transforming the customer experience through new technologies. J Interact Mark 51:57–71

Huseien GF, Shah KW (2022) A review on 5G technology for smart energy management and smart buildings in Singapore. Energy AI 7:100116. https://doi.org/10.1016/J.EGYAI.2021.100116

Jackson SL (2015) Research methods and statistics: a critical thinking approach. Cengage Learning.

Jafari-Sadeghi V, Garcia-Perez A, Candelo E, Couturier J (2021) Exploring the impact of digital transformation on technology entrepreneurship and technological market expansion: the role of technology readiness, exploration and exploitation. J Bus Res 124:100–111

Jain R, Jain K, Behl A, Pereira V, Del Giudice M, Vrontis D (2022) Mainstreaming fashion rental consumption: a systematic and thematic review of literature. J Bus Res 139:1525–1539. https://doi.org/10.1016/J.JBUSRES.2021.10.071

Jayawardena NS, Ross M, Quach S, Behl A, Gupta M, Lang LD (2022) Effective online engagement strategies through gamification: a systematic literature review and a future research agenda. J Global Inf Manag 30(5):1–25. https://doi.org/10.4018/JGIM.290370

Jessen A, Hilken T, Chylinski M, Mahr D, Heller J, Keeling DI, de Ruyter K (2020) The playground effect: how augmented reality drives creative customer engagement. J Bus Res 116:85–98. https://doi.org/10.1016/j.jbusres.2020.05.002

Lee (2020) Re-imagining and improving the customer experience. https://www.fortytwo.sg

Matarazzo M, Penco L, Profumo G, Quaglia R (2021) Digital transformation and customer value creation in made in Italy SMEs: a dynamic capabilities perspective. J Bus Res 123:642–656. https://doi.org/10.1016/J.JBUSRES.2020.10.033

Miller NJ, Schofield-Tomschin S, Kim S (1998) Consumers’ apparel and home furnishings inshopping behavior in rural communities. Cloth Text Res J 16(4):157–166. https://doi.org/10.1177/0887302X9801600402

Mims C (2017) Amazon is leading tech’s takeover of America. Available at: https://www.wsj.com/articles/amazon-is-leading-techs-takeover-of-america-1497653164 (Accessed: 9 December 2020).

Moreno-Llamas A, García-Mayor J, De la Cruz-Sánchez E (2020) The impact of digital technology development on sitting time across Europe. Technol Soc 63:101406

Moreno DP, Hernández AA, Yang MC, Otto KN, Hölttä-Otto K, Linsey JS, Wood KL, Linden A (2014) Fundamental studies in Design-by-Analogy: a focus on domain-knowledge experts and applications to transactional design problems. Des Stud 35(3):232–272

Novy J, Colomb C (2016) Urban tourism and its discontents. In: Colomb C, Novy J (eds.) Protest and resistance in the tourist city. Routledge.

O’leary Z (2017) The essential guide to doing your research project. Sage.

Ponder N (2013) Consumer attitudes and buying behavior for home furniture. Mississippi. Available at: http://ffi.msstate.edu/pdf/consumer_attitudes.pdf%0A .

Saunders M, Lewis P, Thornhill A (2009) Research methods for business students. Pearson education.

Shankar A, Gupta M, Tiwari AK, Behl A (2021) How does convenience impact showrooming intention? Omnichannel retail strategies to manage global retail apocalypse. J Strateg Mark 1–22. https://doi.org/10.1080/0965254X.2021.1965189

Sharma VM, Klein A (2020) Consumer perceived value, involvement, trust, susceptibility to interpersonal influence, and intention to participate in online group buying. J Retail Consum Serv 52:101946

Sheth J (2020) Impact of Covid-19 on consumer behavior: will the old habits return or die? J Bus Res 117:280–283

Singapore Economic Development Board (2018) Singapore Economic Development Board 2018, Singapore:E-COMMERCE Gateway to ASEAN and Southwest Pacific. Available at: http://repositorio.unan.edu.ni/2986/1/5624.pdf. (Accessed: 1 December 2020)

Skare M, Riberio Soriano D (2021) How globalization is changing digital technology adoption: an international perspective. J Innov Knowl 6(4):222–233. https://doi.org/10.1016/J.JIK.2021.04.001

Studio B (2012) Polaków wydatki na meble http://brstudio.eu/polakow-wydatki-na-meble-2012-2015/

Trenerry B, Chng S, Wang Y, Suhaila ZS, Lim SS, Lu HY, Oh PH (2021) Preparing workplaces for digital transformation: an integrative review and framework of multi-level factors. Front Psychol 12:1–24. https://doi.org/10.3389/fpsyg.2021.620766

Usai A, Fiano F, Messeni Petruzzelli A, Paoloni P, Farina Briamonte M, Orlando B (2021) Unveiling the impact of the adoption of digital technologies on firms’ innovation performance. J Bus Res 133:327–336. https://doi.org/10.1016/J.JBUSRES.2021.04.035

Whitelaw S, Mamas MA, Topol E, van Spall HGC(2020) Applications of digital technology in COVID-19 pandemic planning and response. Lancet Digit Health 2:e435–e440. https://doi.org/10.1016/S2589-7500(20)30142-4

Wilmarth MJ, Milstead SM (2020) Theses and dissertations completed in family and consumer sciences: 2019. Fam Consum Sci Res J 49(2):183–200. https://doi.org/10.1111/fcsr.12379

Wiśniewska A, Paginowska A (2006) Research on the furniture market in Poland. Research knowledge of furniture brands and elements of the decision-making process among individual customers. Ogólnopolska Chamber of Commerce of Furniture Manufacturers.

Zwierzyński P (2018) The determinants of consumer behaviours in the furniture market. Ann Mark Manag Econ 3(1):131–143. https://doi.org/10.22630/amme.2017.3.1.12

Download references

Author information

Authors and affiliations.

Amity Global Institute, Singapore, Singapore

• Easwaramoorthy Rangaswamy

Kingdom University, Riffa, Bahrain

Nishad Nawaz

FortyTwo Pte. Ltd., Singapore, Singapore

Zhou Changzhuang

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Nishad Nawaz .

Ethics declarations

Ethical approval.

The procedures used in this study adhere to the principles of the Declaration of Helsinki. The study was conducted according to the guidelines of the Declaration of Helsinki and was approved by the ethics committee of the authors’ affiliate institution.

Informed consent

All study participants provided informed consent.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Rangaswamy, E., Nawaz, N. & Changzhuang, Z. The impact of digital technology on changing consumer behaviours with special reference to the home furnishing sector in Singapore. Humanit Soc Sci Commun 9 , 83 (2022). https://doi.org/10.1057/s41599-022-01102-x

Download citation

Received : 11 October 2021

Accepted : 23 February 2022

Published : 15 March 2022

DOI : https://doi.org/10.1057/s41599-022-01102-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Digitization and the shaping of society – a soft systems study.

• Frank Stowell

Systemic Practice and Action Research (2024)

The evaluation of challenges and impact of digitalisation on consumers in Singapore

• Wong Sin Yong
• Gemini V. Joy

International Journal of System Assurance Engineering and Management (2023)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Elsevier - PMC COVID-19 Collection

COVID-19, consumer behavior, technology, and society: A literature review and bibliometric analysis

Jorge cruz-cárdenas.

a Research Center in Business, Society, and Technology, ESTec, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador

b School of Administrative and Economic Science, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador

Ekaterina Zabelina

c Department of Psychology, Chelyabinsk State University, Bratiev Kashirinykh 129, 454001 Chelyabinsk, Russia

Jorge Guadalupe-Lanas

Andrés palacio-fierro.

d Programa doctoral en Ciencias Jurídicas y Económicas, Universidad Camilo José Cela, Castillo de Alarcón, 49, 28692 Madrid, Spain

Carlos Ramos-Galarza

e Facultad de Psicología, Universidad Católica del Ecuador, Av . 12 de octubre 1076, 170523, Quito, Ecuador

f Centro de Investigación MIST, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador

Associated Data

The COVID-19 crisis is among the most disruptive events in recent decades. Its profound consequences have garnered the interest of many studies in various disciplines, including consumer behavior, thereby warranting an effort to review and systematize the literature. Thus, this study systematizes the knowledge generated by 70 COVID-19 and consumer behavior studies in the Scopus database. It employs descriptive analysis, highlighting the importance of using quantitative methods and China and the US as research settings. Co-occurrence analysis further identified various thematic clusters among the studies. The input-process-output consumer behavior model guided the systematic review, covering several psychological characteristics and consumer behaviors. Accordingly, measures adopted by governments, technology, and social media stand out as external factors. However, revised marketing strategies have been oriented toward counteracting various consumer risks. Hence, given that technological and digital formats mark consumer behavior, firms must incorporate digital transformations in their process.

1. Introduction

The COVID-19 pandemic is among the most relevant events of recent decades. Its social and economic consequences on a global level are enormous. At the social level, the World Health Organization (WHO) has reported over four million global deaths due to COVID-19 ( WHO, 2021a ). Economies have also been severely affected ( Donthu and Gustafsson, 2020 ). The International Monetary Fund (IMF) predicts that the gross domestic product, worldwide, will plummet to about 4.9% in 2020 ( IMF, 2020 ). These remarkable social and economic implications of the pandemic and its unique features have inspired many studies from various disciplines, including consumer behavior. The crisis scenario has profoundly shifted consumer behavior toward one based on technology ( Sheth, 2020 ).

In prior pandemics, social and behavioral science research focused heavily on preventive and health behavior, while consumer behavior received less attention ( Laato et al., 2020 ). The situation has been different for the COVID-19 pandemic; COVID-19 and consumer behavior studies proliferate the literature. Reasonably, such rapidly accumulating bodies of knowledge require organization and systematization, lest such knowledge produced in fast-growing fields remains fragmented ( Snyder, 2019 ). Thus, this study fulfills this need by identifying knowledge generated by 70 relevant studies in the Scopus database, indexed up to January 5, 2021, for systematic processing.

Prior theoretical efforts created a global and general perspective of consumer behavior during the COVID-19 pandemic. Such efforts have sought to propose possible stages in behavior, comparing old and new consumption habits, or explain behaviors based on similarities with other crises and disruptive events, such as other pandemics, wars, or natural disasters (e.g., Kirk and Rifkin, 2020 ; Sheth, 2020 ; Zwanka and Buff, 2020 ). However, this study is evidently among the first to review the literature on COVID-19 and consumer behavior. The study is necessary because, beyond its similarities with other disruptive events, the COVID-19 crisis has several fundamental differences. First, it is truly global ( Brem et al., 2020 ). Second, it coincides with the rapid advance of various disruptive technologies, the confluence of which has been called “digital transformation” ( Abdel-Basset et al., 2021 ).

First, the study conducts descriptive and bibliometric analyses of the 70 selected COVID-19 and consumer behavior articles. Second, an input-process-output consumer behavior model is used to systematize the existing literature. The model, adapted by Cruz-Cárdenas and Arévalo-Chávez (2018) from Schiffman and Wisenblit (2015) for systematic reviews, furnished a comprehensive understanding of the pandemic-era consumer behavior via macro-environmental, micro-environmental, and internal-consumer-factor integration.

Accordingly, government regulations and technology stand out as fundamental forces at the macro level. At the micro-level, specific technological applications like social media and business platforms, social group and family pressure, and marketing strategies stand out. Meanwhile, many personal and psychological characteristics help us to understand how consumers process external influences and make decisions at the consumer level. Finally, regarding purchasing behaviors, the use and adoption of technologies like e-commerce platforms have had a prominent place in consumer behavior during the pandemic.

The remainder of this paper is organized as follows. Section 2 presents the construction of a theoretical framework on consumer behavior and disruptive events. The method is explained in Section 3 . Section 4 presents the descriptive and co-occurrence bibliometric technique results of generating an understanding of the literature interrelationships and characteristics. Section 5 documents the systematization and grouping of the knowledge generated based on an input-process-output model of consumer behavior. Finally, Section 6 concludes with the main implications and scope for future research.

2. Consumer behavior and disruptive events

Many consumer and human behavior studies in the context of disruptive events precede the COVID-19 pandemic. The term “disruptive event” is a situation that leads to profound changes regarding the unit analyzed ( Dahlhamer and Tierney, 1998 ). Thus, it can apply to individual consumers, organizations, industries, or society. Disruptive events can also be classified by their nature (e.g., pandemic, war, natural disaster, and personal calamity).

At the personal level, prior studies establish that in the aftermath of calamities or unfavorable events, such as the death of loved ones, divorces, and illness, consumers get rid of products that remind them of difficult times and, thus, buy new products ( Cruz-Cárdenas and Arévalo-Chávez, 2018 ). Although such disruption studies are interesting, they fail to shed enough light on consumer behavior during the COVID-19 crisis. On a larger scale, past disruptive events—such as other pandemics, natural disasters, or extreme social violence and terrorism—can contribute to understanding the pandemic-induced consumer behavior, because they affect a greater number of consumers simultaneously and in similar fashion.

Natural disasters like earthquakes, floods, hurricanes, and typhoons are frequent. They cause damage to infrastructure, economy, and human lives, thereby creating a permanent field of consumer behavior studies. Some natural disasters are carefully monitored, and their arrival and intensity can be anticipated (e.g., hurricanes). The anticipation of such events induces a behavior of stockpiling basic necessities ( Pan et al., 2020 ). Others cannot be anticipated in the short term (e.g., earthquakes). In both types of natural disasters, consumers may lose possessions and loved ones. The feeling of loss induces impulsive, therapeutic, and replacement purchases ( Delorme et al., 2004 ; Sneath et al., 2009 ). Natural disasters are primarily noted for their destructiveness and scope, which can reach regional levels.

Extreme social violence and so-called terrorism constitute another category of disruptive events affecting a country or region. Terrorism comprises violent actions by a group with less power that seeks to destabilize a government or a dominant organization ( Bates and LaBrecque, 2019 ). Such violent actions often impact human lives and negatively affect the economy and physical infrastructure. Moreover, their intensity and frequency in society are highly variable.

Although terrorist actions significantly affect the economy and infrastructure, the impact on consumer behavior is in the short term ( Baumert et al., 2020 ; Crawford, 2012 ), which induces an avoidant behavior, due to certain consumption options they consider to be of greater risk; that is, consumers choose an alternative option rather than give up their plans or consumption ( Herzenstein et al., 2015 ) (e.g., the choice between air and land travel or a destination change for tourism). The selection of consumption alternatives hinges on past events and anticipated threats ( Baumert et al., 2020 ).

Prior outbreaks from recent decades like SARS, Influenza A, and H1N1 present another type of disruptive event, which consumer behavior scholars have largely ignored ( Laato et al., 2020 ). Current knowledge on human behavior during disease outbreaks stems from other social and human sciences. Thus, two consumption-behavior types have been noted: purchasing necessities and protective equipment, and curbing leisure outside the home. For example, Goodwin et al. (2009) find that the purchase of protective items (e.g., masks and personal hygiene items) and food rose significantly during the influenza A, and H1N1 outbreaks, as people engaged in stockpiling. However, regarding SARS in China, Wen et al. (2005) found that people altered their leisure activities, modes of transportation, and the places they visited. Table 1 summarizes the features of prior disruptive events and the relevant knowledge regarding consumer behavior therein.

Disruptive events, their characteristics, and effects on the consumer.

The COVID-19 pandemic, like other prior disruptive events, has significantly impacted the economy and human life ( IMF, 2020 ; WHO, 2021a ). However, unlike natural disasters and terrorism, it (similar to prior disease outbreaks) does not damage physical infrastructure. Further, it is characterized by its persistence (the current pandemic has continued for a year and a half). Even so, the COVID-19 pandemic is unique in its global scope ( WHO, 2021b ). Moreover, it occurs within the context of significant technological advancement, known in the business and organizational world as “digital transformation” ( Abdel-Basset et al., 2021 ).

Against this comparison, prior to the systematic review, consumer behaviors reported in other disruptive events probably occurred on a large scale. However, the scope of the COVID-19 pandemic and technological advancement is expected to provide a distinctive character to consumer behavior, caught between the unique confluences of the two.

This study was developed in a series of stages, common to systematic literature reviews ( Balaid et al., 2016 ; Cruz-Cárdenas and Arévalo-Chávez, 2018 : Osobajo and Moore, 2017 ) (see Fig. 1 ).

Stages of this study.

3.1 Study objectives

Regarding Stage 1, this study primarily describes and systematizes the existing literature on consumer behavior during the COVID-19 pandemic. This objective can be broken down into three specific objectives. Thus, this study aims

• • O1: To describe the characteristics and interrelationships of relevant studies
• • O2: To generate a structured systematization of their contents and results
• • O3: To establish the limitations and gaps in existing knowledge, thereby ascertaining the scope for future lines of research

Accordingly, recognizing the multidisciplinary nature of consumer behavior, researchers from marketing, business administration, psychology, and economics teamed up to bring together experts in diverse research methodologies, such as machine learning and big data techniques. The study commenced when COVID-19 became a pandemic in March 2020.

3.2 Criteria for inclusion of articles

The study developed several article-inclusion criteria. Importantly, studies must address COVID-19 only from the perspective of consumer behavior. Thus, it was important to differentiate consumer behavior from other types of human behavior in the COVID-19 framework. Consumer behavior encompasses people's behavior in their search, purchase, usage, and disposal of goods and services ( Schiffman and Wisenblit, 2015 ). Further, articles must have an acceptable quality level, be written only in English, and have no time restriction on the date of their publication.

3.3 Search strategies

The search strategies were then developed, operationalizing the inclusion criteria. The study drew from the Scopus database, which offers a good balance between quality and coverage ( Singh et al., 2020 ). The search terms aimed to extract two central contents simultaneously: the COVID-19 pandemic and consumer behavior. The search process was initiated with the following terms: Covid AND (consum* AND behav*). The asterisk in the terms allowed for including variants of the keywords such as: consumer, consumers, consumption behavior, and behavior. Additionally, the search scanned the titles, abstracts, and keywords of the documents.

As the search process progressed, other terms were added, because they were also used significantly by relevant articles; this was particularly important because there was no consensus regarding the name for the pandemic at its inception. Hence, regarding the pandemic, alternative terms included “Covid-19,” “Sars-Cov-2,” “Pandemic,” and “Coronavirus.” Similarly, regarding consumer behavior, “marketing,” “purchasing,” “shopping,” and “buying” were the alternative terms.

The search process involved reading the titles and abstracts of the outputs generated for an initial and main debugging. A second purification was then conducted. Among the biggest search challenges was that, although some articles addressed consumer behavior and included “Covid” or its synonyms in their titles, keywords, and abstracts, as well as their topic incorporation, they were unclear. The situation is attributed to a temporal coincidence with the COVID-19 crisis, rather than a deliberate intention of studying its effects on consumer behavior. From the start of the study to its culmination on January 5, 2021, 347 articles were reviewed, of which 70 relevant articles were selected after satisfying the inclusion and search criteria.

3.4 Method describing and systematizing the literature

The study employed various bibliometric and literature systematization techniques, to describe the characteristics and interrelationships of the 70 articles and systematize their content. Bibliometric techniques estimated the main descriptive statistics of the relevant body of knowledge. Further, a visual analysis of co-occurrence was performed.

The study used content analyses of the generated knowledge and findings to systematize the literature ( Kaur et al., 2021 ), seeking a knowledge organization structure. The search focused on identifying a widely accepted model of consumer behavior. Thus, the selected model was the input-process-output model of Schiffman and Wisenblit (2015) , modified by Cruz-Cárdenas and Arévalo-Chávez (2018) to apply to literature reviews on consumer behavior topics. This model is employed in empirical research (e.g., Ting et al., 2019 ).

Fig. 2 presents the generic model. The left of the model presents the external influences or stimuli, processed and interpreted as per the personal and psychological characteristics of the consumer at the center of the model. The consumer also follows a decision-making process. Finally, the right of the model yields the results or outputs: the purchase and post-purchase behaviors. Furthermore, this study incorporates arrows connecting macro-environmental to micro-environmental forces, marketing strategies, and the consumer. It highlights that the macro-environment spans the entire model ( Kotler and Keller, 2016 ).

Generic model of consumer behavior. Adapted from Schiffman and Wisenblit (2015) and Cruz-Cárdenas and Arévalo-Chávez (2018) .

4. Descriptive and bibliometric analysis

4.1 descriptive analysis of relevant articles.

Table A.1 presents the 70 relevant articles, among which 57 were published in 2020; 12, 2021; and one, in press. Fig. 3 shows the number of articles per their methodology. Most articles (58 articles or 82.9%) employ quantitative empirical approximations, followed by studies with a theoretical approach (five articles or 7.1%). Notably, few studies employed qualitative or mixed methods (5.7% and 4.3%, respectively).

Number of articles according to their methodology.

This marginal use is likely for the following reasons. First, societies and funders exert time constraints for fast and conclusive results. Second, there are many studies on consumer behavior and the adoption of technologies before the COVID-19 pandemic. Third, the rise in machine learning methods, particularly natural language processing, allows for processing significant textual social media data using artificial intelligence ( Géron, 2019 ).

Considering only the 65 empirical studies, Fig. 4 presents the main countries where data was collected. China has 15 articles (23.1%), followed by the US, with seven articles (10.8%), and Italy, five articles (7.7%). Next are India, Romania, the UK, and Vietnam, each with three articles (4.6%). Others attracted 15 articles (23.1), and 11 articles (16.9%) had several countries simultaneously as study settings, either because they deliberately chose several countries or studied social media. China's dominance as a study setting can be attributed to its status as the origin of the pandemic. However, it can also be attributed to China's rapid growth in the scientific field.

Number of empirical articles according to their study setting.

Table 2 presents the journals in which the articles were published. Most articles appeared in three major journals: Sustainability had seven articles (10%), and the International Journal of Environmental Research and Public Health and the Journal of Retailing and Consumer Services each had five articles (7.1%), respectively. Notably, several journals not traditionally linked to consumer studies or marketing are represented, probably because of the multidisciplinary character of consumer studies ( Schiffman and Wisenblit, 2015 ).

Journals in which reviewed articles were published.

While the selected articles examined various products, food was the main preference in 29 articles (41.4%). Other products, studied to a lesser extent, included personal hygiene items, hotels, and the banking sector. Further, the studies widely employed two theories: the theory of planned behavior (TPB) ( Ajzen, 1991 ) and the technology acceptance model (TAM) ( Davis, 1989 ).

TPB stems from psychology, and it asserts that attitude toward behavior (personal view on behavior), subjective norm (perceived social pressure to act), and perceived behavioral control (difficulty in acting) determine the intention of a person to act out a behavior. This behavioral intention then determines whether the behavior occurs ( Ajzen, 1991 ). TAM stems from Information Technology and draws from TPB; it indicates that a user's acceptance of new technology is determined by the perceived usefulness and ease of use ( Davis, 1989 ). TPB and TAM are general theories that allow for much flexibility in application. The two theories and their many variants are widely used in consumer behavior research and, particularly, cases of a new product, service, and technology acceptance ( Lin and Chang, 2011 ; Schmidthuber et al., 2020 ).

Considering the prevalence of TPB and TAM, and their variants in consumer studies prior to COVID-19 (particularly regarding technologies) coupled with the massive popularity of technologies during the pandemic ( Baicu et al., 2020 : Sheth, 2020 ), the dominance of the two theories in this study is not surprising. Furthermore, they also explain the popularity of quantitative methods in the selected studies, and by specifying a set of directional relationships, they allow for testing the proposed models via structural equation modeling ( Kline, 2016 ). The studies reviewed largely model consumer purchasing behaviors in technological environments and include fear or concern about COVID-19 as an additional variable, either in an exogenous or moderating variable role.

4.2 Analysis of the co-occurrence

The study employed co-occurrence analysis to establish the topics of interest in the set of articles on COVID-19 and consumer behavior. The analysis was performed in two ways to obtain more reliable results: keyword-based and title- and abstract-based.

First, we sought to identify the clusters formed based on the co-occurrence of keywords in the set of articles ( Singh et al., 2020 ). We employed VOSviewer 1.6.15 ( VanEck and Waltman, 2010 ) for this analysis. VOSviewer suggests, by default, a minimum number of five occurrences for a term to be considered. However, we set this number to three, given the relatively small number of articles. Generic terms like “article” and “study” were removed during the data cleanup. Additionally, similar terms were grouped into a single term ( van Eck and Waltman, 2010 , 2020 ), such as “Covid-19,” “Covid,” and “pandemic.” Fig. 5 shows the obtained clusters. The nodes represent keywords or concepts, while their size corresponds with their frequency ( van Eck and Waltman, 2010 , 2020 ). VOSviewer represents each cluster of keywords or concepts with a different color.

Co-occurrence network of articles based on keywords.

Cluster 1 (yellow) has “consumer behavior” as a prominent node and groups together other keywords such as “social distance,” “social media,” and “electronic commerce.” Thus, the cluster is related to purchasing behavior during the COVID-19 pandemic, which is strongly marked by technology use. Cluster 2 (green) has the term “COVID-19″ as its central node. It gathers terms such as “public health,” “food waste,” “food consumption,” “sustainability,” and “panic buying.” Hence, this cluster regards the consumption and handling of food during the COVID-19 pandemic. Cluster 3 (blue) has no central node. However, “fear,” “decision making,” and “purchasing” suggest a cluster focused on the purchase decision process. Finally, Cluster 4 (red), while without a prominent node, is the most prevalent. Terms such as “materialism,” “adult,” “attitude,” and “psychology,” “government,” and “economics” suggest that this cluster is mainly about macro, micro, and internal influences on the consumer.

Further, to allow for greater context richness, the second analysis was based on the titles and abstracts of selected articles ( VanEck and Waltman, 2010 ). Similar to the procedure based on keywords and with the same criteria, the minimum number of occurrences of words was set to three. The data was also cleaned by elimination or grouping ( VanEck and Waltman, 2010 ). For example, generic or irrelevant words, such as “article,” “item,” “author,” and “study,” were eliminated. However, similar terms were grouped together, as in the case of “covid,” “covid-19,” and “pandemic.” Fig. 6 shows the results of the co-occurrence analysis based on titles and abstracts.

Co-occurrence network of articles based on titles and abstracts.

The analysis generated four clusters. Cluster 1 (red) had “consumer behavior” as a prominent node and included other terms like “risk perception,” “threat,” “panic buying,” “impulsive buying,” and “China.” Thus, this cluster is related to consumer panic buying. Cluster 2 (green) had as prominent nodes “service,” “emergency,” “purchasing,” and technology-related actions, such as “online shopping,” “e-commerce,” and “internet.” Hence, it regards consumer behavior and the use of technology in purchases. Cluster 3 (blue) featured “food” as a prominent node and included other terms like “stockpiling,” “covid lockdown,” “covid outbreak,” and “policymaker.” Therefore, this cluster focused on consumer behavior in the purchase and handling of food under lockdown conditions. Cluster 4 (yellow) did not have particularly prominent nodes. It included customer,” “infection,” “policy,” “home,” “uncertainty,” “business,” and “reduction,” showing that this cluster refers to the consumer subject to macro, micro, and internal influences.

The analysis of co-occurrence of keywords is similar to that of titles and abstracts in the dominance of the reviewed studies on Covid-19 and consumer behavior, thus increasing the confidence in the results. Accordingly, three fundamental areas can be identified: consumer behavior and technology use; purchasing and handling basic necessities, particularly food; and consumer subject to internal and external (micro and macro) forces. A possible fourth area may induce a discrepancy, putting the keyword analysis emphasis on the decision-making process and the analysis of titles and abstracts in panic purchases.

5. Systematization of the relevant literature

This section presents the analysis and systematization of the 70 relevant studies. The authors used content analysis techniques to identify the main findings from the literature ( Kaur et al., 2021 ). The relevant content is organized using the structure of the consumer behavior model in Fig. 2 .

5.1 Macro-environmental factors

Macro-environmental factors affect the entire analytical micro-environment ( Kotler and Keller, 2016 ). In this study, the micro-environment is built around the consumer, the center of the analysis. The consumer micro-environment is formed by organizations and groups of people close to the consumer (e.g., companies, the media, family, and friends).

Regarding COVID-19 and consumer behavior, five macro forces are fundamental: the COVID-19 pandemic and the technological, political-legal, economic, and socio-cultural environments. High importance is attached to COVID-19, the technological environment, and the politico-legal environment. Various studies indicate how the COVID-19 and available technology confluence has induced consumers to massively and rapidly adopt technologies and increase their consumption of highly digital business formats ( Baicu et al., 2020 : Sheth, 2020 ). Specifically, e-commerce and business platform formats solved possible shortage problems and allowed consumers to accumulate products ( Hao et al., 2020 ; Pillai et al., 2020 ). Further, the technology allowed social lives to thrive amidst the pandemic, reflecting the increased use of social media platforms ( Pillai et al., 2020 ).

The political-legal environment is strongly intertwined with economic performance. Significant legal regulations by many governments were enforced during quarantines, lockdowns, social distancing, and educational service closure ( Yoo and Managi, 2020 ). However, not all governments resorted to lockdown measures. Regardless, economies fell in many areas because of consumer decisions ( Sheridan et al., 2020 ). However, food and hygiene item purchases increased. In non-lockdown (lockdown) countries, consumers were guided by caution (anxiety and fear were) ( Anastasiadou et al., 2020 ; Prentice et al., 2020 ).

Another very important aspect derived from the political-legal environment is trust in government institutions. Increased confidence in governments and their actions made consumers less likely to experience fear of food shortages and engage in panic buying ( Dammeyer, 2020 ; Jeżewska-Zychowicz et al., 2020 ). Effective public announcements moderated the effects of negative feelings, such as anxiety and a sense of losing control in terms of panic buying ( Barnes et al., 2021 ).

A diagnosis of the state of knowledge on macro-environmental factors allows for seeing a significant amount of research on political-legal and technological factors. However, the COVID-19 crisis is dynamic. Currently, many governments have halted lockdown measures, betting more on social distancing as a new mass vaccination phase emerges, which is worthy of exploration. Further, few studies address cultural issues during the COVID-19 crisis, even though culture is another determining force in consumer behavior.

5.2 Micro-environmental factors

As noted, the political-legal macro-environment of the COVID-19 pandemic is marked by lockdown and social distancing measures, while the digital transformation process marks the technological macro-environment. A logical consequence of their interaction is that the micro-environment (family, friends, acquaintances, society, the media, and companies) interacts with consumers through technology and digital media. Section 5.3 will discuss consumer interaction with businesses and companies.

During the COVID-19 crisis, consumers use information as a valuable factor in decision-making, as they actively or passively seek it. Social media is a common source of information. Popular topics regard food acquisition and storage, health issues, social distancing, and economic issues ( Laguna et al., 2020 ). However, social media also induces panic buying, especially during lockdowns. Advice from associates, product shortage perceptions, the COVID-19 spread, official announcements, and global news inspired this behavior ( Ahmend et al., 2020 ; Grashuis et al., 2020 ; (Jeżewska-Zychowicz et al., 2020) ; Naeem, 2021a ). Further, the news, social media, and associates also influence technology use in purchases on company pages, platforms, or apps ( Koch et al., 2020 ; Troise et al., 2021 ).

Therefore, despite contributing to panic buying, the mainstream news media and social media have also curbed the spread of COVID-19 ( Liu et al., 2021 ). The extensive knowledge on the micro-environmental effects on consumer behavior was generated primarily due to previous non-relevant studies that focused on social media; they created a solid base of departure.

5.3 Marketing strategies and influences

Marketing influences are in the consumer's micro-environment. They are vital, because they are tools that companies can design and control. Thus, consumer behavior models usually consider them separately from other influences, such as those discussed in the preceding section. The main marketing tool is the product or service. Others are prices, distribution, and communication strategies.

Two key elements of marketing strategies during the pandemic are reducing various risks and increasing benefits perceived by the consumer. Two central risks marketing strategies must address are the risks of coinfection and conducting online transactions. Further, the reviewed studies address the forms of action regarding the two types of risks. Thus, while the perceived COVID-19 risk increases the probability of online purchases, the perceived risk of online purchases moderates this relationship ( Gao et al., 2020 ).

Accordingly, using technology to digitize processes or products, and reduce physical contact with employees or other consumers, has encouraged consumer purchases during the COVID-19 pandemic. For example, technology that allows consumers to make reservations via smartphones or kiosks reduces the perceived health risk, thereby increasing the probability of hotel reservations ( Shin and Kang, 2020 ). Moreover, state-of-the-art cleaning technology moderates the negative effect of staff interaction on service use intentions ( Shin and Kang, 2020 ). Thus, technology guarantees cleanliness and minimal contact for the consumer. Further, the perceived risk of online transactions involves the possible misuse of personal information and financial fraud ( Tran, 2021 ). Marketing strategies to reduce this risk have focused on building trust and image ( Lv et al., 2020 ; Troise et al., 2021 ). Regarding the strategy duration, other recommended marketing strategies for e-commerce sites and platforms with less renown are increasing profits or reducing prices ( Lv et al., 2020 ; Tran, 2021 ).

During the lockdowns in most countries, consumer demand centered on food products, personal hygiene, and disinfection. Thus, implementing or increasing promotions of non-priority items is a recommended strategy ( Anastasiadou et al., 2020 ). Finally, regarding small businesses that use technology less intensively, the speed of adaptation and digital transformation are vital, even at basic levels. Many small businesses have survived by adopting elementary digital transformation strategies in the form of a mix of social media sales and home delivery services ( Butu et al., 2020 ).

Hence, although there are interesting results, the transcendental importance of studies on marketing strategies within the framework of consumer studies deserves more research. Further, since the pandemic is dynamic, companies must adapt their strategies constantly. Notably, few studies employ case studies or experimental methodologies, which are appropriate for studying the effects of marketing strategies.

5.4 Personal and psychological characteristics and decision-making

Most of the reviewed studies stemmed from this area. The personal characteristics of consumers (e.g., age, gender, income, and educational level) and their psychological characteristics (e.g., motivation, perception, and attitudes) determine how they interpret stimuli ( Schiffman and Wisenblit, 2015 ).

For instance, many studies address gender. There is no consensus about which gender makes the most panic purchases. A study carried from Brazil reports that men tend to make the most panic purchases ( Lins and Aquino, 2020 ), while a study in China ( Wang et al., 2020a ) attributes this behavior to women. However, another study in several European countries found gender differences irrelevant in the tendency to make extra purchases ( Dammeyer, 2020 ). The inconsistency may be attributable to cultural issues; however, the methodology may also have a bearing on the conflicting results. For example, while the study by Lins and Aquino (2020) asked respondents about purchasing products in general, Wang et al. (2020a) focused on food, and Dammeyer (2020) on food, medicine, and hygiene items. The same discrepancy in gender issues and panic purchases extends to the age variable. Some studies found that age is negatively related to the tendency to panic buy ( Lins and Aquino, 2020 ), while other studies found no relationship at all (e.g., Dammeyer, 2020 ).

Many studies also examine the pandemic-induced negative psychological states and feelings. The perceived risk and information overload regarding COVID-19, led to sadness, anxiety, and cognitive dissonance ( Song et al., 2020b ). The perceived severity of the pandemic leads to self-isolation ( Laato et al., 2020 ). The negative psychological states that the consumer experiences, are associated with hoarding behavior. Excessive concern regarding health leads to excessive purchasing and stockpiling of food and hygiene items ( Laato et al., 2020 ). While negative emotions encourage excessive purchases, particularly the purchasing of necessities, they also discourage them from consuming services that involve contact. For example, the fear of contracting COVID-19 has been central to avoiding air transport during the pandemic ( Lamb et al., 2020 ).

Consumer personality traits were also critical to understanding consumer behavior during the COVID-19 crisis. Extraversion (conscientiousness) and neuroticism (openness to experience) were positively (negatively) associated with extra purchases ( Dammeyer, 2020 ). Another personality trait, such as agreeableness (sympathetic or considerate), led to the renunciation of consumption. Consumers with high scores on this trait gave up consumption that could negatively affect third parties ( Lamb et al., 2020 ).

The pandemic has also encouraged favorable attitudes among consumers, be they pro-environmental or pro-health attitudes. The fear of COVID-19 and the uncertainty it brings has a positive effect on people's pro-environmental attitudes, which, in turn, increase trust in green brands ( Jian et al., 2020 ). However, while consumers gave less importance to the nutritional value of food during the first months of the crisis ( Ellison et al., 2021 ), there was an increase in health awareness in later months ( Čvirik, 2020 ).

Despite great interest in consumers’ personal and psychological processes, the purchase decision-making process garnered less attention. Studies note three types of decision-making processes: impulse (e.g., Ahmed et al., 2020 ; Islam et al., 2020 ), panic (e.g., Prentice et al., 2020 ), and rational ( Wang and Hao, 2020 ) purchases.

In summary, consumer behavior, as it relates to consumers’ personal and psychological characteristics, has been widely studied, especially in its relationship with the first phases of COVID-19, characterized by lockdown and social distancing. The broad base of prior knowledge on consumer psychology and the adoption and use of technologies facilitates such studies. Here too, given the dynamic pandemic and its entry into new stages involving vaccination and social distancing, future studies must extend the discussion on personal and psychological processes. In addition, more research should be conducted on purchase decision-making processes during the COVID-19 crisis.

5.5 Purchasing behaviors

In consumer behavior models, purchasing behavior is the output of the model. This output is generated by selecting products and places or points of purchase. During the pandemic, these two behaviors were central to consumers’ strategies to ensure their own well-being.

The imposition lockdowns led to an increase in the purchase of food, beverages, hygiene items, and medicines, inducing frequent stockpiling. This behavior occurred before and during the measures and has been widely confirmed worldwide (e.g., Antonides and van Leeuwen, 2020 ; Prentice et al., 2020 ; Seiler, 2020 ;). After the lockdown and the transition to social distancing, moderate stockpiling may be expected ( Anastasiadou et al., 2020 ). Meanwhile, the consumption of goods and services in industries such as entertainment, dining, travel, and tourism decreased ( Antonides and van Leeuwen, 2020 ; Ellison et al., 2021 ; Seiler, 2020 ; Skare et al., 2021 ). Another essential aspect is the selection of the purchase method. Various purchase methods were implemented to reduce the risk of infection, among which consumers favored online purchases while making changes in their selection of physical retailers.

The lockdown and later, social distancing, inspired many consumers to rapidly adopt purchasing behaviors mediated by technology (e.g., online shopping) ( Butu et al., 2020 ), creating an “online awareness” among populations ( Zwanka and Buff, 2020 ). A digital means of purchase was extended to categories which did not have a strong online presence previously. Thus, online purchases of food, beverages, and cleaning supplies grew ( Antoides and van Leeuwen, 2020 ; Ellison et al., 2020; Hassen et al., 2020 ; Li et al., 2020b ; Wang et al., 2020b ). However, there was also an increase in the use of technology for entertainment. For example, there has been an increase in users and streaming hours on services such as Netflix and Spotify ( Madnani et al., 2020 ). Another change in consumer purchasing behavior regarded the physical point of sale. This change occurred as consumers aimed to decrease the number of trips they made to physical stores (purchase frequency) ( Laguna et al., 2020 ; Principato et al., 2020 , in press; Wang et al., 2020a ). In some countries and cities, consumers stopped buying from large retailers and places that could be crowded, preferring small local retailers instead ( Li et al., 2020b ).

Hence, there is a solid global consolidation of technology in purchasing (i.e., online shopping) and the strengthening of small local retailers. Given the dynamic nature of the COVID-19 crisis, future studies can evaluate the changes in the next stages of the pandemic.

5.6 Post-purchase behavior

Another key behavior is disposal, of which results are very interesting. During the lockdown, there is less food waste, more likely for future supply than ecological reasons ( Amicarelli and Bux, 2021 ; Jribi et al., 2020 ). However, dire health precautions increased the usage of disposable protective items, and more electronic commerce transactions increased waste created by packaging material ( Vanapalli et al., 2021 ). Thus, from a social and environmental perspective, the effects of the pandemic on product waste are mixed.

Future studies can examine product disposition and the new stages of the COVID-19 crisis. Moreover, consumer satisfaction with purchases has garnered less attention in the literature. Fig. 7 presents the model of consumer behavior during the COVID-19 crisis, summarizing the systematization of the literature.

Model of consumer behavior during the COVID-19 crisis.

5.7 Consumer behavior model under COVID-19: the near future

This subsection seeks to use the model ( Figs. 2 and ​ and7) 7 ) to anticipate consumer behaviors, given the ongoing, dynamic development of the pandemic ( WHO, 2021b ). Accordingly, the crisis thus far has induced intense consumer learning, particularly in the use of technologies (personal and psychological factors). Moreover, although technologies can satisfy both hedonic and utilitarian needs ( Cruz-Cárdenas et al., 2021 ), some consumer needs remain unsatisfied, particularly social needs (personal and psychological factors) ( Sheth, 2020 ). However, public vaccination campaigns (macro-environmental factor) and their protective effects on the population can reduce people's fear and avoidance behavior regarding certain products and services (personal and psychological factors). Further, consumers can have a greater range of consumption options (decision-making process), given their decreased fear, and due to the relaxation of restrictions on mobility and the congregation of people (macro-environmental factor). However, the trajectory of the COVID-19 pandemic (macro-environmental factor) will not be a linear process, given the appearance of new waves of infections and strains ( WHO, 2021b ).

Therefore, the new consumer behavior (output or results) will not embark on a gradual return to pre-pandemic conditions. Rather, consumer learning about technologies, attenuated avoidance behavior, and unsatisfied needs mark consumer practices that tend to combine pre-COVID-19 behaviors (some intensified by the level of unsatisfied needs) with new technology-based behaviors (e.g., use of electronic banking, e-learning, e-commerce, and social media). However, this combination of old and new consumer behaviors will likely be dynamic (in varying proportions) and creative, as consumers will have to go through new stages of the pandemic marked by uncertainty.

6. Discussion, implications, and limitations

6.1 the covid-19 pandemic versus other disruptive events: differences and similarities in their nature and consumer behavior.

The COVID-19 pandemic in the context of disruptive events affecting humanity shares traits with other disruptive events and has unique characteristics. Like any disruptive event, it has profoundly impacted societies ( Dahlhamer and Tierney, 1998 ). Among its unique characteristics are its truly global scope and occurrence within the context of the “digital transformation” technological advancement ( Abdel-Basset et al., 2021 ).

Regarding consumer behavior, comparing the study findings to behaviors observed in other disruptive events yield interesting conclusions. Impulsive and panic buying seems to be common to all disruptive events. Therapeutic purchases seem to be more linked to natural disasters, where physical possessions suffer damages. The avoidance behavior of certain products and services appears to be more linked to terrorism and pandemics. However, despite these similarities, the role of technology in shopping has induced a unique consumer behavior under COVID-19. Indeed, technology has been transversal to the different consumer behaviors under COVID-19.

Consumer behavior and COVID-19 studies are characterized by three thematic areas: consumer behavior and technology use; purchase and handling of essential, hygiene, and protective products; and internal and external influences on consumers. Notably, the current pandemic is an ongoing event that follows a non-linear trajectory (WHO, 221b). Hence, the study priorities will surely change, marked by the new stages of the pandemic. For example, in light of the vaccination campaigns, the interest of future studies in the purchase and handling of basic necessities and protection products will decline. Further, given the decreased avoidance behavior, interest in the study of fun and leisure behaviors will increase. However, the use of technologies in consumption will remain at a high profile throughout the pandemic.

6.2 The nature of consumer behavior studies under the COVID-19 pandemic

Studies examining consumer behavior under the COVID-19 pandemic exhibit unique characteristics. Prior studies on consumer behavior and other disruptive events had a significant presence of qualitative studies, given their ability to explore and thoroughly understand how certain phenomena profoundly affect people's lives ( Delorme et al., 2004 ). However, in studies on consumer behavior and COVID-19, their presence is modest, where quantitative studies dominate.

Various factors can explain the preeminence of quantitative studies; however, this subsection addresses the key factor of technology. Specifically, the confluence of intensive use of technologies by consumers during COVID-19, and the body of knowledge accumulated before the pandemic on consumer behavior and the use and adoption of technologies. Hence, this body of knowledge created a solid foundation for quantitatively oriented consumer studies. However, the existing knowledge about consumer behavior and disruptive events did not provide a solid foundation since its extension is rather modest. ( Laato et al., 2020 ).

6.3 Reassessment of pre-COVID-19 knowledge on key topics of consumer behavior and recommendation for future studies

A crucial consequence of the COVID-19 pandemic is the massive rise in the learning and use of technologies ( Baicu et al., 2020 : Sheth, 2020 ), which is unprecedented considering the global scale of the pandemic and its sustained duration. This massive and extensive learning of the use of technologies will have consequences in the validity of knowledge developed before the pandemic in key consumer behavior topics and technology use. Although there are various topics, this subsection will focus on two: Consumer segments in the use of technologies and the digital divide.

Before the pandemic, many studies in different countries apply various scales, including the technology readiness index scale ( Parasuraman and Colby, 2015 ), to gage consumer segments in technology markets. The studies yielded strong results on consumer segments and their sizes. Thus, considering the rapid adoption of technologies during the COVID-19 pandemic, an obvious question is how current this knowledge is. Hence, future studies can determine how the COVID-19 pandemic reconfigured consumer segments in the use of technologies, how they changed regarding their importance, and whether a revision of existing measuring instruments (scales) is necessary.

Moreover, the digital divide (i.e., the gaps in the access and use of technologies between different societal sectors) has also been extensively studied before COVID-19. For example, older and lower-income people used technology-based services to a much lesser degree ( Cruz-Cárdenas et al., 2019 ). The information is useful to design profitable and social marketing strategies. However, the pandemic-induced massive learning of technologies may leave out a part of society. Ultimately, future studies can focus on determining what happened to the digital gaps between social groups as an effect of the pandemic.

6.4 COVID-19 and the future: recommendations for practice and future studies

The review and systematization of the literature leave important recommendations for firms and organizations. Primarily, firms must incorporate rapid digital transformation in their processes. For example, although social media was already significant in societies before the COVID-19 crisis, its role has now been enhanced ( Naeem, 2021b ). The most diverse companies can find a profitable channel of communication and promotion in social networks. Smaller companies can utilize social media to sell products coupled with home delivery ( Butu et al., 2020 ), thereby beginning their digital transformation process. For larger companies, digital social networks can help build communities around their brands, especially during times of uncertainty and increased user traffic.

Second, companies and businesses must consider how to address the risk perceived by consumers. This risk has been articulated as two fundamental types: the risks of infection, and fraud and misuse of data in e-commerce transactions. The perceived risk of infection is expected to diminish with massive vaccination campaigns ( Shin and Kang, 2020 ). However, companies can address the perceived risk of fraud in online transactions via security protocols, incorporation and combination of technologies, and communication and promotion tools. In the latter, the best strategy will be to use the business image to generate consumer confidence ( Troise et al., 2021 ; Lv et al., 2020 ). Further, for an undecided consumer regarding online transactions, promotions aimed at reducing prices and increasing benefits proved useful during the pandemic ( Lv et al., 2020 ; Tran, 2021 ).

Finally, given the non-linear and uncertain trajectory of the pandemic, consumer behavior across the stages of the pandemic is a dynamic combination of old and new behaviors, highlighting the necessity for companies to incorporate flexibility and agility into their culture and operations, and fully align with digital transformation initiatives.

6.5 Limitations

This study has some limitations. Though the article search was performed in the Scopus database, which presents a good balance between quality and coverage ( Singh et al., 2020 ), several articles were not captured in the Scopus index, which could indicate that their quality is heterogeneous. However, this decision was necessary to systematize the literature in a reasonable amount of time.

Author statement

Jorge Cruz-Cárdenas: Writing

CRediT authorship contribution statement

Jorge Cruz-Cárdenas: Conceptualization, Methodology, Formal analysis, Writing – review & editing. Ekaterina Zabelina: Conceptualization, Methodology, Formal analysis, Visualization. Jorge Guadalupe-Lanas: Resources, Investigation. Andrés Palacio-Fierro: Resources, Investigation. Carlos Ramos-Galarza: Methodology, Formal analysis, Visualization.

Biographies

Jorge Cruz-Cárdenas is a senior lecturer at the School of Administrative and Economic Sciences and a researcher at the ESTec Research Center, both at Universidad Tecnológica Indoamérica, Ecuador. He holds a Ph.D. in Economics and Business Management from the University of Alcalá, Spain. His-main research area is consumer behavior in technological environments.

Ekaterina Zabelina is an associate professor at the Department of Psychology of Chelyabinsk State University, Russia. Her main research areas include economic psychology, positive psychology, organizational psychology, and behavioral Science.

Jorge Guadalupe-Lanas holds a Ph.D. in Economics from the University of Picardie Jules Vernes D'amiens in France. He currently serves as Director of ESTec Research Center at Universidad Tecnológica Indoamérica, Ecuador. His-fields of interest include macroeconomic theory, econometric modeling, and experimental economics.

Andrés Palacio-Fierro is a senior lecturer at the School of Administrative and Economic Sciences of Universidad Tecnológica Indoamérica, Ecuador, and a researcher at the ESTec Research Center. He is currently pursuing his doctoral studies at the Camilo José Cela University in Spain. His-research interests are related to topics of consumer behavior.

Carlos Ramos-Galarza is a senior lecturer at the School of Psychology of the Pontificia Universidad Católica del Ecuador and a researcher at Mist Research Center. He holds a Ph.D. from the University of Concepción, Chile. His-main research topics revolve around psychometry and human-technology interaction.

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.techfore.2021.121179 .

Appendix: Articles included in the review according to the study setting

[I nsert Table A.1 here ]

Reviewed articles.

Appendix B. Supplementary materials

• Abdel-Basset M., Chang V., Nabeeh N.A. An intelligent framework using disruptive technologies for COVID-19-19 analysis. Technol. Forecast. Soc. Change. 2021; 163 10.1016/j.techfore.2020.120431. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Ahmed R.R., Streimikiene D., Rolle J.-.A., Pham D. The COVID-19 pandemic and the antecedants for the impulse buying behavior of US citizens. J. Compet. 2020; 12 (3):5–27. [ Google Scholar ]
• Ajzen I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991; 50 (2):179–211. [ Google Scholar ]
• Alaimo L.S., Fiore M., Galati A. How the Covid-19 pandemic is changing online food shopping human behaviour in Italy. Sustainability. 2020; 12 (22):9594. [ Google Scholar ]
• Amicarelli V., Bux C. Food waste in Italian households during the Covid-19 pandemic: a self-reporting approach. J. Food Secur. 2021; 13 :25–37. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Anastasiadou E., Chrissos Anestis M., Karantza I., Vlachakis S. The coronavirus’ effects on consumer behavior and supermarket activities: insights from Greece and Sweden. Int. J. Sociol. Soc. Pol. 2020; 40 (9/10):893–907. [ Google Scholar ]
• Antonides G., van Leeuwen E. Covid-19 crisis in the Netherlands: “only together we can control Corona. Mind Soc. 2020 doi: 10.1007/s11299-020-00257-x. [ CrossRef ] [ Google Scholar ]
• Bahmanyar A., Estebsari A., Ernst D. The impact of different COVID-19 containment measures on electricity consumption in. Europe. Energy Res. Soc. Sci. 2020; 68 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Baicu C.G., Petronela G.G., Gardan D.A., Epuran G. The impact of COVID-19 on consumer behavior in retail banking: evidence from Romania. Manag. Mark: Challeng. Knowl. Soc. 2020; 15 (s1):534–556. [ Google Scholar ]
• Balaid A., Rozan Abd, M. Z., Hikmi S.N., Memon J. Knowledge maps: a systematic literature review and directions for future research. Int. J. Inf. Manag. 2016; 36 (3):451–475. [ Google Scholar ]
• Barnes S.J., Diaz M., Arnaboldi M. Understanding panic buying during COVID-19: a text analytics approach. Expert. Syst. Appl. 2021; 169 [ Google Scholar ]
• Bates R.A., LaBrecque B. Terrorism as economic warfare: america's risky business. J. Public Prof. Sociol. 2019; 11 (1):1–17. [ Google Scholar ]
• Baumert T., de Obesso M.M., Valbuena E. How does the terrorist experience alter consumer behaviour? An analysis of the Spanish case. J. Bus. Res. 2020; 115 :357–364. [ Google Scholar ]
• Brem A., Viardot E., Nylund P.A. Implications of the coronavirus (COVID-19) outbreak for innovation: which technologies will improve our lives? Technol. Forecast. Soc. Change. 2020; 163 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Butu A., Brumă I.S., Tanasă L., Rodino S., Vasiliu C.D., Doboș S., Butu M. The impact of COVID-19 crisis upon the consumer buying behavior of fresh vegetables directly from local producers. case study: the quarantined area of Suceava County. Romania. Int. J. Environ. Res. Public Health. 2020; 17 (15):5485. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Campbell B.L., Rihn A.L., Campbell J.H. Impact of the coronavirus pandemic on plant purchasing in Southeastern United States. Agribusiness. 2020; 37 (1):160–170. [ Google Scholar ]
• Crawford, D., 2012. Recovering from terror: the Egyptian and Balinese experiences worldwide hospitality and tourism themes. 14(1), 91–97.
• Cruz-Cárdenas J., Arévalo-Chávez P. Consumer behavior in the disposal of products: forty years of research. J. Promot. Mang. 2018; 24 (5):617–636. [ Google Scholar ]
• Cruz-Cárdenas J., Zabelina E., Deyneka O., Guadalupe-Lanas J., Velín-Fárez M. Role of demographic factors, attitudes toward technology, and cultural values in the prediction of technology-based consumer behaviors: a study in developing and emerging countries. Technol. Forecasting Soc. Change. 2019; 149 [ Google Scholar ]
• Cruz-Cárdenas J., Guadalupe-Lanas J., Ramos-Galarza C., Palacio-Fierro A. Drivers of technology readiness and motivations for consumption in explaining the tendency of consumers to use technology-based services. J. Bus. Res. 2021; 122 :217–225. [ Google Scholar ]
• Čvirik M. Health-conscious consumer behaviour: the impact of a pandemic on the case of Slovakia. Centr. Eur. Bus. Rev. 2020; 2020 (4):45–58. [ Google Scholar ]
• Dahlhamer J.M., Tierney K.J. Rebounding from disruptive events: business recovery following the Northridge earthquake. Sociol. Spectr. 1998; 18 (2):121–141. [ Google Scholar ]
• Dammeyer J. An explorative study of the individual differences associated with consumer stockpiling during the early stages of the 2020 Coronavirus outbreak in Europe. Pers. Individ. Dif. 2020; 167 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Davis F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989; 13 (3):319–340. [ Google Scholar ]
• Delorme D.E., Zinkhan G.M., Hagen S.C. The process of consumer reactions to possession threats and losses in a natural disaster. Mark. Lett. 2004; 15 (4):185–199. [ Google Scholar ]
• Donthu N., Gustafsson A. Effects of COVID-19 on business and research. J. Bus. Res. 2020; 117 :284–289. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Ellison B., McFadden B., Rickard B.J., Wilson N.L.W. Examining food purchase behavior and food values during the COVID-19 pandemic. Appl. Econ. Perspect. Policy. 2021; 43 (1):58–72. [ Google Scholar ]
• Foroudi P.H., Tabaghdehi S.A., Marvi R. The gloom of the COVID-19 shock in the hospitality industry: a study of consumer risk perception and adaptive belief in the dark cloud of a pandemic. Int. J. Hospital. Manag. 2021; 92 [ Google Scholar ]
• Gao X., Shi X., Guo H., Liu Y. To buy or not buy food online: the impact of the COVID-19 epidemic on the adoption of e-commerce in China. PLoS ONE. 2020; 15 (8) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Géron A. O'Reilly; Sebastopol, Canada: 2019. Hands-on Machine Learning With Scikit-Learn, Keras, and TensorFlow. 2nd ed. [ Google Scholar ]
• Goodwin R., Haque S., Neto F., Myers L.B. Initial psychological response of influenza A, H1N1 (“Swine flu”) BMC Infect. Dis. 2009; 9 (1):1–6. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Goolsbee A., Syverson Ch. Fear, lockdown, and diversion: comparing drivers of pandemic economic decline. J. Public Econ. 2020; 193 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Grashuis J., Skevas T., Segovia M.S. Grocery shopping preferences during the COVID-19 pandemic. Sustainability. 2020; 12 (13):5369. [ Google Scholar ]
• Hall M.C., Prayag G., Fieger P., Dyason D. Beyond panic buying: consumption displacement and COVID-19. J. Serv. Manag. 2020; 32 (1):113–128. [ Google Scholar ]
• Hao N., Wang H.H., Zhou Q. The impact of online grocery shopping on stockpile behavior in Covid-19. China Agricult. Econ. Rev. 2020; 12 (3):459–470. [ Google Scholar ]
• Hassen T.B., El Bilali H., Allahyari M.S. Impact of COVID-19 on food behavior and consumption in Qatar. Sustainability. 2020; 12 (17):6973. [ Google Scholar ]
• Herzenstein M., Horsky S., Posavac S.S. Living with terrorism or withdrawing in terror: perceived control and consumer avoidance. J. Consumer Behav. 2015; 14 :228–236. [ Google Scholar ]
• International Monetary Fund [IMF] (2020). World economic outlook. Available at https://www.imf.org/en/Publications/WEO/Issues/2020/06/24/ .
• Islam T., Pitafi A.H., Arya V., Wang Y., Akhtar N., Mubarik S., Xiaobei L. Panic buying in the COVID-19 pandemic: a multi-country examination. J. Retail. Consum. Serv. 2020; 59 [ Google Scholar ]
• Jaman J.H., Abdulrohman R., Suharso A., Sulistiowati N., Dewi I.P. Sentiment analysis on utilizing online transportation of Indonesian customers using tweets in the normal era and the pandemic Covid-19 era with support vector machine. Adv. Sci. Technol. Eng. Syst. J. 2020; 5 (5):389–394. [ Google Scholar ]
• Jeżewska-Zychowicz M., Plichta M., Królak M. 2020. Consumers’ fears regarding food availability and purchasing behaviors during the COVID-19 pandemic: the importance of trust and perceived stress. Nutrients. 2020; 12 (9):2852. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Jian Y., Yu I.Y., Yang M.X., Zeng K.J. The impacts of fear and uncertainty of COVID-19 on environmental concerns, brand trust, and behavioral intentions toward green hotels. Sustainability. 2020; 12 (20):8688. [ Google Scholar ]
• Jin X., Li J., Song W., Zhao T. The impact of COVID-19 and public health emergencies on consumer purchase of scarce products in China. Front. Public Health. 2020; 8 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Jribi S., Ismail H.B., Doggui D., Debbabi H. COVID-19 virus outbreak lockdown: what impacts on household food wastage? Environ. Dev. Sustain. 2020; 19 :1–17. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kaur P., Dhir A., Tandon A., Alzeiby E.A., Abohassan A.A. A systematic literature review on cyberstalking: an analysis of past achievements and future promises. Technol. Forecast. Soc. Change. 2021; 163 [ Google Scholar ]
• Kim J., Giroux M., Gonzalez-Jimenez H., Jang S., Kim S., Park J., Kim J.-.E., Lee J.C., Choi Y.K. Nudging to reduce the perceived threat of coronavirus and stockpiling intention. J. Advert. 2020; 49 (5):633–647. [ Google Scholar ]
• Kirk C.P., Rifkin L. I'll trade you diamonds for toilet paper: consumer reacting, coping and adapting behaviors in the COVID-19 pandemic. J. Bus. Res. 2020; 117 :124–131. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kline R.B. 4th ed. Guilford; New York: 2016. Principles and Practice of Structural Equation Modeling. [ Google Scholar ]
• Koch J., Frommeyer B., Schewe G. Online shopping motives during the COVID-19 pandemic: lessons from the crisis. Sustainability. 2020; 12 (24):10247. [ Google Scholar ]
• Kotler P., Keller K. Pearson; London: 2016. Marketing management, 15 Ed. [ Google Scholar ]
• Laato S., Islam A.K.M.N., Farooq A., Dhir A. Unusual purchasing behavior during the early stages of the COVID-19 pandemic: the stimulus-organism-response approach. J. Retail. Cons. Serv. 2020; 57 [ Google Scholar ]
• Laguna L., Fiszman S., Puerta P., Chaya C., Tarrega A. The impact of COVID-19 lockdown on food priorities: results from a preliminary study using social media and an online survey with Spanish consumers. Food Qual. Prefer. 2020; 86 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lamb T.L., Winter S.R., Rice S., Ruskin K.J., Vaughn A. Factors that predict passenger's willingness to fly during and after the COVID-19 pandemic. J. Air Transport Manag. 2020; 89 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Li M., Zhao T., Huang E., Li J. How does a public health emergency motivate people's impulsive consumption? an empirical study during the COVID-19 outbreak in China. Int. J. Environ. Res. Public Health. 2020; 17 (14):5019. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Li J.X., Hallsworth A.G., Coca-Stefaniak J.A. Changing grocery shopping behaviours among Chinese consumers at the outset of the COVID-19 outbreak. Tijdschrift Voor Economische en Sociale Geografie. 2020; 111 (3):574–583. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lin J-S.C., Chang H.-.C. The role of technology readiness in self-service technology acceptance. Manag. Serv. Qual. 2011; 21 (4):424–444. [ Google Scholar ]
• Lins S., Aquino S. Development and initial psychometric properties of a panic buying scale during COVID-19 pandemic. Heliyon. 2020; 6 (9):e04746. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Liu N., Chen Z., Bao G. Role of media coverage in mitigating COVID-19 transmission: evidence from China. Technol. Forecast. Soc. Change. 2021; 163 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Long N.N., Khoi B.H. An empirical study about the intention to hoard food during COVID-19 pandemic. EURASIA J. Math. Sci. Tech. Ed. 2020; 16 (7):em1857. [ Google Scholar ]
• Lv J., Wang Z., Huang Yu., Wang T., Wang Yu. How can e-commerce businesses implement discount strategies through social media? Sustainability. 2020; 12 (18):7459. [ Google Scholar ]
• Madnani D., Fernandes S., Madnani N. Analysing the impact of COVID-19 on over-the-top media platforms in India. Int. J. Pervasive Comp. Comm. 2020; 16 (5):457–475. [ Google Scholar ]
• Mehta S., Saxena T., Purohit N. The new consumer behaviour paradigm amid COVID-19: permanent or transient? J. Health Manag. 2020; 22 (7):291–301. [ Google Scholar ]
• Min S., Xiang C., Zhang X.-.H. Impacts of the COVID-19 pandemic on consumers’ food safety knowledge and behavior in China. J. Integr. Agricult. 2020; 19 (12):2926–2936. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Naeem M. Understanding the customer psychology of impulse buying during COVID-19 pandemic: implications for retailers. Int. J. Retail Distrib. Manag. 2021; 49 (3):377–393. [ Google Scholar ]
• Naeem M. Do social media platforms develop consumer panic buying during the fear of Covid-19 pandemic. J. Retail. Cons. Serv. 2021; 58 [ Google Scholar ]
• Oana D. The Impact of the current crisis generated by the COVID-19 pandemic on consumer behavior. Stud. Bus. Econ. 2020; 15 (2):85–99. [ Google Scholar ]
• Osobajo O.A., Moore D. Methodological choices in relationship quality (RQ) research 1987 to 2015: a systematic literature review. J. Relation. Mark. 2017; 16 (1):40–81. [ Google Scholar ]
• Pan X., Dresner M., Mantin B. Pre-hurricane consumer stockpiling and post-hurricane product availability: empirical evidence from natural experiments. Prod. Oper. Manag. 2020; 29 (10):2350–2380. [ Google Scholar ]
• Parasuraman A., Colby C.L. An updated and streamlined technology readiness index: TRI 2.0. J. Serv. Res. 2015; 18 (1):59–74. [ Google Scholar ]
• Petrescu-Mag R.M., Vermeir I., Petrescu D.C., Crista F.L., Banatean-Dunea I. Traditional foods at the click of a button: the preference for the online purchase of Romanian traditional foods during the COVID-19 pandemic. Sustainability. 2020; 12 (23):9956. [ Google Scholar ]
• Pham V.K., Thi T.H.D., Le T.H.H. A study on the COVID-19 awareness affecting the consumer perceived benefits of online shopping in Vietnam. Cogent Bus. Manag. 2020; 7 (1) [ Google Scholar ]
• Pillai V., Ambekar S., Hudnurkar M. Implications of COVID-19 on consumer buying behavior. PalArch's. J. Archaeol. Egypt. 2020; 17 (6):4336–4354. [ Google Scholar ]
• Prentice C., Chen J., Stantic B. Timed intervention in COVID-19 and panic buying. J. Retail. Cons. Serv. 2020; 57 [ Google Scholar ]
• Principato L., Secondi L., Cicatiello C., Mattia G. in press. Caring more about food: the unexpected positive effect of the Covid-19 lockdown on household food management and waste. Socio-Econ Plan. Sci. 2020 doi: 10.1016/j.seps.2020.100953. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Qi X., Yu H., Ploeger A. Exploring influential factors including COVID-19 on green food purchase intentions and the intention–behaviour gap: a qualitative study among consumers in a Chinese context. Int. J. Environ. Res. Public Health. 2020; 17 (19):7106. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Romeo-Arroyo E., Mora M., Vázquez-Araújo L. Consumer behavior in confinement times: food choice and cooking attitudes in Spain. Int. J. Gastron. Food Sci. 2020; 21 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Safara F. A computational model to predict consumer behaviour during COVID-19 pandemic. Comput. Econ. 2020 doi: 10.1007/s10614-020-10069-3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Schiffman L.G., Wisenblit J. 11th ed. Upper Saddle River; NJ, Pearson: 2015. Consumer Behavior. [ Google Scholar ]
• Schmidthuber L., Maresch D., Ginner M. Disruptive technologies and abundance in the service sector—toward a refined technology acceptance model. Technol. Forecast. Soc. Change. 2020; 155 [ Google Scholar ]
• Seiler P. Weighting bias and inflation in the time of COVID-19: evidence from Swiss transaction data. Swiss. J. Econ. Stat. 2020; 156 (1):13. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sheridan A., Andersen A.L., Hansen T., Johannesen N. Social distancing laws cause only small losses of economic activity during the COVID-19 pandemic in Scandinavia. Proc. Natl Acad. Sci. 2020; 117 (34):20468–20473. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sheth J.N. Impact of Covid-19 on consumer behavior: will the old habits return or die? J. Bus. Res. 2020; 117 :280–283. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Shin H., Kang J. Reducing perceived health risk to attract hotel customers in the COVID-19 pandemic era: focused on technology innovation for social distancing and cleanliness. Int. J. Hospital. Manag. 2020; 91 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sidor A., Rzymski P. Dietary choices and habits during COVID-19 lockdown: experience from Poland. Nutrients. 2020; 12 (6):1657. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Singh S., Dhir S., Das V.M., Sharma A. Bibliometric overview of the technological forecasting and social change journal: analysis from 1970 to 2018. Technol. Forecast. Soc. Change. 2020; 154 [ Google Scholar ]
• Skare M., Riveiro Soriano D., Porada-Rochón M. Impact of COVID-19 on the travel and tourism industry. Technol. Forecast. Soc. Change. 2021; 163 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Sneath J.Z., Lacey R., Kennett-Hensel P.A. Coping with a natural disaster: losses, emotions, and impulsive and compulsive buying. Market Lett. 2009; 20 (1):45–60. [ Google Scholar ]
• Snyder H. Literature review as a research methodology: an overview and guidelines. J. Bus. Res. 2019; 104 :333–339. [ Google Scholar ]
• Song W., Jin X., Gao J., Zhao T. Will buying follow others ease their threat of death? An analysis of consumer data during the Period of COVID-19 in China. Int. J. Environ Res. Public Health. 2020; 17 (9):3215. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Song Sh., Yao X., Wen N. What motivates Chinese consumers to avoid information about the COVID-19 pandemic? the perspective of the stimulus-organism-response model. Inf. Process Manag. 2020; 58 (1) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Soule E.K., Mayne Sh., Snipes W., Guy M.C., Breland A., Fagan P. Impacts of COVID-19 on electronic cigarette purchasing, use and related behaviors. Int. J. Environ. Res. Public Health. 2020; 17 (18):6762. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Szymkowiak A., Gaczek P., Jeganathan K., Kulawik P. The impact of emotions on shopping behavior during epidemic: what a business can do to protect customers. J. Cons. Behav. 2021; 20 (1):48–60. [ Google Scholar ]
• Ting H., Thaichon P., Chuah F., Tan S.R. Consumer behaviour and disposition decisions: the why and how of smartphone disposition. J. Retail. Custom. Serv. 2019; 51 :212–220. [ Google Scholar ]
• Tran L.T.T. Managing the effectiveness of e-commerce platforms in a pandemic. J. Retail. Cons. Serv. 2021; 58 [ Google Scholar ]
• Troise C., O'Driscoll A., Tani M., Prisco A. Online food delivery services and behavioural intention: a test of an integrated TAM and TPB framework. British Food J. 2021; 123 (2):664–683. [ Google Scholar ]
• Van Eck N.J., Waltman L. Software survey: vOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010; 84 (2):523–538. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Van Eck, N.J., Waltman, L., 2020. Manual for Vosviewer version 1.6.15. available at https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.15.pdf .
• Vanapalli K.R., Sharma H.B., Ranjan V.P., Samal B., Bhattacharya J., Dubey B.K., Goel S. Challenges and strategies for effective plastic waste management during and post COVID-19 pandemic. Sci. Total Environ. 2021; 750 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wang H.H., Hao N. Panic buying? food hoarding during the pandemic period with city lockdown. J. Integr. Agric. 2020; 19 (12):2916–2925. [ Google Scholar ]
• Wang E.P., An N., Gao Z.F., Kiprop E., Geng X.H. Consumer food stockpiling behavior and willingness to pay for food reserves in COVID-19. Food Secur. 2020; 12 (4):739–747. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wang Y., Xu R., Schwartz M., Ghosh D., Chen X. COVID-19 and retail grocery management: insights from a broad-based consumer survey. IEEE Eng. Manag. Rev. 2020; 48 (3):202–211. [ Google Scholar ]
• Wen Z., Huimin G., Kavanaugh R.R. The impacts of SARS on the consumer behaviour of Chinese domestic tourists. Curr. Issues. Tour. 2005; 8 (1):22–38. [ Google Scholar ]
• World Health Organization, 2021a. Who coronavirus disease (COVID-19) dashboard. Available at https://covid19.who.int/ .
• World Health Organization, 2021b. COVID-19 virtual press conference transcript - 25 June 2021. Available at https://www.who.int/publications/m/item/covid-19-virtual-press-conference-transcript—25-june-2021.
• Yang X. Potential consequences of COVID-19 for sustainable meat consumption: the role of food safety concerns and responsibility attributions. British Food J. 2021; 123 (2):455–474. [ Google Scholar ]
• Yang Y., Li O., Peng X., Wang L. Consumption trends during the COVID-19 crisis: how awe, coping, and social norms drive utilitarian purchases. Front. Psychol. 2020; 11 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Yoo S., Managi S. Global benefits of COVID-19 action. Technol. Forecast. Soc. Change. 2020; 160 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Zwanka R.J., Buff C. COVID-19 generation: a conceptual framework of the consumer behavioral shifts to be caused by the COVID-19 pandemic. J. Int. Cons. Mark. 2020; 33 (1):58–67. [ Google Scholar ]

COVID-19, consumer behavior, technology, and society: A literature review and bibliometric analysis

Affiliations.

• 1 Research Center in Business, Society, and Technology, ESTec, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador.
• 2 School of Administrative and Economic Science, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador.
• 3 Department of Psychology, Chelyabinsk State University, Bratiev Kashirinykh 129, 454001 Chelyabinsk, Russia.
• 4 Programa doctoral en Ciencias Jurídicas y Económicas, Universidad Camilo José Cela, Castillo de Alarcón, 49, 28692 Madrid, Spain.
• 5 Facultad de Psicología, Universidad Católica del Ecuador, Av. 12 de octubre 1076, 170523, Quito, Ecuador.
• 6 Centro de Investigación MIST, Universidad Tecnológica Indoamérica, Machala y Sabanilla s/n, 170301 Quito, Ecuador.
• PMID: 34511647
• PMCID: PMC8418327
• DOI: 10.1016/j.techfore.2021.121179

The COVID-19 crisis is among the most disruptive events in recent decades. Its profound consequences have garnered the interest of many studies in various disciplines, including consumer behavior, thereby warranting an effort to review and systematize the literature. Thus, this study systematizes the knowledge generated by 70 COVID-19 and consumer behavior studies in the Scopus database. It employs descriptive analysis, highlighting the importance of using quantitative methods and China and the US as research settings. Co-occurrence analysis further identified various thematic clusters among the studies. The input-process-output consumer behavior model guided the systematic review, covering several psychological characteristics and consumer behaviors. Accordingly, measures adopted by governments, technology, and social media stand out as external factors. However, revised marketing strategies have been oriented toward counteracting various consumer risks. Hence, given that technological and digital formats mark consumer behavior, firms must incorporate digital transformations in their process.

Keywords: COVID-19; Consumer behavior; Disruptive events; Literature review; Panic buying; Technology.

© 2021 The Author(s). Published by Elsevier Inc.

Customer experience: a systematic literature review and consumer culture theory-based conceptualisation

• Published: 15 February 2020
• Volume 71 , pages 135–176, ( 2021 )

Cite this article

• Muhammad Waqas 1 ,
• Zalfa Laili Binti Hamzah 1 &
• Noor Akma Mohd Salleh 2  

10k Accesses

47 Citations

2 Altmetric

Explore all metrics

The study aims to summarise and classify the existing research and to better understand the past, present, and the future state of the theory of customer experience. The main objectives of this study are to categorise and summarise the customer experience research, identify the extant theoretical perspectives that are used to conceptualise the customer experience, present a new conceptualisation and conceptual model of customer experience based on consumer culture theory and to highlight the emerging trends and gaps in the literature of customer experience. To achieve the stated objectives, an extensive literature review of existing customer experience research was carried out covering 49 journals. A total of 99 empirical and conceptual articles on customer experience from the year 1998 to 2019 was analysed based on different criteria. The findings of this study contribute to the knowledge by highlighting the role of customer attribution of meanings in defining their experiences and how such experiences can predict consumer behaviour.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Online influencer marketing

Customer engagement in social media: a framework and meta-analysis

Customer experience: fundamental premises and implications for research

Abbott L (1955) Quality and competition. Columbia University Press, New York

Google Scholar  

Addis M, Holbrook MB (2001) On the conceptual link between mass customisation and experiential consumption: an explosion of subjectivity. J Consum Behav 1:50–66

Alben L (1996) Defining the criteria for effective interaction design. Interactions 3:11–15

Allen CT, Fournier S, Miller F (2008) Brands and their meaning makers. In: Haugtvedt C, Herr P, Kardes F (eds) Handbook of consumer psychology. Taylor & Francis, Milton Park, pp 781–822

Andreini D, Pedeliento G, Zarantonello L, Solerio C (2019) A renaissance of brand experience: advancing the concept through a multi-perspective analysis. J Bus Res 91:123–133

Arnold MJ, Reynolds KE, Ponder N, Lueg JE (2005) Customer delight in a retail context: investigating delightful and terrible shopping experiences. J Bus Res 58:1132–1145

Arnould EJ, Thompson CJ (2005) Consumer culture theory (CCT): twenty years of research. J Consum Res 31:868–882

Beckman E, Kumar A, Kim Y-K (2013) The impact of brand experience on downtown success. J Travel Res 52:646–658

Belk RW, Costa JA (1998) The mountain man myth: a contemporary consuming fantasy. J Consum Res 25:218–240

Bennett R, Härtel CE, McColl-Kennedy JR (2005) Experience as a moderator of involvement and satisfaction on brand loyalty in a business-to-business setting 02-314R. Ind Mark Manag 34:97–107

Berry LL (2000) Cultivating service brand equity. J Acad Mark Sci 28:128–137

Berry LL, Carbone LP, Haeckel SH (2002) Managing the total customer experience. MIT Sloan Manag Rev 43:85–89

Biedenbach G, Marell A (2010) The impact of customer experience on brand equity in a business-to-business services setting. J Brand Manag 17:446–458

Bilgihan A, Okumus F, Nusair K, Bujisic M (2014) Online experiences: flow theory, measuring online customer experience in e-commerce and managerial implications for the lodging industry. Inf Technol Tour 14:49–71

Bilro RG, Loureiro SMC, Ali F (2018) The role of website stimuli of experience on engagement and brand advocacy. J Hosp Tour Technol 9:204–222

Bolton RN, Kannan PK, Bramlett MD (2000) Implications of loyalty program membership and service experiences for customer retention and value. J Acad Mark Sci 28:95–108

Brakus JJ, Schmitt BH, Zarantonello L (2009) Brand experience: what is it? How is it measured? Does it affect loyalty? J Mark 73:52–68

Branch JD (2007) Postmodern consumption and the high-fidelity audio microculture. In: Belk RW, Sherry JF Jr (eds) Consumer culture theory. JAI Press, Oxford

Braun-LaTour KA, LaTour MS (2005) Transforming consumer experience: when timing matters. J Advert 34:19–30

Braun-LaTour KA, LaTour MS, Pickrell JE, Loftus EF, SUia (2004) How and when advertising can influence memory for consumer experience. J Advert 33:7–25

Bridges E, Florsheim R (2008) Hedonic and utilitarian shopping goals: the online experience. J Bus Res 61:309–314

Brodie RJ, Ilic A, Juric B, Hollebeek L (2013) Consumer engagement in a virtual brand community: an exploratory analysis. J Bus Res 66:105–114

Bronner F, Neijens P (2006) Audience experiences of media context and embedded advertising-a comparison of eight media international. Int J Mark Res 48:81–100

Calder BJ, Malthouse EC, Schaedel U (2009) An experimental study of the relationship between online engagement and advertising effectiveness. J Interact Mark 23:321–331

Carù A, Cova B (2003) Revisiting consumption experience: a more humble but complete view of the concept. Mark Lett 3:267–286

Chandler JD, Lusch RF (2015) Service systems: a broadened framework and research agenda on value propositions, engagement, and service experience. J Serv Res 18:6–22

Constantinides E (2004) Influencing the online consumer’s behavior: the web experience. Internet Res 14:111–126

Constantinides E, Lorenzo-Romero C, Gómez MA (2010) Effects of web experience on consumer choice: a multicultural approach. Internet Res 20:188–209

Cooper H, Schembri S, Miller D (2010) Brand-self identity narratives in the James Bond movies. Psychol Mark 27:557–567

Cova B (1997) Community and consumption: towards a definition of the “linking value” of product or services. Eur J Mark 31:297–316

Creswell JW (2007) Qualitative inquiry and research design: choosing among five approaches, 2nd edn. Sage Publications, Thousand Oaks

Das K (2009) Relationship marketing research (1994–2006) an academic literature review and classification. Mark Intell Plan 27:326–363

Das G, Agarwal J, Malhotra NK, Varshneya G (2019) Does brand experience translate into brand commitment? A mediated-moderation model of brand passion and perceived brand ethicality. J Bus Res 95:479–490

Daugherty T, Li H, Biocca F (2008) Consumer learning and the effects of virtual experience relative to indirect and direct product experience. Psychol Mark 25:568–586

De Keyser A, Lemon KN, Klaus P, Keiningham TL (2015) A framework for understanding and managing the customer experience. Marketing Science Institute working paper series, pp 15–121

de Oliveira Santini F, Ladeira WJ, Sampaio CH, Pinto DC (2018) The brand experience extended model: a meta-analysis. J Brand Manag 25:519–535

De Vries L, Gensler S, Leeflang PS (2012) Popularity of brand posts on brand fan pages: an investigation of the effects of social media marketing. J Interact Mark 26:83–91

Ding CG, Tseng TH (2015) On the relationships among brand experience, hedonic emotions, and brand equity. Eur J Mark 49:994–1015

Elliot S, Fowell S (2000) Expectations versus reality: a snapshot of consumer experiences with internet retailing. Int J Inf Manag 20:323–336

Escalas et al (2013) Self-identity and consumer behavior. J Consum Res 39:15–18

Farndale E, Kelliher C (2013) Implementing performance appraisal: exploring the employee experience. Hum Resour Manag 52:879–897

Fisch C, Block J (2018) Six tips for your (systematic) literature review in business and management research. Manag Rev Q 68:103–106

Flavián C, Guinalíu M, Gurrea R (2006) The influence of familiarity and usability on loyalty to online journalistic services: the role of user experience. J Retail Consum Serv 13:363–375

Forlizzi J, Battarbee K (2004) Understanding experience in interactive systems. In: Proceedings of the 5th conference on designing interactive systems: processes, practices, methods, and techniques. ACM, New York, pp 261–268

Frambach RT, Roest HC, Krishnan TV (2007) The impact of consumer internet experience on channel preference and usage intentions across the different stages of the buying process. J Interact Mark 21:26–41

Froehle CM, Roth AV (2004) New measurement scales for evaluating perceptions of the technology-mediated customer service experience. J Oper Manag 22:1–21

Frow P, Payne A (2007) Towards the ‘perfect’ customer experience. J Brand Manag 15:89–101

Garg R, Rahman Z, Kumar I (2011) Customer experience: a critical literature review and research agenda. Int J Serv Sci 4:146–173

Geertz C (2008) Local knowledge: further essays in interpretive anthropology. Basic books, New York

Gensler S, Völckner F, Liu-Thompkins Y, Wiertz C (2013) Managing brands in the social media environment. J Interact Mark 27:242–256

Gentile C, Spiller N, Noci G (2007) How to sustain the customer experience: an overview of experience components that co-create value with the customer. Eur Manag J 25:395–410

Goldstein SM, Johnston R, Duffy J, Rao J (2002) The service concept: the missing link in service design research? J Oper Manag 20:121–134

Grace D, O’Cass A (2004) Examining service experiences and post-consumption evaluations. J Serv Mark 18:450–461

Greenwell TC, Fink JS, Pastore DL (2002) Assessing the influence of the physical sports facility on customer satisfaction within the context of the service experience. Sport Manag Rev 5:129–148

Grewal D, Levy M, Kumar V (2009) Customer experience management in retailing: an organizing framework. J Retail 85:1–14

Ha HY, Perks H (2005) Effects of consumer perceptions of brand experience on the web: brand familiarity, satisfaction and brand trust. J Consum Behav An Int Res Rev 4:438–452

Hamzah ZL, Alwi SFS, Othman MN (2014) Designing corporate brand experience in an online context: a qualitative insight. J Bus Res 67:2299–2310

Harris P (2007) We the people: the importance of employees in the process of building customer experience. J Brand Manag 15:102–114

Harris K, Baron S, Parker C (2000) Understanding the consumer experience: it’s’ good to talk’. J Mark Manag 16:111–127

Hassenzahl M (2008) User experience (UX): towards an experiential perspective on product quality. In: Proceedings of the 20th conference on l’Interaction Homme-Machine. ACM, pp 11–15

Hatcher EP (1999) Art as culture: an introduction to the anthropology of art. Greenwood Publishing Group, Westport

Hepola J, Karjaluoto H, Hintikka A (2017) The effect of sensory brand experience and involvement on brand equity directly and indirectly through consumer brand engagement. J Prod Brand Manag 26:282–293

Hirschman EC, Holbrook MB (1982) Hedonic consumption: emerging concepts, methods and propositions. J Mark 46:92–101

Hoffman DL, Novak TP (1996) Marketing in hypermedia computer-mediated environments: conceptual foundations. J Mark 60:50–68

Hoffman DL, Novak TP (2017) Consumer and object experience in the internet of things: an assemblage theory approach. J Consum Res 44:1178–1204

Holbrook MB, Hirschman EC (1982) The experiential aspects of consumption: consumer fantasies, feelings, and fun. J Consum Res 9:132–140

Hollebeek LD, Glynn MS, Brodie RJ (2014) Consumer brand engagement in social media: conceptualization, scale development and validation. J Int Mark 28:149–165

Holt DB (2003) Brands and branding. Harvard Business School, Boston

Homburg C, Jozić D, Kuehnl C (2017) Customer experience management: toward implementing an evolving marketing concept. J Acad Mark Sci 45:377–401

Hsu HY, Tsou H-T (2011) Understanding customer experiences in online blog environments. Int J Inf Manag 31:510–523

Huang P, Lurie NH, Mitra S (2009) Searching for experience on the web: an empirical examination of consumer behavior for search and experience goods. J Mark 73:55–69

Hultén B (2011) Sensory marketing: the multi-sensory brand-experience concept. Eur Bus Rev 23:256–273

Iglesias O, Singh JJ, Batista-Foguet JM (2011) The role of brand experience and affective commitment in determining brand loyalty. J Brand Manag 18:570–582

Islam JU, Rahman Z (2016) The transpiring journey of customer engagement research in marketing: a systematic review of the past decade. Manag Dec 54:2008–2034

Jacoby J (2002) Stimulus-organism-response reconsidered: an evolutionary step in modeling (consumer) behavior. J Consum Psychol 12:51–57

Kaplan S (1992) The restorative environment: nature and human experience. In: Relf D (ed) The role of horticulture in human well-being and social development. Timber Press, Arlington, pp 134–142

Keng C-J, Ting H-Y, Chen Y-T (2011) Effects of virtual-experience combinations on consumer-related “sense of virtual community”. Internet Res 21:408–434

Khalifa M, Liu V (2007) Online consumer retention: contingent effects of online shopping habit and online shopping experience. Eur J Inf Syst 16:780–792

Khan I, Fatma M (2017) Antecedents and outcomes of brand experience: an empirical study. J Brand Manag 24:439–452

Khan I, Rahman Z (2015) Brand experience formation mechanism and its possible outcomes: a theoretical framework. Mark Rev 15:239–259

Khan I, Rahman Z, Fatma M (2016) The role of customer brand engagement and brand experience in online banking. Int J Bank Mark 34:1025–1041

Kim H, Suh K-S, Lee U-K (2013) Effects of collaborative online shopping on shopping experience through social and relational perspectives. Inf Manag 50:169–180

Kinard BR, Hartman KB (2013) Are you entertained? The impact of brand integration and brand experience in television-related advergames. J Advert 42:196–203

Kozinets RV (2001) Utopian enterprise: articulating the meanings of Star Trek’s culture of consumption. J Consum Res 28:67–88

Kozinets RV (2002) Can consumers escape the market? Emancipatory illuminations from burning man. J Consum Res 29:20–38

Kuksov D, Shachar R, Wang K (2013) Advertising and consumers’ communications. Mark Sci 32:294–309

LaSalle D, Britton TA (2003) Priceless: turning ordinary products into extraordinary experiences. Harvard Business School Press, Boston

Laugwitz B, Held T, Schrepp M (2008) Construction and evaluation of a user experience questionnaire. In: Symposium of the Austrian HCI and usability engineering group. Springer, Berlin, Heidelberg, pp 63–76

Lee YH, Lim EAC (2008) What’s funny and what’s not: the moderating role of cultural orientation in ad humor. J Advert 37:71–84

Lemke F, Clark M, Wilson H (2011) Customer experience quality: an exploration in business and consumer contexts using repertory grid technique. J Acad Mark Sci 39:846–869

Lemon KN, Verhoef PC (2016) Understanding customer experience throughout the customer journey. J Mark 80:69–96

Lin YH (2015) Innovative brand experience’s influence on brand equity and brand satisfaction. J Bus Res 68:2254–2259

Lindsey-Mullikin J, Munger JL (2011) Companion shoppers and the consumer shopping experience. J Relatsh Mark 10:7–27

Loureiro SMC, de Araújo CMB (2014) Luxury values and experience as drivers for consumers to recommend and pay more. J Retail Consum Serv 21:394–400

Lundqvist A, Liljander V, Gummerus J, Van Riel A (2013) The impact of storytelling on the consumer brand experience: the case of a firm-originated story. J Brand Manag 20:283–297

Mann SJ (2001) Alternative perspectives on the student experience: alienation and engagement. Stud High Educ 26:7–19

Martin J, Mortimer G, Andrews L (2015) Re-examining online customer experience to include purchase frequency and perceived risk. J Retail Consum Serv 25:81–95

Mascarenhas OA, Kesavan R, Bernacchi M (2006) Lasting customer loyalty: a total customer experience approach. J Consum Mark 23:397–405

McCarthy J, Wright P (2004) Technology as experience. Interactions 11:42–43

Menon S, Kahn B (2002) Cross-category effects of induced arousal and pleasure on the Internet shopping experience. J Retail 78:31–40

Mersey RD, Malthouse EC, Calder BJ (2010) Engagement with online media. J Media Bus Stud 7:39–56

Meyer C, Schwager A (2007) Customer experience. Harv Bus Rev 85:1–11

Milligan A, Smith S (2002) Uncommon practice: People who deliver a great brand experience. Financial Times/Prentice Hall, London

Mollen A, Wilson H (2010) Engagement, telepresence and interactivity in online consumer experience: reconciling scholastic and managerial perspectives. J Bus Res 63:919–925

Morgan-Thomas A, Veloutsou C (2013) Beyond technology acceptance: brand relationships and online brand experience. J Bus Res 66:21–27

Mosley RW (2007) Customer experience, organisational culture and the employer brand. J Brand Manag 15:123–134

Mosteller J, Donthu N, Eroglu S (2014) The fluent online shopping experience. J Bus Res 67:2486–2493

MSI (2016) Research priorities 2016–2018. http://www.msi.org/research/2016-2018-research-priorities/ . Accessed 28 Aug 2017

MSI (2018) Research priorities 2018–2020. Marketing Science Institute, Cambridge

Mulet-Forteza C, Genovart-Balaguer J, Mauleon-Mendez E, Merigó JM (2019) A bibliometric research in the tourism, leisure and hospitality fields. J Bus Res 101:819–827

Nairn A, Griffin C, Gaya Wicks P (2008) Children’s use of brand symbolism: a consumer culture theory approach. Eur J Mark 42:627–640

Nambisan S, Baron RA (2007) Interactions in virtual customer environments: implications for product support and customer relationship management. J Int Mark 21:42–62

Ngo LV, Northey G, Duffy S, Thao HTP (2016) Perceptions of others, mindfulness, and brand experience in retail service setting. J Retail Consum Serv 33:43–52

Novak TP, Hoffman DL, Yung Y-F (2000) Measuring the customer experience in online environments: a structural modeling approach. Mark Sci 19:22–42

Nysveen H, Pedersen PE (2004) An exploratory study of customers’ perception of company web sites offering various interactive applications: moderating effects of customers’ Internet experience. Dec Support Syst 37:137–150

Nysveen H, Pedersen PE (2014) Influences of cocreation on brand experience. Int J Mark Res 56:807–832

Nysveen H, Pedersen PE, Skard S (2013) Brand experiences in service organizations: exploring the individual effects of brand experience dimensions. J Brand Manag 20:404–423

O’Cass A, Grace D (2004) Exploring consumer experiences with a service brand. J Prod Brand Manag 13:257–268

Ofir C, Raghubir P, Brosh G, Monroe KB, Heiman A (2008) Memory-based store price judgments: the role of knowledge and shopping experience. J Retail 84:414–423

Palmer A (2010) Customer experience management: a critical review of an emerging idea. J Serv Mark 24:196–208

Piedmont RL, Leach MM (2002) Cross-cultural generalizability of the spiritual transcendence scale in india: spirituality as a universal aspect of human experience. Am Behav Sci 45:1888–1901

Pine BJ, Gilmore JH (1998) Welcome to the experience economy. Harv Bus Rev 76:97–105

Ponsonby-Mccabe S, Boyle E (2006) Understanding brands as experiential spaces: axiological implications for marketing strategists. J Strateg Mark 14:175–189

Prahalad CK, Ramaswamy V (2004) Co-creation experiences: the next practice in value creation. J Interact Mark 18:5–14

Rageh Ismail A, Melewar T, Lim L, Woodside A (2011) Customer experiences with brands: literature review and research directions. Mark Rev 11:205–225

Rahman M (2014) Differentiated brand experience in brand parity through branded branding strategy. J Strateg Mark 22:603–615

Ramaseshan B, Stein A (2014) Connecting the dots between brand experience and brand loyalty: the mediating role of brand personality and brand relationships. J Brand Manag 21:664–683

Rigby D (2011) The future of shopping. Harv Bus Rev 89:65–76

Robertson TS, Gatignon H, Cesareo L (2018) Pop-ups, ephemerality, and consumer experience: the centrality of buzz. J Assoc Consum Res 3:425–439

Rose S, Hair N, Clark M (2011) Online customer experience: a review of the business-to-consumer online purchase context. Int J Manag Rev 13:24–39

Rose S, Clark M, Samouel P, Hair N (2012) Online customer experience in e-retailing: an empirical model of antecedents and outcomes. J Retail 88:308–322

Roswinanto W, Strutton D (2014) Investigating the advertising antecedents to and consequences of brand experience. J Promot Manag 20:607–627

Salmon P (1989) Personal stances in learning. In: Weil SW, McGill I (eds) Making sense of experiential learning: diversity in theory and practice. The Open University Press, Milton Keynes, pp 230–241

Schembri S, Sandberg J (2002) Service quality and the consumer’s experience: towards an interpretive approach. Mark Theory 2:189–205

Schivinski B, Christodoulides G, Dabrowski D (2016) Measuring consumers’ engagement with brand-related social-media content. J Advert Res 56:64–80

Schmitt B (1999) Experiential marketing. J Mark Manag 15:53–67

Schmitt B (2000) Creating and managing brand experiences on the internet. Des Manag J 11:53–58

Schmitt B, Joško Brakus J, Zarantonello L (2015) From experiential psychology to consumer experience. J Consum Psychol 25:166–171

Scholz J, Smith AN (2016) Augmented reality: designing immersive experiences that maximize consumer engagement. Bus Horiz 59:149–161

Schouten JW, McAlexander JH, Koenig HF (2007) Transcendent customer experience and brand community. J Acad Mark Sci 35:357–368

Shaw C, Ivens J (2002) Building great customer experiences, vol 241. Palgrave, London

Sherry JF, Kozinets RV (2007) Comedy of the commons: nomadic spirituality and the Burning Man festival. In: Belk RW, Sherry JF (eds) Consumer culture theory. JAI Press, Oxford, pp 119–147

Shimp TA, Andrews JC (2013) Advertising, promotion, and other aspects of integrated marketing communications, 9th edn. Cengage Learning, Mason

Singh S, Sonnenburg S (2012) Brand performances in social media. J Interact Mark 26:189–197

Skadberg YX, Kimmel JR (2004) Visitors’ flow experience while browsing a web site: its measurement, contributing factors and consequences. Comput Hum Behav 20:403–422

Smith S, Wheeler J (2002) Managing the customer experience: turning customers into advocates. Financial Times/Prentice Hall, Upper Saddle River

Syrdal HA, Briggs E (2018) Engagement with social media content: a qualitative exploration. J Mark theory Pract 26:4–22

Tafesse W (2016a) Conceptualization of brand experience in an event marketing context. J Promot Manag 22:34–48

Tafesse W (2016b) An experiential model of consumer engagement in social media. J Prod Brand Manag 25:424–434

Takatalo J, Nyman G, Laaksonen L (2008) Components of human experience in virtual environments. Comput Hum Behav 24:1–15

Tax SS, Brown SW, Chandrashekaran M (1998) Customer evaluations of service complaint experiences: implications for relationship marketing. J Mark 62:60–76

Thompson CJ, Locander WB, Pollio HR (1989) Putting consumer experience back into consumer research: the philosophy and method of existential-phenomenology. J Consum Res 16:133–146

Thorbjørnsen H, Supphellen M, Nysveen H, Egil P (2002) Building brand relationships online: a comparison of two interactive applications. J Interact Mark 16:17–34

Trevinal AM, Stenger T (2014) Toward a conceptualization of the online shopping experience. J Retail Consum Serv 21:314–326

Triantafillidou A, Siomkos G (2018) The impact of facebook experience on consumers’ behavioral brand engagement. J Res Interact Mark 12:164–192

Turner P (2017) A psychology of user experience: involvement, Affect and Aesthetics. Springer, Cham

Underwood LG, Teresi JA (2002) The daily spiritual experience scale: development, theoretical description, reliability, exploratory factor analysis, and preliminary construct validity using health-related data. Ann Behav Med 24:22–33

Van Noort G, Voorveld HA, Van Reijmersdal EA (2012) Interactivity in brand web sites: cognitive, affective, and behavioral responses explained by consumers’ online flow experience. J Interact Mark 26:223–234

Vargo SL, Lusch RF (2008) Service-dominant logic: continuing the evolution. J Acad Mark Sci 36:1–10

Verhoef PC, Lemon KN, Parasuraman A, Roggeveen A, Tsiros M, Schlesinger LA (2009) Customer experience creation: determinants, dynamics and management strategies. J Retail 85:31–41

Walls A, Okumus F, Wang Y, Kwun DJ-W (2011) Understanding the consumer experience: an exploratory study of luxury hotels. J Hosp Mark Manag 20:166–197

Wan Y, Nakayama M, Sutcliffe N (2012) The impact of age and shopping experiences on the classification of search, experience, and credence goods in online shopping. Inf Syst E bus Manag 10:135–148

Whitener EM (2001) Do “high commitment” human resource practices affect employee commitment? A cross-level analysis using hierarchical linear modeling. J Manag 27:515–535

Won Jeong S, Fiore AM, Niehm LS, Lorenz FO (2009) The role of experiential value in online shopping: the impacts of product presentation on consumer responses towards an apparel web site. Internet Res 19:105–124

Wooten DB, Reed A II (1998) Informational influence and the ambiguity of product experience: order effects on the weighting of evidence. J Consum Psychol 7:79–99

Yoon D, Youn S (2016) Brand experience on the website: its mediating role between perceived interactivity and relationship quality. J Interact Advert 16:1–15

Zarantonello L, Schmitt BH (2010) Using the brand experience scale to profile consumers and predict consumer behaviour. J Brand Manag 17:532–540

Zarantonello L, Schmitt BH (2013) The impact of event marketing on brand equity: the mediating roles of brand experience and brand attitude. Int J Advert 32:255–280

Zenetti G, Klapper D (2016) Advertising effects under consumer heterogeneity–the moderating role of brand experience, advertising recall and attitude. J Retail 92:352–372

Zhang H, Lu Y, Gupta S, Zhao L (2014) What motivates customers to participate in social commerce? The impact of technological environments and virtual customer experiences. Inf Manag 51:1017–1030

Zhang H, Lu Y, Wang B, Wu S (2015) The impacts of technological environments and co-creation experiences on customer participation. Inf Manag 52:468–482

Zolfagharian M, Jordan AT (2007) Multiracial identity and art consumption. In: Belk RW, Sherry JF Jr (eds) Consumer culture theory. JAI Press, Oxford

Download references

Acknowledgements

We would like to thank editor-in-chief (Prof. Dr Joern Block), and the anonymous reviewers for their constructive comments on this paper.

Author information

Authors and affiliations.

Department of Marketing, Faculty of Business and Accountancy, Graduate School of Business, University of Malaya, Kuala Lumpur, Malaysia

Muhammad Waqas & Zalfa Laili Binti Hamzah

Department of Operation and Management Information System, Faculty of Business and Accountancy, Graduate School of Business, University of Malaya, Kuala Lumpur, Malaysia

Noor Akma Mohd Salleh

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Zalfa Laili Binti Hamzah .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

See Table  8 .

See Table  9 .

Rights and permissions

Reprints and permissions

About this article

Waqas, M., Hamzah, Z.L.B. & Salleh, N.A.M. Customer experience: a systematic literature review and consumer culture theory-based conceptualisation. Manag Rev Q 71 , 135–176 (2021). https://doi.org/10.1007/s11301-020-00182-w

Download citation

Received : 08 May 2019

Accepted : 10 February 2020

Published : 15 February 2020

Issue Date : February 2021

DOI : https://doi.org/10.1007/s11301-020-00182-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Customer experience
• Literature review
• Consumer culture theory
• Online experience

JEL Classification

• Find a journal
• Publish with us
• Track your research