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Systematic Review

How Information Technology (IT) Is Shaping Consumer Behavior in the Digital Age: A Systematic Review and Future Research Directions

E-Commerce Department, College of Administrative and Financial Sciences, Saudi Electronic University, Riyadh 11673, Saudi Arabia
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(4), 1556; https://doi.org/10.3390/su16041556
Submission received: 26 November 2023 / Revised: 1 February 2024 / Accepted: 2 February 2024 / Published: 12 February 2024

Abstract

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The success of modern businesses hinges on their capability to recognize and explore emerging patterns in consumer behavior within the context of information technology (IT). While the study of consumer behavior has made notable progress, there remains a need to study the convergence between IT and consumer behavior to discover new prospects and insights that can improve business performance. Therefore, conducting a thorough study to evaluate the current state of research in this area is imperative. This endeavor can accumulate and map current research, extending knowledge and good practices for businesses and stakeholders. This study studied the intersection of IT and consumer behavior using the systematic literature review (SLR) approach and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The primary objective was to review the comprehensiveness of systematic review reports and meta-analysis studies in journals indexed with the SSCI and SCIE categories of the Web of Science. After applying the PRISMA approach, a sample of 40 eligible articles was finalized for further review. It identified four critical themes related to research: technological diffusion, disruptive consumer behavior, IT and consumer behavior, and the impact of IT on consumer behavior. The study’s results deliver practical implications for businesses and stakeholders and contribute to progressing knowledge in this domain.

1. Introduction

Over the last century, information technology (IT) has drastically changed how people live and work worldwide, and the business community has yet to be immune to this disruption. To remain relevant and competitive in the market, businesses must embrace technology to interact with customers, survey their needs, develop superior products, and optimize their organizations to deal with transformations [1]. The acceptance and adoption of IT by consumers worldwide have altered their lifestyles. Even though adopting and implementing IT is a relatively ongoing process, once it becomes a reality, consumers tend to engage in IT practices over an extended period. In addition, IT helps businesses obtain customer information more rapidly and gain a competitive advantage through marketing strategies [1,2]. IT and consumer behavior have made markets more transparent, proposing opportunities and challenges for companies. The hospitality industry is an ideal example of an industry that has transformed into a multifaceted industry due to IT development [3,4,5].
Moreover, IT development and launching information and communication technology (ICT) have progressively generated momentous transformations in consumer behavior [6,7]. Surprisingly, these transformations have resulted in a shift in consumers’ overall behavior, leading to attention to the overall business strategies in the hospitality sector. IT has motivated consumers to augment their overall consumption in the Internet era [8]. The practicality of online experience no longer fascinates consumers with the fast growth of the Internet. However, with the advancement in IT, a real-world experience can be presented to consumers. The continued adjustments to meet consumer demand and the broadening of marketing channels have originated predictable marketing means, and consumers concentrated on instant shopping experience have engaged in online consumption, which profoundly relies on the Internet and can be increased by boosting consumer trust [9]. Subsequently, various studies investigated the role of consumer trust vis-à-vis behavioral intentions in the online market setting [10]. In the meantime, online consumption has exhibited rapid progress with advances in IT, and businesses have used diverse ICT tools to alter consumers’ buying behavior [11]. Consumers use diverse ICT tools like consumer review sites, blogs, social media platforms, and online social communities to connect, communicate, and engage with other consumers by posting reviews and sharing their online purchase experiences. This generates electronic word-of-mouth (eWOM) over online platforms and further impacts consumers’ buying behavior [12,13]. However, the mounting significance of eWOM strategies, accompanied by topical Internet trends, has caused an upsurge in online customer reviews. This has a constructive and explicit influence on consumers’ purchase decision-making process [12,13,14].
A previous study employed and explored the SLR approach in the context of ICT and its environmental effects [15]. The SLR approach was used to study e-businesses’ influence on the environment [16]. Furthermore, “green ICT” and the research application of knowledge management systems were investigated using the SLR approach [17]. Another study explored ICT’s role in “green logistics” [18]. ICT’s direct environmental consequences were assessed in a similar study [19]. Several known surveys were conducted in the context of IT and consumer behavior using the SLR approach. Hence, future studies need to consider the practical and theoretical influence of IT on consumer behavior. In addition, the interplay between information technologies and consumer behavior, which is still unexplored, ought to be explored, as little to no research is available investigating the interplay between them. However, a study on live-streaming commerce that highlighted consumers’ impulsive buying behavior was identified [20]. Existing research studies confirm that IT in the marketing domain is a well-recognized and acknowledged concept by the business community and, consequently, has gained much attention from researchers and marketing practitioners.
Consumer behavior is dynamic; hence, it must be continuously studied to explore its interplay with IT. The current study is an effort in this direction and aims to report the existing gaps in the literature. Furthermore, this study is different from other existing studies, as we not only employed the SLR approach but also employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines (Supplementary Materials) to systematically map or chart the literature addressing the interplay between IT and consumer behavior by locating the most eligible articles based on the full-text review [21,22,23]. The main objective of this study is to provide valuable theoretical insights into IT and consumer behavior research. The findings are anticipated to assist researchers, scholars, businesses, marketers, and practitioners in gaining a more accurate understanding of the interplay between IT and consumer behavior. The results can also contribute to cultivating conceptual acumen in this field. To bridge the observed gaps in the extant research, the following research questions were posed:
RQ1: What are the key themes, key domains, geographical contexts, key characteristics, and key methodologies evident in the extant literature?
RQ2: In what ways does the interplay between IT and consumer behavior exist in the extant literature?
RQ3: What are the key research questions for further research on the interplay between IT and consumer behavior?
The article’s remainder is organized as follows. Section 2 outlines the methodology employed in this study, highlighting the systematic literature review approach, electronic database selection, and article extraction process using the PRISMA approach. Section 3 delivers the key results of the study. Section 4 provides discussions based on the study’s results. The significant theoretical and practical implications of the study, limitations, and future research directions that arise from this work are summarized in Section 5. The study’s conclusion is outlined in Section 6, followed by references.

2. Methodology Used

2.1. Research Approach

Literature reviews generally explore the contemporary significance of conceptual understanding of various topics in research studies. Researchers can achieve their research objectives by addressing the research questions related to their field of research, and different methods of conducting literature reviews are available to map and assess the research area. The systematic literature review (SLR) approach is a suitable research method for performing a literature review to gather relevant articles and produce better insights by reviewing extant works of literature [24]. Many literature review approaches have been devised to enable scholars and researchers to discover answers to diverse research questions and address the prevailing research gaps. These approaches include but are not limited to integrative reviews [25], narrative reviews [26], systematic literature reviews [24], and meta-analyses [21,27]. These approaches enable scholars and researchers to systematically discuss the key results of their research, thereby contributing to the advancement of knowledge in their respective domains.

2.2. Justification of the Selected Research Approach

The study employs the systematic literature review (SLR) approach, a scientific procedure to ensure methodological supervision [28]. The SLR approach was chosen over existing literature review approaches for several reasons. Firstly, it is considered more objective than the narrative review approach [24]. Secondly, using a quantitative approach, the SLR method identifies existing research gaps and provides better insights based on a review of contemporary works of literature [29]. Lastly, the SLR approach enables the generation of wide-ranging conclusions, confining bias and facilitating replicability [30,31,32]. Consequently, the SLR approach is appropriate for accomplishing the objectives of this study. Moreover, the SLR was conducted following the PRISMA protocol 2020 guidelines to ensure transparency and accuracy of the reported reviews [21,33,34]. Though the PRISMA protocol was initially created in the healthcare sector, it has also been adopted and widely used in the social sciences, including business, marketing, and tourism [22,23]. By combining the SLR approach and the PRISMA protocol, this study confirms the excellent quality of input and furnishes valuable insights into studying the interplay between IT and consumer behavior.

2.3. Selection and Justification of Database

For extracting relevant articles, various renowned electronic databases, namely the Web of Science (WoS), Google Scholar, IEEE, Emerald, EBSCO, Scopus, and ScienceDirect, are accessible for a research study. Scopus and the WoS electronic databases are leading electronic databases in diverse specific disciplines and are repeatedly commissioned to investigate extant works of literature [35]. Elsevier Science developed the Scopus electronic database in 2004, a leading electronic database of peer-reviewed research literature in the multidisciplinary fields of studies based on citation and abstract. Gradually, the Scopus database became a valuable tool for conducting review-based research studies [36,37]. The WoS, introduced in 1964 by Thomson Reuters (ISI), is the oldest electronic database with four Web of Science index categories, i.e., SSCI, SCIE, ESCI, and A&HCI [38]. However, based on the evaluation of both electronic databases (i.e., WoS and Scopus), it was found that WoS has followed a selective approach in its journal coverage, which goes back to the year 1990 with a high impact factor and has robust coverage of research domains while the Scopus database has a higher quantity of quality journals but with lower impact factor or no impact factor [39].

2.4. Review Protocol and Temporal Boundary

Using the Web of Science (WoS) database, we searched relevant articles about the interplay between IT and consumer behavior using the keywords Information Technolog*, Consumer Behav*, and Customer Behav*. A temporal boundary was specified for choosing articles based on their publication period to ensure a rigorous and thorough literature review. The deadline for having articles in the review was 31 December 2022, which functioned as a cutoff date for including relevant articles. Any articles published before this date underwent initial data screening to specify the final sample of the most eligible articles.

2.5. Data Screening

Firstly, to obtain the most suitable search results, a search using exact keywords, i.e., “Information Technolog*” AND “Consumer Behav*” OR “Customer Behav*” was used in the “Topic” search field using the Boolean operators “AND” and “OR” along with the stated keywords and 479 articles were displayed. Secondly, a search using exact keywords, i.e., “Information Technolog*” AND “Consumer Behav*” OR “Customer Behav*” was used in the “Abstract” search field, and 125 articles were found. Thirdly, inclusion criteria (document type: article and language: English) were used, and 66 articles were displayed. Finally, full-text articles were assessed using exclusion criteria, i.e., articles not indexed with the SSCI and SCIE, articles with open access restriction, and irrelevant articles were excluded. The final eligible sample size was 40 articles, and the PRISMA-based article selection protocol is shown in Figure 1. Therefore, this study’s systematic review of literature has 40 eligible articles.

2.6. Sample Size Justification

The study’s data screening led to selecting the 40 most relevant articles for analysis, indicating the smallest sample size. Although this final sample size is comparatively modest and represents a small sample size, this selection based on the smallest sample size level of 40 articles is justified following the rule of thumb regarding the smallest sample size level [32]. For the minimum threshold value of 40 articles, a study published in the Journal of Business Research adhered to this rule of thumb and systematically reviewed the literature on the digital entrepreneurship domain [32]. Considering the multidisciplinary nature of the present study, 40 eligible articles achieve the maturity level necessary for a systematic literature review. This study has 40 articles, which are sufficiently mature for review to examine the relationship between IT and consumer behavior. Therefore, “the rule of thumb” permits our study to contribute significantly to the field using the SLR approach, and 40 eligible articles are an acceptable minimum threshold value [40].

2.7. Data Extraction and Analysis

The information from 40 eligible articles was exported into a Microsoft Excel spreadsheet, and the critical information about the articles was recorded in tabular format, including author details, article title, journal name, publication year, abstract, and citation. Table 1 displays the journals selected for the final study. Web of Science analytics and Microsoft Excel Version 2010 have been employed to assess the data to address the stated research questions (RQs).

3. Results

3.1. Study Selection Process

Table 1 and Figure 1 present a general idea of the final selection process of eligible articles related to this study. The preliminary review in the WoS database detected a total of 479 records, of which 101 records were rejected since they did not meet the stated eligibility criteria of this study, 199 documents in irrelevant subject areas (e.g., mathematics), and 54 articles related to trade journals, early access, review articles, and editorial materials. Consequently, 125 articles were deemed eligible for the title–abstract–keyword screening. After the screening, 59 articles were eliminated due to a dearth of pertinency, and 66 articles were selected for full-text evaluation since they meet the inclusion criteria (i.e., relevance to the study objective). Using the PRISMA protocol, 66 articles were screened based on the abstract. Afterward, a full-text reading and review were conducted for each article after downloading it to ensure only articles related to IT and consumer behavior were selected. After reading the full text, seven articles were excluded due to open access restriction, 12 articles were excluded for not being indexed in the SSCI and SCIE categories of Web of Science, and seven articles’ contents were found irrelevant based on the full-text review of each article. Articles not related to IT or consumer behavior were declared irrelevant in the final selection of the articles, leading to 40 eligible articles for inclusion in the final review.

3.2. Study Characteristics

Table 2 illustrates the main characteristics of our selected final sample, 40 articles. The significant results of this study have detected several key factors related to the research theme. The most prominent critical factors identified were customer preferences [41,42,43], consumer dynamism [44], big data influence [45], consumer informedness [46], e-satisfaction [47], consumer privacy [48], and purchasing behavior [49].
The review of the publication year reveals that 50.00% of the articles were published before 2019, while the remaining 50.00% were published in 2019 or after (see Figure 2).
The identified studies were published in business, management, and information journals, such as the International Journal of Research in Marketing, Internet Research, Journal of Business & Industrial Marketing, Journal of Cleaner Production, Journal of Consumer Behaviour, Journal of Service Research, Management Science, MIS Quarterly, Mobile Information Systems, and Psychology & Marketing. Of these, 70.00% of articles were published in the SSCI category of the Web of Science indexed journals, while 30.00% were published in the SCIE category of the Web of Science indexed journals, as shown in Figure 3. As regards the geographical location of the identified studies, the geographical context of each study was determined based on the first author’s affiliation. Our study shows that 20.00% of the studies were conducted in China (eight studies), revealing a mounting concern on the IT and consumer behavior survey in this region. The remaining studies, i.e., 80.00% (32 studies), were carried out in other areas, including Taiwan, USA, UK, Finland, Spain, India, Spain, Romania, Pakistan, Turkey, Iran, Netherlands, Sweden, Lithuania, Germany, and Ecuador as shown in Table 3 and Figure 4.
The present study’s analysis of industry contexts discloses that a substantial proportion of the studies, i.e., 25.00%, were related to the electronic commerce sector, comprising ten studies. Similarly, 20.00% of the studies explored the hospitality and tourism industry (eight studies), while 17.50% focused on retailing (seven studies). Other industries that were identified and examined included the banking and financial service industry (two studies), electronics industry (one study), fashion industry (one study), food industry (one study), gaming industry (one study), and health industry (one study). However, it should be noted that the industry remained unknown in 12.50% of the studies. Table 4 furnishes a thorough overview of the industry-related information identified in this study.
Table 5 exhibits the theoretical lens used to understand the interplay between IT and consumer behavior, including institutional theory [59], theory of planned behavior [74], theory of consumer informedness [47], and unified theory of acceptance and use of technology [61] to name a few. As regards the methodologies investigated in the final sample of this study, the assessment of this study illustrates that 57.50% of the studies were conducted using quantitative research methodology, 22.50% of the studies were performed using qualitative research methodology, 12.50% of the studies were conducted using mixed methods, and 07.50% of the studies were conducted using conceptual research methodology. Table 6 illustrates all information about the identified methodologies in this study. Table 7 summarizes all the notable identified characteristics, themes, theories, geographical context, sectoral context, publication trends, etc.
It is notable that within the final sample of 40 articles chosen for the study, it was observed that four articles had obtained over 100 citations each, with citations ranging from 120 to 384, for example, 384 citations [80], 241 citations [74], 126 citations [59], and 120 citations [60]. Such a high number of citations exhibits the importance and relevancy of these articles within the field of study. However, it is indispensable to acknowledge that around 75% of 30 articles also obtained a respectable number of citations, each receiving five or more. This signifies that the selected sample of articles is myriad and deserves recognition with, for instance, eight citations [41], seven citations [49], six citations [44], and five citations [77]. A thorough citation summary of all 40 eligible articles selected for this study is shown in Figure 5 and Table 8, furnishing a clear outline of the influence of the selected articles.

3.3. Thematic Analysis

3.3.1. Technological Diffusion

Advances in electronic social media communities have dramatically altered the acceptance of IT channels for marketing communication between businesses and consumers in the 21st century. As a result of technological diffusion [65] and IT, the Internet has altered the contemporary global business environment [60], while consumers may experience commotion as IT diffusion accelerates [57]. Despite this, it is easier for businesses to survive and sustain themselves in a rapidly changing global business environment if they detect ongoing variations in consumer behavior [71]. Furthermore, consumers’ acceptance of novel IT channels tends to influence overall consumer behavior by creating distinct challenges for international businesses [59,61,75]. Although IT has evolved quickly, digital media proliferated into manifold IT channels [43]. With IT enactment, online social media communities are progressively occupying a key position in the Internet era [79]. Moreover, with the rapid expansion of the Internet (i.e., IT channels), diverse information streamed, resulting in individuals landing in the era of big data as a product of technological diffusion. Hence, there is a need to recognize disruptive consumer behavior, predominantly online, driven by technological diffusion [56].

3.3.2. Disruptive Consumer Behavior

A global business’s greatest challenge is the impact of online stimulus on online consumer behavior, which must be understood to understand how consumer behaviors are enduringly disrupted [50]. Additionally, the interplay between IT and CB has resulted in catastrophic consumer challenges [58]. It has been proven that gamification is a powerful tool for combating disruptive consumer behavior, but only some research papers examine gamification from a consumer behavioral perspective. However, IT successfully defines gamification and, as a consequence, exploring how IT and consumer behavior interact is becoming increasingly popular as IT channels emerge in the IT era [58].

3.3.3. IT and Consumer Behavior

Businesses face multifaceted and inconsistent consumer behaviors in the IT era, and the advent of diverse IT channels, specifically online social networks, has enabled businesses and marketers to leverage social media marketing [52,62]. The IT industry complements and enhances the customer experience by enriching it as a whole [48] and is not a competitor. IT promotes healthier customer relationships and positively disrupts online consumer buying intentions [72,80]. Correspondingly, IT channels have gradually amplified global businesses’ market shares by contributing to better and more advanced customer services [76]. IT also plays a significant role in recognizing customers’ diverse needs and wants, further altering consumer demands in the existing market [41,44]. However, consumers’ product requirements and preferences quickly shifted in the IT era. Hence, it is vital to emphasize building a healthier collaboration relationship with potential and current consumers by deploying diverse IT channels such as the company website, mobile apps, and social media [64,69]. Similarly, businesses can nurture thorough acumen regarding consumer behavior and IT channels’ inclinations by assessing consumers’ opinions of innumerable IT channels [42,49]. Also, consumers’ perception of IT channels can deliver cutting-edge advantages to businesses, which can further impact consumers’ behavioral intentions, and therefore, companies must emphasize them [74]. Likewise, topical developments in IT have driven the fusion of retail channels into one exclusive channel, i.e., an omnichannel, by amalgamating offline and online channels [51]. Websites, mobile apps, and assorted IT channels have been advancing e-satisfaction among consumers, further enhancing customer loyalty [46,66]. However, preceding literature has revealed that despite the fusion of online and offline retail channels, consumers’ retention through mobile apps is minute [77]. Hence, in this era of IT insurgency, companies can consider deploying modern IT tools to inspect notable factors that impact consumer buying decisions and enjoy exploiting fruitful business outcomes because of the interplay between IT and consumer behavior [67].

3.3.4. Impact of IT on Consumer Behavior

Due to the IT insurgency, global businesses engage with potential consumers via various IT channels, leading to diverse consumer behaviors in online consumer buying decisions [54,73]. In the information age, consumers have become more informed by instantly obtaining all the information they need. Furthermore, this consumer informedness instantaneously plays a key role in defining consumer selections of goods and services for IT used by contending businesses in the market [47]. Although IT switching costs and network impact are instrumental in industry rivalries, businesses’ strategies have been well documented in the existing literature. However, a study investigating IT imprint on the behaviors of consumers has yielded little attention [68]. However, the usage of IT has infused and transformed the prevailing business models of distinct businesses in different industrial settings. Globally, IT has changed political, social, and economic business environments. In the tourism industry context, IT has been altering consumer behavior from the outlook of disposition and redefining the conventional understanding of tourists’ buying decision-making process in the IT era [55]. Moreover, the service industry has comprehensively undergone spectacular service delivery interruptions due to IT diffusion [70]. Concerning the online fashion retail industry, strategies for service failure levels and service recovery levels are supported by IT channels, which further led to augmenting overall consumer behaviors through consumer informedness in the IT era [78].
More notably, disruption in the behavioral intents of consumers is dependent on IT due to its interplay with consumer behavior, and big data demonstrates a significant role in the development of businesses in delivering value to customers [53,63]. Consequently, big data’s impact on the overall business process is built up on the IT channels, further enhancing the overall consumer experiences and disrupting consumer behavior [53]. However, companies across the globe are witnessing diverse challenges in managing customer relationships due to drastic digital transformation. Hence, in this condition, the success of customer relationship management (CRM) implementation is decidedly dependent on the IT applications as a byproduct due to the interplay between IT and consumer behavior [45]. The review of the studies has detected four critical themes related to research themes, i.e., technological diffusion [58], disruptive consumer behavior [59,60,65], IT and consumer behavior [66,69,76], and the impact of IT on consumer behavior [53,54,70], which is shown in Table 9.
At present, IT is the foundation of revolution and consumer experience throughout the globe. Businesses can take advantage of IT in numerous ways to assist their customers. Consequently, the matter is how companies can utilize IT to enhance and cope with their influence on consumer behavior. This interplay between IT and CB is shown in Figure 6, which can be a helping hand for businesses and marketers planning their marketing strategies strategically. Hence, the interplay between IT and CB becomes imperative to attract, retain, and maintain existing customers as they will team up to build competitive advantages for businesses.

4. Key Discussion

It was observed by Xiang et al. [81] that IT in the hospitality industry influences consumer behavior. They identified notable consumer behavior trends that can be used strategically for global companies to identify and implement successful and viable integrated marketing communication strategies [81]. Another study casts light on how consumers understand prominent factors related to website quality. It further exemplifies how businesses can accomplish customer delight in virtual business environments and enlighten them regarding outcomes on consumer behavior [64]. Singh et al. [5] used the ILR approach to discover the persistent disruption in consumer behaviors in diverse businesses exclusively in the service industry context [5]. Additionally, a hypothetical framework that blends the discrepancy of attitude proposition with consumer behavioral perceptions and IT dissemination research was proposed, which assisted businesses in understanding the diverse behaviors of consumers [76]. Even though the connection between a business and the consumer may begin to take shape before the consumer buying process, consumers’ satisfaction levels tend to shape their brand loyalty and overall perceptions of companies. Businesses commenced using technology to build personalized customer interactions, directing loyalty and satisfaction [82]. Even though contemporary studies have investigated consumers’ buying process by probing characteristics such as the reasons that impact their buying decisions and how marketplaces can be targeted, there remains a discrete research gap concerning how consumers’ preferences can be premeditated to diverse IT channels [83,84]. In addition, efforts to provide theoretical understandings that may be employed to map products and businesses with consumers’ preferences to augment marketing actions across diverse IT channels are limited [85,86,87]. Recently, practitioners, researchers, scholars, and marketers have been attracted to the concept of gamification, which focuses generally on customers and is concerned with disruptions in consumer behavior. This literature has put forward a unified agenda for gamification, which supports and further influences online consumer behavior [50]. Also, another study examined online health communities in Iran and contributed to a better insight into consumer behavior employing the Iranian health service sector [65].
The current literature is lacking in this study area in terms of precisely creating integrated marketing strategies. Most businesses recognize the necessity of understanding consumer behavior and preferences regarding online channels [5,76,81]. Unlike preceding research studies, the current study presents significant contributions to IT and CB. Firstly, it categorizes novel thematic insights about the interplay between IT and CB, which makes this study different from existing literature. This study has presented an overview of key themes, key theories, diverse geographical and sectoral/industrial contexts, key factors, etc., to support businesses and marketers in enhancing their overall understanding of this field of study. This study aims to fill the literature-based gaps by identifying the interplay between IT and consumer behavior. This study differs from existing research by analyzing the intricate interplay between IT and CB by implementing the SLR approach and adhering to the PRISMA 2020 guidelines. In contrast to prior studies that failed to propose future research questions in this area, this study presents FRQs that can guide future research [32]. This approach will enable scholars to build upon our findings and contribute to advancing knowledge in IT and CB.

5. Implications, Limitations, and Future Research Directions

5.1. Theoretical and Practical Implications

This study contributes to theoretical and practical knowledge by complementing the evolving theoretical insights among academicians, researchers, and scholars concerning the interplay between IT and CB. From an academic perspective, this study delivers further insights based on the explicitness of the interplay between IT and CB, which may help academics, researchers, and scholars enrich their understanding of this body of research by providing robust conceptual underpinnings. Second, the method (SLR and PRISMA) complements distinctive approaches suitable for multidisciplinary research themes. In addition, this study has practical implications for various industries across diverse geographical locations, and marketers, businesses, and other stakeholders might consider this study as a manual to heighten their conceptual understanding so that they can use it practically in businesses.

5.2. Limitations and Future Research Directions

The study contributes significantly to understanding the relationship between IT and consumer behavior research. Despite this, the study has several limitations. First, data were extracted from the Web of Science database. Therefore, further research may consider using other databases like ScienceDirect or Scopus to extract data. Second, the study only considered articles published in SSCI- and SCIE-indexed journals, so researchers and scholars may prefer to use different journal rankings (e.g., ABDC, ABS, ERA) to identify and extract relevant articles related to their research area. As a third point, eligible literature about the research theme has been reviewed using the PRISMA 2020 guidelines. Therefore, future researchers and scholars may consider using alternative approaches like integrative literature review, meta-analysis, and structured literature review to analyze the topic comprehensively. Fourth, the inclusion criterion regarding article type may limit the scope of the study, and future research studies may consider selecting other document types, such as conference articles. Finally, the study’s publication boundary is limited to 31st December 2022. Consequently, other researchers may choose articles published after this date. Future research studies can study the future research questions (FRQs) outlined in Table 10 to advance theoretical insights on how IT shapes consumer behavior in the digital age.
Moreover, further study can either utilize a conceptual approach (integrative literature review, meta-analysis, structured literature review, SLR, PRISMA, etc.) or might consider using an empirical approach (i.e., qualitative, quantitative, or mixed). Researchers can also employ different inclusion/exclusion criteria and use publication periods up to the present date or might consider screening articles published between 2000 and 2010 or 2010 to 2020. By extending the sample size (i.e., more than 40), researchers and scholars might consider investigating this theme either by employing the Web of Science database or by utilizing multiple databases, namely, IEEE Xplore, Google Scholar, Emerald, ScienceDirect, EBSCOhost, Scopus, etc. Researchers might consider using categories other than Web-of-Science-indexed journals or can consider employing ABDC/ABS/ERA-indexed journals, the selection of journals based on citations/impact factors, etc. However, the present study focuses primarily on the broader impact of IT on consumer behavior in the digital landscape. There are still many questions about how artificial intelligence (AI) impacts consumer behavior and how it helps businesses and consumers, and researchers and scholars might consider them in future research endeavors. Valuable insights into the impact of AI on consumer behavior in the contemporary era are needed to help businesses and academic communities.

6. Conclusions

Internet usage has enabled global customers throughout the globe to access information rapidly with a click of a button [48], making them more receptive to the information they receive. Due to the rapid development of IT, digital platforms can gather, use, and share large amounts of specific consumer information. However, these behaviors may endanger information security, thus causing privacy concerns among consumers [88]. Bearing this in mind, unambiguously owing to the desire to identify consumer buying behavior in the virtual setting, it has become tremendously imperative to comprehend how IT (e.g., online social networks) impacts CB [52]. Generally, contemporary business practices are renovated by digital transformation, principally in the service industry. This endless alteration in consumer behavior has further renovated global businesses’ traditional and digital ecosystems [5]. Hence, there was a need to investigate this interplay of IT and CB. The study was an endeavor to explore the interplay between them by employing the SLR approach to address the identified literature-based gap. The PRISMA protocol was applied to select the most eligible articles based on a full-text review. After using this approach, 40 eligible articles were designated as the final sample. The findings of this research have uncovered four key themes, i.e., technological diffusion, disruptive consumer behavior, IT and consumer behavior, and the impact of IT on consumer behavior.
In an age of globalization, the speedy implementation of information technology in businesses significantly impacts how companies relate to their customers. A consumer’s willingness to engage in electronic commerce depends on their prior knowledge of ICT, the perceived usefulness, the ease of use, and the platform’s trustworthiness [89]. Consumer trust and privacy concerns are significant barriers that may lower customer enthusiasm for online purchasing. However, e-commerce platforms have successfully addressed these concerns by providing customers with privacy and security through information technology [90,91,92]. The advent of the Internet and ICT has significantly altered consumer behavior, shifting how customers interact with businesses and make purchasing decisions [41,62,93]. Companies must acknowledge disruptions in consumer behavior in the long run to survive in a fast, disruptive business environment, a significant challenge they must confront. Consequently, the present study provides a holistic picture of the key characteristics, theories, themes, and many others when examining how IT and CB interact to sense disruptive consumer behaviors [71].

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su16041556/s1, PRISMA 2020 Checklist.

Author Contributions

Conceptualization, P.S., L.K., B.N. and I.A.; methodology, P.S.; software, P.S.; validation, L.K., I.A. and B.N.; formal analysis, P.S.; investigation, I.A.; resources, L.K.; data curation, P.S. and B.N.; writing—original draft preparation, P.S.; writing—review and editing, P.S., L.K., B.N. and I.A.; visualization, P.S.; supervision, L.K. and I.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data used to support the results of this study are included in this article.

Acknowledgments

The authors would like to thank all anonymous reviewers and the journal editorial team for their substantial contributions in making this work impactful.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. PRISMA-based article selection protocol.
Figure 1. PRISMA-based article selection protocol.
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Figure 2. Publication trend based on year of publication.
Figure 2. Publication trend based on year of publication.
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Figure 3. Classification of studies based on the Web of Science Index.
Figure 3. Classification of studies based on the Web of Science Index.
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Figure 4. Geographical dispersion of the selected articles.
Figure 4. Geographical dispersion of the selected articles.
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Figure 5. Year-wise Chart based on Publications and Citations.
Figure 5. Year-wise Chart based on Publications and Citations.
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Figure 6. Interplay between IT and Consumer Behavior.
Figure 6. Interplay between IT and Consumer Behavior.
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Table 1. A list of journals selected based on indexing in the SSCI and SCIE in the Web of Science categories.
Table 1. A list of journals selected based on indexing in the SSCI and SCIE in the Web of Science categories.
S. No.List of JournalsNo. of Article(s) SelectedSSCI/SCIE Indexing
1Business & Information Systems Engineering1SSCI
2Computational Intelligence and Neuroscience1SSCI
3Computers in Human Behavior1SSCI
4Economic Computation & Economic Cybernetics Studies & Research1SCIE
5Engineering Economics1SSCI
6Expert Systems with Applications1SSCI
7Financial Innovation1SSCI
8Frontiers in Psychology1SSCI
9IEEE Access1SCIE
10Information & Management1SCIE
11Information Systems Journal1SSCI
12Information Systems Research1SSCI
13Information Technology and Management2SSCI
14International Journal of Contemporary Hospitality Management1SSCI
15International Journal of Information Management1SSCI
16International Journal of Market Research1SSCI
17International Journal of Research in Marketing1SSCI
18Internet Research1SCIE
19Journal of Business & Industrial Marketing1SSCI
20Journal of Cleaner Production1SCIE
21Journal of Consumer Behaviour1SSCI
22Journal of Environmental Protection and Ecology1SSCI
23Journal of Global Information Management1SSCI
24Journal of Hospitality and Tourism Technology1SSCI
25Journal of Information Technology1SCIE
26Journal of Macroeconomics1SSCI
27Journal of Organizational and End User Computing1SCIE
28Journal of Organizational Computing and Electronic Commerce1SCIE
29Journal of Service Research1SSCI
30Management Science1SCIE
31MIS Quarterly2SCIE
32Mobile Information Systems1SSCI
33Psychology & Marketing1SSCI
34Sustainability1SCIE
35Sustainable Cities and Society1SSCI
36Technology in Society1SSCI
37The Service Industries Journal1SSCI
38Tourism Management1SSCI
Grand Total40
Table 2. Key Characteristics investigated in IT and Consumer Behavior studies.
Table 2. Key Characteristics investigated in IT and Consumer Behavior studies.
SourceKey Characteristics
[41]Key Factor: Customer preferences, Year: 2011, Country: China
[44]Key Factor: Consumer dynamism, Year: 1997, Country: Sweden
[45]Key Factor: Customer relationship management, Publication trend: 2022, Country: Spain
[46]Key Factor: E-satisfaction, Year: 2012, Country: USA
[47]Key Factor: Consumer informedness, Year: 2014, Country: Netherlands
[48]Key Factor: Consumer perspective, Publication trend: 2020, Country: USA
[49]Key Factor: Consumer privacy, Publication trend: 2019, Country: USA
[50]Key Factor: Consumer engagement, Year: 2016, Country: Lithuania
[51]Key Factor: Consumers’ cross-channel search behavior, Publication trend: 2017, Country: USA
[52]Key Factor: Purchasing behavior, Publication trend: 2018, Country: Romania
[53]Key Factor: Big data influence, Publication trend: 2021, Country: USA
[54]Key Factor: Online purchasing, Publication trend: 2022, Country: China
Note: The reported frequencies are based on 40 selected articles from the final sample.
Table 3. Geographical contexts investigated in IT and Consumer Behavior studies.
Table 3. Geographical contexts investigated in IT and Consumer Behavior studies.
CountryNo. of Identified Studies (%)Exemplary Studies
China8 (20.00)[55,56,57,58,59,60]
Ecuador1 (2.50)[61]
Finland1 (2.50)[62]
Germany2 (5.00)[63,64]
India2 (5.00)[43]
Iran1 (2.50)[65]
Lithuania1 (2.50)[50]
Netherlands1 (2.50)[47]
Pakistan1 (2.50)[66]
Romania2 (5.00)[67]
Spain2 (5.00)[68]
Sweden1 (2.50)[44]
Taiwan6 (15.00)[69,70,71,72,73,74]
Turkey1 (2.50)[75]
UK5 (12.50)[76,77,78,79]
USA5 (12.50)[49,51,80]
Note: The reported frequencies are based on 40 selected articles from the final sample.
Table 4. Industry contexts investigated in IT and Consumer Behavior studies.
Table 4. Industry contexts investigated in IT and Consumer Behavior studies.
IndustryNo. of Identified Studies (%)Exemplary Studies
Banking and Financial Service Industry2 (5.00)[76]
Electronic Commerce10 (25.00)[42,54,61,71,79]
Electronics Industry1 (2.50)[58]
Fashion Industry1 (2.50)[78]
Food Industry1 (2.50)[67]
Gaming Industry1 (2.50)[50]
Health Industry1 (2.50)[65]
Hospitality and Tourism Industry8 (20.00)[53,55,56,60]
IT Industry1 (2.50)[72]
Real-Estate1 (2.50)[49]
Retailing7 (17.50)[69,75,77]
Telecom Industry1 (2.50)[68]
Unknown5 (12.50)[52,63,73]
Note: The reported frequencies are based on 40 selected articles from the final sample.
Table 5. Notable key theories investigated in IT and consumer behavior studies.
Table 5. Notable key theories investigated in IT and consumer behavior studies.
SourceTheoretical Lens
[59]Institutional theory
[74]Theory of planned behavior
[41]Long tail theory
[80]Signaling theory
[65]Social support theory
[47]Theory of consumer informedness
[61]Theory of social support
[66]Unified theory of acceptance and use of technology (UTAUT)
[77]ECM-IT theory
[55]Optimum stimulation level theory
[76]Theory of cognitive dissonance
Table 6. Methodologies investigated in IT and consumer behavior studies.
Table 6. Methodologies investigated in IT and consumer behavior studies.
MethodologyNo. of Studies Identified (%)Exemplary Studies
Conceptual3 (7.50)[59]
Empirical—Qualitative9 (22.50)[44,45,49,58,78]
Empirical—Quantitative23 (57.50)[46,52,54,55,61,66,67,72,73,74,76]
Empirical—Mixed approach5 (12.50)[42,65,75]
Note: The reported frequencies are based on 40 selected articles from the final sample.
Table 7. Summary Table in IT and Consumer Behavior studies.
Table 7. Summary Table in IT and Consumer Behavior studies.
S. No.PublisherPublication YearAuthor(s)Article TitleKey Factor(s)Theoretical LensMethodologyKey Theme(s)Domain ContextGeographical Context
1Springer2011Hou, HP; Hu, MY; Chen, L; Choi, JYAn enhanced model framework of personalized material flow servicesCustomer preferencesLong tail theoryEmpirical—QualitativeIT and consumer behaviorRetailingChina
2Elsevier Science Bv1997Wikstrom, SRThe changing consumer in SwedenConsumer dynamismEnabling strategyEmpirical—QualitativeIT and consumer behaviorRetailingSweden
3Elsevier Science Bv2019Xuan, CJ; Kim, CJ; Kim, DHNew dynamics of consumption and outputDynamics of consumptionState-space modelEmpirical—QuantitativeTechnological diffusionRetailingChina
4Elsevier Sci Ltd.2018Tong, X; Nikolic, I; Dijkhuizen, B; van den Hoven, M; Minderhoud, M; Wackerlin, N; Wang, T; Tao, DYBehaviour change in post-consumer recycling: Applying agent-based modelling in social experimentPerceived behavioral controlSocial experimentEmpirical—QualitativeDisruptive consumer behaviorElectronics industryChina
5Kaunas Univ Technol2016Gatautis, R; Vitkauskaite, E; Gadeikiene, A; Piligrimiene, ZGamification as a Mean of Driving Online Consumer Behaviour: SOR Model PerspectiveConsumer engagementStimulus–organism–reaction (SOR) modelConceptualDisruptive consumer behaviorGaming industryLithuania
6Elsevier2019Alamaniotis, M; Bourbakis, N; Tsoukalas, LHEnhancing privacy of electricity consumption in smart cities through morphing of anticipated demand pattern utilizing self-elasticity and genetic algorithmsConsumer privacy Not specifiedEmpirical—QualitativeIT and consumer behaviorReal-estateUSA
7Springer2015Huang, CK; Chang, TY; Narayanan, BGMining the change of customer behavior in dynamic marketsCustomer purchasing patternsFuzzChgMining modelEmpirical—QualitativeTechnological diffusionElectronic commerceTaiwan
8Igi Global2017Khatwani, G; Srivastava, PRAn Optimization Model for Mapping Organization and Consumer Preferences for Internet Information ChannelsConsumer preferencesOptimization modelEmpirical—Mixed methodsIT and consumer behaviorElectronic commerceIndia
9Elsevier Sci Ltd.2006Kim, WG; Ma, XJ; Kim, DJDeterminants of Chinese hotel customers’ e-satisfaction and purchase intentionsE-satisfaction and purchase intentionsNot specifiedEmpirical—QuantitativeTechnological diffusionHospitality and tourism industryChina
10Frontiers Media Sa2022Li, QY; Xu, H; Hu, YBAre you a spontaneous traveler? Effect of sensation seeking on tourist planfulness in the mobile eraSensation seekingOptimum stimulation level theoryEmpirical—QuantitativeImpact of IT on consumer behaviorHospitality and tourism industryChina
11Elsevier Sci Ltd.2014Hajli, MNDeveloping online health communities through digital mediaPerceived valueSocial support theoryEmpirical—Mixed methodsTechnological diffusionHealth industryIran
12Igi Global2018Khatwani, G; Srivastava, PRImpact of Information Technology on Information Search Channel Selection for ConsumersConsumer preferencesNot specifiedEmpirical—QuantitativeTechnological diffusionUnknownIndia
13Sage Publications Ltd.2017Ozuem, W; Patel, A; Howell, KE; Lancaster, GAn exploration of consumers’ response to online service recovery initiativesConsumer perceptionsNot specifiedEmpirical—QualitativeImpact of IT on consumer behaviorFashion industryUK
14Informs2014Li, T; Kauffman, RJ; van Heck, E; Vervest, P; Dellaert, BGCConsumer Informedness and Firm Information StrategyConsumer informednessTheory of consumer informednessEmpirical—Mixed methodsImpact of IT on consumer behaviorHospitality and tourism industryNetherlands
15Palgrave Macmillan Ltd.2009Maicas, JP; Polo, Y; Sese, FJThe role of (personal) network effects and switching costs in determining mobile users’ choiceConsumer perceptionsUtility modelEmpirical—QuantitativeImpact of IT on consumer behaviorTelecom industrySpain
16Pergamon-Elsevier Science Ltd.2015Galehbakhtiari, S; Pouryasouri, THA hermeneutic phenomenological study of online community participation Applications of Fuzzy Cognitive MapsOnline communitiesNot specifiedEmpirical—Mixed methodsTechnological diffusionElectronic commerceUK
17Hindawi Ltd.2022Li, R; Xu, X; Dong, SConstruction of Precision Sales Model for Luxury Market Based on Machine Learning
Consumption behaviorNot specifiedEmpirical—QualitativeTechnological diffusionElectronic commerceChina
18Hindawi Ltd.2022Li, XThe Impact of the Live Delivery of Goods on Consumers’ Purchasing Behaviour in Complex Situations Based on Artificial Intelligence TechnologyOnline purchasingNot specifiedEmpirical—QuantitativeImpact of IT on consumer behaviorElectronic commerceChina
19Wiley2008Martinsons, MGRelationship-based e-commerce: theory and evidence from ChinaConsumer behaviorInstitutional theoryConceptualTechnological diffusionElectronic commerceChina
20Emerald Group Publishing Ltd.2009Lu, HP; Su, PYJFactors affecting purchase intention on mobile shopping web sitesCustomers’ perceptionsTheory of planned behaviorEmpirical—QuantitativeIT and consumer behaviorElectronic commerceTaiwan
21Pergamon-Elsevier Science Ltd.2009Liao, SH; Chen, CM; Hsieh, CL; Hsiao, SCMining information users’ knowledge for one-to-one marketing on information applianceCustomer relationshipNot specifiedEmpirical—QuantitativeImpact of IT on consumer behaviorUnknownTaiwan
22Wiley2021Yuksel, CU; Kaya, CTraces of cultural and personal values on sustainable consumption: An analysis of a small local swap event in Izmir, TurkeySustainable consumptionNot specifiedEmpirical—Mixed methodsTechnological diffusionRetailingTurkey
23IEEE-Inst Electrical Electronics Engineers Inc2018Mendoza-Tello, JC; Mora, H; Pujol-Lopez, FA; Lytras, MDSocial Commerce as a Driver to Enhance Trust and Intention to Use Cryptocurrencies for Electronic PaymentsTrust and intention to useTheory of social supportEmpirical—QuantitativeTechnological diffusionElectronic commerceEcuador
24Emerald Group Publishing Ltd.2020Demirciftci, T; Chen, CC; Erdem, MA tabulation of information technology and consumer behavior in hospitality revenue management researchConsumer perspectiveNot specifiedConceptualIT and consumer behaviorHospitality and tourism industryUSA
25Elsevier Science Bv2014Shih, SP; Lie, T; Klein, G; Jiang, JJInformation technology customer aggression: The importance of an organizational climate of supportEmployee’s emotionsNot specifiedEmpirical—QuantitativeIT and consumer behaviorIT industryTaiwan
26Soc Inform Manage-Mis Res Cent2011Wells, JD; Valacich, JS; Hess, TJWhat signal are you sending? How website quality influences perceptions of product quality and purchase intentionsConsumer perceptionsSignaling theoryEmpirical—QuantitativeIT and consumer behaviorElectronic commerceUSA
27Springer2022Piehlmaier, DMOverconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial adviceRobo-adviceTheory of cognitive dissonanceEmpirical—QuantitativeIT and consumer behaviorBanking and financial service industryUK
28Acad Economic Studies2018Cetina, I; Dumitrescu, L; Fuciu, M; Orzan, G; Stoicescu, CModelling the influences of online social networks on consumers’ buying behaviorPurchasing behaviorTheory of planned behaviorEmpirical—QuantitativeIT and consumer behaviorUnknownRomania
29MDPI2019Lee, HN; Lee, AS; Liang, YWAn Empirical Analysis of Brand as Symbol, Perceived Transaction Value, Perceived Acquisition Value and Customer Loyalty Using Structural Equation ModelingCustomer loyaltyNot specifiedEmpirical—QuantitativeIT and consumer behaviorRetailingTaiwan
30Sage Publications Inc2013Bartl, C; Gouthier, MHJ; Lenker, MDelighting Consumers Click by Click: Antecedents and Effects of Delight OnlineBehavioral intentionsTechnology acceptance model (TAM)Empirical—QuantitativeIT and consumer behaviorElectronic commerceGermany
31Scibulcom Ltd.2015Stoica, I; Popescu, M; Orzan, MConsumer Preferences for Organic Food. A Case Study of Neuromarketing Methods and ToolsConsumer preferencesNot specifiedEmpirical—QuantitativeIT and consumer behaviorFood industryRomania
32Soc Inform Manage-Mis Res Cent2017Gu, ZY; Tayi, GKConsumer Pseudo-Showrooming and Omni-Channel Placement StrategiesConsumers’ cross-channel search behavior Not specifiedEmpirical—QuantitativeIT and consumer behaviorRetailingUSA
33Elsevier Sci Ltd.2019Rahi, S; Abd Ghani, M; Ngah, AHIntegration of Unified Theory of Acceptance and Use of Technology in Internet Banking Adoption Setting: Evidence from PakistanUser intentionUnified theory of acceptance and use of technology (UTAUT)Empirical—QuantitativeIT and consumer behaviorBanking and financial service industryPakistan
34Routledge Journals, Taylor & Francis Ltd.2016Wang, T; Yeh, RKJ; Yen, DC; Nugroho, CAElectronic and in-person service quality of hybrid servicesService qualitySERVQUAL modelEmpirical—QuantitativeImpact of IT on consumer behaviorHospitality and tourism industryTaiwan
35Informs2015Herrmann, PN; Kundisch, DO; Rahman, MSBeating Irrationality: Does Delegating to IT Alleviate the Sunk Cost Effect?Behavioral investmentsNot specifiedEmpirical—QuantitativeImpact of IT on consumer behaviorUnknownGermany
36Taylor & Francis Inc2012Polites, GL; Williams, CK; Karahanna, E; Seligman, LA theoretical framework for consumer e-satisfaction and site stickiness: an evaluation in the context of online hotel reservationsE-satisfactionBagozzi’s self-regulation frameworkEmpirical—QuantitativeIT and consumer behaviorHospitality and tourism industryUSA
37Wiley2022Al-Nabhani, K; Wilson, A; McLean, GExamining consumers’ continuous usage of multichannel retailers’ mobile applicationsConsumer satisfactionECM-IT theoryEmpirical—QuantitativeIT and consumer behaviorRetailingUK
38Emerald Group Publishing Ltd.2021Stylos, N; Zwiegelaar, J; Buhalis, DBig data empowered agility for dynamic, volatile, and time-sensitive service industries: the case of tourism sectorBig data influenceNot specifiedEmpirical—QualitativeImpact of IT on consumer behaviorHospitality and tourism industryUK
39Springer Vieweg-Springer Fachmedien Wiesbaden Gmbh2022Fernandez-Cejas, M; Perez-Gonzalez, CJ; Roda-Garcia, JL; Colebrook, MCURIE: Towards an Ontology and Enterprise Architecture of a CRM Conceptual ModelCustomer relationship managementEA CRM modelEmpirical—QualitativeImpact of IT on consumer behaviorHospitality and tourism industrySpain
40Emerald Group Publishing Ltd.2015Keinanen, H; Kuivalainen, OAntecedents of social media B2B use in industrial marketing context: customers’ viewUser behavioral intent and Social media perceived usefulnessTechnology acceptance model (TAM)Empirical—QuantitativeIT and consumer behaviorUnknownFinland
Table 8. Citation Summary Table of 40 eligible articles based on Web of Science Analytics.
Table 8. Citation Summary Table of 40 eligible articles based on Web of Science Analytics.
S. No.TitleAuthorsSource TitlePublication YearAverage per YearTotal Citations
1What signal are you sending? How website quality influences perceptions of product quality and purchase intentionsWells, John D.; Valacich, Joseph S.; Hess, Traci J.MIS Quarterly201129.54384
2Factors affecting purchase intention on mobile shopping web sitesLu, Hsi-Peng; Su, Philip Yu-JenInternet Research200916.07241
3Relationship-based e-commerce: theory and evidence from ChinaMartinsons, Maris G.Information Systems Journal20087.88126
4Determinants of Chinese hotel customers’ e-satisfaction and purchase intentionsKim, Woo Gon; Ma, Xiaojing; Kim, Dong JinTourism Management20066.67120
5Antecedents of social media B2B use in industrial marketing context: customers’ viewKeinanen, Hanna; Kuivalainen, OlliJournal of Business & Industrial Marketing20158.4476
6Impact of Information Technology on Information Search Channel Selection for ConsumersKhatwani, Gaurav; Srivastava, Praveen RanjanJournal of Organizational and End User Computing20189.8359
7Consumer Pseudo-Showrooming and Omni-Channel Placement StrategiesGu, Zheyin (Jane); Tayi, Giri KumarMIS Quarterly2017856
8A Theoretical Framework for Consumer E-Satisfaction and Site Stickiness: An Evaluation in the Context of Online Hotel ReservationsPolites, Greta L.; Williams, Clay K.; Karahanna, Elena; Seligman, LarryJournal Of Organizational Computing and Electronic Commerce20124.3352
9Social Commerce as a Driver to Enhance Trust and Intention to Use Cryptocurrencies for Electronic PaymentsMendoza-Tello, Julio C.; Mora, Higinio; Pujol-Lopez, Francisco A.; Lytras, Miltiadis D.IEEE Access20187.8347
10Integration of unified theory of acceptance and use of technology in internet banking adoption setting: Evidence from PakistanRahi, Samar; Abd Ghani, Mazuri; Ngah, Abdul HafazTechnology in Society20199.246
11Delighting Consumers Click by Click: Antecedents and Effects of Delight OnlineBartl, Christopher; Gouthier, Matthias H. J.; Lenker, MarkusJournal of Service Research20134.1846
12Big data empowered agility for dynamic, volatile, and time-sensitive service industries: the case of tourism sectorStylos, Nikolaos; Zwiegelaar, Jeremy; Buhalis, DimitriosInternational Journal of Contemporary Hospitality Management20211442
13Gamification as a Mean of Driving Online Consumer Behaviour: SOR Model PerspectiveGatautis, Rimantas; Vitkauskaite, Elena; Gadeikiene, Agne; Piligrimiene, ZanetaInzinerine Ekonomika-Engineering Economics20164.7538
14Behaviour change in post-consumer recycling: Applying agent-based modelling in social experimentTong, Xin; Nikolic, Igor; Dijkhuizen, Bob; van den Hoven, Maurits; Minderhoud, Melle; Wackerlin, Niels; Wang, Tao; Tao, DongyanJournal of Cleaner Production20186.1737
15Developing online health communities through digital mediaHajli, M. NickInternational Journal of Information Management20143.737
16Consumer Informedness and Firm Information StrategyLi, Ting; Kauffman, Robert J.; van Heck, Eric; Vervest, Peter; Dellaert, Benedict G. C.Information Systems Research20143.535
17The role of (personal) network effects and switching costs in determining mobile users’ choicePablo Maicas, Juan; Polo, Yolanda; Javier Sese, FranciscoJournal of Information Technology20092.2734
18An exploration of consumers’ response to online service recovery initiativesOzuem, Wilson; Patel, Amisha; Howell, Kerry E.; Lancaster, GeoffInternational Journal of Market Research20173.2923
19Mining information users’ knowledge for one-to-one marketing on information applianceLiao, Shu-Hsien; Chen, Chyuan-Meei; Hsieh, Chia-Lin; Hsiao, Shih-ChungExpert Systems with Applications20091.218
20A hermeneutic phenomenological study of online community participation Applications of Fuzzy Cognitive MapsGalehbakhtiari, Sara; Pouryasouri, Tahmours HasangholiComputers in Human Behavior20151.3312
21Information technology customer aggression: The importance of an organizational climate of supportShih, Sheng-Pao; Lie, Ting; Klein, Gary; Jiang, James J.Information & Management20141.212
22Electronic and in-person service quality of hybrid servicesWang, Tien; Yeh, Ralph Keng-Jung; Yen, David C.; Nugroho, Christyanto AriService Industries Journal20161.139
23Beating Irrationality: Does Delegating to IT Alleviate the Sunk Cost Effect?Herrmann, Philipp N.; Kundisch, Dennis O.; Rahman, Mohammad S.Management Science201519
24Mining the change of customer behavior in dynamic marketsHuang, Cheng-Kui; Chang, Ting-Yi; Narayanan, Badri G.Information Technology & Management20150.898
25An enhanced model framework of personalized material flow servicesHou, Hanping; Hu, Mingyao; Chen, Li; Choi, Jung Y.Information Technology & Management20110.628
26Enhancing privacy of electricity consumption in smart cities through morphing of anticipated demand pattern utilizing self-elasticity and genetic algorithmsAlamaniotis, Miltiadis; Bourbakis, Nikolaos; Tsoukalas, Lefteri H.Sustainable Cities and Society20191.47
27An Optimization Model for Mapping Organization and Consumer Preferences for Internet Information ChannelsKhatwani, Gaurav; Srivastava, Praveen RanjanJournal of Global Information Management201717
28Consumer Preferences for Organic Food. A Case Study of Neuromarketing Methods and ToolsStoica, I.; Popescu, M.; Orzan, M.Journal of Environmental Protection and Ecology20150.676
29The changing consumer in SwedenWikstrom, SRInternational Journal of Research in Marketing19970.226
30Examining consumers’ continuous usage of multichannel retailers’ mobile applicationsAl-Nabhani, Khalid; Wilson, Alan; McLean, GraemePsychology & Marketing20221.675
31Overconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial advicePiehlmaier, Dominik M.Financial Innovation202224
32Modelling the Influences of Online Social Networks on Consumers’ Buying BehaviourCetina, Iuliana; Dumitrescu, Luigi; Fuciu, Mircea; Orzan, Gheorghe; Stoicescu, CristinaEconomic Computation and Economic Cybernetics Studies and Research20180.674
33An Empirical Analysis of Brand as Symbol, Perceived Transaction Value, Perceived Acquisition Value and Customer Loyalty Using Structural Equation ModelingLee, Huang Ning; Lee, An Sheng; Liang, Yo WenSustainability20190.63
34A tabulation of information technology and consumer behavior in hospitality revenue management researchDemirciftci, Tevfik; Chen, ChihChien; Erdem, MehmetJournal of Hospitality and Tourism Technology20200.52
35Are you a spontaneous traveler? Effect of sensation seeking on tourist planfulness in the mobile eraLi, Qiuyun; Xu, Hong; Hu, YubeiFrontiers in Psychology20220.51
36Traces of cultural and personal values on sustainable consumption: An analysis of a small local swap event in Izmir, TurkeyUckan Yuksel, Can; Kaya, CigdemJournal of Consumer Behaviour20210.251
37New dynamics of consumption and outputXuan, Chunji; Kim, Chang-Jin; Kim, Dong HeonJournal of Macroeconomics20190.21
38Construction of Precision Sales Model for Luxury Market Based on Machine LearningLi, Rong; Xu, Xiang; Dong, ShuaiMobile Information Systems202200
39The Impact of the Live Delivery of Goods on Consumers’ Purchasing Behaviour in Complex Situations Based on Artificial Intelligence TechnologyLi, XiaComputational Intelligence and Neuroscience202200
40CURIE: Towards an Ontology and Enterprise Architecture of a CRM Conceptual ModelFernandez-Cejas, Miguel; Perez-Gonzalez, Carlos J.; Roda-Garcia, Jose L.; Colebrook, MarcosBusiness & Information Systems Engineering202200
Sum40.551622
Table 9. Themes investigated in IT and Consumer Behavior studies.
Table 9. Themes investigated in IT and Consumer Behavior studies.
ThemeNo. of Identified Studies (%)Exemplary Studies
Technological Diffusion2 (5.00)[58]
Disruptive Consumer Behavior10 (25.00)[43,57,60,65,71]
IT and Consumer Behavior18 (45.00)[44,46,48,51,64,67,76,77,80]
Impact of IT on Consumer Behavior10 (25.00)[45,53,55,68,70,78]
Note: The reported frequencies are based on 40 selected articles from the final sample.
Table 10. Future Directions of the Study.
Table 10. Future Directions of the Study.
S. No. Future Research Questions (FRQs)
FRQ1How does IT impact consumer behavior?
FRQ2How can IT support a fundamental groundwork for organizations to recognize, assess, and build successful and viable integrated marketing communication strategies?
FRQ3What are the recent developments in IT vis-à-vis consumer behavior?
FRQ4What are the critical research contexts, theories, and methods for studying IT and consumer behavior?
FRQ5What are the critical factors in understanding consumer behavior against the IT backdrop?
FRQ6What essential role does IT play in shaping consumer behavior with the technological revolution and disrupting consumer habits?
FRQ7How can IT impact the behavioral intention of consumers?
FRQ8How can IT create hedonic motivation among consumers?
FRQ9How can IT impact the consumer’s behavior vis-à-vis procuring goods or services?
FRQ10In what way do customers make buying decisions with the technological revolution?
FRQ11How can businesses efficiently utilize IT channels to target and communicate with prospective markets?
FRQ12How does consumers’ omnichannel search behavior of pseudo-showrooming permit global retailers to attain healthier harmonization between their online and offline channels?
FRQ13How does artificial intelligence (AI) influence consumer behavior?
FRQ14How will AI benefit businesses and customers?
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Singh, P.; Khoshaim, L.; Nuwisser, B.; Alhassan, I. How Information Technology (IT) Is Shaping Consumer Behavior in the Digital Age: A Systematic Review and Future Research Directions. Sustainability 2024, 16, 1556. https://doi.org/10.3390/su16041556

AMA Style

Singh P, Khoshaim L, Nuwisser B, Alhassan I. How Information Technology (IT) Is Shaping Consumer Behavior in the Digital Age: A Systematic Review and Future Research Directions. Sustainability. 2024; 16(4):1556. https://doi.org/10.3390/su16041556

Chicago/Turabian Style

Singh, Prakash, Lama Khoshaim, Bader Nuwisser, and Ibrahim Alhassan. 2024. "How Information Technology (IT) Is Shaping Consumer Behavior in the Digital Age: A Systematic Review and Future Research Directions" Sustainability 16, no. 4: 1556. https://doi.org/10.3390/su16041556

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