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

Abstract

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. A list of journals selected based on indexing in the SSCI and SCIE in the Web of Science categories.

S. No.	List of Journals	No. of Article(s) Selected	SSCI/SCIE Indexing
1	Business & Information Systems Engineering	1	SSCI
2	Computational Intelligence and Neuroscience	1	SSCI
3	Computers in Human Behavior	1	SSCI
4	Economic Computation & Economic Cybernetics Studies & Research	1	SCIE
5	Engineering Economics	1	SSCI
6	Expert Systems with Applications	1	SSCI
7	Financial Innovation	1	SSCI
8	Frontiers in Psychology	1	SSCI
9	IEEE Access	1	SCIE
10	Information & Management	1	SCIE
11	Information Systems Journal	1	SSCI
12	Information Systems Research	1	SSCI
13	Information Technology and Management	2	SSCI
14	International Journal of Contemporary Hospitality Management	1	SSCI
15	International Journal of Information Management	1	SSCI
16	International Journal of Market Research	1	SSCI
17	International Journal of Research in Marketing	1	SSCI
18	Internet Research	1	SCIE
19	Journal of Business & Industrial Marketing	1	SSCI
20	Journal of Cleaner Production	1	SCIE
21	Journal of Consumer Behaviour	1	SSCI
22	Journal of Environmental Protection and Ecology	1	SSCI
23	Journal of Global Information Management	1	SSCI
24	Journal of Hospitality and Tourism Technology	1	SSCI
25	Journal of Information Technology	1	SCIE
26	Journal of Macroeconomics	1	SSCI
27	Journal of Organizational and End User Computing	1	SCIE
28	Journal of Organizational Computing and Electronic Commerce	1	SCIE
29	Journal of Service Research	1	SSCI
30	Management Science	1	SCIE
31	MIS Quarterly	2	SCIE
32	Mobile Information Systems	1	SSCI
33	Psychology & Marketing	1	SSCI
34	Sustainability	1	SCIE
35	Sustainable Cities and Society	1	SSCI
36	Technology in Society	1	SSCI
37	The Service Industries Journal	1	SSCI
38	Tourism Management	1	SSCI
Grand Total		40

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. Key Characteristics investigated in IT and Consumer Behavior studies.

Source	Key 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.

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. Geographical contexts investigated in IT and Consumer Behavior studies.

Country	No. of Identified Studies (%)	Exemplary Studies
China	8 (20.00)	[55,56,57,58,59,60]
Ecuador	1 (2.50)	[61]
Finland	1 (2.50)	[62]
Germany	2 (5.00)	[63,64]
India	2 (5.00)	[43]
Iran	1 (2.50)	[65]
Lithuania	1 (2.50)	[50]
Netherlands	1 (2.50)	[47]
Pakistan	1 (2.50)	[66]
Romania	2 (5.00)	[67]
Spain	2 (5.00)	[68]
Sweden	1 (2.50)	[44]
Taiwan	6 (15.00)	[69,70,71,72,73,74]
Turkey	1 (2.50)	[75]
UK	5 (12.50)	[76,77,78,79]
USA	5 (12.50)	[49,51,80]

Note: The reported frequencies are based on 40 selected articles from the final sample.

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. Industry contexts investigated in IT and Consumer Behavior studies.

Industry	No. of Identified Studies (%)	Exemplary Studies
Banking and Financial Service Industry	2 (5.00)	[76]
Electronic Commerce	10 (25.00)	[42,54,61,71,79]
Electronics Industry	1 (2.50)	[58]
Fashion Industry	1 (2.50)	[78]
Food Industry	1 (2.50)	[67]
Gaming Industry	1 (2.50)	[50]
Health Industry	1 (2.50)	[65]
Hospitality and Tourism Industry	8 (20.00)	[53,55,56,60]
IT Industry	1 (2.50)	[72]
Real-Estate	1 (2.50)	[49]
Retailing	7 (17.50)	[69,75,77]
Telecom Industry	1 (2.50)	[68]
Unknown	5 (12.50)	[52,63,73]

Note: The reported frequencies are based on 40 selected articles from the final sample.

furnishes a thorough overview of the industry-related information identified in this study.

Table 5. Notable key theories investigated in IT and consumer behavior studies.

Source	Theoretical 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

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. Methodologies investigated in IT and consumer behavior studies.

Methodology	No. of Studies Identified (%)	Exemplary Studies
Conceptual	3 (7.50)	[59]
Empirical—Qualitative	9 (22.50)	[44,45,49,58,78]
Empirical—Quantitative	23 (57.50)	[46,52,54,55,61,66,67,72,73,74,76]
Empirical—Mixed approach	5 (12.50)	[42,65,75]

Note: The reported frequencies are based on 40 selected articles from the final sample.

illustrates all information about the identified methodologies in this study.

Table 7. Summary Table in IT and Consumer Behavior studies.

S. No.	Publisher	Publication Year	Author(s)	Article Title	Key Factor(s)	Theoretical Lens	Methodology	Key Theme(s)	Domain Context	Geographical Context
1	Springer	2011	Hou, HP; Hu, MY; Chen, L; Choi, JY	An enhanced model framework of personalized material flow services	Customer preferences	Long tail theory	Empirical—Qualitative	IT and consumer behavior	Retailing	China
2	Elsevier Science Bv	1997	Wikstrom, SR	The changing consumer in Sweden	Consumer dynamism	Enabling strategy	Empirical—Qualitative	IT and consumer behavior	Retailing	Sweden
3	Elsevier Science Bv	2019	Xuan, CJ; Kim, CJ; Kim, DH	New dynamics of consumption and output	Dynamics of consumption	State-space model	Empirical—Quantitative	Technological diffusion	Retailing	China
4	Elsevier Sci Ltd.	2018	Tong, X; Nikolic, I; Dijkhuizen, B; van den Hoven, M; Minderhoud, M; Wackerlin, N; Wang, T; Tao, DY	Behaviour change in post-consumer recycling: Applying agent-based modelling in social experiment	Perceived behavioral control	Social experiment	Empirical—Qualitative	Disruptive consumer behavior	Electronics industry	China
5	Kaunas Univ Technol	2016	Gatautis, R; Vitkauskaite, E; Gadeikiene, A; Piligrimiene, Z	Gamification as a Mean of Driving Online Consumer Behaviour: SOR Model Perspective	Consumer engagement	Stimulus–organism–reaction (SOR) model	Conceptual	Disruptive consumer behavior	Gaming industry	Lithuania
6	Elsevier	2019	Alamaniotis, M; Bourbakis, N; Tsoukalas, LH	Enhancing privacy of electricity consumption in smart cities through morphing of anticipated demand pattern utilizing self-elasticity and genetic algorithms	Consumer privacy	Not specified	Empirical—Qualitative	IT and consumer behavior	Real-estate	USA
7	Springer	2015	Huang, CK; Chang, TY; Narayanan, BG	Mining the change of customer behavior in dynamic markets	Customer purchasing patterns	FuzzChgMining model	Empirical—Qualitative	Technological diffusion	Electronic commerce	Taiwan
8	Igi Global	2017	Khatwani, G; Srivastava, PR	An Optimization Model for Mapping Organization and Consumer Preferences for Internet Information Channels	Consumer preferences	Optimization model	Empirical—Mixed methods	IT and consumer behavior	Electronic commerce	India
9	Elsevier Sci Ltd.	2006	Kim, WG; Ma, XJ; Kim, DJ	Determinants of Chinese hotel customers’ e-satisfaction and purchase intentions	E-satisfaction and purchase intentions	Not specified	Empirical—Quantitative	Technological diffusion	Hospitality and tourism industry	China
10	Frontiers Media Sa	2022	Li, QY; Xu, H; Hu, YB	Are you a spontaneous traveler? Effect of sensation seeking on tourist planfulness in the mobile era	Sensation seeking	Optimum stimulation level theory	Empirical—Quantitative	Impact of IT on consumer behavior	Hospitality and tourism industry	China
11	Elsevier Sci Ltd.	2014	Hajli, MN	Developing online health communities through digital media	Perceived value	Social support theory	Empirical—Mixed methods	Technological diffusion	Health industry	Iran
12	Igi Global	2018	Khatwani, G; Srivastava, PR	Impact of Information Technology on Information Search Channel Selection for Consumers	Consumer preferences	Not specified	Empirical—Quantitative	Technological diffusion	Unknown	India
13	Sage Publications Ltd.	2017	Ozuem, W; Patel, A; Howell, KE; Lancaster, G	An exploration of consumers’ response to online service recovery initiatives	Consumer perceptions	Not specified	Empirical—Qualitative	Impact of IT on consumer behavior	Fashion industry	UK
14	Informs	2014	Li, T; Kauffman, RJ; van Heck, E; Vervest, P; Dellaert, BGC	Consumer Informedness and Firm Information Strategy	Consumer informedness	Theory of consumer informedness	Empirical—Mixed methods	Impact of IT on consumer behavior	Hospitality and tourism industry	Netherlands
15	Palgrave Macmillan Ltd.	2009	Maicas, JP; Polo, Y; Sese, FJ	The role of (personal) network effects and switching costs in determining mobile users’ choice	Consumer perceptions	Utility model	Empirical—Quantitative	Impact of IT on consumer behavior	Telecom industry	Spain
16	Pergamon-Elsevier Science Ltd.	2015	Galehbakhtiari, S; Pouryasouri, TH	A hermeneutic phenomenological study of online community participation Applications of Fuzzy Cognitive Maps	Online communities	Not specified	Empirical—Mixed methods	Technological diffusion	Electronic commerce	UK
17	Hindawi Ltd.	2022	Li, R; Xu, X; Dong, S	Construction of Precision Sales Model for Luxury Market Based on Machine Learning	Consumption behavior	Not specified	Empirical—Qualitative	Technological diffusion	Electronic commerce	China
18	Hindawi Ltd.	2022	Li, X	The Impact of the Live Delivery of Goods on Consumers’ Purchasing Behaviour in Complex Situations Based on Artificial Intelligence Technology	Online purchasing	Not specified	Empirical—Quantitative	Impact of IT on consumer behavior	Electronic commerce	China
19	Wiley	2008	Martinsons, MG	Relationship-based e-commerce: theory and evidence from China	Consumer behavior	Institutional theory	Conceptual	Technological diffusion	Electronic commerce	China
20	Emerald Group Publishing Ltd.	2009	Lu, HP; Su, PYJ	Factors affecting purchase intention on mobile shopping web sites	Customers’ perceptions	Theory of planned behavior	Empirical—Quantitative	IT and consumer behavior	Electronic commerce	Taiwan
21	Pergamon-Elsevier Science Ltd.	2009	Liao, SH; Chen, CM; Hsieh, CL; Hsiao, SC	Mining information users’ knowledge for one-to-one marketing on information appliance	Customer relationship	Not specified	Empirical—Quantitative	Impact of IT on consumer behavior	Unknown	Taiwan
22	Wiley	2021	Yuksel, CU; Kaya, C	Traces of cultural and personal values on sustainable consumption: An analysis of a small local swap event in Izmir, Turkey	Sustainable consumption	Not specified	Empirical—Mixed methods	Technological diffusion	Retailing	Turkey
23	IEEE-Inst Electrical Electronics Engineers Inc	2018	Mendoza-Tello, JC; Mora, H; Pujol-Lopez, FA; Lytras, MD	Social Commerce as a Driver to Enhance Trust and Intention to Use Cryptocurrencies for Electronic Payments	Trust and intention to use	Theory of social support	Empirical—Quantitative	Technological diffusion	Electronic commerce	Ecuador
24	Emerald Group Publishing Ltd.	2020	Demirciftci, T; Chen, CC; Erdem, M	A tabulation of information technology and consumer behavior in hospitality revenue management research	Consumer perspective	Not specified	Conceptual	IT and consumer behavior	Hospitality and tourism industry	USA
25	Elsevier Science Bv	2014	Shih, SP; Lie, T; Klein, G; Jiang, JJ	Information technology customer aggression: The importance of an organizational climate of support	Employee’s emotions	Not specified	Empirical—Quantitative	IT and consumer behavior	IT industry	Taiwan
26	Soc Inform Manage-Mis Res Cent	2011	Wells, JD; Valacich, JS; Hess, TJ	What signal are you sending? How website quality influences perceptions of product quality and purchase intentions	Consumer perceptions	Signaling theory	Empirical—Quantitative	IT and consumer behavior	Electronic commerce	USA
27	Springer	2022	Piehlmaier, DM	Overconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial advice	Robo-advice	Theory of cognitive dissonance	Empirical—Quantitative	IT and consumer behavior	Banking and financial service industry	UK
28	Acad Economic Studies	2018	Cetina, I; Dumitrescu, L; Fuciu, M; Orzan, G; Stoicescu, C	Modelling the influences of online social networks on consumers’ buying behavior	Purchasing behavior	Theory of planned behavior	Empirical—Quantitative	IT and consumer behavior	Unknown	Romania
29	MDPI	2019	Lee, HN; Lee, AS; Liang, YW	An Empirical Analysis of Brand as Symbol, Perceived Transaction Value, Perceived Acquisition Value and Customer Loyalty Using Structural Equation Modeling	Customer loyalty	Not specified	Empirical—Quantitative	IT and consumer behavior	Retailing	Taiwan
30	Sage Publications Inc	2013	Bartl, C; Gouthier, MHJ; Lenker, M	Delighting Consumers Click by Click: Antecedents and Effects of Delight Online	Behavioral intentions	Technology acceptance model (TAM)	Empirical—Quantitative	IT and consumer behavior	Electronic commerce	Germany
31	Scibulcom Ltd.	2015	Stoica, I; Popescu, M; Orzan, M	Consumer Preferences for Organic Food. A Case Study of Neuromarketing Methods and Tools	Consumer preferences	Not specified	Empirical—Quantitative	IT and consumer behavior	Food industry	Romania
32	Soc Inform Manage-Mis Res Cent	2017	Gu, ZY; Tayi, GK	Consumer Pseudo-Showrooming and Omni-Channel Placement Strategies	Consumers’ cross-channel search behavior	Not specified	Empirical—Quantitative	IT and consumer behavior	Retailing	USA
33	Elsevier Sci Ltd.	2019	Rahi, S; Abd Ghani, M; Ngah, AH	Integration of Unified Theory of Acceptance and Use of Technology in Internet Banking Adoption Setting: Evidence from Pakistan	User intention	Unified theory of acceptance and use of technology (UTAUT)	Empirical—Quantitative	IT and consumer behavior	Banking and financial service industry	Pakistan
34	Routledge Journals, Taylor & Francis Ltd.	2016	Wang, T; Yeh, RKJ; Yen, DC; Nugroho, CA	Electronic and in-person service quality of hybrid services	Service quality	SERVQUAL model	Empirical—Quantitative	Impact of IT on consumer behavior	Hospitality and tourism industry	Taiwan
35	Informs	2015	Herrmann, PN; Kundisch, DO; Rahman, MS	Beating Irrationality: Does Delegating to IT Alleviate the Sunk Cost Effect?	Behavioral investments	Not specified	Empirical—Quantitative	Impact of IT on consumer behavior	Unknown	Germany
36	Taylor & Francis Inc	2012	Polites, GL; Williams, CK; Karahanna, E; Seligman, L	A theoretical framework for consumer e-satisfaction and site stickiness: an evaluation in the context of online hotel reservations	E-satisfaction	Bagozzi’s self-regulation framework	Empirical—Quantitative	IT and consumer behavior	Hospitality and tourism industry	USA
37	Wiley	2022	Al-Nabhani, K; Wilson, A; McLean, G	Examining consumers’ continuous usage of multichannel retailers’ mobile applications	Consumer satisfaction	ECM-IT theory	Empirical—Quantitative	IT and consumer behavior	Retailing	UK
38	Emerald Group Publishing Ltd.	2021	Stylos, N; Zwiegelaar, J; Buhalis, D	Big data empowered agility for dynamic, volatile, and time-sensitive service industries: the case of tourism sector	Big data influence	Not specified	Empirical—Qualitative	Impact of IT on consumer behavior	Hospitality and tourism industry	UK
39	Springer Vieweg-Springer Fachmedien Wiesbaden Gmbh	2022	Fernandez-Cejas, M; Perez-Gonzalez, CJ; Roda-Garcia, JL; Colebrook, M	CURIE: Towards an Ontology and Enterprise Architecture of a CRM Conceptual Model	Customer relationship management	EA CRM model	Empirical—Qualitative	Impact of IT on consumer behavior	Hospitality and tourism industry	Spain
40	Emerald Group Publishing Ltd.	2015	Keinanen, H; Kuivalainen, O	Antecedents of social media B2B use in industrial marketing context: customers’ view	User behavioral intent and Social media perceived usefulness	Technology acceptance model (TAM)	Empirical—Quantitative	IT and consumer behavior	Unknown	Finland

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. Citation Summary Table of 40 eligible articles based on Web of Science Analytics.

S. No.	Title	Authors	Source Title	Publication Year	Average per Year	Total Citations
1	What signal are you sending? How website quality influences perceptions of product quality and purchase intentions	Wells, John D.; Valacich, Joseph S.; Hess, Traci J.	MIS Quarterly	2011	29.54	384
2	Factors affecting purchase intention on mobile shopping web sites	Lu, Hsi-Peng; Su, Philip Yu-Jen	Internet Research	2009	16.07	241
3	Relationship-based e-commerce: theory and evidence from China	Martinsons, Maris G.	Information Systems Journal	2008	7.88	126
4	Determinants of Chinese hotel customers’ e-satisfaction and purchase intentions	Kim, Woo Gon; Ma, Xiaojing; Kim, Dong Jin	Tourism Management	2006	6.67	120
5	Antecedents of social media B2B use in industrial marketing context: customers’ view	Keinanen, Hanna; Kuivalainen, Olli	Journal of Business & Industrial Marketing	2015	8.44	76
6	Impact of Information Technology on Information Search Channel Selection for Consumers	Khatwani, Gaurav; Srivastava, Praveen Ranjan	Journal of Organizational and End User Computing	2018	9.83	59
7	Consumer Pseudo-Showrooming and Omni-Channel Placement Strategies	Gu, Zheyin (Jane); Tayi, Giri Kumar	MIS Quarterly	2017	8	56
8	A Theoretical Framework for Consumer E-Satisfaction and Site Stickiness: An Evaluation in the Context of Online Hotel Reservations	Polites, Greta L.; Williams, Clay K.; Karahanna, Elena; Seligman, Larry	Journal Of Organizational Computing and Electronic Commerce	2012	4.33	52
9	Social Commerce as a Driver to Enhance Trust and Intention to Use Cryptocurrencies for Electronic Payments	Mendoza-Tello, Julio C.; Mora, Higinio; Pujol-Lopez, Francisco A.; Lytras, Miltiadis D.	IEEE Access	2018	7.83	47
10	Integration of unified theory of acceptance and use of technology in internet banking adoption setting: Evidence from Pakistan	Rahi, Samar; Abd Ghani, Mazuri; Ngah, Abdul Hafaz	Technology in Society	2019	9.2	46
11	Delighting Consumers Click by Click: Antecedents and Effects of Delight Online	Bartl, Christopher; Gouthier, Matthias H. J.; Lenker, Markus	Journal of Service Research	2013	4.18	46
12	Big data empowered agility for dynamic, volatile, and time-sensitive service industries: the case of tourism sector	Stylos, Nikolaos; Zwiegelaar, Jeremy; Buhalis, Dimitrios	International Journal of Contemporary Hospitality Management	2021	14	42
13	Gamification as a Mean of Driving Online Consumer Behaviour: SOR Model Perspective	Gatautis, Rimantas; Vitkauskaite, Elena; Gadeikiene, Agne; Piligrimiene, Zaneta	Inzinerine Ekonomika-Engineering Economics	2016	4.75	38
14	Behaviour change in post-consumer recycling: Applying agent-based modelling in social experiment	Tong, Xin; Nikolic, Igor; Dijkhuizen, Bob; van den Hoven, Maurits; Minderhoud, Melle; Wackerlin, Niels; Wang, Tao; Tao, Dongyan	Journal of Cleaner Production	2018	6.17	37
15	Developing online health communities through digital media	Hajli, M. Nick	International Journal of Information Management	2014	3.7	37
16	Consumer Informedness and Firm Information Strategy	Li, Ting; Kauffman, Robert J.; van Heck, Eric; Vervest, Peter; Dellaert, Benedict G. C.	Information Systems Research	2014	3.5	35
17	The role of (personal) network effects and switching costs in determining mobile users’ choice	Pablo Maicas, Juan; Polo, Yolanda; Javier Sese, Francisco	Journal of Information Technology	2009	2.27	34
18	An exploration of consumers’ response to online service recovery initiatives	Ozuem, Wilson; Patel, Amisha; Howell, Kerry E.; Lancaster, Geoff	International Journal of Market Research	2017	3.29	23
19	Mining information users’ knowledge for one-to-one marketing on information appliance	Liao, Shu-Hsien; Chen, Chyuan-Meei; Hsieh, Chia-Lin; Hsiao, Shih-Chung	Expert Systems with Applications	2009	1.2	18
20	A hermeneutic phenomenological study of online community participation Applications of Fuzzy Cognitive Maps	Galehbakhtiari, Sara; Pouryasouri, Tahmours Hasangholi	Computers in Human Behavior	2015	1.33	12
21	Information technology customer aggression: The importance of an organizational climate of support	Shih, Sheng-Pao; Lie, Ting; Klein, Gary; Jiang, James J.	Information & Management	2014	1.2	12
22	Electronic and in-person service quality of hybrid services	Wang, Tien; Yeh, Ralph Keng-Jung; Yen, David C.; Nugroho, Christyanto Ari	Service Industries Journal	2016	1.13	9
23	Beating Irrationality: Does Delegating to IT Alleviate the Sunk Cost Effect?	Herrmann, Philipp N.; Kundisch, Dennis O.; Rahman, Mohammad S.	Management Science	2015	1	9
24	Mining the change of customer behavior in dynamic markets	Huang, Cheng-Kui; Chang, Ting-Yi; Narayanan, Badri G.	Information Technology & Management	2015	0.89	8
25	An enhanced model framework of personalized material flow services	Hou, Hanping; Hu, Mingyao; Chen, Li; Choi, Jung Y.	Information Technology & Management	2011	0.62	8
26	Enhancing privacy of electricity consumption in smart cities through morphing of anticipated demand pattern utilizing self-elasticity and genetic algorithms	Alamaniotis, Miltiadis; Bourbakis, Nikolaos; Tsoukalas, Lefteri H.	Sustainable Cities and Society	2019	1.4	7
27	An Optimization Model for Mapping Organization and Consumer Preferences for Internet Information Channels	Khatwani, Gaurav; Srivastava, Praveen Ranjan	Journal of Global Information Management	2017	1	7
28	Consumer Preferences for Organic Food. A Case Study of Neuromarketing Methods and Tools	Stoica, I.; Popescu, M.; Orzan, M.	Journal of Environmental Protection and Ecology	2015	0.67	6
29	The changing consumer in Sweden	Wikstrom, SR	International Journal of Research in Marketing	1997	0.22	6
30	Examining consumers’ continuous usage of multichannel retailers’ mobile applications	Al-Nabhani, Khalid; Wilson, Alan; McLean, Graeme	Psychology & Marketing	2022	1.67	5
31	Overconfidence and the adoption of robo-advice: why overconfident investors drive the expansion of automated financial advice	Piehlmaier, Dominik M.	Financial Innovation	2022	2	4
32	Modelling the Influences of Online Social Networks on Consumers’ Buying Behaviour	Cetina, Iuliana; Dumitrescu, Luigi; Fuciu, Mircea; Orzan, Gheorghe; Stoicescu, Cristina	Economic Computation and Economic Cybernetics Studies and Research	2018	0.67	4
33	An Empirical Analysis of Brand as Symbol, Perceived Transaction Value, Perceived Acquisition Value and Customer Loyalty Using Structural Equation Modeling	Lee, Huang Ning; Lee, An Sheng; Liang, Yo Wen	Sustainability	2019	0.6	3
34	A tabulation of information technology and consumer behavior in hospitality revenue management research	Demirciftci, Tevfik; Chen, ChihChien; Erdem, Mehmet	Journal of Hospitality and Tourism Technology	2020	0.5	2
35	Are you a spontaneous traveler? Effect of sensation seeking on tourist planfulness in the mobile era	Li, Qiuyun; Xu, Hong; Hu, Yubei	Frontiers in Psychology	2022	0.5	1
36	Traces of cultural and personal values on sustainable consumption: An analysis of a small local swap event in Izmir, Turkey	Uckan Yuksel, Can; Kaya, Cigdem	Journal of Consumer Behaviour	2021	0.25	1
37	New dynamics of consumption and output	Xuan, Chunji; Kim, Chang-Jin; Kim, Dong Heon	Journal of Macroeconomics	2019	0.2	1
38	Construction of Precision Sales Model for Luxury Market Based on Machine Learning	Li, Rong; Xu, Xiang; Dong, Shuai	Mobile Information Systems	2022	0	0
39	The Impact of the Live Delivery of Goods on Consumers’ Purchasing Behaviour in Complex Situations Based on Artificial Intelligence Technology	Li, Xia	Computational Intelligence and Neuroscience	2022	0	0
40	CURIE: Towards an Ontology and Enterprise Architecture of a CRM Conceptual Model	Fernandez-Cejas, Miguel; Perez-Gonzalez, Carlos J.; Roda-Garcia, Jose L.; Colebrook, Marcos	Business & Information Systems Engineering	2022	0	0
Sum					40.55	1622

, 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. Themes investigated in IT and Consumer Behavior studies.

Theme	No. of Identified Studies (%)	Exemplary Studies
Technological Diffusion	2 (5.00)	[58]
Disruptive Consumer Behavior	10 (25.00)	[43,57,60,65,71]
IT and Consumer Behavior	18 (45.00)	[44,46,48,51,64,67,76,77,80]
Impact of IT on Consumer Behavior	10 (25.00)	[45,53,55,68,70,78]

Note: The reported frequencies are based on 40 selected articles from the final sample.

.

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. Future Directions of the Study.

S. No.	Future Research Questions (FRQs)
FRQ1	How does IT impact consumer behavior?
FRQ2	How can IT support a fundamental groundwork for organizations to recognize, assess, and build successful and viable integrated marketing communication strategies?
FRQ3	What are the recent developments in IT vis-à-vis consumer behavior?
FRQ4	What are the critical research contexts, theories, and methods for studying IT and consumer behavior?
FRQ5	What are the critical factors in understanding consumer behavior against the IT backdrop?
FRQ6	What essential role does IT play in shaping consumer behavior with the technological revolution and disrupting consumer habits?
FRQ7	How can IT impact the behavioral intention of consumers?
FRQ8	How can IT create hedonic motivation among consumers?
FRQ9	How can IT impact the consumer’s behavior vis-à-vis procuring goods or services?
FRQ10	In what way do customers make buying decisions with the technological revolution?
FRQ11	How can businesses efficiently utilize IT channels to target and communicate with prospective markets?
FRQ12	How does consumers’ omnichannel search behavior of pseudo-showrooming permit global retailers to attain healthier harmonization between their online and offline channels?
FRQ13	How does artificial intelligence (AI) influence consumer behavior?
FRQ14	How will AI benefit businesses and customers?

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].