Bibliometric Analysis of Publications on Impulsive Buying from 2000 to 2025 in the Scopus Database Using R and VOSviewer

Bibliometric Analysis of Publications on Impulsive Buying from 2000 to 2025 in the Scopus Database Using R and VOSviewer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Bibliometric Analysis of Publications on Impulsive Buying from 2000 to 2025 in the Scopus Database Using R and VOSviewer XuZheng Qiu, Ree Chan Ho, Sharif Hassan Md This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9195074/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract B uying trend has become one of the key topic of research in consumer behavior studies due to psychological events and online marketing phenomena. Although many researches have explored consumer decision-making, little research has analyzed the research trends of impulsive buying based on bibliometrics. The aim of this study was to explore the global publication trends and research hotspots of the impulsive buying from 2000 to 2025 based on the bibliometric analysis. The searched defined term was “impulsive buying”, which produced 464 hits across the articles, reviews, conference papers and book chapters in Scopus. With the help of Bibliometrix, Biblioshiny in R and VOSviewer, were used for data organization and visualization. The examination similarly demonstrated an increasing number of papers, especially post 2018, with China, India, and Malaysia acting as dominant knowledge producers. The most prolific authors were Luo X and Parsad C, and Journal of Retailing and Consumer Services was the leading source of publications. The main research themes were hedonic motivation, online shopping, social commerce, and self-control. The intellectual structure, theme progress and global cooperation of impulsive buying research were systematically summarized in this study. Such understanding could help scholars, practitioners, and policy makers address the trajectory of the research field and find further research opportunities. Business and commerce/Business and management Social science/Business and management Business and commerce/Information systems and information technology bibliometric analysis impulsive buying Scopus Biblioshiny application Bibliometrix package R VOSviewer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 1. Introduction During the last two and half decades, impulsive purchasing has gained great attention in marketing, consumer psychology, behavioral economics, and online commerce (Chandrasekhar et al., 2024 ; Gulfraz et al., 2022 ). When the retail environment in the world changes dramatically to become digital ones, learning about impulsive purchasing is essential for academics and practitioners in order to avoid that what causes their business. The proliferation of e-commerce websites, mobile shopping apps, digital ads, and social media influencers have radically transformed the conventional models of consumer decision making, giving new relevance to impulsive buying in the online market environment (Chandrasekhar et al., 2024 ; Rajib & Roy, 2023 ). Impulse purchase is buying something spontaneously, without advance intention to do so (Gonzalez, 2021 ). This behavior has been positively associated with a wide range of psychological, environmental and situational features, including time-pressures, mood states, product saliency, scarcity cues, and digital nudges. Virtual spaces offer many opportunities for such behavior because of their vibrant and interactive nature. Elements such as personalized recommendations, one-click payment facilities, and constant access have increased the chances that a person will engage in impulse buying (Barauskaitė, 2025 ; Chandrasekhar et al., 2024 ). This topic has attracted much academic interest and there is growing number of research papers on the antecedents, mechanisms, and consequences of this topic (Thomas & Gupta, 2022 ). Impulsive buying research keeps growing, it is critically important to systematically review the development of the related area (Kaur & Sharma, 2024 ). In spite of the growing body of conceptual and empirical work on impulsive purchase behavior in offline and online modes, few meta-analyses have been conducted to map the intellectual structure of this field of inquiry. Bibliometric analysis, as an effective methodological means, provides a quantitative and visual way to analyze the scientific evolution, cooperation network and hotspots in a specific domain during a period of time (Pessin et al., 2022 ). It enables the researchers to determine the publishing trends, productive authors and institutions, influential documents, and changes in research focus (Yan & Zhiping, 2023 ). Bibliometric software, and in particualr R-based softwares like Bibliometrix and software for visualization like VOSviewer, have led to the possibility of performing large-scale and reproducible analysis on large sets of bibliographic records (Dahish & Miah, 2022 ; Shi & Duan, 2024 ). These provide functionality that allows researchers to explore different citation-based indicators such as co-authorship networks, keyword co-occurrence and thematic clustering, allowing researchers to delve deep into the structural and dynamic properties of a research domain. These methods have been extensively used in various fields from medical sciences to environmental science fields, technology management and social science, but little bibliometric analyzes of impulsive buying can be seen (Dalal et al., 2023 ). This study has been designed, in order to bridge this gap through a bibliometric analysis of the documents on impulsive buying behavior published during the period 2000–2025 and indexed in Scopus. Scopus is the database selected because it covers the most influential journals and is conducive to bibliometric study (Singh et al., 2021 ). The analysis not only provides historical picture of the publication trends but also traces the evolution of research fronts, patterns of collaboration between authors and countries, and intellectual base leading the field. In light of this, the present research provides useful insights into the development of impulsive buying as a topic and the possible future research directions. The rapid growth of e-retailing (especially after 2010) has been a driving force in pushing academic research in understanding consumer impulsivity in the online context. The interdisciplinary character of research on impulsive buying subject, psychology, marketing, decision sciences and information systems- requires an exhaustive survey to comprehend the knowledge structure. The utilization of data-driven approaches like bibliometric analysis contributes to evidence-based decision-making in academic planning, journal growth, and funding distribution. With help of the bibliometric mapping approach, underexplored fields can be identified, research collaboration discouraged, and direction for doctoral or postdoctoral research be provided. A first analysis of the literature indicates that impulsive buying has been dealt with from the perspectives of emotional intelligence, self-control, web site design, social influence, and consumer personality. The COVID-19 crisis and lockdown measures have also led to renewed interest in online impulsivity given increased digital use and stress-related consumption (Pautrat et al., 2022 ). Despite this increasing interest, however, no study ever has amalgamated this divergent stream of research output into an overarching bibliometric review. Current reviews are often narrative or thematic and do not have the quantitative rigor nor visual analytics as provided by bibliometric approaches. This study utilized a stringent bibliometric approach leveraging R (Bibliometrix and Biblioshiny), and VOSviewer to decode the trends, patterns and networks implicit in impulsive buying research. It aims to answer the main following research questions: RQ1 : What are the annual publication trends in impulsive buying research from 2000 to 2025? RQ2 : Who are the most productive and influential authors, institutions, and countries in this field? RQ3 : What are the prominent themes, keywords, and conceptual structures emerging from the literature? RQ4 : How has the intellectual and social structure of impulsive buying research evolved over time? RQ5 : What research gaps and future directions can be derived from the bibliometric findings? The research implications of this study are theoretical and practical. In theory, it presents an integrated picture of the knowledge map and development topic of impulsive purchasing. It provides researchers, educators, and marketers with the means to consider new perspectives on impulsive buying and develop interdisciplinary models and consumer engagement strategies in digital media. This paper is arranged as follows: Section 2 describes the materials and methods, which consist of data collection and analytical methods. Section 3 provides the main results of the bibliometric analysis, and Section 4 addresses findings. A brief conclusion is given in Section 5 and Section 6 provides future research trend and directions according to existing gaps and emerging trends. 2. Materials and Methods Through bibliometric studies, researchers are offered a robust method of a quantitative nature with which to investigate and map the intellectual structure of a research domain. These are all systematic, reproducible data-driven analyses, as opposed to traditional literature reviews which tend to be qualitative and are influenced by interpretive bias. The present work uses bibliometric analysis to analyze the scholarly research of impulsive buying behavior between the year 2000–2025. The Scopus database extracted the data, the R-based package Bibliometrix and its web interface Biblioshiny was used for the analysis, and data visualization was made with VOSviewer. Bibliometrics is one of the methodological tools for the quantitative analyses of the tons of scientific literature (Singh et al., 2021 ). It uncovers patterns, authorship constellations, pivotal articles, thematic clusters, and intellectual bridges statistically. Descriptive analysis and content analysis were used for this study. Descriptive analysis was used to measure temporal patterns in publications, and content analysis of keyword occurrences and citation analysis revealed thematic tendencies in impulsive buying literature. 2.1 Database Source and Search Strategy Scopus was selected as the primary data source due to its extensive indexing of high-impact peer-reviewed literature across disciplines. The Scopus database also allows for the export of complete bibliographic metadata, which is necessary for conducting a robust bibliometric evaluation (Caputo & Kargina, 2022 ). The document search was conducted by applying the following query string: "Impulsive buying" This search was performed for indexing terms in the title, abstract, and author keyword fields to retrieve all potentially relevant publications. The search period was from January 2000 to April 2025. Only English language articles were included to ensure linguistic consistency and minimize ambiguities in content analysis from translation. The primary search yielded 464 Scopus records. The types of document consisted of journal article, conference paper, book chapter, and review. 2.2 Inclusion and Exclusion Criteria The study carefully selected the peer-reviewed journal articles, conference papers, book chapters, and review articles to maintain quality and relevancy of the dataset. Editorials, short notations, letters to the editors, and preprints were not considered. The title and abstract were manually screened for duplicate entries and for irrelevant records (e.g., DRM and “impulsive buying” in a non-consumer behavior context), and the records of irrelevant articles were deleted. 2.3 Data Preparation and Cleaning The bibliographic records were exported in .CSV, with metadata such as title, authors, abstract, keywords, source title, affiliations, country, document type, and citations. The dataset was then imported into RStudio and the R package Bibliometrix was utilized to preprocess and analyze the data. The study launched the web interfaces of the package, Biblioshiny, by executing the command biblioshiny() so that it becomes accessible to users who are not quite proficient in programming. Bibliometrix package provided the possibility to obtain publication trends, impact of sources, productivity of authors, collaboration networks at country level and keywords co-occurrence maps. It further allowed the application to Bradford's law to characterize the core journals and to the law of Lotka to assess the productivity of the authors (Agrawal, 2025 ). 2.4 Network Visualization with VOSviewer Biblioshiny, alongside VOSviewer, was used for network mapping and visualization of bibliometric data. VOSviewer allows the creation and visualisation of bibliometric networks construced from co-authorship, co-occurrence, citation, bibliographic coupling and co-citation data. The application makes it possible to interactively map the graph of terms, keywords and authors. The keyword co-occurrence network was built with VOSviewer’s text mining function, which accounts for VOSviewer internal algorithm to determine relatedness and clustering of keywords by reference to the co-appearance in the titles and abstracts. Citation and co-authorship networks were generated to identify key participants and collaborate institutions. For the mapping and the identification, the VOSviewer enables the use of clustering algorithm and customization in content viewing (enlarging, color & density), thus fostering an easy comprehension about thematic concentration and research gaps. 2.5 Data Analysis Objectives The bibliometric analysis focused on answering the following core objectives: Descriptive Analytics : Identify annual publication trends, top publishing journals, most cited documents, and most productive authors. Geographical Analysis : Determine the leading countries and institutions contributing to impulsive buying research. Authorship and Collaboration Patterns : Map co-authorship networks and institutional affiliations. Keyword and Thematic Evolution : Analyze keyword frequency and co-occurrence to detect emerging research themes and conceptual shifts. Citation Structures : Identify the most cited papers and sources to determine intellectual influence. The processed results were exported in graphical formats (e.g., .PNG, .CSV) and integrated into the study’s findings section to provide clear evidence supporting the bibliometric conclusions. 3. Results The bibliometrtc research based on 464 records obtained from the Scopus data base and coverage of the period from 2000 to 2025 was able to offer a robust understanding of the map in impulsive buying research field. The main bibliometric indicators computed from the Scopus database by using the Biblioshiny application of the Bibliometrix R package are shown in Table 1 . It gives a macro impression on the dataset with the number of documents, the types of documents, the collaboration among the authors, and the occurrence of keywords. Table 1 Main Information Description Results Key Information About Data Time Span 2000:2025 Sources (Journals, Books, etc.) 130 Documents 464 Average Number of Citations per Document 6.85 References 18,204 Types of Documents Article 375 Conference Paper 100 Book Chapter 28 Review 12 Content of Documents Plus Keywords (ID) 4,380 Keywords Used by Authors (DE) 2,145 Authors Single-Authored Document Authors 65 Multi-Authored Document Authors 738 Collaboration Among Authors Single-Authored Docs 48 Co-Authors per Document 3.72 International Co-authorships % 31.04% 3.1 Publication Growth and Citations Over Time The temporal spread of publication indicates that over the years, there has been a steady, moderate interest towards IB research from 2000 and onwards, but the spike in the last decade is quite noticeable. The “Average Citations per Year” line graph (Fig. 1 ) shows the trend in the number of citations over time. Early 2000s had better average cites per paper ranging from around 2003. But subsequently there was “a stark decline” before some spikes in 2017 and in early 2020 and early 2022, perhaps associated with boosted interest in digital consumer behavior as a result of COVID-19 lockdowns. There is a slow drop to 2024–2025, which may be attributed to the reference lag of younger publications. 3.2 Authors' Productivity The study provided a time-based view of top producers in this field in Fig. 2 “Authors’ Production Over Time”. Authors like Badgaiyan A.J., Prashar S., Parsad C., Luo X. are consistent with their publications for several years. The size of a blue bubble represents TC per year and productive history is indicated by line length. It is also noteworthy that Cheah J.H. shows up as a fairly substantial contributor in recent times (2023–2024) in terms of citation rates, and an average number of lower, but highly cited papers. These results are indicative of a mix of 'old' and innovative organizations shaping the trajectory of the field. 3.3 Co-authorship Networks "Authors Collaboration Network" (Fig. 3 ) shows co-authorship groups and highlights scholarly relationships in the impulsive buying literature. At the second step, nodes (e.g., those of Luo X, Prashar S, and Lim X.J) with a larger size have higher productivity and collaborative centrality. The strength of co-authors collaboration (ties) is depicted by the width of the connecting lines (edges). There were authors like Vijay T.S., Cheah J.H and etc., who could be seen as gatekeeping authors, connecting different author clusters and then disseminating information across institutional or geographic boundaries. This summary underscores the interdisciplinary, intercultural approach of impulsive buying research. 3.4 Institutional Collaboration Figure 4 “Affiliations Collaboration Network” present the collaboration network in the macro scale, where collaboration among different institution can be seen. Universiti Putra Malaysia, UCSI University, Shenzhen University and University of East Anglia appear as leading nodes. The close collaborations between Asian universities, especially Malaysian and Chinese ones, suggest that Southeast Asia has an increasing critical mass of research output. This visual density of connections also suggests the cross-continental relationships with institutions such as the University of Portsmouth and Sun Yat-Sen University, indicating impulsive buying research as a global interdisciplinary involving marketing, psychology, and information systems. 3.5 Most Relevant Authors and Affiliations The top contributors in the area of impulsive buying are plotted in Fig. 5 “Most Relevant Authors”. The following authors (Luo X, Parsad C, and Prashar S) appeared frequently with five articles, and Badgaiyan A.J., Cheah J-H, and Japutra A with the same frequency of 4 articles each. They are not only leading pioneers in the field but also key fountainheads whose research underpins much of what is known to date about impulsive buying. Their work is largely concentrated in digital consumption hedonic motivation and behavioral decision making, positioning them as major influencers in theoretical and applied research. Figure 6 , “Most Relevant Affiliations,” presents the institutional output according to their number of articles. Leading the way is Universiti Putra Malaysia with 17 articles published, testifying to its broaders standing in consumer behavior literature but more particularly in the context of South-East Asia. These are augmented by Universitas Indonesia (15), Kyung Hee University (14) and UCSI University (14). The high representation of Malaysian and Indonesian institutions indicates a regional focus for research which may be due to the fast pace of digitalisation and expansion of consumer markets in these economies. 3.6 Country Contributions and Global Collaboration Patterns In Fig. 7 , the research results of impulsive buying display a high level of international collaboration. China occupies the core position, the number of co-authorship links to which is largest, between Malaysia, Indonesia, USA and Pakistan. The thick web of lines suggests active bilateral and multilateral research collaboration, especially among Asian countries. Partnership provide indication of common emphasis on digital consumer behaviour, online marketplaces and marketing strategies for economic development. This is further exemplified in Fig. 8 (Country Production Over Time) where the longitudinal increase of country publication output can be observed. China, especially after 2015, as well as India, Indonesia, Malaysia, and the USA, expressed the steepest growth curve. The trending point for the number of publications in China shifted to 2012, and the growth could be attributed to funding and policy support in China in the field of digital commerce analytics. Meanwhile, nations such as Malaysia and Indonesia have been ramping up steadily as e-commerce and smartphone usage spreads through their populations. 3.7 Conceptual Structure and Emerging Research Themes A deep analysis of conceptual clusters was conducted using two keyword co-occurrence maps: author keywords and Keywords Plus. In the “Author Keywords Co–occurrence Network” of Fig. 9 , “impulsive buying” represents the central node, strongly connected to related issues such as “purchase intention”, “consumer psychology”, “hedonic motivation” and “online shopping”. Notable links also include “self-control”, “COVID-19”, “trust”, and “social commerce”. This relationship suggests the psychological foundations behind impulsive shopping and its environmental triggers, especially in digital environments. The large number of references to COVID-19 suggests the development of literature on the pandemic-related changes in consumer behavior, and particularly on the Internet. Corroborating with this, Fig. 10 “Keywords Plus Co-occurrence Network” indicates broader thematic associations in the field. There are several clear clusters for “consumption behavior”, “electronic commerce”, “marketing” and “consumer behavior”. The keywords represent interdisciplinary linkage to marketing, retail science, behavioral economics, and technology. “Empirical analysis”, “Adolescents”, “Shopping activity”, and “Decision-making” frequently appeared, indicating interest in demographic differences and implications of impulsive buying. Together of these networks illustrate a research field which is settling down into a mix of theoretical and experimental investigation of data. 3.8 Trend Topics and Term Frequency Understanding the intellectual history of research on impulse purchasing is an important step in identifying the intellectual trajectory in which key terms have been used over time. The “Trend Topics” (Fig. 11 ) depicts the appearance and lasting of the terms that frequently appear over time, as well as their appearance on timeline in the literature. The most featured or persistent ones, such as ‘impulse buying’, ‘consumer behaviour’, and ‘materialism’, have also remained frequently used over the years, particularly from 2015 onwards. New words, such as “social commerce”, “perceived usefulness”, “urge to buy impulsively”, “COVID-19”, and “influencer marketing” capture this more focused change toward digital behavioral influences and their connection to pandemics around 2020. More recent terms such as “generation Z” and “flow experience” emerge with an augmented focus on generation- and experience-related dimensions in impulsive buying. The size of each bubble on the timeline corresponds to the term frequency. The most cited keywords are "hedonic motivation", "e- commerce", "purchase intention" and "online shopping", demonstrating these words are placed at the core of the debate. This emerging terminology reflects the shift from studying consumption behavior in general to specialized psychological and technology-mediated concepts. 3.9 Conceptual Hotspots: Word Cloud Analysis To summarize keyword prominence, a word cloud (Fig. 12 ) was produced based on all author keywords in the dataset. The higher number is that the term has occurred in the corpus of literature. The top themes are “impulse buying”, “impulsive buying behaviour”, “consumer behaviour”, “compulsive buying” and “materialism”. These results signal that there is an emerging interest in the overlap between the categories of planned, unplanned and compulsive consumption. Finally, the dominance of “e-commerce”, “social media”, and “influencer marketing” suggests technological channels are the key issue in evaluating emerging forms of impulsivity. Variables such as “self-control”, “hedonic value”, “flow experience”, and “positive affect” add emphasis to the continued highlighting of emotional and psychological antecedents. As an aggregate, the word cloud is a thematic fingerprint of the field, showcasing age-old constructs, and fresh emerging themes. 3.10 Most Relevant Countries and International Contributions Figure 13 “Corresponding Author's Countries” displays top depositing countries with regard to article contribution. First by quantity, in China, then by India, Indonesia, USA, and Malaysia. Figure also differentiates between SCP (Single Country Publications) and MCP (Multiple Country Publications). Dominant in total production, China exhibits a nice balance between SCP and MCP, which is a sign of its strong involvement in international cooperative research. The USA and the UK, with fewer overall articles, have a high proportion of MCPs, which indicates a strong focus on international collaborations. In contrast, larger proportions of single-country studies are observed for nations like India and Malaysia, indicating the recent development of national-level research centers that have potential to be engaged more in international cooperation. This global spread is a testimony to the fact that impulsive buying is not just any longer a Western-dominated research field, but an area of global significance, particularly in the emerging digital markets of Asia. 3.11 Most Relevant Sources and Publishing Trends Figure 14 displays the source productivity profiling: “Most Relevant Sources”. The Journal of Retailing and Consumer Services is the most prominent outlet with 19 articles, alongside Sustainability (Switzerland) and Journal of Business Research with 8 articles, and Young Consumers- with 8 articles. Other significant publications are Asia Pacific Journal of Marketing and Logistics, Cogent Business and Management, and International Journal of Retail and Distribution Management. This distribution slices to the theme of impulsive purchasing across several fields of academia such as retail management, sustainability, consumer psychology, digital commerce. The substantial number of Sustainable references found point out an increasingly interconnectedness of in-pulse buying with the Sustainable or Ethical purchase a theme notably salient in the context of the post-pandemic, new-normal where consumer awareness is changing. Figure 15 , Sources’ Production Over Time, shows the publications that have appeared cumulatively at and above some of the highest-ranked journals. The trend map indicates that after 2018 there is clear increase of publications, and three journals (Journal of Retailing and Consumer Services, Sustainability and Journal of Business Research) have exponential rise curves after 2020. This trend is consistent with worldwide disturbances of consumption style and the explosive development of online consumerism in the context of COVID-19. 3.12 Country Collaboration Network (VOSviewer Analysis) The country-level collaboration network is displayed in Fig. 16 based on VOSviewer. Its network indicators reveal China, India, Malaysia, and the United Kingdom as key producers, with widely stretched international research collaboration. These nations serve as important hubs linked by various co-authored papers, demonstrating their collaborative efforts in developing knowledge on impulsive buying. China and India exhibit the most cooperation not only within Asia, but also with Europe as well, and their joint publications with Pakistan, Saudi Arabia, Malaysia and the United Kingdom can be observed frequently. In contrast, the U.S and South Korea exhibit partnerships not only with Vietnam but also Indonesia and Taiwan, demonstrating increasing scholarly exchanges between developed and emerging economies. The network clusters correspond to specific regional groupings of collaboration. One group zeroes in on relations between China, India, Pakistan and Saudi Arabia. A second cluster focuses on UK-German-Lithuanian collaboration, frequently via multidisciplinary European opportunities. There are some more clusters indicating the emerging academic collaboration activities between institutions in Southeast Asia (Indonesia, Vietnam and Taiwan). This map highlights this trend of internationalization in the impulsive buying research based on strong regional collaborations and growing cross-border networks. 3.13 Institutional Collaboration Network The partnership network among the institutions is shown in Fig. 17 , which illustrates the interconnection between the universities according to common scholarly output. Important stakeholders in this area include COMSATS University Islamabad, ITM University (India), Coventry University (UK), Chang Jung University (Taiwan) and Fore School of Management (India). Institutional clusters refer to the regional concentration of collaboration and thematic focus. One group comprises tourism and management-oriented institutions, among them the Fore School of Management and College of Hotel and Tourism Management. The other category consists of technology-focused collaborations, such as those between Taibah University and British institutions. A third cluster is based on the active interaction between South Asian business and hospitality schools, working together on areas involving consumer behavior in tourism, digital marketing, and retail management. These trends reflect the increasing cross-disciplinary and regional focus of impulsive buying research, especially in emerging disciplines (e.g., e-commerce, smart consumption, and consumer tourism). 3.14 Author Collaboration Network Figure 18 depicts the authorship collaboration network, showing lead authors and co-authorship relationships among academics. Main authors such as Ooi Keng-Boon, Cheah Jun-Hwa, Luo Xi, Lim Xin-Jean, and Dwivedi Yogesh K. are also well established in the intellectual pillar of some research clusters in Malaysia, China, and the United Kingdom. Ooi Keng-Boon and his Malaysian partners to thank for their studies on online impulse buying, e-commerce adoption and digital system behavior. A research cluster, led by Cheah Jun-Hwa, Luo Xi & Lim Xin-Jean, emphasizes on marketing communication tactics, hedonic motivation and customer psychology, depicting high cross-border collaborations between Chinese and Malaysian academicians. A group includes Garry Wei-Han Tan, Cham Tat-Huei and Aw Eugene Cheng-Xi who focus on social media influence, materialism and online trust. The form of this network embodies coherent communities of authors with common interests and frequent cooperation. These co-authorship bonds reveal the existence of specialized research groups that have made an important contribution to the development and academic impact of the discipline. 4. Discussion There are various findings and implications of this bibliometric and network analysis of im pulse buying literature over the last 25 years. There has been a particularly rapid increase in scientific output on this topic in the past decade, and a remarkable spike after 2018, paralleling in part the development of digitized economy, online social networking and influencer-based marketing. This growth highlights the changing relevance of impulse buying as a psychological construct as well as a marketing-driven concept in the area of consumer studies. There was a total of 464 documents identified in the present study indexed in the Scopus database and the most frequently encountered type of documents were journal articles. More than 80% of the papers were the result of cooperation between two or more researchers; thus a high level of research collaboration prevailed. The strong international and inter-institutional networks, plotted in the collaboration maps, further support the idea that impulsive buying is a universal research issue that crosses fields of psychology, technology, and marketing. Both the three-field Sankey diagram and the authorship visualizations also highlight the importance of specific key actors in the field. The study by Luo X, Parsad C and Prashar S is found to be the most productive, and their research has been greatly related to topics such as materialism, consumer behavior, and social commerce. These researchers largely come from universities in Malaysia, China and India, again underscoring the growing importance of Asia in consumer research. The production schedule demonstrates that these authors have really only gathered pace in the past few years, reflecting the dynamic and developing nature of the field. Keyword clustering identified five majors theme clusters. The first cluster mainly nodes around the central term “impulse buying” is a linked with hedonicc motivattion, online shopping and purchase intention, and is focusing on the emotional and affective drivers of impulsive purchasing behaviour. Another important group is self-regulation, social commerce and materialism, which indicates a continued curiosity on the effect of impulsiveness in relation to inner control and external digital factors. The keywords Generation Z, COVID-19, and influencer marketing in recent publications evidence a generational and contextual broadening of research views. The conceptual structure map constructed by keyword co-occurrence and thematic evolution gives it a knowledge frame that shows how the domain evolves at a certain time. Hedonic shopping value and consumer psychology are early themes and as additional research emerges it extends into trust in e-commerce, social media influence, and technology acceptance models. These findings correspond with current trends toward complexity and interdisciplinarity in contemporary consumer behavior research. Scientific mapping by VOSviewer showed international partnership was active. Nations such as China, India, Malaysia, and the UK were identified as key players in the global research network. China’s strong cooperation with Malaysia and Pakistan, domestically and internationally, further solidify its leading role in digital commerce research. The United States and South Korea also had major bilateral academic connections, which were explained by shared attention to technology platforms and behavioral analytics. Universiti Putra Malaysia, UCSI University, Shenzhen University, and Kyung Hee University were the most active institutions with significant contribution in both theoretical and practical research. Institutional collaboration dynamics, as depicted in the VOSviewer maps, show dense, polycentric collaboration networks, especially within schools of business, tourism, and information technology. The journal spectrum also mirrors the interdisciplinary nature of the subject. The Journal of Retailing and Consumer Services, Sustainability, and The Journal of Business Research were the most influential journals. A focus on the underlying topics reveals that Sustainability appears as a key source among the top sources, and backwards, this trend indicates an increased overlap between impulsive buying behaviour and the dichotomies between ethical consumerism and sustainable marketing or post-pandemic consumer resilience. This trajectory from materialism and hedonic value to the latest terms, such as influencer marketing, social media, and COVID-19, captures changing social, technological, and economic dynamics. This semantic shift also reflects that scholars are interested not only in what causes impulsive buying, but also in properties of environments and technologies that enable it. The results of this bibliometric study provide some important implications. The first reason is that the field is still growing and the high impact authors and institutes, are contributing heavily to the overall output. Secondly, there is clearly some thematic growth in terms of digital technology, triggers of emotion, and marketing approaches under research. Internationality also seems to be on the rise, but again there are still opportunities for more cross-border and cross-disciplinary collaboration. This paper offers a thorough view of the intellectual, geographical, and thematic orbits of research on impulsive buying in the last 25 years. It also lays the groundwork for future research directions, highlighting underexplored clusters, as well as key contributors and methodological trends. In contrast to the previous systematic reviews, this bibliometric review provides a more comprehensive, data-driven overview of the range and development trajectory and hot spots of the field. As the settings of consumer behaviour increasingly change with technology, further research should increasingly focus on hybrid models that combine behavourial psychology, algorithmic targeting and ethical reflections. 5. Conclusions This research provides a wide bibliometric analysis of impulsive buying behavior global output from 2000 to 2025 with records indexed in Scopus. Using the Biblioshiny tool of Bibliometrix package in R and VOSviewer, the key contributors, journals, organization, nations, keywords and latest research trends of the study were discovered. Through the analysis of 464 papers, the study found a clear trend of growing interest, with pronounced increase over the last decade. Journal of Retailing and Consumer Services, Sustainability (Switzerland), and Journal of Business Research were the three most prolific sources. The authors with the most impact were Luo X, Parsad C, and Prashar S, and institutions like Universiti Putra Malaysia and Universitas Indonesia were among the highest in number of publications. China was the top producing and collaborating nation followed by India, Indonesia, the USA and Malaysia, acknowledging the presence of Asia as the major player in this domain of research. In the keyword analysis, " impulse buying "and "impulsive buying behavior" were identified as the most frequently used terms. Among visualizations, themes still showed around hedonic motivation, purchase intention, e-commerce, and materialism, signifying a behavioral or technology-driven focus consisted in the clusters. In terms of networking within the field and the evolution of content, strong cross-national collaboration networks as well as growing interdisciplinarity and relevance for society is reflected. This bibliometric analysis provides a systematic framework of knowledge map for researchers, institutions and policymakers to comprehend the evolution and hot spots in impulsive buying researches. By compiling a quarter century of data, it also exposes new domains for investigation, and the increasing interpenetration of digital commerce and behavioural sciences within consumer research. 6. Future Directions Future studies may investigate sophisticated bibliometric and visualization tools such as machine learning based clustering and predictive map of topic trajectories. Methods like topic dominance modeling, semantic analysis, and temporal keyword evolution prediction have the potential to increase the understanding of research priority drift and subfield emergence. While the study only used the Scopus database in this study due to a comprehensive coverage of citation context, the upcoming study should also apply some comparative datasets from WoS, Dimensions, PUBMED, and GS to verify these findings across different platforms and increase the results robustness. The creation of interactive bibliometric dashboards or advanced visual analytics tools based on the use of AI may permit finer exploration of relationships between authors, cooperation between institutions and interdisciplinary overlap over time. Such utilities would help scholars to customize searches of the literature, identify gaps in citation, and predict influential areas. Future studies could deal with under-researched areas, such as cross-cultural comparisons about impulsivity, the neuroeconomic determinants of purchase decisions, or the influence of AI-based recommendation systems on impulse buying. With the changing landscape of digital platforms and shifting consumer habits, privacy ethics, algorithmic bias, and issues regarding sustainability will increasingly need to be included in the research framework. Future work can provide a more nuanced perspective on developing dynamics of impulsive buying when complemented with increased methodological sophistication and more extensive coverage of the datasets, and when it is integrated with new consumer technologies. Declarations Competing Interests The authors have no relevant financial or non-financial interests to disclose. Ethics Approval Not applicable. This study is based on bibliometric analysis of published literature and does not involve human participants, human data, or animals. Consent to Participate Not applicable. Consent to Publish Not applicable. Funding No funds, grants, or other support were received. Author Contribution Author ContributionsX.Z.Q.: Conceptualization, data collection, formal analysis, visualization, and original draft preparation.H.R.C.: Supervision and critical revision of the manuscript.M.S.H.: Supervision and review of the manuscript.All authors have read and approved the final manuscript. Data Availability The dataset supporting the findings of this study is provided as a supplementary file submitted with the manuscript for peer review. The shared material includes the raw bibliographic data exported from the Scopus database in CSV format, which contains the metadata used for the bibliometric analysis. This dataset is made available to ensure transparency and allow verification of the study’s findings. References Agrawal P (2025) Artificial Intelligence Research (2001–2022): A Bibliometric Journey through Trends and Patterns. J Data Sci Informetrics Cit Stud 4(1):65–77 Barauskaitė B (2025) The impact of scarcity, discounts, free shipping, personalized recommendations, social proof, emotional storytelling, and benefits of products and services on social media advertisements on impulsive purchasing Vilniaus universitetas.] Caputo A, Kargina M (2022) A user-friendly method to merge Scopus and Web of Science data during bibliometric analysis. J Mark Analytics 10(1):82–88 Chandrasekhar K, Das S, Gupta N, Jena SK (2024) Comparative analysis of impulse buying behaviour across retail channels: a study of physical stores, e-commerce websites and mobile shopping apps. Economic Affairs 69(2):1109–1120 Dahish Z, Miah SJ (2022) A bibliometric analysis to explore sentiment analysis in the domain of social media research Dalal G, Vyas P, Chugh P (2023) On-the-Spot Decision Making: A Bibliometric Investigation into Impulse Buying Research Progression, Network Structures and Emerging Trends. IPE J Manage 13(2):49–72 Gonzalez E (2021) Value Consciousness, Enjoyment of Mobile Coupons, and Impulse Buying Tendency. Effects on Mobile Coupon Redemption Intentions. Global J Manage Mark 5(1):1–31 Gulfraz MB, Sufyan M, Mustak M, Salminen J, Srivastava DK (2022) Understanding the impact of online customers’ shopping experience on online impulsive buying: A study on two leading E-commerce platforms. J Retailing Consumer Serv 68:103000 Kaur K, Sharma T (2024) Impulse buying in the digital age: An exploration using systematic literature review approach. J Consumer Behav 23(5):2553–2584 Pautrat M, Le Guen A, Barrault S, Ribadier A, Ballon N, Lebeau J-P, Brunault P (2022) Impulsivity as a risk factor for addictive disorder severity during the COVID-19 lockdown: results from a mixed quantitative and qualitative study. Int J Environ Res Public Health 20(1):705 Pessin VZ, Yamane LH, Siman RR (2022) Smart bibliometrics: an integrated method of science mapping and bibliometric analysis. Scientometrics 127(6):3695–3718 Rajib RI, Roy P (2023) Influence of social media on consumer buying behavior and decision making: insights from surveys and a case. study of Flash Digital Agency in Bangladesh Shi J, Duan Y (2024) Knowledge-map and research trends of circulating tumor cells in breast cancer: a scientometric analysis. Discover Oncol 15(1):506 Singh VK, Singh P, Karmakar M, Leta J, Mayr P (2021) The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis. Scientometrics 126:5113–5142 Thomas A, Gupta V (2022) Tacit knowledge in organizations: bibliometrics and a framework-based systematic review of antecedents, outcomes, theories, methods and future directions. J Knowl Manage 26(4):1014–1041 Yan L, Zhiping W (2023) Mapping the literature on academic publishing: A bibliometric analysis on WOS. SAGE Open 13(1):21582440231158562 Additional Declarations No competing interests reported. Supplementary Files scopus9DATAforBB.csv Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 16 Apr, 2026 Editor invited by journal 06 Apr, 2026 Editor assigned by journal 06 Apr, 2026 Submission checks completed at journal 05 Apr, 2026 First submitted to journal 05 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9195074","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":624465448,"identity":"11f17208-d8d4-4f5b-b430-fb6bdd5f8235","order_by":0,"name":"XuZheng 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09:45:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3689998,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9195074/v1/e7518f45-6ec6-48af-b07b-da576f4b8e03.pdf"},{"id":107708420,"identity":"cbf4a037-9054-4c88-8eb7-316c4743f3a1","added_by":"auto","created_at":"2026-04-24 09:27:00","extension":"csv","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":6150131,"visible":true,"origin":"","legend":"","description":"","filename":"scopus9DATAforBB.csv","url":"https://assets-eu.researchsquare.com/files/rs-9195074/v1/673be8627c757789ec597637.csv"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bibliometric Analysis of Publications on Impulsive Buying from 2000 to 2025 in the Scopus Database Using R and VOSviewer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDuring the last\u0026ensp;two and half decades, impulsive purchasing has gained great attention in marketing, consumer psychology, behavioral economics, and online commerce (Chandrasekhar et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Gulfraz et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). When the retail environment in the world\u0026ensp;changes dramatically to become digital ones, learning about impulsive purchasing is essential for academics and practitioners in order to avoid that what causes their business. The proliferation of e-commerce websites, mobile shopping apps, digital ads, and social media influencers have radically transformed the conventional models of consumer decision\u0026ensp;making, giving new relevance to impulsive buying in the online market environment (Chandrasekhar et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Rajib \u0026amp; Roy, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImpulse purchase is buying something spontaneously, without advance intention\u0026ensp;to do so (Gonzalez, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This behavior has been positively associated with a wide range of psychological, environmental and situational features, including time-pressures, mood\u0026ensp;states, product saliency, scarcity cues, and digital nudges. Virtual spaces offer many opportunities for\u0026ensp;such behavior because of their vibrant and interactive nature. Elements such as personalized recommendations, one-click payment facilities, and\u0026ensp;constant access have increased the chances that a person will engage in impulse buying (Barauskaitė, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Chandrasekhar et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This topic has attracted much academic interest and there is growing number of research papers on the antecedents, mechanisms, and\u0026ensp;consequences of this topic (Thomas \u0026amp; Gupta, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImpulsive buying research keeps growing, it is critically important to systematically review the development of the\u0026ensp;related area (Kaur \u0026amp; Sharma, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In spite of the growing body of conceptual and empirical work on impulsive purchase behavior in offline and online modes, few meta-analyses have been conducted to map the intellectual structure of this field\u0026ensp;of inquiry. Bibliometric analysis, as an\u0026ensp;effective methodological means, provides a quantitative and visual way to analyze the scientific evolution, cooperation network and hotspots in a specific domain during a period of time (Pessin et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It enables the researchers to determine the publishing trends, productive authors and institutions, influential documents,\u0026ensp;and changes in research focus (Yan \u0026amp; Zhiping, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBibliometric software, and in particualr R-based softwares like Bibliometrix and software for visualization like VOSviewer, have led to the possibility of performing large-scale and reproducible analysis on large sets of\u0026ensp;bibliographic records (Dahish \u0026amp; Miah, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Shi \u0026amp; Duan, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These provide functionality that allows researchers to explore different citation-based indicators\u0026ensp;such as co-authorship networks, keyword co-occurrence and thematic clustering, allowing researchers to delve deep into the structural and dynamic properties of a research domain. These methods have been extensively used in various fields from medical sciences to environmental science fields, technology management and social science, but little bibliometric analyzes of impulsive buying can\u0026ensp;be seen (Dalal et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study has been designed, in order to bridge this gap through a bibliometric analysis of the documents on impulsive buying behavior published during the period 2000\u0026ndash;2025\u0026ensp;and indexed in Scopus. Scopus is the database selected because it covers the\u0026ensp;most influential journals and is conducive to bibliometric study (Singh et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The analysis not only provides historical picture of the publication trends but also traces the evolution of research fronts, patterns\u0026ensp;of collaboration between authors and countries, and intellectual base leading the field. In light of this, the present research provides useful insights into the development of impulsive buying as a topic\u0026ensp;and the possible future research directions.\u003c/p\u003e \u003cp\u003eThe rapid growth of\u0026ensp;e-retailing (especially after 2010) has been a driving force in pushing academic research in understanding consumer impulsivity in the online context. The interdisciplinary character of research on impulsive buying subject, psychology, marketing, decision sciences and information systems- requires an exhaustive survey to\u0026ensp;comprehend the knowledge structure. The utilization of data-driven approaches like bibliometric analysis contributes to evidence-based decision-making in academic planning, journal growth, and funding distribution. With help of the bibliometric mapping approach, underexplored fields can be identified, research collaboration discouraged,\u0026ensp;and direction for doctoral or postdoctoral research be provided.\u003c/p\u003e \u003cp\u003eA\u0026ensp;first analysis of the literature indicates that impulsive buying has been dealt with from the perspectives of emotional intelligence, self-control, web site design, social influence, and consumer personality. The COVID-19 crisis and lockdown measures have also led to renewed interest in online impulsivity given increased\u0026ensp;digital use and stress-related consumption (Pautrat et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite this increasing interest, however, no study ever has amalgamated this divergent stream of research\u0026ensp;output into an overarching bibliometric review. Current reviews are often\u0026ensp;narrative or thematic and do not have the quantitative rigor nor visual analytics as provided by bibliometric approaches.\u003c/p\u003e \u003cp\u003eThis study utilized a stringent bibliometric approach leveraging R (Bibliometrix and Biblioshiny), and VOSviewer\u0026ensp;to decode the trends, patterns and networks implicit in impulsive buying research. It aims to answer the\u0026ensp;main following research questions:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRQ1\u003c/b\u003e: What are the annual publication trends in impulsive buying research from 2000 to 2025?\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRQ2\u003c/b\u003e: Who are the most productive and influential authors, institutions, and countries in this field?\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRQ3\u003c/b\u003e: What are the prominent themes, keywords, and conceptual structures emerging from the literature?\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRQ4\u003c/b\u003e: How has the intellectual and social structure of impulsive buying research evolved over time?\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRQ5\u003c/b\u003e: What research gaps and future directions can be derived from the bibliometric findings?\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe research implications of this study\u0026ensp;are theoretical and practical. In theory, it presents an integrated picture of the knowledge map\u0026ensp;and development topic of impulsive purchasing. It provides researchers, educators, and marketers with the means to consider new perspectives on impulsive buying and develop\u0026ensp;interdisciplinary models and consumer engagement strategies in digital media.\u003c/p\u003e \u003cp\u003eThis paper is arranged as follows: Section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e describes the materials and methods, which consist of data collection\u0026ensp;and analytical methods. Section \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides the main results of the bibliometric analysis, and Section \u003cspan refid=\"Sec23\" class=\"InternalRef\"\u003e4\u003c/span\u003e addresses findings. A brief conclusion is given in Section \u003cspan refid=\"Sec24\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Section\u0026ensp;\u003cspan refid=\"Sec25\" class=\"InternalRef\"\u003e6\u003c/span\u003e provides future research trend and directions according to existing gaps and emerging trends.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003eThrough bibliometric studies, researchers are offered a robust method of a\u0026ensp;quantitative nature with which to investigate and map the intellectual structure of a research domain. These are all systematic, reproducible data-driven analyses, as opposed to traditional literature reviews which tend to be qualitative and\u0026ensp;are influenced by interpretive bias. The present work uses bibliometric analysis\u0026ensp;to analyze the scholarly research of impulsive buying behavior between the year 2000\u0026ndash;2025. The Scopus database extracted the data, the R-based package Bibliometrix and its web interface Biblioshiny was used for the analysis, and data\u0026ensp;visualization was made with VOSviewer.\u003c/p\u003e \u003cp\u003eBibliometrics is one\u0026ensp;of the methodological tools for the quantitative analyses of the tons of scientific literature (Singh et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It uncovers patterns, authorship constellations, pivotal articles, thematic clusters,\u0026ensp;and intellectual bridges statistically. Descriptive analysis\u0026ensp;and content analysis were used for this study. Descriptive analysis was used to measure temporal patterns in publications, and content analysis\u0026ensp;of keyword occurrences and citation analysis revealed thematic tendencies in impulsive buying literature.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Database Source and Search Strategy\u003c/h2\u003e \u003cp\u003eScopus was selected as the primary data source due to its extensive indexing of high-impact peer-reviewed literature across disciplines. The Scopus database also allows for the export of complete bibliographic metadata, which is necessary for conducting a robust bibliometric evaluation (Caputo \u0026amp; Kargina, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The document search was conducted by applying the following query string:\u003c/p\u003e \u003cp\u003e\"Impulsive buying\"\u003c/p\u003e \u003cp\u003eThis search was performed\u0026ensp;for indexing terms in the title, abstract, and author keyword fields to retrieve all potentially relevant publications. The search period was\u0026ensp;from January 2000 to April 2025. Only English language articles\u0026ensp;were included to ensure linguistic consistency and minimize ambiguities in content analysis from translation.\u003c/p\u003e \u003cp\u003eThe primary search yielded 464\u0026ensp;Scopus records. The types of\u0026ensp;document consisted of journal article, conference paper, book chapter, and review.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Inclusion and Exclusion Criteria\u003c/h2\u003e \u003cp\u003eThe study carefully selected the peer-reviewed journal articles, conference papers, book chapters, and review articles to maintain quality and\u0026ensp;relevancy of the dataset. Editorials, short notations, letters to\u0026ensp;the editors, and preprints were not considered. The title and abstract were manually screened for duplicate entries and for irrelevant records (e.g., DRM and \u0026ldquo;impulsive buying\u0026rdquo;\u0026ensp;in a non-consumer behavior context), and the records of irrelevant articles were deleted.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Preparation and Cleaning\u003c/h2\u003e \u003cp\u003eThe bibliographic records were exported in\u0026ensp;.CSV, with\u0026ensp;metadata such as title, authors, abstract, keywords, source title, affiliations, country, document type, and citations. The dataset was then imported into RStudio and the R package Bibliometrix was utilized to preprocess\u0026ensp;and analyze the data. The study launched the web interfaces of the\u0026ensp;package, Biblioshiny, by executing the command biblioshiny() so that it becomes accessible to users who are not quite proficient in programming.\u003c/p\u003e \u003cp\u003eBibliometrix package provided the possibility to obtain publication trends, impact of sources, productivity of authors, collaboration networks\u0026ensp;at country level and keywords co-occurrence maps. It further allowed the application to\u0026ensp;Bradford's law to characterize the core journals and to the law of Lotka to assess the productivity of the authors (Agrawal, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Network Visualization with VOSviewer\u003c/h2\u003e \u003cp\u003eBiblioshiny, alongside VOSviewer, was used for network mapping and visualization\u0026ensp;of bibliometric data. VOSviewer allows the creation\u0026ensp;and visualisation of bibliometric networks construced from co-authorship, co-occurrence, citation, bibliographic coupling and co-citation data. The application makes it\u0026ensp;possible to interactively map the graph of terms, keywords and authors.\u003c/p\u003e \u003cp\u003eThe keyword co-occurrence network was built with VOSviewer\u0026rsquo;s text mining function, which accounts for VOSviewer internal algorithm to determine relatedness and clustering of keywords by reference\u0026ensp;to the co-appearance in the titles and abstracts. Citation and co-authorship networks were generated to identify\u0026ensp;key participants and collaborate institutions. For the mapping and the identification, the VOSviewer enables\u0026ensp;the use of clustering algorithm and customization in content viewing (enlarging, color \u0026amp; density), thus fostering an easy comprehension about thematic concentration and research gaps.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data Analysis Objectives\u003c/h2\u003e \u003cp\u003eThe bibliometric analysis focused on answering the following core objectives:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eDescriptive Analytics\u003c/b\u003e: Identify annual publication trends, top publishing journals, most cited documents, and most productive authors.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eGeographical Analysis\u003c/b\u003e: Determine the leading countries and institutions contributing to impulsive buying research.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eAuthorship and Collaboration Patterns\u003c/b\u003e: Map co-authorship networks and institutional affiliations.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eKeyword and Thematic Evolution\u003c/b\u003e: Analyze keyword frequency and co-occurrence to detect emerging research themes and conceptual shifts.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eCitation Structures\u003c/b\u003e: Identify the most cited papers and sources to determine intellectual influence.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe processed results were exported in graphical formats (e.g., .PNG, .CSV) and integrated into the study\u0026rsquo;s findings section to provide clear evidence supporting the bibliometric conclusions.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe bibliometrtc research based on 464 records obtained from the Scopus data base and coverage of the period from 2000 to 2025 was able to\u0026ensp;offer a robust understanding of the map in impulsive buying research field. The main bibliometric indicators computed\u0026ensp;from the Scopus database by using the Biblioshiny application of the Bibliometrix R package are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. It gives a macro impression on the dataset with the number of documents, the types of documents,\u0026ensp;the collaboration among the authors, and the occurrence of keywords.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMain Information\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKey Information About Data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime Span\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2000:2025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSources (Journals, Books, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDocuments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Number of Citations per Document\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTypes of Documents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArticle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConference Paper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBook Chapter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReview\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContent of Documents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlus Keywords (ID)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,380\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKeywords Used by Authors (DE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,145\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle-Authored Document Authors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMulti-Authored Document Authors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e738\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollaboration Among Authors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle-Authored Docs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-Authors per Document\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternational Co-authorships %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.04%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Publication Growth and Citations Over Time\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe temporal spread of publication indicates that over the years,\u0026ensp;there has been a steady, moderate interest towards IB research from 2000 and onwards, but the spike in the last decade is quite noticeable. The \u0026ldquo;Average Citations per Year\u0026rdquo; line graph (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) shows\u0026ensp;the trend in the number of citations over time. Early 2000s had better average cites per paper ranging\u0026ensp;from around 2003. But subsequently there was \u0026ldquo;a stark\u0026ensp;decline\u0026rdquo; before some spikes in 2017 and in early 2020 and early 2022, perhaps associated with boosted interest in digital consumer behavior as a result of COVID-19 lockdowns. There is a\u0026ensp;slow drop to 2024\u0026ndash;2025, which may be attributed to the reference lag of younger publications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Authors' Productivity\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe study provided a time-based view of top producers in this field in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u0026ldquo;Authors\u0026rsquo; Production Over Time\u0026rdquo;. Authors like Badgaiyan A.J.,\u0026ensp;Prashar S., Parsad C., Luo X. are consistent with their publications for several years. The size of a blue bubble represents TC per year and productive\u0026ensp;history is indicated by line length. It is also noteworthy that Cheah J.H. shows up\u0026ensp;as a fairly substantial contributor in recent times (2023\u0026ndash;2024) in terms of citation rates, and an average number of lower, but highly cited papers. These results are indicative of a mix of 'old' and innovative organizations shaping the trajectory of\u0026ensp;the field.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Co-authorship Networks\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\"Authors Collaboration Network\" (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) shows co-authorship groups and highlights\u0026ensp;scholarly relationships in the impulsive buying literature. At the second step, nodes (e.g., those of Luo X, Prashar S, and Lim X.J) with a larger size\u0026ensp;have higher productivity and collaborative centrality. The strength of\u0026ensp;co-authors collaboration (ties) is depicted by the width of the connecting lines (edges). There were authors like Vijay T.S., Cheah J.H and etc., who could be seen as gatekeeping authors, connecting different author clusters and then\u0026ensp;disseminating information across institutional or geographic boundaries. This summary underscores the interdisciplinary, intercultural\u0026ensp;approach of impulsive buying research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Institutional Collaboration\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026ensp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u0026ldquo;Affiliations Collaboration Network\u0026rdquo; present the collaboration network in the macro scale, where collaboration among different institution can be seen. Universiti Putra Malaysia, UCSI University, Shenzhen University and University of East Anglia appear\u0026ensp;as leading nodes. The close collaborations between Asian universities, especially Malaysian and Chinese ones, suggest that Southeast Asia\u0026ensp;has an increasing critical mass of research output. This visual density of connections also suggests the cross-continental relationships with institutions such as the University of Portsmouth and Sun Yat-Sen University, indicating impulsive buying research as a global interdisciplinary involving marketing, psychology, and information\u0026ensp;systems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Most Relevant Authors and Affiliations\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe top contributors in the area of impulsive buying\u0026ensp;are plotted in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u0026ldquo;Most Relevant Authors\u0026rdquo;. The following authors (Luo X, Parsad C, and Prashar S) appeared frequently with five articles, and Badgaiyan A.J., Cheah J-H, and Japutra A with the same frequency of\u0026ensp;4 articles each. They\u0026ensp;are not only leading pioneers in the field but also key fountainheads whose research underpins much of what is known to date about impulsive buying. Their work is largely concentrated in digital consumption hedonic motivation and behavioral\u0026ensp;decision making, positioning them as major influencers in theoretical and applied research.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, \u0026ldquo;Most Relevant Affiliations,\u0026rdquo; presents the institutional output according to their number of articles. Leading the way is Universiti Putra Malaysia with 17 articles published, testifying\u0026ensp;to its broaders standing in consumer behavior literature but more particularly in the context of South-East Asia. These are augmented by Universitas\u0026ensp;Indonesia (15), Kyung Hee University (14) and UCSI University (14). The high representation\u0026ensp;of Malaysian and Indonesian institutions indicates a regional focus for research which may be due to the fast pace of digitalisation and expansion of consumer markets in these economies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Country Contributions and Global Collaboration Patterns\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the research results of impulsive buying display a high level of international collaboration. China occupies the core position, the number of co-authorship links to which is largest,\u0026ensp;between Malaysia, Indonesia, USA and Pakistan. The thick web of lines suggests active bilateral and multilateral\u0026ensp;research collaboration, especially among Asian countries. Partnership provide indication of common emphasis on digital consumer behaviour, online marketplaces and marketing strategies for\u0026ensp;economic development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis is further exemplified in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e (Country Production Over Time) where the longitudinal increase of country publication output\u0026ensp;can be observed. China,\u0026ensp;especially after 2015, as well as India, Indonesia, Malaysia, and the USA, expressed the steepest growth curve. The trending point for the number of publications in China shifted to 2012, and the growth could be attributed to funding and policy\u0026ensp;support in China in the field of digital commerce analytics. Meanwhile, nations such as Malaysia and Indonesia have been\u0026ensp;ramping up steadily as e-commerce and smartphone usage spreads through their populations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Conceptual Structure and Emerging Research Themes\u003c/h2\u003e \u003cp\u003eA deep analysis of conceptual clusters was conducted using two keyword co-occurrence maps: author keywords and Keywords Plus.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn\u0026ensp;the \u0026ldquo;Author Keywords Co\u0026ndash;occurrence Network\u0026rdquo; of Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, \u0026ldquo;impulsive buying\u0026rdquo; represents the central node, strongly connected to related issues such as \u0026ldquo;purchase intention\u0026rdquo;, \u0026ldquo;consumer psychology\u0026rdquo;, \u0026ldquo;hedonic motivation\u0026rdquo; and \u0026ldquo;online shopping\u0026rdquo;. Notable links also\u0026ensp;include \u0026ldquo;self-control\u0026rdquo;, \u0026ldquo;COVID-19\u0026rdquo;, \u0026ldquo;trust\u0026rdquo;, and \u0026ldquo;social commerce\u0026rdquo;. This relationship suggests the psychological foundations behind impulsive shopping and\u0026ensp;its environmental triggers, especially in digital environments. The large number of references to COVID-19\u0026ensp;suggests the development of literature on the pandemic-related changes in consumer behavior, and particularly on the Internet.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCorroborating with\u0026ensp;this, Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e \u0026ldquo;Keywords Plus Co-occurrence Network\u0026rdquo; indicates broader thematic associations in the field. There are several clear clusters for \u0026ldquo;consumption behavior\u0026rdquo;, \u0026ldquo;electronic commerce\u0026rdquo;, \u0026ldquo;marketing\u0026rdquo;\u0026ensp;and \u0026ldquo;consumer behavior\u0026rdquo;. The keywords\u0026ensp;represent interdisciplinary linkage to marketing, retail science, behavioral economics, and technology. \u0026ldquo;Empirical analysis\u0026rdquo;,\u0026ensp;\u0026ldquo;Adolescents\u0026rdquo;, \u0026ldquo;Shopping activity\u0026rdquo;, and \u0026ldquo;Decision-making\u0026rdquo; frequently appeared, indicating interest in demographic differences and implications of impulsive buying. Together of these networks illustrate a research field which is settling down into a mix of theoretical\u0026ensp;and experimental investigation of data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.8 Trend Topics and Term Frequency\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUnderstanding the intellectual history of research on impulse purchasing is an important step in identifying the\u0026ensp;intellectual trajectory in which key terms have been used over time. The \u0026ldquo;Trend Topics\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e) depicts the\u0026ensp;appearance and lasting of the terms that frequently appear over time, as well as their appearance on timeline in the literature.\u003c/p\u003e \u003cp\u003eThe most featured or persistent ones, such as \u0026lsquo;impulse buying\u0026rsquo;, \u0026lsquo;consumer behaviour\u0026rsquo;, and \u0026lsquo;materialism\u0026rsquo;, have also remained frequently used over\u0026ensp;the years, particularly from 2015 onwards. New words, such as\u0026ensp;\u0026ldquo;social commerce\u0026rdquo;, \u0026ldquo;perceived usefulness\u0026rdquo;, \u0026ldquo;urge to buy impulsively\u0026rdquo;, \u0026ldquo;COVID-19\u0026rdquo;, and \u0026ldquo;influencer marketing\u0026rdquo; capture this more focused change toward digital behavioral influences and their connection to pandemics around 2020. More recent terms such as \u0026ldquo;generation Z\u0026rdquo; and \u0026ldquo;flow experience\u0026rdquo; emerge with an augmented focus on generation- and\u0026ensp;experience-related dimensions in impulsive buying.\u003c/p\u003e \u003cp\u003eThe size of each\u0026ensp;bubble on the timeline corresponds to the term frequency. The most cited keywords are \"hedonic\u0026ensp;motivation\", \"e- commerce\", \"purchase intention\" and \"online shopping\", demonstrating these words are placed at the core of the debate. This emerging terminology reflects the\u0026ensp;shift from studying consumption behavior in general to specialized psychological and technology-mediated concepts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.9 Conceptual Hotspots: Word Cloud Analysis\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo summarize keyword prominence, a word cloud (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e) was produced based on all author keywords in the dataset. The higher number\u0026ensp;is that the term has occurred in the corpus of literature. The top themes are\u0026ensp;\u0026ldquo;impulse buying\u0026rdquo;, \u0026ldquo;impulsive buying behaviour\u0026rdquo;, \u0026ldquo;consumer behaviour\u0026rdquo;, \u0026ldquo;compulsive buying\u0026rdquo; and \u0026ldquo;materialism\u0026rdquo;. These\u0026ensp;results signal that there is an emerging interest in the overlap between the categories of planned, unplanned and compulsive consumption. Finally, the dominance of \u0026ldquo;e-commerce\u0026rdquo;, \u0026ldquo;social media\u0026rdquo;, and \u0026ldquo;influencer marketing\u0026rdquo; suggests technological channels are the key issue in evaluating emerging\u0026ensp;forms of impulsivity.\u003c/p\u003e \u003cp\u003eVariables such as \u0026ldquo;self-control\u0026rdquo;, \u0026ldquo;hedonic value\u0026rdquo;, \u0026ldquo;flow experience\u0026rdquo;, and \u0026ldquo;positive affect\u0026rdquo;\u0026ensp;add emphasis to the continued highlighting of emotional and psychological antecedents. As an aggregate, the word cloud is a thematic fingerprint of the field, showcasing age-old constructs, and fresh\u0026ensp;emerging themes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.10 Most Relevant Countries and International Contributions\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e \u0026ldquo;Corresponding Author's Countries\u0026rdquo; displays top depositing countries\u0026ensp;with regard to article contribution. First by\u0026ensp;quantity, in China, then by India, Indonesia, USA, and Malaysia. Figure also differentiates\u0026ensp;between SCP (Single Country Publications) and MCP (Multiple Country Publications). Dominant in total production, China exhibits a nice balance between SCP and MCP, which is a sign of its strong involvement in international\u0026ensp;cooperative research.\u003c/p\u003e \u003cp\u003eThe USA and the UK, with fewer overall articles, have a high proportion of MCPs, which\u0026ensp;indicates a strong focus on international collaborations. In contrast, larger proportions of single-country\u0026ensp;studies are observed for nations like India and Malaysia, indicating the recent development of national-level research centers that have potential to be engaged more in international cooperation. This global spread is a testimony to the fact that impulsive buying is not\u0026ensp;just any longer a Western-dominated research field, but an area of global significance, particularly in the emerging digital markets of Asia.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.11 Most Relevant Sources and Publishing Trends\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e displays the source\u0026ensp;productivity profiling: \u0026ldquo;Most Relevant Sources\u0026rdquo;. The Journal of Retailing and Consumer Services is the most prominent outlet with 19 articles, alongside Sustainability (Switzerland) and Journal of Business Research with 8\u0026ensp;articles, and Young Consumers- with 8 articles. Other significant publications\u0026ensp;are Asia Pacific Journal of Marketing and Logistics, Cogent Business and Management, and International Journal of Retail and Distribution Management.\u003c/p\u003e \u003cp\u003eThis distribution slices to the theme of impulsive purchasing across several fields of\u0026ensp;academia such as retail management, sustainability, consumer psychology, digital commerce. The substantial number of Sustainable references found point out an increasingly interconnectedness of in-pulse buying with the Sustainable or Ethical purchase\u0026ensp;a theme notably salient in the context of the post-pandemic, new-normal where consumer awareness is changing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003e, Sources\u0026rsquo; Production Over Time, shows the publications that have appeared\u0026ensp;cumulatively at and above some of the highest-ranked journals. The trend map indicates that after 2018 there is clear increase of publications, and three journals (Journal\u0026ensp;of Retailing and Consumer Services, Sustainability and Journal of Business Research) have exponential rise curves after 2020. This trend is consistent with worldwide disturbances of consumption style and the explosive development\u0026ensp;of online consumerism in the context of COVID-19.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.12 Country Collaboration Network (VOSviewer Analysis)\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe country-level\u0026ensp;collaboration network is displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e based on VOSviewer. Its network indicators reveal China, India, Malaysia, and the United Kingdom as key producers, with widely stretched\u0026ensp;international research collaboration. These nations serve as important hubs linked by various co-authored papers, demonstrating their collaborative efforts\u0026ensp;in developing knowledge on impulsive buying.\u003c/p\u003e \u003cp\u003eChina and India exhibit the most cooperation not only within Asia, but also with Europe as well, and their joint publications with Pakistan, Saudi Arabia, Malaysia and the United\u0026ensp;Kingdom can be observed frequently. In contrast, the U.S and South Korea exhibit partnerships not only with Vietnam but also Indonesia and Taiwan, demonstrating increasing scholarly exchanges between developed and emerging\u0026ensp;economies.\u003c/p\u003e \u003cp\u003eThe network\u0026ensp;clusters correspond to specific regional groupings of collaboration. One group zeroes in on relations between China,\u0026ensp;India, Pakistan and Saudi Arabia. A second cluster focuses on UK-German-Lithuanian\u0026ensp;collaboration, frequently via multidisciplinary European opportunities. There are some more clusters indicating\u0026ensp;the emerging academic collaboration activities between institutions in Southeast Asia (Indonesia, Vietnam and Taiwan). This map highlights this trend of internationalization in the\u0026ensp;impulsive buying research based on strong regional collaborations and growing cross-border networks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.13 Institutional Collaboration Network\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe partnership network among the institutions is shown\u0026ensp;in Fig.\u0026nbsp;\u003cspan refid=\"Fig17\" class=\"InternalRef\"\u003e17\u003c/span\u003e, which illustrates the interconnection between the universities according to common scholarly output. Important stakeholders in this area include COMSATS University Islamabad, ITM University (India), Coventry University (UK),\u0026ensp;Chang Jung University (Taiwan) and Fore School of Management (India).\u003c/p\u003e \u003cp\u003eInstitutional clusters refer to the regional concentration of collaboration and thematic\u0026ensp;focus. One group comprises tourism and management-oriented institutions, among them the Fore School of Management and College\u0026ensp;of Hotel and Tourism Management. The other\u0026ensp;category consists of technology-focused collaborations, such as those between Taibah University and British institutions. A third cluster is based on the active interaction between South Asian business and hospitality\u0026ensp;schools, working together on areas involving consumer behavior in tourism, digital marketing, and retail management. These trends reflect the increasing cross-disciplinary and regional focus of impulsive buying research, especially in emerging disciplines (e.g., e-commerce, smart\u0026ensp;consumption, and consumer tourism).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.14 Author Collaboration Network\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig18\" class=\"InternalRef\"\u003e18\u003c/span\u003e depicts the\u0026ensp;authorship collaboration network, showing lead authors and co-authorship relationships among academics. Main authors\u0026ensp;such as Ooi Keng-Boon, Cheah Jun-Hwa, Luo Xi, Lim Xin-Jean, and Dwivedi Yogesh K. are also well established in the intellectual pillar of some research clusters in Malaysia, China, and the United Kingdom.\u003c/p\u003e \u003cp\u003eOoi Keng-Boon\u0026ensp;and his Malaysian partners to thank for their studies on online impulse buying, e-commerce adoption and digital system behavior. A research cluster, led by\u0026ensp;Cheah Jun-Hwa, Luo Xi \u0026amp; Lim Xin-Jean, emphasizes on marketing communication tactics, hedonic motivation and customer psychology, depicting high cross-border collaborations between Chinese and Malaysian academicians. A group includes Garry Wei-Han Tan, Cham Tat-Huei and Aw Eugene Cheng-Xi who focus on social media influence, materialism and online trust.\u003c/p\u003e \u003cp\u003eThe form of this network embodies\u0026ensp;coherent communities of authors with common interests and frequent cooperation. These co-authorship bonds reveal the existence of specialized research groups that have made an important contribution to the development\u0026ensp;and academic impact of the discipline.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThere are various findings\u0026ensp;and implications of this bibliometric and network analysis of im pulse buying literature over the last 25 years. There has been a particularly rapid increase in scientific output on this topic in the past decade, and a remarkable spike after 2018, paralleling in part the development of digitized economy, online social networking\u0026ensp;and influencer-based marketing. This\u0026ensp;growth highlights the changing relevance of impulse buying as a psychological construct as well as a marketing-driven concept in the area of consumer studies.\u003c/p\u003e \u003cp\u003eThere was a total of 464 documents identified in the present study indexed in the Scopus database and the most frequently\u0026ensp;encountered type of documents were journal articles. More than 80% of the papers were the result of cooperation between two or more\u0026ensp;researchers; thus a high level of research collaboration prevailed. The strong\u0026ensp;international and inter-institutional networks, plotted in the collaboration maps, further support the idea that impulsive buying is a universal research issue that crosses fields of psychology, technology, and marketing.\u003c/p\u003e \u003cp\u003eBoth the three-field Sankey diagram\u0026ensp;and the authorship visualizations also highlight the importance of specific key actors in the field. The study by Luo X, Parsad C and Prashar S is found to be the most productive, and their research has been greatly related to topics such as materialism, consumer behavior, and social commerce. These researchers largely come from universities in Malaysia, China and India, again underscoring the growing importance\u0026ensp;of Asia in consumer research. The production schedule demonstrates that these\u0026ensp;authors have really only gathered pace in the past few years, reflecting the dynamic and developing nature of the field.\u003c/p\u003e \u003cp\u003eKeyword clustering identified five majors\u0026ensp;theme clusters. The first cluster mainly nodes around the central term \u0026ldquo;impulse buying\u0026rdquo; is a linked with hedonicc motivattion, online shopping and purchase intention,\u0026ensp;and is focusing on the emotional and affective drivers of impulsive purchasing behaviour. Another important group is\u0026ensp;self-regulation, social commerce and materialism, which indicates a continued curiosity on the effect of impulsiveness in relation to inner control and external digital factors. The keywords Generation Z, COVID-19, and influencer marketing in\u0026ensp;recent publications evidence a generational and contextual broadening of research views.\u003c/p\u003e \u003cp\u003eThe conceptual structure map constructed by keyword co-occurrence and thematic evolution\u0026ensp;gives it a knowledge frame that shows how the domain evolves at a certain time. Hedonic shopping value and consumer psychology are early themes and\u0026ensp;as additional research emerges it extends into trust in e-commerce, social media influence, and technology acceptance models. These findings correspond\u0026ensp;with current trends toward complexity and interdisciplinarity in contemporary consumer behavior research.\u003c/p\u003e \u003cp\u003eScientific mapping by VOSviewer\u0026ensp;showed international partnership was active. Nations such as China,\u0026ensp;India, Malaysia, and the UK were identified as key players in the global research network. China\u0026rsquo;s strong cooperation with Malaysia and Pakistan, domestically and\u0026ensp;internationally, further solidify its leading role in digital commerce research. The United States and South Korea also had major bilateral academic connections, which were explained by shared attention to\u0026ensp;technology platforms and behavioral analytics.\u003c/p\u003e \u003cp\u003eUniversiti\u0026ensp;Putra Malaysia, UCSI University, Shenzhen University, and Kyung Hee University were the most active institutions with significant contribution in both theoretical and practical research. Institutional collaboration dynamics, as depicted\u0026ensp;in the VOSviewer maps, show dense, polycentric collaboration networks, especially within schools of business, tourism, and information technology.\u003c/p\u003e \u003cp\u003eThe journal spectrum also\u0026ensp;mirrors the interdisciplinary nature of the subject. The Journal of\u0026ensp;Retailing and Consumer Services, Sustainability, and The Journal of Business Research were the most influential journals. A focus on the underlying topics reveals that Sustainability appears\u0026ensp;as a key source among the top sources, and backwards, this trend indicates an increased overlap between impulsive buying behaviour and the dichotomies between ethical consumerism and sustainable marketing or post-pandemic consumer resilience.\u003c/p\u003e \u003cp\u003eThis trajectory from materialism and hedonic value to the latest terms, such as influencer marketing,\u0026ensp;social media, and COVID-19, captures changing social, technological, and economic dynamics. This semantic shift also reflects that scholars are interested not only in what causes\u0026ensp;impulsive buying, but also in properties of environments and technologies that enable it.\u003c/p\u003e \u003cp\u003eThe results of this\u0026ensp;bibliometric study provide some important implications. The first reason is that\u0026ensp;the field is still growing and the high impact authors and institutes, are contributing heavily to the overall output. Secondly, there is clearly some thematic growth in terms of\u0026ensp;digital technology, triggers of emotion, and marketing approaches under research. Internationality also seems to be on the rise, but again there are\u0026ensp;still opportunities for more cross-border and cross-disciplinary collaboration.\u003c/p\u003e \u003cp\u003eThis paper offers a thorough view of the intellectual, geographical, and thematic orbits of research on impulsive buying\u0026ensp;in the last 25 years. It also lays the groundwork for future research directions, highlighting underexplored clusters, as well as key\u0026ensp;contributors and methodological trends. In contrast to the previous systematic reviews, this bibliometric review provides a more comprehensive, data-driven overview of\u0026ensp;the range and development trajectory and hot spots of the field. As the settings of consumer behaviour increasingly change with technology, further research\u0026ensp;should increasingly focus on hybrid models that combine behavourial psychology, algorithmic targeting and ethical reflections.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis research provides a wide bibliometric analysis of impulsive buying behavior global output\u0026ensp;from 2000 to 2025 with records indexed in Scopus. Using the Biblioshiny tool of Bibliometrix package in\u0026ensp;R and VOSviewer, the key contributors, journals, organization, nations, keywords and latest research trends of the study were discovered. Through the analysis of 464 papers, the study\u0026ensp;found a clear trend of growing interest, with pronounced increase over the last decade.\u003c/p\u003e \u003cp\u003eJournal of Retailing and\u0026ensp;Consumer Services, Sustainability (Switzerland), and Journal of Business Research were the three most prolific sources. The authors with the most impact were Luo X, Parsad C, and Prashar S, and institutions like Universiti Putra Malaysia and Universitas Indonesia were among the highest in number\u0026ensp;of publications. \u0026ensp;China was the top producing and collaborating nation followed by India, Indonesia, the USA and Malaysia, acknowledging the presence of Asia as the major player in this domain of research.\u003c/p\u003e \u003cp\u003eIn the keyword\u0026ensp;analysis, \" impulse buying \"and \"impulsive buying behavior\" were identified as the most frequently used terms. Among visualizations, themes still showed around hedonic motivation, purchase intention, e-commerce, and materialism, signifying a\u0026ensp;behavioral or technology-driven focus consisted in the clusters. In\u0026ensp;terms of networking within the field and the evolution of content, strong cross-national collaboration networks as well as growing interdisciplinarity and relevance for society is reflected.\u003c/p\u003e \u003cp\u003eThis bibliometric analysis provides a systematic framework of knowledge map for researchers, institutions and policymakers to comprehend the evolution and hot\u0026ensp;spots in impulsive buying researches. By compiling a quarter century\u0026ensp;of data, it also exposes new domains for investigation, and the increasing interpenetration of digital commerce and behavioural sciences within consumer research.\u003c/p\u003e"},{"header":"6. Future Directions","content":"\u003cp\u003eFuture studies may investigate sophisticated bibliometric and visualization tools such as machine learning based clustering and predictive map of topic\u0026ensp;trajectories. Methods like topic\u0026ensp;dominance modeling, semantic analysis, and temporal keyword evolution prediction have the potential to increase the understanding of research priority drift and subfield emergence. While the study only used the Scopus database in this study due to a comprehensive coverage of citation context, the upcoming study should also apply some comparative datasets from WoS, Dimensions, PUBMED, and GS to verify these findings across different platforms and\u0026ensp;increase the results robustness.\u003c/p\u003e \u003cp\u003eThe creation of interactive bibliometric dashboards or\u0026ensp;advanced visual analytics tools based on the use of AI may permit finer exploration of relationships between authors, cooperation between institutions and interdisciplinary overlap over time. Such utilities would help scholars to\u0026ensp;customize searches of the literature, identify gaps in citation, and predict influential areas.\u003c/p\u003e \u003cp\u003eFuture studies could deal\u0026ensp;with under-researched areas, such as cross-cultural comparisons about impulsivity, the neuroeconomic determinants of purchase decisions, or the influence of AI-based recommendation systems on impulse buying. With the changing landscape of digital platforms and shifting consumer\u0026ensp;habits, privacy ethics, algorithmic bias, and issues regarding sustainability will increasingly need to be included in the research framework. Future work can provide a more nuanced perspective on developing dynamics of impulsive buying when complemented with increased methodological sophistication and more extensive coverage of the datasets, and\u0026ensp;when it is integrated with new consumer technologies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics Approval\u003c/h2\u003e \u003cp\u003eNot applicable. This study is based on bibliometric analysis of published literature and does not involve human participants, human data, or animals.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Publish\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo funds, grants, or other support were received.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor ContributionsX.Z.Q.: Conceptualization, data collection, formal analysis, visualization, and original draft preparation.H.R.C.: Supervision and critical revision of the manuscript.M.S.H.: Supervision and review of the manuscript.All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe dataset supporting the findings of this study is provided as a supplementary file submitted with the manuscript for peer review. The shared material includes the raw bibliographic data exported from the Scopus database in CSV format, which contains the metadata used for the bibliometric analysis. This dataset is made available to ensure transparency and allow verification of the study\u0026rsquo;s findings.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgrawal P (2025) Artificial Intelligence Research (2001\u0026ndash;2022): A Bibliometric Journey through Trends and Patterns. J Data Sci Informetrics Cit Stud 4(1):65\u0026ndash;77\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarauskaitė B (2025) \u003cem\u003eThe impact of scarcity, discounts, free shipping, personalized recommendations, social proof, emotional storytelling, and benefits of products and services on social media advertisements on impulsive purchasing\u003c/em\u003e Vilniaus universitetas.]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaputo A, Kargina M (2022) A user-friendly method to merge Scopus and Web of Science data during bibliometric analysis. J Mark Analytics 10(1):82\u0026ndash;88\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChandrasekhar K, Das S, Gupta N, Jena SK (2024) Comparative analysis of impulse buying behaviour across retail channels: a study of physical stores, e-commerce websites and mobile shopping apps. Economic Affairs 69(2):1109\u0026ndash;1120\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDahish Z, Miah SJ (2022) A bibliometric analysis to explore sentiment analysis in the domain of social media research\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDalal G, Vyas P, Chugh P (2023) On-the-Spot Decision Making: A Bibliometric Investigation into Impulse Buying Research Progression, Network Structures and Emerging Trends. IPE J Manage 13(2):49\u0026ndash;72\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGonzalez E (2021) Value Consciousness, Enjoyment of Mobile Coupons, and Impulse Buying Tendency. Effects on Mobile Coupon Redemption Intentions. Global J Manage Mark 5(1):1\u0026ndash;31\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGulfraz MB, Sufyan M, Mustak M, Salminen J, Srivastava DK (2022) Understanding the impact of online customers\u0026rsquo; shopping experience on online impulsive buying: A study on two leading E-commerce platforms. J Retailing Consumer Serv 68:103000\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaur K, Sharma T (2024) Impulse buying in the digital age: An exploration using systematic literature review approach. J Consumer Behav 23(5):2553\u0026ndash;2584\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePautrat M, Le Guen A, Barrault S, Ribadier A, Ballon N, Lebeau J-P, Brunault P (2022) Impulsivity as a risk factor for addictive disorder severity during the COVID-19 lockdown: results from a mixed quantitative and qualitative study. Int J Environ Res Public Health 20(1):705\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePessin VZ, Yamane LH, Siman RR (2022) Smart bibliometrics: an integrated method of science mapping and bibliometric analysis. Scientometrics 127(6):3695\u0026ndash;3718\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRajib RI, Roy P (2023) Influence of social media on consumer buying behavior and decision making: insights from surveys and a case. study of Flash Digital Agency in Bangladesh\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi J, Duan Y (2024) Knowledge-map and research trends of circulating tumor cells in breast cancer: a scientometric analysis. Discover Oncol 15(1):506\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh VK, Singh P, Karmakar M, Leta J, Mayr P (2021) The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis. Scientometrics 126:5113\u0026ndash;5142\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThomas A, Gupta V (2022) Tacit knowledge in organizations: bibliometrics and a framework-based systematic review of antecedents, outcomes, theories, methods and future directions. J Knowl Manage 26(4):1014\u0026ndash;1041\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYan L, Zhiping W (2023) Mapping the literature on academic publishing: A bibliometric analysis on WOS. SAGE Open 13(1):21582440231158562\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"bibliometric analysis, impulsive buying, Scopus, Biblioshiny application, Bibliometrix package, R, VOSviewer","lastPublishedDoi":"10.21203/rs.3.rs-9195074/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9195074/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eB\u003c/b\u003euying trend has become one of the key topic of research in consumer behavior studies due to psychological\u0026ensp;events and online marketing phenomena. Although many\u0026ensp;researches have explored consumer decision-making, little research has analyzed the research trends of impulsive buying based on bibliometrics. The aim of this study was to\u0026ensp;explore the global publication trends and research hotspots of the impulsive buying from 2000 to 2025 based on the bibliometric analysis. The searched defined term was \u0026ldquo;impulsive buying\u0026rdquo;, which produced 464 hits across the articles, reviews, conference papers and\u0026ensp;book chapters in Scopus. With the help of Bibliometrix, Biblioshiny in R and VOSviewer, were used\u0026ensp;for data organization and visualization. The examination similarly demonstrated an increasing number of papers, especially post 2018, with China, India, and Malaysia\u0026ensp;acting as dominant knowledge producers. The most prolific authors were Luo X and Parsad C, and Journal\u0026ensp;of Retailing and Consumer Services was the leading source of publications. The main research themes were hedonic motivation, online shopping, social commerce, and\u0026ensp;self-control. The intellectual structure, theme progress and\u0026ensp;global cooperation of impulsive buying research were systematically summarized in this study. Such understanding could help scholars, practitioners, and policy makers address the trajectory of the research field\u0026ensp;and find further research opportunities.\u003c/p\u003e","manuscriptTitle":"Bibliometric Analysis of Publications on Impulsive Buying from 2000 to 2025 in the Scopus Database Using R and VOSviewer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-24 06:28:41","doi":"10.21203/rs.3.rs-9195074/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-16T16:35:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-06T11:42:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-06T09:47:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-05T12:10:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2026-04-05T12:06:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"78754dd9-040c-49e1-a0fd-e42998b2b38e","owner":[],"postedDate":"April 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66466665,"name":"Business and commerce/Business and management"},{"id":66466666,"name":"Social science/Business and management"},{"id":66466667,"name":"Business and commerce/Information systems and information technology"}],"tags":[],"updatedAt":"2026-04-24T06:28:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-24 06:28:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9195074","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9195074","identity":"rs-9195074","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}