Editor’s Introduction 30(4)
Vladimir Zwass
International Journal of Electronic Commerce,
Volume 30, Number 4, 2026, pp. 471-473.
This issue of the International Journal of Electronic Commerce (IJEC) completes its 30th volume. When I founded IJEC as the first and leading scholarly journal devoted entirely to e-commerce (EC), the intellectual and pragmatic contents of the interdisciplinary field were markedly limited in scope and scale as compared to the area it spans today. From its origin, IJEC approached EC as a broad, encompassing field far surpassing e-retail; this has always been the compass of the research we publish. The conceptual hierarchical framework of the field of EC. I proposed in the first issue of the journal has held up well [1]. The components that are now populating it have, of course, advanced and diversified most significantly. The new developments build on the mass global participation in the EC activities; on the individuals’ ability to monetize their intellect, ingenuity, and inventiveness via the Internet/Web; on the ability to rapidly start up and scale a new business model on the existing infrastructural stacks and with the needed contributors located virtually anywhere; the ability to work within the existing structures or outside of them; the individuals’ increasing power to influence the course of marketplaces (and events in general); the ability to leverage massive longitudinal and horizontal data; and on such capabilities as shifting the direct costs of participation to the third parties (say, advertisers).
Over the years of the IJEC publication, these capabilities have given rise to such world-changing phenomena as mobile and social commerce, platformization, cryptocurrencies and other tokens, crowdsourcing and co-creation, digital cities and humans, commerce supported by large language models (LLM), metaverses, livestreaming, gig economy, online influencing, prediction markets—and others. The continuing invention, infusion, and interbreeding of these phenomena shapes the new, and growing, outlines of EC. All of them have been understood better owing to the research works published in IJEC.
The first three papers of the present issue study three nodal aspects of platformization. The first of them addresses crowdfunding platforms, which have taken their place as a significant form of financing. The reward-based crowdfunding platforms bring together the seekers of capital with the investors, particularly in the campaigns for small and riskier projects and startups. Shuya Lu, Shih-Lun (Allen) Tseng, Yinglu (Elle) Wu, Fengxia Zhu, and Jianan Wu investigate the behavior of the potential funders after the campaign’s goal has been reached. As the campaign progresses, the behavior of individuals on the funding side of the platform is influenced by the behavior of other investors. The herding effect differs at different stages of the campaign. The authors’ focus on the post-goal stage brings novel findings as the strength of positive herding gains in view of the successful campaign. The authors discover differential behavior in several aspects with respect to the campaigns for private and public goods. Other, more granular, results contribute to our understanding of social behavior in online fundraising and will help in platform design.
On-demand platforms reverse the customary roles of sellers and buyers. Instead of sellers offering a range of products, the buyers present their demands, typically for services or customized goods. Gig platforms featuring rides, deliveries, and various forms of other—often freelance—labor are all examples of on-demand platforms. Information asymmetry is the key difficulty in buyer supplier matching on such platforms. Reputational information about providers, such as electronic word-of-mouth (eWoM) is widely employed; some platforms are also offering seller’s certification. Here, Ruigang Jia, Peijian Song, Wenyu Yang, and Liangding Jia present their study of the effects of presenting on the platform the demand-side reputations. The disclosure of buyer’s reputation on the platforms is found to enhance the platform’s matching function (as can be expected); the paper offers also more granular results. It may also be expected that in a longer perspective the disclosure of reputation-related information about buyers will lead to the rise in the quality of customers, assuming a validation of the information by the platform. It is to be noted that the platform also gains valuable data.
Indeed, consumer-oriented sales platforms, with Amazon and Alibaba as leading examples, are massive repositories of data on the changing (sometimes rapidly) consumer preferences and broad demand patterns. Access to this data, assisted by the artificial intelligence (AI) software, can be a potent stimulus for manufacturers’ innovation, driving the competitive marketplace. Ruohan Ma, Bo He, and Guang Yang present the results of their game-theoretic analysis of the potential proactive use of their data by platforms through presenting innovation proposals to the manufacturers—and sharing the financial outcomes. With four combinations of selling formats and product pricing that may be deployed, their modeling allows the platforms to select the appropriate ones under the contingencies of a case.
The two subsequent papers present the investigations of product recommendations and reviews, the principal means of matching. With the recent dramatic progress in AI and its infusion in EC, certain platforms are beginning to use AI-generated product reviews for the items lacking consumer produced ones. Such reviews are based on the reviews for similar products. Assuming that such a review is clearly designated as AIgenerated, the practice appears acceptable. But how effective are the reviews? Yizhen Wei, David (Jingjun) Xu, and Kai Li use a laboratory experiment to offer an answer. The authors classify the AI-generated reviews into three categories and determine the one that most effectively induces consumer trust. The results are obtained in the partial presence or total absence of consumer-generated reviews alongside. This forwardlooking paper is of importance as we look to the future of the expanding product repertoires and proliferating deployment of AI.
The concluding paper of the issue, by Guofang Nan, Ruixuan Wang, Jiwei Luo, and Zhiyun Ji, presents a novel approach to providing personalized hotel recommendations, a potentially large category. The authors’ combine users’ preferences and hotel features within an entropy framework, and construct consumer-hotel graphs in order to derive the personalized recommendations. Beyond that, they reduce the compute load of graph processing, which can be significant for larger pair sets. The authors demonstrate the surpassing accuracy of recommendations obtained with their approach as compared to the presently available ones. Clearly, the method offered by the authors can be adapted to other categories of products.
The 30-year milestone is an excellent opportunity for me to thank the members of the journal’s Editorial Board and its outstanding reviewers, without whom none of this would have been possible. The greatest thanks go of course to our authors—they are the
journal.
Reference
[1] Zwass, V. Electronic commerce: Structures and issues. International Journal of Electronic Commerce, 1, 1 (1996), 3–23.