Journal of Theoretical and Applied Electronic Commerce Research

19 pages, 690 KiB

Open AccessArticle

Business and Customer-Based Chatbot Activities: The Role of Customer Satisfaction in Online Purchase Intention and Intention to Reuse Chatbots

by Doğan Mert Akdemir and Zeki Atıl Bulut

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2961-2979; https://doi.org/10.3390/jtaer19040142 - 28 Oct 2024

Abstract

In the online shopping context, brands aim to achieve a high level of profit by providing better customer satisfaction by using various artificial intelligence tools. They try creating a satisfactory customer experience by creating a system that provides never-ending customer support by using [...] Read more.

In the online shopping context, brands aim to achieve a high level of profit by providing better customer satisfaction by using various artificial intelligence tools. They try creating a satisfactory customer experience by creating a system that provides never-ending customer support by using dialog-based chatbots, especially in the field of customer service. However, there is a lack of research investigating the impact of business and customer-based chatbot activities together on online purchase intention and the intention to reuse chatbots. This research considers the use of chatbots as a marketing tool from both customer and business perspectives and aims to determine the factors that affect the customers’ intention to purchase online and reuse chatbots. Accordingly, the impact on customer satisfaction with chatbot usage, which is based on chatbots’ communication quality and customers’ motivations to use chatbots, on online purchase intention and intention to reuse chatbots was examined. Through an online questionnaire with two hundred and ten participants, employing structural equation modeling, we revealed that customer satisfaction with chatbot usage has a greater impact on the intention to reuse chatbots than on online purchase intentions. In addition, chatbot communication quality has a greater impact on customer satisfaction with chatbot usage than customers’ motivation to use chatbots. To solidify these findings, confirmatory factor analysis, along with reliability and validity assessments, were implemented within the analytical framework to provide robust support for the study’s hypotheses. These findings not only provide empirical evidence and implications for companies in online shopping but also extend the understanding of AI tools in marketing, highlighting their subtle impact on consumer decision-making in the dynamic digital marketplace. Full article

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42 pages, 1293 KiB

Open AccessArticle

Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs

by Shiyun Li and Omar Dib

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2919-2960; https://doi.org/10.3390/jtaer19040141 - 26 Oct 2024

Abstract

The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate harmful content, execute phishing schemes, and orchestrate various cyber attacks. As [...] Read more.

The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate harmful content, execute phishing schemes, and orchestrate various cyber attacks. As these threats evolve, detecting malicious URLs (MURLs) has become crucial for safeguarding internet users and ensuring a secure online environment. In response to this urgent need, we propose a novel machine learning-driven framework designed to identify known and unknown MURLs effectively. Our approach leverages a comprehensive dataset encompassing various labels—including benign, phishing, defacement, and malware—to engineer a robust set of features validated through extensive statistical analyses. The resulting malicious URL detection system (MUDS) combines supervised machine learning techniques, tree-based algorithms, and advanced data preprocessing, achieving a high detection accuracy of 96.83% for known MURLs. For unknown MURLs, the proposed framework utilizes CL_K-means, a modified k-means clustering algorithm, alongside two additional biased classifiers, achieving 92.54% accuracy on simulated zero-day datasets. With an average processing time of under 14 milliseconds per instance, MUDS is optimized for real-time integration into network endpoint systems. These outcomes highlight the efficacy and efficiency of the proposed MUDS in fortifying online security by identifying and mitigating MURLs, thereby reinforcing the digital landscape against cyber threats. Full article

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23 pages, 960 KiB

Open AccessArticle

Maintaining Accuracy While Reducing Effort in Online Decision Making: A New Quantitative Approach for Multi-Attribute Decision Problems Based on Principal Component Analysis

by Herbert Jodlbauer and René Riedl

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2896-2918; https://doi.org/10.3390/jtaer19040140 - 22 Oct 2024

Abstract

This paper explores consumer decision making, particularly focusing on the increasing prevalence of choices on the Internet such as online shopping. Examining the fundamental question of how individuals decide how to decide, our paper draws upon the effort–accuracy framework. This framework indicates that [...] Read more.

This paper explores consumer decision making, particularly focusing on the increasing prevalence of choices on the Internet such as online shopping. Examining the fundamental question of how individuals decide how to decide, our paper draws upon the effort–accuracy framework. This framework indicates that people typically consider both the cognitive effort associated with employing a specific decision strategy and the decision quality (i.e., accuracy) implied by using a particular strategy. However, decision strategies with high accuracy imply high effort. Empirical evidence shows that people often use decision strategies that require little effort. As a result, accuracy is often not high. Against this backdrop, this paper introduces a quantitative approach leveraging principal component analysis (PCA) as a decision support tool. Based on a simulation study, the approach demonstrates that it is possible to maintain high accuracy with significantly reduced effort in multi-attribute decision situations where attribute information is available in a quantitative format. This demonstration is based on the example of two decision strategies, which are both theoretically and practically highly relevant: the multi-attribute utility model (MAU) and the elimination-by-aspects strategy (EBA). By employing PCA for dimensionality reduction, the approach becomes particularly advantageous for online shops and online comparison portals, presenting users with concise yet accurate information. It is important to emphasize that our PCA approach is designed for data with a natural ordering, primarily focusing on quantitative variables. Consequently, decision situations where qualitative variables (e.g., product design or color) play a role in the decision-making process will need further exploration in future studies. However, we present a first solution to this problem so that our approach, based on this solution, can be implemented by online shops and online comparison portals in the near future. Full article

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16 pages, 982 KiB

Open AccessArticle

Evolving Consumer Preferences: The Role of Attribute Shifts in Online Travel Agency Satisfaction and Loyalty

by Luyao Zhi and Hong-Youl Ha

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2880-2895; https://doi.org/10.3390/jtaer19040139 - 18 Oct 2024

Abstract

The attributes that people consider when selecting an online travel agency (OTA) change over time, affecting how consumer satisfaction and loyalty evolve. However, attribute weight shifts in subsequent OTA visits cannot be determined using a cross-sectional approach. Thus, this study investigates the linkage [...] Read more.

The attributes that people consider when selecting an online travel agency (OTA) change over time, affecting how consumer satisfaction and loyalty evolve. However, attribute weight shifts in subsequent OTA visits cannot be determined using a cross-sectional approach. Thus, this study investigates the linkage dynamics between satisfaction and loyalty intentions as OTA attribute weights shift over time. We also assess the moderating effect of sales promotions on this linkage across subsequent OTA visits. Using a two-time-lag survey methodology (T1 and T2), we obtain 329 usable data. Our findings demonstrate that the link between satisfaction and loyalty intentions strengthens as customers gain more experience with an OTA. While price and post-service quality weights increase sharply, the weights of security and ease of use decrease. Furthermore, our findings show that the moderating effect of sales promotions does not appear in the early stages of a consumer’s experience with an OTA. Our research is the first to offer a complete understanding of the role of sales promotions based on the satisfaction–loyalty mechanism, considering a broad range of OTA selection attributes. Full article

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29 pages, 13855 KiB

Open AccessArticle

Cart-State-Aware Discovery of E-Commerce Visitor Journeys with Process Mining

by Bilal Topaloglu, Basar Oztaysi and Onur Dogan

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2851-2879; https://doi.org/10.3390/jtaer19040138 - 17 Oct 2024

Abstract

Understanding customer journeys is key to e-commerce success. Many studies have been conducted to obtain journey maps of e-commerce visitors. To our knowledge, a complete, end-to-end and structured map of e-commerce journeys is still missing. In this research, we proposed a four-step methodology [...] Read more.

Understanding customer journeys is key to e-commerce success. Many studies have been conducted to obtain journey maps of e-commerce visitors. To our knowledge, a complete, end-to-end and structured map of e-commerce journeys is still missing. In this research, we proposed a four-step methodology to extract and understand e-commerce visitor journeys using process mining. In order to obtain more structured process diagrams, we used techniques such as activity type enrichment, start and end node identification, and Levenshtein distance-based clustering in this methodology. For the evaluation of the resulting diagrams, we developed a model utilizing expert knowledge. As a result of this empirical study, we identified the most significant factors for process structuredness and their relationships. Using a real-life big dataset which has over 20 million rows, we defined activity-, behavior-, and process-level e-commerce visitor journeys. Exploitation and exploration were the most common journeys, and it was revealed that journeys with exploration behavior had significantly lower conversion rates. At the process level, we mapped the backbones of eight journeys and tested their qualities with the empirical structuredness measure. By using cart statuses at the beginning and end of these journeys, we obtained a high-level end-to-end e-commerce journey that can be used to improve recommendation performance. Additionally, we proposed new metrics to evaluate online user journeys and to benchmark e-commerce journey design success. Full article

(This article belongs to the Topic Online User Behavior in the Context of Big Data)

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23 pages, 846 KiB

Open AccessArticle

The Influence Mechanism of Narrative Strategies Used by Virtual Influencers on Consumer Product Preferences

by Yuelong Zeng, Gefei Pu, Jingwen Liu and Wenting Feng

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2828-2850; https://doi.org/10.3390/jtaer19040137 - 17 Oct 2024

Abstract

As social media has risen, virtual social media influencers have become a significant tool in modern marketing, utilizing computer-generated images (CGI), machine learning algorithms, and artificial intelligence technologies to connect with consumers via virtual online personas. In this study, the Uses and Gratifications [...] Read more.

As social media has risen, virtual social media influencers have become a significant tool in modern marketing, utilizing computer-generated images (CGI), machine learning algorithms, and artificial intelligence technologies to connect with consumers via virtual online personas. In this study, the Uses and Gratifications Theory (UGT) is employed as a theoretical framework to explore the effects of educational narrative strategies and evaluative narrative strategies on consumer product preferences, with an analysis of the mediating role of word-of-mouth effectiveness and the moderating role of perceived product usability. It was demonstrated in Experiment 1 that virtual influencers employing educational narrative strategies are more effective than those using evaluative narrative strategies in enhancing consumer product preferences. The boundaries of the study were clarified in Experiment 2, which found that the main effect of educational narrative strategies utilized by social media influencers to increase consumer product preferences is present only in the context of virtual influencers. In Experiment 3, the mediating role of word-of-mouth recommendation effectiveness in the relationship between narrative strategies and consumer product preferences was further verified. The moderating role of perceived product usability was examined in Experiment 4, and it was found that the main effect is more pronounced in contexts where perceived product usability is low. The results of this study provide theoretical and practical guidance on how companies can effectively leverage virtual influencers to promote their products. Full article

(This article belongs to the Topic Interactive Marketing in the Digital Era)

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15 pages, 781 KiB

Open AccessArticle

The Influence of Artificial Intelligence on Generation Z’s Online Fashion Purchase Intention

by Carmen Ruiz-Viñals, Marilé Pretel-Jiménez, José Luis Del Olmo Arriaga and Albert Miró Pérez

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2813-2827; https://doi.org/10.3390/jtaer19040136 - 15 Oct 2024

Abstract

The advance of digitalization has generated an ever-increasing number of options in the digital sphere. This phenomenon has transformed multiple sectors, including e-commerce and, in particular, the fashion industry. Artificial intelligence (AI) has emerged as a powerful tool that is redefining the online [...] Read more.

The advance of digitalization has generated an ever-increasing number of options in the digital sphere. This phenomenon has transformed multiple sectors, including e-commerce and, in particular, the fashion industry. Artificial intelligence (AI) has emerged as a powerful tool that is redefining the online shopping experience. However, there is little research on how AI influences this purchasing process, limiting its full exploitation. This study provides new insight into how artificial intelligence influences online purchase intention in this sector by examining Generation Z consumers’ attitude and purchase intention using the Echo Look AI device. This study involved 210 university students aged between 18 and 25 years old who were surveyed in the cities of Madrid and Barcelona. The results indicate that perceived quality, attitude towards AI and perceived usefulness have a positive influence on purchase intention. Based on these results, theoretical and practical implications are discussed. Full article

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14 pages, 973 KiB

Open AccessArticle

Antecedents and Consequences of Attitudes toward Donation-Based Crowd-Funding Platforms

by Namhyun Um

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2799-2812; https://doi.org/10.3390/jtaer19040135 - 15 Oct 2024

Abstract

The landscape of fundraising has undergone a transformative shift with the rise in donation-based crowdfunding platforms. This study investigates the multifaceted factors shaping individuals’ attitudes toward these platforms, with a focus on key antecedents. Examining their impact on donation intentions and electronic word-of-mouth [...] Read more.

The landscape of fundraising has undergone a transformative shift with the rise in donation-based crowdfunding platforms. This study investigates the multifaceted factors shaping individuals’ attitudes toward these platforms, with a focus on key antecedents. Examining their impact on donation intentions and electronic word-of-mouth intentions, this research draws from a sample of 326 college students. Our results affirm the critical roles of perceived usefulness, ease of use, credibility, and self-efficacy in influencing attitudes. Additionally, attitudes significantly contribute to both donation and electronic word-of-mouth intentions. Structural model modifications underscore the interdependence of these factors, enhancing the model fit. Our findings offer practical insights for platform administrators, campaign creators, and stakeholders engaged in online philanthropy, highlighting the importance of user-friendly designs, trust-building, and user confidence for successful crowdfunding campaigns. Full article

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16 pages, 717 KiB

Open AccessArticle

How Can Mobile Social Media Sustain Consumers? Assessing the Dynamic Influences of Differentiated Perceived Interactivity on Attitudes, Belongingness, and Stickiness

by Hua Pang, Yang Ruan and Lei Wang

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2783-2798; https://doi.org/10.3390/jtaer19040134 - 14 Oct 2024

Abstract

The swift advancement of wireless communication technology has resulted in the gradual permeation of mobile social media into everyday lives, proffering unparalleled prospects for the dissemination of information and supporting networking. Despite several studies on the perceived interactivity of mobile social media, academic [...] Read more.

The swift advancement of wireless communication technology has resulted in the gradual permeation of mobile social media into everyday lives, proffering unparalleled prospects for the dissemination of information and supporting networking. Despite several studies on the perceived interactivity of mobile social media, academic attention on comprehending the fundamental elements that lead to consumers belonging or sticking to these platforms has been limited. Drawing on previous scientific literature in related domains, this study presents a conceptual research framework that examines the extent to which three distinct facets of perceived interactivity, namely mutual interaction, message responsiveness, and social connectedness, may influence consumers’ attitudes towards mobile social media, ultimately impacting their belongingness and stickiness. This study empirically evaluates data from 665 mobile social media consumers and employs statistical analysis to demonstrate that perceived interactivity significantly influences consumers’ attitudes towards mobile social media platforms. Moreover, consumer attitudes towards these platforms are found to be the most significant predictor of consumer belongingness and stickiness. Furthermore, consumer belongingness also exerts a significant impact on stickiness. By identifying the factors and rationales that influence consumer belongingness and stickiness in using mobile social media, this study addresses the need for a comprehensive evaluation of perceived interactivity and consumer attitudes. The aforementioned discoveries not only have the potential to enhance our comprehension of consumer belongingness and stickiness in the realm of perceived interactivity but also to provide experts with innovative viewpoints, clarify effective strategies for promoting the adoption of mobile social media, and encourage increased levels of user engagement in a society that is saturated with mobile devices. Full article

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18 pages, 932 KiB

Open AccessArticle

How Perceived Similarity between Travel Destinations and Hometowns Influences Consumer Experience in Online Travel Blind Boxes: The Mediating Role of the Aha Moment

by Meilian Liu, Xiaoguang Chen, Xinyue Zhao and Qian Xu

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2765-2782; https://doi.org/10.3390/jtaer19040133 - 11 Oct 2024

Abstract

The blind box market is fast-growing, from toys, baseball cards, and vibrant second-hand products to the recent growing tourism market, becoming the latest trend sweeping through China, not only in offline retailing but also online businesses and e-commerce. For young consumers, the element [...] Read more.

The blind box market is fast-growing, from toys, baseball cards, and vibrant second-hand products to the recent growing tourism market, becoming the latest trend sweeping through China, not only in offline retailing but also online businesses and e-commerce. For young consumers, the element of mystery is a big part of the fun that not everyone can obtain the most special and desirable products. The present research aims to elucidate how travel blind boxes attract young consumers in terms of their psychological connections to travel destinations. In particular, building upon psychological distance theory, this study examines the relationship between perceived similarities between travel destinations and hometowns and the attraction of travel blind boxes. Contributing to the existing literature that mainly describes the phenomenon of the blind box craze but often fails to identify its underlying mechanisms, the present study advances our understanding of such trendy marketing practices by investigating the mediating role of the “aha moment” and the boundary conditions of electronic word-of-mouth recommendations and price sensitivity. Full article

(This article belongs to the Topic Interactive Marketing in the Digital Era)

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18 pages, 705 KiB

Open AccessArticle

Does Information Source Matter? Corporate Reputation Management during Negative Social Responsibility Events

by Hongxia Peng, Qiang Zhang and Zhiqiang Zhang

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2747-2764; https://doi.org/10.3390/jtaer19040132 - 9 Oct 2024

Abstract

In the era of digital marketing, where consumers and enterprises frequently interact with each other, consumers hold different attitudes toward the different sources of information, including corporate social responsibility information. Negative corporate social responsibility can have direct impacts on corporate reputation. Choosing appropriate [...] Read more.

In the era of digital marketing, where consumers and enterprises frequently interact with each other, consumers hold different attitudes toward the different sources of information, including corporate social responsibility information. Negative corporate social responsibility can have direct impacts on corporate reputation. Choosing appropriate channels to publish the negative social responsibility information of enterprises in order to reduce the impact of these negative social events on corporate reputation is imperative for corporate image management. This research examines the differences in the impact of enterprise-generated content and -co-generated content on consumer attitudes using second-hand data analysis and then investigates how different information sources influence corporate reputation through empirical experiments. The results indicate that co-generated content performs better than other sources of information on corporate reputation, while professional user-generated content has the most negative impact. We further identify the external attribution as a mediation mechanism in the relationship between information sources and corporate reputation. The theoretical contributions and managerial implications of the research findings are discussed. Full article

(This article belongs to the Topic Interactive Marketing in the Digital Era)

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19 pages, 1083 KiB

Open AccessArticle

Research on the Relationship between Characteristics of Video Bloggers and Consumers’ Purchase Intentions

by Chong Zhang, Yueliang Liu and Ying Sun

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2728-2746; https://doi.org/10.3390/jtaer19040131 - 8 Oct 2024

Abstract

Video blogging channels for social media technology continue to innovate and evolve, and brands are beginning to rely on social media channels for product marketing. The factors influencing consumers’ purchase intention for products advertised by video bloggers are numerous and unclear. The main [...] Read more.

Video blogging channels for social media technology continue to innovate and evolve, and brands are beginning to rely on social media channels for product marketing. The factors influencing consumers’ purchase intention for products advertised by video bloggers are numerous and unclear. The main purpose of this study is to explore the mechanism by which the characteristics of video bloggers influence the formation of emotional cognition and then influences consumers’ purchase intention. Based on the SOR model, 518 questionnaires were administered to Chinese video blogging users. The AMOS 24.0 and SPSSAU 24.0 web tools were used to analyze the study data. Empirical results indicate that consumers’ perceived homogeneity, expertise, degree of emotional attachment to video bloggers, and perceived source confidence have a direct or indirect positive influence on purchase intentions. Evident advertising intention weakens the relationship between emotional attachment and purchase intention. This result is strategically important for a brand’s advertising efforts and market share and provides new research insights and frameworks for studying consumers’ advertised product purchase behaviors in the context of video blogging channels for social media. Full article

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14 pages, 3352 KiB

Open AccessArticle

Beyond Empathy: Unveiling the Co-Creation Process of Emotions through a Wearable Device

by Bach Q. Ho, Kei Shibuya and Makiko Yoshida

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2714-2727; https://doi.org/10.3390/jtaer19040130 - 8 Oct 2024

Abstract

Emotions fluctuate during the process of social interaction. Although the co-creation of emotions through organizational behavior has been discussed theoretically in existing research, there is no method to demonstrate how emotions are co-created. Instead, previous studies have paid much attention to empathy, in [...] Read more.

Emotions fluctuate during the process of social interaction. Although the co-creation of emotions through organizational behavior has been discussed theoretically in existing research, there is no method to demonstrate how emotions are co-created. Instead, previous studies have paid much attention to empathy, in which a person’s emotions are contagious. In contrast to self-report, which is a traditional method that can only assess emotions at a single point in time and adapts to empathy, biometric technology has made it possible to analyze emotional fluctuations over time. However, previous studies have focused only on understanding the emotional fluctuations of individuals separately. In the present study, we developed a system to measure the co-creation of emotions using a wearable device. The pulse rate was converted into valence as a positive–negative emotion, and the fluctuations in valence were analyzed by cross-correlation. We demonstrated the feasibility of the proposed system through triangulation by integrating biometrics with observation and self-report. The proposed system was verified to measure the co-creation of pair and group emotions using real-world data beyond laboratory settings. The present study contributes to business administration by proposing a critical concept for measuring the co-creation of emotions based on a constructionist approach. Full article

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20 pages, 874 KiB

Open AccessArticle

Enhancing Environmental Awareness for Sustainable Retail: Analysis of the Buy-Online-and-Return-in-Store Policy Adoption Using Theory of Planned Behavior

by Xinyu Yao, Yanfeng Liu and Guanqiu Qi

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2694-2713; https://doi.org/10.3390/jtaer19040129 - 8 Oct 2024

Abstract

This study explores the context of buy-online-and-return-in-store (BORS) policy from an environmental perspective and conducts a comprehensive analysis through the theory of planned behavior (TPB). Adding environmental awareness and awareness of consequences provides a new perspective on how sustainable practices can be enhanced [...] Read more.

This study explores the context of buy-online-and-return-in-store (BORS) policy from an environmental perspective and conducts a comprehensive analysis through the theory of planned behavior (TPB). Adding environmental awareness and awareness of consequences provides a new perspective on how sustainable practices can be enhanced through an omni-channel retail strategy. Survey responses from 405 participants were analyzed using structural equation modeling. Results show that attitudes, subjective norms, and perceived behavioral control are key determinants of practical BORS policy. The study found that environmental awareness significantly influenced BORS adoption directly and indirectly by enhancing perceived behavioral control, whereas consequence awareness primarily affected adoption by shaping consumer attitudes. Compared with consumers who choose to return online, consumers who prefer in-store returns show higher environmental awareness, highlighting the environmental advantages of BORS. In addition, the BORS policy improves overall shopping satisfaction by integrating the convenient process of online purchases and offline returns, allowing consumers to switch freely between different channels. These findings provide valuable insights for retailers and policymakers seeking to promote sustainable consumer behavior to effectively promote the importance of sustainable retail practices. Full article

(This article belongs to the Topic Consumer Psychology and Business Applications)

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21 pages, 1625 KiB

Open AccessArticle

Uncovering How Information Quality Shapes Diverse User Engagement on Content Community Platforms: Harnessing Deep Learning for Feature Extraction

by Yanzi Wang, Min Wang, Zhen Zhu and Haoxiang Ye

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2673-2693; https://doi.org/10.3390/jtaer19040128 - 4 Oct 2024

Abstract

The success of content community platforms (CCPs) heavily depends on the active engagement of users attracted by externally generated content. Previous research has highlighted the differentiation among various forms of user engagement, such as likes, comments, and retweets, in shaping the dynamics of [...] Read more.

The success of content community platforms (CCPs) heavily depends on the active engagement of users attracted by externally generated content. Previous research has highlighted the differentiation among various forms of user engagement, such as likes, comments, and retweets, in shaping the dynamics of value co-creation on CCPs. Our objective is to uncover distinct patterns of impact that information quality features have on these different forms of user engagement. Specifically, we employed deep learning techniques to extract information quality features and identified them as persuasive factors operating through central and peripheral routes based on the elaboration likelihood model (ELM), stimulating user engagement. Our dataset was derived from MaBeeWoo, China’s largest specialized CCP for travelogues with minimal barriers for creating text and image-based travelogues. By utilizing a negative binomial model, our analysis reveals significant differences in antecedents between retweets and likes/comments while also highlighting variations in the impact levels of specific content quality features between likes and comments. These findings suggest contrasting patterns regarding how content quality features influence information production and dissemination on CCPs, underscoring the necessity for platform sponsors to develop adaptive mechanisms aligned with their strategic objectives for incentivizing specific quality features. Full article

(This article belongs to the Collection Utilizing Models for e-Business Decision-Making: From Data to Wisdom)

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23 pages, 588 KiB

Open AccessArticle

Exploring Apparel E-Commerce Unethical Return Experience: A Cross-Country Study

by José Magano, Jana Turčinkova, Mário C. Santos, Roxana Correia and Mikhail Serebriannikov

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2650-2672; https://doi.org/10.3390/jtaer19040127 - 3 Oct 2024

Abstract

This study examines the relationships between socio-demographic factors, purchase frequency, internet expertise, and unethical return behavior in apparel e-commerce, with a particular focus on the act of wardrobing—wearing and then returning used apparel. The research involved a survey of 1026 online apparel consumers [...] Read more.

This study examines the relationships between socio-demographic factors, purchase frequency, internet expertise, and unethical return behavior in apparel e-commerce, with a particular focus on the act of wardrobing—wearing and then returning used apparel. The research involved a survey of 1026 online apparel consumers from Portugal and the Czech Republic. The results show that frequent buyers, internet-savvy users, women and younger e-consumers report more satisfactory return experiences. However, several e-consumers engage in wardrobe shopping, with higher rates observed among males, internet-savvy users and youth. There are differences between the countries studied: in the Czech sample, men and advanced internet users are more likely to engage in wardrobing, while in the Portuguese sample, it is more prevalent among younger e-consumers. The results also document that, overall, men are seven times more likely to practice unethical return, while increasing age decreases the likelihood. The originality of the study lies in its approach and findings, which contribute to the understanding of post-purchase behavior and moral hazards in e-commerce and highlight the need for retailers to balance return policies that prevent abuse while maintaining customer satisfaction. Recommendations are made for improving loyalty programs and personalizing the e-shopping experience to minimize returns and promote ethical consumer behavior. Further research is suggested to develop these findings and improve return management in apparel e-commerce. Full article

20 pages, 812 KiB

Open AccessArticle

The Effects of E-Commerce Recommendation System Transparency on Consumer Trust: Exploring Parallel Multiple Mediators and a Moderator

by Yi Li, Xiaoya Deng, Xiao Hu and Jing Liu

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2630-2649; https://doi.org/10.3390/jtaer19040126 - 1 Oct 2024

Abstract

Recommendation systems are used in various fields of e-commerce and can bring many benefits to consumers but consumers’ trust in recommendation systems (CTRS) is lacking. Recommendation system transparency (RST) is an important factor that affects CTRS. Applying a three-layered trust model, this paper [...] Read more.

Recommendation systems are used in various fields of e-commerce and can bring many benefits to consumers but consumers’ trust in recommendation systems (CTRS) is lacking. Recommendation system transparency (RST) is an important factor that affects CTRS. Applying a three-layered trust model, this paper discusses the influence of RST on CTRS in the e-commerce domain, demonstrating the mediating role of perceived effectiveness and discomfort and the moderating role of consumers’ domain knowledge. We recruited 500 participants for an online hypothetical scenario experiment. The results show that consumers’ perceived effectiveness and discomfort can mediate the relationship between RST and CTRS. Specifically, RST (vs. non-transparency) leads to higher perceived effectiveness ( promoting CTRS) and lower levels of discomfort (which inhibits CTRS), in turn increasing CTRS. Domain knowledge positively moderates the positive impact of RST on perceived effectiveness, while negatively moderating the negative impact of RST on discomfort. Further, gender has a negative impact on CTRS when consumers are purchasing experience products but there is no effect when purchasing search products. Full article

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25 pages, 1208 KiB

Open AccessArticle

The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping

by Ovidiu-Iulian Bunea, Răzvan-Andrei Corboș, Sorina Ioana Mișu, Monica Triculescu and Andreea Trifu

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2605-2629; https://doi.org/10.3390/jtaer19040125 - 30 Sep 2024

Abstract

This study explores the impact of artificial intelligence (AI) tools on the purchase intentions of members of Generation Z (Gen Z) in online shopping, using an adapted technology acceptance model (TAM). It incorporates exposure to AI, usage of AI, and knowledge about AI, [...] Read more.

This study explores the impact of artificial intelligence (AI) tools on the purchase intentions of members of Generation Z (Gen Z) in online shopping, using an adapted technology acceptance model (TAM). It incorporates exposure to AI, usage of AI, and knowledge about AI, alongside the existing TAM parameters of perceived usefulness of AI (PUAI) and perceived ease-of-use of AI (PEUAI). A 38-item questionnaire was distributed, yielding data from 1128 Gen Z respondents. Partial least squares structural equation modeling (PLS-SEM) and importance–performance analysis (IPA) were applied to examine the hypothesized relationships. The study identified significant direct effects of exposure, use, and knowledge on PUAI and PEUAI, and that these effects affected consumers’ purchase intentions. Indirect effects analysis revealed that PUAI and PEUAI mediate between AI exposure, use, knowledge, and purchase intentions, suggesting that greater understanding of and familiarity with AI enhance the propensity to engage in AI-powered online transactions. The ease of integrating AI into daily life and perceived AI utility enhance purchase intentions. The study offers insights for online retailers leveraging AI technologies in an effort to enhance consumer purchase experiences, emphasizing the potential of AI to positively influence choices while enhancing trust, familiarity, and the overall user experience. Full article

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23 pages, 2853 KiB

Open AccessArticle

Unraveling the Influential Mechanisms of Smart Interactions on Stickiness Intention: A Privacy Calculus Perspective

by Jinyi He, Xinjian Liang and Jiaolong Xue

J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2582-2604; https://doi.org/10.3390/jtaer19040124 - 26 Sep 2024

Abstract

Artificial intelligence (AI) technologies are changing the ways of interaction between humans and machines, and smart interactions have become one of the hot topics of artificial intelligent in-home voice assistants (AVAs) by connecting humans, machines, content, and AVAs. Based on the privacy calculus [...] Read more.

Artificial intelligence (AI) technologies are changing the ways of interaction between humans and machines, and smart interactions have become one of the hot topics of artificial intelligent in-home voice assistants (AVAs) by connecting humans, machines, content, and AVAs. Based on the privacy calculus theory (PCT), the authors conducted an online questionnaire-based survey to investigate the influential mechanisms of smart interactions on stickiness intention (SI), demonstrated the positive (negative) effects of smart interactions on benefits and risks, and verified the moderating role of susceptibility to normative influence (SNI). The results show that smart interactions positively impact SI via utilitarian benefit and hedonic benefit; humanness has a U-shaped effect on privacy risk; personalization, connectivity, and linkage positively impact privacy risk; multimodal control negatively impacts privacy risk; and SNI positively moderates the effects of smart interactions on stickiness intention. The study enriched and expanded the literature on smart interactions in the context of AIoT and offered practical implications for AVA service providers and developers to design or optimize smart interactions for AI interactive services. By examining the double-edged sword effects of personalization and humanness, our findings offer novel insights into the privacy calculus in smart interactions. Full article

(This article belongs to the Topic Interactive Marketing in the Digital Era)

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Journal of Theoretical and Applied Electronic Commerce Research

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