JTAER, Vol. 18, Pages 1365-1403: Unveiling the Power of ARIMA, Support Vector and Random Forest Regressors for the Future of the Dutch Employment Market

JTAER, Vol. 18, Pages 1365-1403: Unveiling the Power of ARIMA, Support Vector and Random Forest Regressors for the Future of the Dutch Employment Market

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030069

Authors: Piotr Gajewski Boris Čule Nevena Rankovic

The increasing popularity of online job vacancies and machine learning methods has raised questions about their combination to enhance our understanding of labour markets and algorithms. However, the lack of comparable studies necessitates further investigation. This research aims to explore the effectiveness of Random Forest Regressor (RFR) and Support Vector Regressor (SVR) machine learning models in predicting online job vacancies compared to the auto-regressive ARIMA method. To answer this question, detailed sub-questions are posed in relation to the sub-samples of the main data provided by Birch Consultants, an external partner originally obtained by Jobdigger. Drawing upon previous research on time-series accuracy, this study combines various approaches to benefit society and the external partner. Using the walk-forward validation method, with a 91-day expanding window, it provides precise answers to the sub-questions. Findings suggest that RFR is suitable for forecasting larger samples, while SVR is preferred due to its capability to predict small series despite relatively small scoring benefits and computational costs. Both machine learning models outperform the baseline ARIMA model in capturing complex time-series. Further research should focus on exploring advanced auto-regressive, deep learning, and hybrid models for future investigations.

JTAER, Vol. 18, Pages 1320-1337: The Effect of Price Discrimination on Fairness Perception and Online Hotel Reservation Intention

JTAER, Vol. 18, Pages 1320-1337: The Effect of Price Discrimination on Fairness Perception and Online Hotel Reservation Intention

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030067

Authors: Yi-Fen Chen Tzu-Ting Pang Boedi Hartadi Kuslina

In light of the development of online travel agencies (OTAs), the rules of the entire tourism industry have changed. Due to the ease of finding information and comparing products, consumers can choose a hotel not only by room type, but also by rate, according to their preferences. The purpose of this study was to explore the effect of price discrimination on the fairness perception toward reservation intentions. The interaction effects of the brand familiarity and the type of consumers on the fairness perception were also examined. The study used an experimental design, with 2 price discriminations × 2 brand familiarities × 2 regulatory focuses, on a total of 320 valid subjects. The results showed that advantaged-price discriminations had higher fairness perceptions than equal-price discriminations, and that higher fairness perceptions had higher reservation intentions. The interaction effect of brand familiarity showed no significant impact on the fairness perceptions, while the regulatory focus had a mitigating effect on the price discrimination and on the fairness perceptions. This study provides insights into the relationship between online price discrimination and tourism, and it contributes to the literature on hospitality. It also provides the managerial implications for online hotels in developing pricing strategies.

JTAER, Vol. 18, Pages 1338-1364: A Review of the Lightning Network’s Evolution: Unraveling Its Present State and the Emergence of Disruptive Digital Business Models

JTAER, Vol. 18, Pages 1338-1364: A Review of the Lightning Network’s Evolution: Unraveling Its Present State and the Emergence of Disruptive Digital Business Models

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030068

Authors: Thomas K. Dasaklis Vangelis Malamas

The Lightning Network (LN), a second-layer protocol built on top of the Bitcoin blockchain, is an innovative digital payment solution that offers increased convenience, speed, and cost-effectiveness to consumers and businesses alike. However, there is limited literature available on the characteristics of this nascent technology, the depth and breadth of the various business LN-related applications as well as relevant adoption/implementation challenges. This study aims to contribute to the understanding of the LN’s characteristics, its potential in enhancing business operations and its applicability across different sectors, while taking into account adoption and implementation challenges. We apply a narrative review methodology using a semi-systematic approach to examine new and emerging business models empowered by the LN and its characteristics, topology, performance, privacy and security. We analyze the data to identify key themes and trends in the literature, offering a critical analysis of the strengths and weaknesses of the existing literature. Based on the findings, we provide several clusters of fruitful areas for future research directions. This study not only provides crucial insights for businesses contemplating the adoption of LN to improve their operations and customer experience, but it also represents a substantial academic contribution, offering valuable knowledge and fostering further research in the fields of blockchain technology, FinTech and cryptocurrencies.

JTAER, Vol. 18, Pages 1301-1319: Consumers’ Preferences for Digital Corporate Content on Company Websites: A Best–Worst Scaling Analysis

JTAER, Vol. 18, Pages 1301-1319: Consumers’ Preferences for Digital Corporate Content on Company Websites: A Best–Worst Scaling Analysis

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030066

Authors: Clemens Koob

Digital content marketing (DCM) complements traditional marketing communication approaches and is a major focus of research. Uses and gratifications research posits that DCM only unfolds positive effects if it provides valuable content to consumers. However, there is limited evidence on what constitutes gratifying digital corporate content on company websites. This study aimed to elicit consumers’ preferences for key characteristics of digital corporate content on company websites and whether preferences differ among consumer subgroups. Best–worst scaling (BWS) was used to reveal preferences. To obtain BWS data, a cross-sectional survey was employed. The study sample comprised 1527 consumers from Germany, Switzerland, and Austria. Data were analyzed using counting analysis and conditional logit modeling. Subgroup comparisons were performed with t-tests and one-way ANOVA. The results consistently show that consumers prioritize information value as the most important content characteristic, followed by value in use, entertainment value, process value, and social value. Subgroup comparisons revealed generally similar priorities among consumers, with the greatest heterogeneity being found in assessments of the importance of social value. The study also suggests that consumers prioritize digital corporate content characteristics on company websites differently than they do on social media. These findings contribute to the evolving literature on DCM and provide insights that could help set evidence-based priorities in DCM practice.

JTAER, Vol. 18, Pages 1283-1300: Social Commerce in Europe: A Literature Review and Implications for Researchers, Practitioners, and Policymakers

JTAER, Vol. 18, Pages 1283-1300: Social Commerce in Europe: A Literature Review and Implications for Researchers, Practitioners, and Policymakers

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030065

Authors: Alexandrina Maria Păuceanu Sebastian Văduva Amalia Cristina Nedelcuț

The COVID-19 pandemic has altered consumer behavior, making social commerce a viable alternative throughout the world. Europe is trailing the US and China in adopting this technology, but the prognosis is encouraging. Our goal is to contribute to this process by offering a literature review on social commerce in Europe for researchers, practitioners, and policymakers. We analyzed 4.764 articles published during the 2015–2023 period on the topic of social commerce in Europe utilizing the PRISMA flow diagram. After scrutinizing this large body of literature with various instruments including artificial intelligence (AI), we identified a final list of 45 articles that are most pertinent to our research questions. The emerging themes were that social media is shaping behavior and triggering buying intentions, that trust is paramount in buying impulses and behavior, and that success in social commerce is predicated upon relationships and engagement.

JTAER, Vol. 18, Pages 1238-1256: Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network

JTAER, Vol. 18, Pages 1238-1256: Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030063

Authors: Yunho Maeng Choong C. Lee Haejung Yun

Although the market for Head-Mounted Display Virtual Reality (HMD VR) devices has been growing along with the metaverse trend, the product has not been as widespread as initially expected. As each user has different purposes for use and prefers different features, various factors are expected to influence customer evaluations. Therefore, the present study aims to: (1) analyze customer reviews of hands-on HMD VR devices, provided with new user experience (UX), using text mining, and artificial neural network techniques; (2) comprehensively examine variables that affect user evaluations of VR devices; and (3) suggest major implications for the future development of VR devices. The research procedure consisted of four steps. First, customer reviews on HMD VR devices were collected from Amazon.com. Second, candidate variables were selected based on a literature review, and sentiment scores were extracted. Third, variables were determined through topic modeling, in-depth interviews, and a review of previous studies. Fourth, an artificial neural network analysis was performed by setting customer evaluation as a dependent variable, and the influence of each variable was checked through feature importance. The results indicate that feature importance can be derived from variables, and actionable implications can be identified, unlike in general sentiment analysis.

JTAER, Vol. 18, Pages 1257-1282: “Customer Reviews or Vlogger Reviews?” The Impact of Cross-Platform UGC on the Sales of Experiential Products on E-Commerce Platforms

JTAER, Vol. 18, Pages 1257-1282: “Customer Reviews or Vlogger Reviews?” The Impact of Cross-Platform UGC on the Sales of Experiential Products on E-Commerce Platforms

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030064

Authors: Yiwu Jia Haolin Feng Xin Wang Michelle Alvarado

User-generated content (UGC) from e-commerce platforms and third-party platforms can impact customer-perceived risk and influence product sales in online stores. However, the understanding of UGC from which platform type yields a stronger effect on product sales and how the effects interact across the platforms remains limited. This limitation arises from the complexity of consumer purchasing behavior and information processing, as well as the heterogeneity of UGC features across different platforms and the uncertainty surrounding causal relationships. This study constructs a novel cross-platform framework using the elaboration likelihood model (ELM) to investigate the underlying mechanism of how cross-platform UGC affects online sales of experiential products. Additionally, it examines the mediating effect of purchase intention in the relationship between cross-platform UGC and product sales, as well as the moderating effect of product price. Taking the e-commerce platform Tmall and third-party platform Bilibili as a cross-platform example, we analyzed customer reviews on Tmall and vlogger reviews on Bilibili for 300 cosmetic products, using text sentiment analysis and multiple regression. Results show that the number of product evaluations from third-party platforms positively impacts sales, but this impact is weaker compared to the influence of UGC originating from e-commerce platforms on sales. The underlying mechanism refers to the process by which UGC on an e-commerce platform directly impacts sales and also influences sales through purchase intention. In contrast, UGC on third-party platforms only influences sales through purchase intention. Furthermore, the product price has no significant moderating effect on the positive relationship between review length and sales. This study provides a cross-platform UGC research framework that can guide effective cross-platform marketing management by shedding light on the role of UGC in reducing customer-perceived risk and its impact on online sales of experiential products.

JTAER, Vol. 18, Pages 1217-1237: Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model

JTAER, Vol. 18, Pages 1217-1237: Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030062

Authors: Jorge de Andrés-Sánchez Jaume Gené-Albesa

Conversational robots powered by artificial intelligence (AI) are intensively implemented in the insurance industry. This paper aims to determine the current level of acceptance among consumers regarding the use of conversational robots for interacting with insurers and seeks to identify the factors that influence individuals’ behavioral intention to engage with chatbots. To explain behavioral intention, we tested a structural equation model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. It was supposed that behavioral intention is influenced by performance expectancy, effort expectancy, social influence, and trust, and by the moderating effect of insurance literacy on performance expectancy and effort expectancy. The study reveals a significant overall rejection of robotic technology among respondents. The technology acceptance model tested demonstrates a strong ability to fit the data, explaining nearly 70% of the variance in behavioral intention. Social influence emerges as the most influential variable in explaining the intention to use conversational robots. Furthermore, effort expectancy and trust significantly impact behavioral intention in a positive manner. For chatbots to gain acceptance as a technology, it is crucial to enhance their usability, establish trust, and increase social acceptance among users.

JTAER, Vol. 18, Pages 1177-1195: Pricing Game Models of Hybrid Channel Supply Chain: A Strategic Consumer Behavior Perspective

JTAER, Vol. 18, Pages 1177-1195: Pricing Game Models of Hybrid Channel Supply Chain: A Strategic Consumer Behavior Perspective

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030060

Authors: Xuelong Zhang Yufei Li Jianhua Zhu Xuequan Zhou

The current sales model combining online and offline channels meets the diverse requirements of consumers. However, consumers’ inter-channel switching behavior and strategic behavior also pose significant challenges to pricing decisions in the hybrid channel. Using game theory and consumer utility theory, a retailer-driven pricing model is developed to study the optimal pricing problem for each channel in a mixed-channel supply chain considering the characteristics of channel competition and the waiting behavior of strategic consumers. Study results show there is a negative correlation between the proportion of strategic consumers and the optimal pricing and profit of each channel, and as the proportion of strategic consumers rises, the optimal pricing and profit of manufacturers and retailers all trend downward. Incorporating strategic consumers into the pricing model will assist the supply chain in elucidating the behavior of consumer heterogeneity during various decision-making periods and in making reasonable pricing decisions. Effective guiding strategies, such as pre-discount and purchase restrictions, can reduce the profit loss caused by strategic consumer behavior. The optimal combination of pre-announcement discount and strategic consumer ratio can generate the greatest profit for retailers and the supply chain.

JTAER, Vol. 18, Pages 1196-1216: How Streamers Foster Consumer Stickiness in Live Streaming Sales

JTAER, Vol. 18, Pages 1196-1216: How Streamers Foster Consumer Stickiness in Live Streaming Sales

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030061

Authors: Yongbing Jiao Emine Sarigöllü Liguo Lou Baotao Huang

Streamers play a critical role in fostering consumer stickiness in live streaming sales. Thus, it is necessary to make clear the mechanism of how streamers influence consumer stickiness. Based upon the theories of social support, social identification and consumer stickiness, this study investigates the effects of consumers’ perceived emotional support, informational support, financial support, affectionate support and social network support from streamers on consumer–streamer identification, which in turn affects consumer–streamer stickiness and consumer–brand stickiness in live streaming sales settings. Based on the structural equation modeling analysis of 280 online questionnaires, using the software of Smart PLS 3.0, the results demonstrate that perceived emotional support, perceived informational support, perceived financial support and perceived affectionate support enhance consumer–streamer identification, thereby enhancing consumer–streamer stickiness and consumer–brand stickiness, and thus, consumer–streamer stickiness also enhances consumer–brand stickiness. This study not only extends the theories of live streaming sales, but also provides practical implications for enterprises’ improving consumer–streamer stickiness and consumer–brand stickiness in live streaming sales.