Journal Description
Journal of Theoretical and Applied Electronic Commerce Research
Journal of Theoretical and Applied Electronic Commerce Research
published since 2006, is an international, peer-reviewed, scientific journal owned by the Faculty of Engineering of the Universidad de Talca, and MDPI provides publishing services for the journal since Volume 16, Issue 3 (2021).
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SSCI (Web of Science), dblp, and other databases.
- Journal Rank: JCR - Q2 (Business) / CiteScore - Q1 (General Business, Management and Accounting)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 22.6 days after submission; acceptance to publication is undertaken in 3.9 days (median values for papers published in this journal in the first half of 2023).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Impact Factor:
5.6 (2022);
5-Year Impact Factor:
5.4 (2022)
Latest Articles
Unveiling the Power of ARIMA, Support Vector and Random Forest Regressors for the Future of the Dutch Employment Market
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1365-1403; https://doi.org/10.3390/jtaer18030069 - 08 Aug 2023
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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
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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.
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Open AccessArticle
A Review of the Lightning Network’s Evolution: Unraveling Its Present State and the Emergence of Disruptive Digital Business Models
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1338-1364; https://doi.org/10.3390/jtaer18030068 - 01 Aug 2023
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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
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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.
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The Effect of Price Discrimination on Fairness Perception and Online Hotel Reservation Intention
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1320-1337; https://doi.org/10.3390/jtaer18030067 - 01 Aug 2023
Abstract
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,
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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.
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(This article belongs to the Section Digital Marketing and the Connected Consumer)
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Consumers’ Preferences for Digital Corporate Content on Company Websites: A Best–Worst Scaling Analysis
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J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1301-1319; https://doi.org/10.3390/jtaer18030066 - 25 Jul 2023
Abstract
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
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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.
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(This article belongs to the Section Digital Marketing and the Connected Consumer)
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Social Commerce in Europe: A Literature Review and Implications for Researchers, Practitioners, and Policymakers
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1283-1300; https://doi.org/10.3390/jtaer18030065 - 20 Jul 2023
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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
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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.
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(This article belongs to the Special Issue Social Commerce and the Recent Changes)
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“Customer Reviews or Vlogger Reviews?” The Impact of Cross-Platform UGC on the Sales of Experiential Products on E-Commerce Platforms
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1257-1282; https://doi.org/10.3390/jtaer18030064 - 10 Jul 2023
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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
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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.
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Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1238-1256; https://doi.org/10.3390/jtaer18030063 - 10 Jul 2023
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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
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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.
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(This article belongs to the Special Issue Social Commerce and the Recent Changes)
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Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1217-1237; https://doi.org/10.3390/jtaer18030062 - 07 Jul 2023
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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
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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.
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(This article belongs to the Topic Artificial Intelligence Applications in Financial Technology)
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How Streamers Foster Consumer Stickiness in Live Streaming Sales
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1196-1216; https://doi.org/10.3390/jtaer18030061 - 06 Jul 2023
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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
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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.
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(This article belongs to the Collection The New Era of Digital Marketing)
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Pricing Game Models of Hybrid Channel Supply Chain: A Strategic Consumer Behavior Perspective
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1177-1195; https://doi.org/10.3390/jtaer18030060 - 06 Jul 2023
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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
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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.
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Strata Fee Management in Condominiums via Smart Contracts
J. Theor. Appl. Electron. Commer. Res. 2023, 18(3), 1157-1176; https://doi.org/10.3390/jtaer18030059 - 04 Jul 2023
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Condominiums and similar properties use a stratum to manage daily operations, and owners fund it through strata fees. While existing strata fee management systems may be able to handle such funds, such systems could be more inherently transparent. It is possible to leverage
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Condominiums and similar properties use a stratum to manage daily operations, and owners fund it through strata fees. While existing strata fee management systems may be able to handle such funds, such systems could be more inherently transparent. It is possible to leverage the digital ledger from blockchain networks and smart contracts to build a fully transparent strata fee management system. This paper proposes designing a strata fee management system based on a smart contract in the Ethereum network. Both strata corporations and homeowners can interact with the smart contract to execute common procedures such as paying strata fees and handling expenses. Using smart contracts for strata fee management, it is believed that the chance of fraud by strata corporations is lowered compared to other systems.
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Fear of COVID-19 Effect on Stock Markets: A Proposal for an Algorithmic Trading System Based on Fear
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1142-1156; https://doi.org/10.3390/jtaer18020058 - 12 Jun 2023
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This study analyzes the fear of COVID-19 effect on European stock market returns. For this purpose, the search volumes (SV) collected by Google Trends (GT) and Wikipedia were used as proxies of fear of COVID-19. In a sample from 13 European stock markets,
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This study analyzes the fear of COVID-19 effect on European stock market returns. For this purpose, the search volumes (SV) collected by Google Trends (GT) and Wikipedia were used as proxies of fear of COVID-19. In a sample from 13 European stock markets, fear of COVID-19 was found to be associated with negative European stock returns. Our research employed this observation to propose an algorithmic trading system based on fear of COVID-19. Back-testing results show the possibility of extraordinary returns based on this system. These findings have important implications for political authorities, the mass media, and investors.
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(This article belongs to the Section Entrepreneurship, Innovation, FinTech Accounting and Industry 4.0)
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A Multi-Criteria Group Decision-Making Method for Risk Assessment of Live-Streaming E-Commerce Platform
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1126-1141; https://doi.org/10.3390/jtaer18020057 - 12 Jun 2023
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Live-streaming e-commerce is the future development direction of the retail industry. When retailers choose a live-streaming e-commerce platform, they face the test of various risks of the platform, such as insecure control of capital flow, insufficient support of public domain traffic, etc. Therefore,
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Live-streaming e-commerce is the future development direction of the retail industry. When retailers choose a live-streaming e-commerce platform, they face the test of various risks of the platform, such as insecure control of capital flow, insufficient support of public domain traffic, etc. Therefore, it is necessary to evaluate the risks of the platform to help retailers identify the platform with the lowest risk. Considering the complexity of the risks of live-streaming e-commerce platforms and the ambiguity of the decision-makers thinking, the current method for multi-criteria group decision-making (MCGDM) method in a fuzzy environment rarely discusses the decision-makers weight for the criterion. This paper proposes interval-valued intuitionistic fuzzy multi-criteria group decision-making based on the decision-makers’ professionalism to evaluate the platform’s risks. This method determines the decision-maker’s weight for the criterion based on the professionalism of the decision-maker and uses the technique for order preference by similarity to an ideal solution (TOPSIS) method to rank the alternative platforms. Finally, a risk assessment of the agricultural product live-streaming e-commerce platforms is used as a case study to demonstrate the feasibility and effectiveness of the proposed method. This research will not only provide practical guidance for retailers to choose the live-streaming e-commerce platform with the lowest comprehensive risk but also provide ideas for the research of live-streaming e-commerce from the perspective of risk assessment.
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(This article belongs to the Collection Utilizing Models for e-Business Decision-Making: From Data to Wisdom)
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What Drives VOD Purchases in Mobile TV Services? Exploring Utilization, Motivations, and Personality Traits
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1107-1125; https://doi.org/10.3390/jtaer18020056 - 12 Jun 2023
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Mobile streaming is increasingly viewed as a major advancement in the wireless industry, as it enables users to consume content without any time or space restrictions. Mobile TV serves as an excellent example of streaming, providing services for watching TV content on mobile
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Mobile streaming is increasingly viewed as a major advancement in the wireless industry, as it enables users to consume content without any time or space restrictions. Mobile TV serves as an excellent example of streaming, providing services for watching TV content on mobile devices. While previous studies have explored video-on-demand (VOD) purchasing factors in mobile TV, it is rare to find research examining differences based on users’ mobile TV usage types, such as subscribers and free users. Consequently, we investigated VOD purchase factors for 310 subscribers and 311 free mobile TV users. In other words, using 621 survey responses, we analyze the influence of personality traits, intrinsic and extrinsic motivations, and mobile-related factors on users’ VOD purchase intentions and behavior. Our findings indicate that mobile TV utilization, hedonic needs, and subjective norms are positively related to VOD purchases, and that neuroticism, extraversion, openness, and conscientiousness positively impact mobile TV utilization. We also examine the relationships between the constructs within two sub-groups to highlight the differing perceptions and behavioral patterns of these groups regarding mobile TV utilization and VOD purchases. Theoretical and practical implications are discussed as well.
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(This article belongs to the Section Digital Marketing and the Connected Consumer)
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Optimal Recommendation Strategies for AI-Powered E-Commerce Platforms: A Study of Duopoly Manufacturers and Market Competition
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1086-1106; https://doi.org/10.3390/jtaer18020055 - 07 Jun 2023
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Artificial intelligence-powered recommendation systems have gained popularity as a tool to enhance user experience and boost sales. Platforms often need to make decisions about which seller to recommend and the strength of the recommendation when conducting recommendations. Therefore, it is necessary to explore
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Artificial intelligence-powered recommendation systems have gained popularity as a tool to enhance user experience and boost sales. Platforms often need to make decisions about which seller to recommend and the strength of the recommendation when conducting recommendations. Therefore, it is necessary to explore the recommendation strategy of the platform in the case of duopoly competition. We develop a game model where two competing manufacturers sell products through an agency contract on a common platform, and they can decide whether or not to provide recommendations to the manufacturers. Our highlight lies in the endogenous recommendation strength of the platform. The findings suggest that it is optimal for the platform to offer recommendation services when the commission rate is high. The platform also prefers to only recommend one manufacturer in the market with low or high competition, but it prefers to recommend both manufacturers in moderately competitive markets. From the view of manufacturers, they can benefit from the recommendation service as long as the commission rate is not too low. Moreover, recommending only one manufacturer consistently yields stronger recommendations compared to recommending multiple manufacturers. However, the impact of recommendation on prices is influenced by the commission rate and product substitutability. These results have significant implications for platform decision making and provide valuable insights into the trade-offs involved in the development of recommendation systems.
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(This article belongs to the Collection Advances in Supply Chain Management in the Era of Electronic Commerce)
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From Fake Reviews to Fake News: A Novel Pandemic Model of Misinformation in Digital Networks
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1069-1085; https://doi.org/10.3390/jtaer18020054 - 04 Jun 2023
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Digital networks and E-commerce platforms have had a profound effect on people’s personal, educational, and professional life all around the world. They offer space for advertising, sales, and disseminating news and information, even if they are frequently used for social marketing, interacting, and
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Digital networks and E-commerce platforms have had a profound effect on people’s personal, educational, and professional life all around the world. They offer space for advertising, sales, and disseminating news and information, even if they are frequently used for social marketing, interacting, and sharing thoughts among people. Currently, most E-commerce platforms utilize digital network space for advertisement and an increasing trend of social commerce is visible in all parts of the world. During the Post-COVID-19 pandemic, a rapid increase in digital media and E-commerce usage was observed in all parts of the world for personal and professional aspects. The increase in misinformation through these platforms is a major challenge that the current governments face today as rumors and fake news creates severe detrimental implications in society. In this work, we consider fake reviews and misinformation in online digital networks as a single disease, and thereby, by considering the recent trends in online social media marketing, we formulate a pandemic model for digital networks with a psychological state of human choice. The positivity and stability of the model are mathematically tested and validated. Our analysis and simulation prove that the system is stable and justifiable in the real-world digital environment. The generated pandemic model can be applied to assess the social and emotional intelligence of communities and consumers who are frequently exposed to misinformation and share fake news.
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Pricing Decisions and Coordination in E-Commerce Supply Chain with Wholesale Price Contract Considering Focus Preferences
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1041-1068; https://doi.org/10.3390/jtaer18020053 - 03 Jun 2023
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Decision makers’ behavioral preferences have always been important in coordinating the supply chain. Decision makers need to choose a partner wisely to increase the profitability of the entire supply chain, especially in the competitive e-commerce environment. In this paper, we examine a two-echelon
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Decision makers’ behavioral preferences have always been important in coordinating the supply chain. Decision makers need to choose a partner wisely to increase the profitability of the entire supply chain, especially in the competitive e-commerce environment. In this paper, we examine a two-echelon e-commerce supply chain with one retailer and one supplier using the most popular wholesale price contract to facilitate collaboration. Traditional research has shown that the classical expectation model cannot coordinate the supply chain. We apply the focus theory of choice to describe the retailer’s behavior as a follower, and we examine the impact of the retailer’s pricing decisions on the supplier under different focus preferences and the coordination for the entire supply chain. The lower the parameter φ, which represents the degree of positivity, and the higher the parameter κ, which represents the level of confidence, the closer the profit of the whole supply chain is to the coordination result—both are visualized through numerical experiments and images. In the case of φ determination, the lower the κ, the better the supply chain coordination. The finding implies that the retailer may be able to coordinate the supply chain and produce better results than the expectation model when he or she makes choices using a positive evaluation system that includes both higher levels of optimism and lower levels of confidence. The findings of the FTC model can simultaneously offer a theoretical foundation for expanding collaboration among supply chain participants and management insights for decision makers to choose cooperation partners.
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Open AccessArticle
A Luxury Tourist Destination in Housing for Tourist Purposes: A Study of the New Airbnb Luxe Platform in the Case of Marbella
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 1020-1040; https://doi.org/10.3390/jtaer18020052 - 19 May 2023
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Marbella has a wide range of luxury property rentals, which are the subject of study within the framework of the collaborative economy, where the Airbnb platform stands out as the most used channel. This research focuses on the analysis of the total number
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Marbella has a wide range of luxury property rentals, which are the subject of study within the framework of the collaborative economy, where the Airbnb platform stands out as the most used channel. This research focuses on the analysis of the total number of luxury villas offered in Marbella by Airbnb Luxe and Luxury Retreats. The methodology was carried out in four phases: the first phase involved a review of the literature on tourism and luxury and a study of Marbella as a luxury destination. The second phase focused on the analysis of the types of accommodation that Marbella offers. The third phase focused on the collection of data from the analyzed platform: Airbnb Luxe and Luxury Retreats. Finally, qualitative research consisting of in-depth interviews with owners and real estate agents focused on the luxury sector in Marbella was carried out. The results obtained yield relevant conclusions: Marbella is one of the main luxury holiday destinations in Spain, and the most demanded type of luxe accommodation in Marbella is large luxury villas. The term ‘luxury’ can be subjective, referring to such things as the visible and non-visible aspects that determine the category of a luxury property, hence the need to carry out a study on the luxury segment to establish a precise definition.
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Open AccessReview
Chatbots and Voice Assistants: Digital Transformers of the Company–Customer Interface—A Systematic Review of the Business Research Literature
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J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 995-1019; https://doi.org/10.3390/jtaer18020051 - 18 May 2023
Abstract
Chatbots and voice assistants are digital transformers of the interface between companies and customers. They have become part of the current practice of companies and represent a distinct domain of business research. This trend is significant in the broad business context marked by
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Chatbots and voice assistants are digital transformers of the interface between companies and customers. They have become part of the current practice of companies and represent a distinct domain of business research. This trend is significant in the broad business context marked by the digital transformation of companies, the fast development of e-commerce and the omnichannel behavior of customers. This article is a systematic review of the high-quality business research literature on chatbots and voice assistants. The purpose of this review is to critically analyze the current status of this literature from the perspective of the theories, contexts, characteristics and methodologies applied. The final aim of this review is to support the domain of study by suggesting a relevant agenda for future research. This review brings several contributions to the research domain, including the following: the identification of the main streams of high-quality business research in function of the theories in which the studies are grounded; the development of a conceptual framework of the investigated variables (antecedents, mediators, moderators and consequences); the creation of a conceptual framework of the humanlikeness of chatbots and voice assistants; the development of a conceptual framework of the consumer experience with chatbots and voice assistants and the presentation of insights for business practice.
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(This article belongs to the Special Issue Digital Resilience and Economic Intelligence in the Post-Pandemic Era)
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The Return of the King: The Importance of Killer Content in a Competitive OTT Market
by
and
J. Theor. Appl. Electron. Commer. Res. 2023, 18(2), 976-994; https://doi.org/10.3390/jtaer18020050 - 17 May 2023
Abstract
As the over-the-top (OTT) service market continues to evolve, with new large global players entering the already crowded market, competition between various OTT services for subscribers has intensified. In this study, we aim to investigate the impact of user preference content on the
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As the over-the-top (OTT) service market continues to evolve, with new large global players entering the already crowded market, competition between various OTT services for subscribers has intensified. In this study, we aim to investigate the impact of user preference content on the selection of specific OTT services by consumers. Specifically, we employ the conjoint experiment (CE) method to examine consumer utility, relative importance, and marginal willingness to pay (MWTP) for over-the-top (OTT) subscription service attributes. Especially, the presence of users’ killer content and its impact on MWTP is the focus of our study. As a result of calculating the MWTP for each attribute, we found that users are willing to pay about 7633 KRW (5.8 USD) for the first-ranked killer content in their first preferred genre. To gain a deeper understanding of users’ willingness to pay for OTT services, we further analyzed the data by age group and the number of OTT services in use. Based on the results, we suggest strategic plans for local OTT operators to compete effectively in the fiercely competitive OTT market.
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