Jacob Hornik, Chezy Ofir, Matti Rachamim, Sergei Graguer
The latest effort in delivering computing resources as a service to managers and consumers represents a shift away from computing as a product that is purchased, to computing as a service that is delivered to users over the internet from large-scale data centers. However, with the advent of the cloud-based IoT and artificial intelligence (AI), which are advancing customer experience automations in many application areas, such as recommender systems (RS), a need has arisen for various modifications to support the IoT devices that are at the center of the automation world, including recent language models like ChatGPT and Bard and technologies like nanotechnology. This paper introduces the marketing community to a recent computing development: IoT-driven fog computing (FC). Although numerous research studies have been published on FC “smart” applications, none hitherto have been conducted on fog-based smart marketing domains such as recommender systems. FC is considered a novel computational system, which can mitigate latency and improve bandwidth utilization for autonomous consumer behavior applications requiring real-time data-driven decision making. This paper provides a conceptual framework for studying the effects of fog computing on consumer behavior, with the goal of stimulating future research by using, as an example, the intersection of FC and RS. Indeed, our conceptualization of the “fog-based recommender systems” opens many novel and challenging avenues for academic research, some of which are highlighted in the later part of this paper.
{"title":"Fog Computing-Based Smart Consumer Recommender Systems","authors":"Jacob Hornik, Chezy Ofir, Matti Rachamim, Sergei Graguer","doi":"10.3390/jtaer19010032","DOIUrl":"https://doi.org/10.3390/jtaer19010032","url":null,"abstract":"The latest effort in delivering computing resources as a service to managers and consumers represents a shift away from computing as a product that is purchased, to computing as a service that is delivered to users over the internet from large-scale data centers. However, with the advent of the cloud-based IoT and artificial intelligence (AI), which are advancing customer experience automations in many application areas, such as recommender systems (RS), a need has arisen for various modifications to support the IoT devices that are at the center of the automation world, including recent language models like ChatGPT and Bard and technologies like nanotechnology. This paper introduces the marketing community to a recent computing development: IoT-driven fog computing (FC). Although numerous research studies have been published on FC “smart” applications, none hitherto have been conducted on fog-based smart marketing domains such as recommender systems. FC is considered a novel computational system, which can mitigate latency and improve bandwidth utilization for autonomous consumer behavior applications requiring real-time data-driven decision making. This paper provides a conceptual framework for studying the effects of fog computing on consumer behavior, with the goal of stimulating future research by using, as an example, the intersection of FC and RS. Indeed, our conceptualization of the “fog-based recommender systems” opens many novel and challenging avenues for academic research, some of which are highlighted in the later part of this paper.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"13 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140107503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Consumers’ personality traits significantly influence their perceptions regarding social media advertising. While prior research on consumers’ purchasing intentions in social networking sites advertising has mainly focused on advertising valence antecedents, it is crucial to recognize that consumers’ susceptibility to advertising persuasion, particularly in terms of empathic expression, varies based on a key criterion: whether consumers are driven to attain a specific desired state or are more inclined to avoid an undesirable state. Regulatory Focus Theory (RFT) posits that individuals operate under distinct motivational mechanisms that govern their determination to achieve desired goals, influencing how they process and evaluate advertising messages. In light of RFT, we conducted an online survey with 524 valid responses, utilizing partial least squares (PLS) for research model analysis. The findings revealed that promotion-focused individuals have positively influenced perceptions of social media ad effectiveness (informativeness, ad creativity, perceived relevance, and emotional appeal). In contrast, prevention-focused individuals negatively perceived social media ad effectiveness. Furthermore, this study highlighted that perceived relevance and emotional appeal have a more significant impact on attitudes toward expressing empathy than informativeness and ad creativity.
{"title":"How Personality Traits Affect Customer Empathy Expression of Social Media Ads and Purchasing Intention: A Psychological Perspective","authors":"Serhan Demirci, Chia-Ju Ling, Dai-Rong Lee, Chien-Wen Chen","doi":"10.3390/jtaer19010031","DOIUrl":"https://doi.org/10.3390/jtaer19010031","url":null,"abstract":"Consumers’ personality traits significantly influence their perceptions regarding social media advertising. While prior research on consumers’ purchasing intentions in social networking sites advertising has mainly focused on advertising valence antecedents, it is crucial to recognize that consumers’ susceptibility to advertising persuasion, particularly in terms of empathic expression, varies based on a key criterion: whether consumers are driven to attain a specific desired state or are more inclined to avoid an undesirable state. Regulatory Focus Theory (RFT) posits that individuals operate under distinct motivational mechanisms that govern their determination to achieve desired goals, influencing how they process and evaluate advertising messages. In light of RFT, we conducted an online survey with 524 valid responses, utilizing partial least squares (PLS) for research model analysis. The findings revealed that promotion-focused individuals have positively influenced perceptions of social media ad effectiveness (informativeness, ad creativity, perceived relevance, and emotional appeal). In contrast, prevention-focused individuals negatively perceived social media ad effectiveness. Furthermore, this study highlighted that perceived relevance and emotional appeal have a more significant impact on attitudes toward expressing empathy than informativeness and ad creativity.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"96 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140072800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since 2012, researchers have explored various factors influencing Bitcoin prices. Up until the end of July 2023, more than 9100 research papers on cryptocurrencies were published and indexed in the Web of Science Clarivate platform. The objective of this paper is to analyze the impact of publications on Bitcoin prices. This study aims to uncover significant themes within these research articles, focusing on cryptocurrencies in general and Bitcoin specifically. The research employs latent Dirichlet allocation to identify key topics from the unstructured abstracts. To determine the optimal number of topics, perplexity and topic coherence metrics are calculated. Additionally, the abstracts are processed using BERT-transformers and Word2Vec and their potential to predict Bitcoin prices is assessed. Based on the results, while the research helps in understanding cryptocurrencies, the potential of academic publications to influence Bitcoin prices is not significant, demonstrating a weak connection. In other words, the movements of Bitcoin prices are not influenced by the scientific writing in this specific field. The primary topics emerging from the analysis are the blockchain, market dynamics, transactions, pricing trends, network security, and the mining process. These findings suggest that future research should pay closer attention to issues like the energy demands and environmental impacts of mining, anti-money laundering measures, and behavioral aspects related to cryptocurrencies.
{"title":"The Impact of Academic Publications over the Last Decade on Historical Bitcoin Prices Using Generative Models","authors":"Adela Bâra, Simona-Vasilica Oprea","doi":"10.3390/jtaer19010029","DOIUrl":"https://doi.org/10.3390/jtaer19010029","url":null,"abstract":"Since 2012, researchers have explored various factors influencing Bitcoin prices. Up until the end of July 2023, more than 9100 research papers on cryptocurrencies were published and indexed in the Web of Science Clarivate platform. The objective of this paper is to analyze the impact of publications on Bitcoin prices. This study aims to uncover significant themes within these research articles, focusing on cryptocurrencies in general and Bitcoin specifically. The research employs latent Dirichlet allocation to identify key topics from the unstructured abstracts. To determine the optimal number of topics, perplexity and topic coherence metrics are calculated. Additionally, the abstracts are processed using BERT-transformers and Word2Vec and their potential to predict Bitcoin prices is assessed. Based on the results, while the research helps in understanding cryptocurrencies, the potential of academic publications to influence Bitcoin prices is not significant, demonstrating a weak connection. In other words, the movements of Bitcoin prices are not influenced by the scientific writing in this specific field. The primary topics emerging from the analysis are the blockchain, market dynamics, transactions, pricing trends, network security, and the mining process. These findings suggest that future research should pay closer attention to issues like the energy demands and environmental impacts of mining, anti-money laundering measures, and behavioral aspects related to cryptocurrencies.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"142 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The emergence of the crowdsourcing platform enables seekers to obtain higher-quality services at lower costs. High-quality services are often provided by high-quality solvers, which is the key to the sustainable development of crowdsourcing platforms. Therefore, how to attract more high-quality solvers to participate needs to be focused on. Most previous studies that used stock data to measure crowdsourcing performance failed to describe the contest process of high-quality solvers’ behavior. Different from the previous study, this paper explores the information signals that influence the participation of high-quality solvers in the dynamic process of crowdsourcing contests. Based on the creative projects of the Winvk platform, dynamic models affecting the participation of high-quality solvers are constructed from the perspective of reducing information asymmetry, and the effects of quality signals and intention signals are explored in depth. The results show that for logo design projects, clear information display and monetary mechanisms have a significant impact on alleviating information asymmetry and attracting the participation of high-quality solvers. Interestingly, the effect of market competition on high-quality solvers shows a U-shaped change. The research results provide a reference for enterprises to reduce information asymmetry, obtain high-quality solutions, and enrich the theoretical application in the field of crowdsourcing.
众包平台的出现使寻求者能够以更低的成本获得更高质量的服务。高质量的服务往往由高质量的解决者提供，这是众包平台可持续发展的关键。因此，如何吸引更多高质量的解题者参与进来需要重点关注。以往使用存量数据衡量众包绩效的研究大多未能描述高质量解题者行为的竞赛过程。与以往研究不同，本文探讨了影响高质量解题者参与众包竞赛动态过程的信息信号。基于 Winvk 平台的创意项目，从减少信息不对称的角度构建了影响高质量解题者参与的动态模型，并深入探讨了质量信号和意向信号的影响。结果表明，对于徽标设计项目而言，清晰的信息展示和货币机制对缓解信息不对称、吸引高质量解题者参与有显著影响。有趣的是，市场竞争对高质量解决者的影响呈现出 U 型变化。研究成果为企业减少信息不对称、获得高质量解决方案提供了参考，也丰富了众包领域的理论应用。
{"title":"Do Dynamic Signals Affect High-Quality Solvers’ Participation Behavior? Evidence from the Crowdsourcing Platform","authors":"Xue Liu, Xiaoling Hao","doi":"10.3390/jtaer19010030","DOIUrl":"https://doi.org/10.3390/jtaer19010030","url":null,"abstract":"The emergence of the crowdsourcing platform enables seekers to obtain higher-quality services at lower costs. High-quality services are often provided by high-quality solvers, which is the key to the sustainable development of crowdsourcing platforms. Therefore, how to attract more high-quality solvers to participate needs to be focused on. Most previous studies that used stock data to measure crowdsourcing performance failed to describe the contest process of high-quality solvers’ behavior. Different from the previous study, this paper explores the information signals that influence the participation of high-quality solvers in the dynamic process of crowdsourcing contests. Based on the creative projects of the Winvk platform, dynamic models affecting the participation of high-quality solvers are constructed from the perspective of reducing information asymmetry, and the effects of quality signals and intention signals are explored in depth. The results show that for logo design projects, clear information display and monetary mechanisms have a significant impact on alleviating information asymmetry and attracting the participation of high-quality solvers. Interestingly, the effect of market competition on high-quality solvers shows a U-shaped change. The research results provide a reference for enterprises to reduce information asymmetry, obtain high-quality solutions, and enrich the theoretical application in the field of crowdsourcing.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"29 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
John Magnus Roos, Magnus Jansson, Pernilla J. Bjerkeli
The present study aimed to explore the online shopping of medicines from demographic, geographic, psychographic, and behavioral factors. A quantitative survey design was used with a quote sample representing the Swedish population regarding age, gender, and residential area. In total, 1863 persons responded to a survey, including measures of age, gender, income, education, area of residence, personality traits (BFI-10), values (Rokeach Value Survey), self-estimated health-status, internet usage, online shopping in general, and online shopping of medicines. Firstly, the data were analyzed with chi-squares and independent t-tests. From these initial analyses, online shopping of medicines was associated with young age, female gender, high income and education, living in a big city, extraversion, several values of desirable end-states of existence (e.g., self-respect, a sense of accomplishment, and pleasure), internet usage, and general online shopping. Secondly, the significant (p < 0.05) variables from the initial analysis were included in a logistic regression analysis. This comprehensive model showed that online medication shoppers are best predicted by being female and the use of internet. Unlike what was previously known about medication shoppers, the typical online medication shopper appears to be driven by hedonistic values and self-actualization, rather than health status. We suggest that further research replicate this study outside and inside Sweden, and that health status is measured in a different way.
本研究旨在从人口、地理、心理和行为因素等方面探讨网上购药问题。研究采用了定量调查设计，引用了代表瑞典人口年龄、性别和居住地区的样本。共有 1863 人参与了调查，调查内容包括年龄、性别、收入、教育程度、居住地区、个性特征（BFI-10）、价值观（Rokeach 价值观调查）、自我估计的健康状况、互联网使用情况、网购总体情况以及网购药品情况。首先，对数据进行了卡方检验和独立 t 检验。初步分析结果显示，网购药品与年轻、女性、高收入和高学历、居住在大城市、外向型性格、几种理想生存状态的价值观（如自尊、成就感和愉悦感）、互联网使用情况和一般网购有关。其次，将初步分析中的重要变量（p < 0.05）纳入逻辑回归分析。这一综合模型显示，女性和互联网的使用最能预测网上购药者。与之前对药物购物者的了解不同，典型的网上药物购物者似乎是受享乐主义价值观和自我实现的驱动，而不是受健康状况的驱动。我们建议在瑞典国内外开展进一步的研究，并以不同的方式衡量健康状况。
{"title":"Who Are the Online Medication Shoppers? A Market Segmentation of the Swedish Welfare State","authors":"John Magnus Roos, Magnus Jansson, Pernilla J. Bjerkeli","doi":"10.3390/jtaer19010028","DOIUrl":"https://doi.org/10.3390/jtaer19010028","url":null,"abstract":"The present study aimed to explore the online shopping of medicines from demographic, geographic, psychographic, and behavioral factors. A quantitative survey design was used with a quote sample representing the Swedish population regarding age, gender, and residential area. In total, 1863 persons responded to a survey, including measures of age, gender, income, education, area of residence, personality traits (BFI-10), values (Rokeach Value Survey), self-estimated health-status, internet usage, online shopping in general, and online shopping of medicines. Firstly, the data were analyzed with chi-squares and independent t-tests. From these initial analyses, online shopping of medicines was associated with young age, female gender, high income and education, living in a big city, extraversion, several values of desirable end-states of existence (e.g., self-respect, a sense of accomplishment, and pleasure), internet usage, and general online shopping. Secondly, the significant (p < 0.05) variables from the initial analysis were included in a logistic regression analysis. This comprehensive model showed that online medication shoppers are best predicted by being female and the use of internet. Unlike what was previously known about medication shoppers, the typical online medication shopper appears to be driven by hedonistic values and self-actualization, rather than health status. We suggest that further research replicate this study outside and inside Sweden, and that health status is measured in a different way.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"21 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andreea Raluca Duguleană, Cristina Roxana Tănăsescu, Mihai Duguleană
This research aims to establish the primary drivers influencing the development and consumers’ decision-making process in web3 games—decentralized games that function according to the play-to-earn paradigm. We observe several types of micro-economies developed within five play-to-earn games and highlight four roles consumers play at any given time. Our study offers a different perspective on rational consumer behaviour in cryptocurrency-based games and paves the way to better understanding their dynamics and evolution. Results shed light on the construction of in-game economies and how individuals of a given type engage in different playing activities. Furthermore, we compare the key features of web3 games with those similar to classic online games and assess if the play-and-earn implementations represent an evolution from previous revenue models. Using our proposed methodology, researchers can compare and classify any P2E games. We conclude by establishing a set of actions that enable consumers to benefit from this new phenomenon.
{"title":"Emerging Trends in Play-to-Earn (P2E) Games","authors":"Andreea Raluca Duguleană, Cristina Roxana Tănăsescu, Mihai Duguleană","doi":"10.3390/jtaer19010026","DOIUrl":"https://doi.org/10.3390/jtaer19010026","url":null,"abstract":"This research aims to establish the primary drivers influencing the development and consumers’ decision-making process in web3 games—decentralized games that function according to the play-to-earn paradigm. We observe several types of micro-economies developed within five play-to-earn games and highlight four roles consumers play at any given time. Our study offers a different perspective on rational consumer behaviour in cryptocurrency-based games and paves the way to better understanding their dynamics and evolution. Results shed light on the construction of in-game economies and how individuals of a given type engage in different playing activities. Furthermore, we compare the key features of web3 games with those similar to classic online games and assess if the play-and-earn implementations represent an evolution from previous revenue models. Using our proposed methodology, researchers can compare and classify any P2E games. We conclude by establishing a set of actions that enable consumers to benefit from this new phenomenon.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"18 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140018562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sahiba Khan, Ranjit Singh, H. Kent Baker, Gomtesh Jain
This study examines significant topics and customer sentiments conveyed in reviews of P2P lending applications (apps) in India by employing topic modeling and sentiment analysis. The apps considered are LenDenClub, Faircent, i2ifunding, India Money Mart, and Lendbox. Using Latent Dirichlet Allocation, we identified and labeled 11 topics: application, document, default, login, reject, service, CIBIL, OTP, returns, interface, and withdrawal. The sentiment analysis tool VADER revealed that most users have positive attitudes toward these apps. We also compared the five apps overall and on specific topics. Overall, LenDenClub had the highest proportion of positive reviews. We also compared the prediction abilities of six machine-learning models. Logistic Regression demonstrates high accuracy with all three feature extraction techniques: bag of words, term frequency-inverse document frequency, and hashing. The study assists borrowers and lenders in choosing the most appropriate application and supports P2P lending platforms in recognizing their strengths and weaknesses.
本研究通过采用主题建模和情感分析，研究了印度 P2P 借贷应用程序（应用程序）评论中传达的重要主题和客户情感。研究对象为 LenDenClub、Faircent、i2ifunding、India Money Mart 和 Lendbox。通过使用潜在德里希特分配（Latent Dirichlet Allocation），我们确定并标记了 11 个主题：申请、文件、默认、登录、拒绝、服务、CIBIL、OTP、回报、界面和提款。情感分析工具 VADER 显示，大多数用户对这些应用程序持积极态度。我们还对五款应用程序的整体情况和特定主题进行了比较。总体而言，LenDenClub 的正面评价比例最高。我们还比较了六种机器学习模型的预测能力。Logistic 回归在所有三种特征提取技术（词包、词频-反文档频率和散列）中都表现出较高的准确性。这项研究有助于借款人和贷款人选择最合适的应用程序，并支持 P2P 网络借贷平台认识自身的优缺点。
{"title":"Public Perception of Online P2P Lending Applications","authors":"Sahiba Khan, Ranjit Singh, H. Kent Baker, Gomtesh Jain","doi":"10.3390/jtaer19010027","DOIUrl":"https://doi.org/10.3390/jtaer19010027","url":null,"abstract":"This study examines significant topics and customer sentiments conveyed in reviews of P2P lending applications (apps) in India by employing topic modeling and sentiment analysis. The apps considered are LenDenClub, Faircent, i2ifunding, India Money Mart, and Lendbox. Using Latent Dirichlet Allocation, we identified and labeled 11 topics: application, document, default, login, reject, service, CIBIL, OTP, returns, interface, and withdrawal. The sentiment analysis tool VADER revealed that most users have positive attitudes toward these apps. We also compared the five apps overall and on specific topics. Overall, LenDenClub had the highest proportion of positive reviews. We also compared the prediction abilities of six machine-learning models. Logistic Regression demonstrates high accuracy with all three feature extraction techniques: bag of words, term frequency-inverse document frequency, and hashing. The study assists borrowers and lenders in choosing the most appropriate application and supports P2P lending platforms in recognizing their strengths and weaknesses.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"18 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140018396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Consumers are attracted by the increasing number of available SVOD platforms, but it would be too expensive to pay the subscription fees for all of them. To reduce costs, consumers can combine the use of proprietary subscriptions, non-proprietary subscriptions, and illegal streaming sites. In turn, platforms could enforce access control, a decision that might produce the desired reduction in non-proprietary subscriptions but also an undesired reduction in proprietary subscriptions. The effects of this decision and the determinants of SVOD content demand remain largely unexplored. We propose a baseline model where the SVOD content demand is driven by variety seeking, household financial situation, ethical evaluation, and social norms, as well as a change model where the subscription variation is driven by users’ trait reactance and perceived fairness of the decision. We conducted a survey on the current ways SVOD content is consumed and responses to a hypothetical access control enforcement, with four randomized versions of the authentication mode. Results confirmed many of the proposed determinants and showed a noteworthy reduction in proprietary subscriptions due to the control enforcement but no effect due to the authentication modes. All these findings may help improve future models of SVOD content consumption and better address the difficult challenge of converting unauthorized users into authorized ones.
{"title":"Authorized and Unauthorized Consumption of SVOD Content: Modeling Determinants of Demand and Measuring Effects of Enforcing Access Control","authors":"Ignacio Redondo, Diana Serrano","doi":"10.3390/jtaer19010025","DOIUrl":"https://doi.org/10.3390/jtaer19010025","url":null,"abstract":"Consumers are attracted by the increasing number of available SVOD platforms, but it would be too expensive to pay the subscription fees for all of them. To reduce costs, consumers can combine the use of proprietary subscriptions, non-proprietary subscriptions, and illegal streaming sites. In turn, platforms could enforce access control, a decision that might produce the desired reduction in non-proprietary subscriptions but also an undesired reduction in proprietary subscriptions. The effects of this decision and the determinants of SVOD content demand remain largely unexplored. We propose a baseline model where the SVOD content demand is driven by variety seeking, household financial situation, ethical evaluation, and social norms, as well as a change model where the subscription variation is driven by users’ trait reactance and perceived fairness of the decision. We conducted a survey on the current ways SVOD content is consumed and responses to a hypothetical access control enforcement, with four randomized versions of the authentication mode. Results confirmed many of the proposed determinants and showed a noteworthy reduction in proprietary subscriptions due to the control enforcement but no effect due to the authentication modes. All these findings may help improve future models of SVOD content consumption and better address the difficult challenge of converting unauthorized users into authorized ones.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"10 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140009471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A recommendation system serves as a key factor for improving e-commerce users’ satisfaction by providing them with more accurate and diverse suggestions. A significant body of research has examined the accuracy and diversity of a variety of recommendation systems. However, little is known about the psychological mechanisms through which the recommendation system influences the user satisfaction. Thus, the purpose of this study is to contribute to this gap by examining the mediating and moderating processes underlying this relationship. Drawing from the traditional task-technology fit literature, the study developed a moderated mediation model, simultaneously considering the roles of a user’s feeling state and shopping goal. We adopted a scenario-based experimental approach to test three hypotheses contained in the model. The results showed that there is an interaction effect between shopping goals and types of recommendation (diversity and accuracy) on user satisfaction. Specifically, when a user’s shopping goal aligns with recommendation results in terms of accuracy and diversity, the user satisfaction is enhanced. Furthermore, this study evaluated the mediating role of feeling right and psychological reactance for a better understanding of this interactive relationship. We tested the moderated mediation effect of feeling right and the psychological reactance moderated by the user shopping goal. For goal-directed users, accurate recommendations trigger the activation of feeling right, consequently increasing the user satisfaction. Conversely, when exploratory users face accurate recommendations, they activate psychological reactance, which leads to a reduction in user satisfaction. Finally, we discuss the implications for the study of recommendation systems, and for how marketers/online retailers can implement them to improve online customers’ shopping experience.
{"title":"The Impact of Recommendation System on User Satisfaction: A Moderated Mediation Approach","authors":"Xinyue He, Qi Liu, Sunho Jung","doi":"10.3390/jtaer19010024","DOIUrl":"https://doi.org/10.3390/jtaer19010024","url":null,"abstract":"A recommendation system serves as a key factor for improving e-commerce users’ satisfaction by providing them with more accurate and diverse suggestions. A significant body of research has examined the accuracy and diversity of a variety of recommendation systems. However, little is known about the psychological mechanisms through which the recommendation system influences the user satisfaction. Thus, the purpose of this study is to contribute to this gap by examining the mediating and moderating processes underlying this relationship. Drawing from the traditional task-technology fit literature, the study developed a moderated mediation model, simultaneously considering the roles of a user’s feeling state and shopping goal. We adopted a scenario-based experimental approach to test three hypotheses contained in the model. The results showed that there is an interaction effect between shopping goals and types of recommendation (diversity and accuracy) on user satisfaction. Specifically, when a user’s shopping goal aligns with recommendation results in terms of accuracy and diversity, the user satisfaction is enhanced. Furthermore, this study evaluated the mediating role of feeling right and psychological reactance for a better understanding of this interactive relationship. We tested the moderated mediation effect of feeling right and the psychological reactance moderated by the user shopping goal. For goal-directed users, accurate recommendations trigger the activation of feeling right, consequently increasing the user satisfaction. Conversely, when exploratory users face accurate recommendations, they activate psychological reactance, which leads to a reduction in user satisfaction. Finally, we discuss the implications for the study of recommendation systems, and for how marketers/online retailers can implement them to improve online customers’ shopping experience.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"241 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140009469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the widespread adoption of mobile payments (m-payments) and their impact on different generations, particularly post-COVID-19. We fill a gap in research by suggesting a new way to understand this phenomenon through the lens of social cognitive theory. We employed a multi-stage sampling technique, including purposive, quota, and snowball sampling, to ensure comparable group sizes for four generations and obtained usable survey data from 716 Thai online shoppers. The results reveal direct and indirect (through perceived values) significant relationships between technological self-efficacy and m-payment intention. While perceived values, which constitute functional, emotional, monetary, and social values, fully mediate the relationship between technological self-efficacy and m-payment intention in Gen B and Gen X consumers, it only partially mediates such a relationship in the Gen Y and Gen Z cohorts. Our findings also provide crucial theoretical and practical insights for digital commerce in the evolving landscape of m-payment adoption.
本研究调查了移动支付（m-payments）的广泛应用及其对不同世代的影响，尤其是在 COVID-19 之后。我们通过社会认知理论的视角，提出了一种理解这一现象的新方法，从而填补了研究空白。我们采用了多阶段抽样技术，包括目的性抽样、配额抽样和滚雪球抽样，以确保四代人的群体规模具有可比性，并从 716 名泰国网上购物者那里获得了可用的调查数据。结果显示，技术自我效能感与移动支付意向之间存在直接和间接（通过感知价值）的显著关系。感知价值包括功能价值、情感价值、金钱价值和社会价值，它在 B 代和 X 代消费者中完全调节了技术自我效能感与移动支付意向之间的关系，但在 Y 代和 Z 代消费者中仅部分调节了这种关系。我们的研究结果还为数字商务在不断发展的移动支付应用环境中提供了重要的理论和实践启示。
{"title":"Investigating M-Payment Intention across Consumer Cohorts","authors":"Amonrat Thoumrungroje, Lokweetpun Suprawan","doi":"10.3390/jtaer19010023","DOIUrl":"https://doi.org/10.3390/jtaer19010023","url":null,"abstract":"This study investigates the widespread adoption of mobile payments (m-payments) and their impact on different generations, particularly post-COVID-19. We fill a gap in research by suggesting a new way to understand this phenomenon through the lens of social cognitive theory. We employed a multi-stage sampling technique, including purposive, quota, and snowball sampling, to ensure comparable group sizes for four generations and obtained usable survey data from 716 Thai online shoppers. The results reveal direct and indirect (through perceived values) significant relationships between technological self-efficacy and m-payment intention. While perceived values, which constitute functional, emotional, monetary, and social values, fully mediate the relationship between technological self-efficacy and m-payment intention in Gen B and Gen X consumers, it only partially mediates such a relationship in the Gen Y and Gen Z cohorts. Our findings also provide crucial theoretical and practical insights for digital commerce in the evolving landscape of m-payment adoption.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"46 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139901960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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