Consumers’ growing interest in the environmental and social impacts of products has increased demand for sustainable fashion items, particularly denim. Emerging technologies such as blockchain technology and labeling certifications have been developed to address sustainability issues by improving supply chain transparency and efficiency. This research investigates the trade-offs consumers make when purchasing sustainable denim jeans and the impact of sociodemographic factors on their decision-making process. Employing a conjoint analysis approach, four attributes were examined: price, brand name, types of materials, and eco-labeling. The results indicated that price is still the most influential factor, followed by material, brand name, and eco-label. Although eco-labeling is of little importance to consumers, it offers valuable insights for effective communication of sustainable practices. Consumers prefer denim with a blockchain eco-label, followed by a fair-trade certificate. This research enhances the understanding of consumer behavior toward sustainable consumption and offers strategic insights for denim producers and marketers.
{"title":"Consumption of Sustainable Denim Products: The Contribution of Blockchain Certified Eco-Labels","authors":"Xingqiu Lou, Yingjiao Xu","doi":"10.3390/jtaer19010021","DOIUrl":"https://doi.org/10.3390/jtaer19010021","url":null,"abstract":"Consumers’ growing interest in the environmental and social impacts of products has increased demand for sustainable fashion items, particularly denim. Emerging technologies such as blockchain technology and labeling certifications have been developed to address sustainability issues by improving supply chain transparency and efficiency. This research investigates the trade-offs consumers make when purchasing sustainable denim jeans and the impact of sociodemographic factors on their decision-making process. Employing a conjoint analysis approach, four attributes were examined: price, brand name, types of materials, and eco-labeling. The results indicated that price is still the most influential factor, followed by material, brand name, and eco-label. Although eco-labeling is of little importance to consumers, it offers valuable insights for effective communication of sustainable practices. Consumers prefer denim with a blockchain eco-label, followed by a fair-trade certificate. This research enhances the understanding of consumer behavior toward sustainable consumption and offers strategic insights for denim producers and marketers.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"1 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139902047","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}
Modern e-businesses heavily rely on advanced data analytics for product recommendations. However, there are still untapped opportunities to enhance user interfaces. Currently, online stores offer a single-page version to all customers, overlooking individual characteristics. This paper aims to identify the essential components and present a framework for enabling multiple e-commerce user interfaces. It also seeks to address challenges associated with personalized e-commerce user interfaces. The methodology includes detailing the framework for serving diverse e-commerce user interfaces and presenting pilot implementation results. Key components, particularly the role of algorithms in personalizing the user experience, are outlined. The results demonstrate promising outcomes for the implementation of the pilot solution, which caters to various e-commerce user interfaces. User characteristics support multivariant websites, with algorithms facilitating continuous learning. Newly proposed metrics effectively measure changes in user behavior resulting from different interface deployments. This paper underscores the central role of personalized e-commerce user interfaces in optimizing online store efficiency. The framework, supported by machine learning algorithms, showcases the feasibility and benefits of different page versions. The identified components, challenges, and proposed metrics contribute to a comprehensive solution and set the stage for further development of personalized e-commerce interfaces.
{"title":"Functional Framework for Multivariant E-Commerce User Interfaces","authors":"Adam Wasilewski","doi":"10.3390/jtaer19010022","DOIUrl":"https://doi.org/10.3390/jtaer19010022","url":null,"abstract":"Modern e-businesses heavily rely on advanced data analytics for product recommendations. However, there are still untapped opportunities to enhance user interfaces. Currently, online stores offer a single-page version to all customers, overlooking individual characteristics. This paper aims to identify the essential components and present a framework for enabling multiple e-commerce user interfaces. It also seeks to address challenges associated with personalized e-commerce user interfaces. The methodology includes detailing the framework for serving diverse e-commerce user interfaces and presenting pilot implementation results. Key components, particularly the role of algorithms in personalizing the user experience, are outlined. The results demonstrate promising outcomes for the implementation of the pilot solution, which caters to various e-commerce user interfaces. User characteristics support multivariant websites, with algorithms facilitating continuous learning. Newly proposed metrics effectively measure changes in user behavior resulting from different interface deployments. This paper underscores the central role of personalized e-commerce user interfaces in optimizing online store efficiency. The framework, supported by machine learning algorithms, showcases the feasibility and benefits of different page versions. The identified components, challenges, and proposed metrics contribute to a comprehensive solution and set the stage for further development of personalized e-commerce interfaces.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"52 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139902012","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}
Meeting customer requirements in software project management, even for large digital enterprises, proves challenging due to unpredictable human factors. It involves meticulous planning and environmental factor analysis, ultimately benefiting both companies and customers. This paper came as a natural extension of our previous work where we left ourselves curious about what impact environmental complexity factors (ECFs) have in a use case point (UCP) approach. Additionally, we wanted to possibly decrease the mean magnitude relative error (MMRE) with deep learning models such as long-short-term-memory (LSTM) and gradient recurrent unit (GRU). The data augmentation technique was used to artificially increase the number of projects, since in the industry world, digital enterprises are not keen to share their data. The LSTM model outperformed the GRU and XGBoost models, while the average MMRE in all phases of the experiment for all models achieved 4.8%. Moreover, the post-agnostic models showed the overall and individual impact of eight ECFs, where the third ECF “team experience” on a new project has been shown as the most influential one. Finally, it is important to emphasize that effectively managing human factors within ECFs in UCPs can have a significant impact on the successful completion of a project.
{"title":"Delving into Human Factors through LSTM by Navigating Environmental Complexity Factors within Use Case Points for Digital Enterprises","authors":"Nevena Rankovic, Dragica Rankovic","doi":"10.3390/jtaer19010020","DOIUrl":"https://doi.org/10.3390/jtaer19010020","url":null,"abstract":"Meeting customer requirements in software project management, even for large digital enterprises, proves challenging due to unpredictable human factors. It involves meticulous planning and environmental factor analysis, ultimately benefiting both companies and customers. This paper came as a natural extension of our previous work where we left ourselves curious about what impact environmental complexity factors (ECFs) have in a use case point (UCP) approach. Additionally, we wanted to possibly decrease the mean magnitude relative error (MMRE) with deep learning models such as long-short-term-memory (LSTM) and gradient recurrent unit (GRU). The data augmentation technique was used to artificially increase the number of projects, since in the industry world, digital enterprises are not keen to share their data. The LSTM model outperformed the GRU and XGBoost models, while the average MMRE in all phases of the experiment for all models achieved 4.8%. Moreover, the post-agnostic models showed the overall and individual impact of eight ECFs, where the third ECF “team experience” on a new project has been shown as the most influential one. Finally, it is important to emphasize that effectively managing human factors within ECFs in UCPs can have a significant impact on the successful completion of a project.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"11 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139751747","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}
Kangsun Shin, Seonggoo Ji, Ihsan Ullah Jan, Younghoon Kim
The purpose of this study is to examine the effects of a salesperson’s techno-demands and techno-resources created by new sales-related information technology on salespersons’ attitudinal and behavioral outcomes such as job burnout, job satisfaction, turnover intention, and sales performance. In order to test the proposed framework, data were collected from 305 salespeople in Korea. The results of a partial least squared structural equation modeling (PLS-SEM) analysis showed that techno-demands have a significant positive effect on salespeople’s job burnout and techno-resources have a significant positive effect on salespeople’s job satisfaction. Salespeople’s job burnout has a significant positive effect on salespeople’s turnover intention, whereas salespeople’s job satisfaction has a significant positive effect on salespeople’s sales performance. Finally, salespeople’s job satisfaction has a negative effect on turnover intention. Theoretically, this study develops a new comprehensive framework of the techno demands–resources model and is empirically tested in the context of salespeople. Managerially, the findings offer important insights to practitioners to leverage techno-resources to accelerate the sales technologies for sales activities.
{"title":"The Roles of Sales Technologies for Salespeople: Techno Demands and Resources Model Perspective","authors":"Kangsun Shin, Seonggoo Ji, Ihsan Ullah Jan, Younghoon Kim","doi":"10.3390/jtaer19010019","DOIUrl":"https://doi.org/10.3390/jtaer19010019","url":null,"abstract":"The purpose of this study is to examine the effects of a salesperson’s techno-demands and techno-resources created by new sales-related information technology on salespersons’ attitudinal and behavioral outcomes such as job burnout, job satisfaction, turnover intention, and sales performance. In order to test the proposed framework, data were collected from 305 salespeople in Korea. The results of a partial least squared structural equation modeling (PLS-SEM) analysis showed that techno-demands have a significant positive effect on salespeople’s job burnout and techno-resources have a significant positive effect on salespeople’s job satisfaction. Salespeople’s job burnout has a significant positive effect on salespeople’s turnover intention, whereas salespeople’s job satisfaction has a significant positive effect on salespeople’s sales performance. Finally, salespeople’s job satisfaction has a negative effect on turnover intention. Theoretically, this study develops a new comprehensive framework of the techno demands–resources model and is empirically tested in the context of salespeople. Managerially, the findings offer important insights to practitioners to leverage techno-resources to accelerate the sales technologies for sales activities.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"36 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139751686","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}
Patient-generated health data (PGHD) have great potential to improve clinical outcomes. As providers consider whether and how to incorporate PGHD into their clinical workflows, platforms by Apple and Amazon stand to fundamentally alter the landscape. With the aim to examine the conditions under which providers would adopt PGHD and possibly sign on with a platform, we analyzed the incentives and optimal strategies of two healthcare providers, a monopoly platform, and consumers using stylized game-theoretic models and solve for potential equilibria. We found that consumer surplus always increased with PGHD adoption, but social welfare may drop. The larger provider had more incentive to adopt PGHD than the smaller provider, but these incentives were reversed in the case of platform adoption. Accordingly, the platform enrolled the smaller provider first and possibly both providers. The emergence of the platform raised provider surplus, potentially at the expense of the consumers, despite offering its service to them for free. These results illustrate the importance of economic incentives regarding whether and how PGHD could be incorporated into our current healthcare system.
{"title":"A Game-Theoretic Analysis of the Adoption of Patient-Generated Health Data","authors":"M. Tolga Akçura, Zafer D. Ozdemir, Hakan Tarakci","doi":"10.3390/jtaer19010017","DOIUrl":"https://doi.org/10.3390/jtaer19010017","url":null,"abstract":"Patient-generated health data (PGHD) have great potential to improve clinical outcomes. As providers consider whether and how to incorporate PGHD into their clinical workflows, platforms by Apple and Amazon stand to fundamentally alter the landscape. With the aim to examine the conditions under which providers would adopt PGHD and possibly sign on with a platform, we analyzed the incentives and optimal strategies of two healthcare providers, a monopoly platform, and consumers using stylized game-theoretic models and solve for potential equilibria. We found that consumer surplus always increased with PGHD adoption, but social welfare may drop. The larger provider had more incentive to adopt PGHD than the smaller provider, but these incentives were reversed in the case of platform adoption. Accordingly, the platform enrolled the smaller provider first and possibly both providers. The emergence of the platform raised provider surplus, potentially at the expense of the consumers, despite offering its service to them for free. These results illustrate the importance of economic incentives regarding whether and how PGHD could be incorporated into our current healthcare system.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"17 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139751661","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}
Rodica Manuela Gogonea, Liviu Cătălin Moraru, Dumitru Alexandru Bodislav, Loredana Maria Păunescu, Carmen Florentina Vlăsceanu
The emergence of the COVID-19 pandemic has resulted in notable transformations of the commerce landscape, particularly in the realm of electronic commerce. This sector has experienced a precipitous advancement, characterized by substantial modifications of online business under-takings, encompassing both products and services. The aim of the current research was to explore the similarities and differences between European Union member states in the context of e-commerce in the post-pandemic period, taking into consideration the population’s level of education, the risk of poverty, as well as households’ access to the internet. The analysis was conducted for the year 2021, which represented the most recent year for which data were available, and was based on the application of the hierarchical cluster methodology, which included the Ward method and the Robust Tests of Equality of Means (Welch and Brown–Forsythe). Five clusters resulted, which included a minimum of three countries and a maximum of nine. The present study focused on examining the similarities and disparities within clusters, as well as among countries belonging to those clusters. These observed similarities and disparities are believed to be the outcome of various indicators that influence the realm of electronic commerce, and they are contingent upon the economic development level of each country and their ability to cope with the challenges posed by the COVID-19 pandemic. The information obtained in this study pertains to the future of electronic commerce in the sense of identifying premises that allow the development and application of development strategies.
{"title":"Similarities and Disparities of e-Commerce in the European Union in the Post-Pandemic Period","authors":"Rodica Manuela Gogonea, Liviu Cătălin Moraru, Dumitru Alexandru Bodislav, Loredana Maria Păunescu, Carmen Florentina Vlăsceanu","doi":"10.3390/jtaer19010018","DOIUrl":"https://doi.org/10.3390/jtaer19010018","url":null,"abstract":"The emergence of the COVID-19 pandemic has resulted in notable transformations of the commerce landscape, particularly in the realm of electronic commerce. This sector has experienced a precipitous advancement, characterized by substantial modifications of online business under-takings, encompassing both products and services. The aim of the current research was to explore the similarities and differences between European Union member states in the context of e-commerce in the post-pandemic period, taking into consideration the population’s level of education, the risk of poverty, as well as households’ access to the internet. The analysis was conducted for the year 2021, which represented the most recent year for which data were available, and was based on the application of the hierarchical cluster methodology, which included the Ward method and the Robust Tests of Equality of Means (Welch and Brown–Forsythe). Five clusters resulted, which included a minimum of three countries and a maximum of nine. The present study focused on examining the similarities and disparities within clusters, as well as among countries belonging to those clusters. These observed similarities and disparities are believed to be the outcome of various indicators that influence the realm of electronic commerce, and they are contingent upon the economic development level of each country and their ability to cope with the challenges posed by the COVID-19 pandemic. The information obtained in this study pertains to the future of electronic commerce in the sense of identifying premises that allow the development and application of development strategies.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"256 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139751672","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 article addresses the pervasive issue of fraud in financial transactions by introducing the Graph Attention Network (GAN) into graph neural networks. The article integrates Node Attention Networks and Semantic Attention Networks to construct a Dual-Head Attention Network module, enabling a comprehensive analysis of complex relationships in user transaction data. This approach adeptly handles non-linear features and intricate data interaction relationships. The article incorporates a Gradient-Boosting Decision Tree (GBDT) to enhance fraud identification to create the GBDT–Dual-channel Graph Attention Network (GBDT-DGAN). In a bid to ensure user privacy, this article introduces blockchain technology, culminating in the development of a financial anti-fraud model that fuses blockchain with the GBDT-DGAN algorithm. Experimental verification demonstrates the model’s accuracy, reaching 93.82%, a notable improvement of at least 5.76% compared to baseline algorithms such as Convolutional Neural Networks. The recall and F1 values stand at 89.5% and 81.66%, respectively. Additionally, the model exhibits superior network data transmission security, maintaining a packet loss rate below 7%. Consequently, the proposed model significantly outperforms traditional approaches in financial fraud detection accuracy and ensures excellent network data transmission security, offering an efficient and secure solution for fraud detection in the financial domain.
{"title":"Financial Anti-Fraud Based on Dual-Channel Graph Attention Network","authors":"Sizheng Wei, Suan Lee","doi":"10.3390/jtaer19010016","DOIUrl":"https://doi.org/10.3390/jtaer19010016","url":null,"abstract":"This article addresses the pervasive issue of fraud in financial transactions by introducing the Graph Attention Network (GAN) into graph neural networks. The article integrates Node Attention Networks and Semantic Attention Networks to construct a Dual-Head Attention Network module, enabling a comprehensive analysis of complex relationships in user transaction data. This approach adeptly handles non-linear features and intricate data interaction relationships. The article incorporates a Gradient-Boosting Decision Tree (GBDT) to enhance fraud identification to create the GBDT–Dual-channel Graph Attention Network (GBDT-DGAN). In a bid to ensure user privacy, this article introduces blockchain technology, culminating in the development of a financial anti-fraud model that fuses blockchain with the GBDT-DGAN algorithm. Experimental verification demonstrates the model’s accuracy, reaching 93.82%, a notable improvement of at least 5.76% compared to baseline algorithms such as Convolutional Neural Networks. The recall and F1 values stand at 89.5% and 81.66%, respectively. Additionally, the model exhibits superior network data transmission security, maintaining a packet loss rate below 7%. Consequently, the proposed model significantly outperforms traditional approaches in financial fraud detection accuracy and ensures excellent network data transmission security, offering an efficient and secure solution for fraud detection in the financial domain.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"54 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139678992","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}
Mining user satisfaction decision stages from online reviews is helpful for understanding user preferences and conducting user-centered product improvements. Therefore, this study develops a two-stage nonlinear user satisfaction decision model (USDM). First, we use word2vec technology and lexicon-based sentiment analysis to mine the sentiment polarity of each product attribute in the reviews. Then, we develop KANO mapping rules using utility functions to classify consumer preferences based on attribute importance. Based on this, a two-stage nonlinear USDM is developed to describe post-purchase evaluation behavior. In the first non-compensatory stage, consumers determine their initial satisfaction level based on the performance of basic attributes. If the performance of these attributes is poor, it is almost impossible for users to be satisfied. In the compensatory stage, the performance of the remaining attributes collectively affects final satisfaction through participation in user utility calculation. With the use of reviews from JD.com, we develop a genetic algorithm to determine feasible solutions for the USDM and verify its validity and robustness. The USDM is proven to be effective in predicting user satisfaction compared to other classic models and machine learning algorithms. This study provides a universal pattern for user satisfaction decisions and extends the study on preference analysis.
{"title":"A Two-Stage Nonlinear User Satisfaction Decision Model Based on Online Review Mining: Considering Non-Compensatory and Compensatory Stages","authors":"Shugang Li, Boyi Zhu, Yuqi Zhang, Fang Liu, Zhaoxu Yu","doi":"10.3390/jtaer19010015","DOIUrl":"https://doi.org/10.3390/jtaer19010015","url":null,"abstract":"Mining user satisfaction decision stages from online reviews is helpful for understanding user preferences and conducting user-centered product improvements. Therefore, this study develops a two-stage nonlinear user satisfaction decision model (USDM). First, we use word2vec technology and lexicon-based sentiment analysis to mine the sentiment polarity of each product attribute in the reviews. Then, we develop KANO mapping rules using utility functions to classify consumer preferences based on attribute importance. Based on this, a two-stage nonlinear USDM is developed to describe post-purchase evaluation behavior. In the first non-compensatory stage, consumers determine their initial satisfaction level based on the performance of basic attributes. If the performance of these attributes is poor, it is almost impossible for users to be satisfied. In the compensatory stage, the performance of the remaining attributes collectively affects final satisfaction through participation in user utility calculation. With the use of reviews from JD.com, we develop a genetic algorithm to determine feasible solutions for the USDM and verify its validity and robustness. The USDM is proven to be effective in predicting user satisfaction compared to other classic models and machine learning algorithms. This study provides a universal pattern for user satisfaction decisions and extends the study on preference analysis.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"28 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139679133","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}
Through the actions and interactions of video platform users, talent shows have expanded from the entertainment sphere to the social sphere and become an everyday part of life. Watching talent shows on online platforms, especially through participation in multi-platform interaction, is an ever developing and innovative field in many regions. This study adopts a multiple case analysis approach. We analyze and compare three cases of talent shows, examining aspects of their value co-creation, digital platform, dynamic capability and value network through an exploration of a series of creative activities on digital video platforms. Talent shows provide a unique environment in which different actors interact, co-exist and co-create value, i.e., another form of O2O marketing. These actors include producers, entertainment companies, sponsors and fans, and fan value co-creation currently takes many different forms, which are experienced, engaged and interacted with through different platforms. The findings contribute to examining the underlying dynamics of TV talent shows, in addition to explaining how they are achieving sustainable advantages in the media market. Furthermore, this study aims to understand the service ecosystem of network talent shows from the perspective of industrial innovation strategy; consequently, this research can help to promote the implications of this new form of digital content services and its innovation strategies.
{"title":"Value Co-Creation on TV Talent Shows: Cases from Mainland China, Taiwan and Hong Kong","authors":"Wai-Kit Ng, Cheng-Ming Yang, Chun-Liang Chen","doi":"10.3390/jtaer19010014","DOIUrl":"https://doi.org/10.3390/jtaer19010014","url":null,"abstract":"Through the actions and interactions of video platform users, talent shows have expanded from the entertainment sphere to the social sphere and become an everyday part of life. Watching talent shows on online platforms, especially through participation in multi-platform interaction, is an ever developing and innovative field in many regions. This study adopts a multiple case analysis approach. We analyze and compare three cases of talent shows, examining aspects of their value co-creation, digital platform, dynamic capability and value network through an exploration of a series of creative activities on digital video platforms. Talent shows provide a unique environment in which different actors interact, co-exist and co-create value, i.e., another form of O2O marketing. These actors include producers, entertainment companies, sponsors and fans, and fan value co-creation currently takes many different forms, which are experienced, engaged and interacted with through different platforms. The findings contribute to examining the underlying dynamics of TV talent shows, in addition to explaining how they are achieving sustainable advantages in the media market. Furthermore, this study aims to understand the service ecosystem of network talent shows from the perspective of industrial innovation strategy; consequently, this research can help to promote the implications of this new form of digital content services and its innovation strategies.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"34 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139645816","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}
Although channel consistency and seamlessness have been regarded as two critical factors in conducting omnichannel business, their combined effect has yet to be revealed. By employing a polynomial regression, this study disentangles the combined effect of channel consistency and seamlessness on customer experience in the omnichannel context. The results indicate that enhancing channel consistency and seamlessness simultaneously can improve the omnichannel customer experience. The combined effect of a high (low) level of channel consistency and a low (high) level of channel seamlessness on the omnichannel customer experience is also positive. Data vulnerability can strengthen the combined effect of channel consistency and seamlessness on customer experience in the omnichannel context. This study not only uncovers the complex influences of different combinations of channel consistency and seamlessness but also provides new insights into conducting omnichannel retail for practitioners.
{"title":"Demystifying the Combined Effect of Consistency and Seamlessness on the Omnichannel Customer Experience: A Polynomial Regression Analysis","authors":"Wei Gao, Ning Jiang","doi":"10.3390/jtaer19010013","DOIUrl":"https://doi.org/10.3390/jtaer19010013","url":null,"abstract":"Although channel consistency and seamlessness have been regarded as two critical factors in conducting omnichannel business, their combined effect has yet to be revealed. By employing a polynomial regression, this study disentangles the combined effect of channel consistency and seamlessness on customer experience in the omnichannel context. The results indicate that enhancing channel consistency and seamlessness simultaneously can improve the omnichannel customer experience. The combined effect of a high (low) level of channel consistency and a low (high) level of channel seamlessness on the omnichannel customer experience is also positive. Data vulnerability can strengthen the combined effect of channel consistency and seamlessness on customer experience in the omnichannel context. This study not only uncovers the complex influences of different combinations of channel consistency and seamlessness but also provides new insights into conducting omnichannel retail for practitioners.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":"177 1","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139645815","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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