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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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}
Online retailers offer free shipping services, such as threshold free shipping (TFS) and membership free shipping (MFS), to promote sales and provide a better shopping experience to consumers in online retailing. Although MFS attracts more member-consumers, it encourages consumers to place more small orders than TFS, which significantly increases the operational costs of the online retailer. To address this issue, we propose two price discount policies under the MFS service, namely the limited-time discount and the threshold discount. Then, we build analytical models under these two policies to explore the impacts of offering price discounts on the retailer’s profit and consumers’ welfare. We find that no matter which discount policy is adopted, consumers are more likely to consolidate several small orders from different time periods into a big one to obtain the discount. The economies of scale generated by consumers consolidating their orders under these discount policies can help reduce online retailers’ operational costs. Therefore, regardless of any discount policy offered by the online retailer under the MFS service, consumers will place more big orders and more member-consumers are attracted, i.e., the online retailer can have its cake and eat it too. Our research findings provide decision-making insights for practitioners who offer free shipping services and price discounts to consumers in online retailing.
{"title":"Have Your Cake and Eat It? Price Discount Programs under the Membership Free Shipping Policy in Online Retailing","authors":"Zhipeng Tang, Guowei Hua, Tai Chiu Edwin Cheng, Xiaowei Li, Jingxin Dong","doi":"10.3390/jtaer19010012","DOIUrl":"https://doi.org/10.3390/jtaer19010012","url":null,"abstract":"Online retailers offer free shipping services, such as threshold free shipping (TFS) and membership free shipping (MFS), to promote sales and provide a better shopping experience to consumers in online retailing. Although MFS attracts more member-consumers, it encourages consumers to place more small orders than TFS, which significantly increases the operational costs of the online retailer. To address this issue, we propose two price discount policies under the MFS service, namely the limited-time discount and the threshold discount. Then, we build analytical models under these two policies to explore the impacts of offering price discounts on the retailer’s profit and consumers’ welfare. We find that no matter which discount policy is adopted, consumers are more likely to consolidate several small orders from different time periods into a big one to obtain the discount. The economies of scale generated by consumers consolidating their orders under these discount policies can help reduce online retailers’ operational costs. Therefore, regardless of any discount policy offered by the online retailer under the MFS service, consumers will place more big orders and more member-consumers are attracted, i.e., the online retailer can have its cake and eat it too. Our research findings provide decision-making insights for practitioners who offer free shipping services and price discounts to consumers in online retailing.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139581257","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}
María Jesús Carrasco-Santos, Carmen Cristófol-Rodríguez, Ismael Begdouri-Rodríguez
This research study explores the representation of men in fashion advertising and investigates whether societal and fashion evolution has contributed to a departure from traditional stereotypes. The research methodology comprised three phases: content analysis, surveys, and in-depth interviews with an expert panel, examining how men’s clothing has been communicated in fashion over a span of 50 years, with a focus on three renowned brands: Lacoste, Burberry, and Hugo Boss. The findings reveal a notable shift in fashion advertising targeting men, characterized by increased racial diversity among models and a more diverse depiction of attitudes and poses. However, homosexual or bisexual couples remain largely unrepresented. The study highlights the influence of advertising on shaping the image of the “new man”, evident through the diminishing gender boundaries in clothing and accessories and the persistent struggle to break free from stereotypes. The study underscores the significance of ongoing efforts to promote diversity and inclusivity in fashion advertising.
{"title":"Evolution of Men’s Image in Fashion Advertising: Breaking Stereotypes and Embracing Diversity","authors":"María Jesús Carrasco-Santos, Carmen Cristófol-Rodríguez, Ismael Begdouri-Rodríguez","doi":"10.3390/jtaer19010011","DOIUrl":"https://doi.org/10.3390/jtaer19010011","url":null,"abstract":"This research study explores the representation of men in fashion advertising and investigates whether societal and fashion evolution has contributed to a departure from traditional stereotypes. The research methodology comprised three phases: content analysis, surveys, and in-depth interviews with an expert panel, examining how men’s clothing has been communicated in fashion over a span of 50 years, with a focus on three renowned brands: Lacoste, Burberry, and Hugo Boss. The findings reveal a notable shift in fashion advertising targeting men, characterized by increased racial diversity among models and a more diverse depiction of attitudes and poses. However, homosexual or bisexual couples remain largely unrepresented. The study highlights the influence of advertising on shaping the image of the “new man”, evident through the diminishing gender boundaries in clothing and accessories and the persistent struggle to break free from stereotypes. The study underscores the significance of ongoing efforts to promote diversity and inclusivity in fashion advertising.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139581256","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 Internet of Things (IoT) was born from the fusion of virtual and physical space and became the initiator of many scientific fields. Economic sustainability is the key to further development and progress. To keep up with the changes, it is necessary to adapt economic models and concepts to meet the requirements of future smart environments. Today, the need for electronic commerce (e-commerce) has become an economic priority during the transition between Industry 4.0 and Industry 5.0. Unlike mass production in Industry 4.0, customized production in Industry 5.0 should gain additional benefits in vertical management and decision-making concepts. The authors’ research is focused on e-commerce in a three-layer vertical IoT environment. The vertical IoT concept is composed of edge, fog, and cloud layers. Given the ubiquity of artificial intelligence in data processing, economic analysis, and predictions, this paper presents a few state-of-the-art machine learning (ML) algorithms facilitating the transition from a flat to a vertical e-commerce concept. The authors also propose hands-on ML algorithms for a few e-commerce types: consumer–consumer and consumer–company–consumer relationships. These algorithms are mainly composed of convolutional neural networks (CNNs), natural language understanding (NLU), sequential pattern mining (SPM), reinforcement learning (RL for agent training), algorithms for clicking on the item prediction, consumer behavior learning, etc. All presented concepts, algorithms, and models are described in detail.
{"title":"The Future of Electronic Commerce in the IoT Environment","authors":"Antonina Lazić, Saša Milić, Dragan Vukmirović","doi":"10.3390/jtaer19010010","DOIUrl":"https://doi.org/10.3390/jtaer19010010","url":null,"abstract":"The Internet of Things (IoT) was born from the fusion of virtual and physical space and became the initiator of many scientific fields. Economic sustainability is the key to further development and progress. To keep up with the changes, it is necessary to adapt economic models and concepts to meet the requirements of future smart environments. Today, the need for electronic commerce (e-commerce) has become an economic priority during the transition between Industry 4.0 and Industry 5.0. Unlike mass production in Industry 4.0, customized production in Industry 5.0 should gain additional benefits in vertical management and decision-making concepts. The authors’ research is focused on e-commerce in a three-layer vertical IoT environment. The vertical IoT concept is composed of edge, fog, and cloud layers. Given the ubiquity of artificial intelligence in data processing, economic analysis, and predictions, this paper presents a few state-of-the-art machine learning (ML) algorithms facilitating the transition from a flat to a vertical e-commerce concept. The authors also propose hands-on ML algorithms for a few e-commerce types: consumer–consumer and consumer–company–consumer relationships. These algorithms are mainly composed of convolutional neural networks (CNNs), natural language understanding (NLU), sequential pattern mining (SPM), reinforcement learning (RL for agent training), algorithms for clicking on the item prediction, consumer behavior learning, etc. All presented concepts, algorithms, and models are described in detail.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139581185","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：