Given the increasing competition and the impact of digital media in the automobile industry, dealerships need to understand the antecedents of customer happiness and brand love. The goals of the study are to analyse the combined influence of the cognitive and affective drivers of brand love for high-involvement products and its effects on behavioural intentions, paying special attention to the moderating role of susceptibility to information posted on social media. Using a sample of 317 Jordanian car buyers, a structural model is tested that confirms that the sales consultant’s empathy is a strong predictor of customer happiness during a car purchase and a stronger predictor of his/her trust in the car dealership. Happiness and trust translate into greater brand love, which in turn can generate resistance towards negative information posted on social media; positive electronic word-of-mouth; and willingness to pay more. Happiness fully mediated the relationship between empathy and car brand love. The effect of the impact of the perceived empathy of salespeople on customer happiness was stronger for consumers with low susceptibility to information posted on social media. This work expands the academic knowledge of the direct mediating and moderating effects of brand love.
{"title":"Understanding the Dynamics of Brand Love in the Automobile Industry","authors":"Mohamad Hashem, Carla Ruiz, Rafael Currás-Pérez","doi":"10.3390/jtaer19020059","DOIUrl":"https://doi.org/10.3390/jtaer19020059","url":null,"abstract":"Given the increasing competition and the impact of digital media in the automobile industry, dealerships need to understand the antecedents of customer happiness and brand love. The goals of the study are to analyse the combined influence of the cognitive and affective drivers of brand love for high-involvement products and its effects on behavioural intentions, paying special attention to the moderating role of susceptibility to information posted on social media. Using a sample of 317 Jordanian car buyers, a structural model is tested that confirms that the sales consultant’s empathy is a strong predictor of customer happiness during a car purchase and a stronger predictor of his/her trust in the car dealership. Happiness and trust translate into greater brand love, which in turn can generate resistance towards negative information posted on social media; positive electronic word-of-mouth; and willingness to pay more. Happiness fully mediated the relationship between empathy and car brand love. The effect of the impact of the perceived empathy of salespeople on customer happiness was stronger for consumers with low susceptibility to information posted on social media. This work expands the academic knowledge of the direct mediating and moderating effects of brand love.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141109042","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}
Textual emotion recognition (TER) has significant commercial potential since it can be used as an excellent tool to monitor a brand/business reputation, understand customer satisfaction, and personalize recommendations. It is considered a natural language processing task that can be used to understand and classify emotions such as anger, happiness, and surprise being conveyed in a piece of text (product reviews, tweets, and comments). Despite the advanced development of deep learning and particularly transformer architectures, Arabic-focused models for emotion classification have not achieved satisfactory accuracy. This is mainly due to the morphological richness, agglutination, dialectal variation, and low-resource datasets of the Arabic language, as well as the unique features of user-generated text such as noisiness, shortness, and informal language. This study aims to illustrate the effectiveness of large language models on Arabic multi-label emotion classification. We evaluated GPT-3.5 Turbo and GPT-4 using three different settings: in-context learning, emotional stimuli prompt, and fine-tuning. The ultimate objective of this research paper is to determine if these LLMs, which have multilingual capabilities, could contribute to enhancing the aforementioned task and encourage its use within the context of an e-commerce environment for example. The experimental results indicated that the fine-tuned GPT-3.5 Turbo model achieved an accuracy of 62.03%, a micro-averaged F1-score of 73%, and a macro-averaged F1-score of 62%, establishing a new state-of-the-art benchmark for the task of Arabic multi-label emotion recognition.
文本情感识别（TER）具有巨大的商业潜力，因为它可以作为监测品牌/企业声誉、了解客户满意度和个性化推荐的绝佳工具。它被认为是一种自然语言处理任务，可用于理解和分类文本（产品评论、推特和评论）中传达的愤怒、快乐和惊讶等情绪。尽管深度学习，尤其是转换器架构的发展非常迅速，但以阿拉伯语为重点的情感分类模型并未达到令人满意的准确度。这主要是由于阿拉伯语的形态丰富性、聚合性、方言差异和低资源数据集，以及用户生成文本的独特特征，如噪音、短小和非正式语言。本研究旨在说明大型语言模型在阿拉伯语多标签情感分类中的有效性。我们使用三种不同的设置对 GPT-3.5 Turbo 和 GPT-4 进行了评估：上下文学习、情感刺激提示和微调。本研究论文的最终目的是确定这些具有多语言功能的 LLM 是否有助于增强上述任务，并鼓励在电子商务环境等背景下使用这些 LLM。实验结果表明，经过微调的 GPT-3.5 Turbo 模型的准确率达到了 62.03%，微观平均 F1 分数为 73%，宏观平均 F1 分数为 62%，为阿拉伯语多标签情感识别任务建立了一个新的先进基准。
{"title":"Evaluating Arabic Emotion Recognition Task Using ChatGPT Models: A Comparative Analysis between Emotional Stimuli Prompt, Fine-Tuning, and In-Context Learning","authors":"El Habib Nfaoui, Hanane Elfaik","doi":"10.3390/jtaer19020058","DOIUrl":"https://doi.org/10.3390/jtaer19020058","url":null,"abstract":"Textual emotion recognition (TER) has significant commercial potential since it can be used as an excellent tool to monitor a brand/business reputation, understand customer satisfaction, and personalize recommendations. It is considered a natural language processing task that can be used to understand and classify emotions such as anger, happiness, and surprise being conveyed in a piece of text (product reviews, tweets, and comments). Despite the advanced development of deep learning and particularly transformer architectures, Arabic-focused models for emotion classification have not achieved satisfactory accuracy. This is mainly due to the morphological richness, agglutination, dialectal variation, and low-resource datasets of the Arabic language, as well as the unique features of user-generated text such as noisiness, shortness, and informal language. This study aims to illustrate the effectiveness of large language models on Arabic multi-label emotion classification. We evaluated GPT-3.5 Turbo and GPT-4 using three different settings: in-context learning, emotional stimuli prompt, and fine-tuning. The ultimate objective of this research paper is to determine if these LLMs, which have multilingual capabilities, could contribute to enhancing the aforementioned task and encourage its use within the context of an e-commerce environment for example. The experimental results indicated that the fine-tuned GPT-3.5 Turbo model achieved an accuracy of 62.03%, a micro-averaged F1-score of 73%, and a macro-averaged F1-score of 62%, establishing a new state-of-the-art benchmark for the task of Arabic multi-label emotion recognition.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140932066","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}
Eye tracking plays a crucial role in consumer research. The aim of this work is to present the statuses of studies that used eye tracking as an instrument in consumer research to investigate food from a marketing perspective. For this purpose, a bibliometric review of 118 articles from the Business Source Premier and Web of Science Core Collection database was compiled. The bibliometric review provides information on publication trends, leading authors, collaborative networks, journals, institutions, countries, articles, keywords, and themes investigated. Publications in the research field have appeared since 2011, primarily in Europe, the United States, and Uruguay. Three areas of research streams were identified: (1) how consumers became aware of and chose food, (2) nutritional information and its impact, and (3) how food information and its visual attention led to certain consumer behavior. The bibliographic review summarized past research directions and, thus, identified possibilities for future research streams.
眼动仪在消费者研究中起着至关重要的作用。这项工作的目的是介绍在消费者研究中使用眼动仪从营销角度调查食品的研究现状。为此，我们对 Business Source Premier 和 Web of Science Core Collection 数据库中的 118 篇文章进行了文献计量审查。文献计量综述提供了有关出版趋势、主要作者、合作网络、期刊、机构、国家、文章、关键词和调查主题的信息。自 2011 年以来，该研究领域的出版物主要出现在欧洲、美国和乌拉圭。确定了三个研究领域：(1) 消费者如何认识和选择食品，(2) 营养信息及其影响，(3) 食品信息及其视觉注意力如何导致某些消费行为。文献综述总结了过去的研究方向，从而确定了未来研究方向的可能性。
{"title":"Eye Tracking as an Instrument in Consumer Research to Investigate Food from A Marketing Perspective: A Bibliometric and Visual Analysis","authors":"Tonia Ruppenthal, Nils Schweers","doi":"10.3390/jtaer19020057","DOIUrl":"https://doi.org/10.3390/jtaer19020057","url":null,"abstract":"Eye tracking plays a crucial role in consumer research. The aim of this work is to present the statuses of studies that used eye tracking as an instrument in consumer research to investigate food from a marketing perspective. For this purpose, a bibliometric review of 118 articles from the Business Source Premier and Web of Science Core Collection database was compiled. The bibliometric review provides information on publication trends, leading authors, collaborative networks, journals, institutions, countries, articles, keywords, and themes investigated. Publications in the research field have appeared since 2011, primarily in Europe, the United States, and Uruguay. Three areas of research streams were identified: (1) how consumers became aware of and chose food, (2) nutritional information and its impact, and (3) how food information and its visual attention led to certain consumer behavior. The bibliographic review summarized past research directions and, thus, identified possibilities for future research streams.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140932124","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 often rely on evaluations such as online reviews shared by other consumers when making purchasing decisions. Online reviews have emerged as a crucial marketing tool that offers a distinct advantage over traditional methods by fostering trust among consumers. Previous studies have identified group similarity between consumers and reviewers as a key variable with a potential impact on consumer responses and purchase intention. However, the results remain inconclusive. In this study, we identify self-construal and group similarity as key factors in the influence of online review ratings on consumers’ purchase intentions. We further investigate the role of consumers’ self-construal in shaping consumers’ perceptions of online reviews in terms of belongingness and diagnosticity. To test the hypothesis, we conducted a 2 (online review rating) × 2 (group similarity) × 2 (self-construal) ANOVA on 276 subjects collected through Amazon Mechanical Turk (MTurk), and contrast analysis and PROCESS macro model 12 were used for the interaction effect analysis and moderated mediation analysis. Our findings reveal that consumers with an interdependent self-construal are sensitive to both review ratings and group similarity with regards to their purchase intentions. They demonstrate a positive purchase intention when both group similarity and online review ratings are high. However, their purchase intention is not influenced by review ratings when group similarity is low. Conversely, consumers with an independent self-construal exhibit a more positive purchase intention when the online review rating is high, irrespective of group similarity. Additionally, our study highlights the mediating roles of perceived diagnosticity and belongingness in the relationship between online review ratings, group similarity, self-construal, and purchase intentions. Results show significant indirect effects for perceived diagnosticity and belongingness, meaning that the impact of online review ratings on purchase intention is mediated by these two variables. The outcomes of our research offer theoretical and practical implications concerning online reviews and suggest new avenues for future research in the area of online consumer behavior.
消费者在做出购买决定时，往往依赖于其他消费者分享的在线评论等评价。在线评论已成为一种重要的营销工具，与传统方法相比，它通过增进消费者之间的信任而具有明显优势。以往的研究发现，消费者与评论者之间的群体相似性是一个关键变量，可能对消费者的反应和购买意向产生影响。然而，研究结果仍未得出结论。在本研究中，我们将自我概念和群体相似性视为在线评论评级影响消费者购买意向的关键因素。我们进一步研究了消费者的自我建构在影响消费者对在线评论的归属感和诊断性方面所起的作用。为验证假设，我们对通过亚马逊机械土耳其（MTurk）收集的 276 名受试者进行了 2（在线评论评分）×2（群体相似性）×2（自我建构）方差分析，并使用对比分析和 PROCESS 宏模型 12 进行了交互效应分析和调节中介分析。我们的研究结果表明，具有相互依存自我结构的消费者在购买意向方面对评论评分和群体相似性都很敏感。当群体相似度和在线评论评分都很高时，他们会表现出积极的购买意向。然而，当群体相似度较低时，他们的购买意向不受评论评级的影响。相反，无论群体相似度如何，当在线评论评分较高时，具有独立自我概念的消费者会表现出更积极的购买意向。此外，我们的研究还强调了感知诊断性和归属感在网络评论评分、群体相似性、自我建构和购买意向之间的中介作用。研究结果表明，感知诊断性和归属感具有明显的间接效应，这意味着在线评论评分对购买意向的影响是由这两个变量中介的。我们的研究成果提供了有关在线评论的理论和实践意义，并为在线消费者行为领域的未来研究提出了新的途径。
{"title":"The Impact of Online Reviews on Consumers’ Purchase Intentions: Examining the Social Influence of Online Reviews, Group Similarity, and Self-Construal","authors":"Yunjeong Ahn, Jieun Lee","doi":"10.3390/jtaer19020055","DOIUrl":"https://doi.org/10.3390/jtaer19020055","url":null,"abstract":"Consumers often rely on evaluations such as online reviews shared by other consumers when making purchasing decisions. Online reviews have emerged as a crucial marketing tool that offers a distinct advantage over traditional methods by fostering trust among consumers. Previous studies have identified group similarity between consumers and reviewers as a key variable with a potential impact on consumer responses and purchase intention. However, the results remain inconclusive. In this study, we identify self-construal and group similarity as key factors in the influence of online review ratings on consumers’ purchase intentions. We further investigate the role of consumers’ self-construal in shaping consumers’ perceptions of online reviews in terms of belongingness and diagnosticity. To test the hypothesis, we conducted a 2 (online review rating) × 2 (group similarity) × 2 (self-construal) ANOVA on 276 subjects collected through Amazon Mechanical Turk (MTurk), and contrast analysis and PROCESS macro model 12 were used for the interaction effect analysis and moderated mediation analysis. Our findings reveal that consumers with an interdependent self-construal are sensitive to both review ratings and group similarity with regards to their purchase intentions. They demonstrate a positive purchase intention when both group similarity and online review ratings are high. However, their purchase intention is not influenced by review ratings when group similarity is low. Conversely, consumers with an independent self-construal exhibit a more positive purchase intention when the online review rating is high, irrespective of group similarity. Additionally, our study highlights the mediating roles of perceived diagnosticity and belongingness in the relationship between online review ratings, group similarity, self-construal, and purchase intentions. Results show significant indirect effects for perceived diagnosticity and belongingness, meaning that the impact of online review ratings on purchase intention is mediated by these two variables. The outcomes of our research offer theoretical and practical implications concerning online reviews and suggest new avenues for future research in the area of online consumer behavior.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140932052","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 paper investigates the estimated return rate and optimal order quantity under three cross-border e-commerce return logistics modes: direct mail (from predecessor), in situ destruction (new), and insurance (new). The estimated return rate under each model was analyzed and it was found that different modes have different thresholds in delivery lead time (the time retailers need to deliver goods to customers), and within which the estimated return rate increases as the delivery lead time increases. And a size comparison of the estimated return rates for the three models was conducted. A profit model was constructed based on the estimated return rate model, the optimal order quantity was calculated, and the effects of different factors (tax, postage, and delivery lead time etc.) on it were analyzed. For the insurance model, the effect of bearing the insurance ratio between retailers and consumers on the optimal order quantity was examined. The goal of this paper was to construct a model of the estimated return rate for the two new modes and to compare the estimated return rate of the three modes, which provides a reference for retailers to choose among the diversified return logistics modes and then make the best ordering strategy according to the influence of different factors on the optimal order quantity.
{"title":"Research on B2C Cross-Border Electronic Commerce Return Logistics Model Selection Based on Estimated Return Rate","authors":"Yi Li, Zhiyang Li","doi":"10.3390/jtaer19020054","DOIUrl":"https://doi.org/10.3390/jtaer19020054","url":null,"abstract":"This paper investigates the estimated return rate and optimal order quantity under three cross-border e-commerce return logistics modes: direct mail (from predecessor), in situ destruction (new), and insurance (new). The estimated return rate under each model was analyzed and it was found that different modes have different thresholds in delivery lead time (the time retailers need to deliver goods to customers), and within which the estimated return rate increases as the delivery lead time increases. And a size comparison of the estimated return rates for the three models was conducted. A profit model was constructed based on the estimated return rate model, the optimal order quantity was calculated, and the effects of different factors (tax, postage, and delivery lead time etc.) on it were analyzed. For the insurance model, the effect of bearing the insurance ratio between retailers and consumers on the optimal order quantity was examined. The goal of this paper was to construct a model of the estimated return rate for the two new modes and to compare the estimated return rate of the three modes, which provides a reference for retailers to choose among the diversified return logistics modes and then make the best ordering strategy according to the influence of different factors on the optimal order quantity.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140941788","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}
Sellers of platforms offering cashback rewards for favorable comments (hereinafter CRFC) to generate positive online reviews are ubiquitous. This research examines when and how a CRFC influences consumers’ post-purchase behavioral intentions regarding repurchase and recommendation. Anchoring on the relationship norms theory and casting light on consumers’ self-perceptions, the effect of a CRFC on consumers’ post-purchase behavioral intentions is contingent on the relationship norms. The findings of a pilot study and two experimental studies show that after a CRFC offer, communal consumers experienced lower post-purchase behavioral intentions than exchange consumers, and that consumers’ feeling of self-disgust is the mechanism underlying this interactive effect. Specifically, a CRFC is effective for exchange consumers but not for communal consumers because it triggers self-disgust in communal consumers. This paper thus reveals the mediating role of self-disgust in the interactive effect of CRFC and relationship norms on post-purchase behavioral intentions. The implications for sellers, platforms and consumers are discussed.
{"title":"From a Penny to Self-Disgust: How Cashback Rewards for Favorable Comments and Relationship Norms Affect Consumers’ Post-Purchase Behavioral Intentions","authors":"Qingqing Guo","doi":"10.3390/jtaer19020056","DOIUrl":"https://doi.org/10.3390/jtaer19020056","url":null,"abstract":"Sellers of platforms offering cashback rewards for favorable comments (hereinafter CRFC) to generate positive online reviews are ubiquitous. This research examines when and how a CRFC influences consumers’ post-purchase behavioral intentions regarding repurchase and recommendation. Anchoring on the relationship norms theory and casting light on consumers’ self-perceptions, the effect of a CRFC on consumers’ post-purchase behavioral intentions is contingent on the relationship norms. The findings of a pilot study and two experimental studies show that after a CRFC offer, communal consumers experienced lower post-purchase behavioral intentions than exchange consumers, and that consumers’ feeling of self-disgust is the mechanism underlying this interactive effect. Specifically, a CRFC is effective for exchange consumers but not for communal consumers because it triggers self-disgust in communal consumers. This paper thus reveals the mediating role of self-disgust in the interactive effect of CRFC and relationship norms on post-purchase behavioral intentions. The implications for sellers, platforms and consumers are discussed.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140941931","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 examines the effects of three interactive voice assistant (VA) features (responsiveness, ubiquitous connectivity, and personalization) on consumer happiness. An online survey was administered to 316 VA consumers, and the data were analyzed using structural equation modeling with SmartPLS 4 software. The results indicate that VA responsiveness, ubiquitous connectivity, and personalization have significant effects on consumer happiness. This study also provides evidence that consumer happiness is influenced by VA features through the mediating roles of autonomy and timeliness. Notably, perceived privacy risk has a dual effect, negatively affecting happiness but positively moderating the relationship between autonomy and happiness, suggesting a complex interplay between benefits and concerns in user interactions with VAs. This study highlights the need for VA businesses to consider both the enhancing and mitigating factors of technology for user experiences. Furthermore, our findings have significant implications for VA businesses and executives, suggesting that improved interactions through these VA features can better serve consumers and enhance their experiences.
{"title":"Unlock Happy Interactions: Voice Assistants Enable Autonomy and Timeliness","authors":"Linlin Mo, Liangbo Zhang, Xiaohui Sun, Zhimin Zhou","doi":"10.3390/jtaer19020053","DOIUrl":"https://doi.org/10.3390/jtaer19020053","url":null,"abstract":"This study examines the effects of three interactive voice assistant (VA) features (responsiveness, ubiquitous connectivity, and personalization) on consumer happiness. An online survey was administered to 316 VA consumers, and the data were analyzed using structural equation modeling with SmartPLS 4 software. The results indicate that VA responsiveness, ubiquitous connectivity, and personalization have significant effects on consumer happiness. This study also provides evidence that consumer happiness is influenced by VA features through the mediating roles of autonomy and timeliness. Notably, perceived privacy risk has a dual effect, negatively affecting happiness but positively moderating the relationship between autonomy and happiness, suggesting a complex interplay between benefits and concerns in user interactions with VAs. This study highlights the need for VA businesses to consider both the enhancing and mitigating factors of technology for user experiences. Furthermore, our findings have significant implications for VA businesses and executives, suggesting that improved interactions through these VA features can better serve consumers and enhance their experiences.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140838953","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}
Giovanny Haro-Sosa, Beatriz Moliner-Velázquez, Irene Gil-Saura, Maria Fuentes-Blasco
A growing body of the literature on the study of online reviews presents interesting research opportunities, especially in services highly frequented by young consumer segments, such as restaurants. In this context, the present study examines the restaurant electronic word-of-mouth (EWOM) behavior of Millennial consumers by addressing both review queries before the purchase decision and writing and sending after the purchase. Based on the theory of reasoned action, a double objective is pursued. On the one hand, the influence of motivations related to extroversion, social benefits, and altruism on EWOM sending behavior is analyzed. On the other hand, the moderating role of EWOM consultation in these relationships is studied. Using a sample of 341 Millennials from Ecuador, a structural model is constructed that confirms the contribution of two types of motivations in sending EWOM: those of extroversion and those of social benefits. The results also reveal the moderating role of EWOM consultation alone in the effects of extraversion and altruism motivations. Managerial implications for restaurants derived from this study include improvements in the design of digital communication strategies tailored to Millennial customers based on their motivations.
{"title":"Motivations toward Electronic Word-of-Mouth Sending Behavior Regarding Restaurant Experiences in the Millennial Generation","authors":"Giovanny Haro-Sosa, Beatriz Moliner-Velázquez, Irene Gil-Saura, Maria Fuentes-Blasco","doi":"10.3390/jtaer19020052","DOIUrl":"https://doi.org/10.3390/jtaer19020052","url":null,"abstract":"A growing body of the literature on the study of online reviews presents interesting research opportunities, especially in services highly frequented by young consumer segments, such as restaurants. In this context, the present study examines the restaurant electronic word-of-mouth (EWOM) behavior of Millennial consumers by addressing both review queries before the purchase decision and writing and sending after the purchase. Based on the theory of reasoned action, a double objective is pursued. On the one hand, the influence of motivations related to extroversion, social benefits, and altruism on EWOM sending behavior is analyzed. On the other hand, the moderating role of EWOM consultation in these relationships is studied. Using a sample of 341 Millennials from Ecuador, a structural model is constructed that confirms the contribution of two types of motivations in sending EWOM: those of extroversion and those of social benefits. The results also reveal the moderating role of EWOM consultation alone in the effects of extraversion and altruism motivations. Managerial implications for restaurants derived from this study include improvements in the design of digital communication strategies tailored to Millennial customers based on their motivations.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140798856","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 examines the dynamic interplay between platform providers and complementors in the context of digital ecosystems, focusing on the complementary factors of affordance, autonomy, and super-modularity. Using national survey data from the Korean digital industry, the study applied multivariate ordered probit and k-mode clustering models to analyze what determines these factors and how these factors are interrelated from the perspective of platform providers and complementors, respectively. The results indicate that platform providers with open APIs promote affordance, but providing an SDK inhibits affordance. In terms of complementors, choosing a platform providing APIs increases super-modularity. And affordance increases when using the platform for logistics and new product development. In addition, we found that affordance and autonomy have a trade-off relationship from the perspective of both platform providers and complementors. Finally, we classified platforms and complementors into subgroups with respect to affordance, autonomy, and super-modularity using cluster analysis and found that the size of a complementor’s firm, such as revenue and number of employees, influences which platform it chooses. Conversely, the size of a platform provider also influences how much autonomy and collaboration it offers. This study contributes to the understanding of digital platform ecosystems and provides insights for practitioners on how to leverage platform dynamics to enhance competitive advantage.
本研究探讨了数字生态系统背景下平台提供者与互补者之间的动态互动关系，重点关注可负担性、自主性和超模块性等互补因素。本研究利用韩国数字产业的全国性调查数据，采用多元有序概率模型和 K 模式聚类模型，分别从平台提供者和补充者的角度分析了决定这些因素的因素以及这些因素之间的相互关系。结果表明，提供开放式应用程序接口的平台提供商会促进可负担性，而提供 SDK 则会抑制可负担性。从补充者的角度来看，选择提供应用程序接口的平台会增加超模块性。而在使用平台进行物流和新产品开发时，承受能力也会提高。此外，我们还发现，从平台提供者和补充者的角度来看，可负担性和自主性之间存在权衡关系。最后，我们利用聚类分析法将平台和补充者按可负担性、自主性和超模块性划分为不同的子群，发现补充者公司的规模（如收入和员工人数）会影响其选择的平台。相反，平台提供商的规模也会影响其提供自主性和协作性的程度。这项研究有助于人们了解数字平台生态系统，并为从业者如何利用平台动态提升竞争优势提供了启示。
{"title":"Interplay between Platform Providers and Complementors via Affordance, Autonomy, and Super-Modularity: The Empirical Investigation of the Korean Digital Industry","authors":"Dongnyok Shim","doi":"10.3390/jtaer19020051","DOIUrl":"https://doi.org/10.3390/jtaer19020051","url":null,"abstract":"This study examines the dynamic interplay between platform providers and complementors in the context of digital ecosystems, focusing on the complementary factors of affordance, autonomy, and super-modularity. Using national survey data from the Korean digital industry, the study applied multivariate ordered probit and k-mode clustering models to analyze what determines these factors and how these factors are interrelated from the perspective of platform providers and complementors, respectively. The results indicate that platform providers with open APIs promote affordance, but providing an SDK inhibits affordance. In terms of complementors, choosing a platform providing APIs increases super-modularity. And affordance increases when using the platform for logistics and new product development. In addition, we found that affordance and autonomy have a trade-off relationship from the perspective of both platform providers and complementors. Finally, we classified platforms and complementors into subgroups with respect to affordance, autonomy, and super-modularity using cluster analysis and found that the size of a complementor’s firm, such as revenue and number of employees, influences which platform it chooses. Conversely, the size of a platform provider also influences how much autonomy and collaboration it offers. This study contributes to the understanding of digital platform ecosystems and provides insights for practitioners on how to leverage platform dynamics to enhance competitive advantage.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140798860","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}
Jiayin Li, Xing Su, Jiahao Liang, P. Y. Mok, Jintu Fan
In the context of the Fashion Apparel Industry 4.0, a transformative evolution is directed towards the Online Apparel Mass Customization (OAMC) strategy, which provides efficient and personalized apparel product solutions to consumers. A critical challenge within this customization process is the determination of sizes. While existing research addresses comfort evaluation in relation to wearer and garment fit, little attention has been given to how garment fit influences the wearer’s body image, which is also an important purchase consideration. This study investigates the impact of garment fit on the wearer’s body scale perception using quantitative research design. A digital dataset of avatars, clothed in varying sizes of T-shirts, were created for the body scale perception experiment, and an Artificial Neural Network (ANN) model was developed to predict the effect of T-shirt fit on body image. With only a small number of garments and body measurements as inputs, the ANN model can accurately predict the body scales of the clothed persons. It was found that the effect of apparel fit on body image varies depending on the wearer’s gender, body size, and shape. This model can be applied to enhance the online garment shopping experience with respect to personalized body image enhancement.
在时尚服饰工业 4.0 的背景下，在线服装大规模定制（OAMC）战略是一个转型发展的方向，它为消费者提供高效和个性化的服装产品解决方案。在这一定制过程中，一个关键的挑战是尺寸的确定。虽然现有研究涉及与穿着者和服装合身度相关的舒适度评估，但很少关注服装合身度如何影响穿着者的身体形象，而身体形象也是重要的购买考虑因素。本研究采用定量研究设计，调查服装合身度对穿着者身体尺度感知的影响。为进行人体尺度感知实验，我们创建了一个穿着不同尺寸 T 恤的化身数字数据集，并开发了一个人工神经网络（ANN）模型来预测 T 恤合身度对身体形象的影响。只需输入少量服装和身体测量数据，人工神经网络模型就能准确预测着装者的体型。研究发现，服装合身度对身体形象的影响因穿着者的性别、体型和体形而异。该模型可应用于增强个性化身体形象方面的在线服装购物体验。
{"title":"Tailoring Garment Fit for Personalized Body Image Enhancement: Insights from Digital Fitting Research","authors":"Jiayin Li, Xing Su, Jiahao Liang, P. Y. Mok, Jintu Fan","doi":"10.3390/jtaer19020049","DOIUrl":"https://doi.org/10.3390/jtaer19020049","url":null,"abstract":"In the context of the Fashion Apparel Industry 4.0, a transformative evolution is directed towards the Online Apparel Mass Customization (OAMC) strategy, which provides efficient and personalized apparel product solutions to consumers. A critical challenge within this customization process is the determination of sizes. While existing research addresses comfort evaluation in relation to wearer and garment fit, little attention has been given to how garment fit influences the wearer’s body image, which is also an important purchase consideration. This study investigates the impact of garment fit on the wearer’s body scale perception using quantitative research design. A digital dataset of avatars, clothed in varying sizes of T-shirts, were created for the body scale perception experiment, and an Artificial Neural Network (ANN) model was developed to predict the effect of T-shirt fit on body image. With only a small number of garments and body measurements as inputs, the ANN model can accurately predict the body scales of the clothed persons. It was found that the effect of apparel fit on body image varies depending on the wearer’s gender, body size, and shape. This model can be applied to enhance the online garment shopping experience with respect to personalized body image enhancement.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140635227","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：