Journal of Retailing and Consumer Services最新文献_第4页

Understanding user motivations for goal disclosure on social media: Structure, measurement and impact on goal attainment

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-30 DOI: 10.1016/j.jretconser.2025.104246

Jian Li , Yanping Gong , Chunyan Chen , Qing Ouyang

Despite growing interest in individual goal disclosure by both consumers and enterprises, limited research has investigated the underlying motivations behind goal disclosure on social media and its impact on goal attainment. This study aimed to elucidate the foundational structure of user motivations for goal disclosure on social media (UMGDSM), develop a reliable and valid scale to measure these motivations, and uncover the relationship between various goal disclosure motivations and goal attainment. To achieve these objectives, we conducted an in-depth interview qualitative study followed by three online quantitative studies, using samples from diverse Chinese social media users. In Study 1 (N = 30), in-depth interview data were analyzed using grounded theory to establish the motivational structure of goal disclosure. In Study 2 (N = 180), we developed a parsimonious 20-item scale to measure UMGDSM. In Study 3 (N = 407), the reliability and validity of the multidimensional scale were established. In Study 4 (N = 412), we determined the nomological validity of the scale by documenting the relationship between the UMGDSM and goal attainment. As the first study to conceptualize and operationalize UMGDSM, this work establishes a foundation for understanding motivations behind goal disclosure behaviors on social media, uncovers the diverse effects of UMGDSM on goal attainment, and broadens the theoretical perspective on goal disclosure. These findings offer valuable insights for social media users and businesses in refining publicity and implementing data-driven, precision marketing strategies.

{"title":"Understanding user motivations for goal disclosure on social media: Structure, measurement and impact on goal attainment","authors":"Jian Li , Yanping Gong , Chunyan Chen , Qing Ouyang","doi":"10.1016/j.jretconser.2025.104246","DOIUrl":"10.1016/j.jretconser.2025.104246","url":null,"abstract":"<div><div>Despite growing interest in individual goal disclosure by both consumers and enterprises, limited research has investigated the underlying motivations behind goal disclosure on social media and its impact on goal attainment. This study aimed to elucidate the foundational structure of user motivations for goal disclosure on social media (UMGDSM), develop a reliable and valid scale to measure these motivations, and uncover the relationship between various goal disclosure motivations and goal attainment. To achieve these objectives, we conducted an in-depth interview qualitative study followed by three online quantitative studies, using samples from diverse Chinese social media users. In Study 1 (<em>N</em> = 30), in-depth interview data were analyzed using grounded theory to establish the motivational structure of goal disclosure. In Study 2 (<em>N</em> = 180), we developed a parsimonious 20-item scale to measure UMGDSM. In Study 3 (<em>N</em> = 407), the reliability and validity of the multidimensional scale were established. In Study 4 (<em>N</em> = 412), we determined the nomological validity of the scale by documenting the relationship between the UMGDSM and goal attainment. As the first study to conceptualize and operationalize UMGDSM, this work establishes a foundation for understanding motivations behind goal disclosure behaviors on social media, uncovers the diverse effects of UMGDSM on goal attainment, and broadens the theoretical perspective on goal disclosure. These findings offer valuable insights for social media users and businesses in refining publicity and implementing data-driven, precision marketing strategies.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104246"},"PeriodicalIF":11.0,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bridging Digital Product Passports and in-store experiences: How augmented reality enhances decision comfort and reuse intentions

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-29 DOI: 10.1016/j.jretconser.2025.104242

Kishokanth Jeganathan , Andrzej Szymkowiak

The fashion industry is under increasing pressure to adopt more sustainable practices by decoupling its economic growth from negative environmental impacts, as consumers become more environmentally conscious. What is concerning, however, is the significant gap that persists between consumer-reported attitudes and green purchasing behaviors. This study explores the potential of augmented reality (AR) as a communication medium to integrate Digital Product Passports (DPPs) into brick-and-mortar retail, enhancing consumer decision-making and encouraging the reuse of DPPs. With DPPs soon to be mandated for retailers under new sustainability regulations, this research, grounded in the Elaboration Likelihood Model (ELM), investigates how information quality and the satisfaction of the AR experience influence decision comfort and subsequent reuse intentions. The findings reveal that both the persuasiveness of information and the satisfaction of the AR experience significantly enhance decision comfort, which in turn strongly predicts reuse intentions. Interestingly, while information persuasiveness positively impacts decision comfort, the completeness of information does not. Additionally, the study highlights that consumer knowledge moderates the relationship between decision comfort and reuse intentions. This research extends the ELM by incorporating decision comfort as a key factor in driving long-term behavioral outcomes and offers actionable insights for retailers. By leveraging AR technology, retailers can create engaging and informative shopping experiences that align with consumer demands for sustainability and ensure compliance with forthcoming environmental regulations.

{"title":"Bridging Digital Product Passports and in-store experiences: How augmented reality enhances decision comfort and reuse intentions","authors":"Kishokanth Jeganathan , Andrzej Szymkowiak","doi":"10.1016/j.jretconser.2025.104242","DOIUrl":"10.1016/j.jretconser.2025.104242","url":null,"abstract":"<div><div>The fashion industry is under increasing pressure to adopt more sustainable practices by decoupling its economic growth from negative environmental impacts, as consumers become more environmentally conscious. What is concerning, however, is the significant gap that persists between consumer-reported attitudes and green purchasing behaviors. This study explores the potential of augmented reality (AR) as a communication medium to integrate Digital Product Passports (DPPs) into brick-and-mortar retail, enhancing consumer decision-making and encouraging the reuse of DPPs. With DPPs soon to be mandated for retailers under new sustainability regulations, this research, grounded in the Elaboration Likelihood Model (ELM), investigates how information quality and the satisfaction of the AR experience influence decision comfort and subsequent reuse intentions. The findings reveal that both the persuasiveness of information and the satisfaction of the AR experience significantly enhance decision comfort, which in turn strongly predicts reuse intentions. Interestingly, while information persuasiveness positively impacts decision comfort, the completeness of information does not. Additionally, the study highlights that consumer knowledge moderates the relationship between decision comfort and reuse intentions. This research extends the ELM by incorporating decision comfort as a key factor in driving long-term behavioral outcomes and offers actionable insights for retailers. By leveraging AR technology, retailers can create engaging and informative shopping experiences that align with consumer demands for sustainability and ensure compliance with forthcoming environmental regulations.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104242"},"PeriodicalIF":11.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying targeted needs from online marketer- and user-generated data

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-28 DOI: 10.1016/j.jretconser.2025.104245

Ye Bai , Grace Yu-Buck

On e-retailing sites, marketer-generated content (MGC), user-generated content (UGC), and potential user-generated content (PUGC) are constantly conveying their needs. Identifying and clustering these needs, especially targeted needs, helps implement differentiated market strategies, improves the helpfulness of user's review content, and enhances potential user's purchase experiences. If so, then, how to identify diverse needs and find out where they are targeted (lower/higher). Based on Maslow's hierarchy of needs theory, the authors propose a need hierarchy framework to explore these questions. We utilize the datasets from two experiential products on Amazon.com and combine text mining methods with regression analyses to identify and cluster the targeted needs of online-generated content. The results show that the needs conveyed by MGC, UGC and PUGC are hierarchical and targeted, and the targeted needs are mapped to higher levels. Furthermore, we also find that the needs conveyed by PUGC are influenced by and aligned with needs of UGC. The findings reveal the deeper value of online-generated content for identifying needs, and provide a highlight for studying needs of Maslow's hierarchy of needs theory in the new field of e-commerce. Meanwhile, the results obtain the new ideas for enhancing the online interaction experiences of all the stakeholders.

{"title":"Identifying targeted needs from online marketer- and user-generated data","authors":"Ye Bai , Grace Yu-Buck","doi":"10.1016/j.jretconser.2025.104245","DOIUrl":"10.1016/j.jretconser.2025.104245","url":null,"abstract":"<div><div>On e-retailing sites, marketer-generated content (MGC), user-generated content (UGC), and potential user-generated content (PUGC) are constantly conveying their needs. Identifying and clustering these needs, especially targeted needs, helps implement differentiated market strategies, improves the helpfulness of user's review content, and enhances potential user's purchase experiences. If so, then, how to identify diverse needs and find out where they are targeted (lower/higher). Based on Maslow's hierarchy of needs theory, the authors propose a need hierarchy framework to explore these questions. We utilize the datasets from two experiential products on <span><span>Amazon.com</span><svg><path></path></svg></span> and combine text mining methods with regression analyses to identify and cluster the targeted needs of online-generated content. The results show that the needs conveyed by MGC, UGC and PUGC are hierarchical and targeted, and the targeted needs are mapped to higher levels. Furthermore, we also find that the needs conveyed by PUGC are influenced by and aligned with needs of UGC. The findings reveal the deeper value of online-generated content for identifying needs, and provide a highlight for studying needs of Maslow's hierarchy of needs theory in the new field of e-commerce. Meanwhile, the results obtain the new ideas for enhancing the online interaction experiences of all the stakeholders.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104245"},"PeriodicalIF":11.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial intelligence digital employees and sustainable innovation in online retail: The mediating role of ambidextrous green innovation and the moderating role of ethical anxiety

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-27 DOI: 10.1016/j.jretconser.2025.104235

Shaofeng Wang , Hao Zhang

The proliferation of artificial intelligence (AI) is rapidly transforming businesses across industries, driving an increased focus on sustainable innovation for long-term competitiveness. Within the online retail sector, AI-powered digital employees are emerging as key players in this transformation. This study investigates how AI digital employee adoption influences future sustainable innovation performance in online retail, examining the mediating roles of ambidextrous green innovation and the moderating effect of ethical anxiety. Drawing on the Antecedents-Behaviour-Consequences (ABC) model, we propose an Adoption-Innovations-Future Performance (AIF) framework to examine these relationships in the context of TikTok online retailers. Using a two-wave time-lagged survey of 302 online retailers, we find that digital employee adoption positively affects exploitative and exploratory green innovation, which in turn enhances future sustainable innovation performance. Digital employee ethical anxiety negatively moderates the relationship between adoption and green innovation but strengthens the positive link between adoption and future performance. The fsQCA results reveal three configurations leading to high sustainable innovation performance. This research contributes to the literature on digital transformation in retail and consumer services by elucidating the complex mechanisms through which digital employees influence organizational outcomes. The findings offer important implications for retailers seeking to leverage digital technologies for sustainability in their operations and customer service.

{"title":"Artificial intelligence digital employees and sustainable innovation in online retail: The mediating role of ambidextrous green innovation and the moderating role of ethical anxiety","authors":"Shaofeng Wang , Hao Zhang","doi":"10.1016/j.jretconser.2025.104235","DOIUrl":"10.1016/j.jretconser.2025.104235","url":null,"abstract":"<div><div>The proliferation of artificial intelligence (AI) is rapidly transforming businesses across industries, driving an increased focus on sustainable innovation for long-term competitiveness. Within the online retail sector, AI-powered digital employees are emerging as key players in this transformation. This study investigates how AI digital employee adoption influences future sustainable innovation performance in online retail, examining the mediating roles of ambidextrous green innovation and the moderating effect of ethical anxiety. Drawing on the Antecedents-Behaviour-Consequences (ABC) model, we propose an Adoption-Innovations-Future Performance (AIF) framework to examine these relationships in the context of TikTok online retailers. Using a two-wave time-lagged survey of 302 online retailers, we find that digital employee adoption positively affects exploitative and exploratory green innovation, which in turn enhances future sustainable innovation performance. Digital employee ethical anxiety negatively moderates the relationship between adoption and green innovation but strengthens the positive link between adoption and future performance. The fsQCA results reveal three configurations leading to high sustainable innovation performance. This research contributes to the literature on digital transformation in retail and consumer services by elucidating the complex mechanisms through which digital employees influence organizational outcomes. The findings offer important implications for retailers seeking to leverage digital technologies for sustainability in their operations and customer service.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104235"},"PeriodicalIF":11.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generating product reviews from aspect-based ratings using large language models

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-27 DOI: 10.1016/j.jretconser.2025.104244

Prince Pandey, Jyoti Prakash Singh

The rapid growth of e-commerce has made textual reviews and product ratings crucial for consumer purchase decisions. However, the overall Likert scale rating of the product does not convey any information about major aspects of a product. In contrast, many textual reviews often lack detailing of various aspects of the product, leading to incomplete feedback. This paper proposes a framework that generates detailed textual reviews from user-provided ratings on various aspects of a product using large language models (LLMs). Our approach enhances the online product review system by integrating specific feedback from structured ratings, resulting in more detailed and reliable product reviews. Our results show that AI-generated reviews exhibit high readability, coherence, relevance, and informativeness, rivaling human-written reviews to the extent that distinguishing between the two proves challenging, even for human evaluators. This research contributes to develop more accurate and comprehensive review systems, enhancing the overall quality and usefulness of e-commerce reviews and empowering consumers to make informed purchasing decisions. The proposed framework offers a valuable tool for businesses and e-commerce platforms to improve product reviews, enhance customer satisfaction, and increase sales.

{"title":"Generating product reviews from aspect-based ratings using large language models","authors":"Prince Pandey, Jyoti Prakash Singh","doi":"10.1016/j.jretconser.2025.104244","DOIUrl":"10.1016/j.jretconser.2025.104244","url":null,"abstract":"<div><div>The rapid growth of e-commerce has made textual reviews and product ratings crucial for consumer purchase decisions. However, the overall Likert scale rating of the product does not convey any information about major aspects of a product. In contrast, many textual reviews often lack detailing of various aspects of the product, leading to incomplete feedback. This paper proposes a framework that generates detailed textual reviews from user-provided ratings on various aspects of a product using large language models (LLMs). Our approach enhances the online product review system by integrating specific feedback from structured ratings, resulting in more detailed and reliable product reviews. Our results show that AI-generated reviews exhibit high readability, coherence, relevance, and informativeness, rivaling human-written reviews to the extent that distinguishing between the two proves challenging, even for human evaluators. This research contributes to develop more accurate and comprehensive review systems, enhancing the overall quality and usefulness of e-commerce reviews and empowering consumers to make informed purchasing decisions. The proposed framework offers a valuable tool for businesses and e-commerce platforms to improve product reviews, enhance customer satisfaction, and increase sales.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104244"},"PeriodicalIF":11.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Which corporate social responsibility (CSR) approach optimizes customer engagement behavior? The role of customer-brand identification, brand love, and social communication

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-27 DOI: 10.1016/j.jretconser.2025.104230

Rasha Dahrouj , Omar S. Itani , Linda D. Hollebeek , Hossein Eslami , Abdul-Nasser Kassar

While the CSR literature proliferates, understanding the effects of chiefly proactive (vs. chiefly reactive) CSR activities on customers' brand identification and brand love lags, leaving managers in the dark. To illuminate these issues, three studies were conducted. First, study 1 deployed an experimental design to test the effect of chiefly proactive/reactive social CSR activities on customer-brand relationships, as measured by brand identification and -love, and their respective impact on customer engagement. To ensure the validity and generalizability of the results, a second study was conducted, which replicated the previous study's design, albeit focusing on environmental CSR activities. Using survey data, study 3 tested the moderating role of social CSR communication on the association of chiefly proactive/reactive CSR activities on customer-brand identification and brand love. The findings suggest chiefly proactive (vs. -reactive) CSR's particular effectiveness in driving customer-brand identification, -love, and engagement. The study uncovered social CSR communication's key role in building customer-brand relationships, particularly for chiefly proactive CSR activities. Moreover, it shows that the effectiveness of CSR activities improves when social CSR communication is used to communicate the firm's CSR efforts on social media. This study offers theoretical insights and practical suggestions.

{"title":"Which corporate social responsibility (CSR) approach optimizes customer engagement behavior? The role of customer-brand identification, brand love, and social communication","authors":"Rasha Dahrouj , Omar S. Itani , Linda D. Hollebeek , Hossein Eslami , Abdul-Nasser Kassar","doi":"10.1016/j.jretconser.2025.104230","DOIUrl":"10.1016/j.jretconser.2025.104230","url":null,"abstract":"<div><div>While the CSR literature proliferates, understanding the effects of chiefly proactive (vs. chiefly reactive) CSR activities on customers' brand identification and brand love lags, leaving managers in the dark. To illuminate these issues, three studies were conducted. First, study 1 deployed an experimental design to test the effect of chiefly proactive/reactive social CSR activities on customer-brand relationships, as measured by brand identification and -love, and their respective impact on customer engagement. To ensure the validity and generalizability of the results, a second study was conducted, which replicated the previous study's design, albeit focusing on environmental CSR activities. Using survey data, study 3 tested the moderating role of social CSR communication on the association of chiefly proactive/reactive CSR activities on customer-brand identification and brand love. The findings suggest chiefly proactive (vs. -reactive) CSR's particular effectiveness in driving customer-brand identification, -love, and engagement. The study uncovered social CSR communication's key role in building customer-brand relationships, particularly for chiefly proactive CSR activities. Moreover, it shows that the effectiveness of CSR activities improves when social CSR communication is used to communicate the firm's CSR efforts on social media. This study offers theoretical insights and practical suggestions.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104230"},"PeriodicalIF":11.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decoding willingness to buy in live-streaming retail: The application of stimulus organism response model using PLS-SEM and SEM-ANN

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-22 DOI: 10.1016/j.jretconser.2025.104236

Irfan Hameed , Bibi Zainab , Umair Akram , Woo Jia Ying , Chesney Chan Xing , Kamran Khan

This study aims to explore the factors influencing consumer engagement in live-streaming retail. Using the Stimulus-Organism-Response (SOR) framework, the research examines the impact of relational bonds, trust, internal perceptual processes, and product uncertainty on consumer behavior. A structured questionnaire was used to collect data from live-streaming shoppers following the purposive sampling technique. The respondents were approached through social media platforms, and 437 responses were received. Partial least squares structural equation modeling (PLS-SEM) and artificial neural networks (ANN) analysis have been performed to extract the findings. The results showed that financial, social, and structural bonds positively influence trust. Trust has an encouraging influence on the internal perception process, leading to purchase intention. Additionally, trust reduces product uncertainty, which ultimately diminishes purchase intention. Influencers and companies interested in live-streaming should focus on relational bonds, consumers' internal perception processes, and reducing product uncertainty. Additionally, the ANN's non-linear output provided further insight into the significance of cognitive drivers. The findings benefit emerging influencers and companies striving to make their marks in the varying online sphere.

{"title":"Decoding willingness to buy in live-streaming retail: The application of stimulus organism response model using PLS-SEM and SEM-ANN","authors":"Irfan Hameed , Bibi Zainab , Umair Akram , Woo Jia Ying , Chesney Chan Xing , Kamran Khan","doi":"10.1016/j.jretconser.2025.104236","DOIUrl":"10.1016/j.jretconser.2025.104236","url":null,"abstract":"<div><div>This study aims to explore the factors influencing consumer engagement in live-streaming retail. Using the Stimulus-Organism-Response (SOR) framework, the research examines the impact of relational bonds, trust, internal perceptual processes, and product uncertainty on consumer behavior. A structured questionnaire was used to collect data from live-streaming shoppers following the purposive sampling technique. The respondents were approached through social media platforms, and 437 responses were received. Partial least squares structural equation modeling (PLS-SEM) and artificial neural networks (ANN) analysis have been performed to extract the findings. The results showed that financial, social, and structural bonds positively influence trust. Trust has an encouraging influence on the internal perception process, leading to purchase intention. Additionally, trust reduces product uncertainty, which ultimately diminishes purchase intention. Influencers and companies interested in live-streaming should focus on relational bonds, consumers' internal perception processes, and reducing product uncertainty. Additionally, the ANN's non-linear output provided further insight into the significance of cognitive drivers. The findings benefit emerging influencers and companies striving to make their marks in the varying online sphere.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104236"},"PeriodicalIF":11.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unraveling how poor logistics service quality of cross-border E-commerce influences customer complaints based on text mining and association analysis

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-21 DOI: 10.1016/j.jretconser.2025.104237

Yu Zhang, Huimin Huang

Logistics issues in cross-border online shopping have become an important hotspot for customer complaints. However, limited research has explored how poor logistics service quality (LSQ) can trigger customer complaints. This study systematically discusses the complex causal relationship between poor LSQ and customer complaints based on the expectation-disconfirmation theory, through analyzing 200 typical cases collected from China's professional online consumer dispute mediation platforms. Six categories of poor LSQ contributing to customer complaints were identified through text mining: insecurity, uneconomic, unreliable, untimely, low information quality, and low contact quality using the grounded theory approach. In the second stage, five valid strong association rules were generated using association rule mining (ARM), demonstrating that the factors leading to customer complaints were interrelated rather than independent. Specifically, the "delayed delivery" indicator of untimely is associated with the "outdated information" indicator of low information quality; the "long transport times" and “delayed delivery” indicators of untimely are associated with the "poor service attitude" indicator of low contact quality; the "damaged goods" indicator of insecurity is associated with the "unguaranteed goods claims" indicator of unreliable, and the "outdated information" indicator of low information quality is associated with the "poor service attitude" indicator of low contact quality. These findings enable cross-border e-commerce practitioners and logistics service providers to implement targeted strategies to promote LSQ, minimizing customers' negative expectation disconfirmation and reducing customer complaints.

{"title":"Unraveling how poor logistics service quality of cross-border E-commerce influences customer complaints based on text mining and association analysis","authors":"Yu Zhang, Huimin Huang","doi":"10.1016/j.jretconser.2025.104237","DOIUrl":"10.1016/j.jretconser.2025.104237","url":null,"abstract":"<div><div>Logistics issues in cross-border online shopping have become an important hotspot for customer complaints. However, limited research has explored how poor logistics service quality (LSQ) can trigger customer complaints. This study systematically discusses the complex causal relationship between poor LSQ and customer complaints based on the expectation-disconfirmation theory, through analyzing 200 typical cases collected from China's professional online consumer dispute mediation platforms. Six categories of poor LSQ contributing to customer complaints were identified through text mining: insecurity, uneconomic, unreliable, untimely, low information quality, and low contact quality using the grounded theory approach. In the second stage, five valid strong association rules were generated using association rule mining (ARM), demonstrating that the factors leading to customer complaints were interrelated rather than independent. Specifically, the \"delayed delivery\" indicator of untimely is associated with the \"outdated information\" indicator of low information quality; the \"long transport times\" and “delayed delivery” indicators of untimely are associated with the \"poor service attitude\" indicator of low contact quality; the \"damaged goods\" indicator of insecurity is associated with the \"unguaranteed goods claims\" indicator of unreliable, and the \"outdated information\" indicator of low information quality is associated with the \"poor service attitude\" indicator of low contact quality. These findings enable cross-border e-commerce practitioners and logistics service providers to implement targeted strategies to promote LSQ, minimizing customers' negative expectation disconfirmation and reducing customer complaints.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104237"},"PeriodicalIF":11.0,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring sustainable consumer behaviour in retail: A teacher-student model framework for socio-economic insights

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-21 DOI: 10.1016/j.jretconser.2025.104227

Sumit Tripathi , Roma Trigunait

This study examines the socio-economic factors that shape consumer behaviour related to carbon footprint awareness within the retail and services sectors. Utilizing a structured, dual-model framework, we analyse the complex relationships between key socio-economic determinants, such as income, education, age, gender, and environmental consciousness, and sustainable behaviours, including recycling, green product searches, and engagement with eco-friendly practices. The methodology combines two machine learning models to achieve both detailed analysis and interpretability. The primary model, based on the Tabular Network Regressor (TabNet), captures nuanced, high-dimensional interactions across socio-economic variables, while the secondary, interpretive model, using the Categorical Boosting Regressor (catBoost), simplifies these insights without compromising accuracy, making findings accessible for policy-oriented applications. Our results reveal that income, education, and environmental consciousness are significant predictors of carbon footprint awareness. Moreover, consumers who regularly engage in sustainable actions, such as recycling or searching for eco-friendly products, exhibit heightened awareness of their environmental impact, underscoring the influence of habitual eco-conscious behaviours. Through a Shapley Additive Explanations (SHAP) analysis, this study enhances the interpretability of results, providing a clear, data-driven understanding of how specific socio-economic factors contribute to sustainable consumer actions. This research advances knowledge on socio-economic influences in sustainability by offering actionable insights for policymakers, including targeted strategies that address diverse demographic characteristics and promote inclusive, effective policies for sustainable consumer behaviour in the retail and services industries.

{"title":"Exploring sustainable consumer behaviour in retail: A teacher-student model framework for socio-economic insights","authors":"Sumit Tripathi , Roma Trigunait","doi":"10.1016/j.jretconser.2025.104227","DOIUrl":"10.1016/j.jretconser.2025.104227","url":null,"abstract":"<div><div>This study examines the socio-economic factors that shape consumer behaviour related to carbon footprint awareness within the retail and services sectors. Utilizing a structured, dual-model framework, we analyse the complex relationships between key socio-economic determinants, such as income, education, age, gender, and environmental consciousness, and sustainable behaviours, including recycling, green product searches, and engagement with eco-friendly practices. The methodology combines two machine learning models to achieve both detailed analysis and interpretability. The primary model, based on the Tabular Network Regressor (TabNet), captures nuanced, high-dimensional interactions across socio-economic variables, while the secondary, interpretive model, using the Categorical Boosting Regressor (catBoost), simplifies these insights without compromising accuracy, making findings accessible for policy-oriented applications. Our results reveal that income, education, and environmental consciousness are significant predictors of carbon footprint awareness. Moreover, consumers who regularly engage in sustainable actions, such as recycling or searching for eco-friendly products, exhibit heightened awareness of their environmental impact, underscoring the influence of habitual eco-conscious behaviours. Through a Shapley Additive Explanations (SHAP) analysis, this study enhances the interpretability of results, providing a clear, data-driven understanding of how specific socio-economic factors contribute to sustainable consumer actions. This research advances knowledge on socio-economic influences in sustainability by offering actionable insights for policymakers, including targeted strategies that address diverse demographic characteristics and promote inclusive, effective policies for sustainable consumer behaviour in the retail and services industries.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104227"},"PeriodicalIF":11.0,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143171747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From familiarity to acceptance: The impact of Generative Artificial Intelligence on consumer adoption of retail chatbots

IF 11 1区管理学 Q1 BUSINESS

Journal of Retailing and Consumer Services

Pub Date : 2025-01-17 DOI: 10.1016/j.jretconser.2025.104234

Marta Arce-Urriza , Raquel Chocarro , Mónica Cortiñas , Gustavo Marcos-Matás

This study investigates the influence of Generative Artificial Intelligence (GenAI) on consumer adoption of retail chatbots, focusing on how GenAI impacts key adoption determinants, the role of familiarity and assessing its effects across different stages of the customer journey. We conducted two waves of surveys, one pre- and one post-GenAI integration, to compare consumer perceptions across three customer service tasks. Using the Service Robot Acceptance Model (SRAM) as a framework, we found that GenAI enhances consumer perceptions of chatbot usefulness, human-likeness, and familiarity, thereby increasing adoption intentions. However, trust remains largely unchanged, and privacy concerns have risen post-GenAI. Additionally, the relationships remain stable across customer journey stages, with familiarity playing a key role. Our findings extend SRAM to the retail context with GenAI, offering new insights into the temporal stability of chatbot adoption factors. It underscores familiarity's dual role (direct and indirect) in fostering adoption, while highlighting that GenAI impacts specific aspects of consumer interaction. These findings provide insights for retailers to leverage GenAI-powered chatbots to enhance customer engagement and satisfaction.

{"title":"From familiarity to acceptance: The impact of Generative Artificial Intelligence on consumer adoption of retail chatbots","authors":"Marta Arce-Urriza , Raquel Chocarro , Mónica Cortiñas , Gustavo Marcos-Matás","doi":"10.1016/j.jretconser.2025.104234","DOIUrl":"10.1016/j.jretconser.2025.104234","url":null,"abstract":"<div><div>This study investigates the influence of Generative Artificial Intelligence (GenAI) on consumer adoption of retail chatbots, focusing on how GenAI impacts key adoption determinants, the role of familiarity and assessing its effects across different stages of the customer journey. We conducted two waves of surveys, one pre- and one post-GenAI integration, to compare consumer perceptions across three customer service tasks. Using the Service Robot Acceptance Model (SRAM) as a framework, we found that GenAI enhances consumer perceptions of chatbot usefulness, human-likeness, and familiarity, thereby increasing adoption intentions. However, trust remains largely unchanged, and privacy concerns have risen post-GenAI. Additionally, the relationships remain stable across customer journey stages, with familiarity playing a key role. Our findings extend SRAM to the retail context with GenAI, offering new insights into the temporal stability of chatbot adoption factors. It underscores familiarity's dual role (direct and indirect) in fostering adoption, while highlighting that GenAI impacts specific aspects of consumer interaction. These findings provide insights for retailers to leverage GenAI-powered chatbots to enhance customer engagement and satisfaction.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104234"},"PeriodicalIF":11.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0