Pub Date : 2024-02-15DOI: 10.1108/imds-09-2023-0623
Maosheng Yang, Lei Feng, Honghong Zhou, Shih-Chih Chen, Ming K. Lim, Ming-Lang Tseng
PurposeThis study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.Design/methodology/approachThis study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.FindingsThe findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.Originality/valueThis study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.
{"title":"Perceived interactivity in real estate APP increases consumers' psychological well-being: a moderated mediation model","authors":"Maosheng Yang, Lei Feng, Honghong Zhou, Shih-Chih Chen, Ming K. Lim, Ming-Lang Tseng","doi":"10.1108/imds-09-2023-0623","DOIUrl":"https://doi.org/10.1108/imds-09-2023-0623","url":null,"abstract":"PurposeThis study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.Design/methodology/approachThis study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.FindingsThe findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.Originality/valueThis study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139776593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.1108/imds-06-2023-0377
Hongjoo Woo, Wi-Suk Kwon, A. Sadachar, Zhenghao Tong, Jimin Yang
PurposeWhen retail businesses, especially small businesses with greater vulnerability, could not meet consumers in person during the recent pandemic crisis, how did they adapt to the situation? This study examined how small business practitioners (SBPs’) perceptions, trust and adoption intention levels for social media, as well as the relationships among these variables, changed before and during the crisis based on the integration of the contingency theory and the diffusion of innovation theory (DIT).Design/methodology/approachOnline surveys were conducted with USA SBPs before (n = 175) and during (n = 225) the recent pandemic. The hypotheses were tested using structural equation modeling (SEM), multivariate analysis of variance (MANOVA) and multiple-group SEM analysis.FindingsThe results confirmed significant sequential positive relationships between SBPs’ perceived external pressure and perceived benefits of adopting social media, which in turn led to their trust in and then adoption intentions for social media. Further, the comparisons between the pre- and in-pandemic samples revealed that SBPs’ perceptions and adoption intentions all became significantly higher during (vs before) the pandemic, but the structural relationships among these variables weakened during the pandemic.Originality/valueThis study uses a novel approach to integrate the contingency theory with the DIT to propose small businesses' perceptions, trust and adoption intentions for social media during the innovation decision process under rapid contingency changes. Our findings also offer practical implications including recommendations for small businesses’ innovation management as well as training programs.
目的在最近的大流行病危机中，当零售企业，尤其是更脆弱的小企业无法亲自与消费者见面时，他们是如何适应这种情况的？本研究在整合权变理论和创新扩散理论（DIT）的基础上，考察了小企业从业者（SBPs）在危机前和危机期间对社交媒体的认知、信任和采用意向水平，以及这些变量之间的关系。结果结果表明，SBPs 感知到的外部压力与感知到的采用社交媒体的益处之间存在显著的正向关系，这反过来又导致了他们对社交媒体的信任，进而产生了采用社交媒体的意愿。此外，大流行前和大流行中样本的比较显示，小企业在大流行期间（与大流行前相比）的感知和采用意向都显著提高，但这些变量之间的结构关系在大流行期间有所减弱。 原创性/价值 本研究采用一种新颖的方法，将权变理论与 DIT 相结合，提出了小企业在快速权变下的创新决策过程中对社交媒体的感知、信任和采用意向。我们的研究结果还具有实际意义，包括对小型企业创新管理和培训计划的建议。
{"title":"Small retail businesses' social media adoption amid a crisis","authors":"Hongjoo Woo, Wi-Suk Kwon, A. Sadachar, Zhenghao Tong, Jimin Yang","doi":"10.1108/imds-06-2023-0377","DOIUrl":"https://doi.org/10.1108/imds-06-2023-0377","url":null,"abstract":"PurposeWhen retail businesses, especially small businesses with greater vulnerability, could not meet consumers in person during the recent pandemic crisis, how did they adapt to the situation? This study examined how small business practitioners (SBPs’) perceptions, trust and adoption intention levels for social media, as well as the relationships among these variables, changed before and during the crisis based on the integration of the contingency theory and the diffusion of innovation theory (DIT).Design/methodology/approachOnline surveys were conducted with USA SBPs before (n = 175) and during (n = 225) the recent pandemic. The hypotheses were tested using structural equation modeling (SEM), multivariate analysis of variance (MANOVA) and multiple-group SEM analysis.FindingsThe results confirmed significant sequential positive relationships between SBPs’ perceived external pressure and perceived benefits of adopting social media, which in turn led to their trust in and then adoption intentions for social media. Further, the comparisons between the pre- and in-pandemic samples revealed that SBPs’ perceptions and adoption intentions all became significantly higher during (vs before) the pandemic, but the structural relationships among these variables weakened during the pandemic.Originality/valueThis study uses a novel approach to integrate the contingency theory with the DIT to propose small businesses' perceptions, trust and adoption intentions for social media during the innovation decision process under rapid contingency changes. Our findings also offer practical implications including recommendations for small businesses’ innovation management as well as training programs.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"62 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139802238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.1108/imds-06-2023-0377
Hongjoo Woo, Wi-Suk Kwon, A. Sadachar, Zhenghao Tong, Jimin Yang
PurposeWhen retail businesses, especially small businesses with greater vulnerability, could not meet consumers in person during the recent pandemic crisis, how did they adapt to the situation? This study examined how small business practitioners (SBPs’) perceptions, trust and adoption intention levels for social media, as well as the relationships among these variables, changed before and during the crisis based on the integration of the contingency theory and the diffusion of innovation theory (DIT).Design/methodology/approachOnline surveys were conducted with USA SBPs before (n = 175) and during (n = 225) the recent pandemic. The hypotheses were tested using structural equation modeling (SEM), multivariate analysis of variance (MANOVA) and multiple-group SEM analysis.FindingsThe results confirmed significant sequential positive relationships between SBPs’ perceived external pressure and perceived benefits of adopting social media, which in turn led to their trust in and then adoption intentions for social media. Further, the comparisons between the pre- and in-pandemic samples revealed that SBPs’ perceptions and adoption intentions all became significantly higher during (vs before) the pandemic, but the structural relationships among these variables weakened during the pandemic.Originality/valueThis study uses a novel approach to integrate the contingency theory with the DIT to propose small businesses' perceptions, trust and adoption intentions for social media during the innovation decision process under rapid contingency changes. Our findings also offer practical implications including recommendations for small businesses’ innovation management as well as training programs.
目的在最近的大流行病危机中，当零售企业，尤其是更脆弱的小企业无法亲自与消费者见面时，他们是如何适应这种情况的？本研究在整合权变理论和创新扩散理论（DIT）的基础上，考察了小企业从业者（SBPs）在危机前和危机期间对社交媒体的认知、信任和采用意向水平，以及这些变量之间的关系。结果结果表明，SBPs 感知到的外部压力与感知到的采用社交媒体的益处之间存在显著的正向关系，这反过来又导致了他们对社交媒体的信任，进而产生了采用社交媒体的意愿。此外，大流行前和大流行中样本的比较显示，小企业在大流行期间（与大流行前相比）的感知和采用意向都显著提高，但这些变量之间的结构关系在大流行期间有所减弱。 原创性/价值 本研究采用一种新颖的方法，将权变理论与 DIT 相结合，提出了小企业在快速权变下的创新决策过程中对社交媒体的感知、信任和采用意向。我们的研究结果还具有实际意义，包括对小型企业创新管理和培训计划的建议。
{"title":"Small retail businesses' social media adoption amid a crisis","authors":"Hongjoo Woo, Wi-Suk Kwon, A. Sadachar, Zhenghao Tong, Jimin Yang","doi":"10.1108/imds-06-2023-0377","DOIUrl":"https://doi.org/10.1108/imds-06-2023-0377","url":null,"abstract":"PurposeWhen retail businesses, especially small businesses with greater vulnerability, could not meet consumers in person during the recent pandemic crisis, how did they adapt to the situation? This study examined how small business practitioners (SBPs’) perceptions, trust and adoption intention levels for social media, as well as the relationships among these variables, changed before and during the crisis based on the integration of the contingency theory and the diffusion of innovation theory (DIT).Design/methodology/approachOnline surveys were conducted with USA SBPs before (n = 175) and during (n = 225) the recent pandemic. The hypotheses were tested using structural equation modeling (SEM), multivariate analysis of variance (MANOVA) and multiple-group SEM analysis.FindingsThe results confirmed significant sequential positive relationships between SBPs’ perceived external pressure and perceived benefits of adopting social media, which in turn led to their trust in and then adoption intentions for social media. Further, the comparisons between the pre- and in-pandemic samples revealed that SBPs’ perceptions and adoption intentions all became significantly higher during (vs before) the pandemic, but the structural relationships among these variables weakened during the pandemic.Originality/valueThis study uses a novel approach to integrate the contingency theory with the DIT to propose small businesses' perceptions, trust and adoption intentions for social media during the innovation decision process under rapid contingency changes. Our findings also offer practical implications including recommendations for small businesses’ innovation management as well as training programs.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"34 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139862214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.1108/imds-04-2023-0231
Lin Wang, Huiyu Zhu, Xia Li, Yang Zhao
PurposeAlthough user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.Design/methodology/approachThe authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.FindingsThe authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.Originality/valueThis study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.
目的虽然用户粘性在电子商务直播领域已被研究了数年，但在这一领域，很少有人关注流媒体属性对用户粘性的影响。本研究以刺激-机体-反应（S-O-R）理论为基础，探讨了流媒体属性如何影响用户粘性。作者从中国电商直播用户中获取了 496 个有效样本，并使用偏最小二乘法结构方程建模（PLS-SEM）探讨了用户粘性的形成。人工神经网络（ANN）用于捕捉线性和非线性关系，并分析重要变量的归一化重要性排序，对 PLS-SEM 结果进行补充。专业知识和可信度对感知信息质量有积极影响。此外，流媒体品牌偏好在 PSI 与用户粘性之间以及感知信息质量与用户粘性之间起到了中介作用。与 PLS-SEM 相比，ANN 的预测能力更为稳健。此外，PLS-SEM 和 ANN 的结果都表明，吸引力是用户粘性的最强预测因子。原创性/价值本研究解释了流媒体属性如何影响用户粘性，为今后研究直播电商中的用户行为提供了参考价值。基于 ANN 对变量间线性和非线性关系的探索是对现有研究的补充。此外，本研究的结果对从业者如何提高用户粘性也有借鉴意义，有助于直播行业的发展。
{"title":"Formation mechanism of user stickiness in live e-commerce: the hybrid PLS-SEM and ANN approach","authors":"Lin Wang, Huiyu Zhu, Xia Li, Yang Zhao","doi":"10.1108/imds-04-2023-0231","DOIUrl":"https://doi.org/10.1108/imds-04-2023-0231","url":null,"abstract":"PurposeAlthough user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.Design/methodology/approachThe authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.FindingsThe authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.Originality/valueThis study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139871556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.1108/imds-04-2023-0231
Lin Wang, Huiyu Zhu, Xia Li, Yang Zhao
PurposeAlthough user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.Design/methodology/approachThe authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.FindingsThe authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.Originality/valueThis study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.
目的虽然用户粘性在电子商务直播领域已被研究了数年，但在这一领域，很少有人关注流媒体属性对用户粘性的影响。本研究以刺激-机体-反应（S-O-R）理论为基础，探讨了流媒体属性如何影响用户粘性。作者从中国电商直播用户中获取了 496 个有效样本，并使用偏最小二乘法结构方程建模（PLS-SEM）探讨了用户粘性的形成。人工神经网络（ANN）用于捕捉线性和非线性关系，并分析重要变量的归一化重要性排序，对 PLS-SEM 结果进行补充。专业知识和可信度对感知信息质量有积极影响。此外，流媒体品牌偏好在 PSI 与用户粘性之间以及感知信息质量与用户粘性之间起到了中介作用。与 PLS-SEM 相比，ANN 的预测能力更为稳健。此外，PLS-SEM 和 ANN 的结果都表明，吸引力是用户粘性的最强预测因子。原创性/价值本研究解释了流媒体属性如何影响用户粘性，为今后研究直播电商中的用户行为提供了参考价值。基于 ANN 对变量间线性和非线性关系的探索是对现有研究的补充。此外，本研究的结果对从业者如何提高用户粘性也有借鉴意义，有助于直播行业的发展。
{"title":"Formation mechanism of user stickiness in live e-commerce: the hybrid PLS-SEM and ANN approach","authors":"Lin Wang, Huiyu Zhu, Xia Li, Yang Zhao","doi":"10.1108/imds-04-2023-0231","DOIUrl":"https://doi.org/10.1108/imds-04-2023-0231","url":null,"abstract":"PurposeAlthough user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.Design/methodology/approachThe authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.FindingsThe authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.Originality/valueThis study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"37 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139811614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.1108/imds-08-2023-0532
Jianlan Zhong, Han Cheng, Fu Jia
PurposeDespite its crucial role in ensuring food safety, traceability remains underutilized by small and medium-sized enterprises (SMEs), a vital component of China’s agricultural supply chain, thereby compromising the integrity of the supply chain traceability system. Therefore, this study sets out to explore the factors influencing SMEs’ adoption of traceability systems and the impact of these factors on SMEs’ intent to adopt such systems. Furthermore, the study presents a model to deepen understanding of system adoption in SMEs and provides a simulation demonstrating the evolutionary trajectory of adoption behavior.Design/methodology/approachThis study considers the pivotal aspects of system adoption in SMEs, aiming to identify the influential factors through a grounded theory-based case study. Concurrently, it seeks to develop a mathematical model for SMEs’ adoption patterns and simulate the evolution of SMEs’ adoption behaviors using the Q-learning algorithm.FindingsThe adoption of traceability among SMEs is significantly influenced by factors such as system attributes, SMEs’ capability endowment, environmental factors and policy support and control. However, aspects of the SMEs’ capability endowment, specifically their learning rate and decay rate, have minimal impact on the adoption process. Furthermore, group pressure can expedite the attainment of an equilibrium state, wherein all SMEs adopt the system.Originality/valueThis study fills the existing knowledge gap about the adoption of traceability by SMEs in China’s agricultural supply chain. This study represents the pioneer study that identifies the factors influencing SMEs’ adoption and examines the effects of these factors on their traceability adoption, employing a multi-methodological approach that incorporates grounded theory, mathematical modeling and the Q-learning algorithm.
{"title":"Adoption decision of agricultural product traceability system in small and micro enterprises","authors":"Jianlan Zhong, Han Cheng, Fu Jia","doi":"10.1108/imds-08-2023-0532","DOIUrl":"https://doi.org/10.1108/imds-08-2023-0532","url":null,"abstract":"PurposeDespite its crucial role in ensuring food safety, traceability remains underutilized by small and medium-sized enterprises (SMEs), a vital component of China’s agricultural supply chain, thereby compromising the integrity of the supply chain traceability system. Therefore, this study sets out to explore the factors influencing SMEs’ adoption of traceability systems and the impact of these factors on SMEs’ intent to adopt such systems. Furthermore, the study presents a model to deepen understanding of system adoption in SMEs and provides a simulation demonstrating the evolutionary trajectory of adoption behavior.Design/methodology/approachThis study considers the pivotal aspects of system adoption in SMEs, aiming to identify the influential factors through a grounded theory-based case study. Concurrently, it seeks to develop a mathematical model for SMEs’ adoption patterns and simulate the evolution of SMEs’ adoption behaviors using the Q-learning algorithm.FindingsThe adoption of traceability among SMEs is significantly influenced by factors such as system attributes, SMEs’ capability endowment, environmental factors and policy support and control. However, aspects of the SMEs’ capability endowment, specifically their learning rate and decay rate, have minimal impact on the adoption process. Furthermore, group pressure can expedite the attainment of an equilibrium state, wherein all SMEs adopt the system.Originality/valueThis study fills the existing knowledge gap about the adoption of traceability by SMEs in China’s agricultural supply chain. This study represents the pioneer study that identifies the factors influencing SMEs’ adoption and examines the effects of these factors on their traceability adoption, employing a multi-methodological approach that incorporates grounded theory, mathematical modeling and the Q-learning algorithm.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"25 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139816555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.1108/imds-08-2023-0532
Jianlan Zhong, Han Cheng, Fu Jia
PurposeDespite its crucial role in ensuring food safety, traceability remains underutilized by small and medium-sized enterprises (SMEs), a vital component of China’s agricultural supply chain, thereby compromising the integrity of the supply chain traceability system. Therefore, this study sets out to explore the factors influencing SMEs’ adoption of traceability systems and the impact of these factors on SMEs’ intent to adopt such systems. Furthermore, the study presents a model to deepen understanding of system adoption in SMEs and provides a simulation demonstrating the evolutionary trajectory of adoption behavior.Design/methodology/approachThis study considers the pivotal aspects of system adoption in SMEs, aiming to identify the influential factors through a grounded theory-based case study. Concurrently, it seeks to develop a mathematical model for SMEs’ adoption patterns and simulate the evolution of SMEs’ adoption behaviors using the Q-learning algorithm.FindingsThe adoption of traceability among SMEs is significantly influenced by factors such as system attributes, SMEs’ capability endowment, environmental factors and policy support and control. However, aspects of the SMEs’ capability endowment, specifically their learning rate and decay rate, have minimal impact on the adoption process. Furthermore, group pressure can expedite the attainment of an equilibrium state, wherein all SMEs adopt the system.Originality/valueThis study fills the existing knowledge gap about the adoption of traceability by SMEs in China’s agricultural supply chain. This study represents the pioneer study that identifies the factors influencing SMEs’ adoption and examines the effects of these factors on their traceability adoption, employing a multi-methodological approach that incorporates grounded theory, mathematical modeling and the Q-learning algorithm.
{"title":"Adoption decision of agricultural product traceability system in small and micro enterprises","authors":"Jianlan Zhong, Han Cheng, Fu Jia","doi":"10.1108/imds-08-2023-0532","DOIUrl":"https://doi.org/10.1108/imds-08-2023-0532","url":null,"abstract":"PurposeDespite its crucial role in ensuring food safety, traceability remains underutilized by small and medium-sized enterprises (SMEs), a vital component of China’s agricultural supply chain, thereby compromising the integrity of the supply chain traceability system. Therefore, this study sets out to explore the factors influencing SMEs’ adoption of traceability systems and the impact of these factors on SMEs’ intent to adopt such systems. Furthermore, the study presents a model to deepen understanding of system adoption in SMEs and provides a simulation demonstrating the evolutionary trajectory of adoption behavior.Design/methodology/approachThis study considers the pivotal aspects of system adoption in SMEs, aiming to identify the influential factors through a grounded theory-based case study. Concurrently, it seeks to develop a mathematical model for SMEs’ adoption patterns and simulate the evolution of SMEs’ adoption behaviors using the Q-learning algorithm.FindingsThe adoption of traceability among SMEs is significantly influenced by factors such as system attributes, SMEs’ capability endowment, environmental factors and policy support and control. However, aspects of the SMEs’ capability endowment, specifically their learning rate and decay rate, have minimal impact on the adoption process. Furthermore, group pressure can expedite the attainment of an equilibrium state, wherein all SMEs adopt the system.Originality/valueThis study fills the existing knowledge gap about the adoption of traceability by SMEs in China’s agricultural supply chain. This study represents the pioneer study that identifies the factors influencing SMEs’ adoption and examines the effects of these factors on their traceability adoption, employing a multi-methodological approach that incorporates grounded theory, mathematical modeling and the Q-learning algorithm.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"7 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139876122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-24DOI: 10.1108/imds-07-2023-0517
Stuart John Barnes
PurposeColor psychology theory reveals that complex images with very varied palettes and many different colors are likely to be considered unattractive by individuals. Notwithstanding, web content containing social signals may be more attractive via the initiation of a social connection. This research investigates a predictive model blending variables from these theoretical perspectives to determine crowdfunding success.Design/methodology/approachThe research is based on data from 176,614 Kickstarter projects. A number of machine learning and artificial intelligence techniques were employed to analyze the listing images for color complexity and the presence of people, while specific language features, including socialness, were measured in the listing text. Logistic regression was applied, controlling for several additional variables and predictive model was developed.FindingsThe findings supported the color complexity and socialness effects on crowdfunding success. The model achieves notable predictive value explaining 56.4% of variance. Listing images containing fewer colors and that have more similar colors are more likely to be crowdfunded successfully. Listings that convey greater socialness have a greater likelihood of being funded.Originality/valueThis investigation contributes a unique understanding of the effect of features of both socialness and color complexity on the success of crowdfunding ventures. A second contribution comes from the process and methods employed in the study, which provides a clear blueprint for the processing of large-scale analysis of soft information (images and text) in order to use them as variables in the scientific testing of theory.
{"title":"Understanding the effects of socialness and color complexity in listing images on crowdfunding behavior","authors":"Stuart John Barnes","doi":"10.1108/imds-07-2023-0517","DOIUrl":"https://doi.org/10.1108/imds-07-2023-0517","url":null,"abstract":"PurposeColor psychology theory reveals that complex images with very varied palettes and many different colors are likely to be considered unattractive by individuals. Notwithstanding, web content containing social signals may be more attractive via the initiation of a social connection. This research investigates a predictive model blending variables from these theoretical perspectives to determine crowdfunding success.Design/methodology/approachThe research is based on data from 176,614 Kickstarter projects. A number of machine learning and artificial intelligence techniques were employed to analyze the listing images for color complexity and the presence of people, while specific language features, including socialness, were measured in the listing text. Logistic regression was applied, controlling for several additional variables and predictive model was developed.FindingsThe findings supported the color complexity and socialness effects on crowdfunding success. The model achieves notable predictive value explaining 56.4% of variance. Listing images containing fewer colors and that have more similar colors are more likely to be crowdfunded successfully. Listings that convey greater socialness have a greater likelihood of being funded.Originality/valueThis investigation contributes a unique understanding of the effect of features of both socialness and color complexity on the success of crowdfunding ventures. A second contribution comes from the process and methods employed in the study, which provides a clear blueprint for the processing of large-scale analysis of soft information (images and text) in order to use them as variables in the scientific testing of theory.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"50 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139599519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-16DOI: 10.1108/imds-03-2023-0173
J. Fang, Vincent C.S. Lee, Haiyan Wang
PurposeThis paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.Design/methodology/approachAn adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.FindingsThe results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.Practical implicationsThe findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.Originality/valueThis study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.
{"title":"Optimal service resource management strategy for IoT-based health information system considering value co-creation of users","authors":"J. Fang, Vincent C.S. Lee, Haiyan Wang","doi":"10.1108/imds-03-2023-0173","DOIUrl":"https://doi.org/10.1108/imds-03-2023-0173","url":null,"abstract":"PurposeThis paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.Design/methodology/approachAn adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.FindingsThe results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.Practical implicationsThe findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.Originality/valueThis study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":" 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139618839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-09DOI: 10.1108/imds-05-2023-0343
Pianpian Yang, Hong Sheng, Congcong Yang, Yuanyue Feng
PurposeThis research examines the underlying psychological process of customers' impulsive buying on social media through the lens of customer inspiration. Drawing on the customer inspiration theory, it identifies the factors influencing customer inspiration on social media from three perspectives: source characteristics, platform characteristics and personal characteristics, which subsequently lead to impulsive buying. Since the conceptualization of source credibility includes three mostly reported components: attractiveness, expertise and trustworthiness, it further contrasts the effects of three dimensions of source credibility on customer inspiration.Design/methodology/approachA structural equation model of customers' impulsive buying on social media was developed through the lens of customer inspiration. An online survey with 625 participants was conducted to test the hypotheses, and the partial least squares (PLS3) method was used.FindingsThis research found that source credibility, social presence and customer innovativeness are antecedents of customer inspiration on social media, which positively influence the inspired-by state of the customers, which impacts the inspired-to state and further leads to impulsive buying. By comparing the three dimensions of source credibility, the authors found that attractiveness and expertise positively affect the inspired-by state, while trustworthiness has no significant effect.Originality/valueThis research establishes the link between impulsive buying and customer inspiration, which provides a new psychological perspective to understand impulsive buying. In addition, it investigates the source characteristics of customer inspiration by comparing the effect of three dimensions of source credibility on customer inspiration, which provides the first evidence for connecting customer inspiration and source credibility.
{"title":"How social media promotes impulsive buying: examining the role of customer inspiration","authors":"Pianpian Yang, Hong Sheng, Congcong Yang, Yuanyue Feng","doi":"10.1108/imds-05-2023-0343","DOIUrl":"https://doi.org/10.1108/imds-05-2023-0343","url":null,"abstract":"PurposeThis research examines the underlying psychological process of customers' impulsive buying on social media through the lens of customer inspiration. Drawing on the customer inspiration theory, it identifies the factors influencing customer inspiration on social media from three perspectives: source characteristics, platform characteristics and personal characteristics, which subsequently lead to impulsive buying. Since the conceptualization of source credibility includes three mostly reported components: attractiveness, expertise and trustworthiness, it further contrasts the effects of three dimensions of source credibility on customer inspiration.Design/methodology/approachA structural equation model of customers' impulsive buying on social media was developed through the lens of customer inspiration. An online survey with 625 participants was conducted to test the hypotheses, and the partial least squares (PLS3) method was used.FindingsThis research found that source credibility, social presence and customer innovativeness are antecedents of customer inspiration on social media, which positively influence the inspired-by state of the customers, which impacts the inspired-to state and further leads to impulsive buying. By comparing the three dimensions of source credibility, the authors found that attractiveness and expertise positively affect the inspired-by state, while trustworthiness has no significant effect.Originality/valueThis research establishes the link between impulsive buying and customer inspiration, which provides a new psychological perspective to understand impulsive buying. In addition, it investigates the source characteristics of customer inspiration by comparing the effect of three dimensions of source credibility on customer inspiration, which provides the first evidence for connecting customer inspiration and source credibility.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139441721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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