Industrial Management & Data SystemsTable of Contents for Industrial Management & Data Systems. List of articles from the current issue, including Just Accepted (EarlyCite)https://www.emerald.com/insight/publication/issn/0263-5577/vol/124/iss/3?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestIndustrial Management & Data SystemsEmerald Publishing LimitedIndustrial Management & Data SystemsIndustrial Management & Data Systemshttps://www.emerald.com/insight/proxy/containerImg?link=/resource/publication/journal/f77e81ae89be8939a60895ef13e527fd/urn:emeraldgroup.com:asset:id:binary:imds.cover.jpghttps://www.emerald.com/insight/publication/issn/0263-5577/vol/124/iss/3?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThe diffusion of platform self-operation on reputation-based two-layer networkhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-06-2023-0356/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestDue to the cross-network effect, two-sided users communicate with each other, producing a coupling network. To study the spread of platform self-operation in two-sided users' marketing and purchasing tactics, this paper considers the differences in reputation acquired by platform-owned and third-party operating channels. This study proposes a two-layer network with cross-network links: one layer represents the social network of consumers, while the other layer represents the competitive network of buyers. A closed system of differential equations, based on the binary dynamics of the stochastic network, is developed to study the trend and stability points of the platform self-operation dissemination. Then the overall benefits of platform are analyzed to unify the platform diffusion and pricing strategies. The degree of difference in social influence and cross-network effects affect diffusion synergistically. Cross-network effects hinder diffusion when there is a significant difference of social influence between consumers and sellers but promote diffusion when there is little difference of social influence between consumers and sellers. Additionally, the network weights and reputation gap exhibit a nonlinear correlation with diffusion. For pricing strategy of the platform, it can achieve maximum profit when the pricing of self-operated goods and third-party-operated goods is equal. This study considers the complex network architecture created by bilateral markets and the dynamic influence of group interactions on product. Additionally, this study takes reputation into account when considering the price and dissemination tactics of various operating channels, offering guidelines for platforms to control merchants and mediate disputes between various operating channels.The diffusion of platform self-operation on reputation-based two-layer network
Ping Li, Bin Wu
Industrial Management & Data Systems, Vol. 124, No. 3, pp.949-977

Due to the cross-network effect, two-sided users communicate with each other, producing a coupling network. To study the spread of platform self-operation in two-sided users' marketing and purchasing tactics, this paper considers the differences in reputation acquired by platform-owned and third-party operating channels.

This study proposes a two-layer network with cross-network links: one layer represents the social network of consumers, while the other layer represents the competitive network of buyers. A closed system of differential equations, based on the binary dynamics of the stochastic network, is developed to study the trend and stability points of the platform self-operation dissemination. Then the overall benefits of platform are analyzed to unify the platform diffusion and pricing strategies.

The degree of difference in social influence and cross-network effects affect diffusion synergistically. Cross-network effects hinder diffusion when there is a significant difference of social influence between consumers and sellers but promote diffusion when there is little difference of social influence between consumers and sellers. Additionally, the network weights and reputation gap exhibit a nonlinear correlation with diffusion. For pricing strategy of the platform, it can achieve maximum profit when the pricing of self-operated goods and third-party-operated goods is equal.

This study considers the complex network architecture created by bilateral markets and the dynamic influence of group interactions on product. Additionally, this study takes reputation into account when considering the price and dissemination tactics of various operating channels, offering guidelines for platforms to control merchants and mediate disputes between various operating channels.

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The diffusion of platform self-operation on reputation-based two-layer network10.1108/IMDS-06-2023-0356Industrial Management & Data Systems2023-12-25© 2023 Emerald Publishing LimitedPing LiBin WuIndustrial Management & Data Systems12432023-12-2510.1108/IMDS-06-2023-0356https://www.emerald.com/insight/content/doi/10.1108/IMDS-06-2023-0356/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2023 Emerald Publishing Limited
Do knowledge sharing and big data analytics capabilities matter for green absorptive capacity and green entrepreneurship orientation? Implications for green innovationhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2023-0508/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThis study is the first to examine how big data analytics (BDA) capabilities affect green absorptive capacity (GAC) and green entrepreneurship orientation (GEO). It uses the dynamic capability view, BDA and knowledge-sharing literature. There is a lack of studies addressing the BDA–GAC and BDA–GEO relationships and their potential impact on green innovation. Continuing the ongoing research discussion, a few studies examined the vital implications of knowledge sharing (KS) on GAC, GEO and green innovation. The study used a cross-sectional and stratified random sampling technique to collect data through self-administered surveys among Chinese manufacturing firm employees. The study applied SmartPLS to analyze the obtained data. The findings revealed that BDA capabilities positively influence GAC and GEO. In addition, GEO and KS positively impact green innovation. The KS recorded a positive impact on GAC and GEO. Furthermore, GAC and GEO recorded a partial mediating effect. The study acknowledges that GAC is the backbone of a firm green entrepreneurial orientation, which needs to be aligned with BDA capabilities to anticipate future green business trends. GAC's help drives GEO's green business agenda. KS plays a strategic role in developing GAC, fostering GEO and improving green innovation. The study highlights the necessity of aligning BDA capabilities to fit firms' GEO green business agendas. This study focuses on the role of BDA capabilities in developing firms' green dynamics capabilities (e.g. GAC), which helps GEO drive superior green business growth. KS develops GAC and boosts GEO to enhance green innovation.Do knowledge sharing and big data analytics capabilities matter for green absorptive capacity and green entrepreneurship orientation? Implications for green innovation
Lahcene Makhloufi
Industrial Management & Data Systems, Vol. 124, No. 3, pp.978-1004

This study is the first to examine how big data analytics (BDA) capabilities affect green absorptive capacity (GAC) and green entrepreneurship orientation (GEO). It uses the dynamic capability view, BDA and knowledge-sharing literature. There is a lack of studies addressing the BDA–GAC and BDA–GEO relationships and their potential impact on green innovation. Continuing the ongoing research discussion, a few studies examined the vital implications of knowledge sharing (KS) on GAC, GEO and green innovation.

The study used a cross-sectional and stratified random sampling technique to collect data through self-administered surveys among Chinese manufacturing firm employees. The study applied SmartPLS to analyze the obtained data.

The findings revealed that BDA capabilities positively influence GAC and GEO. In addition, GEO and KS positively impact green innovation. The KS recorded a positive impact on GAC and GEO. Furthermore, GAC and GEO recorded a partial mediating effect.

The study acknowledges that GAC is the backbone of a firm green entrepreneurial orientation, which needs to be aligned with BDA capabilities to anticipate future green business trends. GAC's help drives GEO's green business agenda. KS plays a strategic role in developing GAC, fostering GEO and improving green innovation.

The study highlights the necessity of aligning BDA capabilities to fit firms' GEO green business agendas. This study focuses on the role of BDA capabilities in developing firms' green dynamics capabilities (e.g. GAC), which helps GEO drive superior green business growth. KS develops GAC and boosts GEO to enhance green innovation.

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Do knowledge sharing and big data analytics capabilities matter for green absorptive capacity and green entrepreneurship orientation? Implications for green innovation10.1108/IMDS-07-2023-0508Industrial Management & Data Systems2023-12-19© 2023 Emerald Publishing LimitedLahcene MakhloufiIndustrial Management & Data Systems12432023-12-1910.1108/IMDS-07-2023-0508https://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2023-0508/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2023 Emerald Publishing Limited
Logistics performance system and their impact on economic corridors: a developing economy perspectivehttps://www.emerald.com/insight/content/doi/10.1108/IMDS-03-2023-0151/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThis study aims to investigate the various systems in logistics industry of Pakistan through the lens of the World Bank's logistics performance indicators (LPI) and understand their impact on the China–Pakistan economic corridor (CPEC) that is a vital part of China's belt and road initiative (BRI). In this study thematic analysis was performed on twenty-three semi-structured interviews with experts in Pakistan's logistics and supply chain sector to gain an in-depth insight into the logistics performance relative to CPEC. A performance gap exists in the logistics systems in Pakistan, both for hard and soft infrastructure. The significant challenges are the inefficiencies of the government, minimal use of information and computing technology (ICT), and an incapable workforce. It is essential to be cognizant of the ground realities and amendments required in the existing policies and practices in light of the challenges faced and best practices adopted by developed and developing countries with good standing in logistics performance. This study will guide policymakers and practitioners for hard and soft logistics infrastructure improvement, which may benefit economic corridors in general and CPEC in particular. This study contributes to the existing literature by highlighting the role of ICT in improving both soft and hard logistics infrastructure, which can lead to significant development of economic corridors. The study makes use of a case study of the CPEC to demonstrate the lack of ICT can hamper the growth of an economic corridor despite billions of dollars of investment in the hard infrastructure development projects.Logistics performance system and their impact on economic corridors: a developing economy perspective
Muhammad Saleem Sumbal, Mujtaba Hassan Agha, Aleena Nisar, Felix T.S. Chan
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1005-1025

This study aims to investigate the various systems in logistics industry of Pakistan through the lens of the World Bank's logistics performance indicators (LPI) and understand their impact on the China–Pakistan economic corridor (CPEC) that is a vital part of China's belt and road initiative (BRI).

In this study thematic analysis was performed on twenty-three semi-structured interviews with experts in Pakistan's logistics and supply chain sector to gain an in-depth insight into the logistics performance relative to CPEC.

A performance gap exists in the logistics systems in Pakistan, both for hard and soft infrastructure. The significant challenges are the inefficiencies of the government, minimal use of information and computing technology (ICT), and an incapable workforce. It is essential to be cognizant of the ground realities and amendments required in the existing policies and practices in light of the challenges faced and best practices adopted by developed and developing countries with good standing in logistics performance. This study will guide policymakers and practitioners for hard and soft logistics infrastructure improvement, which may benefit economic corridors in general and CPEC in particular.

This study contributes to the existing literature by highlighting the role of ICT in improving both soft and hard logistics infrastructure, which can lead to significant development of economic corridors. The study makes use of a case study of the CPEC to demonstrate the lack of ICT can hamper the growth of an economic corridor despite billions of dollars of investment in the hard infrastructure development projects.

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Logistics performance system and their impact on economic corridors: a developing economy perspective10.1108/IMDS-03-2023-0151Industrial Management & Data Systems2023-12-25© 2023 Emerald Publishing LimitedMuhammad Saleem SumbalMujtaba Hassan AghaAleena NisarFelix T.S. ChanIndustrial Management & Data Systems12432023-12-2510.1108/IMDS-03-2023-0151https://www.emerald.com/insight/content/doi/10.1108/IMDS-03-2023-0151/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2023 Emerald Publishing Limited
A big data analytics method for the influence of WeChat public platform articles on blood donation behaviorhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0571/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThe purpose of this paper is to explore the impact and mechanism of WeChat public platforms articles (abbreviated as WPP) on blood donation behavior using data of WPPA and donation behavior data. This paper uses multiple linear regression methods, web crawlers and natural language processing technology. It first quantifies the impact of WPP published articles on donation behavior. On this basis, it then selects data from the day of article publication to further study the impact of article dissemination on donation behavior from the perspective of reading quantity, and analyzes the influencing factors of article reading quantity. The results show that on the same day that an article is published, there is an increase of 13.8 and 14.3% in blood donation volume and fan registrations, respectively. The mediating effect exists. However, the day after an article is published, there is no longer any effect on blood donations. With a 1% increase in reading quantity, blood donation volume on the day of article publication increases by 0.13%, and this positive impact is promoted by the quality of the articles. A conc ise articles title and body and rich images help drive reading quantity. Moreover, blood donors prefer to read articles about blood dynamics and donation promotion, while articles about news, announcements and administrative affairs make them less inclined to read. First, it focuses on WPPA, quantifies the impact of articles on blood donation behavior and analyzes the mechanism. Second, the authors study the impact and timeliness of social media article dissemination to address the insufficiency of existing research. Third, the study provides a scientific basis for the editing and publishing of articles, helping blood banks improve the effectiveness of publicity and recruitment.A big data analytics method for the influence of WeChat public platform articles on blood donation behavior
Xinyu Guo, Xu Chen, Xiaoke Liang
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1026-1049

The purpose of this paper is to explore the impact and mechanism of WeChat public platforms articles (abbreviated as WPP) on blood donation behavior using data of WPPA and donation behavior data.

This paper uses multiple linear regression methods, web crawlers and natural language processing technology. It first quantifies the impact of WPP published articles on donation behavior. On this basis, it then selects data from the day of article publication to further study the impact of article dissemination on donation behavior from the perspective of reading quantity, and analyzes the influencing factors of article reading quantity.

The results show that on the same day that an article is published, there is an increase of 13.8 and 14.3% in blood donation volume and fan registrations, respectively. The mediating effect exists. However, the day after an article is published, there is no longer any effect on blood donations. With a 1% increase in reading quantity, blood donation volume on the day of article publication increases by 0.13%, and this positive impact is promoted by the quality of the articles. A conc ise articles title and body and rich images help drive reading quantity. Moreover, blood donors prefer to read articles about blood dynamics and donation promotion, while articles about news, announcements and administrative affairs make them less inclined to read.

First, it focuses on WPPA, quantifies the impact of articles on blood donation behavior and analyzes the mechanism. Second, the authors study the impact and timeliness of social media article dissemination to address the insufficiency of existing research. Third, the study provides a scientific basis for the editing and publishing of articles, helping blood banks improve the effectiveness of publicity and recruitment.

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A big data analytics method for the influence of WeChat public platform articles on blood donation behavior10.1108/IMDS-08-2023-0571Industrial Management & Data Systems2023-12-26© 2023 Emerald Publishing LimitedXinyu GuoXu ChenXiaoke LiangIndustrial Management & Data Systems12432023-12-2610.1108/IMDS-08-2023-0571https://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0571/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2023 Emerald Publishing Limited
Acceptance of digital twins of customer demands for supply chain optimisation: an analysis of three hierarchical digital twin levelshttps://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2023-0467/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestInaccurate capturing and processing of customer requirements result in negative economic and ecological effects. Digital twins of customer demands promise to remedy these issues. However, successful implementation necessitates users' technology acceptance. This study contrasts three hierarchical digital twin levels with different degrees of user integration and examines determinants for their respective acceptance. A structural equation model is applied in a comparative manner, considering different levels of digital twin radicalness. A multidimensional approach is used to measure attitudes towards usage. Data are collected in the context of organisational supply management. Results show harmonious effects across digital twin levels. This indicates that technological radicality plays only a subordinate role when assessing acceptance determinants such as user perception on ease of use, usefulness, trust and risk. Rather than focussing solely on technological factors, findings suggest that users prioritise the actual outcome and efficiency of the system. This perspective offers practical implications for organisations seeking to implement advanced systems and emphasises the significance of user perceptions beyond technological features. The societal impact of this research are an appreciation of customer roles in the supply chain where an enhanced detection of customer needs and preferences aligns businesses with the dynamic and evolving demands of a diverse and a continuously environmentally-conscious consumer base. This study applies a measurement model for technology acceptance in a unique and multidimensional manner. Thereby, a comparative analysis of user perceptions across different digital twin levels sheds more light on a nascent, promising and underexplored technological method. This interdisciplinary research combined knowledge from the supply chain management and management information systems fields by highlighting key factors for the adoption of complex technological methods.Acceptance of digital twins of customer demands for supply chain optimisation: an analysis of three hierarchical digital twin levels
Dominik Oehlschläger, Andreas H. Glas, Michael Eßig
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1050-1075

Inaccurate capturing and processing of customer requirements result in negative economic and ecological effects. Digital twins of customer demands promise to remedy these issues. However, successful implementation necessitates users' technology acceptance. This study contrasts three hierarchical digital twin levels with different degrees of user integration and examines determinants for their respective acceptance.

A structural equation model is applied in a comparative manner, considering different levels of digital twin radicalness. A multidimensional approach is used to measure attitudes towards usage. Data are collected in the context of organisational supply management.

Results show harmonious effects across digital twin levels. This indicates that technological radicality plays only a subordinate role when assessing acceptance determinants such as user perception on ease of use, usefulness, trust and risk.

Rather than focussing solely on technological factors, findings suggest that users prioritise the actual outcome and efficiency of the system. This perspective offers practical implications for organisations seeking to implement advanced systems and emphasises the significance of user perceptions beyond technological features.

The societal impact of this research are an appreciation of customer roles in the supply chain where an enhanced detection of customer needs and preferences aligns businesses with the dynamic and evolving demands of a diverse and a continuously environmentally-conscious consumer base.

This study applies a measurement model for technology acceptance in a unique and multidimensional manner. Thereby, a comparative analysis of user perceptions across different digital twin levels sheds more light on a nascent, promising and underexplored technological method. This interdisciplinary research combined knowledge from the supply chain management and management information systems fields by highlighting key factors for the adoption of complex technological methods.

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Acceptance of digital twins of customer demands for supply chain optimisation: an analysis of three hierarchical digital twin levels10.1108/IMDS-07-2023-0467Industrial Management & Data Systems2023-12-26© 2023 Emerald Publishing LimitedDominik OehlschlägerAndreas H. GlasMichael EßigIndustrial Management & Data Systems12432023-12-2610.1108/IMDS-07-2023-0467https://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2023-0467/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2023 Emerald Publishing Limited
An electric vehicle routing model with charging stations consideration for sustainable logisticshttps://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0581/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestRecently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process. This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China. The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions. The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics. In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.An electric vehicle routing model with charging stations consideration for sustainable logistics
Yan Li, Ming K. Lim, Weiqing Xiong, Xingjun Huang, Yuhe Shi, Songyi Wang
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1076-1106

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

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An electric vehicle routing model with charging stations consideration for sustainable logistics10.1108/IMDS-08-2023-0581Industrial Management & Data Systems2023-12-26© 2023 Emerald Publishing LimitedYan LiMing K. LimWeiqing XiongXingjun HuangYuhe ShiSongyi WangIndustrial Management & Data Systems12432023-12-2610.1108/IMDS-08-2023-0581https://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0581/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2023 Emerald Publishing Limited
Improving digital work experience: an experimental investigation of IT identity and organization supporthttps://www.emerald.com/insight/content/doi/10.1108/IMDS-02-2023-0128/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestImproving digital work experience is critical for the job performance of individuals and the competitiveness of organizations due to their increasing use. This paper investigates how organization support affects the digital work experience of individuals differently depending on their levels of information technology (IT) identity. Drawing upon the IT identity literature and the conservation of resources (COR) theory, a conceptual model is developed, tested and validated using the data collected in Australia through an experimental design in which IT identity is manipulated. This study reveals a nuanced impact of organization support on shaping digital work experience. Specifically, it finds that technical support is more effective in improving the digital work experience of individuals with a high level of IT identity, whereas well-being support is more effective in enhancing the digital work experience of individuals with a low level of IT identity. This research contributes to the IT identity literature by introducing a novel experimental design to manipulate IT identity in the digital work context. It also contributes to the digital work literature by introducing a resource perspective for identifying well-being support, technical support and IT identity as the key resources in shaping digital work experience and calling for attention to IT identity as a boundary condition on the effectiveness of organization support. The findings can help organizations formulate better strategies and policies to improve digital work experience by providing tailored support to individuals with different levels of IT identity.Improving digital work experience: an experimental investigation of IT identity and organization support
Shea X. Fan, Sophia Xiaoxia Duan, Hepu Deng
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1107-1131

Improving digital work experience is critical for the job performance of individuals and the competitiveness of organizations due to their increasing use. This paper investigates how organization support affects the digital work experience of individuals differently depending on their levels of information technology (IT) identity.

Drawing upon the IT identity literature and the conservation of resources (COR) theory, a conceptual model is developed, tested and validated using the data collected in Australia through an experimental design in which IT identity is manipulated.

This study reveals a nuanced impact of organization support on shaping digital work experience. Specifically, it finds that technical support is more effective in improving the digital work experience of individuals with a high level of IT identity, whereas well-being support is more effective in enhancing the digital work experience of individuals with a low level of IT identity.

This research contributes to the IT identity literature by introducing a novel experimental design to manipulate IT identity in the digital work context. It also contributes to the digital work literature by introducing a resource perspective for identifying well-being support, technical support and IT identity as the key resources in shaping digital work experience and calling for attention to IT identity as a boundary condition on the effectiveness of organization support. The findings can help organizations formulate better strategies and policies to improve digital work experience by providing tailored support to individuals with different levels of IT identity.

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Improving digital work experience: an experimental investigation of IT identity and organization support10.1108/IMDS-02-2023-0128Industrial Management & Data Systems2024-01-09© 2023 Emerald Publishing LimitedShea X. FanSophia Xiaoxia DuanHepu DengIndustrial Management & Data Systems12432024-01-0910.1108/IMDS-02-2023-0128https://www.emerald.com/insight/content/doi/10.1108/IMDS-02-2023-0128/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2023 Emerald Publishing Limited
Optimal service resource management strategy for IoT-based health information system considering value co-creation of usershttps://www.emerald.com/insight/content/doi/10.1108/IMDS-03-2023-0173/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThis 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. An 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. The 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. The findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs. This 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.Optimal service resource management strategy for IoT-based health information system considering value co-creation of users
Ji Fang, Vincent C.S. Lee, Haiyan Wang
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1132-1154

This 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.

An 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.

The 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.

The findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.

This 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.

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Optimal service resource management strategy for IoT-based health information system considering value co-creation of users10.1108/IMDS-03-2023-0173Industrial Management & Data Systems2024-01-16© 2024 Emerald Publishing LimitedJi FangVincent C.S. LeeHaiyan WangIndustrial Management & Data Systems12432024-01-1610.1108/IMDS-03-2023-0173https://www.emerald.com/insight/content/doi/10.1108/IMDS-03-2023-0173/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Configuring mobile app update strategy for growth: An empirical analysis of a landscape search modelhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-03-2023-0181/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThis study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment. Using a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance. This study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology. This study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.Configuring mobile app update strategy for growth: An empirical analysis of a landscape search model
Fei Wang, Ning Nan, Jing Zhao
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1155-1178

This study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.

Using a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.

This study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.

This study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.

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Configuring mobile app update strategy for growth: An empirical analysis of a landscape search model10.1108/IMDS-03-2023-0181Industrial Management & Data Systems2024-01-22© 2024 Emerald Publishing LimitedFei WangNing NanJing ZhaoIndustrial Management & Data Systems12432024-01-2210.1108/IMDS-03-2023-0181https://www.emerald.com/insight/content/doi/10.1108/IMDS-03-2023-0181/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Understanding the effects of socialness and color complexity in listing images on crowdfunding behaviorhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2023-0517/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestColor 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. The 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. The 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. This 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.Understanding the effects of socialness and color complexity in listing images on crowdfunding behavior
Stuart John Barnes
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1179-1202

Color 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.

The 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.

The 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.

This 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.

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Understanding the effects of socialness and color complexity in listing images on crowdfunding behavior10.1108/IMDS-07-2023-0517Industrial Management & Data Systems2024-01-24© 2024 Emerald Publishing LimitedStuart John BarnesIndustrial Management & Data Systems12432024-01-2410.1108/IMDS-07-2023-0517https://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2023-0517/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Big data analytics capability in building supply chain resilience: the moderating effect of innovation-focused complementary assetshttps://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2022-0411/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThis research investigates the mechanism by which big data capability enables superior supply chain resilience (SCRe) by empirically examining the links among big data analytics (BDA), supply chain flexibility (SCF) and SCRe, with innovation-focused complementary assets (CA-I) as the moderator. Extensive surveys were conducted to gather 308 responses from Malaysian manufacturing firms in order to explore this framework. The structural and measurement models were examined and evaluated by using partial least squares structural equation modelling. The findings revealed that BDA is linked to flexibilities in a manufacturing firm’s value chain, which in turn is related to the firm’s SCRe. However, the association between BDA and SCRe is surprisingly non-significant. Additionally, CA-I was discovered to moderate the connections between all of the constructs, except for the relationship between BDA and SCRe. Such findings imply that with the aim of enhancing resilience, a company should concentrate on SCF; and that BDA capability is a prerequisite for increasing these flexibilities. This research extrapolates the findings of previous studies regarding BDA’s influence on SCRe by investigating the indirect effect of SCF, as well as the moderating influence of CA-I. This research is one of the first few studies to empirically examine the relationships between BDA, SCF and SCRe across manufacturing firms, with CA-I acting as a moderator.Big data analytics capability in building supply chain resilience: the moderating effect of innovation-focused complementary assets
Voon Hsien Lee, Pik-Yin Foo, Tat-Huei Cham, Teck-Soon Hew, Garry Wei-Han Tan, Keng-Boon Ooi
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1203-1233

This research investigates the mechanism by which big data capability enables superior supply chain resilience (SCRe) by empirically examining the links among big data analytics (BDA), supply chain flexibility (SCF) and SCRe, with innovation-focused complementary assets (CA-I) as the moderator.

Extensive surveys were conducted to gather 308 responses from Malaysian manufacturing firms in order to explore this framework. The structural and measurement models were examined and evaluated by using partial least squares structural equation modelling.

The findings revealed that BDA is linked to flexibilities in a manufacturing firm’s value chain, which in turn is related to the firm’s SCRe. However, the association between BDA and SCRe is surprisingly non-significant. Additionally, CA-I was discovered to moderate the connections between all of the constructs, except for the relationship between BDA and SCRe. Such findings imply that with the aim of enhancing resilience, a company should concentrate on SCF; and that BDA capability is a prerequisite for increasing these flexibilities.

This research extrapolates the findings of previous studies regarding BDA’s influence on SCRe by investigating the indirect effect of SCF, as well as the moderating influence of CA-I. This research is one of the first few studies to empirically examine the relationships between BDA, SCF and SCRe across manufacturing firms, with CA-I acting as a moderator.

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Big data analytics capability in building supply chain resilience: the moderating effect of innovation-focused complementary assets10.1108/IMDS-07-2022-0411Industrial Management & Data Systems2024-01-29© 2024 Emerald Publishing LimitedVoon Hsien LeePik-Yin FooTat-Huei ChamTeck-Soon HewGarry Wei-Han TanKeng-Boon OoiIndustrial Management & Data Systems12432024-01-2910.1108/IMDS-07-2022-0411https://www.emerald.com/insight/content/doi/10.1108/IMDS-07-2022-0411/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Formation mechanism of user stickiness in live e-commerce: the hybrid PLS-SEM and ANN approachhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-04-2023-0231/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestAlthough 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. The 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. The 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. This 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.Formation mechanism of user stickiness in live e-commerce: the hybrid PLS-SEM and ANN approach
Lin Wang, Huiyu Zhu, Xia Li, Yang Zhao
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1234-1262

Although 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.

The 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.

The 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.

This 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.

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Formation mechanism of user stickiness in live e-commerce: the hybrid PLS-SEM and ANN approach10.1108/IMDS-04-2023-0231Industrial Management & Data Systems2024-02-02© 2024 Emerald Publishing LimitedLin WangHuiyu ZhuXia LiYang ZhaoIndustrial Management & Data Systems12432024-02-0210.1108/IMDS-04-2023-0231https://www.emerald.com/insight/content/doi/10.1108/IMDS-04-2023-0231/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Adoption decision of agricultural product traceability system in small and micro enterpriseshttps://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0532/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestDespite 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. This 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. The 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. This 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.Adoption decision of agricultural product traceability system in small and micro enterprises
Jianlan Zhong, Han Cheng, Fu Jia
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1263-1298

Despite 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.

This 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.

The 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.

This 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.

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Adoption decision of agricultural product traceability system in small and micro enterprises10.1108/IMDS-08-2023-0532Industrial Management & Data Systems2024-02-01© 2024 Emerald Publishing LimitedJianlan ZhongHan ChengFu JiaIndustrial Management & Data Systems12432024-02-0110.1108/IMDS-08-2023-0532https://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0532/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Small retail businesses' social media adoption amid a crisishttps://www.emerald.com/insight/content/doi/10.1108/IMDS-06-2023-0377/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestWhen 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). Online 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. The 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. This 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.Small retail businesses' social media adoption amid a crisis
Hongjoo Woo, Wi-Suk Kwon, Amrut Sadachar, Zhenghao Tong, Jimin Yang
Industrial Management & Data Systems, Vol. 124, No. 3, pp.1299-1325

When 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).

Online 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.

The 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.

This 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.

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Small retail businesses' social media adoption amid a crisis10.1108/IMDS-06-2023-0377Industrial Management & Data Systems2024-02-06© 2024 Emerald Publishing LimitedHongjoo WooWi-Suk KwonAmrut SadacharZhenghao TongJimin YangIndustrial Management & Data Systems12432024-02-0610.1108/IMDS-06-2023-0377https://www.emerald.com/insight/content/doi/10.1108/IMDS-06-2023-0377/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Like it, buy it? Examining the role of bookmarking in the mediation of visual appeal and purchase intent from a dual-system perspectivehttps://www.emerald.com/insight/content/doi/10.1108/IMDS-02-2023-0131/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestWhile prior studies have explored the relationship between visual appeal and purchasing decisions, the role of bookmarking has largely been underemphasized. This research aims to address this gap by focusing on the impact of bookmarking on consumer behavior, guided by the cognitive load theory and dual-system theory. The authors executed a controlled experiment and analyzed the results using a two-stage regression method that linked visual appeal, bookmarking and purchase intent. Further empirical analysis was conducted to authenticate the authors' proposed model, utilizing real-world mobile commerce data from a clothing company. This study's findings suggest that visual appeal influences purchase intent primarily through the full mediation of bookmarking, rather than exerting a direct influence. Furthermore, an increase in colorfulness corresponds positively with visual appeal, while visual complexity exhibits an inverted U-shaped relationship with it. This study provides novel insights into the choice-set formation process through the theoretical lens of dual-system theory. Additionally, the authors employed an image processing technique to quantify a product's visual appeal as depicted in a photograph. This study also incorporates a comprehensive econometric analysis to connect the objective aspects of visual appeal with subjective responses.Like it, buy it? Examining the role of bookmarking in the mediation of visual appeal and purchase intent from a dual-system perspective
Youngjoon Yu, Jae-Hyeon Ahn, Dongyeon Kim, Kyuhong Park
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

While prior studies have explored the relationship between visual appeal and purchasing decisions, the role of bookmarking has largely been underemphasized. This research aims to address this gap by focusing on the impact of bookmarking on consumer behavior, guided by the cognitive load theory and dual-system theory.

The authors executed a controlled experiment and analyzed the results using a two-stage regression method that linked visual appeal, bookmarking and purchase intent. Further empirical analysis was conducted to authenticate the authors' proposed model, utilizing real-world mobile commerce data from a clothing company.

This study's findings suggest that visual appeal influences purchase intent primarily through the full mediation of bookmarking, rather than exerting a direct influence. Furthermore, an increase in colorfulness corresponds positively with visual appeal, while visual complexity exhibits an inverted U-shaped relationship with it.

This study provides novel insights into the choice-set formation process through the theoretical lens of dual-system theory. Additionally, the authors employed an image processing technique to quantify a product's visual appeal as depicted in a photograph. This study also incorporates a comprehensive econometric analysis to connect the objective aspects of visual appeal with subjective responses.

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Like it, buy it? Examining the role of bookmarking in the mediation of visual appeal and purchase intent from a dual-system perspective10.1108/IMDS-02-2023-0131Industrial Management & Data Systems2024-01-01© 2023 Emerald Publishing LimitedYoungjoon YuJae-Hyeon AhnDongyeon KimKyuhong ParkIndustrial Management & Data Systemsahead-of-printahead-of-print2024-01-0110.1108/IMDS-02-2023-0131https://www.emerald.com/insight/content/doi/10.1108/IMDS-02-2023-0131/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2023 Emerald Publishing Limited
Publishers notehttps://www.emerald.com/insight/content/doi/10.1108/IMDS-03-2019-0194/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestPublishers notePublishers note
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-]]>
Publishers note10.1108/IMDS-03-2019-0194Industrial Management & Data Systems2020-08-31© 2020 Emerald Publishing LimitedIndustrial Management & Data Systemsahead-of-printahead-of-print2020-08-3110.1108/IMDS-03-2019-0194https://www.emerald.com/insight/content/doi/10.1108/IMDS-03-2019-0194/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2020 Emerald Publishing Limited
Enterprise social media and knowledge creation capability: a comparison between pre- and post-COVID-19 pandemichttps://www.emerald.com/insight/content/doi/10.1108/IMDS-05-2023-0300/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestDrawing upon the theory of communication visibility, this research intends to investigate the direct effect of enterprise social media (ESM) usage on team members’ knowledge creation capability (KCC) and the mediating effects of psychological safety and team identification. In addition, it aims to untangle how the efficacy of ESM usage varies between pre- and post-COVID-19 periods. Using two-wave survey data from 240 members nested within 60 teams, this study utilizes a multilevel approach to test the proposed hypotheses. We discover that ESM usage enhances team members’ KCC. More importantly, the results show that psychological safety and team identification mediate the ESM–KCC linkage. Interestingly, we further find that the impacts of ESM usage on team members’ KCC, psychological safety, and team identification are stronger in the pre-COVID-19 period than those in the post-COVID-19 period. This research sheds light on the ESM literature by unraveling the mechanisms of psychological safety and team identification underlying the linkage between ESM usage and team members’ KCC. Moreover, it advances our understanding of the differential efficacy of ESM usage in pre- and post-COVID-19 periods.Enterprise social media and knowledge creation capability: a comparison between pre- and post-COVID-19 pandemic
Jing Dai, Dong Xu, Jinan Shao, Jia Jia Lim, Wuyue Shangguan
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

Drawing upon the theory of communication visibility, this research intends to investigate the direct effect of enterprise social media (ESM) usage on team members’ knowledge creation capability (KCC) and the mediating effects of psychological safety and team identification. In addition, it aims to untangle how the efficacy of ESM usage varies between pre- and post-COVID-19 periods.

Using two-wave survey data from 240 members nested within 60 teams, this study utilizes a multilevel approach to test the proposed hypotheses.

We discover that ESM usage enhances team members’ KCC. More importantly, the results show that psychological safety and team identification mediate the ESM–KCC linkage. Interestingly, we further find that the impacts of ESM usage on team members’ KCC, psychological safety, and team identification are stronger in the pre-COVID-19 period than those in the post-COVID-19 period.

This research sheds light on the ESM literature by unraveling the mechanisms of psychological safety and team identification underlying the linkage between ESM usage and team members’ KCC. Moreover, it advances our understanding of the differential efficacy of ESM usage in pre- and post-COVID-19 periods.

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Enterprise social media and knowledge creation capability: a comparison between pre- and post-COVID-19 pandemic10.1108/IMDS-05-2023-0300Industrial Management & Data Systems2024-02-15© 2024 Emerald Publishing LimitedJing DaiDong XuJinan ShaoJia Jia LimWuyue ShangguanIndustrial Management & Data Systemsahead-of-printahead-of-print2024-02-1510.1108/IMDS-05-2023-0300https://www.emerald.com/insight/content/doi/10.1108/IMDS-05-2023-0300/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Is UGC sentiment helpful for recommendation? An application of sentiment-based recommendation modelhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-05-2023-0335/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestGiven the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China. After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis. The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies. The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types. This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.Is UGC sentiment helpful for recommendation? An application of sentiment-based recommendation model
Mengyang Gao, Jun Wang, Ou Liu
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.

After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.

The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.

The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.

This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.

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Is UGC sentiment helpful for recommendation? An application of sentiment-based recommendation model10.1108/IMDS-05-2023-0335Industrial Management & Data Systems2024-02-16© 2024 Emerald Publishing LimitedMengyang GaoJun WangOu LiuIndustrial Management & Data Systemsahead-of-printahead-of-print2024-02-1610.1108/IMDS-05-2023-0335https://www.emerald.com/insight/content/doi/10.1108/IMDS-05-2023-0335/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Optimal channel selection considering price competition and information sharing under demand uncertaintyhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-06-2023-0419/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThe rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty. This study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate. This study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel. This research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.Optimal channel selection considering price competition and information sharing under demand uncertainty
Nan Chen, Jianfeng Cai, Devika Kannan, Kannan Govindan
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

The rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty.

This study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate.

This study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel.

This research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.

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Optimal channel selection considering price competition and information sharing under demand uncertainty10.1108/IMDS-06-2023-0419Industrial Management & Data Systems2024-03-13© 2024 Emerald Publishing LimitedNan ChenJianfeng CaiDevika KannanKannan GovindanIndustrial Management & Data Systemsahead-of-printahead-of-print2024-03-1310.1108/IMDS-06-2023-0419https://www.emerald.com/insight/content/doi/10.1108/IMDS-06-2023-0419/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Knowledge trajectory of eSports as an emerging field of researchhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-06-2023-0423/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestResearch on electric sports (eSports) has experienced significant growth in recent years as a consequence of increasing connectivity, institutionalization, and technological advances. However, the interdisciplinary nature of the eSports as a field and the burgeoning growth in eSports articles have rendered it necessary to conduct a systematic review of extant literature to take stock of the knowledge accumulated. To this end, we aim to undertake a comprehensive review of extant literature that takes stock of published research to derive opportunities for future research in the realm of eSports. In so doing, we contribute to the advancement of the field by mapping out the knowledge trajectory of eSports research and elucidating areas that have remained underexplored thus far. To conduct systematic review of the eSports literature, we employed a framework that included six essential steps: protocol, search, appraisal, synthesis, analysis, and report. This comprehensive approach enables us to meticulously investigate the existing body of literature on eSports and identify key trends and topics addressed within the field. By conducting the multidisciplinary systematic literature review, we thoroughly assess the current state of eSports literature and subsequently outline potential research avenues that can contribute to eSports fields. This study draws on a six-phase framework – member preparation, team formation, character selection, team coordination, team performance, and team reflection – to illustrate the roles played by different levels of analysis unit (i.e. characters, players, and teams) and three distinct yet interconnected stages (i.e. inputs, process, and outputs) within eSports games as well as the research opportunities it brings. We conducted a rigorous systematic review of the eSports literature by using quantitative citation analysis and qualitative content analysis. Furthermore, we adopted team dynamic view of eSports to identify potential research avenues for future research that contribute to advancing our understanding of the eSports tournaments.Knowledge trajectory of eSports as an emerging field of research
Jiantao Zhu, Chuhan Cao, Hefu Liu, Eric Tze Kuan Lim, Chee-Wee Tan
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

Research on electric sports (eSports) has experienced significant growth in recent years as a consequence of increasing connectivity, institutionalization, and technological advances. However, the interdisciplinary nature of the eSports as a field and the burgeoning growth in eSports articles have rendered it necessary to conduct a systematic review of extant literature to take stock of the knowledge accumulated. To this end, we aim to undertake a comprehensive review of extant literature that takes stock of published research to derive opportunities for future research in the realm of eSports. In so doing, we contribute to the advancement of the field by mapping out the knowledge trajectory of eSports research and elucidating areas that have remained underexplored thus far.

To conduct systematic review of the eSports literature, we employed a framework that included six essential steps: protocol, search, appraisal, synthesis, analysis, and report. This comprehensive approach enables us to meticulously investigate the existing body of literature on eSports and identify key trends and topics addressed within the field. By conducting the multidisciplinary systematic literature review, we thoroughly assess the current state of eSports literature and subsequently outline potential research avenues that can contribute to eSports fields.

This study draws on a six-phase framework – member preparation, team formation, character selection, team coordination, team performance, and team reflection – to illustrate the roles played by different levels of analysis unit (i.e. characters, players, and teams) and three distinct yet interconnected stages (i.e. inputs, process, and outputs) within eSports games as well as the research opportunities it brings.

We conducted a rigorous systematic review of the eSports literature by using quantitative citation analysis and qualitative content analysis. Furthermore, we adopted team dynamic view of eSports to identify potential research avenues for future research that contribute to advancing our understanding of the eSports tournaments.

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Knowledge trajectory of eSports as an emerging field of research10.1108/IMDS-06-2023-0423Industrial Management & Data Systems2024-03-15© 2024 Emerald Publishing LimitedJiantao ZhuChuhan CaoHefu LiuEric Tze Kuan LimChee-Wee TanIndustrial Management & Data Systemsahead-of-printahead-of-print2024-03-1510.1108/IMDS-06-2023-0423https://www.emerald.com/insight/content/doi/10.1108/IMDS-06-2023-0423/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Assessing impacts of emergency industry demonstration on firm profitability: the role of blockchain strategies and technologieshttps://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0559/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThe objective of this study is to explore the impact of a government-supported initiative for operational security, specifically the establishment of the national security emergency industry demonstration base, on the profitability of local publicly traded companies. Additionally, the study investigates the significance of firms' blockchain strategies and technologies within this framework. Using the differences-in-differences (DID) approach, this study evaluates the impact of China's national security emergency industry demonstration bases (2015–2022) on the profitability of local firms. Data from the China Research Data Service (CNRDS) platform and investor Q&As informed our analysis of firms' blockchain strategy and technology, underpinned by detailed data collection and a robust DID model. Emergency industry demonstration bases have notably boosted enterprise profitability in both return on assets (ROA) and return on equity (ROE). Companies adopting blockchain strategies and operational technology see a clear rise in profitability over non-blockchain peers. Additionally, the technical operation of blockchain presents a more pronounced advantage than at the strategic level. We introduced a new perspective, emphasizing the enhancement of corporate operational safety and financial performance through the pathway of emergency industry policies, driven by the collaboration between government and businesses. Furthermore, we delved into the potential application value of blockchain strategies and technologies in enhancing operational security and the emergency industry.Assessing impacts of emergency industry demonstration on firm profitability: the role of blockchain strategies and technologies
Yingjie Ju, Jianliang Yang, Jingping Ma, Yuehang Hou
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

The objective of this study is to explore the impact of a government-supported initiative for operational security, specifically the establishment of the national security emergency industry demonstration base, on the profitability of local publicly traded companies. Additionally, the study investigates the significance of firms' blockchain strategies and technologies within this framework.

Using the differences-in-differences (DID) approach, this study evaluates the impact of China's national security emergency industry demonstration bases (2015–2022) on the profitability of local firms. Data from the China Research Data Service (CNRDS) platform and investor Q&As informed our analysis of firms' blockchain strategy and technology, underpinned by detailed data collection and a robust DID model.

Emergency industry demonstration bases have notably boosted enterprise profitability in both return on assets (ROA) and return on equity (ROE). Companies adopting blockchain strategies and operational technology see a clear rise in profitability over non-blockchain peers. Additionally, the technical operation of blockchain presents a more pronounced advantage than at the strategic level.

We introduced a new perspective, emphasizing the enhancement of corporate operational safety and financial performance through the pathway of emergency industry policies, driven by the collaboration between government and businesses. Furthermore, we delved into the potential application value of blockchain strategies and technologies in enhancing operational security and the emergency industry.

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Assessing impacts of emergency industry demonstration on firm profitability: the role of blockchain strategies and technologies10.1108/IMDS-08-2023-0559Industrial Management & Data Systems2024-03-26© 2024 Emerald Publishing LimitedYingjie JuJianliang YangJingping MaYuehang HouIndustrial Management & Data Systemsahead-of-printahead-of-print2024-03-2610.1108/IMDS-08-2023-0559https://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0559/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Optimal integration decision of industrial internet platform for third-party components in two-sided networkshttps://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0599/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestWith the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components. We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function. First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components. Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.Optimal integration decision of industrial internet platform for third-party components in two-sided networks
Nan Feng, Lei Zhang, Xin Liu, Jing Xie
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

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Optimal integration decision of industrial internet platform for third-party components in two-sided networks10.1108/IMDS-08-2023-0599Industrial Management & Data Systems2024-03-15© 2024 Emerald Publishing LimitedNan FengLei ZhangXin LiuJing XieIndustrial Management & Data Systemsahead-of-printahead-of-print2024-03-1510.1108/IMDS-08-2023-0599https://www.emerald.com/insight/content/doi/10.1108/IMDS-08-2023-0599/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Benefit and risk evaluation of inland nuclear generation investment in Kazakhstan combined with an analytical MGT methodhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-09-2020-0562/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestIn the process of building the “Belt and Road” and “Bright Road” community of interests between China and Kazakhstan, this paper proposes the construction of an inland nuclear power plant in Kazakhstan. Considering the uncertainty of investment in nuclear power generation, the authors propose the MGT (Monte-Carlo and Gaussian Radial Basis with Tensor factorization) utility evaluation model to evaluate the risk of investment in nuclear power in Kazakhstan and provide a relevant reference for decision making on inland nuclear investment in Kazakhstan. Based on real options portfolio combined with a weighted utility function, this study takes into account the uncertainties associated with nuclear power investments through a minimum variance Monte Carlo approach, proposes a noise-enhancing process combined with geometric Brownian motion in solving complex conditions, and incorporates a measure of investment flexibility and strategic value in the investment, and then uses a deep noise reduction encoder to learn the initial values for potential features of cost and investment effectiveness. A Gaussian radial basis function used to construct a weighted utility function for each uncertainty, generate a minimization of the objective function for the tensor decomposition, and then optimize the objective loss function for the tensor decomposition, find the corresponding weights, and perform noise reduction to generalize the nonlinear problem to evaluate the effectiveness of nuclear power investment. Finally, the two dimensions of cost and risk (estimation of investment value and measurement of investment risk) are applied and simulated through actual data in Kazakhstan. The authors assess the core indicators of Kazakhstan's nuclear power plants throughout their construction and operating cycles, based on data relating to a cluster of nuclear power plants of 10 different technologies. The authors compared it with several popular methods for evaluating the benefits of nuclear power generation and conducted subsequent sensitivity analyses of key indicators. Experimental results on the dataset show that the MGT method outperforms the other four methods and that changes in nuclear investment returns are more sensitive to changes in costs while operating cash flows from nuclear power are certainly an effective way to drive investment reform in inland nuclear power generation in Kazakhstan at current levels of investment costs. Future research could consider exploring other excellent methods to improve the accuracy of the investment prediction further using sparseness and noise interference. Also consider collecting some expert advice and providing more appropriate specific suggestions, which will facilitate the application in practice. The Novel Coronavirus epidemic has plunged the global economy into a deep recession, the tension between China and the US has made the energy cooperation road unusually tortuous, Kazakhstan in Central Asia has natural geographical and resource advantages, so China–Kazakhstan energy cooperation as a new era of opportunity, providing a strong guarantee for China's political and economic stability. The basic idea of building large-scale nuclear power plants in Balkhash and Aktau is put forward, considering the development strategy of building Kazakhstan into a regional international energy base. This work will be a good inspiration for the investment of nuclear generation. This study solves the problem of increasing noise by combining Monte Carlo simulation with geometric Brownian motion under complex conditions, adds the measure of investment flexibility and strategic value, constructs the utility function of noise reduction weight based on Gaussian radial basis function and extends the nonlinear problem to the evaluation of nuclear power investment benefit.Benefit and risk evaluation of inland nuclear generation investment in Kazakhstan combined with an analytical MGT method
Liangyan Liu, Ming Cheng
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

In the process of building the “Belt and Road” and “Bright Road” community of interests between China and Kazakhstan, this paper proposes the construction of an inland nuclear power plant in Kazakhstan. Considering the uncertainty of investment in nuclear power generation, the authors propose the MGT (Monte-Carlo and Gaussian Radial Basis with Tensor factorization) utility evaluation model to evaluate the risk of investment in nuclear power in Kazakhstan and provide a relevant reference for decision making on inland nuclear investment in Kazakhstan.

Based on real options portfolio combined with a weighted utility function, this study takes into account the uncertainties associated with nuclear power investments through a minimum variance Monte Carlo approach, proposes a noise-enhancing process combined with geometric Brownian motion in solving complex conditions, and incorporates a measure of investment flexibility and strategic value in the investment, and then uses a deep noise reduction encoder to learn the initial values for potential features of cost and investment effectiveness. A Gaussian radial basis function used to construct a weighted utility function for each uncertainty, generate a minimization of the objective function for the tensor decomposition, and then optimize the objective loss function for the tensor decomposition, find the corresponding weights, and perform noise reduction to generalize the nonlinear problem to evaluate the effectiveness of nuclear power investment. Finally, the two dimensions of cost and risk (estimation of investment value and measurement of investment risk) are applied and simulated through actual data in Kazakhstan.

The authors assess the core indicators of Kazakhstan's nuclear power plants throughout their construction and operating cycles, based on data relating to a cluster of nuclear power plants of 10 different technologies. The authors compared it with several popular methods for evaluating the benefits of nuclear power generation and conducted subsequent sensitivity analyses of key indicators. Experimental results on the dataset show that the MGT method outperforms the other four methods and that changes in nuclear investment returns are more sensitive to changes in costs while operating cash flows from nuclear power are certainly an effective way to drive investment reform in inland nuclear power generation in Kazakhstan at current levels of investment costs.

Future research could consider exploring other excellent methods to improve the accuracy of the investment prediction further using sparseness and noise interference. Also consider collecting some expert advice and providing more appropriate specific suggestions, which will facilitate the application in practice.

The Novel Coronavirus epidemic has plunged the global economy into a deep recession, the tension between China and the US has made the energy cooperation road unusually tortuous, Kazakhstan in Central Asia has natural geographical and resource advantages, so China–Kazakhstan energy cooperation as a new era of opportunity, providing a strong guarantee for China's political and economic stability. The basic idea of building large-scale nuclear power plants in Balkhash and Aktau is put forward, considering the development strategy of building Kazakhstan into a regional international energy base. This work will be a good inspiration for the investment of nuclear generation.

This study solves the problem of increasing noise by combining Monte Carlo simulation with geometric Brownian motion under complex conditions, adds the measure of investment flexibility and strategic value, constructs the utility function of noise reduction weight based on Gaussian radial basis function and extends the nonlinear problem to the evaluation of nuclear power investment benefit.

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Benefit and risk evaluation of inland nuclear generation investment in Kazakhstan combined with an analytical MGT method10.1108/IMDS-09-2020-0562Industrial Management & Data Systems2022-01-26© 2022 Emerald Publishing LimitedLiangyan LiuMing ChengIndustrial Management & Data Systemsahead-of-printahead-of-print2022-01-2610.1108/IMDS-09-2020-0562https://www.emerald.com/insight/content/doi/10.1108/IMDS-09-2020-0562/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2022 Emerald Publishing Limited
Perceived interactivity in real estate APP increases consumers' psychological well-being: a moderated mediation modelhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-09-2023-0623/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThis 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. This 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. The 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. This 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.Perceived interactivity in real estate APP increases consumers' psychological well-being: a moderated mediation model
Maosheng Yang, Lei Feng, Honghong Zhou, Shih-Chih Chen, Ming K. Lim, Ming-Lang Tseng
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

This 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.

This 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.

The 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.

This 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.

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Perceived interactivity in real estate APP increases consumers' psychological well-being: a moderated mediation model10.1108/IMDS-09-2023-0623Industrial Management & Data Systems2024-02-15© 2024 Emerald Publishing LimitedMaosheng YangLei FengHonghong ZhouShih-Chih ChenMing K. LimMing-Lang TsengIndustrial Management & Data Systemsahead-of-printahead-of-print2024-02-1510.1108/IMDS-09-2023-0623https://www.emerald.com/insight/content/doi/10.1108/IMDS-09-2023-0623/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Triple A supply chain management and sustainabilityhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-10-2023-0756/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestSustainability is of growing significance in the contemporary business landscape as organizations strive to minimize their environmental impact and optimize supply chain (SC) operations. Gaining insights into the influence of Triple A SC practices on sustainable performance can offer valuable perspectives for practitioners and policymakers. This study aims to comprehensively review existing academic literature on Triple A supply chain management (SCM) and sustainability, examining its impact on sustainable performance while identifying key influencing factors. This review follows the six steps and 14 decisions of conducting a systematic literature review to comprehensively review 57 papers published between 2004 and 2023. Based on the content analysis of the selected papers, this study summarizes the antecedents, practices and outcomes of Triple A SCM, with a particular focus on its implications for sustainability. This paper builds a conceptual framework from the descriptive and thematic findings to enrich the relevant aspects of Triple A SCM. This study establishes a connection between Triple A SCM and sustainable performance by examining its impact on economic, social and environmental aspects. This review identifies research gaps and acknowledges the lack of specificity in implementing Triple A SCM across diverse industries, regions and competitive markets with varying external environments. It emphasizes the necessity to customize approaches based on contextual factors and provides valuable recommendations for future research to advance the concept of Triple A SCM.Triple A supply chain management and sustainability
Fu Jia, Kexin Li, Tianyu Zhang, Lujie Chen
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

Sustainability is of growing significance in the contemporary business landscape as organizations strive to minimize their environmental impact and optimize supply chain (SC) operations. Gaining insights into the influence of Triple A SC practices on sustainable performance can offer valuable perspectives for practitioners and policymakers. This study aims to comprehensively review existing academic literature on Triple A supply chain management (SCM) and sustainability, examining its impact on sustainable performance while identifying key influencing factors.

This review follows the six steps and 14 decisions of conducting a systematic literature review to comprehensively review 57 papers published between 2004 and 2023.

Based on the content analysis of the selected papers, this study summarizes the antecedents, practices and outcomes of Triple A SCM, with a particular focus on its implications for sustainability. This paper builds a conceptual framework from the descriptive and thematic findings to enrich the relevant aspects of Triple A SCM.

This study establishes a connection between Triple A SCM and sustainable performance by examining its impact on economic, social and environmental aspects. This review identifies research gaps and acknowledges the lack of specificity in implementing Triple A SCM across diverse industries, regions and competitive markets with varying external environments. It emphasizes the necessity to customize approaches based on contextual factors and provides valuable recommendations for future research to advance the concept of Triple A SCM.

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Triple A supply chain management and sustainability10.1108/IMDS-10-2023-0756Industrial Management & Data Systems2024-02-22© 2024 Emerald Publishing LimitedFu JiaKexin LiTianyu ZhangLujie ChenIndustrial Management & Data Systemsahead-of-printahead-of-print2024-02-2210.1108/IMDS-10-2023-0756https://www.emerald.com/insight/content/doi/10.1108/IMDS-10-2023-0756/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Investigating the effects of gamification affordances on users’ green intrinsic motivation: a cognitive evaluation perspectivehttps://www.emerald.com/insight/content/doi/10.1108/IMDS-12-2022-0753/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestBased on cognitive evaluation theory and gamification affordances, this study aims to understand how gamification affordances influence users’ intention to engage in sustainable behaviour and how new trends in Ant Forest influence its impact on green intrinsic motivation to support sustainable behaviours. The authors developed a research model to explore the mechanisms underlying gamification affordances, psychological needs and green intrinsic motivation. Partial least squares structural equation modelling was used to assess the survey data (n = 393) and test the research model. The results show that different gamification affordances can satisfy users’ needs for autonomy, competence and relatedness, which positively influences their green intrinsic motivation and engagement in sustainable behaviours. However, some affordances, such as competition, might negatively impact these psychological needs. This research updates information system research on environmental sustainability and the Ant Forest context. The authors provide a new framework that links gamification affordances, psychological needs and sustainable behaviour. The study also examines changing trends in Ant Forest and their implications.Investigating the effects of gamification affordances on users’ green intrinsic motivation: a cognitive evaluation perspective
Sihan Cheng, Cong Cao
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

Based on cognitive evaluation theory and gamification affordances, this study aims to understand how gamification affordances influence users’ intention to engage in sustainable behaviour and how new trends in Ant Forest influence its impact on green intrinsic motivation to support sustainable behaviours.

The authors developed a research model to explore the mechanisms underlying gamification affordances, psychological needs and green intrinsic motivation. Partial least squares structural equation modelling was used to assess the survey data (n = 393) and test the research model.

The results show that different gamification affordances can satisfy users’ needs for autonomy, competence and relatedness, which positively influences their green intrinsic motivation and engagement in sustainable behaviours. However, some affordances, such as competition, might negatively impact these psychological needs.

This research updates information system research on environmental sustainability and the Ant Forest context. The authors provide a new framework that links gamification affordances, psychological needs and sustainable behaviour. The study also examines changing trends in Ant Forest and their implications.

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Investigating the effects of gamification affordances on users’ green intrinsic motivation: a cognitive evaluation perspective10.1108/IMDS-12-2022-0753Industrial Management & Data Systems2024-02-16© 2024 Emerald Publishing LimitedSihan ChengCong CaoIndustrial Management & Data Systemsahead-of-printahead-of-print2024-02-1610.1108/IMDS-12-2022-0753https://www.emerald.com/insight/content/doi/10.1108/IMDS-12-2022-0753/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited
Exploring online social platform affordances for digital creators: a multi-method approach using qualitative and configurational analysishttps://www.emerald.com/insight/content/doi/10.1108/IMDS-12-2023-0951/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThis study explores the key platform affordances that online social platform providers need to offer digital creators to strengthen the creator ecosystem, one of the leading accelerators for platform growth. Specifically, it aims to investigate how these affordances make the dynamic combinations for high platform quality across diverse platform types and demographic characteristics of digital creators. This study adopts a multi-method approach. Drawing upon the affordance theory, Study 1 aims to identify the key affordances of online social platforms based on relevant literature and the qualitative interview data collected from 22 digital creators, thereby constructing a conceptual framework of key platform affordances for digital creators. Building on the findings of Study 1, Study 2 explores the dynamic combinations of these platform affordances that contribute to platform quality using a configurational approach. Data from online surveys of 185 digital creators were analyzed using fuzzy set qualitative comparative analysis (fsQCA). The results of Study 1 identified key online social platform affordances for digital creators, including Storytelling, Socialization, Design, Development, Promotion, and Protection affordance. Study 2 showed that the combinations of these platform affordances for digital creators are diverse according to the types of platforms, creators’ gender, and their professionality. Like many studies, this research also has several limitations. One limitation of the research is the potential constraint of the extent of how well the data samples represent the group of creators who are actively producing digital content. Despite the addition of screening questions and meticulous data filtering, it is possible that we did not secure sufficient data from creators who are actively engaged in creative activities. In future research, it is worth contemplating the acquisition of data from actual groups of creators, such as creator communities. Future researchers anticipate obtaining more in-depth and accurate data by directly involving and collaborating with creators. This study highlights the need for online social platforms to enhance features for storytelling, socializing, design, development, promotion, and protection, fostering a robust digital creator ecosystem. It emphasizes clear communication of these affordances, ensuring creators can effectively utilize them. Importantly, platforms should adapt these features to accommodate diverse creator profiles, considering differences in gender and expertise levels, especially in emerging spaces like the Metaverse. This approach ensures an equitable and enriching experience for all users and creators, underlining the importance of dynamic interaction and inclusivity in platform development and creator support strategies. This study underscores the social implications of evolving digital creator ecosystems on online platforms. Identifying six key affordances essential for digital creators highlights the need for platforms to enhance storytelling, socializing, design, development, promotion, and product protection. Crucially, it emphasizes inclusivity, urging platforms to consider diverse creator profiles, including gender and expertise differences, particularly in transitioning from traditional social media to the Metaverse. This approach nurtures a more robust creator ecosystem and fosters an equitable and enriching experience for all users. It signals a shift towards more dynamic, adaptive online environments catering to diverse creators and audiences. For academics, this study builds the conceptual framework of online social platform affordances for digital creators. Using the configurational approach, this study identified various interdependent relationships among the affordances, which are nuanced by specific contexts, and suggested novel insights for future studies. For practices, the findings specified by creators and platform types are expected to guide platform providers in developing strategies to support digital creators and contribute to platform growth.Exploring online social platform affordances for digital creators: a multi-method approach using qualitative and configurational analysis
Seoyoun Lee, Younghoon Chang, One-Ki Daniel Lee, Sunghan Ryu, Qiuju Yin
Industrial Management & Data Systems, Vol. ahead-of-print, No. ahead-of-print, pp.-

This study explores the key platform affordances that online social platform providers need to offer digital creators to strengthen the creator ecosystem, one of the leading accelerators for platform growth. Specifically, it aims to investigate how these affordances make the dynamic combinations for high platform quality across diverse platform types and demographic characteristics of digital creators.

This study adopts a multi-method approach. Drawing upon the affordance theory, Study 1 aims to identify the key affordances of online social platforms based on relevant literature and the qualitative interview data collected from 22 digital creators, thereby constructing a conceptual framework of key platform affordances for digital creators. Building on the findings of Study 1, Study 2 explores the dynamic combinations of these platform affordances that contribute to platform quality using a configurational approach. Data from online surveys of 185 digital creators were analyzed using fuzzy set qualitative comparative analysis (fsQCA).

The results of Study 1 identified key online social platform affordances for digital creators, including Storytelling, Socialization, Design, Development, Promotion, and Protection affordance. Study 2 showed that the combinations of these platform affordances for digital creators are diverse according to the types of platforms, creators’ gender, and their professionality.

Like many studies, this research also has several limitations. One limitation of the research is the potential constraint of the extent of how well the data samples represent the group of creators who are actively producing digital content. Despite the addition of screening questions and meticulous data filtering, it is possible that we did not secure sufficient data from creators who are actively engaged in creative activities. In future research, it is worth contemplating the acquisition of data from actual groups of creators, such as creator communities. Future researchers anticipate obtaining more in-depth and accurate data by directly involving and collaborating with creators.

This study highlights the need for online social platforms to enhance features for storytelling, socializing, design, development, promotion, and protection, fostering a robust digital creator ecosystem. It emphasizes clear communication of these affordances, ensuring creators can effectively utilize them. Importantly, platforms should adapt these features to accommodate diverse creator profiles, considering differences in gender and expertise levels, especially in emerging spaces like the Metaverse. This approach ensures an equitable and enriching experience for all users and creators, underlining the importance of dynamic interaction and inclusivity in platform development and creator support strategies.

This study underscores the social implications of evolving digital creator ecosystems on online platforms. Identifying six key affordances essential for digital creators highlights the need for platforms to enhance storytelling, socializing, design, development, promotion, and product protection. Crucially, it emphasizes inclusivity, urging platforms to consider diverse creator profiles, including gender and expertise differences, particularly in transitioning from traditional social media to the Metaverse. This approach nurtures a more robust creator ecosystem and fosters an equitable and enriching experience for all users. It signals a shift towards more dynamic, adaptive online environments catering to diverse creators and audiences.

For academics, this study builds the conceptual framework of online social platform affordances for digital creators. Using the configurational approach, this study identified various interdependent relationships among the affordances, which are nuanced by specific contexts, and suggested novel insights for future studies. For practices, the findings specified by creators and platform types are expected to guide platform providers in developing strategies to support digital creators and contribute to platform growth.

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Exploring online social platform affordances for digital creators: a multi-method approach using qualitative and configurational analysis10.1108/IMDS-12-2023-0951Industrial Management & Data Systems2024-02-22© 2024 Emerald Publishing LimitedSeoyoun LeeYounghoon ChangOne-Ki Daniel LeeSunghan RyuQiuju YinIndustrial Management & Data Systemsahead-of-printahead-of-print2024-02-2210.1108/IMDS-12-2023-0951https://www.emerald.com/insight/content/doi/10.1108/IMDS-12-2023-0951/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 2024 Emerald Publishing Limited