Pub Date : 2024-08-09DOI: 10.1108/imds-12-2023-0977
M. Al-Shboul
PurposeThis study tries to examine the effect of artificial intelligence (AI) drivers on the willingness to adopt the human capital supply chain (HCSC) in manufacturing firms (MFs) in developing countries (DCs) including Jordan, Saudi Arabia, Bahrain, Qatar and the United Arab Emirates, which are listed in the Chambers of Industry of these countries.Design/methodology/approachThe quantitative methodology with a simple random sampling method was adopted using a questionnaire survey-based approach to collect data from 233 out of 1,055 participants (human resource (HR) managers and information technology (IT) senior managers) from various MFs (private and commercial), representing a 22% response rate. Covariance-based structural equation modeling (CB-SEM) was used to analyze the raw data using Amos V.25.FindingsThe results of this study showed that there are positive and statistically significant direct association effects between the reliability of use (RoU), competitive pressures (CPs) and user confidence (UC) factors on the willingness to adopt AI in HCSC in the MFs in DCs. At the same time, there is no significant effect on a firm’s infrastructure readiness (FIRs), in addition to the indirect effect of UC in the relationship between CPs and FIRs on the willingness to adopt AI in HCSC.Originality/valueSuch findings of this study can provide insightful implications for stakeholders and policymakers regarding the importance of using predictive AI drivers' effect on willingness to adopt the HCSC in the MFs in DCs as emerging economies. Additionally, the managers might focus on the existence of a significant positive indirect effect of UC as a mediating factor in the relationship between FIRs and willingness to adopt AI and its applications in HCSC systems and departments.
{"title":"Artificial intelligence drivers' effect on willingness to adopt the human capital supply chain in manufacturing firms: an empirical investigation from developing countries – a mediation model","authors":"M. Al-Shboul","doi":"10.1108/imds-12-2023-0977","DOIUrl":"https://doi.org/10.1108/imds-12-2023-0977","url":null,"abstract":"PurposeThis study tries to examine the effect of artificial intelligence (AI) drivers on the willingness to adopt the human capital supply chain (HCSC) in manufacturing firms (MFs) in developing countries (DCs) including Jordan, Saudi Arabia, Bahrain, Qatar and the United Arab Emirates, which are listed in the Chambers of Industry of these countries.Design/methodology/approachThe quantitative methodology with a simple random sampling method was adopted using a questionnaire survey-based approach to collect data from 233 out of 1,055 participants (human resource (HR) managers and information technology (IT) senior managers) from various MFs (private and commercial), representing a 22% response rate. Covariance-based structural equation modeling (CB-SEM) was used to analyze the raw data using Amos V.25.FindingsThe results of this study showed that there are positive and statistically significant direct association effects between the reliability of use (RoU), competitive pressures (CPs) and user confidence (UC) factors on the willingness to adopt AI in HCSC in the MFs in DCs. At the same time, there is no significant effect on a firm’s infrastructure readiness (FIRs), in addition to the indirect effect of UC in the relationship between CPs and FIRs on the willingness to adopt AI in HCSC.Originality/valueSuch findings of this study can provide insightful implications for stakeholders and policymakers regarding the importance of using predictive AI drivers' effect on willingness to adopt the HCSC in the MFs in DCs as emerging economies. Additionally, the managers might focus on the existence of a significant positive indirect effect of UC as a mediating factor in the relationship between FIRs and willingness to adopt AI and its applications in HCSC systems and departments.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-24DOI: 10.1108/imds-08-2023-0598
Mingze Yuan, Lin Ma, T. Qu, Matthias Thürer, George Q. Huang
Purpose Workload contribution calculation approaches in the existing literature overestimate or underestimate indirect workload, which increases both workload fluctuation and shop floor throughput performance. This study optimizes a Corrected Aggregate Workload (CAW) approach to control the workload contribution of workstations and Work In Progress (WIP) levels, thereby improving the shop floor throughput performance.Design/methodology/approach This study adopts simulation experiment by SimPy, and experimental factors are: (1) two workload contribution methods (CAW method and considering Position Corrected Aggregate Workload [PCAW] method); (2) two release methods (LUMS COR release and immediate release); (3) eleven workload norms for LUMS COR release (from 7- to 15-time units), and infinite workload norm for immediate release; and (4) two dispatching rules (First Come First Served, FCFS and Operation Due Date, ODD). Each scenario is replicated 100 times, and for each replication data are collected for 10,000 time units, being the warm-up period set to 3,000-time units.Findings The results of this study confirm that the PCAW calculation method outperforms the CAW method, especially during higher workload norm levels. The PCAW method is considered the better solution in practice due to its excellent performance in terms of percentage tardiness and mean tardiness time. The efficient workload contribution approach, as discussed in this study, has the potential to offset delivery performance loss that results from throughput performance loss.Originality/valueThis study proposes a novel approach that considers the workstations’ position in the routing of the job and the position of jobs CAW method. The results demonstrated that it allows shop floor throughput time to be short and feasible. It controls WIP by workload contribution of workstations, resulting in a lean shop floor. Therefore, workload contribution calculation is of particular significance for high-variety Make-To-Order (MTO) companies.
{"title":"Corrected Aggregate Workload approach on order release by considering job’s routing position induced variable indirect load","authors":"Mingze Yuan, Lin Ma, T. Qu, Matthias Thürer, George Q. Huang","doi":"10.1108/imds-08-2023-0598","DOIUrl":"https://doi.org/10.1108/imds-08-2023-0598","url":null,"abstract":"Purpose Workload contribution calculation approaches in the existing literature overestimate or underestimate indirect workload, which increases both workload fluctuation and shop floor throughput performance. This study optimizes a Corrected Aggregate Workload (CAW) approach to control the workload contribution of workstations and Work In Progress (WIP) levels, thereby improving the shop floor throughput performance.Design/methodology/approach This study adopts simulation experiment by SimPy, and experimental factors are: (1) two workload contribution methods (CAW method and considering Position Corrected Aggregate Workload [PCAW] method); (2) two release methods (LUMS COR release and immediate release); (3) eleven workload norms for LUMS COR release (from 7- to 15-time units), and infinite workload norm for immediate release; and (4) two dispatching rules (First Come First Served, FCFS and Operation Due Date, ODD). Each scenario is replicated 100 times, and for each replication data are collected for 10,000 time units, being the warm-up period set to 3,000-time units.Findings The results of this study confirm that the PCAW calculation method outperforms the CAW method, especially during higher workload norm levels. The PCAW method is considered the better solution in practice due to its excellent performance in terms of percentage tardiness and mean tardiness time. The efficient workload contribution approach, as discussed in this study, has the potential to offset delivery performance loss that results from throughput performance loss.Originality/valueThis study proposes a novel approach that considers the workstations’ position in the routing of the job and the position of jobs CAW method. The results demonstrated that it allows shop floor throughput time to be short and feasible. It controls WIP by workload contribution of workstations, resulting in a lean shop floor. Therefore, workload contribution calculation is of particular significance for high-variety Make-To-Order (MTO) companies.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-24DOI: 10.1108/imds-07-2023-0444
Qian Wang, Zhen Shao
PurposeWith the wide usage of digital technologies, employees’ digital creativity serves as a stepping stone in driving the process of organizational digital innovation. However, scant attention has been devoted to understanding the relationship between leadership and employees’ digital creativity within the digital technology usage context. Drawing upon social cognitive theory, our study aims to explore the relationship between transformational leadership and employees’ digital creativity through the mediating roles of creative self-efficacy and ambidextrous learning.Design/methodology/approachA field survey was conducted in China, garnering survey data from 223 employees actively engaged with digital technologies in their daily work. We empirically test the structural equation model to verify the hypotheses.FindingsThe results reveal a positive association between transformational leadership and employees’ digital creativity, with a consequential cascade mediation facilitated through creative self-efficacy and exploitation and exploration.Originality/valueThe empirical research not only enriches comprehension of individual-level digital creativity but also provides valuable practical insights for managers seeking to effectively drive digital innovation within their organizations.
{"title":"Linking transformational leadership and digital creativity from the lens of social cognitive theory","authors":"Qian Wang, Zhen Shao","doi":"10.1108/imds-07-2023-0444","DOIUrl":"https://doi.org/10.1108/imds-07-2023-0444","url":null,"abstract":"PurposeWith the wide usage of digital technologies, employees’ digital creativity serves as a stepping stone in driving the process of organizational digital innovation. However, scant attention has been devoted to understanding the relationship between leadership and employees’ digital creativity within the digital technology usage context. Drawing upon social cognitive theory, our study aims to explore the relationship between transformational leadership and employees’ digital creativity through the mediating roles of creative self-efficacy and ambidextrous learning.Design/methodology/approachA field survey was conducted in China, garnering survey data from 223 employees actively engaged with digital technologies in their daily work. We empirically test the structural equation model to verify the hypotheses.FindingsThe results reveal a positive association between transformational leadership and employees’ digital creativity, with a consequential cascade mediation facilitated through creative self-efficacy and exploitation and exploration.Originality/valueThe empirical research not only enriches comprehension of individual-level digital creativity but also provides valuable practical insights for managers seeking to effectively drive digital innovation within their organizations.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-22DOI: 10.1108/imds-08-2023-0580
Gabriel Cepeda, José L. Roldán, Misty A. Sabol, Joe Hair, Alain Yee Loong Chong
Purpose Rigorous applications of analytical tools in information systems (IS) research are important for developing new knowledge and innovations in the field. Emerging tools provide building blocks for future inquiry, practice and innovation. This article summarizes the findings of an analysis of the adoption and reporting of partial least squares structural equation modeling (PLS-SEM) analytical tools by Industrial Management & Data Systems authors in the most recent five-year period.Design/methodology/approach Selected emerging advanced PLS-SEM analytical tools that have experienced limited adoption are highlighted to broaden awareness of their value to IS researchers.Findings PLS-SEM analytical tools that facilitate understanding increasingly complex theoretical models and deliver improved prediction assessment are now available. IS researchers should explore the opportunities to apply these new tools to more fully describe the contributions of their research.Research limitations/implications Findings demonstrate the increasing acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is a preferred structural equation modeling (SEM) method in many research settings and will become even more widely applied when IS researchers are aware of and apply the new analytical tools.Practical implications Emerging PLS-SEM methodological developments will help IS researchers examine new theoretical concepts and relationships and publish their work. Researchers are encouraged to engage in more complete analyses by applying the applicable emerging tools.Originality/value Applications of PLS-SEM for prediction, theory testing and confirmation have increased in recent years. Information system scholars should continue to exercise sound practice by applying these new analytical tools where applicable. Recommended guidelines following Hair et al. (2019; 2022) are included.
目的 在信息系统（IS）研究中严格应用分析工具对于开发新知识和领域创新非常重要。新兴工具为未来的探索、实践和创新提供了基石。本文总结了《工业管理与数据系统》作者在最近五年中对偏最小二乘法结构方程建模（PLS-SEM）分析工具的采用和报告的分析结果。IS 研究人员应探索应用这些新工具的机会，以更全面地描述其研究成果。研究局限性/影响 研究结果表明，PLS-SEM 作为 IS 领域的另一种有用研究方法，已被越来越多的人所接受。在许多研究环境中，PLS-SEM 是一种首选的结构方程建模（SEM）方法，当 IS 研究人员了解并应用新的分析工具时，PLS-SEM 将得到更广泛的应用。鼓励研究人员应用适用的新兴工具进行更全面的分析。信息系统学者应在适用的情况下应用这些新的分析工具，从而继续进行合理的实践。其中包括遵循 Hair 等人（2019；2022）的建议指南。
{"title":"Emerging opportunities for information systems researchers to expand their PLS-SEM analytical toolbox","authors":"Gabriel Cepeda, José L. Roldán, Misty A. Sabol, Joe Hair, Alain Yee Loong Chong","doi":"10.1108/imds-08-2023-0580","DOIUrl":"https://doi.org/10.1108/imds-08-2023-0580","url":null,"abstract":"Purpose Rigorous applications of analytical tools in information systems (IS) research are important for developing new knowledge and innovations in the field. Emerging tools provide building blocks for future inquiry, practice and innovation. This article summarizes the findings of an analysis of the adoption and reporting of partial least squares structural equation modeling (PLS-SEM) analytical tools by Industrial Management & Data Systems authors in the most recent five-year period.Design/methodology/approach Selected emerging advanced PLS-SEM analytical tools that have experienced limited adoption are highlighted to broaden awareness of their value to IS researchers.Findings PLS-SEM analytical tools that facilitate understanding increasingly complex theoretical models and deliver improved prediction assessment are now available. IS researchers should explore the opportunities to apply these new tools to more fully describe the contributions of their research.Research limitations/implications Findings demonstrate the increasing acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is a preferred structural equation modeling (SEM) method in many research settings and will become even more widely applied when IS researchers are aware of and apply the new analytical tools.Practical implications Emerging PLS-SEM methodological developments will help IS researchers examine new theoretical concepts and relationships and publish their work. Researchers are encouraged to engage in more complete analyses by applying the applicable emerging tools.Originality/value Applications of PLS-SEM for prediction, theory testing and confirmation have increased in recent years. Information system scholars should continue to exercise sound practice by applying these new analytical tools where applicable. Recommended guidelines following Hair et al. (2019; 2022) are included.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141111716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PurposeConsidering the financial service providers’ (FSPs) information asymmetry in evaluating the supplier and their distinct quit probabilities, we want to examine the supplier’s preference of the financing schemes if both the bank and the online platform exist and how the buyer sets the contract terms in the two financing schemes.Design/methodology/approachWe establish a Stackelberg game model to capture the interactions among three parties, i.e. a supplier, a capital-sufficient buyer and an FSP (either a bank or an online platform), within a first-time contract.FindingsIn the non-FSPs’ quit case, the buyer’s profit is higher under the bank loan scenario, while the supplier’s profit performs adversely. The supply chain’s profit is heavily dependent on the buyer’s profit difference between the two financing schemes. Moreover, we find that the supplier borrows the money to exactly cover the production cost. The equilibrium solutions of the FSPs’ quit case and of the capital-sufficient supplier’s case are also derived.Originality/valueFirst, we assign different risk profiles to different FSPs in our setting so that modeling a previously ignored but practically significant problem. Second, we innovatively take the FSP’s quit probability into account in our model. Third, we elucidate how these factors can influence the relative efficiency of the two types of financing schemes and the settings of the contract, which further complements and extends the current SCF research.
{"title":"Sourcing from supplier in the presence of financial service providers’ information asymmetry and quit probabilities","authors":"Chaorui Huang, Song-Man Wu, Hoi-Lam Ma, Sai-Ho Chung","doi":"10.1108/imds-09-2023-0694","DOIUrl":"https://doi.org/10.1108/imds-09-2023-0694","url":null,"abstract":"PurposeConsidering the financial service providers’ (FSPs) information asymmetry in evaluating the supplier and their distinct quit probabilities, we want to examine the supplier’s preference of the financing schemes if both the bank and the online platform exist and how the buyer sets the contract terms in the two financing schemes.Design/methodology/approachWe establish a Stackelberg game model to capture the interactions among three parties, i.e. a supplier, a capital-sufficient buyer and an FSP (either a bank or an online platform), within a first-time contract.FindingsIn the non-FSPs’ quit case, the buyer’s profit is higher under the bank loan scenario, while the supplier’s profit performs adversely. The supply chain’s profit is heavily dependent on the buyer’s profit difference between the two financing schemes. Moreover, we find that the supplier borrows the money to exactly cover the production cost. The equilibrium solutions of the FSPs’ quit case and of the capital-sufficient supplier’s case are also derived.Originality/valueFirst, we assign different risk profiles to different FSPs in our setting so that modeling a previously ignored but practically significant problem. Second, we innovatively take the FSP’s quit probability into account in our model. Third, we elucidate how these factors can influence the relative efficiency of the two types of financing schemes and the settings of the contract, which further complements and extends the current SCF research.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.1108/imds-12-2023-0921
M. Shahidzadeh, Sajjad Shokouhyar
PurposeIn recent times, the field of corporate intelligence has gained substantial prominence, employing advanced data analysis techniques to yield pivotal insights for instantaneous strategic and tactical decision-making. Expanding beyond rudimentary post observation and analysis, social media analytics unfolds a comprehensive exploration of diverse data streams encompassing social media platforms and blogs, thereby facilitating an all-encompassing understanding of the dynamic social customer landscape. During an extensive evaluation of social media presence, various indicators such as popularity, impressions, user engagement, content flow, and brand references undergo meticulous scrutiny. Invaluable intelligence lies within user-generated data stemming from social media platforms, encompassing valuable customer perspectives, feedback, and recommendations that have the potential to revolutionize numerous operational facets, including supply chain management. Despite its intrinsic worth, the actual business value of social media data is frequently overshadowed due to the pervasive abundance of content saturating the digital realm. In response to this concern, the present study introduces a cutting-edge system known as the Enterprise Just-in-time Decision Support System (EJDSS).Design/methodology/approachLeveraging deep learning techniques and advanced analytics of social media data, the EJDSS aims to propel business operations forward. Specifically tailored to the domain of marketing, the framework delineates a practical methodology for extracting invaluable insights from the vast expanse of social data. This scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.FindingsTo substantiate the efficacy of the EJDSS, a detailed case study centered around reverse logistics resource recycling is presented, accompanied by experimental findings that underscore the system’s exceptional performance. The study showcases remarkable precision, robustness, F1 score, and variance statistics, attaining impressive figures of 83.62%, 78.44%, 83.67%, and 3.79%, respectively.Originality/valueThis scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.
{"title":"Unveiling just-in-time decision support system using social media analytics: a case study on reverse logistics resource recycling","authors":"M. Shahidzadeh, Sajjad Shokouhyar","doi":"10.1108/imds-12-2023-0921","DOIUrl":"https://doi.org/10.1108/imds-12-2023-0921","url":null,"abstract":"PurposeIn recent times, the field of corporate intelligence has gained substantial prominence, employing advanced data analysis techniques to yield pivotal insights for instantaneous strategic and tactical decision-making. Expanding beyond rudimentary post observation and analysis, social media analytics unfolds a comprehensive exploration of diverse data streams encompassing social media platforms and blogs, thereby facilitating an all-encompassing understanding of the dynamic social customer landscape. During an extensive evaluation of social media presence, various indicators such as popularity, impressions, user engagement, content flow, and brand references undergo meticulous scrutiny. Invaluable intelligence lies within user-generated data stemming from social media platforms, encompassing valuable customer perspectives, feedback, and recommendations that have the potential to revolutionize numerous operational facets, including supply chain management. Despite its intrinsic worth, the actual business value of social media data is frequently overshadowed due to the pervasive abundance of content saturating the digital realm. In response to this concern, the present study introduces a cutting-edge system known as the Enterprise Just-in-time Decision Support System (EJDSS).Design/methodology/approachLeveraging deep learning techniques and advanced analytics of social media data, the EJDSS aims to propel business operations forward. Specifically tailored to the domain of marketing, the framework delineates a practical methodology for extracting invaluable insights from the vast expanse of social data. This scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.FindingsTo substantiate the efficacy of the EJDSS, a detailed case study centered around reverse logistics resource recycling is presented, accompanied by experimental findings that underscore the system’s exceptional performance. The study showcases remarkable precision, robustness, F1 score, and variance statistics, attaining impressive figures of 83.62%, 78.44%, 83.67%, and 3.79%, respectively.Originality/valueThis scholarly work offers a comprehensive overview of fundamental principles, pertinent challenges, functional aspects, and significant advancements in the realm of extensive social data analysis. Moreover, it presents compelling real-world scenarios that vividly illustrate the tangible advantages companies stand to gain by incorporating social data analytics into their decision-making processes and capitalizing on emerging investment prospects.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141126320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-25DOI: 10.1108/imds-03-2023-0175
Minghuan Shou, Furong Jia, Jie Yu
PurposeThe aging population, a higher proportion of older adults (aged 65+), is considered a global and severe problem, while the information systems (IS) literature on detecting the relationship between the aging population and the development of electronic commerce (e-commerce) is limited and insufficient. Hence, the main objective of this paper is to examine whether an aging population can moderate the effect of infrastructure constructions on e-commerce sales and whether an aging population can affect e-commerce sales.Design/methodology/approachTo investigate the relationship between the aging population and e-commerce sales, this study proposes two potential influential mechanisms: moderating the effects of infrastructure development on e-commerce sales and direct influence. Subsequently, a sample of 31 Chinese provinces from 2013 to 2019 is utilized to conduct regression analyses in order to examine these hypotheses.FindingsThe findings suggest that the development of urban transportation infrastructure and network constructions can significantly contribute to the enhancement of e-commerce sales, and the influence cannot be affected by aging population. Furthermore, it is noteworthy that an aging population can have a positive effect on e-commerce sales.Practical implicationsThe findings can inform future infrastructure constructions by assessing the potential of infrastructure projects to boost e-commerce sales and examining whether this effect varies in an aging population context.Originality/valueThe findings substantiate the pivotal role of older adults in the e-commerce industry. Moreover, the obtained results establish a positive relationship between an aging population and e-commerce sales, thereby offering diverse perspectives on existing theories.
{"title":"Developing urban infrastructure constructions for increasing e-commerce sales: the moderating roles of aging population","authors":"Minghuan Shou, Furong Jia, Jie Yu","doi":"10.1108/imds-03-2023-0175","DOIUrl":"https://doi.org/10.1108/imds-03-2023-0175","url":null,"abstract":"PurposeThe aging population, a higher proportion of older adults (aged 65+), is considered a global and severe problem, while the information systems (IS) literature on detecting the relationship between the aging population and the development of electronic commerce (e-commerce) is limited and insufficient. Hence, the main objective of this paper is to examine whether an aging population can moderate the effect of infrastructure constructions on e-commerce sales and whether an aging population can affect e-commerce sales.Design/methodology/approachTo investigate the relationship between the aging population and e-commerce sales, this study proposes two potential influential mechanisms: moderating the effects of infrastructure development on e-commerce sales and direct influence. Subsequently, a sample of 31 Chinese provinces from 2013 to 2019 is utilized to conduct regression analyses in order to examine these hypotheses.FindingsThe findings suggest that the development of urban transportation infrastructure and network constructions can significantly contribute to the enhancement of e-commerce sales, and the influence cannot be affected by aging population. Furthermore, it is noteworthy that an aging population can have a positive effect on e-commerce sales.Practical implicationsThe findings can inform future infrastructure constructions by assessing the potential of infrastructure projects to boost e-commerce sales and examining whether this effect varies in an aging population context.Originality/valueThe findings substantiate the pivotal role of older adults in the e-commerce industry. Moreover, the obtained results establish a positive relationship between an aging population and e-commerce sales, thereby offering diverse perspectives on existing theories.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140654588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-25DOI: 10.1108/imds-08-2023-0541
Peiyuan Gao, Yongjian Li, Weihua Liu, Chaolun Yuan, Paul Tae-Woo Lee, Shangsong Long
PurposeConsidering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.Design/methodology/approachThe study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.FindingsThe results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.Originality/valueMost scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.
{"title":"Impacts of digital technology innovation for social responsibility of platform enterprises on shareholder value","authors":"Peiyuan Gao, Yongjian Li, Weihua Liu, Chaolun Yuan, Paul Tae-Woo Lee, Shangsong Long","doi":"10.1108/imds-08-2023-0541","DOIUrl":"https://doi.org/10.1108/imds-08-2023-0541","url":null,"abstract":"PurposeConsidering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.Design/methodology/approachThe study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.FindingsThe results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.Originality/valueMost scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140654761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-23DOI: 10.1108/imds-07-2023-0435
Jialing Liu, Fangwei Zhu, Jiang Wei
PurposeThis study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.Design/methodology/approachThe authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.FindingsThe results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.Originality/valueThe findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.
{"title":"Network constraint and online group innovation: a dual perspective of inter-community group network and intra-community group network","authors":"Jialing Liu, Fangwei Zhu, Jiang Wei","doi":"10.1108/imds-07-2023-0435","DOIUrl":"https://doi.org/10.1108/imds-07-2023-0435","url":null,"abstract":"PurposeThis study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.Design/methodology/approachThe authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.FindingsThe results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.Originality/valueThe findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140666672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-22DOI: 10.1108/imds-02-2023-0086
Hua Liu, Shaobo Wei
PurposeDrawing upon resource dependence theory, this study aims to examine how a firm’s information technology (IT) capabilities (i.e. IT integration and IT reconfiguration) influence its responses to disruptions – bridging with a current supplier and buffering with an alternative supplier. We further examine how such relationships are moderated by the firm–supplier relative dependence (i.e. firm dependence advantage and supplier dependence advantage).Design/methodology/approachBased on data from 141 match-paired surveys of firms in China, we test our model.FindingsOur study finds that IT integration positively influences bridging and IT reconfiguration positively influences buffering. Furthermore, our findings indicate that the positive impact of IT integration on bridging is negatively influenced by the firm’s dependence (FD) advantage but positively moderated by the supplier’s dependence advantage. By contrast, the positive impact of IT reconfiguration on buffering is negatively influenced by the FD advantage.Originality/valueOur study provides a more nuanced insight into the effects of IT capabilities on disruption responses and a better understanding of the buyer–supplier dependence boundary conditions under which these effects vary.
目的根据资源依赖理论，本研究旨在探讨企业的信息技术（IT）能力（即 IT 整合和 IT 重组）如何影响其对中断的反应--与当前供应商的桥接以及与替代供应商的缓冲。我们进一步研究了这种关系如何受到企业-供应商相对依赖性（即企业依赖优势和供应商依赖优势）的调节。研究结果我们的研究发现，信息技术整合对桥接产生积极影响，信息技术重组对缓冲产生积极影响。此外，我们的研究结果表明，IT 整合对桥接的积极影响受企业依赖（FD）优势的负面影响，但受供应商依赖优势的积极调节。与此相反，IT 重构对缓冲的积极影响受到 FD 优势的消极影响。原创性/价值我们的研究为 IT 能力对中断响应的影响提供了更细致的洞察，并使我们更好地理解了买方-供应商依赖性的边界条件，在这些条件下，这些影响会发生变化。
{"title":"Bridging versus buffering: how IT capabilities and dependence advantage shape responses to supply chain disruptions?","authors":"Hua Liu, Shaobo Wei","doi":"10.1108/imds-02-2023-0086","DOIUrl":"https://doi.org/10.1108/imds-02-2023-0086","url":null,"abstract":"PurposeDrawing upon resource dependence theory, this study aims to examine how a firm’s information technology (IT) capabilities (i.e. IT integration and IT reconfiguration) influence its responses to disruptions – bridging with a current supplier and buffering with an alternative supplier. We further examine how such relationships are moderated by the firm–supplier relative dependence (i.e. firm dependence advantage and supplier dependence advantage).Design/methodology/approachBased on data from 141 match-paired surveys of firms in China, we test our model.FindingsOur study finds that IT integration positively influences bridging and IT reconfiguration positively influences buffering. Furthermore, our findings indicate that the positive impact of IT integration on bridging is negatively influenced by the firm’s dependence (FD) advantage but positively moderated by the supplier’s dependence advantage. By contrast, the positive impact of IT reconfiguration on buffering is negatively influenced by the FD advantage.Originality/valueOur study provides a more nuanced insight into the effects of IT capabilities on disruption responses and a better understanding of the buyer–supplier dependence boundary conditions under which these effects vary.","PeriodicalId":270213,"journal":{"name":"Industrial Management & Data Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140677065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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