J. Enterp. Inf. Manag.最新文献

{"title":"Green supply chain management for operational performance: anteceding impact of corporate social responsibility and moderating effects of relational capital","authors":"Jiawei Xu, Yubing Yu, Ye Wu, Z. Zhang, Y. Liu, Yanhong Cao, Prajwal Eachempati","doi":"10.1108/jeim-06-2021-0260","DOIUrl":"https://doi.org/10.1108/jeim-06-2021-0260","url":null,"abstract":"PurposeThe paper aims to study the relationship between corporate social responsibility, green supply chain management, and operational performance and the moderating effects of relational capital on these relationships.Design/methodology/approach The authors conduct an empirical study with a structural equation modeling approach to investigate the relationship between corporate social responsibility—constructed by the quality and environmental responsibility, green supply chain management—including green supplier and customer management and operational performance—manifested by quality, cost, flexibility, and delivery performance using data from 308 manufacturers in China. Besides, the authors explore the moderating effect of supplier and customer relational capital on these relationships.FindingsThe findings indicate that a company's quality and environmental responsibility significantly impacts its green supply chain management practices, which further improve its operational performance in quality, cost, flexibility, and delivery. In addition, supplier and customer relational capital strengthens the influence of environmental responsibility on green supply chain management. While supplier relational capital reinforces the impact of green supplier management on flexibility and delivery performance, customer relational capital only strengthens the influence of green customer management on flexibility performance.Originality/valueThe study enriches the extant literature by developing a holistic framework integrating corporate social responsibility, green supply chain management, relational capital, and operational performance and unraveling their intricate relationships. The authors’ findings help practitioners prioritize proactive steps in environmental conservation more than achieving operational performance.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124733231","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}

{"title":"Evaluation of circular supply chains barriers in the era of Industry 4.0 transition using an extended decision-making approach","authors":"Chao Shang, P. Saeidi, C. Goh","doi":"10.1108/jeim-09-2021-0396","DOIUrl":"https://doi.org/10.1108/jeim-09-2021-0396","url":null,"abstract":"PurposeThe poor leadership style is a key obstacle to the effective implementation of Industry 4.0 technologies. To successfully apply the Industry 4.0 technologies, which can enhance the sustainability of firms, senior management needs to be inspiring and transformational. On the other hand, numerous factors can hinder the Industry 4.0 transition and “Circular Supply Chain (CSC)” transformation. Therefore, the main purpose of this study is to evaluate the related barriers of CSCs in the era of Industry 4.0 transition.Design/methodology/approachThe current study developed an innovative decision-making approach with the help of the “Combined Compromise Solution (CoCoSo)” method and “Criteria Importance Through Intercriteria Correlation (CRITIC)” method on the “q-Rung Orthopair Fuzzy Sets (q-ROFSs).” CRITIC in this combined method was used to predict the importance or weighting degrees of the CSCs barriers in the age of Industry 4.0 transition.FindingsThe results of this study found that the absence of knowledge about the Industry 4.0 technologies and circular approaches was the first barrier followed by the problems associated with data security in relationship management in circular flows, the deficiency of knowledge regarding the data management among stakeholders and the lack of awareness about the potential benefits of autonomous systems in labor-oriented “End-of-Life (EOL)” activities for CSCs in the era of Industry 4.0 transition.Research limitations/implicationsA limitation may be that despite the generalizability of the proposed framework, the results may differ when it is implemented in different sectors. By emphasizing the obstacles to sustainable operations of supply chains (SCs) in the context of circular economy (CE) and Industry 4.0, researchers working in the same domain may be encouraged to find ways to remove such obstacles in different settings. As suggested in this study, the priority of various barriers helps researchers suggest effective strategies for the sustainable development of companies within the current dynamic business atmosphere.Practical implicationsThe findings of this paper can aid industry practitioners in fixing their attention on the digitization or automation of their systems in the context of sustainability or resource circularity. Note that within the current context of CE, one of the crucial issues is how to conserve the existing resources; the answer to this question can save the environment.Originality/valueThe current paper proposed a new multi-criteria decision-making method using q-ROFSs to analyze, rank and evaluate the CSC barriers in the age of Industry 4.0 transition. To this end, a new decision-making approach with the help of CRITIC and CoCoSo methods on q-ROFSs called q-ROF-CRITIC-CoCoSo was introduced to evaluate the CSCs barriers in the era of Industry 4.0 transition.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133865907","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}

{"title":"The effects of supply chain risk information processing capability and supply chain finance on supply chain resilience: a moderated and mediated model","authors":"Yaqin Yuan, Wei Li","doi":"10.1108/jeim-09-2021-0383","DOIUrl":"https://doi.org/10.1108/jeim-09-2021-0383","url":null,"abstract":"PurposeThis study aims to investigate the impact of supply chain risk (SCR) information processing capabilities (e.g. SCR information sharing and SCR information analysis) and supply chain finance (SCF) on supply chain resilience, as well as the moderating effect of environmental uncertainty in the relationship between SCF and supply chain resilience.Design/methodology/approachThis paper proposes a theoretical model grounded on the information processing theory. Data collected from 216 Chinese firms are used to test the theoretical model by employing structural equation modelling.FindingsThe findings reveal that SCR information processing capabilities have a significant impact on both SCF and supply chain resilience. SCF plays a partial mediating role in the relationship between SCR information processing capabilities and supply chain resilience. In addition, environmental uncertainty moderates the relationship between SCF and supply chain resilience.Originality/valueFirst, this paper enriches the knowledge of how information processing capability affects SCF and supply chain resilience as the study considers the more granular SCR information rather than general information that has been discussed in previous studies. Second, this is one of the first papers to establish the relationship between SCF and supply chain resilience in emerging economies. Next, the paper extends the theoretical framework of the antecedents and consequences of SCF. Moreover, the study further facilitates the understanding of the role of the external environment in SCR and SCF management.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129375982","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}

{"title":"Mapping the links between Industry 4.0, circular economy and sustainability: a systematic literature review","authors":"V. S. Patyal, Pranjal Sarma, S. Modgil, Tirthankar Nag, Denis Dennehy","doi":"10.1108/jeim-05-2021-0197","DOIUrl":"https://doi.org/10.1108/jeim-05-2021-0197","url":null,"abstract":"PurposeThe study aims to map the links between Industry 4.0 (I-4.0) technologies and circular economy (CE) for sustainable operations and their role to achieving the selected number of sustainable development goals (SDGs).Design/methodology/approachThe study adopts a systematic literature review method to identify 76 primary studies that were published between January 2010 and December 2020. The authors synthesized the existing literature using Scopus database to investigate I-4.0 technologies and CE to select SDGs.FindingsThe findings of the study bridge the gap in the literature at the intersection between I-4.0 and sustainable operations in line with the regenerate, share, optimize, loop, virtualize and exchange (ReSOLVE) framework leading to CE practices. Further, the study also depicts the CE practices leading to the select SDGs (“SDG 6: Clean Water and Sanitation,” “SDG 7: Affordable and Clean Energy,” “SDG 9: Industry, Innovation and Infrastructure,” “SDG 12: Responsible Consumption and Production” and “SDG 13: Climate Action”). The study proposes a conceptual framework based on the linkages above, which can help organizations to realign their management practices, thereby achieving specific SDGs.Originality/valueThe originality of the study is substantiated by a unique I-4.0-sustainable operations-CE-SDGs (ISOCES) framework that integrates I-4.0 and CE for sustainable development. The framework is unique, as it is based on an in-depth and systematic review of the literature that maps the links between I-4.0, CE and sustainability.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133191860","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}

{"title":"Evaluate the sustainable marketing strategy to optimal online leasing of new energy vehicles under the background big data economy","authors":"Tang Daifen","doi":"10.1108/jeim-02-2021-0087","DOIUrl":"https://doi.org/10.1108/jeim-02-2021-0087","url":null,"abstract":"PurposeUnder the big data background, there are many influencing factors for investors of new energy vehicles (NEV), and government subsidies promote the sustainable development of the new energy vehicle industry. Therefore, the purpose of the study is to provide solutions for the sustainable development of NEV.Design/methodology/approachThe sustainable marketing strategy of NEV in China is put forward. This paper first analyzes the subsidy policy effect of NEV under the background of big data. It then establishes the online optimal leasing strategy under multiple strategy choices and the online leasing strategy of multiple vehicles under the inflation market.FindingsWith the fixed cost of NEV in each lease period, the optimal competition ratio of online decision-makers will continue to decrease with the increase of the difference between prepaid funds and government subsidies. In the decision-making of renting and purchasing multiple vehicles, the general strategy competition ratio is 2.922, while the optimal competition ratio of the online renting and purchasing strategy proposed by the research is 2.723.Research limitations/implicationsThe research is limited by the limited data and information collected, so the optimal decision-making model has some limitations. The authors need to find more representative data to optimize the model.Practical implicationsAs an emerging industry, NEV have developed rapidly in recent years. Based on the online algorithm and competitive ratio theory, this paper solves the decision-making problem of operators and gives the optimal strategy to promote the green development of the new energy vehicle industry.Originality/valueThis paper proposes the optimal strategy for online investors of new energy vehicle operators by combining online algorithm and competitive ratio theory. The numerical analysis results of the optimal online model under multi strategy selection show that with the same difference between prepaid funds and government subsidies, the time point will be delayed and the time point will be advanced as the cost of leasing NEV in each period increases.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126322421","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}

{"title":"Understanding mobile users' information adoption behaviour: an extension of the information adoption model","authors":"Abdulaziz Elwalda, Ismail Erkan, Mushfiqur Rahman, Deniz Zeren","doi":"10.1108/jeim-04-2020-0129","DOIUrl":"https://doi.org/10.1108/jeim-04-2020-0129","url":null,"abstract":"PurposeMobile messaging applications (MMAs) have surpassed top social media platforms. Recent and rapid use of MMAs has made it extremely difficult to ignore the existence of customer-to-customer (C2C) mobile information. This study, therefore, aims to expand the knowledge of customers' adoption behaviour of such information.Design/methodology/approachThrough applying and utilizing social support theory (SST) and the information adoption model (IAM), this study introduces a holistic theoretical model, explaining customers' adoption of information derived from MMAs and exploring the antecedents of IAM. Based on the data collected from 305 UK MMA users, this study empirically tests the research model using structural equation modelling estimation.FindingsThe results of this study reveal that social support is a key antecedent of information quality and credibility and support IAM in terms of its ability to explain MMAs' information adoption.Practical implicationsThe insights are valuable for businesses and marketers to understand customers' mobile communications and be socially support-oriented while developing marketing communication strategies.Originality/valueThe study integrates SST and IAM to improve the understanding of customers' information adoption behaviour. It is the first attempt that establishes that social support is a key antecedent of IAM.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129618124","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}

{"title":"Analyzing the Internet financial market risk management using data mining and deep learning methods","authors":"Ran Feng, Xiao-yu Qu","doi":"10.1108/jeim-03-2021-0155","DOIUrl":"https://doi.org/10.1108/jeim-03-2021-0155","url":null,"abstract":"PurposeTo identify and analyze the occurrence of Internet financial market risk, data mining technology is combined with deep learning to process and analyze. The market risk management of the Internet is to improve the management level of Internet financial risk, improve the policy of Internet financial supervision and promote the healthy development of Internet finance.Design/methodology/approachIn this exploration, data mining technology is combined with deep learning to mine the Internet financial data, warn the potential risks in the market and provide targeted risk management measures. Therefore, in this article, to improve the application ability of data mining in dealing with Internet financial risk management, the radial basis function (RBF) neural network algorithm optimized by ant colony optimization (ACO) is proposed.FindingsThe results show that the actual error of the ACO optimized RBF neural network is 0.249, which is 0.149 different from the target error, indicating that the optimized algorithm can make the calculation results more accurate. The fitting results of the RBF neural network and ACO optimized RBF neural network for nonlinear function are compared. Compared with the performance of other algorithms, the error of ACO optimized RBF neural network is 0.249, the running time is 2.212 s, and the number of iterations is 36, which is far less than the actual results of the other two algorithms.Originality/valueThe optimized algorithm has a better spatial mapping and generalization ability and can get higher accuracy in short-term training. Therefore, the ACO optimized RBF neural network algorithm designed in this exploration has a high accuracy for the prediction of Internet financial market risk.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114708370","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}

{"title":"Leveraging enterprise social network technology: understanding the roles of compatibility and intrinsic motivation","authors":"Qiong Jia, Yang Lei, Yue Guo, Xiaotong Li","doi":"10.1108/jeim-05-2021-0225","DOIUrl":"https://doi.org/10.1108/jeim-05-2021-0225","url":null,"abstract":"PurposeThis study explores the factors influencing the value of enterprise social media (ESM) from the perspective of compatibility. Establishing a theoretical model based on compatibility theory, the authors examine the effects of two dimensions of compatibility and the mediating effects of employees' intrinsic motivations. ESM is an important tool that helps companies to enhance knowledge sharing and cross-department collaboration. Thus, it is important to understand factors that can facilitate the role of ESM in improving enterprise operating performance.Design/methodology/approachThe authors conducted a survey among 353 users of a leading ESM platform and empirically investigated how compatibility influences ESM value through employees' intrinsic motivations. Structural equation modeling (SEM) was applied to study the relationship among compatibility, employees' intrinsic motivations and ESM value.FindingsThe empirical research results indicate that compatibility of self-interest with group interest influences the value of ESM, and intrinsic motivations toward collaboration and toward knowledge management partially mediate the effects of the two dimensions of compatibility on ESM value.Research limitations/implicationsFirst, the empirical analysis relies on data from surveying employees of Chinese companies. Therefore, one direction for future research is to reexamine the model using data from other countries. Second, the effects of compatibility identified in the study may vary among different ESM platforms. In addition, the findings may change for organizations having different sizes.Practical implicationsThis finding suggests that managers should pay close attention to potential conflicts of interest when implementing ESM to enhance group communication and collaboration. This study also highlights the importance of compatibility of new working processes with experience in practice. In addition, intrinsic motivations towards both cooperation and knowledge management in ESM are important factors influencing the value creation of ESM. Therefore, to cultivate employees' intrinsic motivation, managers and organizations need to facilitate the formation of a collaborative atmosphere and habits of cooperative adoption.Originality/valueAlthough previous studies show that compatibility is a strong belief salient to technology acceptance and continuance usage behavior, the operational definition of compatibility developed by prior studies has generally been limited to the technology perspective and the individual level. However, the primary benefit of ESM is enabling online team collaboration and knowledge sharing across various departments. Thus, the level of compatibility between employees' self-interests and group interests may influence their intrinsic motivations toward ESM usage. From this perspective of individual–group interest conflicts, the authors propose a conceptual research model based on the theory of compatibility in innovation diffus","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126520114","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}

{"title":"The coordination effect of B2B digital process capabilities on competitive performance: balancing or complementing","authors":"Zhen Zhu, Shuai-fu Lin, Yi Jiang, Qi Liu","doi":"10.1108/jeim-01-2021-0037","DOIUrl":"https://doi.org/10.1108/jeim-01-2021-0037","url":null,"abstract":"PurposeThe purpose of this paper is to investigate the consequences of two strategies of coordinating the online procurement capability and the online channel management capability on competitive performance.Design/methodology/approachA research model is presented to examine the performance impacts of these two coordination strategies, namely the balancing strategy (achieving a close match relationship) and the complementing strategy (maintaining the synergy effect), and tested using firm-level data collected from 196 manufacturing firms in China. Garen's two-stage econometric technique was used to identify the impacts of two coordination strategies on competitive performance.FindingsOur study discusses and compares two different coordination strategies of mitigating the operational tensions across processes and deploying resource configurations for improving competitive performance. Our results show that while the balancing strategy can mitigate the risks resulted, the complementing strategy does not create synergistic effects on the focal firms' competitive performance.Originality/valueThe results extend our understanding of the nature of B2B digital process coordination both in IS management and supply chain operations.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132949065","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}

{"title":"The role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries","authors":"V. Narwane, Rakesh D. Raut, V. Yadav, N. Cheikhrouhou, B. Narkhede, P. Priyadarshinee","doi":"10.1108/jeim-11-2020-0463","DOIUrl":"https://doi.org/10.1108/jeim-11-2020-0463","url":null,"abstract":"PurposeBig data is relevant to the supply chain, as it provides analytics tools for decision-making and business intelligence. Supply Chain 4.0 and big data are necessary for organisations to handle volatile, dynamic and global value networks. This paper aims to investigate the mediating role of “big data analytics” between Supply Chain 4.0 business performance and nine performance factors.Design/methodology/approachA two-stage hybrid model of statistical analysis and artificial neural network analysis is used for analysing the data. Data gathered from 321 responses from 40 Indian manufacturing organisations are collected for the analysis.FindingsStatistical analysis results show that performance factors of organisational and top management, sustainable procurement and sourcing, environmental, information and product delivery, operational, technical and knowledge, and collaborative planning have a significant effect on big data adoption. Furthermore, the results were given to the artificial neural network model as input and results show “information and product delivery” and “sustainable procurement and sourcing” as the two most vital predictors of big data adoption.Research limitations/implicationsThis study confirms the mediating role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries. This study guides to formulate management policies and organisation vision about big data analytics.Originality/valueFor the first time, the impact of big data on Supply Chain 4.0 is discussed in the context of Indian manufacturing organisations. The proposed hybrid model intends to evaluate the mediating role of big data analytics to enhance Supply Chain 4.0 business performance.","PeriodicalId":390951,"journal":{"name":"J. Enterp. Inf. Manag.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127531700","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}