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首页> 外文期刊>Journal of Cleaner Production >Linking big data analytics and operational sustainability practices for sustainable business management
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Linking big data analytics and operational sustainability practices for sustainable business management

机译：将大数据分析和运营可持续发展实践与可持续业务管理联系起来

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Big data analytics is becoming very popular concept in academia as well as in industry. It has come up with new decision tools to design data-driven supply chains. The manufacturing industry is under huge pressure to integrate sustainable practices into their overall business for sustainbale operations management. The purpose of this study is to analyse the predictors of sustainable business performance through big data analytics in the context of developing countries. Data was collected from manufacturing firms those have adopted sustainable practices. A hybrid Structural Equation Modelling - Artificial Neural Network model is used to analyse 316 responses of Indian professional experts. Factor analysis results shows that management and leadership style, state and central-government policy, supplier integration, internal business process, and customer integration have a significant influence on big data analytics and sustainability practices. Furthermore, the results obtained from structural equation modelling were feed as input to the artificial neural network model. The study findings shows that management and leadership style, state and central-government policy as the two most important predictors of big data analytics and sustainability practices. The results provide unique insights into manufacturing firms to improve their sustainable business performance from an operations management viewpoint. The study provides theoretical and practical insights into big data implementation issues in accomplishing sustainability practices in business organisations of emerging economies. (C) 2019 Elsevier Ltd. All rights reserved.
机译：大数据分析在学术界以及工业中变得非常受欢迎。它提出了新的决策工具来设计数据驱动的供应链。制造业受到巨大的压力，将可持续惯例整合到他们的综合业务中，以便为AcceptBale运营管理提供。本研究的目的是通过发展中国家背景下的大数据分析来分析可持续业务绩效的预测因素。从制造公司收集数据，这些公司采用可持续惯例。一种混合结构方程模型 - 人工神经网络模型用于分析316个印度专家专家的回应。因素分析结果表明，管理和领导风格，国家和中央政府政策，供应商集成，内部业务流程和客户集成对大数据分析和可持续发展实践产生了重大影响。此外，从结构方程建模获得的结果被馈送为对人工神经网络模型的输入。研究结果表明，管理和领导风格，国家和中央政府作为大数据分析和可持续发展实践的两个最重要的预测因子。结果为制造企业提供了独特的见解，从运营管理方面提高其可持续业务绩效。该研究为在新兴经济体业务组织中实现了较大的数据实施问题提供了理论和实践洞察。 （c）2019 Elsevier Ltd.保留所有权利。

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