Effects of Big Data Analytics on Sustainable Manufacturing: A Comparative Study Analysis

IF 1.6 Q3 URBAN STUDIES
C. Er, Thikrait Al Mosawi
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引用次数: 0

Abstract

Application of big data analytics (BDA) is seen in various disciplines within an organization to predict trends, explore opportunities and monitor performance. Among all the industries, BDA presents immense value in sustainable manufacturing (SM) given that it is an industry that consumes a high amount of energy, emits high amounts of waste and carbon emissions and requires a large amount of manpower. This paper aims at illustrating the effects of BDA in supporting SM by studying the Indian manufacturing firms which have unfavorable labor laws compared to other developing countries. With an extensive literature review, this paper discusses the relationship between BDA and sustainability, the capabilities of BDA, the concept of SM, the BDA framework for SM, the relationship between Industry 4.0 and SM and the challenges of implementing BDA. Using qualitative meta-analysis research methodology, the paper examines the nine common critical success factors that enable SM through BDA implementation by comparing 15 primary studies. Finally, the paper concludes the research findings and outlines future research directions. The study provides theoretical and practical contributions to BDA implementation in achieving effective SM practices in emerging economies.
大数据分析对可持续制造业影响的比较研究分析
大数据分析(BDA)应用于组织内的各个学科,以预测趋势、探索机会和监控绩效。在所有行业中,BDA在可持续制造业(SM)中具有巨大价值,因为它是一个消耗大量能源、排放大量废物和碳排放并需要大量人力的行业。本文旨在通过研究与其他发展中国家相比劳动法不利的印度制造业企业,说明BDA在支持SM方面的作用。通过广泛的文献综述,本文讨论了BDA与可持续性之间的关系、BDA的能力、SM的概念、SM的BDA框架、工业4.0与SM之间的关系以及实施BDA的挑战。本文采用定性荟萃分析研究方法,通过对15项主要研究的比较,检验了通过BDA实施SM的9个常见关键成功因素。最后,本文对研究结果进行了总结,并对未来的研究方向进行了展望。该研究为BDA在新兴经济体实现有效SM实践方面的实施提供了理论和实践贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.90
自引率
0.00%
发文量
24
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