大数据分析与供应链绩效:供应链能力与创新的中介作用

Management Science Letters Pub Date : 2022-01-01 DOI:10.5267/j.msl.2022.4.003

Amjad Ali, Shoeb Ahmed

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引用次数: 0

摘要

本研究旨在研究大数据分析、创新和能力对供应链的影响，并发现组织灵活性对供应链绩效的调节作用(SCP)，以及竞争强度作为控制变量对供应链绩效的影响。本研究旨在提出一个基于资源基础理论的关系观的理论模型。通过问卷调查的方式收集数据，25家制造企业的管理者参与了本次调查。本研究发现BDA与SCI、SCC以及SCP有良好且强烈的关联。在这项研究中，大多数制造商公司都使用BDA来加速他们的站立算法，更快地处理大量数据集。

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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Big data analytics and supply chain performance: The mediating role of supply chain capabilities and innovation

This study aims to examine the influence of Big Data analytics, innovation & capabilities in the supply chain as well as to find the moderating effect of organisational flexibility on the performance of the supply chain (SCP) and find the effect of competitive intensity as a controlling variable on the performance of supply chain. This research aims to present a theoretical model based on the resource-based theory's relational view (RBV). The data was collected through a survey questionnaire and 25 manufacturer firms managers participate in this survey. According to the findings of this study BDA has a favourable and strong association with SCI and SCC, as well as SCP. The majority of the manufacturers' firms in this research employed BDA to speed up their standing algorithms quicker with massive data sets.

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来源期刊

Management Science Letters

自引率

0.00%

发文量

审稿时长

20 weeks

期刊介绍： Management Science Letters is a peer reviewed, monthly publication dedicated to create a forum for scientists in all over the world who wish to share their experiences and knowledge in the field of management skills in the form of original, high quality and value added articles. The journal''s policy is to perform a peer review on all submitted articles and the papers will be appeared in a form of online on our website as soon as the review result becomes positive. The journal covers both empirical and theoretical aspects of management and gives the chance on sharing knowledge among practitioners. Management Science Letters is dedicated for publishing in the following areas: • Quality Management • Production Management (Scheduling, Production management, etc.) • Total Quality Management (TQM) • Six Sigma • Production Efficiency • Just in Time Inventory • Data Envelopment Analysis • Balanced Score Card • Activity Based Cost (ABC) • Technology Acceptance Model • Marketing planning and Customer Relationship Management • Critical Success Factors • e-learning • Customer satisfaction, Job satisfaction, Job turnover, • Organizational commitment, Employee Commitment • Knowledge Management • Knowledge sharing • Human Resources Management (Employee training, Employee Performance, Work achievements,) • Small and medium-sized enterprises (SMEs) issues and Economic development • Innovation, Creativity, Productivity and Performance • Multi-Criteria Decision Making Applications in Management Science (AHP, BWM, TOPSIS, …) • Education Management, Social development, Public Policy • Tourism Industry, Tourism promotion, Tourism directorates • Business performance and financial performance