Technical Efficiency in the Manufacturing Industry: A Meta-Regression Analysis

Q2 Business, Management and Accounting

Global Business and Organizational Excellence Pub Date : 2025-03-18 DOI:10.1002/joe.22297

Bijoy Kumar Dey, Charbel Jose Chiappetta Jabbour, Satish Kumar, Ujjwal Kanti Paul

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Abstract

The goal of this paper is to conduct a meta-regression of technical efficiency (TE) in the manufacturing industry, which determines the best possible alternatives that will maximize the outputs using a given level of resources or minimize the inputs to produce a given level of output under given technical conditions. It also examines the impacts of methodological and study-specific attributes on average TE. A total of 103 articles published between 1993 and 2023 were extracted from nine prominent electronic databases. The results discuss a total of 650 TE distributions of manufacturing firms spread all over the world. The findings indicate that improving efficiency makes it possible for an average manufacturing firm in the data set to produce 39% additional output without changing the technology and input. The method of estimating the TE, the functional form of models used, the scale of operations, firm size, and geographic location influence the average TE reported in the literature. Our study advances to extend the literature on TE, and to the best of our knowledge, there has not yet been a published document on a meta-regression on the TE of manufacturing industries.

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制造业技术效率：一个元回归分析

本文的目标是对制造业的技术效率（TE）进行元回归，它确定了在给定技术条件下使用给定资源水平最大化产出或最小化投入以产生给定产出水平的最佳可能替代方案。它还检查了方法和研究特定属性对平均TE的影响。从9个著名的电子数据库中提取了1993年至2023年间发表的103篇文章。结果讨论了分布在世界各地的650家制造企业的TE分布。研究结果表明，在不改变技术和投入的情况下，提高效率可以使数据集中的普通制造企业生产39%的额外产出。估计TE的方法、使用的模型的功能形式、经营规模、企业规模和地理位置影响文献中报告的平均TE。我们的研究进展扩展了关于TE的文献，据我们所知，还没有发表过关于制造业TE的元回归的文件。

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

Global Business and Organizational Excellence Business, Management and Accounting-Business and International Management

CiteScore

7.70

自引率

0.00%

发文量

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