期刊
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
卷 210, 期 -, 页码 27-41出版社
ELSEVIER
DOI: 10.1016/j.ijpe.2019.01.003
关键词
Manufacturing strategy; Performance objectives; Decision areas; Cause and effect relationships; Multiple linear regression
资金
- Coordenagao de Aperfeicoamento de Pessoal de Nivel Superior - Brasil (CAPES) [001]
- Conselho Nacional de Desenvolvimento Cientifico e TecnolOgico (CNPq) [308239/2015-6]
Manufacturing strategy has an important role in business competitive strategy, because it connects performance indicators to company goals. Operations strategy is organized in performance objectives and decision areas constructs that define its content. This paper aims to understand the cause and effect relationships between operations strategy constructs. Considering performance as a dependent variable qualified as the 'effect', and the independent variables as decision areas policies and resources, which play the role as 'cause'. This paper intends to answer two hypotheses: Performance results are dependent on policies and capabilities that are addressed and managed by companies' decision areas; There are specific relationships that connect performance results to decision areas capabilities and policies in 'High Performance Manufacturing Companies'. The study uses information obtained from the 4th round of the 'High Performance Manufacturing Survey'. The dataset is formed by indicators from 304 manufacturing companies of three industries: automotive, electronics and machine tools; that operate in 13 countries. The techniques used for analyzing the available data are descriptive statistics, factor analysis, and multiple linear regression. Results show that innovation, flexibility, quality, cost, speed, and reliability performance have a systemic dependence on structural and infrastructural decision areas, which cover design and managerial perspectives. The study also presents a systemic view that maps the effects on performance by capabilities and policies that are managed by decision areas. The first hypothesis is confirmed by the structural elements that define performance objectives and decision areas, however the second derived hypothesis is partially confirmed, where two patterns are identified by two group of factors: innovation and flexibility, versus cost, quality and time. The understanding of the 'performance function' has an immediate effect on connect it to improvement actions.
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