工业工程案例研究中的方法论问题:重新审视进一步建议的挑战

Paulo Augusto Cauchick-Miguel, Thayla Tavares Sousa-Zomer, Guilherme Tortorella
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引用次数: 0

摘要

本文讨论了巴西学术界在工业工程(IE)进行基于案例的研究时遇到的困难。它还提供了进一步的建议,以提高方法的严谨性。本文通过提供巴西研究方法的历史视角,为案例研究的实践做出了贡献,并为改进案例研究的采用以及方法的严谨性提供了指导。研究方法首先通过文献综述确定进行案例研究时的主要挑战。然后,对巴西学者进行了一项探索性调查,以确定这些学者所感受到的挑战。然后提供建议,特别是关于数据分析阶段。这些建议是根据现有文献和作者进行定性研究的经验来讨论的。学者们认为,在进行案例研究时存在的困难可分为三个“阿奎拉的地狱”:(1)理论背景薄弱;(2)案例研究设计/规划粗心;(iii)脆弱/不确定的数据分析。改进数据分析过程的建议包括建立叙述、数据简化、改进编码等。提高有效性也是必要的。这些建议对早期研究人员特别有意义,并为在进行案例研究时提高稳健性提供了指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methodological concerns in case-based research in industrial engineering: revisiting the challenges towards further recommendations
Paper aims This paper addresses difficulties among the Brazilian scholarly community in industrial engineering (IE) when conducting case-based research. It also provides further recommendations to increase methodological rigour. Originality The paper contributes to the practice of case research by providing a historical perspective of research methodology in Brazil and offering guidance to improve case research adoption as well as the methodological rigour. Research method The main challenges when conducting case research were first identified through a literature review. Then, an exploratory survey with Brazilian scholars was conducted to identify challenges perceived by those. Recommendations are then provided, especially regarding the data analysis stage. The recommendations are discussed in the light of the existing literature and based on authors’ experience in conducting qualitative research. Main findings Difficulties when conducting case research identified by scholars can be classified in three ‘Aquila’s hells’: (i) weak theoretical background, (ii) careless case study design/planning; and (iii) fragile/uncertain data analysis. Suggestions to improve the data analysis process consist of building a narrative, data reduction, improving coding, etc. Improving validity is also necessary. Implications for theory and practice The recommendations are especially meaningful to early-stage researchers and provide guidance to improve robustness when conducting case research.
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