理解和识别定性案例研究中的“主题”

Q4 Business, Management and Accounting South Asian Journal of Business and Management Cases Pub Date : 2022-10-27 DOI:10.1177/22779779221134659
Shreya Mishra, A. Dey
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引用次数: 3

摘要

主题是任何定性研究方法的核心。主题是无法被观察到的,因为它们是存在于研究参与者/受访者头脑中的感知、经历、感受、价值观和情绪。如果研究人员觉得主题是可见的,不需要额外的努力来提取,她可能被上下文混淆了。因为主题是嵌入在受访者头脑中的无形感知和经验,为了提取它们,研究人员需要“问”问题。深入访谈或焦点小组讨论是更容易发现主题的过程。只有通过访谈或焦点小组讨论或两者兼而有之收集数据后,研究人员才能转向二手数据来源。确定与理论相关的主题决定了研究的贡献。主题应该远离上下文的任何方面的描述。主题应该更接近于解释一项研究的内生结构。此外,定性案例研究(QCSR)的贡献通常来自“理论的延伸”或“发展更深层次的理解-现象的新含义”。然而,缺乏关于如何识别主题的知识导致了肤浅的发现,对文学的贡献有限或没有。因此,这篇社论致力于解释确定主题的过程,以便通过QCSR做出重大贡献。主题可以用任何形式的定性研究方法来识别,无论是现象学、叙事分析、扎根理论、主题分析还是任何其他形式。然而,确定主题的目的和过程可能会有所不同,不仅基于方法,而且基于研究问题(Braun & Clarke, 2006)。例如,主题分析有助于识别数据中出现的共同模式,因此,如果目标是搜索独特的主题,那么它不是一种合适的方法(Kiger & Varpio, 2020)。而使用扎根理论是适当的,当研究人员寻找重要的主题,可以是特殊的。我们不提倡任何特定的分析过程来确定主题,相反,我们将重点解释在数据中寻找什么,以便确定适当的主题。
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Understanding and Identifying ‘Themes’ in Qualitative Case Study Research
Themes are at the heart of any qualitative research approach. Themes cannot be observed as they are perceptions, experiences, feelings, values and emotions residing in the minds of participants/respondents of a research. If a researcher feels that a theme is visible and no extra effort will be needed to extract, she may be confusing with the context. Because the themes are invisible perceptions and experiences embedded in the minds of respondents, to extract them the researcher needs to ‘ask’ questions. In-depth interviews or focus group discussions are easier processes to detect the themes. Only after collecting data with either interviews or focus group discussions or both, a researcher can turn to secondary sources of data. Identification of themes that connect with the theory determines the contribution of research. Themes should be far away from the description of any facet of the context. Themes should be closer to explaining the endogenous constructs of a research. Further, often the contribution of a qualitative case study research (QCSR) emerges from the ‘extension of a theory’ or ‘developing deeper understanding—fresh meaning of a phenomenon’. However, the lack of knowledge on how to identify themes results in shallow findings with limited to no contribution towards literature. This editorial is thus dedicated to explaining the process of identifying themes to make significant contributions through a QCSR. Themes are identified with any form of qualitative research method, be it phenomenology, narrative analysis, grounded theory, thematic analysis or any other form. However, the purpose and process of identifying themes may differ based not only on the methodology but also the research questions (Braun & Clarke, 2006). For instance, a thematic analysis helps to identify common patterns emerging from data, hence it is not an appropriate method if the objective is to search for unique themes (Kiger & Varpio, 2020). While the use of grounded theory is proper when the researcher looks for significant themes which can be idiosyncratic. We are not advocating any particular analysis process for identifying themes, rather we shall focus on explaining what to look for in data so that appropriate themes can be identified.
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来源期刊
South Asian Journal of Business and Management Cases
South Asian Journal of Business and Management Cases Business, Management and Accounting-Management of Technology and Innovation
CiteScore
1.70
自引率
0.00%
发文量
19
期刊介绍: South Asian Journal of Business and Management Cases (SAJBMC) is a peer-reviewed, tri-annual journal of Birla Institute of Management Technology, Greater Noida (India). The journal aims to provide a space for high-quality original research or analytical cases, evidence-based case studies, comparative studies on industry sectors, products, and practical applications of management concepts. The journal likes to publish problem-solving, decisional and applied types of cases. Such cases must have linkage with theory, at least one dilemma (also known as case issue) and a protagonist around whom the case issue will revolve. Publication of pure research, applied research and field studies with empirical data do not fall under the domain of SAJBMC. Fictitious cases are not welcome.
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