Research questions and subsequent methodology in the field of management continue to evolve, bringing about more complex models and heightened data requirements and considerations. Thus, the difficulties associated with meeting the requirements of growing methodological rigor (e.g., increasing sample size) have influenced scholars to develop procedures aimed at mitigating these challenges. One such practice is parceling or combining subsets of scale items to form composite indicators of latent variables. Since introduced, parceling approaches have proliferated in a piecemeal fashion, leading to inconsistencies and inaccuracies regarding how parceling is both conducted and reported. With limited consensus about how to parcel, scholars risk perpetuating disjointed, incomplete, or errant approaches that confound the quality of research, accenting the need for a review that organizes the concept of parceling. In response, we offer an examination of parceling in management research with the aim of offering much-needed insight and instruction. To accomplish this, we provide insights that include an overview of parceling from practical and theoretical standpoints, needed clarification surrounding the importance of construct dimensionality when parceling, and robust, informed insights into best practices to aid future researchers in appropriately crafting and reporting on parceling moving forward.

中文翻译：

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在管理研究中使用地块的方法和理论：改进分析的概述和指南


管理领域的研究问题和后续方法不断发展，带来了更复杂的模型和更高的数据要求和考虑。因此，与满足日益增长的方法严谨性要求（例如，增加样本量）相关的困难影响了学者制定旨在缓解这些挑战的程序。其中一种做法是将尺度项目的子集打包或组合，以形成潜在变量的复合指标。自引入以来，包裹方法以零散的方式激增，导致包裹的进行和报告方式不一致和不准确。由于对如何打包的共识有限，学者们有可能使脱节、不完整或错误的方法长期存在，从而混淆研究质量，从而强调需要组织打包概念的综述。作为回应，我们提供了对管理研究中包裹的检查，旨在提供急需的见解和指导。为了实现这一目标，我们提供了见解，包括从实践和理论角度对包裹的概述，需要澄清包裹时结构维度的重要性，以及对最佳实践的可靠、明智的见解，以帮助未来的研究人员适当地制定和报告未来的包裹。