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Computer-assisted construct classification of organizational performance concerning different stakeholder groups

arXiv 2107.05133 ↗First posted 11 Jul 2021cs.CLcited by 0

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Abstract (arXiv)

The number of research articles in business and management has dramatically increased along with terminology, constructs, and measures. Proper classification of organizational performance constructs from research articles plays an important role in categorizing the literature and understanding to whom its research implications may be relevant. In this work, we classify constructs (i.e., concepts and terminology used to capture different aspects of organizational performance) in research articles into a three-level categorization: (a) performance and non-performance categories (Level 0); (b) for performance constructs, stakeholder group-level of performance concerning investors, customers, employees, and the society (community and natural environment) (Level 1); and (c) for each stakeholder group-level, subcategories of different ways of measurement (Level 2). We observed that increasing contextual information with features extracted from surrounding sentences and external references improves classification of disaggregate-level labels, given limited training data. Our research has implications for computer-assisted construct identification and classification - an essential step for research synthesis.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 15 references that are in the map. First posted on arXiv 11 Jul 2021.

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References · 1

  1. 2021Machine Reading of Hypotheses for Organizational Research Reviews and Pre-trained Models via R Shiny App for Non-Programmerscited by 1

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