Psycho-managerial text mining (PMTM): a framework for developing and validating psychological/managerial constructs from a theory/text-driven approach

Jorge Iván Pérez Rave (), Gloria Patricia Jaramillo Álvarez () and Juan Carlos Correa Morales ()
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Jorge Iván Pérez Rave: Universidad Nacional de Colombia
Gloria Patricia Jaramillo Álvarez: Universidad Nacional de Colombia
Juan Carlos Correa Morales: Universidad Nacional de Colombia

Journal of Marketing Analytics, 2023, vol. 11, issue 4, No 18, 777-808

Abstract: Abstract This paper addresses two concerns in the construction and validation of psychological/managerial constructs from texts: (1) The procedure for studying content validity is mainly based on human tasks, subjectivity, limited to small data, and difficult to reproduce/replicate; (2) Traditional latent variable representation (a merged list or random parcel of words) lacks theoretical rationality and does not guarantee the representativity of valuable qualities, perceptual entities, and actions of the construct. The paper proposes a framework—PMTM—for developing/validating measures of psychological/managerial constructs from texts (three stages and 16 steps) by incorporating linguistic, psychometrical, and computational resources. PMTM includes five new properties to guide content validity analysis automatically, and contains a new method for refining dictionaries, entitled “embedded voting,” which emulates expert judgments. In addition, the paper provides empirical evidence derived from the application of PMTM to the case of transformational leadership using data from organizational documents, interviews, essays, blog posts, surveys, and speeches by former US presidents. The framework can also be used as a comprehensive template with the potential to exploit customer/service texts from a theory/text-driven approach to overcome recent challenges stated by the marketing literature, including the lack of standardization and inconsistency in the definitions and measurement of marketing constructs.

Keywords: Text mining; Text analytics; Constructs analysis; Automated dictionary creation; Theory/text-driven approach; Transformational leadership (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1057/s41270-022-00181-8

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