Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/114032
| Title: | Good theories predict : unveiling the untapped potential of “necessity” theorizing | Authors: | Lee, W Lu, L |
Issue Date: | Feb-2025 | Source: | Journal of hospitality and tourism research, Feb. 2025, v. 49, no. 2, p. 219-234 | Abstract: | In this paper, we seek to introduce the concept of necessity logic of causality, which, despite its inherent merits in parsimony and predictive accuracy, has not received adequate attention. Our paper begins by providing a comprehensive review of various causal logic, including sufficiency, necessity, and contributory. We then critically examine the key assumptions of necessary causation (i.e., non-additivity, determinism, and asymmetry), and highlight the benefits of necessary causalities in theoretical innovation. Also, we workshop methodological protocols for necessity theory testing. Subsequently, we explore the potential of integrating necessity theories in the hospitality and tourism field by drawing on conceptual-contextual theorizing, leading to the development of “homegrown” theories. We also contend that necessary causality in transdisciplinary research can facilitate broader knowledge exchange to neighboring domains. We conclude by identifying promising research areas for necessity theorizing and testing in hospitality and tourism research. | Keywords: | Causality Necessary causality Necessary condition analysis Necessity theorizing Necessity theory |
Publisher: | SAGE Publications | Journal: | Journal of hospitality and tourism research | ISSN: | 1096-3480 | EISSN: | 1557-7554 | DOI: | 10.1177/10963480231188666 | Rights: | This is the accepted version of the publication Lee, W., & Lu, L. (2023). Good Theories Predict: Unveiling the Untapped Potential of “Necessity” Theorizing. Journal of Hospitality & Tourism Research, 49(2), 219-234. Copyright © 2023 The Author(s). DOI: 10.1177/10963480231188666. |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Lee_Good_Theories_Predict.pdf | Pre-Published version | 738.93 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.



