A causal configurational analysis of knowledge hiding from a conversational constraint perspective: evidence from China

Purpose Drawing on Conversational Constraint Theory (CCT), this study aims to examine the causal relationships between constraint elements in knowledge-request conversations (i.e. request directness, request politeness, public versus private requests, affective relationships, the requestee’s gender and negative affective states), and knowledge hiding. Design/methodology/approach A survey of 386 knowledge employees from different companies in China was conducted. Event reconstruction principles were applied to reduce potential recall bias. Necessary Condition Analysis (NCA) and fuzzy set Qualitative Comparative Analysis (fsQCA) were used. NCA and fsQCA were used to perform necessary causality analyses (“No Y without X”), whereas fsQCA was used to conduct sufficiency analyses (“If X, then Y”). Findings The results show that no single factor in knowledge requests serves as a necessary condition for either high or low knowledge hiding; four pathways with different configurations lead to high knowledge hiding; and no consistent pathways leading to low knowledge hiding were identified, highlighting causal asymmetry in comparison to pathways leading to high knowledge hiding. Originality/value First, this study advances research on the antecedents of knowledge hiding by verifying the complex causal relationships between conversational constraints and knowledge hiding. Second, it offers new insights by proposing an integrated framework based on CCT. Third, a mixed-method approach, combining NCA and fsQCA, is used to provide a detailed analysis of the antecedents of knowledge hiding.

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Publication Details

Journal
Journal of Knowledge Management
Published
2025-04-21
DOI
https://doi.org/10.1108/jkm-04-2024-0412
Citations
2
Primary Topic
Knowledge Management and Sharing
Type
article
Field-Weighted Citation Impact
7.73
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article

A causal configurational analysis of knowledge hiding from a conversational constraint perspective: evidence from China

Peixu He, Amitabh Anand, Jianqing Cheng, Qing Xia et al.
2 citations
Journal of Knowledge Management
Knowledge Management and Sharing
7.73
article

A causal configurational analysis of knowledge hiding from a conversational constraint perspective: evidence from China

Peixu He, Amitabh Anand, Jianqing Cheng, Qing Xia, Cuiling Jiang
article en
2 citations

Abstract

Purpose Drawing on Conversational Constraint Theory (CCT), this study aims to examine the causal relationships between constraint elements in knowledge-request conversations (i.e. request directness, request politeness, public versus private requests, affective relationships, the requestee’s gender and negative affective states), and knowledge hiding. Design/methodology/approach A survey of 386 knowledge employees from different companies in China was conducted. Event reconstruction principles were applied to reduce potential recall bias. Necessary Condition Analysis (NCA) and fuzzy set Qualitative Comparative Analysis (fsQCA) were used. NCA and fsQCA were used to perform necessary causality analyses (“No Y without X”), whereas fsQCA was used to conduct sufficiency analyses (“If X, then Y”). Findings The results show that no single factor in knowledge requests serves as a necessary condition for either high or low knowledge hiding; four pathways with different configurations lead to high knowledge hiding; and no consistent pathways leading to low knowledge hiding were identified, highlighting causal asymmetry in comparison to pathways leading to high knowledge hiding. Originality/value First, this study advances research on the antecedents of knowledge hiding by verifying the complex causal relationships between conversational constraints and knowledge hiding. Second, it offers new insights by proposing an integrated framework based on CCT. Third, a mixed-method approach, combining NCA and fsQCA, is used to provide a detailed analysis of the antecedents of knowledge hiding.

Journal of Knowledge ManagementVol. 29(6)
Huaqiao University (CN), Excelia Business School (FR), Xiangtan University (CN), Yunnan University of Finance And Economics (CN), Kedge Business School (FR)
Openalex Percentile: Top 4%
Knowledge Management and Sharing
7.73
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