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The critical incident technique (CIT) is widely used in many disciplines; however, scholars have acknowledged challenges associated with analyzing qualitative data when using this technique. Therefore, the purpose of this article is to address the data analysis issues that have been raised by introducing some different contemporary ways of analyzing qualitative critical incident data drawn from recent dissertations conducted in the human resource development (HRD) field.

This article describes and illustrates different contemporary qualitative re-storying and cross-incident analysis approaches with examples drawn from previously and recently conducted qualitative HRD dissertations that have used the CIT.

Qualitative CIT analysis comprises two processes: re-storying and cross-incident analysis. The narrative inquiry–based re-storying approaches the authors illustrate include poetic narrative and dramatic emplotting. The analytical approaches we illustrate for cross-incident analysis include thematic assertion, grounded theory, and post-structural analysis/assemblages. The use of the aforementioned approaches offers researchers contemporary tools that can deepen meaning and understanding of qualitative CIT data, which address challenges that have been acknowledged regarding the difficulty of analyzing CIT data.

The different contemporary qualitative approaches that we have introduced and illustrated in this study provide researchers using the CIT with additional tools to address the challenges of analyzing qualitative CIT data, specifically with regard to data reduction of lengthy narrative transcripts through re-storying as well as cross-incident analyses that can substantially deepen meaning, as well as build new theory and problematize the data through existing theory.

A strength of the CIT is its focus on actual events that have occurred from which reasoning, behaviors, and decision-making can be examined to develop more informed practices.

The CIT is a very popular and flexible method for collecting data that is widely used in many disciplines. However, data analysis can be especially difficult given the volume of narrative qualitative data that can result from data collection. This paper describes and illustrates different contemporary approaches analyzing qualitative CIT data, specifically the processes of re-storying and cross-incident analysis, to address these concerns in the literature as well as to enhance and further evolve the use of the CIT method.

This paper aims to study the effects of perceived organizational support (POS) on employees’ knowledge sharing intention (KSI). More specifically, this study examined whether these effects are moderated by job characteristics (JCs) and are mediated by organizational citizenship behavior (OCB).

Data for 426 employees were collected via an online questionnaire from four IT companies in South Korea. Combined effects in the variable set were analyzed using conditional process analyses (Hayes, 2013).

The results indicate that POS positively affects OCB and KSI, and that JCs moderate the relationship between POS and OCB. Also, the relationship between POS and KSI is mediated by OCB, and the hypothesized moderated mediation model is confirmed.

This study is novel in empirically establishing how employees’ KSI is affected by POS as an integrative construct bringing together JCs and OCB. This paper intends to fill a methodological gap and nurture future research by adopting conditional process analyses assessing whether JCs moderate the relationship between POS and OCB and mediate the effects of OCB on KSI.