Haien Ding is a Ph.D. candidate at the Department of Leadership and Organizational Behaviour, BI Norwegian Business School. In his Ph.D. research project, he is committed to exploring the antecedents, outcomes, and boundary conditions of illegitimate tasks to promote the thriving and flourishing of employees. His research interests include work stress, motivation, well-being, innovation, advanced regression analysis techniques, configurational comparative methods (e.g., qualitative comparative analysis), necessary condition analysis, and open science.
Publications
Ding, Haien (2023)
Qualitative Comparative Analysis: Search Target, Reflection on the Top-Down Approach, and Introduction of the Bottom-Up Approach
Based on the INUS theory of causality, the search target of qualitative comparative analysis (QCA) is to find all the minimally sufficient conditions for the outcome’s occurrence in a data set, where the condition’s sufficiency, the necessity of the condition’s components, and the completeness of the solution are three core requirements. However, QCA’s current top-down approach, which relies on a truth table and Boolean minimization, cannot meet the main objective of QCA. Conditions generated by the top-down approach can be insufficient for the outcome or contain unnecessary components that can be removed. We found evidence supporting our arguments by examining the correctness of top-down QCA in Study 1. Then, we show that QCA can also proceed with a “bottom-up” search strategy in sufficiency analysis, similar to coincidence analysis (CNA). We contrast solutions of the top-down and bottom-up QCA approaches by analyzing a simulated crisp-set data set in Study 2 and a real-world fuzzy-set data set in Study 3. Both results show that only the bottom-up approach can produce all the minimally sufficient conditions. We contribute to the ongoing debate pertain QCA solution types and QCA algorithms by critically evaluating the limitations of QCA’s top-down approach and introducing a bottom-up approach for QCA.
Ding, Haien & Kuvaas, Bård (2023)
Using necessary condition analysis in managerial psychology research: introduction, empirical demonstration and methodological discussion
Purpose In this paper, the authors aim to present a novel methodological tool – necessary condition analysis (NCA) to aid managerial psychology researchers in properly testing necessity statements. Design/methodology/approach The authors employ NCA to analyze whether three basic psychological needs for autonomy, competence and relatedness are necessary for work engagement. Findings The authors illustrate the value and application of NCA by revealing that basic psychological needs for autonomy, competence and relatedness are necessary for work engagement, as proposed by self-determination theory (SDT). Originality/value The authors illustrate the importance of the sufficiency-necessity distinction and the relevance of a necessity logic in managerial psychology. They also discuss NCA's methodological implications for managerial psychology research, theory and practice.
Ding, Haien & Kuvaas, Bård (2022)
Illegitimate tasks: A systematic literature review and agenda for future research
Although expecting to undertake core tasks affirming their professional identity, employees often have to deal with tasks they perceive as unnecessary or unreasonable. The concept of illegitimate tasks captures this phenomenon and has attracted growing attention since its first appearance. Illegitimate tasks have been found to explain unique variance in well-being and strain. Given a burgeoning body of literature, a systematic narrative review of illegitimate tasks is warranted. This review summarises research regarding illegitimate tasks’ antecedents (leadership, workplace characteristics, individual characteristics, and job characteristics) and outcomes (emotions, work attitudes and cognition, work behaviour, health and well-being, and interpersonal relationships). In addition, we review work done to date regarding the moderators and mediators of these relationships. Finally, we offer future directions for research.
Ding, Haien (2022)
What kinds of countries have better innovation performance?–A country-level fsQCA and NCA study
Innovation is critical to boosting economic growth and combating social problems. Based on national innovation systems, this study investigates how combinations of multiple factors (i.e., R&D investment, human capital, social freedom, democracy, globalization, and country affluence) lead to high national innovation performance. This study adopts fuzzy-set qualitative comparative analysis (fsQCA) to explore multiple conjunctural causations of innovation performance using a multi-source dataset of 116 countries. It identifies two configurations for high innovation performance: leveraging human capital and leveraging R&D investment. It also adopts a necessary condition analysis (NCA) to examine the necessary relationships between every condition and the outcome. NCA finds that R&D investment, globalization, and country affluence are necessary conditions for innovation performance, although they have different degrees of importance. This study advances the knowledge on national innovation performance and demonstrates how NCA can add complementary insights to the findings of fsQCA.