Purpose – The purpose of this paper is to investigate how performance measurement systems (PMSs) might be designed in order to empower managers of state-owned enterprises (SOEs) towards an active work role. Design/methodology/approach – The study is based on a conceptual approach that combines insights from prior research on performance measurement with that on dimensions of psychological empowerment. An exploratory case study is used to further develop propositions for the design of an empowering PMS. Data from in-depth interviews with six managers of diverse SOEs located within a German city enables the tracing of underlying causal mechanisms. Findings – PMSs that are designed according to the principles of goal clarity, balanced goal difficulty, autonomy-enhancing measurement, and a broad goal scope can positively influence the four dimensions of empowerment: meaning, competence, self-determination, and impact. Practical implications – The study’s propositions can be used to enhance the governance of SOEs through a particular design of PMSs. This research thus responds to the call for a new generation of governance mechanisms within the complex setting of SOEs. Originality/value – Current research on PMSs is extended through the construct of psychological empowerment. Thus, an existing governance mechanism is further developed towards being more effective for use in the context of SOEs.

PurposeThis study examines the interplay of formal types of control (input, behavior and outcome) exercised on municipally owned corporations (MOCs). It further investigates whether particular informal contingencies (trust and interdependence) predict affiliation to the derived municipal control configurations.Design/methodology/approachThe paper applies an exploratory cluster analysis based on survey data from 243 top-level managers of German MOCs. It then investigates the clustered municipal control configurations using binomial logistic regression.FindingsThe exploratory analysis reveals four municipal control configurations: (1) input-dominated control, (2) outcome-dominated control, (3) mixed input/outcome control and (4) “neglect of formal control”. As expected, both of the informal contingencies demonstrate strong predictive power. More precisely, trust increases the likelihood of belonging to the dominant outcome control cluster and interdependence increases the likelihood of belonging to the mixed input/outcome control cluster. Surprisingly, the neglect of formal control cluster is characterized by low trust and low interdependence.Originality/valueThe study sheds light on the widely assumed but understudied interplay of different formal controls in hybrid governance settings. Furthermore, the analysis stresses the importance of trust and interdependence when explaining hybrid control configurations.

This study assesses the extent to which the two main Configurational Comparative Methods (CCMs), i.e. Qualitative Comparative Analysis (QCA) and Coincidence Analysis (CNA), produce different models. It further explains how this non-identity is due to the different algorithms upon which both methods are based, namely QCA’s Quine–McCluskey algorithm and the CNA algorithm. I offer an overview of the fundamental differences between QCA and CNA and demonstrate both underlying algorithms on three data sets of ascending proximity to real-world data. Subsequent simulation studies in scenarios of varying sample sizes and degrees of noise in the data show high overall ratios of non-identity between the QCA parsimonious solution and the CNA atomic solution for varying analytical choices, i.e. different consistency and coverage threshold values and ways to derive QCA’s parsimonious solution. Clarity on the contrasts between the two methods is supposed to enable scholars to make more informed decisions on their methodological approaches, enhance their understanding of what is happening behind the results generated by the software packages, and better navigate the interpretation of results. Clarity on the non-identity between the underlying algorithms and their consequences for the results is supposed to provide a basis for a methodological discussion about which method and which variants thereof are more successful in deriving which search target.

This research seeks to improve our understanding of how intrinsic motivation is instantiated. Three motivation theories, flow theory, self-determination theory, and empowerment theory, have informed our understanding of the foundations of intrinsic motivation at work. Taken jointly, they suggest six causal factors for intrinsic motivation: (1) perceived competence, (2) perceived challenge, (3) perceived autonomy, (4) perceived impact, (5) perceived social relatedness, and (6) perceived meaningfulness. Integrating different theoretical perspectives, I employ a case-based configurational approach and conduct coincidence analyses on survey data from a German public utility to analyse the nuanced interplay of these six causal factors for intrinsic motivation. My data show that high perceived meaningfulness or high perceived autonomy is sufficient for high perceived intrinsic motivation and at least one of the two conditions must be present. Further, my findings reveal a common cause structure in which perceived impact is not a causal factor for intrinsic motivation but an additional outcome factor. Subsequent analyses shed light on possible roles of the remaining proposed causal factors by drawing a tentative causal chain structure. The results of this study enhance our understanding of the causal complexity underlying the formation of intrinsic motivation.