Materializing Innovation Capability: A Management Control Perspective

Abstract

Recent research in strategic management claims that firms need appropriate structures for capabilities to materialize into performance. Following this argument, we posit that the design of management control systems influences a firm's ability to exploit innovation capability and translate it into innovation performance. While we argue for value communication and employee selection as suitable control practices in this context, we expect performance monitoring and behavior monitoring to obstruct the materialization of innovation capability in organizations. Moreover, we elucidate the role of perceived environmental uncertainty as a relevant contextual factor that influences the costs and benefits of management control practices and the extent to which they can support or hinder the innovation process. We empirically test our hypotheses by combining survey data with patent information of the firms in our sample. In sum, our study contributes to the innovation literature within and beyond the field of accounting by highlighting the crucial role of management control in translating a firm's innovation capability into actual innovation performance.

Tone from the top in risk management: A complementarity perspective on how control systems influence risk awareness

“…The need for information collection and processing, guidance and flexibility is more pressing in a situation of high PEU as compared to a stable environment. In a setting of high PEU, employees will perceive more lack of direction (Grabner, Posch, & Wabnegg, 2018), perceive a greater risk of organizational failure, experience a lack of confidence and fear that their decisions could cause trouble (Agle, Nagarajan, Sonnenfeld, & Srinivasan, 2006;Bstieler, 2005). Thus employees will seek more guidance regarding risk.…”

In the field of tension between creativity and efficiency: a systematic literature review of management control systems for innovation activities

“…While diagnostic and boundary controls negatively impact the level of innovation, the exact opposite applies to beliefs and interactive controls (Haustein et al , 2014). Particularly, these control mechanisms should be designed to communicate value rather than to strictly monitor progress towards pre-defined targets (Grabner et al , 2018). Further, learning mechanisms such as knowledge codification are the key to the creation of such capabilities (Zollo and Winter, 2002).…”

Influência do sistema de mensuração de desempenho na agilidade organizacional e na inovação aberta

“…Estes resultados coadunam com o consenso existente na literatura, no qual o uso isolado do controle diagnóstico limita a inovação de produtos (Lill et al, 2021), porque cria impulsos que não necessariamente conseguem gerar tensões favoráveis à inovação (Curtis & Sweeney, 2017). O controle diagnóstico é projetado para monitorar o progresso em direção às metas predefinidas, logo seu mecanismo de funcionamento demanda pouca capacidade de busca e de recuperação de conhecimento relevantes para que a agilidade organizacional ocorra (Grabner et al, 2018), razão pela qual a mediação não foi confirmada.…”