Institutional means-ends decoupling work in industrial R&D project implementation

Abstract

Managing goals is a key network management function and is critical in the implementation of industrial R&D projects. In this paper, we explore the implementation of an industrial R&D project, focusing in particular upon the role of means-ends decoupling work to understand how the goals are managed. We combine several data sources in our case research to explore project implementation through an understanding of means-ends decoupling work. We collected indepth interviews, archival records and field observations within the R&D research setting of an industrial R&D project in the period of 2015 to 2017. Our findings identify three types of means-ends decoupling work in R&D project implementation: 'work on' causal complexity, 'work at' behavioural invisibility, and 'work with' practice multiplicity. In addition, we uncover six dynamic micro-mechanisms that collectively influence the making and nature of meansends decoupling work and therefore serve to allow for the fluid switching of work as the institutional conditions permit. Overall, our findings have significant implications for understanding means-ends decoupling as a highly skilled network competence for managing R&D project implementation goals.

How do projects decouple from coercive pressures? A study of decoupling in construction projects

“…Di Maddaloni and Sabini (2022) introduced the concept of means-end decoupling as a powerful perspective to understand the discrepancy between what project managers perceive to be moral (including communities), versus what project organisations actually do (not including them). Jabbouri et al (2019) identified three types of means-ends decoupling work in R&D project implementation: "work on" causal complexity, "work at" behavioural invisibility, and "work with" practice multiplicity. Despite some recent studies started to emerge looking at, especially, means-end decoupling, there is still a lack of studies looking at project responses in the context of coercive pressures.…”

An artificial intelligence (AI)-readiness and adoption framework for AgriTech firms

“…Many contemporary organizations adopt external practices as a response for institutional pressures (Bromley and Powell, 2012). Such firms would implement cutting edge technological practices, which have an ambiguous links to the firms' core goals (Jabbouri et al, 2019;Wijen, 2014).…”

“…This preliminary process aims at diagnosing the firms' most prevailing business problems, that can be potentially addressed through AI implementation. Organizations should not fall in the trap of adopting AI as a "symbolic action" (Bromley and Powell, 2012), to cope with increasing pressures for being "technology-driven" (Jabbouri et al, 2019).…”

“…The high rate of failure of technology adoption and implementation (Jabbouri et al, 2019) compels AgriTech firms to devote more effort into preparing the ground and maximizing their readiness for future adoptions. In this regard, the AI readiness process comprises a set of strategic actions to be performed prior to the AI adoption.…”

“…One path, could be to target international firms, managers, entrepreneurs, experts, and scholars from the field of AI and AgriTech, and aim at assessing the collective perceptions and discourse of such audiences on the topic of AI adoption within AgriTech firms. Within this vein, the process of AI adoption is often seen as the primary phase of a rigorous strategic process of implementation and achievement (Bromley & Powell, 2012;Jabbouri et al, 2019;Wijen, 2014). As such, the post-adoption phase of AI could be explored to unravel some of the implementation challenges and goal achievement barriers.…”