How organizational structure transforms risky innovations into performance – A computer simulation

Abstract

This paper investigates the mutual interdependencies between organizational architectures, decision making and performance. Through applying agency-based Monte-Carlo simulations, we reveal how three types of organizational structure (hierarchical, polyarchical and hybrid) aggregate innovations on the micro level into corporate performance. By considering three different initial project portfolios (incremental innovations, innovations with spillover effects and innovations that have to overcome a critical mass), we analyze which organizational architectures may be superior regarding selecting good projects, avoiding collective myopia and overcoming organizational inertia. Results suggest that in a risky environment, firms with rigid hierarchies can achieve a much higher performance than horizontally organized firms even when the quality of the decision-making by managers is poor. Results also highlight the dangers involved in erecting a more hybrid-type organization because such an organization might become over-challenged and unable to handle risky innovations adequately. Finally, we discuss how firms could be structured to increase performance and to minimize risks.

Evaluating the effect of organizational architecture in developing science and technology parks under differing innovation environments

“…This underlines that in start-up conditions (as well as under conditions of negative innovation environment) the hierarchical star architecture is always most efficient (Al-kfairy et al, 2019a). This indicates, as previously reported (Will et al 2019) that there is little difference between qualified and non-qualified managers in environments with many bad innovations. It also implies there could be scalability issues in the "star" model when expanding the STP, if there is not a concomitant increase in the decision-making quality in the CI.…”

“…The results presented show that concepts of "business ambidexterity" (see Benner and Tushman, 2003;Benner and Tushman, 2015;and O'Reilly III and Tushman, 2013), can be extended to clusters of firms, in this case STPs. However, there are unexpected differences between STPs and single organizations: Will et al (2019) showed that for spreading innovations inside a single organization, multiple layers of F managers making decisions at close to coin-flipping (50:50) efficiency were still beneficial because at each decision round, moving up the hierarchy, 50% of expensive "bad" innovations were removed. In contrast, in the STP case, increasing the number of hierarchies showed a negative impact even when decision-making was good at both CI and F levels, and this is due to increased transaction costs negating the advantage gained.…”

“…Different decision-making methods were simulated based on the organizational architectures using a Cellular Automata approach (Davis et al, 2007), similar to studies published previously (Alkfairy et al, 2019a;Will et al, 2019;Mellor, 2014a). Simulations were performed when organisational architecture is based on one of the following:…”

“…Furthermore, because the central Cluster Initiative (CI) performs the selection, makes all decisions and implements them, the quality of CI management team is positively related to STP performance (Albahari, 2015;Albahari et al 2016). Will et al (2019) emphasise that innovations are not all positive and that especially in environments seeking innovations, that costly negative "bad" innovations abound (Mellor, 2019). At its most simple, then where the benefit of a "good" innovation is I and the costs to achieve it are C, then the net gain is I-C. Where an innovation is unsuitable for whatever reason, then the net loss is larger, namely; -(I+C) (Mellor, 2019) implying that STPs need a constant positive-sum game just to survive.…”

Computer modelling reveals the optimal development for the organisational structure of business clusters

“…Nobel Laureate Joseph Stiglitz (see e.g. Sah and Stiglitz, 1986, and more recently Will et al, 2019) have shown that ambidextrous organizational structure determines organizational performance.…”