Team Learning: A Theoretical Integration and Review

With the increasing emphasis on work teams as the primary architecture of organizational structure, scholars have begun to focus attention on team learning, the processes that support it, and the important outcomes that depend on it. Although the literature addressing learning in teams is broad, it is also messy and fraught with conceptual confusion. This chapter presents a theoretical integration and review. The goal is to organize theory and research on team learning, identify actionable frameworks and findings, and emphasize promising targets for future research. We emphasize three theoretical foci in our examination of team learning, treating it as multilevel (individual and team, not individual or team), dynamic (iterative and progressive; a process not an outcome), and emergent (outcomes of team learning can manifest in different ways over time). The integrative theoretical heuristic distinguishes team learning process theories, supporting emergent states, team knowledge representations, and respective influences on team performance and effectiveness. Promising directions for theory development and research are discussed

Modelling bargaining behaviors within biotech clusters - Towards the "power of the weak" emergence?

If spatial and industrial economics theorical models, such as industrial districts, clusters, or learning regions propose a large analysis of differentiated coordination mecanisms, it however not really takes into account behavior of dispute dynamics, such as conflict of bargaining and power, which can explain both diversity and ambivalence of local coordinations. So, our purpose in this contribution is to bring to light that bargaining and power conflicts are at stake in coordinations structuration within territories. We base this contribution on Artificial Life simulations involving public and private local actors who bargain to share a local resource using more or less sophisticated strategies. On a methodologic point of view, our thought is based on an empirical established fact. Analysis of a biotechnology cluster in Toulouse-France (Leroux I., 2002, 2004) indeed contributes to bring to light that coordinations involving pharmaceutical industry, local communities and local research laboratories are based on direct or indirect evolving domination and concession bargaining games. If industrial firms play "the power of the weak" game, making concession of their decision power to public research laboratories, they endeavour systematically to exerce an influence or a discrimination power, by using hided and indirect means that forward by local communities.Starting from this established fact, we propose Artificial Life simulations of local bargaining games, inspired from the T. Ellingsen (1997) bargaining evolutionnary game. This is a Nash demand game under ultimatum. It leads to the interaction of obstinate agents whose demands are independent of those of the adversaries, and sophisticated agents who adapt their demand to that hoped for of their adversaries rather than gain nothing. As a result, our simulations show that bargainings between these local actors lead to an agreement which is not a perfect share, or an "universal" rule, but a compromise frequently hiding complex mecanisms of domination and concession. The main contribution of these simulations, which are based on genetic algorithms, is to put in a prominent position the variations of behavioral rules. We show how bargaining is an evolving processus based on domination and concession behaviors (influence, coercion,…) bringing to light the T. Schelling (1960) "power of the weak". This result brings to the fore the question of flexibility and phasing dynamics of power behaviors in local coordination bargainings. This model can contributes to open new researches focused on power and conflict strategies within local coordinations.

Investigating the impact of networking capability on firm innovation performance:using the resource-action-performance framework

The author's final peer reviewed version can be found by following the URI link. The Publisher's final version can be found by following the DOI link.Purpose The experience of successful firms has proven that one of the most important ways to promote co-learning and create successful networked innovations is the proper application of inter-organizational knowledge mechanisms. This study aims to use a resource-action-performance framework to open the black box on the relationship between networking capability and innovation performance. The research population embraces companies in the Iranian automotive industry. Design/methodology/approach Due to the latent nature of the variables studied, the required data are collected through a web-based cross-sectional survey. First, the content validity of the measurement tool is evaluated by experts. Then, a pre-test is conducted to assess the reliability of the measurement tool. All data are gathered by the Iranian Vehicle Manufacturers Association (IVMA) and Iranian Auto Parts Manufacturers Association (IAPMA) samples. The power analysis method and G*Power software are used to determine the sample size. Moreover, SmartPLS 3 and IBM SPSS 25 software are used for data analysis of the conceptual model and relating hypotheses. Findings The results of this study indicated that the relationships between networking capability, inter-organizational knowledge mechanisms and inter-organizational learning result in a self-reinforcing loop, with a marked impact on firm innovation performance. Originality/value Since there is little understanding of the interdependencies of networking capability, inter-organizational knowledge mechanisms, co-learning and their effect on firm innovation performance, most previous research studies have focused on only one or two of the above-mentioned variables. Thus, their cumulative effect has not examined yet. Looking at inter-organizational relationships from a network perspective and knowledge-based view (KBV), and to consider the simultaneous effect of knowledge mechanisms and learning as intermediary actions alongside, to consider the performance effect of the capability-building process, are the main advantages of this research