In this paper we examine the adaptability of the Japanese style lean organization system and the traditional American style mass organization system under changing environments. From an organizational design perspective, key structural aspects of the two organizations are modeled in a problem solving context using computational methods. Organizational-level performance in terms of decision making accuracy and severity of errors is measured as an indicator of organizational adaptability under conditions where the task environment shifts between predictable to unpredictable or vise versa. Our study shows that both organizations have their respective advantages under different task environments and that they adapt to environmental shifts in different forms. Specifically, when the time pressure is high the lean organization system’s performance is virtually identical to the mass organization system, even though the lean organization system’s members are more proactive. When the time pressure is low, the mass organization system shows a much faster adaptability when the environment shifts to a predictable one but it is also more vulnerable when the environment shifts to an unpredictable one. In contrast, the lean organization system’s response to the changing environment is characterized by its slower adaptability. When the environment shifts to an unpredictable one, the lean organization system shows a gradual improvement till reaching a high level. When the environment shifts to a predictable one, however, the lean organization system shows a gradual

Organizations sometimes face critical situations or crises that can induce severe consequences or even disasters if wrong decisions are made. The bulk of crisis management research has relied heavily on case study methods yet often with rhetorical or even inconsistent suggestions. With an exclusive focus on crisis prevention, the issue of how organizations can maintain good performance when faced with critical situations has largely remained unexplored. There is also an apparent lack of consideration regarding how aspects of organizational design and task environment interact and affect organizational performance under critical situations. In this paper, we attempt to address this issue from an open system’s perspective and integrate techniques of computational modeling with the analyses of two crisis cases, the Vincennes incident and the Hinsdale incident. The use of a computational model with strong organization theory foundation has provided a systematic mechanism for abstracting empirical information and generating theoretical results, thus complementing conventional case analyses, which thrive on in-depth information but are often limited by the lack of analytical ability to provide theoretical insight that goes beyond empirical descriptions. For the two crisis cases, the study shows, through detailed quantitative illustrations, that the computer model can be very effective in predicting organizational performance and suggesting designs that organizations can employ to mitigate the impact of crises. This study has demonstrated that our approach of computational case analysis can be very successful in providing systematic and explicit guidance for effective crisis mitigation both theoretically and empirically.

This paper starts with a survey of different notions of learning, and finds that the “logic ” of discovery has been neglected. The paradox of “exploitation ” and “ exploration”, derived from the organization literature, is proposed as the core issue. We need to recognize the importance of organization and co-ordination, in learning and innovation. This implies, among other things, that transaction cost theory must be incorporated in our theory of learning and innovation. The paper proposes a constructivist, interactionist view of knowledge. This has implications for our concept of the firm and inter-firm relations. It discusses a cycle of discovery which extends the life-cycle theory of innovation, and it considers the implications for organizational (dis)integration. 1 Types of learning First, let us review the perspectives on learning presented in the economics literature. Productivity studies have identified the 80 % rule: a doubling of turnover yields a reduction of average cost to 80 % of its original level. This has sometimes been ascribed to the “learning curve ” (Yelle 1979). However, this rule can be explained fully by an “engineering ” effect of scale that has nothing

This study explores the organizational impact of a variety of important promotion systems commonly practiced in organizations including up-or-out systems, absolute merit-based systems, relative merit-based systems, and seniority-based systems. Through the computer simulation of organizations in a distributed decision making setting, the results indicate that the effectiveness of any promotion system is dependent on a range of factors including the nature of the task environment, the design of the organizational structure, the frequency of monitoring, the criteria of performance, and the transferability of task knowledge. This study has implications not only for understanding organizational promotion systems from the contingency perspective, but also for bridging the fields of strategic human resource management and computational organization theory.

Abstract: A plan of action is given for a newly funded research project on organizational evolution. In this study, our goals are to apply an evolutionary framework to organizational learning. The process includes a collaborative effort with partner companies to identify the working mechanisms behind the evolution of policies or decision rules. We also use computer simulations as a tool to examine our findings. Introduction: This document describes a plan of action for a three-phase research project

This paper presents a preliminary investigation of the relationship between the process of functional division of labour and the modes in which activities and plans are coordinated. We consider a very simple production process: a given heap of bank-notes has to be counted by a group of accountants. Because of limited individual capabilities and/or the possibilities of mistakes and external disturbances, the task has to be divided among several accountants and a hierarchical coordination problem arises. We can imagine several different ways of socially implementing coordination of devided tasks. 1) a central planner can compute the optimal architecture of the system; 2) a central planner can promote quantity adjustments by moving accountants from hierarchical levels where there exist idle resources to levels where resources are insufficient; 3) quasi-market mechanisms can use quantity or price signals for promoting decentralized adjustments. By means of a simple simulation model, based ...

We experimentally study decentralized organizational learning. Our objective is to understand how learning members of an organization cope with the confounding effects of the simultaneous learning of others. We test the predictions of a stylized, rational agent model of organizational learning that provides sharp predictions as to how learning members of an organization might cope with the simultaneous learning of others as a function of fundamental variables, e.g., firm size and the discount factor. While the problem of learning while others are learning is quite difficult, we find support for the comparative static predictions of the model’s unique symmetric equilibrium.

As an exploratory step toward integrating differing views in the field of top management succession, this study takes an open system’s perspective and examines the effect of top management succession on organizational performance, in particular decision-making accuracy, under conditions where various organizational and environmental factors can interact. Through a formal computer simulation model that captures the basic behaviors of human decision making and the fundamental characteristics of organizational and environmental settings, the results show that whether top management successions may affect organizational performance, and if so, how organizational performance may be affected, depends on such contextual variables as industry environment, organizational structure, succession type, and organizational age. This study has also demonstrated the importance of moving toward a more systematic and precise contingency approach and the power of computer modeling in understanding the multilevel process of top management succession in complex and dynamic organizations.

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Despite much research, debate continues about the impact of risk taking on a firm’s future performance. Unlike prior studies, we propose that risk-return relationships evolve as firms age and learn, particularly in high-velocity settings where accumulated knowledge affects how firms respond to technological change. Discerning this requires three things absent from prior analyses: (1) studying an entire population; (2) modeling evolutionary processes; and (3) using separate models to capture how a firm’s gains and losses (i.e., its strong and weak performances) unfold across time. Using this framework, we found that (a) risk-return relationships generally evolved from positive to negative as firms aged; because (b) firms learned to avoid large losses at younger ages than they learned to sustain large gains; yet (c) the risk taking that followed below-aspiration performance moderated those effects such that major setbacks prompted large future gains and large future losses among older firms and downward spirals among younger ones. 1 Relationships between risk and return are central to our lives. In the hope of emotional or monetary rewards, some people take risks by climbing mountains, changing employers, or switching careers. Some executives take risks in pursuit of better pay and enhanced reputations, and some firms pursue risky strategies in a quest for higher sales and profits.