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The author introduces a strategic responsiveness model that reflects an organization’s ability to sense environmental changes and learn from emergent adaptive responses that attempt to realign organizational activities and gain a better fit with the changing conditions. The author shows in computational simulations how superior strategic adaptation is associated with higher average returns and lower performance risk among firms that compete in the same industry contexts and generate negatively skewed outcome distributions consistent with empirical observations. The model is refined to incorporate an interactive strategy-making process, where experiential insights from decentralized initiatives update forward-looking projections in central planning. The ensuing analysis demonstrates how this adaptive strategy-making approach further enhances the favorable risk-return outcomes. The author discusses these findings and the implications for the study of dynamic adaptive strategy-making processes.

Contemporary organizations with multinational business activities must strive to achieve strategic responsiveness to thrive and survive as they operate across a highly dynamic and complex global business environment. Here we emphasize the importance of combining the slow analytical strategy processes at headquarters with the fast autonomous responses taken by frontline agents in the subsidiaries in view of the changing conditions. New business developments are observed first in the fast activities around the multinational periphery where updated experiences from ongoing responses create useful insights that can be used strategically if management at headquarters is cognizant about its existence and able to collect this information. We introduce the notion of democratizing the strategic engagement of managers and employees at all levels and locations of the multinational corporation (MNC) as an essential leadership paradigm. The implied interaction between slow central analytical reasoning at headquarters and updated insights from fast decentralized initiatives in local subsidiaries constitutes an effective dynamic responsive mechanism. This dynamic interaction implies that critical strategic decisions made in the MNC must be informed by the diverse updated insights of managers and employees operating on the corporate frontlines tapping into the crowd wisdom readily available in and around the organization.

This chapter estimates a dynamic reduced-form model of intra-firm promotions using an employer–employee panel of over 300 of the largest corporations in the United States in the period from 1981 to 1988. The estimation conditions on unobserved individual heterogeneity and allows for both an endogenous initial condition and sample attrition linked to individual heterogeneity in demonstrating the relative importance of variables that influence promotion. The role of the executive’s functional area in promotion is considered along with the existence and source of promotion fast tracks. We find that while the principal determinant of promotions is unobserved individual heterogeneity, functional area has a high explanatory power, resulting in promotion probabilities that differ by functional area for executives at the same reporting level and firm. No evidence is found that an executive’s recent speed of advancement in pay grade has a positive causal impact on in-sample promotions after conditioning on the executive’s career speed of advancement, except for the lowest level executives the data. Fast tracks appear to largely result from heterogeneity in persistent individual characteristics, not from an inherent benefit in recent advancement itself.

In view of a disruptive environment, the authors consider theories that explain left-skewed performance outcomes and inverse risk–return relationships where some rationales imply causal dependencies with slightly differing outcomes while others refer to spurious artifacts. These literatures are briefly outlined and dynamic response capabilities introduced as an alternative perspective expressed as strategic responsiveness where commonly observed performance outcomes derive from heterogeneous response capabilities among firms that compete in dynamic environments. Financial performance outcomes are analyzed empirically based on a comprehensive corporate dataset where computational simulations of adaptive strategy making among firms generate comparable outcomes from a simple strategic responsiveness model. The findings demonstrate how diverse adaptive strategy-making processes can generate a substantial part, if not all, of the commonly observed artifacts of firm financial performance. The implications of these results are discussed pointing to propitious approaches of analyzing the impact of dynamic adaptive strategies.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

How can leaders adopt a mindset that maximizes learning, remains responsive to short-term emergent opportunities, and simultaneously strengthens longer-term dynamic capabilities of the organization? This chapter explores the organizational decisions and practices leaders can initiate to extend, strengthen, or transform “ordinary capabilities” (Winter, 2003) into enhanced improvisational competence and dynamic capabilities. We call this leadership logic the “jazz mindset.” We draw upon seven characteristics of jazz bands as outlined by Barrett (1998) to show that strategic leaders of business organizations can enhance dynamic capabilities by strengthening practices observed in improvising jazz bands.

This chapter discusses the formulation of an agent-based model to simulate day-to-day dynamics in activity-travel patterns, based on short and long-term adaptations to exogenous and exogenous changes.

The model is based on theoretical considerations of bounded rationality. Agents are able to explore the area, adapt their aspirations and develop habitual behaviour. If they experience dissatisfaction, stress emerges and this may lead to short or long-term adaptations of an agent’s activity-travel patterns. Both cognitive and affective responses are taken into account, when agents evaluate available options. Moreover, memory-activation and forgetting processes play a significant role in the development of habitual behaviour.

Results of numerical simulations show the effect of memory-activation and emotion-related parameters on habit formation, on the decision-making process and on overall model behaviour. Effects of specific aspects of bounded rationality on the evolution of dynamics in the activity-travel patterns of an individual are illustrated. Effects seem realistic, behaviourally rich and, therefore, more sensitive to a larger spectrum of policies.

The model is unique in its kind. It is one of the first attempts to formulate a dynamic model of activity-travel behaviour, based on principle of bounded rationality, which includes both cognitive and affective mechanism of adaptation.

This article provides an overview of the panel vector autoregressive models (VAR) used in macroeconomics and finance to study the dynamic relationships between heterogeneous assets, households, firms, sectors, and countries. We discuss what their distinctive features are, what they are used for, and how they can be derived from economic theory. We also describe how they are estimated and how shock identification is performed. We compare panel VAR models to other approaches used in the literature to estimate dynamic models involving heterogeneous units. Finally, we show how structural time variation can be dealt with.