Limitations in Exploration and Exploitation Processes during the Emergence of Strategic Decision-Making

Decision problems and their relationship with the moments in time is a theme to be explored in the strategy studies field. In fact, several scholars conceptualize strategy from a decision-making perspective, framing it as a sequence of interconnected decisions that involve the allocation of resources necessary for implementation. One way to understand the timing of strategic decisions is through the lens of deliberate versus emergent strategies. Within this framework, organizational ambidexterity—defined as the dynamic balance between exploration and exploitation processes—has been proposed as a key cognitive dimension influencing managerial decision-making. These processes, grounded in organizational learning theory, are subject to constraints such as temporal myopia, which can hinder the ability to appropriately weigh short-term outcomes against long-term implications. In this context, the present study aims to identify the limitations inherent in exploration and exploitation processes that may influence strategy formulation, as discussed in the existing literature. This objective was pursued through a systematic literature review using the Scopus database. The review focused on scholarly contributions addressing decision-making in relation to exploration and exploitation, and the results were categorized into substantial, applied, and complementary contributions. As a result, this study reveals a set of thematic categories —including resources, term, type of activity, background, structure, knowledge, and strategy— that differentiate exploration from exploitation processes. These categories also help illuminate the limitations of each process and their potential influence on the timing and nature of strategic decisions

Business · Engineering ethics · Management science · Political science · Process management · Competitive and Knowledge Intelligence · Engineering · Innovation and Knowledge Management · Technology Assessment and Management

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• A tale of two databases

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• La simulación basada en agentes

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