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While recent research has referred to a cognitive view on “business modelling,” it remains unclear in specifying the cognitive foundations of how such modelling happens. This paper proposes building on heuristics as models of individual cognition, which have proved effective foundations of adaptive individual and managerial behaviors. By also drawing on gestalt theory to specify principles of modelling as rule-based form giving, we propose business modelling as a managerial cognitive process of configuring heuristics. The paper makes three contributions. First, we introduce heuristics to the business modelling literature and so provide an established theory of adaptive individual behavior that strengthens the cognitive foundations of business modelling. Second, we conceptualize and theorize on the cognitive activity of business modelling as an iterative process of configuring heuristics by applying gestalt principles. Although the literature on business models has referred to the theories of configurations and gestalt, it has been left to this work to make the theoretical linkages between heuristics, gestalt theory and business modelling explicit. Third, our work contributes to the micro-foundations of the cognitive processes underlying business modelling and thus to broader accounts of adaptive managerial behaviors.

In this study, the authors examine acquirers’ selection of legal advisors for mergers and acquisitions (M&A) transactions. The authors first confirm the importance of their own prior experience and imitation within this context. Then, the authors propose and find that firms with less experience in performing M&A deals place more emphasis on imitating others while firms with more experience with a particular legal advisor focus less on others’ experience with this advisor. The authors further find that when they imitate, firms selectively, rather than broadly, imitate others by focusing on their industry or state peers. The authors present corroborating evidence for these hypotheses through analyzing a matched sample of acquirer – legal advisor pairs developed from an initial dataset of 29,398 domestic and cross-border acquisitions performed by US firms between 2000 and 2010.

Following Philip Selznick’s lead in using pragmatist social science to understand issues of public concern we conducted a study of failed innovation in the commercial construction industry (CCI). We find that social heuristics – collectively constructed and maintained interpretive decision-making frames – significantly shape economic and non-economic decision-making practices. Social heuristics are the outcome of industry-based “institutionalization processes” and are widely held and commonly relied on in CCI to reduce uncertainty endemic to decision-making; they provide actors with both a priori and ex post facto justifications for economic decisions that appear socially rational to industry co-participants. In the CCI – a project-centered production network – social heuristics as shared institutions sustain network-based social order but in so doing discourage novel technologies and impede innovation. Social heuristics are actor-level constructs that reflect macro-level institutional arrangements and networked production relations. The concept of social heuristics offers the promise of developing a genuinely social theory of individual economic choice and action that is historically informed, contextually situated, and neither psychologically nor structurally reductionist.

Business model research has long focused on external triggers, drivers, and enablers of business model adoption. What is less well known is how business models are adopted in practice. Using a conceptual framework developed by Baden-Fuller and Mangematin, we propose 16 ideal types of business models. Based on a qualitative comparative analysis of 77 businesses, we explore the antecedents of these business model types, paying particular attention to multi-sided models, which are growing in prominence, and require businesses to manage complexity and interdependencies. Surprisingly, our analyses reveal that tools developed to support business design, creativity, or visualization were systematically absent from the operationalization of complex, multi-sided business models. The paper contributes to our understanding in three ways: (1) it reveals how businesses with complex, multi-sided models are crafted using heuristics rather than rational business model design tools, (2) it highlights consistent relationships between the practices employed during business creation/reconfiguration and the business models that are adopted, and (3) it opens fruitful research avenues to develop tools to support heuristics in business design and implementation.

Strategic option generation is a fundamental step in strategy formulation. Several lenses have been proposed to explain its foundations, including the microeconomics positioning school, and the resource and capabilities based view of the firm. These approaches are largely based on inductive and deductive logics, which are not the logics that provide strategic options that are potentially novel, profitable, and largely differentiated from competitive offerings. In this chapter, we propose a unifying framework of the cognitive foundations of strategic option generation. Building on five fundamental cognitive acts – imitation, framing, analogical reasoning, abductive reasoning, and mental simulation, this proposed model both synthesizes the extant literature and provides guidance about promising avenues for future theoretical and empirical research.

Purpose – This chapter illustrates how agent-based modeling (ABM) simulations may be incorporated into future emerging market research so as to build and strengthen existing and new theory. The area of strategy and organizations has used cellular automata, NK landscapes, and network simulations, but international business has rarely entertained their use. This is a loss for the area because emerging markets are rapidly growing and changing while research lags behind. Emerging markets are extremely complex environments best studied using simulations as complementary to existing research tools.

Design/methodology/approach – This chapter divides emerging market studies into three main areas including (1) foreign direct investment, (2) governance structures, and (3) international trade exporting. Through a discussion of the existing research in each of these areas, research opportunities applying ABM are identified. Illustrations allow explanation of the three agent-based simulation methods, as mentioned, based on previous ABM research in strategy and demonstrate how ABM may be applied to future emerging market studies.

Findings – A main insight is that ABM could lead to the rapid catch-up and improvement of emerging market research, especially when data for empirical work is limited, nonexistent, or prohibitively expensive to gather. ABM does not replace empirical work, but past research can be clarified and early theory developed so that if data becomes available, empirical work can be sharp and quickly realized having strong theoretical guidance.

Originality/value – This work, aimed at emerging market researchers, uniquely highlights why and how simulation tools are required and may be used in emerging market research.

Organizational networks are generally considered major antecedents of mutual influence in adopting similar practices, typically via a structure of dense ties, or closure. We propose that under conditions of competitive interdependence, closure may be associated with links established to access resources and knowledge and become a possible source of differentiation rather than imitation. We test these and other antecedents of imitative behavior and performance in the Italian TV industry with 12 years of data on 501 productions. We find that network closure is associated with lower imitation, centrality, but not status, leads to imitation, and that imitation lowers performance.

Based on a synthesis of findings from psychology, neuroscience, and machine learning, we propose a unified theory of curiosity as a form of motivated cognition. Curiosity, we propose, is comprised of a family of mechanisms that range in complexity from simple heuristics based on novelty, salience, or surprise, to drives based on reward and uncertainty reduction and finally, to self-directed metacognitive processes. These mechanisms, we propose, have evolved to allow agents to discover useful regularities in the world – steering them toward niches of maximal learning progress and away from both random and highly familiar tasks. We emphasize that curiosity arises organically in conjunction with cognition and motivation, being generated by cognitive processes and in turn, motivating them. We hope that this view will spur the systematic study of curiosity as an integral aspect of cognition and decision making during development and adulthood.