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This chapter’s focus is comparative causal mapping (CCM) methods in MOC research. For a background, the chapter discusses first the conceptual (cognitive theoretic) basis in typical CCM studies and its implications for understanding the target phenomena and for CCM methods. Next, it presents the CMAP3 software and describes its operating logic and main functions. Third, the chapter describes how to use CMAP3 in three prototypical cases of CCM, each characterized by different research objectives, kinds of data, and methods of data acquisition but also by potential dilemmas. The chapter concludes by speculating about the future directions of causal mapping and suggesting some ideas for developing in particular large-N CCM methods.

The purpose of this study is to illustrate the use of the ad hoc methodology of causal mapping to support the process of quantifying the financial returns related to sustainability investments. The present study uses two methods to build causal maps, that is aggregate and congregate mapping, in order to capture managerial cognition and derive a model that reflects companies’ competitive advantages. The resulting causal map is a prerequisite and serves as a building block for the design of the organisation’s performance management systems for sustainability.

This study relies on qualitative, deductive research undertaken at the leading international pharmaceutical company Novo Nordisk. This chapter presents the results of a longitudinal study developed through an action research approach conducted at the Company over a four-year period.

This study illustrates how the described approach for developing causal maps can facilitate the elicitation of managerial tacit knowledge and the consequent identification of indicators to quantify the investments in sustainability.

This chapter proves the relevance of causal mapping as a comprehensive, articulated basis for developing and improving organisations’ strategic performance measurement systems (SPMSs).

This study’s main contribution is the triangulation of multiple qualitative methods to enhance the reliability of causal maps. This innovative approach supports the use of causal mapping to extract managerial tacit knowledge in order to identify indicators for the evaluation of investments in sustainability.

Research has highlighted the cognitive nature of the business model intended as a cognitive representation describing a business’ value creation and value capture activities. Although the content of the business model has been extensively investigated from this perspective, less attention has been paid to the business model’s causal structure – that is the pattern of cause-effect relations that, in top managers’ or entrepreneurs’ understandings, link value creation and value capture activities. Building on the strategic cognition literature, this paper argues that conceptualizing and analysing business models as cognitive maps can shed light on four important properties of a business model’s causal structure: the levels of complexity, focus and clustering that characterize the causal structure and the mechanisms underlying the causal links featured in that structure. I use examples of business models drawn from the literature as illustrations to describe these four properties. Finally, I discuss the value of a cognitive mapping approach for augmenting extant theories and practices of business model design.

This chapter applies Axelrod’s (1976) and Huff’s (Huff, A. S. (1990). Mapping strategic thought. In A. S. Huff (Ed.), Mapping strategic thought (pp. 88–115). Chichester: Wiley; Jenkins & Huff, 2002) approach to mapping strategic thought (causal mapping) to (1) categorize how manufacturers of new fast moving consumer goods (FMCGs) may respond to environmental feedback to their decisions and (2) assess the effectiveness of alternative implemented decisions in assisting organizational growth. The manufacturing of new FMCGs requires timely product modifications in the assumptions of entrepreneur thinking in response to environmental responses/non-responses to decisions/actions of the manufacturing enterprise. A detailed example of causal mapping analysis is presented for a manufacturing entrepreneurial case study; the example covers processes linking events, decisions, and activities in business start-up, growth, and failure of the enterprise. The chapter closes by suggesting that causal mapping analysis is a valuable tool for advancing theory construction from case study research. The chapter provides a research plan for future reports applying causal mapping in retailing entrepreneur studies.

Our primary objective is to provide method-related broad guidelines to researchers on the entire spectrum of issues involved in cause mapping and to encourage researchers to use causal mapping techniques in strategy research. We challenge strategists to open the black box and investigate the mental models that depict the cause and effect beliefs of managers, “walk” readers through the causal mapping process by discussing the “nuts and bolts” of cause mapping, provide an illustration, and outline “key issues to consider.” We conclude with a discussion of some promising research directions.

At the level of a cognitive schema, a business model is a mental map of a firm’s value-creating, value-delivering, and value-capturing activities and the linkages between them. An important question in the study of business models as cognitive schemas is whether and how schemas differ across industry actors and whether the differences are connected to the variation observed in actual business models in the industry. This chapter examines, in particular, the ways in which business model schemas of industry insiders differ from those of industry outsiders. Using data from interviews with chief executive officers (CEOs) of 30 legal-tech firms, we graphically construct and analyze the CEOs’ schemas of important causal interdependencies between their firms’ activities. The analysis shows systematic differences between insiders and outsider CEOs’ schemas. We theorize that these differences underlie insider and outsider CEOs’ distinct approaches to opportunity recognition, expertise perception, and value framing, and have consequences for actual business model evolution in the industry.

In this chapter, the authors reflect on their experience of editing the first five volumes of the book series New Horizons in Managerial and Organizational Cognition. The authors summarize some of the contributions of articles published in the series, including those comprising this fifth volume. From its beginnings as a follow-up publication of the second Frontiers in Managerial and Organizational Cognition (MOC) conference, the series has moved in several directions exploring how the field is developing, and what new applications of MOC theories and methods are being explored. The authors identify and highlight several lines of investigation in particular: work that furthers their understanding of schema and cognitive mapping, work on framing, work on identity, work on heuristics and intuition, work on emotions, and modern methodological advances, enabled by IT and other technologies.

In this brief introduction, we reflect on the diversity of studies connecting cognition to innovation and the enormous potential that exists for further research. Research streams on cognition in organizations, innovation in organizations, and intra- and entrepreneurship have developed in parallel over the past decades, with frequent touchpoints, notably in terms of theories of cognition informing studies on the processes of innovation and creativity. Cognition theories have thus been considered as micro-foundations of many theories of innovation. Here, we outline the many ways that theories of cognition can yield insights for studies of innovation and discuss the contributions of chapters comprising this third volume of New Horizons in Managerial and Organizational Cognition.

In order to shed light on the implications of the business intelligence (BI) for management accounting (MA) and decision making, this study investigates as to how the use of the BI affects the production, transmission, and reception of performance measures (PM).

To investigate the issue at hand, a case study of an Italian company is carried out. The case study method is deemed suitable to explore the complex, penetrating, and unpredictable relationship between BI and PM.

The case analysis shows that the use of the BI can affect the production of PM by leading the organization to frame PM into an indicator setting. Moreover, the BI can affect the transmission by introducing a new, “visual” approach for presenting PM to decision makers, which is also relevant in the reception as a mobilizing factor.

This study contributes to improving the understanding of BI implications for MA and decision making, which is still limited in the accounting academia. Additionally, this research adds to extant knowledge about the relationship between measurement and management; more specifically, it contributes to understanding the “fate” of PM.

Furthermore, the findings illustrated in this chapter can be relevant from a practical point of view: by showing the role that BI solutions can play in producing and transmitting PM, the study shows the potential contribution of the use of the BI in managing and overcoming problems arising in these phases, favoring the use of these measures.

The implications and influence of different cognitive map structures on decision-making, reasoning, predictions about future events, affect, and behavior remain poorly understood. To-date, we have not had the mechanisms to determine whether any measure of cognitive map structure picks up anything more than would be detected on a purely random basis. We report a Monte Carlo method of simulation used to empirically estimate parameterized probability outcomes as a means to better understand the behavior of cognitive map. Using worked examples, we demonstrate how the results of our simulation permit the use of exact statistics which can be applied by hand to an individual map or groups of maps, providing maximum utility for the collective and cumulative process of theory building and testing.