Methodological Challenges and Advances in Managerial and Organizational Cognition: Volume 2

This book comprises the second volume in the recently launched New Horizons in Managerial and Organizational Cognition book series. Volume 1 (Sund, Galavan, & Huff, 2016), addressed the topic of strategic uncertainty. This second volume comprises a collection of contributions that variously report new methodological developments in managerial and organizational cognition, reflect critically on those developments, and consider the challenges that have yet to be confronted in order to further advance this exciting and dynamic interdisciplinary field. Contextualizing within an overarching framework the various contributions selected for inclusion in the present volume, in this opening chapter we reflect more broadly on what we consider the most significant developments that have occurred over recent years and the most significant challenges that lie ahead.

In this chapter we examine some possibilities of using computer simulation methods to model the interaction of affect and cognition in organizations, with a particular focus on agent-based modeling (ABM) techniques. Our chapter has two main aims. First, we take stock of methodological progress in this area, highlighting important developments in the modeling of affect and cognition in other fields, including psychology and economics. Second, we outline how ABM in particular can help to advance managerial and organizational cognition by building and testing theoretical models predicated on the interaction of affect and cognition. We argue that using ABM for this purpose can improve the level of specificity of cognitive and affective concepts and their interrelationships in organizational theories, yield more behaviorally plausible models of behavior in and of organizations, and deepen understanding of the generative behavioral mechanisms of multi-level organizational phenomena. We highlight possibilities for using ABM to model affect–cognition interactions in studies of mental models, collective cognition, diversity in work groups and teams, and organizational decision-making.

I present a way of conducting open-ended interviews that I have used in my own research. Good preparation for interviews includes learning about the interviewee and their context beforehand, developing a list of potential follow-up themes, and various hygiene factors. During the interview, key practices include building psychological safety and earning professional respect, phasing questions appropriately, using various types of elaborating questions, tolerating long pauses, and recognizing that managers are rarely naïve interviewees. Analyzing interview data requires being mindful of the content rather than coding it mechanically, using theories to aide interpretation, and getting deeply engaged with the data.

Leadership training has led to a large amount of research due to the belief that such training can lead to (or more precisely cause) positive changes in followers’ behavior and work performance. This chapter describes some of the conditions necessary for research to show a causal relationship between leadership training and outcomes. It then describes different research designs, employed in leadership training research, and considers the types of problems that can affect inferences about causality. The chapter focuses on the role of randomization of leaders (e.g., into training vs. non-training conditions) as a key methodological procedure and alludes to problems of achieving this in field settings.

Policy-capturing is an experimental technique potentially capable of providing powerful insights into the cognitive bases of work-related decision processes by revealing actors’ “implicit” models of the problem at hand, thereby opening up the “black box” of managerial and organizational cognition. This chapter considers the strengths and weaknesses of policy-capturing vis-à-vis alternative approaches that seek to capture, in varying ways, the inner workings of people’s minds as they make decisions. It then outlines the critical issues that need to be addressed when designing policy-capturing studies and offers practical advice to would-be users concerning some of the common pitfalls of the technique and ways of avoiding them.

With behavioral experiments and protocol analysis, researchers can capture cognition in action. Using behavioral experiments, they can study realized behavior, not perception or self-reports. And they can do that in a controlled laboratory environment to establish causality, curbing spurious relationships. With protocol analysis, a method to elicit decision-makers’ thoughts, researchers can tap into cognitive processes. In combination, the two methods offer a novel approach to grasp mental processes alongside behavior, to reach causality and replicate findings. We describe the methods, demonstrate how researchers can apply them, and share practices from the design of experimental instruments to the replication of findings.

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 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.

Our preoccupation with the Repertory Grid Technique has left little time and attention to the core ideas articulated in Kelly’s (1955) Theory of Personal Constructs. After more than 20 years engaging with the method, I have (re)discovered his theorizing about man’s quest for knowing, to be the most insightful. This chapter shares my reflections/reflexions about the crucial role he placed on the notion of “anticipation.” I position this importance within the context of the challenges of our times and advocate that his “psychology of the unknown” is just as important today as it was 62 years ago.

In light of the growing interest in neuroscience within the managerial and organizational cognition (MOC) scholarly domain at large, this chapter advances current knowledge on core neuroscience methods. It does so by building on the theoretical analysis put forward by Healey and Hodgkinson (2014, 2015), and by offering a thorough – yet accessible – methodological framework for a better understanding of key cognitive and social neuroscience methods. Classifying neuroscience methods based on their degree of resolution, functionality, and anatomical focus, the chapter outlines their features, practicalities, advantages and disadvantages. Specifically, it focuses on functional magnetic resonance imaging, electroencephalography, magnetoencephalography, heart rate variability, and skin conductance response. Equipped with knowledge of these methods, researchers will be able to further their understanding of the potential synergies between management and neuroscience, to better appreciate and evaluate the value of neuroscience methods, and to look at new ways to frame old and new research questions in MOC. The chapter also builds bridges between researchers and practitioners by rebalancing the hype and hopes surrounding the use of neuroscience in management theory and practice.

If we want to improve managerial cognition, we need to capture the full spectrum of cognitive functions and the complex processes through which they unfold. I propose two very different methods (one older and low-tech, one newer and high-tech) that allow us to observe cognitive functions and processes directly in real time.

Managerial cognition is a fundamental area informing all sub-fields in strategy, and therefore, a systematic review of the methodological choices of premier strategy publications aids cognition researchers in choosing methods. However, past studies have given little attention to the methods recently published in premier journals. This chapter both illustrates a common cognitive method – content analysis – and uses it to analyze the methodological content of 573 publications from two prominent management journals. Our findings provide cognition scholars with useful information about current methodological standards. Our findings also will help students choose methods courses and will spark a healthy debate about methodological expectations.