Search results

This research employed two neurophysiological techniques (electroencephalograms (EEG) and galvanic skin response (GSR)) and machine learning algorithms to capture and analyze relationship-oriented leadership (ROL) and task-oriented leadership (TOL). By grounding the study in the theoretical perspectives of transformational leadership and embodied leadership, the study draws connections to the human body's role in activating ROL and TOL styles.

EEG and GSR signals were recorded during resting state and event-related brain activity for 52 study participants. Both leadership styles were assessed independently using a standard questionnaire, and brain activity was captured by presenting subjects with emotional stimuli.

ROL revealed differences in EEG baseline over the frontal lobes during emotional stimuli, but no differences were found in GSR signals. TOL style, on the other hand, did not present significant differences in either EEG or GSR responses, as no biomarkers showed differences. Hence, it was concluded that EEG measures were better at recognizing brain activity associated with ROL than TOL. EEG signals were also strongest when individuals were presented with stimuli containing positive (specifically, happy) emotional content. A subsequent machine learning model developed using EEG and GSR data to recognize high/low levels of ROL and TOL predicted ROL with 81% accuracy.

The current research integrates psychophysiological techniques like EEG with machine learning to capture and analyze study variables. In doing so, the study addresses biases associated with self-reported surveys that are conventionally used in management research. This rigorous and interdisciplinary research advances leadership literature by striking a balance between neurological data and the theoretical underpinnings of transformational and embodied leadership.

This chapter introduces electroencephalography (EEG), a measure of neurophysiological activity, as a critical method for investigating individual and team decision-making and cognition. EEG is a useful tool for expanding the theoretical and research horizons in organizational cognitive neuroscience, with a lower financial cost and higher portability than other neuroimaging methods (e.g., functional magnetic resonance imaging). This chapter briefly reviews past work that has applied cognitive neuroscience methods to investigate cognitive processes and outcomes. The focus is on describing contemporary EEG measures that reflect individual cognition and compare them to complementary measures in the field of psychology and management. The authors discuss how neurobiological measures of cognition relate to and may predict both individual cognitive performance and team cognitive performance (decision-making). This chapter aims to assist scholars in the field of managerial and organizational cognition in understanding the complementarity between psychological and neurophysiological methods, and how they may be combined to develop new hypotheses in the intersection of these research fields.

For organizational neuroscience to progress, it requires an overarching theoretical framework that locates neural processes appropriately within the wider context of organizational cognitive activities. In this chapter, we argue the case for building such a framework on two foundations: (1) critical realism, and (2) socially situated cognition. Critical realism holds to the importance of identifying biophysical roots for organizational activity (including neurophysiological processes) while acknowledging the top-down influence of higher-level, emergent organizational phenomena such as routines and structures, thereby avoiding the trap of reductionism. Socially situated cognition connects the brain, body, and mind to social, cultural, and environmental forces, as significant components of complex organizational systems. By focusing on adaptive action as the primary explanandum, socially situated cognition posits that, although the brain plays a driving role in adaptive organizational activity, this activity also relies on the body, situational context, and cognitive processes that are distributed across organizational agents and artifacts. The value of the framework that we sketch out is twofold. First, it promises to help organizational neuroscience become more than an arena for validating basic neuroscience concepts, enabling organizational researchers to backfill into social neuroscience, by identifying unique relations between the brain and social organization. Second, it promises to build deeper connections between neuroscience and mainstream theories of organizational behavior, by advancing models of managerial and organizational cognition that are biologically informed and socially situated.

In the era of Big Data, larger volumes of data arrive in various forms at an increasing pace but of questionable quality and value. The abundant information (that emanates from these 5Vs – volume, variety, velocity, veracity, and value) taxes the bounded capacity of managers. This chapter introduces a taxonomy of approaches available for strategic decision making in an information-rich environment, several of which showcase that automation can help to augment (not supplant) managerial decision making. This taxonomy is then applied to an innovation context. Mapping a stylized version of the phases of the innovation process (i.e., front-end innovation, new product development, commercialization) onto the four decision-making approaches yields an organizing framework for understanding strategic decision making in the realm of innovation. The chapter concludes by identifying promising areas for future research.

This conceptual chapter: (1) explicates the foundational terminology regarding strategic decision making in a marketing context; (2) provides a primer on the era of Big Data and making strategic decisions in an information-rich environment; (3) introduces a taxonomy, which features approaches to decision making in an information-rich environment; and (4) applies the taxonomy in an innovation context to yield an organizing framework.

This chapter focuses on the nascent field that is emerging at the intersection of innovation, marketing strategy, and information-rich environments, and breaks new ground by exploring automation available to aid managerial decision making in this realm.

The main practical implication is to elucidate that managers can apply different approaches to decision making in today’s information-rich environment. Tables 2–4 provide to managers 12 examples of the types of decision making in an innovation context.

This chapter introduces a new taxonomy to classify four approaches for making strategic decisions in an information-rich environment, and extends that framework to the innovation realm. This framework aims to prompt researchers to explore important topics that exist at the intersection of innovation, marketing strategy, and managerial decision making in an information-rich environment.

Presents the scientific methodology from the enlarged cybernetical perspective that recognizes the anisotropy of time, the probabilistic character of natural laws, and the entry that the incomplete determinism in Nature opens to the occurrence of innovation, growth, organization, teleology communication, control, contest and freedom. The new tier to the methodological edifice that cybernetics provides stands on the earlier tiers, which go back to the Ionians (c. 500 BC). However, the new insights reveal flaws in the earlier tiers, and their removal strengthens the entire edifice. The new concepts of teleological activity and contest allow the clear demarcation of the military sciences as those whose subject matter is teleological activity involving contest. The paramount question “what ought to be done”, outside the empirical realm, is embraced by the scientific methodology. It also embraces the cognitive sciences that ask how the human mind is able to discover, and how the sequence of discoveries might converge to a true description of reality.

In response to recent calls to better understand the brain’s role in organizational behavior, we propose a series of theoretical tests to examine the question “can brains manage?” Our tests ask whether brains can manage without bodies and without extracranial resources, whether they can manage in social isolation, and whether brains are the ultimate controllers of emotional and cognitive aspects of organizational behavior. Our analysis shows that, to accomplish work-related tasks in organizations, the brain relies on and closely interfaces with the body, interpersonal and social dynamics, and cognitive and emotional processes that are distributed across persons and artifacts. The results of this “thought experiment” suggest that the brain is more appropriately conceived as a regulatory organ that integrates top-down (i.e., social, artifactual and environmental) and bottom-up (i.e., neural) influences on organizational behavior, rather than the sole cause of that behavior. Drawing on a socially situated perspective, our analysis develops a framework that connects brain, body and mind to social, cultural, and environmental forces, as significant components of complex emotional and cognitive organizational systems. We discuss the implications for the emerging field of organizational cognitive neuroscience and for conceptualizing the interaction between the brain, cognition and emotion in organizations.

The purpose of the paper is to examine variables to be included in a measurement instrument which measures workplace learning related to recent research into quality management and brain functioning.

A literature review was conducted, investigating measures of workplace learning as well as the connections between brain functioning and management. Further studies will use the brain integration scale to compare levels of brain integration with measures of workplace learning.

The variables “empathy”, “presence and communication”, “continuity”, “influence”, “development”, “work-integrated learning” and “flow” were found to be relevant from the literature review to be tested for inclusion in the measurement instrument. A measurement model with these variables included has been developed.

This paper is conceptual in its nature. Empirical studies are needed to validate the propositions.

The proposed measurement instrument can be used by managers to gain insight into underlying mechanisms in the organizational culture that influence employees’ learning and potential for development. Thus, it can aid managers to achieve profound learning in their organizations, which is necessary for continuously maintaining high quality of products and services.

For society, the implementation of the proposed measurement instrument in companies could lead to better health and higher job satisfaction among employees.

Traditional ways of measuring working environment are rarely connected to brain functioning of the employees. Only requiring small resources, this approach adds to an understanding of underlying mechanisms.

Recent neuroscience research shows that two large-scale cortical networks are involved in organizational behavior. These two networks are naturally antagonistic – when one is active the other tends to be suppressed. The focus of the chapter is to apply the opposing-domains hypothesis to problems associated with: (1) trying to balance creative thinking and global processing with analytic reasoning and focused attention; (2) avoiding ethical dangers associated with an imbalance in task positive network (TPN) and default mode network (DMN) thinking; and (3) properly motivating and incentivizing employees so as not to lead to an imbalance between the TPN and DMN. We contend that the opposing-domains hypothesis can inform organizational and leadership theory in areas where single-dimensional dual-process models are inadequate.

The application of physiological methods to the study of psychological phenomena has garnered considerable interest in recent years. These methods have proved especially useful to the study of emotions, since evidence suggests that validly measuring a person’s emotional state using traditional, psychometric methods such as surveys or observation is considerably more difficult than once thought. The present chapter reviews the challenges associated with measuring emotions from a purely psychological perspective, and suggests that the study of emotions in organizations can benefit from the use of physiological measurement to complement traditional assessment methods. We review more established approaches to physiological measurement, including those related to hormone secretion, cardiovascular activity, and skin conductance. We then highlight somewhat more recent attempts to use neurological scanning. A theme of this chapter is that both psychological and physiological measures are relevant to understanding and assessing emotions in organizations. Accordingly, we propose a multi-method approach involving both types of assessment. Finally, we discuss the practical and ethical implications of employing various forms of physiological measurement in the study of emotions, specifically in the context of organizations.