Dyadic data analysis

Knight, A. P., & Humphrey, S. E. (In Press). Dyadic data analysis. In S. E. Humphrey and J. M. LeBreton (Eds.), The Handbook for Multilevel Theory, Measurement, and Analysis. Washington, DC: American Psychological Association.

Abstract. Many foundational theories in the social sciences rely upon assumptions about dyadic interpersonal perceptions, behaviors, and relationships. This chapter provides a broad introduction to foundational concepts and techniques in analyzing dyadic data. The authors describe in detail one specific approach to dyadic data analysis—the social relations model—and provide software functions for conducting the analysis using multilevel modeling in R. The value of dyadic data analysis is illustrated through a discussion of prior publications that have used this approach. The authors also provide a step-by-step empirical example of how to use the social relations model with multilevel modeling in R, focused on dyadic trust in workgroups. The chapter concludes with a discussion of alternative approaches, beyond the social relations model, for analyzing dyadic data.

Innovations in unobtrusive methods

Knight, A. P. (In Press). Innovations in unobtrusive methods. In A. Bryman and D. A. Buchanan (Eds.), Unconventional Methodology in Organization and Management Research. Oxford: Oxford University Press.

Abstract. Twenty years ago, engineer and computer scientist Rosalind Picard (1997, p.228) imagined a future in which ‘a financial analyst might combine his cell phone, pager, online stock reports, analysis software, and personal email agent into one computer that fits in a belt, watch and shirt pocket’.  Clearly the future is now.  An estimated 1.4 billion people owned a smartphone in 2013 – more than one fifth of the global population (Heggestuen, 2013).  By 2020, that proportion is expected to rise to approximately 70 percent (Ericsson, 2015).  And smartphones are just the tip of the iceberg, as a proliferation of internet-connected devices expands the linkages among humans, computers, and networks.  Consider just a few of the devices released recently.  Glasses developed by companies like Google and Snap enable users to capture and share multimedia content in real-time; wristbands like those developed by Fitbit, Apple, and Samsung facilitate fitness tracking, payments, and more.

The ubiquity of connected devices (Swan, 2012) – and the metrics that they unobtrusively capture – has led data to become increasingly central to the global economy.  Companies have integrated novel unobtrusive data streams into their business models and operations (e.g. Walker, 2012; Wilson, 2013).  These data streams can elucidate consumer preferences and responses to advertising, enhance human resource practices, and improve collaboration networks – to name just a few publicized applications.

Much like new data streams have enriched contemporary businesses, innovative unobtrusive methods hold great promise for researchers who study organizational functioning (Tonidandel et al., 2016).  The idea that researchers can benefit from using unobtrusive methods is certainly not new.  More than half a century ago, Webb and colleagues (1966) implored researchers in their classic book Unobtrusive Measures to use a more diverse set of data streams in their work, noting that, ‘Today the dominant mass of social science research is based upon interviews and questionnaires.  We lament this overdependence upon a single fallible method’ (pp.1-2).  Notwithstanding a steady drumbeat of pleas over the years for researchers to use unobtrusive methods (e.g. Hill et al., 2014; Webb and Weick, 1979), survey methods continue to dominate the literature, especially in organizational behaviour, and researchers still often rely on a single data source (Podsakoff et al., 2012; Scandura and Williams, 2000).

The purpose of this chapter is to describe a new suite of unobtrusive methods, such as the traces that people leave throughout the digital world as they search the Internet, post content on social media, and navigate an increasingly digitally-connected physical world.  These methods, which did not exist when Webb and colleagues published their book, make it easier and cheaper for researchers to use unobtrusive methods than ever before.  As a result, we social science researchers have fewer and fewer excuses for relying on a single source of data, obtrusively acquired, in empirical studies.

Organizational affective tone

Knight, A. P., Menges, J. I., & Bruch. H. (In Press). Organizational affective tone: A meso perspective on the origins and effects of consistent affect in organizations. Academy of Management Journal.

Abstract. Grounded in an open systems perspective, we build and test new theory about how the kinds of industries in which an organization participates influences organizational affective tone and connects to workforce strain. We propose that the more an organization’s activities lie in consumer-centric industries (e.g., service, retail), the more positive and less negative the organization’s affective tone. We connect consumer-centric industry participation and affective tone by explaining how personnel policies and organizational structure generate and sustain consistent positive and negative affect throughout an organization. Additionally, we examine the effects of organizational affective tone on workforce strain. The results of a survey-based study of 24,015 human resource managers, top management team members, and employees of 161 firms largely support our predictions. We discuss the implications of considering macro contextual factors for understanding affect in organizations.

Resources and relationships in entrepreneurship

Huang, L., & Knight, A. P. (2017). Resources and relationships in entrepreneurship: An exchange theory of the development and effects of the entrepreneur-investor relationship. Academy of Management Review, 42, 80-102.

Abstract. We develop a theoretical model, grounded in exchange theory, about the process through which relationships between entrepreneurs and investors develop and influence the growth of new ventures. Our theory highlights the multifaceted relationships that entrepreneurs and investors share—comprising both affective and instrumental dimensions—and the bidirectional exchanges of social and financial resources that build these relationships over time. An exchange theory perspective sheds light on the emergence of different patterns of relationship development over time and how different kinds of resource exchange contribute to new venture growth, contingent on the core problems that a venture faces at a given stage of development. We discuss implications of an exchange perspective on resources and relationships in entrepreneurship for theory, research, and practice.

Using recurrence analysis to examine group dynamics

Knight, A. P., Kennedy, D. M., McComb, S. A. (2016). Using recurrence analysis to examine group dynamics. Group Dynamics: Theory, Research, and Practice, 20, 223-241.

Abstract. This article provides an accessible introduction to recurrence analysis—an analytical approach that has great promise for helping researchers understand group dynamics. Recurrence analysis is a technique with roots in the systems dynamics literature that was developed to reveal the properties of complex, nonlinear systems. By tracking when a system visits similar states at multiple points in its life—and the form or pattern of these recurrences over time—recurrence analysis equips researchers with a set of new metrics for assessing the properties of group dynamics, such as recurrence rate (i.e., stability), determinism (i.e., predictability), and entropy (i.e., complexity). Recent work has shown the potential value of recurrence analysis across a number of different disciplines. To extend its use within the domain of group dynamics, the authors present a conceptual overview of the technique and give a step-by-step tutorial on how to use recurrence analysis to study groups. An exemplar application of recurrence analysis using dialogue-based data from 63 three-person student groups illustrates the use of recurrence analysis in examining how groups change their focus on different processes over time. This is followed by a discussion of variations of recurrence analysis and implications for research questions within the literature on groups. When group researchers track group processes or emergent states over time, and thus compile a time series dataset, recurrence analysis can be a useful technique for measuring the properties of groups as dynamic systems.

The impact of environment and occupation on the health and safety of active duty air force members

Erich, R., Eaton, M., Mayes, R., Pierce, L., Knight, A. P., Genovesi, P., Escobar, J., Mychalczuk, G., Selent, M. (2016). The impact of environment and occupation on the health and safety of active duty Air Force members: Database development and de-identification. Military Medicine, 181, 821-826.

Abstract. Preparing data for medical research can be challenging, detail oriented, and time consuming. Transcription errors, missing or nonsensical data, and records not applicable to the study population may hamper progress and, if unaddressed, can lead to erroneous conclusions. In addition, study data may be housed in multiple disparate databases and complex formats. Merging methods may be incomplete to obtain temporally synchronized data elements. We created a comprehensive database to explore the general hypothesis that environmental and occupational factors influence health outcomes and risk-taking behavior among active duty Air Force personnel. Several databases containing demographics, medical records, health survey responses, and safety incident reports were cleaned, validated, and linked to form a comprehensive, relational database. The final step involved removing and transforming personally identifiable information to form a Health Insurance Portability and Accountability Act compliant limited database. Initial data consisted of over 62.8 million records containing 221 variables. When completed, approximately 23.9 million clean and valid records with 214 variables remained. With a clean, robust database, future analysis aims to identify high-risk career fields for targeted interventions or uncover potential protective factors in low-risk career fields.

The effects of group affect on social integration and task performance

Knight, A. P., & Eisenkraft, N. (2015). Positive is usually good, negative is not always bad: The effects of group affect on social integration and task performance. Journal of Applied Psychology, 100, 1214-1227.

Abstract. Grounded in a social functional perspective, this article examines the conditions under which group affect influences group functioning. Using meta-analysis, the authors leverage heterogeneity across 39 independent studies of 2,799 groups to understand how contextual factors—group affect source (exogenous or endogenous to the group) and group life span (one-shot or ongoing)—moderate the influence of shared feelings on social integration and task performance. As predicted, results indicate that group positive affect has consistent positive effects on social integration and task performance regardless of contextual idiosyncrasies. The effects of group negative affect, on the other hand, are context-dependent. Shared negative feelings promote social integration and task performance when stemming from an exogenous source or experienced in a 1-shot group, but undermine social integration and task performance when stemming from an endogenous source or experienced in an ongoing group. The authors discuss implications of their findings and highlight directions for future theory and research on group affect.

Group affect

Barsade, S. G., & Knight, A. P. (2015). Group affect. Annual Review of Organizational Behavior and Organizational Psychology, 2, 21-46.

Abstract. Over two decades of research has indicated that group affect is an important factor that shapes group processes and outcomes. We review and synthesize research on group affect, encompassing trait affect, moods, and emotions at a collective level in purposive teams. We begin by defining group affect and examining four major types of collective affective constructs: (a) convergence in group affect; (b) affective diversity, that is, divergence in group affect; (c) emotional culture; and (d) group affect as a dynamic process that changes over time. We describe the nomological network of group affect, examining both its group-level antecedents and group-level consequences. Antecedents include group leadership, group member attributes, and interactions between and relationships among group members. Consequences of group affect include attitudes about the group and group-level cooperation and conflict, creativity, decision making, and performance. We close by discussing current research knowns, research needs, and what lies on the conceptual and methodological frontiers of this domain.

Who defers to whom and why?

Joshi, A., & Knight, A. P. (2015). Who defers to whom and why? Implications of demographic differences and dyadic deference for team effectiveness. Academy of Management Journal, 58, 59-84.

Abstract. We develop and test predictions about how demographic differences influence dyadic deference in multidisciplinary research teams, and how differential patterns of dyadic deference emerge to shape team-level effectiveness. We present a dual pathway model that recognizes that two distinct mechanisms—task contributions and social affinity— account for how team members’ demographic attributes contribute to deference. Furthermore, we propose that the extent to which these different mechanisms are prevalent in a team has implications for the team’s research productivity, with deference based on social affinity detracting from it and deference based on task contributions enhancing it. Using longitudinal data from a sample of 55 multidisciplinary research teams comprising 619 scientists, we found general support for our conceptual model. Our findings underscore the importance of accounting for multiple interpersonal mechanisms to understand the complex, multilevel nature of deference in teams.

Affect and change in exploratory search over time

Knight, A. P. (2015). Mood at the midpoint: Affect and change in exploratory search over time in teams that face a deadline. Organization Science, 26, 99-118.

Abstract. The purpose of this paper is to advance the team dynamics and group development literatures by developing and testing a theoretical model of how affect shapes transitions in teams over time. Integrating the group transitions literature with theory and research on the mood-as-input theory, I propose that shared team mood influences the extent to which team members seek out and experiment with alternative ways of completing their work at different points in a team’s life. In the first half of the team’s life, when team members are relatively task-focused, I argue that team positive mood (i.e., a positively valenced affective state shared by team members at a given point in time) stimulates, whereas team negative mood (i.e., a negatively valenced affective state shared by team members) suppresses, exploratory search. At the temporal midpoint, however, when team members’ focus on performance heightens, team positive mood acts as a shutoff switch for search, leading to a decline in exploratory search over the second half of the team’s life. Team negative mood at the midpoint, on the other hand, leads team members to persist in exploratory search, even as a deadline draws near. A team’s trajectory of exploratory search over time, I propose, influences team performance such that it is highest when teams engage in high exploratory search early in the team’s life and decline in exploratory search over the second half of the team’s life. The results of a longitudinal, survey-based study of teams preparing for a military competition largely support my predictions.