Age and Work

Advances in Theory, Methods, and Practice

Hannes Zacher, Cort W. Rudolph, Hannes Zacher, Cort W. Rudolph

• Publisher: Routledge
• Year: 2022
• eBook ISBN: 9781000542622
• Topic: Business
• Subtopic: Organisational Behaviour
• Index: Business

The edited volume Age and Work: Advances in Theory, Methods, and Practice presents a systematic collection of key advances in theory, methods, and practice regarding age(ing) and work. This cutting-edge collection breaks new ground by developing novel and useful theory, explaining underutilized but important methodological approaches, and suggesting original practical applications of emerging research topics.

The book begins with a prologue by the World Health Organization's unit head for aging and health, an introduction on the topic by the editors, and an overview of past, current, and future workforce age trends. Subsequently, the first main section outlines theoretical advances regarding alternative age constructs (e.g., subjective age), intersectionality of age with gender and social class, paradoxical age-related actions, generational identity, and integration of lifespan theories. The second section presents methodological advances regarding behavioral assessment, age at the team and organizational levels, longitudinal and diary methods, experiments and interventions, qualitative methods, and the use of archival data. The third section covers practical advances regarding age and job crafting, knowledge exchange, the work/nonwork interface, healthy aging, and absenteeism and presenteeism, and organizational meta-strategies for younger and older workers. The book concludes with an epilogue by an eminent scholar in age and work.

Written in a scientific yet accessible manner, the book offers a valuable resource for undergraduate and graduate students, academics in the fields of psychology and business, as well as practitioners working in the areas of human resource management and organizational development.

SECTION III Advances in Methods to Study Age and Work

8 PERCEIVED AND ACTUAL BEHAVIORS IN RESEARCH ON AGE AND WORK

Fabiola H. Gerpott and Nale Lehmann-Willenbrock

DOI: 10.4324/9781003089674-11

It has been well documented that people change physically and psychologically with age. Some of these changes are demonstrated through people’s behaviors at work.

—(Taneva et al., 2016, p. 397)

The Goal: Studying Actual Behavior

The opening quote mentions a fact that motivates many age and work scholars to engage in research that aims to understand the antecedents, changes, and consequences of younger and older employees’ behaviors at work. However, the field so far largely studies perceptions of behavior. To explain this statement, it is worth pondering on what we mean when we refer to the study of behavior. We define behavior as any observable action (verbal statement, movement, emotional expression, and so forth) performed by a person that is socially meaningful in the present moment (e.g., Gerpott et al., 2020; Uher, 2016).

Our definition of behavior has two important components that deserve further elaboration. First, the definition focuses on observable actions. As such, we exclude internal bodily functions as they are not directly observable and are not under the control of the individual (Aron, 2010). Second, the notion that behavior must be socially meaningful means that we are interested in behavior as a transmitter of social information. This does not mean that socially meaningful behavior is necessarily logically comprehensible, intentional, or completely self-determined. Rather, behavior can include unconsciously guided acts, occur in highly interdependent contexts, or be enacted thoughtlessly. It also does not necessarily require the physical presence of other people (e.g., a person who composes an email to their team when working by themselves in the office shows a socially meaningful behavior although no one is watching). What our definition of behavior does require is that the behavior can at least potentially trigger reactions by another individual (i.e., the definition does not include biomarkers such as heartbeats or fMRI activation patterns that cannot be observed by others).

To qualify as a study of behavior, the behavior itself must be the focal act of interest. For example, whereas completing a questionnaire is a behavioral response shown by an individual (i.e., a scholar can observe that a participant is ticking certain answer boxes), we would only consider this a socially meaningful act in a behavior-focused research design if the ticking behavior itself is investigated. However, in most research designs on age and work, this has not been the case as scholars are typically interested in the content that is conveyed through the response behavior (i.e., perceived behaviors, inner convictions, attitudes, etc.) but not the response behavior itself.

Our definition of behavior further implies that we differentiate between research based on “actual behavior” and empirical work that relies on “per-ceptions of behavior.” Studies investigating perceptions of the acts that a focal person engages in use self-reports or other-reports of involved individuals (e.g., peers, supervisors, employees). In contrast, studies that employ measures of actual behavior rely on technology-based behavior tracking (e.g., automatic speech detection, eye tracking) or systematic annotation or coding of behavior by outside observers according to reproducible observation procedures and coding rules (e.g., a researcher classifying the verbal behavior exhibited by participants who were observed during a social interaction). Broadly speaking, this entails that we differentiate survey-based research from research designs that capture behaviors (i.e., the focus of the present chapter), manipulate behaviors (see Chapter 11), or train/develop actual behaviors (see Chapter 14).

The purpose of our chapter is to convince scholars that the time is ripe for age research to combine questionnaire-focused research practices with behavior-based research designs, such as those put forward in this chapter and in the next chapters on methodological advances. Such an enrichment of our methodological toolbox can be used to triangulate results across different methodologies, as well as help to expand theories to explain why there are systematic differences in what people think or perceive they or others do and what they actually do. To preview the structure of this chapter, we begin with a short recap of the problem (i.e., research is often not studying actual behavior) and provide a disclaimer (i.e., studying actual behavior is not a silver bullet). Based on this foundation, we provide an overview of prevalent tools to capture behavior and delineate a conceptual framework for selecting an appropriate time-theoretical scope in behavior research. We end with some future research inspiration that hopefully motivates scholars in the field of age and work to develop more concrete ideas on how their future work could profit from data triangulation by incorporating behavioral measures in their research designs.

The Problem: Not Studying Behavior

Recognizing that people act upon their perceptions and, in doing so, create a rather objective reflection of the world (Gerpott et al., 2018), one may wonder why scholars should even bother about actual behavior. Indeed, the “cognitive revolution” with its focus on inner psychological processes quickly ousted behaviorism with its exclusive focus on observable behavior (Baumeister et al., 2007). And there are many advantages of using questionnaires to capture perceptions of behavior: Scholars can, for example, easily ask about everyday work activities that are difficult to capture via behavioral observation, filling in surveys is often cheaper and requires less data collection effort than obtaining behavioral data, and self-reports are more easily approved by companies and Institutional Review Boards as data security concerns are lower (after all, people can easily lie when they do not want to report about a certain behavior). Considering these exemplary advantages (and there are many more), the laborious path of capturing, manipulating, or training/developing behavior in studies on younger and/or older study participants’ behaviors at work may seem like an unnecessary scholarly effort.

However, most scholars will agree that individuals’ perceptions can differ substantially from what is happening in organizational reality. Behavioral measures and self-reports often capture different aspects of work-related phenomena, which is also reflected in the empirical finding that self-reports and behavioral measures tend to be only weakly correlated (Dang et al., 2020). The weak correlation between survey-based proxies and observations of actual behavior concerns people’s reporting of both their own and others’ behavior in hypothetical as well as already experienced situations. Such discrepancies are often driven by a social desirability bias and could, for example, mean that employees drastically overreport their willingness to share knowledge with an older/younger colleague—a prosocial behavior typically captured with survey designs in age and work research (see Chapter 15). This tendency may become even stronger for older employees, because—in line with socioemotional selectivity theory (Carstensen et al., 1999)—with increasing age, people tend to remember situations with a higher self-serving bias (Mezulis et al., 2004). Lastly, employees’ actual knowledge-sharing behavior may be more strongly influenced by bodily cues of attractiveness and youthfulness than they would admit (or could imagine; see also Tsay, 2020) because people underestimate the degree to which biases influence their behavior. If the age and work field derives practical implications based only on potentially biased survey reports without ever verifying them with studies of actual behavior, this carries the serious risk of designing training and intervention programs that do not work—or, even worse, that systematically discriminate against younger and/or older employees.

Disclaimer

In positioning this chapter, we want to emphasize that our intention is by no means to completely replace survey research with unobtrusive behavioral measurements. The choice of an appropriate design and measurement tool always depends on the research question that should be answered and the focal variables of interest. For instance, regarding attitudes as focal variables, asking participants to report about their own attitudes in a survey is often an adequate approach. Furthermore, when using behavior-focused measurement tools, scholars need to be aware that they come with their own challenges. While a discussion of these challenges could certainly fill another book chapter or even book, we highlight three key issues. First, behavioral measurement tools may not be as objective as scholars often claim. To illustrate, scholars who annotate the verbal or nonverbal behavior of participants while observing a workplace interaction need to interpret the behavior. Even when using a standardized coding scheme for this task and ensuring inter-rater reliability, the annotation of the data is still bound to the cultural context and the accompanying translation of meaning. Second, although research shows that employees quickly forget about the fact that they are observed and behave as they normally would (e.g., Kauffeld & Lehmann-Willenbrock, 2012), one can nevertheless raise concerns about behavioral data being subject to biases that are imposed via the process of observation. A classic example in that regard is the Hawthorne effect, which refers to the idea that people behave differently just because they know they are the subject of research (for criticism questioning the existence of this effect see Jones, 1992; Wickström & Bendix, 2000). Third, considering that behavior is often assessed in specific social interactions, the retest reliability (and thus predictive validity) can be lower than for survey instruments that ask participants to report general perceptions. For example, when asking an older employee about their general tendency to share knowledge with younger employees at work, they may respond consistently in a survey over several measurement points. However, when observing and coding two concrete incidents of knowledge sharing with two different younger colleagues, the behavior of the very same person may show high variability depending for example on how much they like each of the two younger colleagues or whether there are differences in the intellectual capability of the two knowledge receivers. Accordingly, the focus in behavior studies lies often on the behavior itself, instead of between-person differences (Dang et al., 2020).

Recognizing that both survey- and behavior-based research has shortcomings, the purpose of our chapter is to increase methodological diversity in research regarding age and work by encouraging the field to combine both data collection approaches to ultimately gain a richer conceptual understanding of how perceptions and behavior are connected (Gerpott et al., 2020). The almost exclusive focus on survey designs puts age-and-work research at risk of falling behind technological solutions for capturing behavioral data to understand younger and older employees’ activities at work. For example, computer scientists have established models that can automatically analyze online interactions to recognize when a person may have trouble learning shared knowledge, without requiring the knowledge receiver to explicitly express their learning difficulties (Soller & Lesgold, 2003). Moreover, eye-tracking software can be utilized to war...

Table of contents

• Cover Page
• Half Title Page
• Series Page
• Title Page
• Copyright Page
• Dedication Page
• Table of Contents Page
• List of Figures Page
• List of Tables Page
• Editor Biographies Page
• Contributor Biographies Page
• Series Foreword Page
• Prologue Page
• SECTION I Introduction and Overview
• SECTION II Advances in Theory on Age and Work
• SECTION III Advances in Methods to Study Age and Work
• SECTION IV Advances in Practice Regarding Age and Work
• Epilogue
• Index