Scott Tonidandel, Phillip W. Braddy and John W. Fleenor
The purpose of this paper is to examine the relative importance of four managerial skill dimensions (technical skill, administrative skill, human skill, and citizenship behavior…
Abstract
Purpose
The purpose of this paper is to examine the relative importance of four managerial skill dimensions (technical skill, administrative skill, human skill, and citizenship behavior) for predicting managerial effectiveness. In addition, it aims to explore whether the relative importance of these skill dimensions varies as a function of gender or organizational level.
Design/methodology/approach
Participants were 733 managers enrolled in a nationally recognized leadership development program. Ratings of managerial skill were obtained from peers using a well‐validated 360‐degree assessment instrument, while manager effectiveness ratings were provided by supervisors. Moderated multiple regression and relative weight analysis were used to test the study's hypotheses.
Findings
Using ratings provided by multiple sources, these results show that all four of the managerial skill dimensions were significantly important predictors of manager effectiveness. Human skills were significantly more important than technical skill and citizenship behavior, while administrative skills were most important overall. Gender was not a significant moderator of the skill‐effectiveness relationship, but organizational level was.
Practical implications
Individuals tasked with selecting, developing, or placing managers should take all four skill dimensions into account. Moreover, special consideration should be given to administrative skill, and this emphasis should increase for managers higher up in the organizational hierarchy.
Originality/value
Although prior research has speculated about the importance of different managerial skills, this study is the first to provide empirical support for this skill typology in predicting actual managerial effectiveness using appropriate statistical analyses for examining the relative importance of these skill dimensions.
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Jeremy D. Mackey, Charn P. McAllister, Liam P. Maher and Gang Wang
Recently, there has been an increase in the number and type of studies in the organizational sciences that examine curvilinear relationships. These studies are important because…
Abstract
Recently, there has been an increase in the number and type of studies in the organizational sciences that examine curvilinear relationships. These studies are important because some relationships have context-specific inflection points that alter their magnitude and/or direction. Although some scholars have utilized basic techniques to make meta-analytic inferences about curvilinear effects with the limited information available about them, there is still a tremendous opportunity to advance our knowledge by utilizing rigorous techniques to meta-analytically examine curvilinear effects. In a recent study, we used a novel meta-analytic approach in an effort to comprehensively examine curvilinear relationships between destructive leadership and followers' workplace outcomes. The purpose of this chapter is to provide an actionable guide for conducting curvilinear meta-analyses by describing the meta-analytic techniques we used in our recent study. Our contributions include a detailed guide for conducting curvilinear meta-analyses, the useful context we provide to facilitate its implementation, and our identification of opportunities for scholars to leverage our technique in future studies to generate nuanced knowledge that can advance their fields.
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Derek R. Avery, Scott Tonidandel, Sabrina D. Volpone and Aditi Raghuram
Though a number of demographics (e.g. sex, age) have been associated with work overload, scholars have yet to consider the potential impact of immigrant status. This is important…
Abstract
Purpose
Though a number of demographics (e.g. sex, age) have been associated with work overload, scholars have yet to consider the potential impact of immigrant status. This is important because immigrants constitute a significant proportion of the workforce, and evidence suggests many employers believe they are easier to exploit. This paper aims to examine work hours, interpersonal justice, and immigrant status as predictors of work overload.
Design/methodology/approach
The hypotheses were tested using a large, national random telephone survey of employees in the United States (n=2,757).
Findings
As expected, employees who worked more hours tended to perceive more work overload. Importantly, however, this effect interacted with interpersonal justice differently for immigrant and native‐born employees. Justice attenuated the effect of work hours for the former but seemed to exacerbate it somewhat for the latter. Of note, the interactive effect was more than five times larger for immigrants than for natives.
Practical implications
The study shows that supervisors might require their employees to work longer hours without necessarily being perceived as abusive (i.e. overloading them). Doing so, however, requires treating employees justly in the form of respect, courtesy, and dignity. Though this form of just treatment is important for all employees, its effects are especially pronounced for immigrants.
Originality/value
The relationship between the number of hours worked and perceptions of work overload is examined for immigrant and non‐immigrant workers in the USA.
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Helena D. Cooper-Thomas, Jessica Xu and Alan M. Saks
The purpose of this paper is to apply and test a theory specifying which resources are most important for employee engagement. Specifically, this paper draws on resource theory to…
Abstract
Purpose
The purpose of this paper is to apply and test a theory specifying which resources are most important for employee engagement. Specifically, this paper draws on resource theory to outline six resources (love, status, services, information, goods, money) provided by the organization that employees will exchange for engagement.
Design/methodology/approach
The paper’s main focus is theoretical, outlining how resource theory provides a more nuanced classification and understanding of the workplace antecedents of engagement. Specifically, engagement is proposed to represent love as a resource, since engagement represents the whole-hearted investment of oneself. Thus, employees will exchange engagement for employer resources that similarly denote individual warmth and caring. The resource classification is assessed using engagement data from IBM NZ (n=13,929).
Findings
The theoretical analysis identifies eight workplace resources, five of which are proposed to be exchanged for engagement: mission, vision and values; opportunities for development; supportive leadership; job resources; and teamwork. Subsequent empirical analysis of IBM NZ data identified three similar constructs, with two being stronger predictors of employee engagement: learning and development; and vision and purpose. This provides some initial support for the application of resource theory to engagement.
Practical implications
Resource theory enables the identification of specific resources that will more strongly facilitate engagement: those which demonstrate warmth and caring for the employee.
Originality/value
Resource theory adds specificity in identifying which workplace resources will be exchanged for engagement, and therefore extends existing models of engagement, and is valuable for future employee engagement research and practice.
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Michael Howe, James K. Summers and Jacob A. Holwerda
The increasing prevalence and availability of big data represent a potentially revolutionary development for human resource management (HRM) scholars. Despite this, the current…
Abstract
The increasing prevalence and availability of big data represent a potentially revolutionary development for human resource management (HRM) scholars. Despite this, the current literature provides eclectic and often contradictory guidance for scholars attempting to conceptualize big data and subsequently incorporate it into relevant theoretical frameworks. The authors attempt to bridge this gap by discussing key considerations relevant to understanding and integrating big data into the existing theoretical landscape. Building on a novel, integrative definition of big data, the authors propose a parsimonious theoretical framework utilizing the established dimensions of complexity and dynamism as meta-attributes to bring order to the various attributes that have been proposed as central to defining big data (e.g., volume, variety, velocity, and variability). Throughout, the authors highlight numerous theoretical and empirical opportunities and considerations that this perspective holds for future HRM scholarship.
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Big Data is likely to have significant implications for the way in which services are planned, organised or delivered as well as the way in which we evaluate them. The increase in…
Abstract
Purpose
Big Data is likely to have significant implications for the way in which services are planned, organised or delivered as well as the way in which we evaluate them. The increase in data availability creates particular challenges for evaluators in the field of integrated care and the purpose of this paper is to set out how we may usefully reframe these challenges in the longer term.
Design/methodology/approach
Using the characteristics of Big Data as defined in the literature, the paper develops a narrative around the data and research design challenges and how they influence evaluation studies in the field of care integration.
Findings
Big Data will have significant implications for how we conduct integrated care evaluations. In particular, dynamic modelling and study designs capable of accommodating new epistemic foundations for the phenomena of social organisations, such as emergence and feedback loops, are likely to be most helpful. Big Data also generates opportunities for exploratory data analysis approaches, as opposed to static model development and testing. Evaluators may find research designs useful that champion realist approaches or single-n designs.
Originality/value
This paper reflects on the emerging literature and changing practice of data generation and data use in health care. It draws on organisational theory and outlines implications of Big Data for evaluating care integration initiatives.
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Allan H. Church, Lorraine M. Dawson, Kira L. Barden, Christina R. Fleck, Christopher T. Rotolo and Michael Tuller
Benchmark surveys regarding talent management assessment practices and interventions of choice for organization development (OD) practitioners have shown 360-degree feedback to be…
Abstract
Benchmark surveys regarding talent management assessment practices and interventions of choice for organization development (OD) practitioners have shown 360-degree feedback to be a popular tool for both development and decision-making in the field today. Although much has been written about implementing 360-degree feedback since its inception in the 1990s, few longitudinal case examples exist where interventions have been applied and their impact measured successfully. This chapter closes the gap by providing research findings and key learnings from five different implementation strategies for enhancing 360-degree feedback in a large multi-national organization. Recommendations and implications for future research are discussed.
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Stuti Thapa, Louis Tay and Daphne Hou
Experience sampling methods (ESM) have enabled researchers to capture intensive longitudinal data and how worker well-being changes over time. The conceptual advances in…
Abstract
Experience sampling methods (ESM) have enabled researchers to capture intensive longitudinal data and how worker well-being changes over time. The conceptual advances in understanding the variability of well-being are discussed. These emerging forms in the literature include affective inertia, affective variability, affective reactivity, and density distributions. While most ESM research has relied on the active provision of data by participants (i.e., self-reports), technological advances have enabled different forms of passive sensing that are useful for assessing and tracking well-being and its contextual factors. These include accelerometer data, location data, and physiological data. The strengths and weaknesses of passively sensed data and future ways forward are discussed, where the use of both active and passive forms of ESM data in the assessment and promotion of worker well-being is expected.
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John Bret Becton, H. Jack Walker, J. Bruce Gilstrap and Paul H. Schwager
The purpose of this paper is to investigate how HR professionals use social networking website information to evaluate applicants’ propensity to engage in counterproductive work…
Abstract
Purpose
The purpose of this paper is to investigate how HR professionals use social networking website information to evaluate applicants’ propensity to engage in counterproductive work behaviors and suitability for hire.
Design/methodology/approach
Using an experimental design, 354 HR professionals participated in a two-part study. In part 1, participants viewed a fictitious resume and rated the applicant’s likelihood to engage in counterproductive work behavior as well as likelihood of a hiring recommendation. In part 2, participants viewed a fictitious social networking website profile for the applicant and repeated the ratings from part 1. The authors analyzed their responses to determine the effect viewing a social network website (SNW) profile had on ratings of the applicant.
Findings
Unprofessional SNW information negatively affected ratings of applicants regardless of applicants’ qualifications, while professional SNW profile information failed to improve evaluations regardless of qualifications.
Originality/value
Anecdotal reports suggest that many employers use SNW information to eliminate job applicants from consideration despite an absence of empirical research that has examined how SNW content influences HR recruiters’ evaluation of job applicants. This study represents one of the first attempts to understand how HR professionals use such information in screening applicants. The findings suggest that unprofessional SNW profiles negatively influence recruiter evaluations while professional SNW profile content has little to no effect on evaluations.