The HPWS and AMO: a dynamic study of system- and individual-level effects

PurposeDrawing on the dynamic model of ability, motivation, opportunity (AMO) for human resource research, this study aims to examine how organizational system-level (i.e. the high-performance work system (HPWS)) and individual-level AMO affect employees' performance. Specifically, this paper proposes that employee task performance is resultant from the integration of system- and individual-level AMO factors with employee contextual performance.Design/methodology/approachA survey design is employed with data collected from 250 employees working in New Zealand's service sector.FindingsThis study finds both organizational system (HPWS) and individual AMO dimensions have positive associations with employees' performance. At the system level, the supportive role played by contextual performance is highlighted with pro-social behaviors fully mediating the relationship between the HPWS and task performance. At the individual level, contextual performance is found to partially mediate the relationship between ability and task performance and fully mediate the relationship between motivation and task performance. Opportunity, on the other hand, is significantly associated with task but not contextual performance.Originality/valueIn acknowledging there are a plurality of factors that impact performance, this study enriches our understanding of AMO's influence in the context of people management.

Statistical Methods in Human Resource Research: Dearth or Diversity? Evidence from Published Literature

This article attempts to find out if there is breadth in application of quantitative techniques in published literature within the field of human resource management (HRM). In addition, it investigates the holistic use of specific categories of statistics, and if there are categories that are neglected. The study utilises a combination of research questions and hypotheses. The broad categories of statistics that this study focussed on include descriptive, data science statistics, exploratory graphical, advanced statistics such as structural equation modelling, Bayesian statistics and inferential statistics. It goes further to study application of machine learning statistics in HRM research. Using archival methodology, the article utilises a sample of 120 journal papers to answer formulated research questions and hypotheses. Descriptive statistics, exploratory graphical analysis and inferential statistics are used in the analysis. The findings indicate that there are neglected statistics in HRM research. Overall, most statistical categories are underutilised. HRM journal editors, researchers and practitioners must stock HRM methodological toolbox.

Research in nonprofit human resource management from 2015 to 2018

PurposeThis paper systematically reviews the past four years of research on human resource management (HRM) in nonprofit organizations (NPOs) to better understand: (1) recent theoretical and empirical developments and where scholarship in the field is headed (i.e. trends); (2) what topics and findings are especially important to understanding how the thought and practice of nonprofit HRM differs from that in public and for-profit organizations (i.e. insights); and (3) what gaps exist in current knowledge and scholarship and some real-world, practice-driven developments in people management that illuminate promising future research directions (i.e. opportunities).Design/methodology/approachSixty-seven peer-reviewed journal articles covering the period 2015–2018 were identified using a university library database search, as well as by-hand searches through every issue of 22 nonprofit and 36 human resources-related journals during the four-year period.FindingsThe findings highlight strong continued interest by scholars in a wide range of nonprofit HRM issues, coverage of these issues by a worldwide network of researchers who bring global perspectives and contexts to the study of nonprofit HRM, and rich theoretical and methodological diversity. Yet, compared with the universe of possible human resource topics and several leading-edge developments in organizations and societies that might affect the way people are managed in nonprofits, the paper uncovers gaps in the most recent knowledge base.Originality/valueThe paper creates a compilation of the most recent nonprofit human resource research to be used as a tool for scholars, students, and practitioners for many years to come.

Measuring the use of human resources practices and employee attitudes

Purpose – The purpose of this paper is to introduce a new data source available for researchers with interest in human resources management (HRM) and personnel economics, the Linked Personnel Panel (LPP). Design/methodology/approach – The LPP is a longitudinal and representative employer-employee data set covering establishments in Germany and a subset of their workforce and is designed for quantitative empirical human resource research. Findings – The LPP employee survey applies a number of established scales to measure job characteristics and job perceptions, personal characteristics, employee attitudes towards the organization and employee behaviour. This paper gives an overview of both the employer and employee survey and outlines the definitions, origins, and statistical properties of the scales used in the individual questionnaire. Practical implications – The paper describes how researchers can access the data. Originality/value – First, the data set combines employer and employee surveys that can be matched to each other. Second, it can also be linked to a number of additional administrative data sets. Third, the LPP covers a wide range of firms and workers from different backgrounds. Finally, because of its longitudinal dimension, the LPP should facilitate the study of causal effects of HRM practices.

Research in Medicine: Essentials for Developing Countries

(Extract) The well-being has been the highest topic for humanity throughout the adventure of mankind on the earth. Therefore, extensive efforts have been performed on the science of medicine, and glorious advances have been gained especially in the last two centuries. Research is essential for medicine to develop new therapeutic methods and to monitor the results of the current treatment given to the patient. These are possibly the simplest reasons for investigations in medicine. On the other hand, qualified human resource, research ethics, financial supports, regular data recording and analysis, and publication are important issues for improvement of the medical researches in the developing countries.

Towards a methodology to assess organizational learning capability

PurposeThe present study aims to revalidate a measurement scale for organizational learning capability in the context of university faculty members. This is a particularly relevant context because it deals with knowledge‐intensive services. Following Chiva et al., organizational learning capability was conceptualized as a second factor construct including five dimensions: experimentation, risk taking, interaction with the external environment, dialogue and participative decision making.Design/methodology/approachData were collected from the Instituto Tecnológico de Costa Rica, a leading university in Costa Rica. The survey was addressed to faculty members. A total of 795 valid questionnaires were obtained. Using confirmatory factor analysis, the construct measurement model was tested and the scale was validated.FindingsThe results show the internal consistency and the satisfactory factorial structure of the scale within the context of knowledge‐intensive services.Originality/valueThis validation of organizational learning capability measurement instruments has considered cultural differences (Spain vs Costa Rica), sectorial differences (industrial vs services), and the different educational background distribution of the sample. Another contribution of our study is the consideration of the non‐independence of observations through the complex Mplus method, since the samples in human resource research are affected by multilevel influences.