{"title":"The employee-related antecedents of work performance: exploring a three-sided model for Human Resources Management","authors":"Filippo Ferrari","doi":"10.1108/bpmj-12-2023-0946","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This research paper aims to integrate the employee-related factors that empirical literature considers antecedents of performance (skills, work motivation, personal characteristics) into a multiple linear regression model, and to test such a model in order to measure the level of each individual factor on the performance.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>Quantitative, multisource research approach. After testing the validity of the model with a Confirmatory Factor Analysis, this research applies the multiple linear regression model Work performance = a(Skills) + b(Work Motivation) + c(Personal Characteristics) + e(constant) to two different samples of workers: chemical technicians (<em>N</em> = 63) and salespeople (<em>N</em> = 61).</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>This study confirms the factorial structure of the antecedents of work performance, showing that skills, motivation, and personal characteristics are three general employee-related factors underlying work performance. The statistical analysis highlights a variance in performance between 40 and 65% explained by employee-related factors, hence leaving 35–60% as due to factors outside the model (firm/environment-related and/or job-related factors, or other skills and personal characteristics not considered in the model). The study also highlights that employee-related factors sometimes affect performance differently than job designers' expectations, and sometimes even negatively.</p><!--/ Abstract__block -->\n<h3>Research limitations/implications</h3>\n<p>The equation was tested on two case studies, so further explorations are needed. Furthermore, the approach adopted is inductive thus describing performance as it is, not as it should be. Therefore, it explains the best actual performance of workers, not the ideal performance.</p><!--/ Abstract__block -->\n<h3>Practical implications</h3>\n<p>The equation tested here represents a simple and valid tool to guide many Human Resource Management practices, such as; selection, training, development, and career orientation.</p><!--/ Abstract__block -->\n<h3>Social implications</h3>\n<p>Findings provide a valid indication for designing and managing human resource management systems more even-handedly, from an organizational and employee point of view. In doing so, it drives organizations towards a better Person/Job fit.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>The study represents one of the first attempts to take into consideration multiple factors simultaneously in explaining work performance.</p><!--/ Abstract__block -->","PeriodicalId":47964,"journal":{"name":"Business Process Management Journal","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Business Process Management Journal","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/bpmj-12-2023-0946","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
This research paper aims to integrate the employee-related factors that empirical literature considers antecedents of performance (skills, work motivation, personal characteristics) into a multiple linear regression model, and to test such a model in order to measure the level of each individual factor on the performance.
Design/methodology/approach
Quantitative, multisource research approach. After testing the validity of the model with a Confirmatory Factor Analysis, this research applies the multiple linear regression model Work performance = a(Skills) + b(Work Motivation) + c(Personal Characteristics) + e(constant) to two different samples of workers: chemical technicians (N = 63) and salespeople (N = 61).
Findings
This study confirms the factorial structure of the antecedents of work performance, showing that skills, motivation, and personal characteristics are three general employee-related factors underlying work performance. The statistical analysis highlights a variance in performance between 40 and 65% explained by employee-related factors, hence leaving 35–60% as due to factors outside the model (firm/environment-related and/or job-related factors, or other skills and personal characteristics not considered in the model). The study also highlights that employee-related factors sometimes affect performance differently than job designers' expectations, and sometimes even negatively.
Research limitations/implications
The equation was tested on two case studies, so further explorations are needed. Furthermore, the approach adopted is inductive thus describing performance as it is, not as it should be. Therefore, it explains the best actual performance of workers, not the ideal performance.
Practical implications
The equation tested here represents a simple and valid tool to guide many Human Resource Management practices, such as; selection, training, development, and career orientation.
Social implications
Findings provide a valid indication for designing and managing human resource management systems more even-handedly, from an organizational and employee point of view. In doing so, it drives organizations towards a better Person/Job fit.
Originality/value
The study represents one of the first attempts to take into consideration multiple factors simultaneously in explaining work performance.
期刊介绍:
Business processes are a fundamental building block of organizational success. Even though effectively managing business process is a key activity for business prosperity, there remain considerable gaps in understanding how to drive efficiency through a process approach. Building a clear and deep understanding of the range process, how they function, and how to manage them is the major challenge facing modern business. Business Process Management Journal (BPMJ) examines how a variety of business processes intrinsic to organizational efficiency and effectiveness are integrated and managed for competitive success. BPMJ builds a deep appreciation of how to manage business processes effectively by disseminating best practice. Coverage includes: BPM in eBusiness, eCommerce and eGovernment Web-based enterprise application integration eBPM, ERP, CRM, ASP & SCM Knowledge management and learning organization Methodologies, techniques and tools of business process modeling, analysis and design Techniques of moving from one-shot business process re-engineering to continuous improvement Best practices in BPM Performance management Tools and techniques of change management BPM case studies.