Predictive performance models in the South African Business Process Services industry

SA Journal of Industrial Psychology ISSN: (Online) 2071-0763, (Print) 0258-5200 Page 1 of 16 Original Research Predictive performance models in the South African Business Process Services industry Authors: Chris T.G. Jacobs1 Gerhard (Gert) Roodt1 Affiliations: 1 Department of Industrial Psychology and People Management, College of Business and Economics, University of Johannesburg, South Africa Corresponding author: Chris Jacobs, Dates: Received: 17 Oct. 2017 Accepted: 16 Oct. 2018 Published: 20 Feb. 2019 How to cite this article: Jacobs, C.T.G. & Roodt, G. (2019). Predictive performance models in the South African Business Process Services industry. SA Journal of Industrial Psychology/SA Tydskrif vir Bedryfsielkunde, 45(0), a1493. https://doi.org/ 10.4102/sajip.v45i0.1493 Copyright: © 2019. The Authors. Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License. Orientation: An earlier systematic literature review study (Jacobs & Roodt, 2011) conducted on research in Business Process Services (BPS) industry sector companies identified a number of variables that could be empirically linked to turnover intention and individual performance. The literature pointed to a potential health promotion process, as well as an individual performance process in the BPS environment. Research purpose: The purpose of this study is to test two different predictive models that may explain two distal outcomes, namely turnover intention and individual employee performance, in the South African (SA) BPS industry. Motivation for the study: There is little, if any, peer-reviewed, empirical research available on the BPS industry that links variables to either proximate or distal outcome variables, such as turnover intention and individual employee performance. Research approach/design and method: A two-stage, census-based sampling approach was followed that initially targeted 40 organisations within the industry that employ about 13000 employees. Sixteen of these organisations (employing about 6800 individuals) indicated that they wish to voluntarily participate in the study; 821 individuals were targeted to participate in the cross-sectional survey and 487 usable responses were obtained (a 59% response rate). Multivariate data analyses were conducted from an exploratory perspective to retrospectively explain relationships in the structural models. Main findings: An overall health promotion process model that predicted the distal outcome, turnover intention, was confirmed within the context of this exploratory study, where human resource management (HRM) practices, job demands (JDs) and job resources (JRs) were related to burnout as the only proximate outcome. On the other hand, an individual performance enhancing process model was also confirmed within the context of this exploratory study by using HRM practices, JRs and JDs, together with proximate variables, such as employee competence and engagement, to explain the distal outcome, individual performance. Practical/managerial implications: The study has implications for executive (strategic) management, human resource (HR) professionals and work unit team leaders in the BPS industry. This study shows which JRs contribute towards the reduction of burnout and turnover intention in the BPS context. On the other hand, it explains how HRM practices, as well as JRs and JDs, in combination with employee competence and engagement, can be used to promote individual performance. Contribution/value-add: This is the first SA study that uses a range of variables in a multivariate analysis to predict turnover intention and individual performance in the SA BPS industry. Introduction Business Process Services (BPS) is an umbrella term that describes an industry sector that includes a number of different types of business activities, such as contact centre services (CCS) – or more commonly known as call centres, information technology outsourcing (ITO), knowledge process outsourcing (KPO) and shared service centres (SSCs) (Frost & Sullivan Consulting, 2009). In South Africa, the BPS industry is a relatively new sector (Dimension Data, 2008) and is focused on performing ‘… a business process activity either in full or in part’ (Engman, 2007, p. 8). Read online: Scan this QR code with your smart phone or mobile device to read online. In the BPS industry, the increase of adverse consequences, such as decreased customer satisfaction levels, lower contact resolution rates, higher employee attrition and absenteeism has been noted (Dimension Data, 2008, 2014). These trends are indicative of the need for a better predictive ability http://www.sajip.co.za Open Access Page 2 of 16 at managing human capital in BPS environments (Fitz-Enz, 2009). Drivers of the aforementioned consequences are often quoted to be a work environment of a more technological, product- and information-overload nature. Customer expectations demand increasingly more complex business transactions across omni-communication channels with a resulting emphasis on higher employee skill sets requirements (Aksin, Armony, & Mehrotra, 2007). Extreme work pressures and overly controlled and monitored work environments resulted in these environments often being labelled as ideally suited for ‘panopticon control’ (Banks & Roodt, 2011). Against this backdrop, Jacobs and Roodt (2011) conducted a systematic literature review in order to identify variables that were empirically related to BPS performance. The literature pointed to a potential health promotion process, as well as an individual performance process. Eight human capital predictive constructs were identified that empirically related to turnover intention and/or employee performance. These key constructs are human resource management practices, job demands (JDs), job resources (JRs), employee competence, employee engagement, person–environment fit (P–E fit), employee well-being and burnout. To date, no South African (SA) study could be found that integrated these variables into a comprehensive (multivariate), predictive, empiricallytested model. The main objective of the study will therefore be to investigate a human capital predictive model of turnover intention and employee performance in the BPS industry. The two research objectives flossing for the main objective are: • to establish if HRM practices, JRs and JDs, in combination with proximate variables (well-being, burnout and engagement), predict the distal outcome, turnover intention • to establish if HRM practices, JRs and JDs, in combination with proximate variables (P–E fit, employee competence and engagement), predict the distal outcome, individual performance. The importance and relevance of the study are twofold: Firstly, it will identify which variables contribute independently or interactively to proximate outcomes (such as engagement, burnout, well-being, P–E fit and employee competence) and distal outcomes (such as turnover intention or indivi (...truncated)