The Impact of High Performance Work Systems on Business Performance: Examining the Role of Employee Wellbeing

Abstract

This thesis has two main objectives. The first objective of this thesis is to examine employees’ experience of HPWS in their respective business units. The second objective is to develop a conceptual model that determines how these perceptions are related to their wellbeing and performance. In doing so, both the mutual gains and conflicting outcomes perspectives have been examined. In addition, POS and JDR theories are proposed as alternative theoretical perspectives in examining the pathways through which HPWS can impact on employee wellbeing and business unit level performance. Specifically, building on the notion of JDR model, job control and supervisor support have been hypothesized as important resources to minimize the negative impact of excessive job demands on wellbeing. For the purpose of analysis, data had been collected from 828 employees from 140 business units in insurance industry of Pakistan. The structural equation modeling technique is used to validate the measurement model and for examining the inter-relationships among HPWS, employee wellbeing and business unit level performance. At business unit level, the findings lend support for mutual gains perspective. The pathway linking HPWS to business unit level performance via mutual gains perspective received strong support. The empirical findings show that: (1) AMO bundles of HPWS had strong positive influence on POS; (2) Only motivation bundle was significantly and negatively related to excessive job demands while ability and opportunity bundles had no impact on excessive job demands; (3) HPWS, through POS, showed positive impact on employee wellbeing; (4) job satisfaction fully mediates the relationship between HPWS and business unit level performance. Overall, the thesis indicates that while mutual gains perspective is useful in explaining the link between HPWS-wellbeing-performance, extending theory to include new explanatory variables such as POS increases our understanding of the underlying phenomena.