Impact of soft TQM practices on employee work role performance: role of innovative work behaviour and initiative climate

Author:

Vihari Nitin SimhaORCID,Yadav MohitORCID,Panda Tapan KumarORCID

Abstract

PurposeThe purpose of this paper is to investigate the effect of soft total quality management (TQM) practices on employee work role performance in the manufacturing sector of United Arab Emirates. It also examined the indirect effect of innovative work behaviour and initiative climate.Design/methodology/approachThe study is based on a conclusive research design and survey data was collected from 290 employees working in non-managerial positions across various manufacturing companies in UAE. The hypotheses of the empirical study are tested using structural equation modelling. The indirect effects created through moderated mediation are analysed using Hayes Process Macro.FindingsThe results show that soft TQM practices have a positive influence on work role performance. Employee innovative work behaviour acts as a partial mediator and initiative climate moderates the relationship.Research limitations/implicationsThe study adopted a cross-sectional analysis and single informants are used, so it is advised that the interpretation of the results is made with enough caution.Practical implicationsPractitioners must bear in mind that when the employees are adequately trained, empowered, involved and organized as team, it would result in employee innovative behaviour and improved work role performance. The top management should be persuaded to be more committed to the above-mentioned activities for more positive employee-level outcomes.Originality/valueVery few studies have conducted an empirical validation at the intersection of human resource management (HRM) and TQM. This is one of the first studies to examine the relationship between soft TQM and employee work role performance.

Publisher

Emerald

Subject

Strategy and Management,General Business, Management and Accounting,Business and International Management,General Decision Sciences

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