This study explores the issue of drivers of service employee behaviour and performance, as antecedents of customer experiences that constitute key strategic outputs for service organizations. A proposed new construct, Engagement Climate, was developed and put forth as the "behavioural foundation" that the Service Climate model needs in the prediction of service employee behaviour and performance. The construct stems from the interpretation of engagement as an affect-based motivational process, and from the conceptualization of its antecedents as a specific type of psychological climate. Engagement Climate comprises a set of affectively charged psychological perceptions of the work environment, or engagement climate dimensions, which are conducive to the experience of engagement, a motivational state that triggers the investment of personal resources into the job role. Engagement Climate, as a latent social psychological construct, should virtually transcend the context of any one organisation or sector. However, given the nature of service work, Engagement Climate may most readily be observed (and fostered) in the context of services, in particular among front-line employees.The empirical study, consisting of a cross-sectional statistical survey, aimed to develop and pilot-test a questionnaire measure of Engagement Climate and to investigate its factor structure within a service organization. Data were collected from a total of 544 travel agents from a leading travel group in Spain. The factorial validity of the model comprising ten dimensions, namely Autonomy, Supervisor support, Clarity, Cohesion, Fairness, Trust, Challenge, Recognition, Self-expression, and Overload, was demonstrated using confirmatory factor analyses (CFA). The scale and subscales comprising the measurement model all showed good internal consistency and reliability values. Also, the hypothesized direct effects of engagement climate on personal engagement, as well as the relatively weaker effect of engagement climate on job satisfaction, were both confirmed using structural equation modelling (SEM).
|Date of Award||16 Feb 2017|
- University Of Strathclyde
|Supervisor||Thomas Baum (Supervisor) & Dora Scholarios (Supervisor)|