Smart maintenance : instrument development, content validation and an empirical pilot

Purpose: Scholars and practitioners within industrial maintenance management are focused on understanding antecedents, correlates and consequences of the concept of “Smart Maintenance,” which consists of the four dimensions, namely, data-driven decision-making, human capital resource, internal integration and external integration. In order to facilitate this understanding, valid and reliable empirical measures need to be developed. Therefore, this paper aims to develop a psychometric instrument that measures the four dimensions of Smart Maintenance. Design/methodology/approach: The results from two sequential empirical studies are presented, which include generating items to represent the constructs, assessment of content validity, as well as an empirical pilot test. With input from 50 industrial experts, a pool of 80 items that represent the constructs are generated. Thereafter, using data from 42 industrial and academic raters, the content validity of all items is assessed quantitatively. Finally, using data from 59 manufacturing plants, the dimensionality and factor structure of the instrument are tested. Findings: The authors demonstrate content validity and provide evidence of good model fit and psychometric properties for one-factor models with 8–11 items for each of the four constructs, as well as a combined 24-item four-factor model. Originality/value: The authors provide recommendations for scholarly use of the instrument in further theory-testing research, as well as its practical use to assess, benchmark and longitudinally evaluate Smart Maintenance within the manufacturing industry.