Green Service: Construct Development and Measurement Validation

Abstract

Facing the growing concern of environmental impact, green service (GS) has emerged as an important research topic in production and operations management. However, empirical research on GS is hindered by the lack of theoretically developed and empirically validated measurement scales covering various practices in service operations of a supply chain. GS indicates the strategic orientation of firms in developing a combination of practices and routines to reduce environmental impact in service operations that span from product development to servicing customers. Grounded in the natural resource‐based view (NRBV), this study conceptualizes GS from the supply chain perspective and in the consumer‐product context to develop a GS measurement model. Collecting secondary and primary data in both qualitative and quantitative forms, this study reports the development of GS multi‐item measurement scales using a multi‐method research design that combines interviews, content analysis, and mass survey. GS is operationalized as a multi‐dimensional construct reflecting three complementary dimensions, namely pollution prevention‐, product‐, and long‐term development‐oriented GS practices, where each of them comprises three sub‐dimensions, resulting in a total of 34 measurement items. The empirically validated scales can be used to advance theory and practices of GS, while providing a useful reference for firms to evaluate their GS efforts, and identify areas for improvement.

The role of Big Data in explaining disaster resilience in supply chains for sustainability

“…Consistent with the call for innovative sources of data and prior environmental and operations management literature (Tate et al, 2010;Chan et al, 2015), a qualitative content analysis is a useful method to identify disaster resilience antecedents for sustainability in real life practices from accessible documents and communication materials (Boyer and Swink, 2008). This approach has helped us to overcome the limitations of literature review and in-depth interviews with experts by improving the generalizability of the measurement scales (Chan et al, 2015).…”

Multi‐Methodological Research in Operations Management

“…Chan et al. () applied MMA to theoretically develop and empirically validate the measurement of green service (GS). Their research approaches included exploratory cases (interviews), content analysis of industrial documents, and QE studies based on survey data.…”

Examining top management commitment to TQM diffusion using institutional and upper echelon theories

“…Company information was extracted from two databases: the ACMA (Automotive Components Manufacturers Association of India) and Dun & Bradstreet. Following prior studies (Bowen et al 2001;Menor and Roth, 2007;Chan et al 2016), a package containing the structured questionnaire, a cover letter explaining the research, and a self-addressed pre-paid envelope were mailed to the senior quality manager at each auto-component manufacturing organisation that has adopted TQM in some way (as uncovered via our initial background research and selection of participants).…”

“…Secondary data were collected from annual reports for those organisations comprising our sample frame. This strategy has helped us: (i) overcome the limitations of the reported literature and in-depth interviews by improving the generalizability of the measurement scales; and (ii) reduce key informant bias and common method bias (see Roth, 2007;Chan et al 2016). Table 2 were measured on a five-point Likert scale with anchors ranging from strongly disagree (1) to strongly agree (5).…”