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Based on the theory testing process, this research identifies the constructs or variables for the survey research, including their respective operational definitions. Generally, variables identified in a theoretical model provide an insight into the research problem and represent the aspect of the problem that the study aims to explain (Bryman, 2016; p151). The definitions of variables are critical to develop meaningful measurements of concepts within the theoretical model. Because of the emphasis on rigorous statistical tests in quantitative studies, the definitions of variables also need to be developed clearly and formally (Wacker, 2004).

Based on the theoretical model in Figure 4-3, four main variables are identified for this study. They are Cyber-Physical Systems (CPS), Operational Performance (OP), Operational Capabilities (OC), and Advanced Manufacturing Capabilities (AMC).

Table 4-6 describes their nominal definitions for the context of this research.

Cyber-Physical Systems (CPS) is defined as “automated systems that enable connection of the operations of the physical reality with computing and communication infrastructures” (Jazdi, 2014; p2). This definition emphasises the integration of computational systems with physical processes, either by machines or humans.

Variables Nominal Definitions Cyber-Physical

Systems (CPS)

• “Automated systems that enable connection of the operations of the physical reality with computing and communication infrastructures” (Jazdi, 2014; p2).

• This research uses the term “CPS adoption” to refer to the extent-of-use of CPS elements including tools, equipment, systems, techniques, and methodologies; and its implementation or installation into specific manufacturing process flows for their proper intended use.

• For clarity, this research refers to “technology adoption”, “technology implementation”, and “technology use” collectively (Das & Nair, 2010).

Operational Performance (OP)

The outcome of operational activities undertaken by firms that relate to changes in cost, quality, delivery, and flexibility (Ahmad & Schroeder, 2003).

Operational Capabilities (OC)

“The capacity of an organization to purposefully bundle its resource base in ways that enable the organization to perform the ongoing task of transforming inputs into outputs” (Coltman & Devinney (2013; p557) citing Helfat et al. (2007)).

Advanced Manufacturing Capabilities (AMC)

Advanced manufacturing technologies (AMT) refer to the combination of computer-based systems and production techniques that are

implemented and integrated into the firm’s manufacturing processes (Boyer et al., 1997; Kotha & Swamidass, 2000, Swink & Nair, 2007). Thus, AMC refers to a firm’s ability to perform tasks and activities over the long term by utilising AMT.

Table 4-6: Variables in this study and their respective nominal definitions

As an independent variable, CPS denotes the extent of CPS technology adoption, whereby technology adoption refers to “the stage in which a technology is selected for use by an individual or an organization” (Sharma & Mishra (2014; p18) citing Carr Jr. (1999)). The scope of technology adoption for this research includes “technology implementation” and “technology use” (Das and Nair, 2010), to emphasise the extent of actual use of technology, and not merely acquisition and possession. Additionally, because CPS adoption has not been studied extensively in OM research, the scope of CPS adoption for this study also draws references from research on the extent of investment in AMT (Boyer, 1997; Jonsson, 2000) and the extent of use of AMT (Snell & Dean, 1992; Small, 1999).

Thus, CPS adoption refers to the procurement of CPS elements including tools, equipment, systems, techniques, and methodologies; and its implementation or installation into specific manufacturing process flows for their proper intended use.

This study infers that the characteristics and challenges of CPS adoption are similar to that of AMT adoption.

The dependent variable Operational Performance (OP) subscribes to the notion that performance success indicators can be in the form of changes in competitive capabilities targets involving cost, quality, delivery, and flexibility (Ahmad & Schroeder, 2003). These targets represent the outcome of operational activities undertaken by firms and have been used in various empirical studies. For instance, Devaraj et al. (2007) identifies operational performance as a construct focusing on cost, delivery, and flexibility, while McAffee (2002) applies delivery and flexibility to define the operational performance construct for his research. Whereas, Machuca et al. (2011) employs unit cost of manufacturing, on-time delivery performance, and flexibility in changing product mix, and Prajogo and Olhager (2012) use speed of delivery and production costs as two of the components of the operational performance construct.

The theoretical model for this research combines Operational Capabilities (OC) and Advanced Manufacturing Capabilities (AMC) as a moderating variable. OC in particular, refers to a firm’s capacity to bundle its resources to “enable the organisation to perform the ongoing task of transforming inputs into outputs” (Coltman & Devinney (2013; p557) citing Helfat et al. (2007)). Because operational capabilities have been identified in literature as embedded in combinations of employee skills, facilities and equipment, processes and routines, as well as administrative synchronisation (Teece, 2014), they infer the significance of human skills to manage all the said components.

Meanwhile, Advanced Manufacturing Capabilities (AMC) is applied in the theoretical model to denote a specific reference to a firm’s ability to perform tasks and activities over the long term by utilising AMT.

AMT is described in empirical studies as computer-based systems and manufacturing techniques that are implemented to improve production operations (Suresh & Meredith, 1985; Small & Chen, 1995; Small, 1999; Kotha and Swamidass, 2000, Swink & Nair, 2007; Chung & Swink, 2009). Because AMT has featured prominently in literature focusing on improving firms’ manufacturing

processes since the late 1980s, firms are said to have developed the experience in developing the corresponding advanced manufacturing capabilities (Goyal & Grover, 2012). Therefore, AMC is also recognised in the theoretical model as the result of past technology adoption undertaken by firms.