CHAPTER 3 RESEARCH MODEL AND HYPOTHESES
3.2 The Research Model of the Study
The aim of this section is to present and to justify the overall research model of my study. The research model is based on the high-level model introduced in Chapter 1 (see Figure 1-2 in section 1.4).
The dependent variables (representing the extent of e-procurement use) were the breadth of e-procurement use (the range of e-procurement forms and functionalities used within the organisation, see Figure 2-1 for a descriptive model of forms of e- procurement) and the depth of e-procurement use (the extent to which the organisation relies on e-procurement). The content of the breadth of e-procurement use construct was defined to address research question one (see section 1.3 for the research questions of my study) and, thus, to account for both the information and the transaction perspectives and to include all of the forms of e-procurement identified in the literature review (see Figure 2-1). The dependent variables are discussed in detail in section 3.3.
To address research question two (see section 1.3), factors hypothesised to affect breadth and depth of e-procurement use (the determinants of breadth and depth) were included in the model. The choice of the determinants was based on technology- organisation-environment (TOE) framework (introduced in section 2.6), diffusion of innovation (DOI) theory (introduced in section 2.6), and on the results of prior studies of factors affecting e-procurement adoption and use, summarised in section 2.7.7.
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Even though a broad range of theories are relevant to understanding the determinants of the extent of e-procurement use by organisations (as discussed in section 2.6), TOE framework and DOI theory are the most widely validated in prior studies of technology adoption and use. (Al-Qirim, 2005, Prescott, 1995, and Zhu, Dong, Xu, et al., 2006, explicitly recommended combining TOE framework with DOI theory to formulate models of technology adoption and use by organisations.)
Based on DOI theory, relative advantage, compatibility, and complexity were included as factors from the technological context. All factors found in prior studies to affect e-procurement adoption and use (listed in section 2.7.7) were considered for inclusion in the model. (I adopted a view that e-procurement use is the outcome of a large number of adoption decisions, and, therefore, considered factors found to affect adoption along with factors found to affect breadth and depth.) Care was taken to keep the model as parsimonious as possible, and not to include redundant factors.
Perceived benefits are synonymous with relative advantage, the existing practice of relying on information technology infrastructure makes current practices more compatible with the practice of using e-procurement, and high implementation costs are likely to be associated with complex systems (see section 2.7.7.1 for a discussion of perceived benefits, information technology infrastructure, and perceived implementation costs). Therefore, perceived benefits were judged to be covered by relative advantage, information technology infrastructure by compatibility, and perceived implementation costs by complexity. Consequently, to keep the research model parsimonious, perceived benefits, information technology infrastructure, and perceived implementation costs were not added to the model as separate factors.
Organisational learning ability and information sharing culture at the level of the organisation are related to employee knowledge (Hong & Kuo, 1999; Lin, 2007). Therefore, they were not added as separate factors. Information sharing at the level of the supply chain was found to be poorly understood in prior literature and presented considerable challenges in terms of research design (such as deciding which organisations belong to a supply chain and sampling from the population of supply chains); therefore, I judged addressing information sharing at the level of the
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supply chain to be not feasible in view of the resource limitations of my study. Employee knowledge was added as a factor from the organisational context, along with top management support.
Normative pressures, extent of adoption among competitors, and business partners’
influence were accounted for by a single factor from the environmental context, external pressure (following the approach taken by Grandon and Pearson, 2004, in their study of e-commerce adoption in small and medium US businesses). Partner readiness was added as a separate factor from the environmental context.
Thus, all of the contexts of the TOE framework were covered in the model.
Table 3-1 Factors Included in the Research Model
Factor included in the model Related factors found to have effect in prior studiesa Technological context
Relative advantage Perceived benefits
Compatibility Information technology infrastructure
Complexity Perceived implementation costs
Organisational context Top management support Top management support
Employee knowledge Organisational learning ability, employee knowledge and skills, information sharing culture
Environmental context Partner readiness Trading partner readiness
External pressure Normative pressures, extent of adoption among competitors, business partners’ influence
a
Factors found to have effect on e-procurement adoption or use in prior studies (and thus, listed in section 2.7.7) and accounted for in the model. Firm size and industry were found to have effect in prior studies, but were not included in the model because the study focused on firms in a limited size range (small and medium enterprises) and in a single industry (manufacturing).
Firm size and industry were not added to the model; my study focused on a single industry (manufacturing) and on organisations in a limited size range (small and medium organisations). Therefore, it was not expected that these factors would have effect for the population addressed in my study (see sections 4.3.3 and 4.3.4 for a description of the population and of the sample, respectively).
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The factors included in the model (listed in Table 3-1) are summarised and related to the factors suggested by the literature review in Table 2-10. The resulting research model is given in Figure 3-1. I found little grounds in the prior literature or in relevant theories to clearly differentiate factors contributing to breadth of e- procurement use from factors contributing to depth of e-procurement use. Therefore, the research model was structured similar to the research model by Wu et al. (2007); all determinants were hypothesised to affect both the breadth and the depth of e- procurement use. H2 H7 H6 H5 H4
H3 Extent of e-procurement use
ENVIRONMENT ORGANISATION TECHNOLOGY Relative advantage Compatibility Complexity
Top management support Employee knowledge External pressure Breadth of e-procurement use Depth of e-procurement use Partner readiness H1
Figure 3-1. The research model.
To further justify the research model presented in Figure 3-1 and to explore its meaning, the content of the dependent variables, the breadth of e-procurement use and the depth of e-procurement use, is elaborated in section 3.3. The content of the determinants is further elaborated and the individual hypotheses are justified one-by- one in section 3.4.
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