Unit of Analysis in Digitally-Enabled Electronic Procurement Research: A Literature Analysis

Unit of Analysis in Digitally-Enabled Electronic Procurement Research: A Literature Analysis

Md Mahbubur Rahim, Maryam Jabberzadeh, Nergiz Ilhan
DOI: 10.4018/978-1-7998-5171-4.ch005
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E-procurement systems that have been in place for over a decade have begun incorporating digital tools like big data, cloud computing, internet of things, and data mining. Hence, there exists a rich literature on earlier e-procurement systems and advanced digitally-enabled e-procurement systems. Existing literature on these systems addresses many research issues (e.g., adoption) associated with e-procurement. However, one critical issue that has so far received no rigorous attention is about “unit of analysis,” a methodological concern of importance, for e-procurement research context. Hence, the aim of this chapter is twofold: 1) to discuss how the notion of “unit of analysis” has been conceptualised in the e-procurement literature and 2) to discuss how its use has been justified by e-procurement scholars to address the research issues under investigation. Finally, the chapter provides several interesting findings and outlines future research directions.
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Electronic procurement (E-procurement) represents a key area of e-commerce (EC) discipline (Barua et al., 2001; Gunasekaran et al., 2009). Although e-procurement systems emerged in early 2000 with the proliferation of the Internet, but in recent years these systems have begun incorporating more advanced digital tools (Srai & Lorentz, 2019). Hence, they are also known as digital procurement or digitally enabled e-procurement systems. The importance of such systems is highly recognised in the e-commerce literature due to two reasons. First, e-procurement is considered as the starting point for many organisations’ overall e-commerce strategy (Chang et al., 2004). Second, e-procurement systems focus on automating and improving procurement process that is regarded as one of the most critical functions of supply chain (Novack & Simco, 1991). Given its importance, considerable research attention has been given by scholars to investigate various issues associated with e-procurement systems. Hence, there currently exists a rich body of literature on e-procurement as acknowledged by scholars like Rahim & As-Saber (2011).

Existing e-procurement literature typically addresses several key issues (e.g. cost savings, partner relationship, transparency, effectiveness of ordering process) associated with the stages (i.e. adoption, implementation, post-implementation) of e-procurement systems life cycle. However, one critical issue that has so far received scarce research attention is: “unit of analysis”. This represents an important methodological concern for e-procurement research context that has largely been ignored by e-procurement researchers. In particular, it is not clearly known how the choice of an appropriate “unit of analysis” is justified by e-procurement researchers in order to address various research questions posed by them. Addressing this research gap is important because e-procurement involves multiple stakeholders having different motives (Rahim & Kurnia, 2014). This in turn requires attention to define a “unit of analysis” appropriate to address the research issues under investigation for e-procurement context. Hence, the purpose of this book chapter is to discuss how the notion of “unit of analysis” has been conceptualised in the e-procurement literature. This purpose is addressed in terms of the following two specific research questions:

  • 1.

    What units of analysis are generally reported in the literature for e-procurement context?

  • 2.

    What issues are generally considered by the researchers when choosing an appropriate unit of analysis for their e-procurement research context?

These research questions are addressed by undertaking a systematic literature analysis on e-procurement. A total of 116 articles, from peer-reviewed journals, addressing various aspects of e-procurement have been identified from multiple streams of literature (e.g. information systems, e-commerce, management, supply chain management), and then were subsequently analysed. Based on a critical analysis, this chapter reports two key findings concerning the use of “unit of analysis” for e-procurement research context. First, an overwhelming majority of studies (i.e. 84 out of 116 articles, representing 72%) make no explicit reference to “unit of analysis”. Second, out of those 32 articles that explicitly report choosing a “unit of analysis” suitable for e-procurement research context, a slight majority (19 out of 32 articles representing 59%) have provided a clear explanation in support of choosing “unit of analysis” that merit discussion.


Background Literature

  • Definitions and Attributes of Unit of Analysis: A review of literature on “unit of analysis” indicates the existence of multiple definitions (Table 1) that have commonly been cited in the EC and IS literature streams. These definitions are either proposed by some IS/EC scholars (Shanks et al., 2012), or borrowed by them from other disciplines (e.g. social science).

Key Terms in this Chapter

Unit of Analysis: Treated as a “thing” or “phenomenon” or “subject of research interest” that is being discussed.

Methodology: A research approach (qualitative, quantitative, hybrid) that is adopted to empirically evaluate a research model to find answers.

E-procurement: Represents a class of software systems that can automate the key tasks involved in procurement process.

Generalisability: The applicability of research findings from one context to another.

Research Boundary: Represents the scope that is outside a research investigation.

Systematic Literature Review: An approach that synthesises prior theoretical as well as empirical evidence on a research issue.

Value: Represents a positive outcome that emerges as a result of e-procurement implementation.

Digital Procurement: An e-procurement system that includes advanced digital tools like Internet of Things, data mining, and cloud computing to automate and further streamline procurement process.

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