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Roger Clarke's 'Research Methods for eCommerce'

Appropriate Research Methods for Electronic Commerce

Roger Clarke

Principal, Xamax Consultancy Pty Ltd, Canberra

Visiting Fellow, Department of Computer Science, Australian National University

Version of 19 April 2000

© Xamax Consultancy Pty Ltd, 1989, 1994, 1996, 1999, 2000

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The research domain of electronic commerce is particularly challenging, because of the lack of established definitions, and the high volatility of the phenomena. The urgent need for quality information presents a classic case of the need for instrumentalist research, which pursues outcomes of relevance to practitioners of the discipline, subject to the constraint of achieving sufficient rigour.


1. Introduction

Specialist journals in electronic commerce, in particular the International Journal of Electronic Commerce, and Electronic Markets, carry very few articles that directly address the question of which research methods are appropriate to this domain. This might be because textbooks are available that address the question of research methodology, and that these suffice (e.g. Emory 1985, Kervin 1992, Cooper & Schindler 1998).

Alternatively, the absence of discussion may be a sign of maturity in the information systems discipline, because there are already ample references in the I.S. literature, which are studied by doctoral candidates during their preparation for entry to the research profession. See, in particular, Ives et al. (1980), Nolan & Wetherbe (1980), Sprague (1980), Hamilton & Ives (1982), McFarlan (1984), Benbasat (1984), Mumford et al. (1985), Jenkins (1985), Galliers (1985), Culnan (1986, 1987), Culnan & Swanson (1987), Galliers & Land (1987), Alavi et al. (1989), Banville & Landry (1989), Galliers (1990, 1992a, 1992b), Orlikowski & Baroudi (1991), Nissen et al. (1991), Alavi & Carlson (1992), Galliers (1993), Benbasat & Weber (1996), Lee et al. (1997), and Mingers & Stowell (1997).

This paper is written because the author believes that any such sentiments would be exaggerated. Electronic commerce is a domain of study within various disciplines, importantly including the discipline of information systems. Many domains that are examined by I.S. specialists present serious challenges; but electronic commerce presents even more significant obstacles to the academic seeking to undertake and present high-quality research. Among these are:

The purpose of this paper is to provide a perspective on the methods that should be applied to electronic commerce research. It should aid both the assessment of articles, and the preparation of research designs.

There is a great deal of scope for terminological ambiguity in this topic. This paper uses the following terms in the following ways:

The paper commences by reviewing several different schools of thought in relation to research approaches. The challenges confronting information systems research are summarised, so that electronic commerce research can be situated within it. Important considerations in empirical research are identified, and assessment criteria suggested for a research design. Some specific instances of electronic commerce research are considered, and conclusions are drawn.

2. The Dimensions of Research Approaches

The discipline of Information Systems in general, and the research domain of electronic commerce in particular, are both crossroards at which differing approaches to research intersect.

In Clarke (1992), it was argued that information systems overlaps with both the computer science and the business clusters of disciplines; for example, software engineering and database management and some aspects of application software development are properly studied within computer science, and systems analysis and organisational behaviour within business-related disciplines.

A further distinction can be drawn, based on the motivation underlying the research. The primary distinction is between:

A further dimension of research is associated with the form of the theory on which research is based. The theory may be merely descriptive of aspects of the domain, or it may be explanatory of behaviour, or (most ambitiously), it may have predictive power. It was argued in Clarke (1997) that information systems research also has a policy dimension, which demands that some work extend even further, into prescriptive or normative mode.

Beyond these distinctions lies another fundamental difference in the manner in which research can be approached. The following section examines three separate traditions, the first two of which derive from the business disciplines, and the third from computer science and engineering.

3. Research Traditions

This section provides a brief overview of each of the three major research traditions that are evident in information systems in general, and electronic commerce in particular. They are:

The first two are business discipline approaches, and there is a fundamental tension between them. This was much debated during the 1980s and 1990s. See, in particular, Hirschheim 1985, Boland 1985, Klein & Lyytinen 1985, Turner 1990, Lee 1991, Orlikowski & Baroudi 1991, Rouse & Dick 1994, Robey 1996. By the mid-1990s, King & Appleglate (1997) argued that the debate was no longer generating useful information.

The appellations used in this paper, 'scientific' and 'interpretivist', naturally over-simplify the nature of both of them, and the distinction between them. The alternative labels 'quantitative' and 'qualitative' are often used in the literature. Those terms are properly used to describe the nature of the data that is gathered in empirical research (e.g. Van Maanen 1979, Marshall & Rosman 1984, Miles & Hubermann 1984, Cash & Lawrence 1989, Patton 1990, Myers 1997a, Lee et al. 1997). Their use to distinguish schools of thought in research is, on the other hand, quite deficent and misleading. Their use in that sense is accordingly avoided in this paper.

3.1 The Conventional Scientific Research Tradition

This section presents a simplified description of the notion of scientific method, closely akin to what Kuhn (1962, 1970) referred to as 'normal science'. It is intended as a recapitulation of key elements of a graduate unit in philosophy of science or research methods, not as a substitute for such studies.

Conventional scientific approaches to research were developed over several centuries in the context of what are now referred to as 'the physical sciences'. It has been co-opted by 'the social sciences', which can be loosely depicted as being those whose domains of study include agents that exercise free will, or at least appear to do so. Some information systems research is close to the realm of the physical sciences; but most of it sits squarely within the social sciences.

Conventional science adopts the assumption that there is a real world, comprising objects and processes. This real world cannot be directly understood by humans, nor 'captured' into human artefacts. However it can be observed. On the basis of observation of the real world, humans form theories as to how it came to be the way it is, and how and why the processes take place. In an applied discipline such as Information Systems, it is common to depend on theories borrowed from 'reference disciplines'.

Theories should ideally be expressed in deductive form, such that a set of axioms or postulates, operated on by conventional deductive logic, lead to inferences. A scientific theory, á la Popper (1959, 1968), is one which is capable of generating inferences which are, at least in principle, refutable by reference to the real world. Religious and ideological theories generally result in inferences such as "through grace, a believer is saved" (Christian liturgy) and "only a virtuous ruler can survive" (Machiavelli), which cannot be subjected to such testing. Such theories are therefore a-scientific (a term which is descriptive, and should not be interpreted as being pejorative).

In order to establish whether the theory has the capability to describe, explain, and especially to predict, the behaviour of the real world, it is necessary to construct tests of the inferences arising from a theory. Inferences are generally expressed at a conceptual level, however; for example, "experienced auditors are better judges of the extent to which substantive tests of controls should be undertaken". In order to actually perform tests, it is necessary to express them in 'operational' terms, in the form generally referred to as hypotheses, e.g. "the proportion of auditors who select the same extent of substantive testing as recommended by a panel of experts will be highly correlated with their number of years of auditing experience".

The outcomes of hypothesis testing provide feedback to the theory. If the hypotheses are not confirmed, then evidence exists that the theory may be wrong (in Kuhnian terms, this is an 'anomaly'). If the results can be reproduced by others, then at least some aspects of the theory should be regarded as refuted. If the data support the hypotheses, then there is justification for increased or sustained confidence in the theory's effectiveness, or at least continued use of the theory. As findings accumulate which support a wide range of hypotheses generated from the theory, it tends to be regarded as authoritative within some range of applicability.

Research that stops at that point is 'pure'; but it is also incestuous, because there is a risk of the ideas rattling around the abstract realm of theory, perhaps tested from time to time against the real world, but without useful implications for that world. In an instrumentalist discipline, which is how most people would regard information systems in general and electronic commerce research in particular, the outcomes of research must be demonstrated to be relevant and useful to professionals and managers as well.

Research that is based on observations of the real world is referred to as 'empirical research'. Empiricism is relevant at two points in the conventional cycle:

It is important to appreciate the role of theory. It is perfectly feasible to create hypotheses directly from a small collection of observations, without any statement of underlying principles and logical derivation of inferences. The weakness of this approach is that the outcomes of the research can merely refute, or provide conditional support for, those specific hypotheses; there is no accumulation of knowledge. On the other hand, where the hypotheses are derived from a body of theory, the results arising from the research accumulate, and can be used again by the researcher and others to flesh out knowledge.

Information Systems is an applied discipline, however, and lacks a solid body of existing theory. In practice, therefore, it is uncommon in IS to have a theory readily available. It is most common to have a partial theory that requires embellishment, and/or to co-opt a theory from a 'reference discipline' such as organisational behaviour, management accounting or computer science.

In the various reference disciplines, many theories are available. Many of them, however, were developed for purposes related at best tenuously with IS. Some which appear relevant may well prove not to be appropriate, e.g. because they are specific to a particular culture (often the U.S.A. or some part thereof), or the unit of analysis is individuals in a loose-knit community rather than individuals acting within an organisational context (e.g. Rogers' diffusion of innovations theory), or the domain to which they are applied is significantly different from that for which the theory was developed (e.g. Hofstede's theory of cultural variation).

Where no appropriate theory can be found as a basis for research, it may be necessary to undertake 'exploratory research'. This involves open-ended study, largely unguided by theory and intended to provide a new body of empirical knowledge from which theories might be able to be postulated.

The following diagram depicts that process of conventional scientific method that was described above. The button below the diagram provides an annotated animation of the flow. [Note that the animation appears in a new window, which can be closed after it has been run].

Exhibit 1: Conventional Scientific Method

In summary, conventional science consists of extracting new hypotheses from an existing theory, testing them, and adding the results to the pool of knowledge. It presupposes the existence of:

3.2 The Interpretivist Approach to Research

Conventional science is based on 'rational positivist' thought. This includes the presumptions that there is a 'real world', that data can be gathered by observing it, and that those data are factual, truthful and unambiguous. The 'post-positivist', 'interpretivist' philosophy, on the other hand, asserts that these assumptions are unwarranted, that 'facts' and 'truth' are a chimera, that 'objective' observation is impossible, and that the act of observation-and-interpretation is dependent on the perspective adopted by the observer.

Interpretivists criticise even the physical scientists for the narrowness of their assumptions. Their criticisms strike home particularly strongly in the social sciences, where the objects of study are influenced by so many factors, and are extremely difficult to isolate and control in experimental laboratory settings. See, for example, Boland (1985), Hirschheim & Klein (1994), and Walsham (1993, 1995a).

The interpretivist approach confronts the difficulties presented by the nature of the research domain, and in particular:

This leads to a requirements that multiple interpretations of the same phenomena must be allowed for, and that no truth is attainable.

A further approach, philosophically distinct but usefully dealt with here (Myers 1997a), is the 'critical theory' school of thought. This considers that a researcher is trapped within the status quo, and that research involves the surfacing of the tensions and working towards their relaxation.

3.3 The Engineering Approach to Research

Within the information systems segment of the computer science and engineering discipline, the research that is most directly relevant to electronic commerce is of an engineering rather than a scientific orientation, and is essentially concerned with technology, including artefacts, techniques and combinations of both of them.

Information systems research undertaken within this tradition tends to be applied or problem-solving in its orientation. It is of two broad types:

4. Research Techniques

Research techniques can be distinguished firstly on the basis of whether or not they are empirical, that is to say that they involve observation of the 'real world'.

Among the empirical techniques, 'scientific' techniques are distinguishable from 'interpretivist' techniques on the basis that science claims to be able to achieve a high degree of 'objectivity', in some sense such as the replicability of experiments, whereas interpretivists question whether objectivity is attainable, or even meaningful.

This section categorises research techniques into the following groups:

4.1 Non-Empirical Techniques

The following techniques are detached from real-world data. This is not to say that they are necessarily totally remote or irrelevant, but rather that they are once-removed, depending on synthetic data, or on conceptual thinking about abstractions. The primary techniques are:

4.2 Scientific Research Techniques

The following are common techniques that can be applied by information systems researchers to the electronic commerce research domain, within the scientific tradition:

A number of additional techniques may be applied within either a scientific or an interpretivist context. They are listed below.

4.3 Interpretivist Research Techniques

The following are techniques which are unequivocally interpretivist in their style:

Additional techniques, which may be applied within either a scientific or an interpretivist context, are listed below.

4.4 Research Techniques at the Scientific/Interpretivist Boundary

Several research techniques can be applied within either a scientific or an interpretivist context. In each case. there are differences in the detailed application of the technique, because work undertaken within the scientific tradition requires careful attention to the rigour with which the instrument is designed and validated, and the data is captured and analysed; whereas, in the interpretivist tradition, the focus is on openness to alternative perspectives and on the identification of ambiguities in the data and the setting.

The techniques include:

4.5 Engineering Research Techniques

Information systems research conducted within the computer science and engineering context uses two categories of research technique:

5. The Quality of IS Research

Underlying all discussions about research is the question of what quality means. This in turn depends on the objectives that are ascribed to it.

If the primary purpose of research is to increase the pool of abstract knowledge, then the criteria of quality are inherently internal, and rigour is critical. If, on the other hand, the primary purpose of research is to contribute to the practice of information systems (instrumentalism), then the criteria are external, and relevance is much more important, and rigour of process is a contraint. The relevance-versus-rigour debate is reawakened from time to time. See Keen (1980), Benbasat & Zmud (1999), and Lee (1999).

Whether the pure research or the instrumentalist perspective is adopted, many observers feel that the quality of information systems research leaves much to be desired. Until the mid-1980s, conceptual (i.e. non-empirical) papers dominated the literature, even in the most highly-regarded journals. Despite this, there has been, and remains, a shortage of theories, and even an absence of a 'cumulative tradition' which would lead to the establishment of theories (Keen 1980). Where pre-theoretical 'research frameworks' have been established, they have not been used to any great extent. Conceptual, theoretical contributions continue to be common, and there continues to be a high incidence of articles excusing themselves from the harsher tests of rigour by depicting themselves as 'exploratory research'.

There has been, and remains, a shortage of validated constructs (i.e. conceptually-expressed notions for which operational definitions have been established and tested in a variety of settings), and of validated survey instruments. See Straub (1989). Some maturation has been noticeable recently, however, with the establishment of a database of instruments (Newstead et al. 1998). In addition, particularly prior to the last decade, the quality of statistical understanding and analysis demonstrated by researchers undertaking research in the scientific tradition was relatively low (Baroudi & Orlokowski 1989, Pervan & Klass 1992, Grover et al. 1993). A great deal of case study research has been undertaken in such a manner that it could provide nothing more than a free-standing instance of interest, possibly useful in teaching, but of no research significance Yin (1984), Benbasat et al. (1987) and Lee (1989).

Empirical research has been dominated by descriptive approaches. Most models have limited explanatory power, and even less predictive value, let alone clear prescriptive implications.

There has been inadequate application of the principle of 'triangulation', i.e. the gathering of data from multiple sources, and the comparison and cross-analysis of that data. Of particular importance has been the inadequate exploitation of the complementariness between quantitative and qualitative data, and a marked unpreparedness of those working in the scientific tradition to accept qualitative data as having a place in research. See, for example, Jick (1979) and Kaplan & Duchon (1988). The attitude of researchers working in the scientific tradition sometimes goes to the extreme of denying that the interpretivist approach is empirical; and some interpretivists are dismissive of the meaningfulness of research conducted in the scientific tradition.

A further serious concern has been that, even though the study of time-variant phenomena necessitates the use of longitudinal rather than cross-sectional studies, longitudinal studies have remained uncommon (Vitalari 1985, Vitalari & Venkatesh 1991). This reflects, in part, deficiencies in the funding of research, the short time available to doctoral candidates to conduct the empirical component of their thesis work, and the career-structures available to researchers.

6. Application to Electronic Commerce

The preceding sections have provided a scan of information systems research, designed to establish a firm foundation for a discussion of research in the electronic commerce domain. The following sub-sections consider quality factors, identify challenges, and examines some specific categories of research.

6.1 Definition and Scope

The research domain of electronic commerce is capable of a variety of definitions. In particular, it could be as broad as any form of business undertaken with the assistance of electronic tools, or only those that involve trading. There are many phases through which trading passes; and many sub-domains depending on the particular categories of goods and services, on the nature of the trading parties, and on the social and technological networking used.

For discussions of the term's definition and scope, see Clarke (1993 and 1997) and Zwass (1996).

6.2 Quality Considerations

Each instance of information systems research in the domain of electronic commerce requires:

In order to satisfy contemporary expectations, research in electronic commerce needs to exhibit the following characteristics:

The following, more specific considerations are suggested as being particularly important:

An application of these quality factors is to be found in the selection criteria for the Outstanding Paper Award at the annual Bled Electronic Commerce Conference.

6.3 Challenges

On the basis of the preceding discussion, specific difficulties confronting research into electronic commerce can be identified:

Research in any new domain is highly risk-prone. Research in electronic commerce is especially challenging.

6.4 Instances

It is useful to consider some common instances of research in electronic commerce, and to reflect on the extent to which they are subject to the difficulties identified above.

These quick reviews of particular kinds of EC research further evidence the extent and depth of the challenges confronting the researcher.

7. Conclusions

Research in the domain of electronic commerce is directly confronted by the 'relevance versus rigour' debate. It is crucial that researchers:

This author doubts the wisdom of pure research in a domain as directly business-related as electronic commerce, and suggests that the instrumentalist motivation is far more appropriate. This implies that researchers need to achieve a degree of relevance and external validity appropriate to the needs of the information systems discipline, and relevance and applicability to the needs of the information systems profession and its clientele, subject to a sufficient degree of rigour , internal quality and external validity.


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This paper is a further development on presentations in graduate seminars at the Australian National University between 1989 and 1995, at the Bled Electronic Commerce Conference and at the Johannes-Kepler-Universität Linz in June 1994, at Monash University's Faculty of Business & Electronic Commerce in Churchill, Victoria in April 1996, at the School of Accounting and Information Systems at the University of South Australia, Adelaide, in September 1999, and at the Australian National University's Department of Computer Science in February 2000.

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