John Mingers

Combining IS Research Methods: Towards a Pluralist Methodology

This paper puts forward arguments in favor of a pluralist approach to IS research. Rather than advocating a single paradigm, be it interpretive or positivist, or even a plurality of paradigms within the discipline as a whole, it suggests that research results will be richer and more reliable if different research methods, preferably from different (existing) paradigms, are routinely combined together. The paper is organized into three sections after the Introduction. In §2, the main arguments for the desirability of multimethod research are put forward, while §3 discusses its feasibility in theory and practice. §4 outlines two frameworks that are helpful in designing mixed-method research studies. These are illustrated with a critical evaluation of three examples of empirical research.

An Empirical Comparison of Pruning Methods for Decision Tree Induction

This paper compares five methods for pruning decision trees, developed from sets of examples. When used with uncertain rather than deterministic data, decision-tree induction involves three main stages—creating a complete tree able to classify all the training examples, pruning this tree to give statistical reliability, and processing the pruned tree to improve understandability. This paper concerns the second stage—pruning. It presents empirical comparisons of the five methods across several domains. The results show that three methods—critical value, error complexity and reduced error—perform well, while the other two may cause problems. They also show that there is no significant interaction between the creation and pruning methods.

An Empirical Comparison of Selection Measures for Decision-Tree Induction

One approach to induction is to develop a decision tree from a set of examples. When used with noisy rather than deterministic data, the method involves three main stages – creating a complete tree able to classify all the examples, pruning this tree to give statistical reliability, and processing the pruned tree to improve understandability. This paper is concerned with the first stage – tree creation – which relies on a measure for “goodness of split,” that is, how well the attributes discriminate between classes. Some problems encountered at this stage are missing data and multi-valued attributes. The paper considers a number of different measures and experimentally examines their behavior in four domains. The results show that the choice of measure affects the size of a tree but not its accuracy, which remains the same even when attributes are selected randomly.

Problem structuring methods in action

This paper provides a review and evaluation of the use of problem structuring methods (PSMs) in practice. It starts by describing the origins of PSMs, the type of problem situation for which they are suitable, and the characteristics of some leading methods. An overview of the practice of PSMs is provided from a number of angles, including case studies and surveys of applications. A number of issues in the application of PSMs are discussed, in particular an account of the debate about evaluation of the success of PSMs; the selection of an appropriate method; multimethodology; and a variety of aspects of the maintenance of relationships with the client organisation(s). Finally, some possible future developments are suggested, especially through productive interactions with similar or related practices.

Multimethodology: Towards a framework for mixing methodologies

In recent years the predilection for Systems/OR practice to be underpinned by a single methodology has been called into question, and reports on multimethodology projects are now filtering through into the literature. This paper takes a closer look at multimethodology. It outlines a number of different possibilities for combining methodologies, and considers why such a development might be desirable for more effective practice, in particular by focusing upon how it can deal more effectively with the richness of the real world and better assist through the various intervention stages. The paper outlines some of the philosophical, cultural and cognitive feasibility issues that multimethodology raises. It then describes a framework that can attend to the relative strengths of different methodologies and provide a basis for constructing multimethodology designs. Finally it presents a systematic way of decomposing methodologies to identify detachable elements, and the paper concludes by outlining aspects of an agenda for further research that emerges out of the discussion.

REAL-IZING INFORMATION SYSTEMS: CRITICAL REALISM AS AN UNDERPINNING PHILOSOPHY FOR INFORMATION SYSTEMS

The paper begins by pointing out the diversity of philosophical positions within IS, and the range of reactions to this diversity. It then discusses problems within the underlying philosophies of science—particularly positivism and interpretivism. With this as a background, the paper proposes critical realism as an underpinning philosophy that has the potential to overcome both sets of difficulties. The theoretical arguments are practically illustrated by critiques of (positivist) statistical analysis and (interpretivist) soft systems methodology.

The paucity of multimethod research: a review of the information systems literature

Abstract.  It has commonly been argued that the use of different research methods within the information system (IS) discipline and within individual pieces of research will produce richer and more reliable results. This paper reports on a survey of the IS literature to discover the extent of multimethod research. The findings are that such work is relatively scarce, and where it occurs involves only a small set of traditional methods. Possible reasons for this are discussed.

A Review of the Recent Contribution of Systems Thinking to Operational Research and Management Science

The systems approach, or systems thinking, has been intimately connected with the development of OR and management science initially through the work of founders such as Churchman and Ackoff and latterly through innovations such as soft systems. In this paper we have undertaken a review of the contribution that systems thinking has been making more recently, especially to the practice of OR. Systems thinking is a discipline in its own right, with many theoretical and methodological developments, but it is also applicable to almost any problem area because of its generality, and so such a review must always be selective. We have looked at the literature from both a theoretical and an applications orientation. In the first part we consider the main systems theories and methodologies in terms of their recent developments and also their applications. This covers: the systems approach, complexity theory, cybernetics, system dynamics, soft OR and PSMs, critical systems and multimethodology. In the second part we review the main domains of application: strategy, information systems, organisations, production and operations, ecology and agriculture, and medicine and health. Our overall conclusion is that while systems may not be well established institutionally, in terms of academic departments, it is incredibly healthy in terms of the quantity and variety of its applications.

The contribution of critical realism as an underpinning philosophy for OR/MS and systems

Many issues are under debate as to the philosophical nature of OR/MS: is it science or technology? Is it natural or social science? Can it be realist as well as being interpretivist? There are also many debates within the philosophy of science itself. This paper proposes that a particular account of the philosophy of science, known as ‘critical realism’, is especially suitable as an underpinning of OR/MS. The structure of the argument of this paper is to outline the main positions within the philosophy of science and highlight their problems, especially from the point of view of OR/MS; then to introduce critical realism and to show how it addresses these problems and how it is particularly appropriate for OR/MS; and finally to illustrate this by considering examples of various practical OR methods.

A classification of the philosophical assumptions of management science methods

This paper presents a framework within which to examine and compare the main philosophical assumptions underpinning management science methods. It takes the position that they all have in common the basic mechanism of modelling, but that they differ in terms of what they model (ontology), how they model (epistemology), and why they model (axiology). A wide range of both hard and soft methods and methodologies ace categorised within the paper. One of the purposes of the framework is to assist in the process of multimethodology—that is, combining together several methods in an intervention. In particular, it will assist users in understanding both the implicit or explicit assumptions underlying methods, and their principle aims and purposes, in order to be able to make more informed and critically aware choices when designing particular combinations in practice.