Theory development from a new science perspective
Yee Choy Leong
Universiti Putra
Tel: 03-89467731, Fax: 03-89486188, e-mail: yee@econ.upm.edu.my
Abstract
The positivism paradigm currently dominates scientific research in management. A positivism paradigm is a system of philosophy based on things that can be seen or proved and assumes that the social world can be measured objectively. However, there is another philosophical position in management research, interpretivism, proposes that reality is actually socially constructed and must therefore be inferred from the meanings of the social actors. The debate between these two paradigms systems is always framed in terms of a choice between the generations of knowledge is either more towards science (Positivism) or social science (interpretivism). Nevertheless, there are other important kinds of knowledge beyond these two apparent dichotomies. It is known as Mode 2 (knowledge produced in the context of application). This form of knowledge is usually associated with real industry application. Managers today are more concerning about solution of problems rather than research philosophy. Solution to problems is considered as practical knowledge. A great amount of research currently underway is of this kind. The paper aims to review and discuss the two earlier paradigm systems as well as a new system. The generation of practical knowledge from a new system may view from a different scientific perspective and thus it has a different epistemological position. This paper focuses on the philosophical position of a new system thus the arguments in this paper are mainly at the level of assumption, rather than at the level of operationalisation.
Keywords: positivism; interpretivism; paradigm; philosophy; epistemology
THE MEANING OF PHILOSOPHY OF SCIENCE
The philosophy of one’s research is about the way in which the researcher views the world. Today, there is an ongoing debate in the field of management about choice of research philosophy between two competing paradigms: positivism and interpretivism. A positivist assumes that the social world can be measured objectively. A positivist is a system of philosophy based on things that can be seen or proved such as cars, machines, or furniture (Bryman & Bell, 2007). The second philosophical position, interpretivism, proposes that reality is actually socially constructed and must therefore be inferred from the meanings of the social actors (Bryman & Bell, 2007). The first philosophy gives rise to scientific knowledge, and the second contributes to philosophical understanding. The debate is always framed in terms of a choice between the generation of knowledge is either more towards science (Positivism) or social science (interpretivism). However, there are other important kinds of knowledge beyond these two apparent dichotomies. It is known as Mode 2 (knowledge produced in the context of application). A great amount of research currently underway is of this kind of knowledge generation (Tranfield, 2002). According to Gibbon et al. (1994), Mode 1 refers to traditional modes of knowledge production according to accepted disciplinary criteria and influenced by the norms of scientific enquiry such as from the paradigms of positivism and interpretivism. Mode 2 builds on scientific and philosophical knowledge. This new accumulation of knowledge is outside the boundaries of established science, but always drawing on science and social science to solve problems in the world of practice (Tranfield, 2002). The generation of Mode 2 knowledge can be done with a combined methodology, toolism (Yee, 2009a). This combined methodology form a new way of knowledge generation and it is usually associated with real industry application. In a real practical situation, management researchers are adopting a more pragmatic view by solving real life practical problems in a real world. Managers are concerning about solution of problems rather than research philosophy and theory development.
In practical research, we start from a particular problem ‘in the real world’, and bring together all the intellectual resources that can be brought to bear on its solution. The problem has to be defined and the method of solution has to be discovered. The person working in this way may have to create and identify original problem solutions every step of the way. This will usually involve a variety of theories and methods, often ranging across more than one discipline since real-world problems are likely to be 'messy' and not soluble within the narrow confines of an academic discipline.
Generation of emerging knowledge in management
The issue of theory development and knowledge generation in management research has been debated in many ways. One of the most important questions about these arguments is that whether the knowledge generated is scientific or not. Traditionally, theories developed in management are in the forms of constructs, frameworks, models, matrices, typologies, etc. However, there are other forms that knowledge can be represented, such as tools, processes, roadmaps, or charts. Are these forms of knowledge representation acceptable as useful contribution in research?
According to Oxford Advanced Learner’s Dictionary, the followings are the definitions of these terms:
Traditional knowledge:
- Framework – a set of beliefs, ideas or rules that is used as the basis for making judgments, decisions, etc.
- Construct – an idea or a belief that is based on various pieces of evidence which are not always true
- Category – a group of people or things with particular features in common.
- Model – a simple description of a system, used for explaining how something works or calculating what might happen, etc.
- Matrix – an arrangement of numbers, symbols, etc. in rows and columns, treated as a single quantity or a system of lines, roads, etc. that cross each other, forming a series of squares or shapes in between
- Typology – a system of dividing things into different types
Emerging Knowledge:
- System – an organized set of ideas or theories or a particular way of doing something. A group of things, pieces of equipment etc. that are connected or work together.
- Tool – a thing that helps you to do your job or to achieve something
- Process – a series of things that are done in order to achieve a particular result or a series of things that happen, especially ones that result in natural changes
- Roadmap – a set of instructions or suggestions about how to do something or find out about something or a map that shows the roads of an area, especially one that is designed for a person who is driving a car
- Charts – a page or sheet of information in the form of diagrams, lists of figures, etc.
- Procedure – a way of doing something especially the usual or correct way.
Based on the understanding of the definitions above, both traditional and emerging knowledge have their specific characteristics. Table 1 below differentiates the characteristics of traditional and emerging knowledge.
Table 1 Characteristics of traditional and emerging knowledge
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| Prescriptive |
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| Implementing |
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| Approach |
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| Application |
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| Improve performance |
Descriptive 
Understanding 
Abstraction 
Representation 
Improve prediction Build upon the recent argument that much management research was not reliable for use by practicing community in providing a basis for justifying their decision-making and actions, a new science perspective would provide a radical solution for further in-depth debate among the academic community. In applying toolism methodology, researchers are someone who is “concerned with the design, installation, and improvement of integrated systems of man, machine, money, information and workplace by drawing upon specialized knowledge and skills in the mathematical, physical, and social sciences, together with the principles and methods of management to specify, predict, and evaluate the results to be obtained from such systems”. Applying the solution must be done in a very systematic and logical way. Not only that it must be validated by managers, but it also has to be logic and trustworthy.
The traditional method of enquiry with the theories being generated (i.e. traditional knowledge) are useful from a curricular perspective, it is much less useful from an application perspective. Traditional knowledge is very much descriptive in nature while emerging knowledge is prescriptive in nature. In toolism, we begin the reduction of theory to practice, and building theory from practice. We focus on a real world actual implementation rather than on an academic understanding. In this sense, the academic boundary distinctions among multiple disciplines will gradually disappear and migrate to a setting that is defined by business processes rather than academic discipline. What is important to us is our impact on business performance rather than on particular tools, techniques, or disciplinary focus. The disciplinary tool, knowledge, or technique becomes valuable when it is applied and we see its instrumentality for achieving positive business performances.
Solution to problems is considered as practical knowledge. Practical knowledge is also accepted as one type of knowledge (Gibbon et al., 1994), but may be difficult to generate. The generation of practical knowledge may view this research from a different scientific perspective and thus it has a different epistemological position. Research aims to generate practical knowledge may be treated as an ‘applied science’, such as engineering in physical sciences or medicine in biological sciences. The question now is whether we treat the field of management as science, social science, or applied science.
DISCUSSION
From this paper, the main benefit of the new perspective is that it results in Mode 2 knowledge that is directly applicable to industry. Practising managers can use this knowledge without having to modify or adapt it to their situations. Furthermore, toolism is not only relevant to practitioners but follows the systematic enquiry of scientific research method. The combine methodology generates relevant data from practical experiences meeting both the practical and academic requirement.
Perhaps, the most important question to raise here is whether the new science perspective follows a proper, systematic scientific enquiry? Theory generated in Mode 2 according to Tranfield (2002) has the following characteristics: “problems are set and solved in the context of application, using a trans-disciplinary approach, with a socially distributed research team, working in a heterarchical structure, resulting in theory development and dissemination/application of findings accurring at the point of production rather than the latter being temporally dislocated from the former.” Clearly, Transfield supported the notion that mode 2 production process makes knowledge contributions. Although these knowledge contributions are rarely in the traditionally acceptable science, because replication studies are unlikely to be used based on the normal science approach. However, the form of knowledge that mode 2 could generate based on this paper is in terms of tools, processes, roadmaps, charts, pictures, template/forms, flowcharts, or managerial guidelines. This is different from the traditional knowledge that are in the forms of constructs, frameworks, models, matrices, and typologies.
Transfield argued that, “Undertaking strategic research to produce exemplars of archetypal forms of organisation design, might provide a worthy goal for mode 2 management research. Not only would this contribute to management knowledge by providing a thesaurus of what works in which circumstances, in much the same way as engineers create design templates for physical artefacts, but it would also facilitate managers in their roles as organisational architects and engineers.”
The acceptance argument was further strengthened by van Aken (2001). In his tripartite typology of scientific fields, he differentiates science into formal science, explanatory science, and design science. His thesis about formal science is that this science is based on logic and maths, but is empirically void. The objective of science is to build systems of propositions whose main test is their internal logical consistency. Explanatory science such as normal science, describes, explain and predict observable phenomena. Design science, according to him, “…include fields which sit between practice on the one hand and more fundamental disciplines on the other. They include engineering, medicine, and management. They are preoccupied with the question ‘how should things be?’ and aim to …develop knowledge for the design and realisation of artefacts, i.e. to solve construction problems, or to be used in the improvement of the performance of existing entities, i.e. to solve improvement problems… Research aims at developing knowledge and its application should lead to intended results.”(p. 5)
van Aken (2001) explained, “Design science are postulated to develop valid and reliable knowledge in the form of ‘field tested and grounded technological rules’. These rules facilitate both academic advancement and also can be used by practitioners in designing, configuring and implementing solutions to specific problems.” He further illustrated, “…management research might be argued to be best positioned within the social sciences as engineering in the physical and medicine in the biological sciences. Whereas engineering and medicine are concerned with the proper arrangement of physical and human biological artefacts respectively…”
The process of theory development or knowledge generation concerns about the validity and reliability of the theory produced. The data collection in the new science perspective based on toolism uses a collection of managers’ viewpoints. Differences in viewpoints will have to be clarified first before it is used. This validation is done through the minds of the managers rather than based on a large amount of written documents or reports from the firm, analysed and judged by researchers without participation of managers. The way of data collection may look simplicity to some researchers, however, through face-to-face discussion and challenge of opinions/viewpoints among managers, information is re-evaluated and re-confirmed by the users of information. Anyhow, written reports or survey questionnaire are also based on these managers’ opinions. Are these kinds of data collection methods not subject to any possible bias?
“Researchers improve the internal validity of a theory when they examine the phenomena from as many perspectives as possible” (Christensen and Carlile, 2009).
“Scholars who examine the phenomena and outcomes of interest from …the viewpoints of different functional groups in a company, can either incorporate what they learn into their explanations of causality, or rule out other explanations so that theirs is the only plausible one left standing” (Christensen and Carlile, 2009).
The problems with respondents give biased or inaccurate data can be solved in the new science perspective. Ability of managers to recall memories in answering a survey questionnaire would be reminded in the discussion. However, factual descriptions such as quantitative data were likely to be more accurate than managers’ opinions. To some researchers, especially the quantitative researcher would have a very negative perception of the field research because it is not based on large amount of quantitative data and thus for them it is less reliable.
The question of reliability has long been the criticism among the quantitative researchers towards field research. Field research is high in validity but low in reliability. Many researchers believed that the measure of statistical significance and goodness of fit test are relevant measures of reliability. This is because they perceived numerical data as more trustworthy than qualitative data. But, is this data really ‘objective’? Christensen and Carlile (2009) defended that “numbers [used in many research projects are] representing revenues, costs, and profits in financial statements are the result of processes of estimation, negotiation, debate, and politics that can produce grossly inaccurate reflections of true cost and profit.” They further argued that “Even the ‘hardest’ of numbers, such as those measuring prices and product performance, really are manifestations of the prioritizations, fudging measurements, exaggerations, and negotiations that occurred prior to a number appearing as a proxy for all of those things.”
They suggested, “The healthiest mind-set for researcher is that nearly all data – whether presented in the form of a large quantitative data set on one extreme, or an ethnographic description of behaviour on the other – are subjective. Numerical and verbal data alike are abstractions from a much more complex reality, out of which the researcher attempts to pull the most salient variables or patterns for examination.” They continued “There should be no smugness among quantitative researchers about the alleged objectivity of their data, and no defensiveness amongst field researcher about the subjectivity of theirs. We are all in the same subjective boat, and are obligated to do our best to be humble and honest with ourselves and our colleagues about where our data comes from as we participate individually within and collectively across the theory-building cycle.”
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