Functions

Several authors (e.g. Dubin, 1969; Hudson and Ozanne, 1988; Bacharach,1989; Meredith, 1998 and Koskela, 2005) argue that the key functions of a theory are

prediction and explanation.

In this respect, Dubin (1969) discusses that there are two meanings for the prediction function: (1) that we can foretell the value of one or more units making up a system; or (2) that we can anticipate the condition or state of a system as a whole. In both instances the focus of attention is upon an outcome. Hudson and Ozanne (1988) add that with explanation or prediction we are usually interested in the similarities of a system. Bacharach (1989) argues that prediction tests the meaning of the explanations provided.

In regards to explanation, Dubin (1969) uses the term “understanding” to refer to the knowledge that explains the interaction between units of a system. However, according to Hudson and Ozanne (1988) understanding is a never ending process rather than an end. To them, with understanding, we are equally, if not more, interested in differences. Bacharach (1989) argues that explanation is used to establish meaning, i.e. to explain the prediction mechanism and how it relates to the investigated phenomena. According to Meredith (1998) understanding entails both explanation and prediction and more. Kaplan (1964)24as cited in Meredith (1998) illustrates this with the example of the ancient astronomers who made excellent predictions of the future positions of the planets; they could also explain the rationale behind the prediction but were unable to say why (understanding) that and not another mechanism was right.

According to Koskela (2005), prediction and explanation relates to the scientific functions of a theory. For this author, the functions of a theory can be further expanded and associated with their scientific and practical use (Table 6). Koskela (2005) augments to the previously discussed functions the predisposition that theories have to validate knowledge and provide direction to research. In respect to direction for research, Koskela argues that identified discrepancies between theory and empirical observation, in general, leads to new research and investigation.

In regards to its practical functions, Koskela (2005) argues that theories play a role in supporting methods and tools as an explanation is provided to why they work. The same role applies in relation to teaching, communicating and transferring knowledge across different fields. In addition to that, Cooper (2005) argues that theories help practitioners to identify the root cause of their problems. Once practitioners know “what is going on” they can try to establish practical ways (e.g. methods and tools) to interfere in a specific situation aiming to change it.

Table 6 - Functions of a theory according to its relation with its scientific and practical use Scientific Practical Explanation Prediction Validation Direction of research

Supporting methods and tools Teaching

Communication Knowledge transfer

In this paper it is assumed that the scientific function of a theory is to explain how and why phenomenon happen. In this process, knowledge is generated from both correct (known things) and incorrect explanations (yet to be known things). In this respect, knowledge development constitutes a function itself. On the other hand, in addition to the practical functions presented, theories (whether explicit or not, correct or not) form the basis of our arguments and decisions in the “real world” aiming to change, develop and create things.

3.5.3 Trade-offs

The process of building theories involves “solving” trade-offs and admitting limitations. For instance, due to intrinsic limitations, research will always be imperfect in relation to testing all possible or relevant contextual and temporal scenarios. Thus, a compromise related to the scope of the study that will generate the theory has to be made so as to progress the research. However, scope is only one aspect that generates trade-offs.

According to Weick (1979)25 as cited in Sutton and Staw (1995), organizational scholars, like those in other social science fields, often are forced to make trade-offs between generality, simplicity, and accuracy. For DiMaggio (1995) this happens because theory building involves different purposes and embodies different values. In other words, a theory is the result of a hybrid combination of qualities that includes covering-law, enlightenment and process approaches (DiMaggio, 1995). As such, the process of developing logically consistent and integrated arguments becomes a challenge (Sutton and Staw, 1995). According to DiMaggio (1995), some of the challenging and common trade-offs experienced by theory developers include26:

Clarity versus de-familiarisation: quoting Plato’s paradox, if you know what

something is, there is no need for research and if you do not know you will not recognise it. Thus, theory building involves “de-familiarisation”, which is the process of enabling a native to see its own world with a new “fresh” pair of eyes (DiMaggio, 1995). For instance, using different ontologies to investigate the same phenomena can promote similar or different understandings. According to DiMaggio (1995) both are essential ‘old words’ and neologisms. In this case, to confront a new reality can bring out our values from our subconscious and help us to reassess them.

Focus versus Multidimensionality: multidimensionality means to consider different

characteristics related to the investigated phenomenon such as agency, culture, structure and several other abstract categories in its rhetoric (DiMaggio, 1995). For instance, a multi-dimensional take on building design will consider the views and needs of investors, different user groups, designers and contractors. A focused one will concentrate on one of them. DiMaggio (1995) highlights that focused theories have fewer and highly specialised readers and fewer interpretations (or different reception). Contrastingly, multidimensional ones attract more readers with different backgrounds and different interpretations or something to say. Thus, if on the one hand you limit the variables and relationships involved in the phenomenon, risking

25 _{In Weick, Karl E. 1979. The social psychology of organizing, 2}nd _{ed. Reading, MA: Addison-Wesley.} 26 _{The viewpoint presented here is limited as DiMaggio (1995) adopts a subjective ontological point of} view (i.e. the world is something created by the human mind). Therefore, balance and equilibrium is recommended since each person has a different background that will influence their understanding. The debate related to other ontological positions are not discussed here and the authors acknowledge

developing something interesting, on the other you expand, and testing all relationships becomes challenging or impossible

Comprehensiveness versus memorability: If our job is to explain the world, rather than

to note small but paradoxical statistical relationships, should not we focus precisely on the measures and processes that explain the most? DiMaggio (1995) confronts the problem related to levels of generalisation (i.e. can the same theory be applied in other contexts?). In this respect, the debate relates to the extent that a general theory can be accessed and validated or a specific one made relevant.

In relation generalisation, Meredith (1998) emphasizes the issues of rigour when developing a theory. For Meredith (1998) rigour is associated with the level of replicability of research and/or phenomenon. Meredith (1998) argues that on the one hand theories generated within a controlled environment could have limited generalizability, as the chances that the laboratory conditions exist in the real world are limited or non-existent. The same applies for those using cases studies, where the chance that the contextual and temporal setting where the theory was developed will never be the same in another case.

3.5.4 Summary and Discussion

This section proposes a discussion about theory building. This topic is relevant to the development of this thesis as knowledge and therefore evidence are generated as its theoretical support is presented. The discussion presented here is focused on highlighting the different terminology used to refer to theory, its functions and trade- offs.

In relation to available definitions, the review revealed that there is no consensus amongst academics conducting research in the area. In this respect, a definition was proposed that incorporates the shared and specific features considered within each studied definition. In relation to a phenomenon, that includes the relevant and irrelevant “parts” and the relationship mechanisms between those, its prediction capacity supported by evidence and the explanation for how evidence can be gathered, as well as the rationale behind the explanation and finally the context (generic or specific) in which the theory applies.

In terms of its function, the debate relates, in general, to scientific functions of theories. In this respect, explanation, prediction, validation and direction to research were highlighted as key functions. Without further discussion, theories are considered as a type of knowledge (theoretical knowledge) for which the JTB rules apply. In addition, practical functions of theories were discussed. These refer, in general, to theory building as a mechanism for knowledge exchange and justification/rationale for decision-making.

Finally, the process of theory building was discussed in relation to internal conflicting issues that lead to trade-offs. Key aspects where discussed, such as clarity, focus and comprehensiveness and their respective opposites. Rigour and replicability were also discussed as impacting on the generation of trade-offs in the development of theories. The definition, function and trade-off aspects of theory building, forms here a framework for the assessment of theories. These aspects are summarised below:

• Completeness: Were all relevant parts considered, and irrelevant ones

systematically removed?

• Usefulness: Does the theory stimulate discussion and practical changes? Does it

help to explain or predict an event?

• Coherence: Are the author’s assumptions, explanations and justifications explicit?

• Bias: Have the relevant dimensions (lenses) been used to interpret the phenomena?

• Replicability: Can results from theory test be replicated?

• Challenge: Does the theory challenge the current thinking?

• Novelty and Innovation: Is it really a new theory? Is it a contemporary subject?

• Validation: are test mechanisms representative of investigated phenomena

• Relevance: How many times? How many places? How big is the population

affected by the phenomenon?

• Generalisation: Is the theory abstract enough that it can be applied to different

specific events?

• Rigour: Are methods and data collection reliable? Have different ontologies and