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  OrganizationScience Vol. 22, No. 5, September–October 2011, pp. 1312–1321 issn1047-7039 eissn1526-5455 11 2205 1312 http://dx.doi.org/10.1287/orsc.1100.0636 ©2011 INFORMS “I’ve Got a Theory Paper—Do You?”: Conceptual, Empirical, and Theoretical Contributions to Knowledge in the Organizational Sciences Zur Shapira Department of Management, Stern School of Business, New York University, New York, New York 10012 zshapira@stern.nyu.edu I s “the field of management’s devotion to theory t
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  OrganizationScience Vol. 22, No. 5, September–October 2011, pp. 1312–1321 issn 1047-7039  eissn 1526-5455  11  2205  1312http://dx.doi.org/10.1287/orsc.1100.0636©2011 INFORMS “I’ve Got a Theory Paper—Do You?”: Conceptual,Empirical, and Theoretical Contributions to Knowledge inthe Organizational Sciences Zur Shapira Department of Management, Stern School of Business, New York University, New York, New York 10012zshapira@stern.nyu.edu I s “the field of management’s devotion to theory too much of a good thing?” [Hambrick, D. C. 2007. The field of management’s devotion to theory: Too much of a good thing? Acad. Management J. 50 (6) 1346–1352]. In his paper,Hambrick criticizes the practice employed by many journals in the management field that requires that papers submitted forpublication make a strong theoretical contribution. I argue that part of the problem is caused by the misunderstanding andmisuse of the term “theory.” To clarify the status of theory, I review three modes of research formulation in the organizationalsciences: theories, models, and conceptual frameworks. Language plays an important role in scientific research. I thereforediscuss two research languages that are used in research in management that appear to be the farthest apart: mathematics,which is the language of precision; and narratives, which is the language that provides rich data. I provide a discussion of the use of mathematics in theory development and the use of narratives in research development. The two languages andthree modes of research formulation are needed for contribution to knowledge, which should be the main goal of researchin organization science. Key words : theory; model; mathematics; narratives  History : Published online in Articles in Advance April 29, 2011. There is nothing so practical as a good theory .(Lewin 1952, p. 169) In a provocative article, Hambrick (2007) laments themanagement field’s devotion to theory. He criticizes thepractice employed by many journals in the field thatrequires that papers submitted for publication make astrong theoretical contribution. He points at a confusingstate of affairs in the management field where an authorwho conducts valuable empirical research meets a bar-rier upon submitting a paper to a journal. Often, authorsare told that because there is no contribution to theoryin their paper, it has to be rejected. As Hambrick (2007)notes, this practice does not help the science of organi-zations and can hinder its progress (see also Corley andGioia 2011). Although I am familiar with this practiceof journals requiring contribution to theory, it appearsthat the word “theory” is misused in the managementfield, and this may be part of the reason journals tend toreject manuscripts that otherwise would not be rejected.I share his concern but nevertheless think that the seed of the problem lies in an erroneous understanding of whata theory is.A theory signifies the highest level of inquiry in sci-ence. It is a formulation of the relationships among thecore elements of a system of variables that ideally isarrived at after overcoming multiple hurdles and sev-eral stages of refinement and empirical testing. Unfor-tunately, I have come to realize that the term “theorypaper” is often used in the management field merely todescribe a nonempirical paper. I have often heard a man-agement scholar saying that he or she has a theory paper,but in many such papers there was no theory, whichcame on top of having no data. This, along with state-ments about contribution to theory being a necessarycondition for publication in top management journals,creates real confusion as to what the term “theory” actu-ally means in the management field. In the first part of this piece, I attempt to clarify the importance of theoryby discussing different forms of research formulation(conceptual frameworks, models, and theories) that pro-vide a wide range of approaches to formalizing researchin an increasing level of rigor.Research, whether empirical or theoretical, isexpressed in a language for description and commu-nication. The second part of the paper is devoted totwo major languages that are often used in managementresearch: mathematics and narratives. I describe eachlanguage and show how using each can lead to scien-tific development. These two languages are at the twoextremes of formality, where mathematics is a languagethat describes ideas in a very precise way but at times atthe expense of the richness of a domain. Narrative is aform of research language that provides rich descriptionsbut often at the expense of precision. I end this paper by 1312  Shapira: Conceptual, Empirical, and Theoretical Contributions to Knowledge in the Organizational Sciences Organization Science 22(5), pp. 1312–1321, ©2011 INFORMS 1313 arguing that the goal of scientific research in manage-ment should be contribution to knowledge that is basedon a combination of conceptual, theoretical, and empiri-cal work. Research in management often starts by identi-fying questions that are observed in the field where nar-ratives provide the description of the phenomena underinvestigation. When possible, a conceptual framework emerges that may lead to model development and ulti-mately to theory construction. The latter often requiresthe use of a more formal language such as mathematics. Theories, Models, and ConceptualFrameworks A Theory: A Coarse Definition and a Few Examples The scope of this paper does not allow a thorough dis-cussion of what a theory is, and this presentation isbrief and incomplete. Yet this discussion is needed sothat one can know whether he has a theory or not, aswell as to motivate the comparison to other avenuesof knowledge creation (models and conceptual frame-works) and to discuss how empirical research is linkedto theory development. A theory is commonly defined asan analytic structure or system that attempts to explaina particular set of empirical phenomena. Theories dif-fer in depth and scope; there are theories that attemptto cover many phenomena, such as Einstein’s attemptto develop a general theory that would unite gravitationwith quantum mechanics. In the social sciences, Simondevoted the latter part of his life to developing a gen-eral theory of problem solving. In contrast, an exam-ple of a more specific theory in the social sciences isTversky’s (1972) “elimination by aspects,” which is avery elegant theory of choice that makes clear assump-tions and derives specific predictions, several of whichwere tested in different choice contexts (see Fader andMcAlister 1990). Prospect theory (Kahneman and Tver-sky 1979) is another example of a theory of choice thathas had an enormous influence in the social sciences.Without attempting to survey the rich literature on theessence of theory in the philosophy of science (see, e.g.,Lakatos 1978, Popper 1959), I highlight a few generalaspects of the notion of theory.(1) A theory is constructed to provide a coherentexplanation of a set of observed phenomena.(2) Theories make assumptions and, based on them,draw logical derivations . Those derivations lead to spe-cific predictions regarding the subject matter with whichthe theory deals.(3) A theory should be formulated in a way thatmakes it clear how it can be refuted  or falsified  .(4) The ultimate test of a theory is achieved by com-paring its predictions to reality. Thus, a theory’s predic-tions are subject to a false/true test.Of the many theories in the natural sciences, perhapsthe most famous is the relativity theory in physics. Manythink of Einstein’s theory of relativity as one of thegreatest achievements in scientific inquiry. Its publica-tion (both the special and the general versions) changedan entire way of thinking and conducting research inphysics and in the sciences in general. Relativity theorywas not just a theorem about a unique relation betweentwo variables; rather, it defined a four-dimensional spacethat led to a new way of thinking about the relationbetween time and space. It stated that there is an upperlimit to speed, which is the speed of light and is constant.Based on its assumptions, several testable hypothesesand predictions were derived. One of these derivations,E = MC 2 , is perhaps the most well-known equation inscience at large. General relativity theory predicts thatlight bends when it travels in the neighborhood of mas-sive objects such as the sun, a phenomenon known aslight deflection. This prediction was tested by measuringthe change in position of stars on the celestial sphereas they passed near the sun. Eddington and his collab-orators performed the measurement in 1911 during atotal solar eclipse simultaneously in the cities of Sobral,Ceará, Brazil and São Tomé and Príncipe on the westcoast of Africa (e.g., Dyson et al. 1920). The measure-ments confirmed Einstein’s predictions and corroboratedhis theory.An example of an influential theory in the socialsciences is game theory (see Von Neumann andMorgenstern 1944). Its influence increased over theyears, and it became a major building block of moderneconomics. The formal ways in which game theory dealswith competition, cooperation, coordination, matching,and more led Varian to state, ”Indeed, most economicbehavior can be viewed as a special case of game the-ory” (1992, p. 259).I think that part of the confusion among managementresearchers concerning the need for and evaluation of theoretical work is caused by the use of the term “the-ory” in a very loose sense. For example, in the social sci-ences “utility theory” is a term used to describe rationalchoice in general and is not a theory in the narrow senseof the word. A more peculiar misnomer is “organiza-tion theory,” which actually describes a level of analysisrather than a theory per se.What role have theories played in the developmentof the organization sciences, and what role should theyplay going forward? The field of organizations actuallyemerged with empirical and observational studies (see,e.g., Taylor 1911), and it was mainly Cyert, March, andSimon who transformed the body of observations into atheoretical framework. The books Administrative Behav-ior  (Simon 1947), Organizations (March and Simon1958), and A Behavioral Theory of the Firm (Cyert andMarch 1963) have had a tremendous effect on the field.The Carnegie approach pushed the field of organizations  Shapira: Conceptual, Empirical, and Theoretical Contributions to Knowledge in the Organizational Sciences 1314 Organization Science 22(5), pp. 1312–1321, ©2011 INFORMS into the realm of science by making assumptions, deriva-tions, and predictions and by using mathematics and for-mal language to describe the relations among variables.The above discussion of theory fits nicely the CarnegieSchool tradition, where theories, models, and conceptualand empirical work led to a major development in theorganization sciences. A Model Models are important tools in scientific inquiry. A modelimplies a formulation that(1) derives predictions based on clearly specifiedassumptions, and(2) is precise and falsifiable.The major differences between a theory and a modelare the first and fourth points described previously as thecriteria for theory. That is, a model does not necessar-ily need to provide an explanation of the phenomenonit deals with and does not need to make a claim abouttruth. Therefore, a test of a model is not  one of a“true/false” type but rather a kind of a “usefulness”test. For example, Regnier and Harr (2006) developed amodel for predicting hurricane landfall based on histori-cal data on tropical cyclone tracks and data derived fromexisting forecasts to estimate the likelihood of landfallat a particular location. The goal of the model was tohelp local decision makers by evaluating the trade-off between lead time and forecast accuracy, estimating thevalue of waiting for improving forecasts to reduce thefrequency of false alarms. Such a model can be eval-uated in terms of saving life and damage as well ascost of operations. The model can prove useful for adecision maker who needs to decide on evacuation. Itis not intended to explain the way hurricanes develop,from which the location of landfall can also be theo-retically derived; this is an endeavor that is much morecomplicated.Another example relates to the heliocentric modelof the planets’ movements. Kepler modified the exist-ing model, and his adjusted model, which was basedon extensive data on the location of the planets, did avery good job of predicting planetary motions. How-ever, Kepler did not provide a clear explanation of whatwas behind his equations. Indeed, his model lost itseminence when Newton developed his theory of grav-itation (see Livio 2009). Kepler’s equations, however,could be derived from Newton’s theory. Hence, lookingat Kepler’s equations from a Newtonian perspective pro-vides an example of a “theoretical model”—that is, amodel derived from a theory rather than from data.Examples about the use of models based on datarather than a theory are found in the social sciences aswell. One such arena has been the explanation and pre-diction of the effects of star actors on the financial suc-cess of movies. The data-based models by Ravid (1999)and Elberse (2007) provide sophisticated analyses forthe prediction of future movies’ success. Lampel andShamsie (2000) propose a wider theoretical backgroundthat examines how information asymmetries influencecompetitive dynamics in the film industry to explain thedeterminants of as well as predict the success of newfilms. Another example is depicted by recent develop-ments in imaging (functional magnetic resonance imag-ine) that do not go beyond correlational analysis, andthere is no theory at the moment that can explain thecomplex processes in the brain that cause blood to flowfrom one area to another. However, as more data get col-lected, better predictions will be made about the associ-ation between responses to different questions and activ-ity in different domains of the brain.Examples of useful models abound in the natural sci-ences and are very common in economics. One areathat has developed over the years at Carnegie and otherplaces is the use of computer simulations to study pro-cesses of thinking (Newell and Simon 1972). Realizingthat the use of mathematics for arriving at closed-formsolutions is rather restrictive in studying phenomenasuch as human and social behavior, many researchersbuilt simulation models to get better insights aboutsocial and organizational phenomena (see Burton andObel 2011).Models are precise, especially if they are formulatedin mathematical terms. At times, however, researchersapproach new domains that do not allow them touse precise symbols to describe the phenomena theyare studying. In such cases, researchers try to buildconceptual frameworks, which may not be as specific asmodels but may provide a general system of organizingthe observations. Conceptual Frameworks Theories and models differ from conceptual frameworksin that they make testable predictions. Work of this typemay not be possible in, say, an initial stage of scientificinquiry in a new domain. At such a stage, scientists mayseek to develop frameworks that help organize empiricalobservations by using coherent and meaningful frame-works. Such frameworks allow scholars to make senseof the field and understand its boundaries, major find-ings, and challenges. Thus, in comparison with the fourcriteria for theory and the two for a model describedabove, the criteria for a conceptual framework are that it(1) provides a structure to organize observations, and(2) describes the structure in a clear and precisemanner.Research in the biological and life sciences often usesclassifications and categorizations as a main researchmethod. Paleontologists use such methods to createorder among many different phenomena. The srcinalstudy of the evolution of species (Darwin 1859) startedwith a collection of empirical data and developed a morecomprehensive framework to account for the data. This  Shapira: Conceptual, Empirical, and Theoretical Contributions to Knowledge in the Organizational Sciences Organization Science 22(5), pp. 1312–1321, ©2011 INFORMS 1315 framework had an immense influence on thinking inboth the biological as well as the social sciences. Itserves as an example of a domain that was developed inan inductive manner into a comprehensive framework.A recent treatise by Dawkins (2009) argues that the gen-eral framework of evolution is superior to many otherperspectives on the development of life that are basedon nonscientific assumptions.Organizational change can serve as an example of a conceptual framework in organizational behavior andtheory. This framework helps describe the many forcesthat operate in organizational settings, some of whichfacilitate change while others do not. Lewin’s (1952)field forces analysis does a great job of providing aschematic representation of such forces. There are othertreatments of organizational change, and some modelsof change have been developed. However, although theframework may be useful in analyzing cases of changein organizations, it has not developed into a coherentset of assumptions, derivations, and predictions as gametheory has, for example.A conceptual framework does not necessarily makestrong assumptions the way a theory does, and it may notbe as tightly structured as a mathematical or a computa-tional model. Yet a good conceptual framework may leadto new insights and may open new avenues of thinkingon particular phenomena. Its ultimate test, so to speak, iswhether it leads to a better organizing of the major issuesin a particular domain of inquiry. Such organization canenhance our understanding and may eventually lead todeveloping models for prediction and ultimately to the-ories that explain the nature of the domain of inquiry. 1 The Role of Language in Scientific Progressand Theory Development Researchers need to communicate with each other abouttheir ideas, conjectures, and findings. To communicate,they need to use a common language that they and theircommunity understand. There are different languagesthat can be differentiated by the degree to which theyare precise on one hand and rich on another. Usually,the richer a description, the less precise it is, and viceversa. Consider, for example, research in strategic man-agement that attempts to analyze variations in perfor-mance among firms. Authors of such papers can say, forexample, that variable X affects performance so that thehigher X is, the higher the performance is. Such a state-ment is not as precise as writing performance = 2 X . Thequantitative expression is more precise than the verbalstatement. Of course, the researcher can say it in words:“As X increases, performance increases in a double-foldmanner”; this is precise but clumsy. The mathematicalexpression is more parsimonious and provides a better fitwith Popper’s (1959) criteria for scientific expressions.At the other end lies a situation where a researcheris observing a group discussion in a foreign countryin a language that he or she does not understand. Tocommunicate the essence of his or her observations, theresearcher will need to use a narrative format that will berelatively rich but may not be precise. Verbal theories aremuch more ambiguous than mathematically formulatedtheories (Harris 1976), but in some situations richnessmay be a better way to describe the research contextthan a more precise language.In constructing theories, models, and conceptualframeworks, a researcher can use different languagessuch as mathematics, simulations, and graphical tools,as well as verbal description and narratives. Accordingto classical treatment by philosophers of science (Pop-per 1959), a theory has to be parsimonious; that is, if two theories are offered for explaining the same phe-nomenon, and do so with a similar degree of success,the one that is more concise and shorter is thought todominate the other. Ultimately, this view almost man-dates that the language of science be mathematics andthat theories should be formulated with mathematicaltools. Such an argument can be valid in situations wherethe domain of investigation is mature enough to allowprecision in theorizing. When a domain of inquiry isstill in its nascent stage, the use of mathematical toolsmay be premature, and the development of knowledgeat such a stage may benefit more from the use of nar-rative and other less formal tools. When such a domaindevelops further, mathematics can be used to help sortout good theories from weaker ones. Researchers shoulduse a language that matches the stage of the problemthey are studying. Descriptive narratives should be usedin the first stage of a field study (along with the col-lection of hard facts/data) to get the perspectives of theparticipants on the phenomenon. As the research projectmakes progress and certain patterns emerge from thedata, models can be developed using formal languagesuch as mathematics.The discussion in the first section follows argumentsmade by the psychologist and philosopher of scienceMeehl (1967), who subscribed to the Popperian traditionand argued that science makes progress in a cumulativemanner. He claimed that in an advanced field of sciencesuch as physics, theories make point predictions aboutparameter values. Theory development progresses byattempting to surmount hurdles that are increasingly dif-ficult. To do this, theories need to be formulated mathe-matically, and tests of a theory should be framed as testsof specific point predictions. If a theory passes a test—namely, that a point prediction has been supported—thatpoint becomes the null hypothesis in future tests. Thatpoint prediction is contrasted against an even more dif-ficult point prediction arrived at by developing the the-ory further. This approach can be contrasted with thetesting of “no-difference” null hypotheses. Hypothesesof this type can be rejected by merely increasing thesample size. Thus, although significant differences can
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