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Ambiguity in Research: Not Necessarily a Bad Thing

Michael S. Cole
Auburn University

The significant discoveries, the best science, requires us to be more venturesome and heretic in research design, and to explore fundamental questions without knowing the answer in advance. The worth of the research outcome is measured by surprise. The greater the surprise, the more interesting the result, and the greater the new knowledge about organizations (Daft and Lewin, 1990)

In a recent issue of TIP, Holland, Hogan, and Shelton (1999) provide a harsh, yet honest outlook as to why psychologists are often negatively perceived by the public. In their introspective review, the authors suggest the use of psychological jargon and lack of clearly defined constructs contributes to our unpopular image. In addition, they proffer the disregard of measurable data as detrimental to our reputation with the public (i.e., business, government). To overcome these issues, Holland et al. (1999) suggest spending more time operationally defining the constructs and making measurement decisions based on data. Although I agree with their suggestions (for the most part), I am troubled with Holland et al.'s contention suggesting "… without common definitions, it is impossible to establish convincing generalizations and meaningful relationships between variables (p. 35)." As a psychologist, I agree with the methodological desirability of precision when measuring organizational constructs. However, as an I-O practitioner, I understand that organizations are comprised of robust, multidimensional interactions occurring at the individual, group, and organizational levels. In fact, the actual equivocality of meaning experienced by real people is part of the very dynamic of organizational life. Therefore, the complexity of the organization and purpose of the research should decide the level of precision and/or ambiguity present in the exploration.

The purpose of this response is to discuss these issues and consider the utility and appropriateness of ambiguity in a research design. First, I will discuss precision and the inherent flaws that accompany a rigidly defined construct. Then I will introduce ambiguity as a research tool and present an example from the literature when ambiguity was found to be helpful. Finally, I will conclude with an emphatic assertion that we should refrain from discounting the use of ambiguity and balance the two designs within research.

Precision Vision

Psychologists often argue that to further scientific knowledge we must precisely define the constructs in question. For example, Holland et al. (1999) suggest that communication will be unsuccessful unless essential concepts are clearly defined. St. Clair and Quinn (1997) report precision can be useful, but also has the capability to close down dialogue. When too much attention is directed toward definitional precision, researchers lose sight of the initial purpose of the investigation. Moreover, researchers' designed constructs may impose a reality on the Ss population that doesn't exist (which is part of the argument for more qualitative research approaches). For example, researchers often spend more effort building an argument for their interpretation of the construct than time spent designing the study. Weick (1979) notes that researchers often forget construct measurement is only a means to understanding. Once the organization is forced into a countable form, it's stripped of what made it worth counting in the first place (Leach, 1967). Such a hazard is especially dangerous when precision overtakes a nascent research domain. Kuhn (1962) notes normal science establishes a paradigm for a way of thinking about a phenomenon. Once institutionalized, the shared paradigm becomes a basis of scholarly conviction. In the worst case scenario, a research domain may be adversely affected by positivist techniques that trivialize research with concern for minor definitional problems unconnected with relevant issues (e.g., Mills, 1959).

Ambiguity as a Research Tool

Before we can agree on a precise, clear operationalization of a construct in question, we must fully understand what we are researching. Such an understanding commonly requires concerted attention to the ambiguity inherent in the exploration (St. Clair & Quinn, 1997). Assuming the question is even worth asking, Daft and Lewin (1990) suggest why ask the question if the researcher understands the phenomenon well enough to operationally define the constructs, state hypotheses, and control confounds. Similarly, Kirk and Miller (1986, p.17) note "… in order to test a hypothesis, the investigator must already know what he or she is going to discover." Thus, constructs that allow some degree of interpretation may not only benefit from researchers' willingness to scientifically test the phenomenon, but also extend our knowledge and understanding in new and creative ways. It is when the research "focus becomes so tightly constrained that there is no disagreement about our constructs that we run the risk of failing to obtain creative insights into phenomena" (St. Clair & Quinn, 1997, p. 102).

Consider for example implementing an organizational change process without some degree of ambiguity. Quinn and colleagues (St. Clair & Quinn, 1997; Spreitzer & Quinn, 1996) discuss the Ford-University of Michigan LEAD Program as an example when ambiguity was appropriate. The goal of the program was to empower middle management to make important organizational changes and become better leaders. The managers received a week of leadership and organizational change education. At no time were they provided a definition of empowerment. Over a 6-month period, managers were urged to empower themselves and make organizational changes. Of 191 LEAD managers involved in the study, 17% made changes in their interpersonal skills, 21% made changes that improved their business unit, 16% made changes at the organizational level while another 36% performed more "global" organizational changes. The authors concluded if they would have provided an empowerment definition, managers might have added an evaluative component that would have restricted their range of thought. Rather, leaving empowerment equivocally defined, managers created their own understanding of empowerment by re-evaluating themselves, managerial roles, and the organization.

The above discussion is not intended to suggest that precision is the death knell of I-O psychology; however, when we continually extol and reward (i.e., publish) scholars for contributions that are irrelevant to real world problems, we are in fact contributing to our positivist image. In the eyes of the practitioner, this "focused" scholarly research is of little use in a manager's attempt to empower or motivate the workforce. We have to do a better job of relating our work to the practicing manager.

A Question of Balance

It is my argument that both precision and ambiguity can be utilized beneficially in organizational research. Without a doubt, precision has allowed the field to empirically examine otherwise amorphous psychological constructs. In addition, without some degree of precision scholars would be divided into camps unable to communicate with one another. Finally, precision allows multi-faceted constructs (e.g., conscientiousness) to be segmented into empirically discrete phenomenon. On the other hand, ambiguity is essential when exploring underdeveloped domains to gain a broad understanding of the phenomenon in question. In addition, ambiguity is a useful tool when implementing organizational change processes, and is a pathway to innovation. As professionals in a field whose reputation and image depends on our furthering scientific knowledge while also increasing managers' "bottomline," we must be aware of the impact of our explorations. Precision is helpful in certain situations; however, ambiguity is not necessarily a bad thing!


Daft, R. L. & Lewin, A. Y. (1990). Can organization studies begin to break out of the normal science straitjacket? An editorial essay. Organization Science, 1(1), 1_9.

Holland, B., Hogan, R. T., and Shelton, D. (1999). From phrenology to fraud: The breakdown of science in the practice of I-O psychology, The I-O Psychologist, 36(3), 35_36.

Kirk, J. & Miller, M. L. (1986). Reliability and validity in qualitative research. Beverly Hills, CA: Sage Publications.

Kuhn, T. S. (1962). The principles of scientific management. New York: Harper & Row.

Leach, E. R. (1967). An anthropologist's reflections on a social survey. In D. G. Jongmans and P. C. Gutkins (Eds.), Anthropologists in the field, 75-88. Atlantic Highlands, NJ: Humanities Press.

Mills, C. W. (1959). The sociological imagination. New York: Oxford University Press.

Spreitzer, G. M. & Quinn, R. E. (1996). Empowering middle managers to be transformational leaders. Journal of Applied Behavioral Science, 32(3), 237_261.

St. Clair, L. & Quinn, R. E. (1997) Progress without precision: The value of ambiguity as a tool for learning about organizational phenomena. In R. W. Woodman and W. A. Pasmore (Eds.), Research in organizational change and development: 105_129. Greenwhich, CT: JAI Press.

Weick, K. E. (1979). The social psychology of organizing. Reading, MA: Addison-Wesley Publishing.

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