Triangulation in Organizational Research: Validating Knowledge in Human Competence at Work

Triangulation in Organizational Research: Validating Knowledge in Human Competence at Work

Ben Tran (Alliant International University, USA)
DOI: 10.4018/978-1-4666-6371-8.ch007
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The use of qualitative and quantitative methods in studying the same phenomenon has received attention among the scholars and researchers. As a result, it has become an accepted practice to use some form of triangulation in social research. In the social sciences, the use of triangulation can be traced back to Campbell and Fiskel. This was later developed by Webb and elaborated by Denzin beyond its conventional association with research methods and designs in science. The objective of science is to discover, describe, and explain the fact, whereas in the case of social science it is to observe, verify, and conclude. This chapter also covers the positivist view and the postmodernism and post-positivism paradigms of triangulation as well as the types of knowledge derived from the usage of triangulation in organizational research. This chapter concludes with how triangulation validates knowledge in human competence within an organizational setting.
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Good research practice obligates the researcher to triangulate, that is, to use multiple methods, data sources, and researchers to enhance the validity of research findings. Regardless of which philosophical, epistemological, or methodological perspectives an evaluator is working from, it is necessary to use multiple methods and sources of data in execution of a study in order to withstand critique by colleagues (Mathison, 1988). Methodological triangulation is the most discussed type of triangulation and refers to the use of multiple methods in the examination of a social phenomenon. Psychologists have long used Denzin’s notion of within-method triangulation in assessing psychological traits. Multiple scales comprise a psychological assessment such as an intelligence test in an effort to assess the different aspects of intelligence (Mathison, 1988).

In social science, triangulation is defined as the mixing of data or methods so that diverse viewpoints or standpoints cast light upon a topic. The mixing of data types, known as data triangulation, is often thought to help in validating the claims that might arise from an initial pilot study (Olsen, 2004). In social research, triangulation is used in a less literal sense, for it involves the use of multiple methods and measures of an empirical phenomenon in order “to overcome problems of bias and validity” (Blaikie, 1991, p. 115; Blaikie, 2000, p. 262-269; Scandura & Williams, 2000) for improving the validity of research or evaluation findings (Miles & Huberman, 1984, p. 235). It is essentially a strategy that will aid in the elimination of bias and allow the dismissal of plausible rival explanations such that a truth proposition about some social phenomenon can be made (Campbell & Fiskem 1959; Denzin, 1978, 1989; Webb, Campbell, Schwartz, & Sechrest, 1966). Historically, triangulation is a new concept in the social science repertoire dating back to a paper published by Campbell and Fiske in 1959.

A central focus for researchers within management and organizational sciences is producing knowledge about human action and activities in organizations. Traditionally, according to Sandberg (2005), knowledge has been produced from quantitative or qualitative approaches within the positivistic research tradition. However, during the past three decades, interest in qualitative approaches based on the interpretive research tradition has steadily increased in management and organizational sciences (Alvesson & Skoldberg, 1999; Prasad & Prasad, 2002; Zald, 1996), as well as within social sciences more generally (Atkinson, Coffey, & Delamont, 1003; Denzin & Lincoln, 1994; Flick, 2002; Lincoln & Denzin, 2003; Schwandt, 1994). The strong growth of interpretive approaches mainly stems from a dissatisfaction with the methods and procedures for producing scientific knowledge within positivistic research.

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