10.1016/S0272-6963(98)00023-0

10.1016/S0272-6963(98)00023-0 1 <h5>Introduction</h5> A number of recent papers and editorials (e.g., Wood and Britney, 1989 ; McCutcheon and Meredith, 1993 ; Ebert, 1989 ) have pointed out the relative paucity of case and field research in operations management. This form of empirical research continues to be poorly understood and infrequently published in our top journals. In part, this may be due to unfamiliarity with the nature of theory building using case and field study methods. As one example, a researcher some time back submitted a paper on steel mini-mill technology in the early days of mini-mills. The paper was rejected on the basis of a referee's criticism that a sample of nine was simply too small for statistical conclusions. The researcher's rejoinder was that this was not a sample, it was the entire population ! Both the referee and the editor were then at a loss, not knowing where to go from there. The intent of this paper is to clearly convey why the empirical methods of case and field research are preferred to the more traditional rationalist ( Meredith et al., 1989 ) methods of optimization, simulation, and statistical modeling for building new operations management theories. In doing http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

10.1016/S0272-6963(98)00023-0

Elsevier — Jun 11, 2020

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Abstract

1 <h5>Introduction</h5> A number of recent papers and editorials (e.g., Wood and Britney, 1989 ; McCutcheon and Meredith, 1993 ; Ebert, 1989 ) have pointed out the relative paucity of case and field research in operations management. This form of empirical research continues to be poorly understood and infrequently published in our top journals. In part, this may be due to unfamiliarity with the nature of theory building using case and field study methods. As one example, a researcher some time back submitted a paper on steel mini-mill technology in the early days of mini-mills. The paper was rejected on the basis of a referee's criticism that a sample of nine was simply too small for statistical conclusions. The researcher's rejoinder was that this was not a sample, it was the entire population ! Both the referee and the editor were then at a loss, not knowing where to go from there. The intent of this paper is to clearly convey why the empirical methods of case and field research are preferred to the more traditional rationalist ( Meredith et al., 1989 ) methods of optimization, simulation, and statistical modeling for building new operations management theories. In doing

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