The authors have had a continuing interest in entrepreneurial technology based firms. During the last twenty years, microelectronics firms and their allied industries have grown from virtually non-existent sales in 1977 to over a trillion dollars in sales worldwide in 1996 (Value Line, 1997). Firms associated with this industry have produced great wealth for their founders, shareholders, and the communities in which they were located. For example, an initial $2,100 investment in Microsoft stock when it went public would have yielded a profit to the shareholder of over $307,000 eleven years later (Valueline, 1997). Concomitant with the wealth and job creation, entrepreneurs and their firms have become a fertile area for academic research.
A growing number of researchers have begun to focus on single
industry studies, identifying strategies for firms in specific,
or at least similar, industries (Carter et. al, 1994; McDougall
et. al, 1994). Several recent studies have identified the
necessity of studying single industry firms (Boeker, 1989; Feeser
and Willard, 1990; McDougall and Robinson, 1990; McDougall et.
al, 1994; Teach and Schwartz, 1995; Schwartz and Teach, 1996).
These and other studies have found that there were important
relationships resulting from industry effects, either through
location in the industry channel (Carter et. al, 1992) or through
the combined effects of industry, entrepreneur and strategy
(Sandberg and Hofer, 1987). Industry specificity
also affords the researcher the ability to study firms which play by the "same set of rules" (William's et. al, 1995).
While there may be different views of how to account for specific industries in research methodology (Carter et. al, 1994), it would appear that narrowly defining populations for study by four or five digit SIC codes, would be appropriate. However, many firms, particularly public firms, do operate in several different industries, thus creating uncertainty as to the validity and subsequent generalizations based upon the analyzed results.
Differing prescriptive strategies of innovation and market differentiation (Miller and Toulouse, 1986); quality and technology; (Fombrun and Wally, 1989); cost leadership and innovativeness (Chaganti et. al, 1989); low cost producer and niche markets (Boeker, 1989); cost leadership and differentiation (Green et. al, 1990; Meyer and Roberts, 1986); price competition, small market niches, and premium pricing (McDougall and Robinson, 1990) have been identified for technology based firms.
Studies are performed at specific points in time utilizing data provided by anonymous respondents replying to survey instruments. Specific sets of different firms are then analyzed. The studies sometimes yielded dissimilar results, which authors have had little, some, or great difficulty explaining, particularly when the results were counterintuitive (Meyer and Roberts, 1986; Cooper, 1984; Stearns et. al, 1995).
One study (Carter et. al., 1994) explained why results of analyzing strategy typologies differed from study to study. It was suggested that strategy archetypes, while dominating a particular industry, would vary by the respondent firms' positions in the channel. Strategy was defined as a multidimensional construct which represented a composite or bundle of actions and tactics. This definition would explain why strategies studied at a point in time would only be operational at a point in time. Typically, anonymous respondent-completed questionnaires are utilized by researchers seeking the identification of the firms' strategies and the performance measures at a specific point in time. This information is utilized to define clusters of strategies which are then related to the identified performance measures (Covin et. al, 1990). While the technique can be appropriate, the results depend upon the concurrently collected performance measures. Because respondents and their firms are anonymous, follow-up studies at later points in time rarely include the same firms from the original study. Thus, the possibility of tracking strategy effects over time are lost and the overall results are simply collections of static studies.
Frequently the authors of static studies aggregate the sample data into a set of "rapidly growing" firms and a set of "slow to non-growing" firms and search for common sets of strategies. Strategies found in common with rapidly growing firms are concluded to be strategies that increase performance. In a similar vein, common strategies of slower growing firms are viewed as strategies which do not enhance performance. The problem with static studies is that they do not reflect changes in the environment and the subsequent changes in firms' competitive positions.
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