Testing the validity of Miles and Snow's typology.

Croteau, Anne-Marie ; Raymond, Louis ; Bergeron, Francois 等

INTRODUCTION

Since the early 1990s, improving the information system planning process has been one of the top ten concerns of senior information systems executives (e.g., Janz, Brancheau & Wetherbe, 1996). Gartner Group's 1999 annual survey reports that aligning information technology with business goals is still CIOs' critical technology management issues (Raphaelian & Broadbent, 1999). In order to carry out this planning process successfully, it is deemed important to align the information systems plan with the organization's business plan. A few recent studies have successfully observed the effect of the alignment of information technology with organizational variables on organizational performance. Specifically, information systems management and business strategy gain to be mutually planned to improve organizational growth and profitability (Bergeron & Raymond, 1995; Raymond, Pare & Bergeron, 1995; Chan, Huff, Barclay & Copeland, 1997).

From a methodological point of view, various instruments have been used to explore the relationship between business strategy and performance; for instance, Venkatraman's (1989) instrument on strategic orientation has been frequently used. However, the best known approach to characterize business strategy originates from Miles and Snow (1978), which has been quoted more than 650 times in the last years (Social Sciences Quotation Index, 1989-1998). The principal strength of this typology is the simultaneous consideration of the structure and processes necessary for the realization of a given type of business strategy. Miles and Snow's (1978) typology reflects a complex view of organizational and environmental processes, as well as the attributes of product, market, technology, organizational structure and management characteristics (Smith, Guthrie & Chen, 1989).

Within the context of strategic alignment of information technology, the purpose of this research is to validate Miles and Snow's typology as operationalized by Segev (I 987).

MILES AND SNOW'S TYPOLOGY

Business strategy is the outcome of decisions made to guide an organization with respect to the environment, structure and processes that influence its organizational performance. Approaches to identifying a business strategy can be textual, multivariate or typological (Hambrick, 1980). The typological approach is recognized as creating a better understanding of the strategic reality of an organization, since all types of business strategy are viewed as having particular characteristics but a common strategic orientation. While several typologies have been proposed (see Ansoff & Stewart, 1967; Freeman, 1974; Porter, 1980; Miles & Snow, 1978), the most frequently used in empirical research is Miles and Snow's (Zahra & Pearce, 1990, Smith, Guthrie & Chen, 1989).

Miles and Snow's typology consists of four ideal types of business strategy defined as prospector, analyzer, defender, and reactor. Firms choose one type rather than another according, to the perception they have of their environment. The first three types can be considered along a continuum, expected to enhance organizational performance. The prospector strategy is at one end of the continuum, and the defender one at the other. The analyzer strategy is a combination of the two. The reactor strategy is excluded from the continuum since it represents an organization having, no specific strategy identified. This last type is expected to impede organizational performance.

Organizations opting for the prospector strategy wish to have access to the largest possible market. They are characterized by their repeated efforts to innovate and bring about possible changes in their industry. Organizations selecting the defender strategy have a restricted market and stress production efficiency. They emphasize the excellence of their products, the quality of their services, and their lower prices. Organizations choosing the analyzer strategy do all of the above, but in moderation. Finally, organizations having a reactor strategy ignore new opportunities, nor can they maintain markets already acquired or take true risks.

Several empirical studies have used Miles and Snow's typology (1978) (Snow & Hrebiniak, 1980; Hambrick, 1983; Conant, Moksa & Burnett, 1989; Namiki, 1989; Smith, Guthrie & Chen, 1989; Tavakolian, 1989; Shortell & Zajac, 1990; Thomas, Litschert & Ramaswamy, 1991; Parry & Parry, 1992; Abernethy & Guthrie, 1994; Julien et al., 1996, Karimi et al, 1996). The presence of the four strategic types vary depending upon the industry, the sample size or the other constructs linked to business strategy. Among those studies, some have used an item-based approach (Segev, 1987; Conant et al., 1989; Namiki, 1989; Smith et al., 1989; Thomas et al, 1991), whereas others have used the self-typing approach (Snow & Hrebiniak, 1980; Tavakolian, 1989; Shortell & Zajac, 1990; Parry & Parry, 1992; Julien et al., 1996; Karimi et al., 1996).

METHODOLOGY

The instrument used to measure Miles and Snow's typology in this study was taken from Segev (1987) which uses 25 items on a Likert-type scale varying from I to 7 (highly disagree to highly agree). This instrument was chosen among others because of its content validity, characterizing all four types of business strategy, and was the only one readily made available to researchers through its publication. Following in-depth interviews used to pre-test the research instrument, questionnaires were sent to a sample 1,949 Canadian firms. These companies were listed in Dun & Bradstreet's directory. The selection criteria were to have more than 250 employees and to come from various branches of industry. A total of 301 companies returned the questionnaire addressed to the CEO for a final response rate of 15.4%.

RESULTS

Given the research objectives, a confirmatory factor analysis approach was adopted, using, Wold's (1982) PLS ("partial least squares") implementation of structural equation modeling. Such an approach is based on a priori' information about the structure of the business strategy construct. The structural model estimation and results provide assessments of unidimensionality and convergent validity, reliability, discriminant validity, and predictive validity of this construct.

The structural model to be solved for unidimensionality and convergent validity can be defined as x = [LAMBDA][xi] + [delta] where x is a vector of the 25 observed variables (indicators or items), [xi] is a vector of the 4 latent variables (traits or factors), [delta] is a vector of random (measurement) errors, and [LAMBDA] is a 25 by 4 matrix of factor loadings ([lambda]) relating the observed variables to the latent variables. The initial PLS estimates obtained for [LAMBDA] are presented in Table 1. Six items (D4, D5, D7, AN2, AN3, PR5) were dropped because of their weak loadings on their hypothesized factors. A seventh one (ANI: "The firm adopts quickly promising innovations in the industry") was transferred from the analyzer to the prospector dimension as it loaded more strongly on the latter and could plausibly be attributed to it on a theoretical basis. The results obtained from estimating the modified model, based on the 19 remaining items, are presented in Table 2. Based on the new values obtained, it can be concluded that the four types of business strategy achieve unidimensionality and convergent validity.

Within the structural equation modeling framework, construct reliability ([rho]) is conceptualized as the proportion of measured variance in the observed variables attributed to their underlying latent variable, and is calculated as the ratio of factor variance to the sum of factor and error variance. Thus, a [rho] value greater than the recommended 0.7 value indicates that the factor captured at least 70% of the measurement variance. Returning to Table 2, one sees this to be the case for all four dimensions in the modified model.

Discriminant validity refers to the extent to which the measures of the four types of business strategy are unique from each other. This is verified when the square root of the average variance extracted by a factor from its associated items (i.e., [[[[SIGMA].sub.i=1,q] [[lambda].sub.i,j.sup.2] / q].sup.1/2]) is inferior to the correlation (i.e.,[[shared variance].sup.1/2]) between this factor and any other factor. Looking at Table 3, this is shown to be the case for all four dimensions, thus confirming their distinctive characteristics.

When looking at the predictive validity of a construct, one ascertains if its measures relate to an antecedent or consequent construct in accordance to the theoretical framework from which it emanates. In this study, given Miles and Snow's (1978) arguments on the links between their typology and business performance and the use of this typology in subsequent empirical studies, the four types of business strategy were related to two fundamental dimensions of performance, namely growth and profitability, using Venkatraman's (1989) perceptual measure (3 and 5 items respectively). The results of correlating the business strategy and performance constructs are presented in Table 4 and discussed below.

DISCUSSION

Overall, the data analyzed seem to adequately support the notion that the four types of business strategy are unidimensional, and that the operational indicators used here show reliability and construct validity. One can further discuss the behavior of these indicators in terms of statistical and theoretical criteria by examining the relationships among the types, as well as between each type and performance. Looking at the intercorrelations of the four dimensions estimated by PLS (Table 3), one finds as expected that the more firms exhibit reactive behaviors, the less they act in both a prospective and an analytical manner. Whereas firms that exhibit more prospective behaviors also tend to be more analytical and less defensive. This empirical pattern of interrelationships among the four types of strategic activities thus appears to be coherent with Miles and Snow's underlying assumptions on strategic types.

Results presented in Table 4 show how each type of business strategy relates to business growth in terms of sales and market share increases, and to profitability in terms of financial position relative to the competition. As predicted by the theory, reactor and prospector business strategies are respectively associated here with inferior and superior performance. However, the relationship of both defender and analyzer business strategies with performance was not significant. One could tentatively argue here from a contingency theory point of view. Being less extreme, more "middle-of-the-road", defender and analyzer business strategies would need to match other fundamental aspects of the organization to be effective, and thus cannot be shown to increase performance without taking into account other dimensions such as the firm's environment, structure and information technology.

CONCLUSION

It can be concluded from this study that Miles and Snow's typology of business strategy, as operationalized by Segev, is a valid instrument once modified through statistical analysis. The modifications consist in removing inconsistent items and assigning one item to a different strategic type. These changes may be due to the fact that Segev's instrument had been tested with students, and thus possibly lacked external validity. An evolution in the concept of business strategy, between the time the measure was designed (1987) and its present testing (1999) might be another reason. Overall, the redesigned instrument is now considered appropriate to pursue research on the strategic alignment of information technology.

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Anne-Marie Croteau, Concordia University

Louis Raymond, Universite du Quebec a Trois-Rivieres

Francois Bergeron, Universite Laval Table 1 : Unidimensionality, convergent validity, and reliability of initial model factor reactor defender analyzer prospector item R1 .75 (a) - - - R2 .73 - - - R3 .67 - - - RI - .69 - - D2 - .68 - - D3 - .62 - - D4 - .07 - - D5 - .18 - - D6 - .61 - - D7 - .25 - - D8 - .65 - - D9 - .59 - - AN1 - - .61 .67 AN2 - - - - AN3 - - - - AN4 - - .68 - AN5 - - .34 - AN6 - - .75 - PRl - - - .67 PR2 - - - .52 PR3 - - - .59 PR4 - - - .68 PR5 - - - .13 PR6 - - .66 PR7 - - .71 [rho] .76 .74 .69 .78 (a) loading of observed variable on latent variable (a dash indicates a loading inferior to 0.40) Table 2 : Unidimensionality, convergent validity, and reliability of modified model factor reactor defender analyzer prospector item R1 .75 R2 .73 - - - R3 .67 - - - D1 - .70 - - D2 - .71 - - D3 - .59 - - D4 - (removed) - - D5 - (removed) - - D6 - .61 - - D7 - (removed) - - D8 - .64 - - D9 - .57 - - AN1 - - (removed) .69 AN2 - - (removed) - AN3 - - (removed) - AN4 - - .82 - AN5 - - .43 - AN6 - - .70 - PRl - - - .47 PR2 - - - .53 PR3 - - - .64 PR4 - - - .69 PR5 - - - (removed) PR6 - - - .71 PR7 - - - .8l [rho] (b) .76 .80 .70 .84 (b) reliability coefficient = [([SIGMA][lambda]).sup.2]/[([SIGMA][lambda]).sup.2]+ [([SIGMA][lambda]).sup.2] Table 3 : Assessment of discriminant validity Strategy reactor defend analyzer prospect reactor .72 (a) defender .08 (b) .64 analyzer -.32 *** .10 .67 prospect -.52 *** -.21 ** .30 *** .66 * : p<.05 ** : p<.01 *** : p<.001 (a) diagonal : [(average variance extracted from the observed variables by the latent variable).sup.1/2] = ([[[SIGMA][lambda].sup.2]/q).sup.1/2] (b) subdiagonals : correlation between latent variables = [(shared variance).sup.1/2] (c) correlation with the two Performance dimensions (whose measurement was assessed similarly to the Strategy dimensions, satisfying criteria of reliability, unidimensionality, convergent and discriminant validity) Table 4 : Assessment of predictive validity Strategy reactor defend analyzer prospect With Perform (c) Growth -.30 *** -.01 -.02 .36 *** Profit -.15 * -.01 -.02 .24 *** * : p<.05 ** : p<.01 *** : p<.001 (a) diagonal : [(average variance extracted from the observed variables by the latent variable).sup.1/2] = ([[[SIGMA][lambda].sup.2]/q).sup.1/2] (b) subdiagonals : correlation between latent variables = [(shared variance).sup.1/2] (c) correlation with the two Performance dimensions (whose measurement was assessed similarly to the Strategy dimensions, satisfying criteria of reliability, unidimensionality, convergent and discriminant validity)