The impacts of information technology on business performance has been a focus of research in recent years. In this regard, contingency models based on the notion of “fit” between the organization's management of IT, its environment, strategy, and structure seem to show promise. Six perspectives are examined as they pertain to the relationships between the firm's environmental uncertainty, its strategic orientation, its structure, its strategic management of IT, and its performance, namely moderation, mediation and matching as bivariate approaches to fit, and covariation, profile deviation and gestalts as systems approaches. These relationships are analyzed by means of an empirical study of 110 small enterprises. Results obtained from applying and comparing the six perspectives illustrate their significant differences and confirm the need for conceptual and methodological rigor when applying contingency theory in strategic information technology management research.
Since the publication, in 1961, of Burns and Stalker's pioneering work, the idea that there is no one best way to manage an organization has been the underlying assumption of a great number of research models, in several areas of study. Organization theorists have focused on the study of contingency models that share the “underlying premise that context and structure must somehow fit together if the organization is to perform well” [2, p. 514]. In strategic management, the general axiom of contingency theory is that no “strategy is universally superior, irrespective of the environmental or organizational context” [3, p. 424]. Contingency models, which hypothesize that there is no best way to organize, have also been proposed and tested in IS, be it for studying strategies for information requirements determination [4], individual impacts of information technology [5], IT impact on learning [6], the impact of IT problem solving tools on task performance [7] and [8], or IT impacts on organization performance [9], [10] and [11].
While they agree that contingency theory has been an important contributor to the advancement of knowledge, several authors have deplored the fact that researchers were not cautious or consistent enough in defining the concept of fit — which is central to any contingency model — and in selecting the most suitable data analysis approach to a given definition of fit [2], [12], [13] and [14]. Definitional rigor is critical, since different conceptual definitions of fit imply different meanings of a contingency theory and different expected empirical results [2]. This lack of definitional and methodological rigor has led to inconsistent results and could eventually alter the very meaning of a theory [3], [13], [15] and [16].
Along the years, much effort has been put on understanding and clarifying the theoretical and methodological issues associated with contingency models. In organization theory for instance, Drazin and Van de Ven [2], and Van de Ven and Drazin [16] have examined different approaches to defining fit and to testing fit-based hypotheses. In a conceptual article, Venkatraman [3] proposed a classificatory framework for the concept of fit, wherein six different perspectives of fit are defined. This was done in an effort toward definitional clarity of the concept of fit and to help researchers draw the appropriate links between the verbalization of fit-based relationships and the statistical analyses chosen to test these relationships. The six fit perspectives and the related statistical analysis methods were illustrated by referring to previous studies in the domain of business strategy. Building on this work, Chan et al. [17] performed a comparative analysis of two of the six perspectives of fit defined by Venkatraman [3], in the particular context of the relationship between IT and organizational performance.
The present study pursues the previous efforts in conducting a comparative analysis of all six fit perspectives in the context of the IT–performance relationship. Moreover, it examines the contingency relationships between strategic orientation of the firm, strategic IT management, organizational structure, environmental uncertainty, and business performance. These relationships are analyzed by means of an empirical study of 110 firms. Alternative perspectives of fit are first presented followed by the study's theoretical background, methodology, a discussion of the results and their implications.
This study is the first to encompass the concept of “fit” in empirical strategic IT management research in such a comprehensive, systematic manner. While the relatively low response rate puts some limits on the generalizability of the study, results reinforce Venkatraman's contention that different conceptualizations, verbalizations, and methods of analysis of fit will lead to different results.
Relative to the theory, the results suggest that neglecting to specify the exact perspective of fit used in earlier studies may have often lead researchers to obtain contradictory, mixed, or inconsistent results. These various perspective are so singular in their nature, consequences, and explanatory power that they cannot be selected indifferently neither can they simply be labeled as competing theories. The results of this study on the conceptualization and analysis of fit lead us to recommend that future research clearly specify the type of fit examined, i.e., moderation, mediation, matching, covariation, profile deviation, or gestalts. Authors should also theoretically support their choice before conducting their study and discuss the results with respect to the theory and the selected perspective of fit. The results also suggest that a systems perspective of fit is richer and will provide fuller explanation that bivariate approaches. As to the choice of a particular systems approach, the profile deviation and covariation perspectives of fit appear to be better suited to theory testing while the gestalts perspective would be more appropriate to theory building.
