تنظیمات محیط بازار، استراتژی های رقابتی، فن آوری تولید و سیاست های مدیریت منابع انسانی : تجزیه و تحلیل مناسب دو صنعت و دو کشور
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|3497||2003||32 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Scandinavian Journal of Management, Volume 19, Issue 1, March 2003, Pages 31–62
In this paper an attempt is made to gain further insight into the environment–strategy–performance linkages. A framework is developed to relate managers’ perceptions of their market environment and competitive strategies to the (advanced) production technologies and human resource management (HRM) policies adopted by their firms. Data from 12 Dutch and 8 British companies in the chemical and food & drink industries reveals that firms with coherent environment–strategy–technology–HRM configurations outperform rivals with incoherent profiles. Further, refined typologies of manufacturing technologies and HRM policies are proposed.
A central theme of strategy literature has been and still is the alignment of generic and specific strategies to the environmental context. The assumption underlying the great majority of these so-called contingency studies is that a fit between environment, strategy and structure has to be established if the organization is to perform effectively. Over the years this hypothesis has been supported by an innumerable number of empirical studies (e.g., Dess & Davis, 1984; Miller, 1988; Conant, Mokwa, & Rajan Varadarajan, 1990; Powell, 1992; Schroeder, Congden, & Gopinath, 1995; Ward, Bickford, & Keong Leong, 1996). Our main reason for adding another study to the impressive stock of existing research is that most alignment studies focus on a few elements of the environment–strategy–structure relationship only. Rarely have they addressed more than a single internal element at the functional strategy level (Zajac, Kraatz, & Bresser, 2000). Although there is a somewhat larger body of research in the ‘gestalt’ perspective that addresses configurations of mainly environmental, strategy and structural variables simultaneously (e.g., Miller & Friesen, 1984; Chakravarthy, 1986; Roth, 1992), the focus in this tradition is not on the examination of the specifics of the underlying separate relationships. Since the effective implementation of strategy involves the alignment of many different elements, there is a need for multi-dimensional empirical studies that combine insights from fit as ‘gestalt’ and fit as matching perspectives (Venkatraman, 1989; Ward, Bickford, & Keong Leong, 1996). The purpose of this study is therefore to explore empirically the relationship between elements of the market environment, competitive strategy and two functional strategies. Specifically, the present study incorporates manufacturing technology and human resource management (HRM) variables in the general environment–strategy–performance framework, and examines this ‘fit’ argument using a British–Dutch data set. The well-established contingency prediction is, then, that firms with coherent environment–strategy–technology–HRM configurations outperform their rivals whose profiles are incoherent. The current study thus provides a contribution to renewing the “strategy–structure–performance paradigm” (Galunic & Eisenhardt, 1994) by: (i) applying a multi-variable and complex model of fit; (ii) taking account of multi-faceted and potentially reciprocal contingencies; and (iii) developing new concepts of co-alignment elements by proposing alternative typologies. The approach adopted in this paper consists of three broad steps. After discussing our chosen perspective on fit and briefly presenting the sample and methodology, we come to step 1, which consists of an empirical specification of the core variables; step 2 then builds on this specification and offers some propositions on the potential relationships between the variables; step 3 comprises a discussion of the results.
نتیجه گیری انگلیسی
The aim of this study was to examine empirically the relationship between the market environment, competitive strategy and functional strategies in the areas of manufacturing technology and HRM. To accomplish this aim, the study has been organized in three main steps. In the first step, the core variables were empirically specified. In the second step, five propositions were generated regarding the relationships between the variables, in line with the perspective on fit represented by the integration school. Four propositions described the relation between the environmental and the organizational aspects on the one hand and strategy on the other hand, while the fifth proposition took up the link with performance. Finally, in the third step, our findings with respect to the propositions are presented. In both industries the profiles defined by means of Propositions 1–4 do seem to be present in many of the companies in our sample. Proposition 5, whereby companies that aligned the different contingency elements into a perfectly consistent profile were expected to achieve an above-average performance, is also in general confirmed by our analysis. In the food & drink industry, three companies, i.e. companies 10 and 11 in cluster I and company 14 in cluster II, all with an ideal-type fit, exhibited an above-average performance. In the chemical industry two above-average performing companies with ideal-type alignments—company 3 in cluster II and company 5 in cluster IV—were detected. Further, two companies for which an ideal-type fit was doubtful in the sense that they may have over invested in either production technology or HRM are among the above-average performers. Food & drink company 15 employs true HRM and flexible continuous process production, where traditional personnel management and some sort of less sophisticated production technology would have been sufficient. Chemical company 7 had flexible continuous process production, where the requirements of the market environment and the competitive strategy could have been met by a less advanced production system. These results point to an interesting phenomenon reminiscent of the distinction drawn by Chakravarthy (1986) for measuring the quality of a firm's transformation. The author identifies ‘adaptive specialization’ and ‘adaptive generalization’. Adaptive specialization refers to the process of improving the goodness of fit in a given situation. This applies to all the companies with an ideal-type match in our sample. Adaptive generalization refers to investment in a surplus of ‘slack resources’, which enables the firm to improve its ability to adapt to changing conditions. Such an approach can in fact be viewed as an investment in dynamic capabilities (Miles & Snow, 1994; Teece, Pisano, & Shuen, 1997). According to the dynamic capabilities approach a firm can achieve a competitive advantage from its ability to adapt management capabilities and form its difficult-to-copy combinations of organizational, functional and technological skills. This notion is supported by research into the relationship between manufacturing flexibility and human resource policies (Upton, 1995; Youndt et al., 1996). This apparently applies to our sample's company 15, which employs an ‘overly’ advanced technology-HRM combination. Company 7, according to this reasoning, could enhance its performance by improving its technology-HRM fit. We should be cautious in applying this kind of argument to the firms in our sample however, because the use of ROS as the performance measure means that only companies that have successfully created and utilized these slack resources are recognized as such. Firms that were in the process of investing in manufacturing technology and/or HRM, and were therefore suffering from a lower level of performance in the year investigated, will not be detected. Besides the companies that had performed above average, two reactors (Miles & Snow, 1978) or ‘stuck-in-the-middle’ companies (Porter, 1980) were identified. Food & drink company 18 and chemical firm 2 both suffer from internal inconsistencies that are not matched either by the competitive strategy or the market environment. As our propositions predict, both companies suffer from inferior performance. Essentially, the present study offers a twofold contribution to the literature. First, the analysis applies a multi-fit framework that takes account of functional strategies regarding manufacturing technology and HRM policy, as well as the standard contingencies of competitive strategy and market environment. The results presented in this study are promising in terms of efforts to integrate the fit-as-matching and fit-as-gestalt perspectives. Second, on a basis of the data two refined typologies have been developed, namely for manufacturing technologies and HRM policies. Given the prominence of both these elements in running a firm in the modern era of hypercompetition (D’Aveni, 1994) and information revolution (Shapiro & Varian, 1999), any contribution to a more profound understanding of the performance implications of the two functional strategies yields a certain added value. The subtle interplay between the four multi-faceted contingencies is clearly so complex that the realization of a fit certainly cannot be taken for granted, as the evident failures in our sample have revealed. The realization of fit is probably a nice example of the intangible-assets-bundle argument that is central to the resource-based view of the firm (Wernerfelt, 1984; Maijoor & Van Witteloostuijn, 1996; Pennings, Lee, & Van Witteloostuijn, 1998). That is to say, firms that are successful in producing fit can benefit from the sustainable rent potential that accompanies the difficult-to-imitate bundles of resources reflected in the causal ambiguities of the fit phenomenon (Dierickx & Cool (1986a) and Barney (1986b); Dierickx & Cool, 1989). Although the results are promising, they remain subject to the limitations of an exploratory research design. The best way to strengthen the approach adopted in this study would be to focus on the following three issues. 1. The analysis would benefit from a larger sample of firms. It would then be easier to explore how great a percentage performance is explained by the six types of fit investigated, or what type of fit contributes most or least to performance. At this point the data set is too limited to permit parametric multi-variate analyses. 2. In addition to the current data on intended strategy it would be interesting to get some measures of the strategy that is actually implemented. An example of this would be chemical company 1, where we expect the competitive strategy actually implemented to differ from the one formally stated, since the functional strategies regarding manufacturing technology and HRM policy are internally consistent and aligned with the environment. 3. The measure of performance used could be extended to a multi-faceted proxy that as well as multiple measures of financial performance, also includes non-financial data. Since the objectives of the companies’ strategies are hardly ever limited to financial goals, performance measures should include this broader perspective. The analysis with respect to Proposition 5 in particluar could benefit from such an approach.