32 resultados para Resource-Based View

em University of Queensland eSpace - Australia


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Firms have embraced electronic commerce as a means of doing business, either because they see it as a way to improve efficiency, grow market share, expand into new markets, or because they view it as essential for survival. Recent research in the United States provides some evidence that the market does value investments in electronic commerce. Following research that suggests that, in certain circumstances, the market values noninnovative investments as well as innovative investments in new products, we partition electronic commerce investment project announcements into innovative and noninnovative to determine whether there are excess returns associated with these types of announcements. Apart from our overall results being consistent with the United States findings that the market values investments in electronic commerce projects, we also find that noninnovative investments are perceived as more valuable to the firm than innovative investments. On average, the market expects innovative investments to earn a return commensurate with their risk. We conclude that innovative electronic commerce projects are most likely seen by the capital market as easily replicable, and consequently have little, if any, competitive advantage period. On the other hand, we conclude from the noninnovative investment results that these types of investments are seen as being compatible with a firm's assets-in-place, in particular, its information technology capabilities, a view consistent with the resource-based view of the firm.

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For most complex emergent technologies, product-market success depends on efficient linkages between changing lead innovators within the R&D process. In this paper, our unit of analysis is a complex high technology product and the system of alliance linkages formed to progress a product through R&D milestones. We present a model and evidence for advancing our understanding of how achieving early-to-market returns depends on systemic absorptive capacity. This systemic absorptive capacity is the cumulative efficiency in the use of absorptive capacity to link changing lead innovators across successive milestones in R&D product development. We advance propositions of how systemic absorptive capacity can explain performance differences between rival product development systems competing for early-to-market returns with similar products through accelerating speed to market, cost and quality advantages. These explanations are contrasted with the conclusions of previous studies that have focused on absorptive capacity of single firms or single alliances in RD.

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Resource-based views of the firm and in particular Kay's (Why Firms Succeed. Oxford: Oxford Univ. Press, 1995) model of sustainable competitive advantage have been used to advance an understanding of differences in the competitive advantage of private-sector firms. We extend the analysis to a public-sector firm where its major purpose includes engaging in public good by giving away its knowledge base and services. The case highlights the paradox that many public-sector organizations face in simultaneously pursuing public good and sustainable competitive advantage. While Kay's model is applicable for understanding intergovernmental agency competition, we find it necessary to incorporate resource dependency theory to address the paradox. Implications for theory and practice are provided. (C) 2002 Elsevier Inc. All rights reseved.

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In the last few years, transaction cost economics has become a popular theory within the construction research community. This approach has been singularly applied as a means to explain and predict phenomena concerning the construction firm, including its vertical boundaries. However, this is at a time when the chief proponents of transaction costs are urging researchers to take a pluralistic stance in relation to the theory of the firm. The aim of this paper is to develop a pluralistic approach to the vertical boundaries of the construction firm. In order to achieve this, an integrative framework is described, based on the development of the efficient boundaries problem and the capabilities approach to vertical integration. Specifically, this framework draws on the complementary strengths of transaction cost economics and the resource-based view. It is concluded that the potential relative merits of theoretical pluralism, in terms of the vertical boundaries of the construction firm, are sufficient grounds to motivate empirical testing of the predictions associated with the integrative framework of vertical integration presented

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Creating competitive industries has become one of the key tasks of governments. Different adaptation outcomes in industries across nations cannot be accounted for fully simply by an emphasis on firm-level capabilities, market-driven policies, or state-level policies. We propose an integrative framework that draws on both the strategic management and political economy literature to explain variations in national industrial competitiveness.. We discuss differences with respect to institutional characteristics and capabilities, competitive outcomes, conditions of best fit, and who bears the cost of industry adaptation.

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Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD