مدل سازی هوشمند بلوغ کسب و کار الکترونیکی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|3737||2007||16 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 32, Issue 2, February 2007, Pages 687–702
E-business has a significant impact on managers and academics. Despite the rhetoric surrounding e-business strategy formulation mechanisms, which support reasoning of the effect of strategic change activities to the maturity of the e-business models, are still emerging. This paper describes an attempt to build and operate such a reasoning mechanism as a novel supplement to e-business strategy formulation exercises. This new approach proposes the utilization of the fuzzy causal characteristics of Fuzzy Cognitive Maps (FCMs) as the underlying methodology in order to generate a hierarchical and dynamic network of interconnected maturity indicators. By using FCMs, this research aims at simulating complex strategic models with imprecise relationships while quantifying the impact of strategic changes to the overall e-business efficiency. This research establishes generic adaptive domains – maps in order to implement the integration of hierarchical FCMs into e-business strategy formulation activities. Finally, this paper discusses experiments with the proposed mechanism and comments on its usability.
Today, there is an increasing demand for a strategic-level assessment of e-business capabilities that can be assembled and analyzed rapidly at low cost and without significant intrusion into the subject enterprises. The benefits from completing such an exercise are quite straightforward, for instance, identification of significant strengths and weaknesses, establishment of a rationale for action, a reference point for measuring future progress, etc. This paper proposes a novel supplement to strategic-level maturity assessment methodologies based on fuzzy cognitive maps (FCMs). This decision aid mechanism proposes a new approach to supplement the current status analysis and objectives composition phases of typical e-business strategy formulation projects, by supporting “intelligent” modeling of e-business maturity and “intelligent” reasoning of the anticipated impact of e-business strategic change initiatives. The proposed mechanism utilizes the fuzzy causal characteristics of FCMs as a new modeling technique to develop a causal representation of dynamic e-business maturity domains. This research proposes a holistic set of adaptive domains in order to generate a hierarchical network of interconnected e-business maturity indicators. The proposed mechanism aims at simulating the operational efficiency of complex hierarchical strategy models with imprecise relationships while quantifying the impact of strategic alignment to the overall e-business efficiency. Also, this paper proposes an updated FCM algorithm to model effectively the hierarchical and distributed nature of e-business maturity. This application of FCMs in modeling the maturity of e-business is considered to be novel. Moreover, it is the belief of this paper that the fuzzy reasoning capabilities enhance considerably the usefulness of the proposed mechanism while reducing the effort to identify precise maturity measurements. The proposed model has both theoretical and practical benefits. Given the demand for effective strategic positioning of e-business initiatives, such a succinct mechanism of conveying the essential dynamics of e-business fundamental principles is believed to be useful for anyone contemplating or undertaking an e-business strategy formulation exercise. Primarily, the proposed model targets the principle beneficiaries and stakeholders of strategy formulation projects (enterprise top administration, strategic decision makers, internal auditors, etc) assisting them to reason effectively about the status of e-business maturity metrics, given the (actual or hypothetical) implementation of a set of strategic changes. Nevertheless, the explanatory nature of the mechanism can prove to be useful in a wider educational setting. This paper consists of five sections. Section 2 presents a short literature overview, Section 3 presents an overview of the FCM based system, while Section 4 discusses the new approach to e-business maturity modeling based on FCMs. Finally, Section 5 concludes this paper and briefly discuses future research activities.
نتیجه گیری انگلیسی
This paper presented an intelligent supplement to typical e-business strategy formulation methodologies based on fuzzy cognitive maps (FCM). This decision aid mechanism proposed a new domain-based approach to supplementing the current status analysis and objectives setting phases of typical e-business strategy formulation projects, by supporting “intelligent” modeling of e-business maturity and “intelligent” reasoning of the anticipated impact of strategic change initiatives. By using FCM, the proposed mechanism drew a causal representation of e-business maturity principles; it simulated the operational efficiency of complex strategy models with imprecise relationships and quantified the impact of strategic change to the e-business model. Preliminary experimental results indicated that the mechanism did not provide fundamentally different estimates than expert decisions. It provided reasonably good estimates of the impact of strategic change initiatives to the e-business model, while the maintenance effort did not pose as a prohibitory factor. Moreover, the decomposition of maturity metrics supported reasoning of the performance roadmap and the complex relationships that affect the overall e-performance. The proposed mechanism should not be regarded only as an effective e-business modeling support tool. Its main purpose is to drive strategic change activities rather than limit itself to qualitative simulations. Moreover, the proposed mechanism should not be seen as an “one-off” decision aid. It should be a means for setting a course for continuous strategic alignment (Langbert & Friedman, 2002). Future research will focus on conducting further real life experiments to test and promote the usability of the tool, but also to identify potential pitfalls. Furthermore, future research will focus on the automatic determination of appropriate fuzzy sets (e.g. utilizing pattern recognition, mass assignments, empirical data, etc.) for the representation of linguistic variables to suit each particular e-business project domain. Finally, further research will focus on implementing backward map traversal, a form of adbuctive reasoning (Flach & Kakas, 1998). This feature offers the functionality of determining the condition(s) Cij that should hold in order to infer the desired Cj in the causal relationship View the MathML sourceCij→wjkCk. Incorporating integrity constraints reduces the search space and eliminates combinatory search explosion. Backward reasoning has been tested extensively in other applications and its integration in the proposed methodology may prove beneficiary.