淡江大學機構典藏:Item 987654321/55847
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    題名: Forecast Competitor Service Strategy with Service Taxonomy and CI Data
    作者: Liu, Chun-hsien;Wang, Chu-ching
    貢獻者: 淡江大學企業管理學系
    關鍵詞: Business strategy;CI typology;Competitive intelligence;Service process;Service taxonomy
    日期: 2008-08
    上傳時間: 2011-09-02 09:48:47 (UTC+8)
    出版者: W Yorks: Emerald Group Publishing Ltd.
    摘要: Purpose

    The paper aims to develop a service taxonomy model and a mathematical process to forecast a competitor's service business strategy in a multiple service business context by inputting CI data such as the profits of existing core services.
    Design/methodology/approach

    A qualitative method of literature review is adopted to build a service taxonomy model and form two propositions. Based on the multiple business process integration concept of the resource‐based view, a mathematical process constituted by service modules and weights is developed. Salient components of the competitor's service business are identified to forecast the competitor's service business strategy after utilizing optimization heuristics of 80/20 and large number rules.
    Findings

    The model is able not only to forecast a competitor's service business strategy, but can also help develop the firm's own new service strategy. The resources of the firm can then be realigned to counteract the competitor's strategy.
    Research limitations/implications

    The developed model is mainly applicable to service businesses. The collection and use of CI data must consider ethical issues, which might limit the sources of data.
    Practical implications

    To forecast a competitor's strategy correctly , good quality CI practice is necessary. Experienced people in the CI department are critical to the production of good quality forecasts.
    Originality/value

    The contribution to CI impact studies is that the mathematical forecasting process is developed based on
    關聯: European Journal of Marketing 42(7-8), pp.746-765
    DOI: 10.1108/03090560810877132
    顯示於類別:[企業管理學系暨研究所] 期刊論文

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