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Forecast competitor service strategy with service taxonomy and CI data

Forecast competitor service strategy with service taxonomy and CI data 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 qualitative service taxonomical research. Key elements of the service process are identified as salient elements, which serve as the main focusing points in forecasting competitors' strategy. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Journal of Marketing Emerald Publishing

Forecast competitor service strategy with service taxonomy and CI data

Chun‐Hsien Liu; Chu‐Ching Wang
European Journal of Marketing , Volume 42 (7/8): 20 – Jul 25, 2008
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References (85)

Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
0309-0566
DOI
10.1108/03090560810877132
Publisher site
See Article on Publisher Site

Abstract

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 qualitative service taxonomical research. Key elements of the service process are identified as salient elements, which serve as the main focusing points in forecasting competitors' strategy.

Journal

European Journal of Marketing – Emerald Publishing

Published: Jul 25, 2008

Keywords: Competitive strategy; Marketing intelligence; Service industries; Management strategy; Forecasting

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