Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/465D75E7-B682-4F83-B4D2-06880BD38D08 | ||
| Year | 2012 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
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| Bibliographic Citation | G. Baltas, S.Tsafarakis, C. Saridakis, N. Matsatsinis." Biologically inspired approaches to strategic service design optimal service diversification through evolutionary and swarm intelligence models," J.of Service Res.,vol. 16 ,no. 2, pp. 186-201,Dec. 12.doi:10.1177/1094670512468215 https://doi.org/10.1177/1094670512468215 | ||
| Appears in Collections |
This article introduces nature-inspired modeling to strategic service management. It determines optimal service diversification through an evolutionary mechanism of natural selection and population genetics as well as a model of cooperative behavior and collective intelligence in swarms. Specifically, we design and implement Genetic and Particle Swarm Optimization algorithms to stated-preference data derived from a conjoint experiment measuring consumer preferences for service attributes in a retail setting. The proposed procedure provides key insights to strategic service management such as optimal service design, optimal mix of service offerings in terms of consumer demand, and local adaptation of service portfolios. It demonstrates how diversification meets heterogeneous customer preferences and how localized solutions address cross-country differences. The findings suggest that variation in service portfolios elevates customer utility, in the sense that diversified offerings better match heterogeneous customer needs. In an intuitive fashion, consumer diversity is such that a uniform service portfolio is inferior to differentiated offerings, especially with regard to salient service attributes. The results also illustrate that localized diversification strategies are necessary for multistore, multimarket operations. Our method has valuable implications for managers aiming to improve how they design their services. A new tool is introduced which handles tangible and intangible service elements and allows service design optimization by predicting which elements create the most compelling service contexts from a customer perspective. The tool also facilitates localized diversification decisions by adapting critical service attributes to local markets. Bio-inspired models shed new light on marketing phenomena and reveal opportunities for empirical research.
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