By combining the advantages of systematic and behavioural-based international market selection approaches, we build and test an International Market Selection (IMS) decision process method that is able to capture, within a small firm’s risk-averse setting, the entrepreneur’s experience, reduce cognitive biases, and preserve the flexibility of the decision. The unit of analysis is the IMS decision process of a small firm venturing abroad. We adopt a ranking approach based on three-step screening. We assess the markets through a multi-criteria approach with a wider set of variables aggregated within a tree-shaped model. To obtain the ranking we use a Fuzzy Expert System (FES) as an evaluative tool. The results show that the proposed decision method is consistent with the entrepreneur’s strategic orientation and experience, while preserving the flexibility requested for decision making in small firms. Unlike traditional behavioural IMS approaches, the method demonstrates an ability to reduce the cognitive biases associated with the use of a limited set of variables and unreliable evaluation models. The single-case-study approach limits generalization of the findings. The proposed methodology helps the decision maker to improve the quality of the IMS decision by reducing the effect of cognitive biases that usually affect traditional behavioural models. For the first time, a decision-process methodology based on an FES is applied to a small firm’s IMS problem.

International market selection for small firms: a fuzzy-based decision process / Marchi, Gianluca; Vignola, Marina; Facchinetti, Gisella; Mastroleo, Giovanni. - In: EUROPEAN JOURNAL OF MARKETING. - ISSN 0309-0566. - STAMPA. - 48 issue 11/12:(2014), pp. 2198-2212. [10.1108/EJM-09-2012-0512]

International market selection for small firms: a fuzzy-based decision process

MARCHI, Gianluca;VIGNOLA, Marina;FACCHINETTI, Gisella;MASTROLEO, Giovanni
2014

Abstract

By combining the advantages of systematic and behavioural-based international market selection approaches, we build and test an International Market Selection (IMS) decision process method that is able to capture, within a small firm’s risk-averse setting, the entrepreneur’s experience, reduce cognitive biases, and preserve the flexibility of the decision. The unit of analysis is the IMS decision process of a small firm venturing abroad. We adopt a ranking approach based on three-step screening. We assess the markets through a multi-criteria approach with a wider set of variables aggregated within a tree-shaped model. To obtain the ranking we use a Fuzzy Expert System (FES) as an evaluative tool. The results show that the proposed decision method is consistent with the entrepreneur’s strategic orientation and experience, while preserving the flexibility requested for decision making in small firms. Unlike traditional behavioural IMS approaches, the method demonstrates an ability to reduce the cognitive biases associated with the use of a limited set of variables and unreliable evaluation models. The single-case-study approach limits generalization of the findings. The proposed methodology helps the decision maker to improve the quality of the IMS decision by reducing the effect of cognitive biases that usually affect traditional behavioural models. For the first time, a decision-process methodology based on an FES is applied to a small firm’s IMS problem.
2014
48 issue 11/12
2198
2212
International market selection for small firms: a fuzzy-based decision process / Marchi, Gianluca; Vignola, Marina; Facchinetti, Gisella; Mastroleo, Giovanni. - In: EUROPEAN JOURNAL OF MARKETING. - ISSN 0309-0566. - STAMPA. - 48 issue 11/12:(2014), pp. 2198-2212. [10.1108/EJM-09-2012-0512]
Marchi, Gianluca; Vignola, Marina; Facchinetti, Gisella; Mastroleo, Giovanni
File in questo prodotto:
File Dimensione Formato  
EJM-09-2012-0512.pdf

Accesso riservato

Tipologia: Versione pubblicata dall'editore
Dimensione 209.35 kB
Formato Adobe PDF
209.35 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1006713
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 22
  • ???jsp.display-item.citation.isi??? 17
social impact