RT Journal Article
T1 Evaluating the internationalization success of companies through a hybrid grouping harmony search-extreme learning machine approach
A1 Landa-Torres, Itziar
A1 Ortiz-García, Emilio G.
A1 Salcedo-Sanz, Sancho
A1 Segovia-Vargas, María J.
A1 Gil-López, Sergio
A1 Miranda García, Isabel Marta
A1 Leiva-Murillo, Jose María
A1 Del Ser, Javier
K1 Company internationalization
K1 Exporting performance
K1 Extreme learning machines
K1 Ensembles
K1 Harmony search
AB The internationalization of a company is widely understood as the corporative strategy for growing through external markets. It usually embodies a hard process, whichaffects diverse activities of the value chain and impacts on the organizational structure of the company. There is not a general model for a successful international company, so the success of an internationalization procedure must be estimated based on different variables addressing the status, strategy and market characteristics of the company at hand. This paper presents a novel hybrid soft-computing approach for evaluating the internationalization success of a company based on existing past data. Specifically, we propose a hybrid algorithm composed by a grouping-based harmony search (HS) approach and an extreme learning machine (ELM) ensemble. The proposed hybrid scheme further incorporates a feature selection method, which is obtained by means of a given group in the HS encoding format, whereas the ELM ensemble renders the final accuracy metric of the model.Practical results for the proposed hybrid technique are obtained in a real application based on the exporting success of Spanish manufacturing companies, which are shown to be satisfactory in comparison with alternative state-of-the-art techniques.
PB Institute of Electrical and Electronics Engineers
SN 1932-4553
YR 2012
FD 2012
LK https://hdl.handle.net/10433/22756
UL https://hdl.handle.net/10433/22756
LA en
NO I. Landa-Torres et al., "Evaluating the Internationalization Success of Companies Through a Hybrid Grouping Harmony Search—Extreme Learning Machine Approach," in IEEE Journal of Selected Topics in Signal Processing, vol. 6, no. 4, pp. 388-398, Aug. 2012, doi: 10.1109/JSTSP.2012.2199463
NO Departamento de Economía Financiera y Contabilidad. Universidad Pablo de Olavide.
DS RIO
RD May 30, 2026