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Development of a firm export performance measurement model using a hybrid multi-attribute decision-making method

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Date
2020
Author
Dahooie, Jalil Heidary
Meidutė-Kavaliauskienė, Ieva
Vanaki, Amir Salar
Podviezko, Askoldas
Abadi, Elham Beheshti Jazan
Metadata
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Abstract
Purpose- The present study is aimed to develop a firm export performance measurement model. Increased levels of globalization are forcing firms, especially SMEs (i.e., Small and Medium-sized Enterprise) and entrepreneurial firms to enter new markets and increase their exports. Consequently, export performance measurement has become a vital tool for achieving competitive advantages, and this type of measurement is considered an important topic of research in the field of international marketing. However, the literature lacks a comprehensive framework for measuring export performance even though many criteria for gauging this performance’s parameters have been discovered and applied. Methodology - A literature review was conducted and the most important criteria for export performance measurement was identified using weights obtained by stepwise weight assessment ratio analysis method. Then, the export performance of 5 firms was evaluated using the additive ratio assessment method with interval-valued triangular fuzzy numbers. Findings-The 15 most significant criteria were identified and categorized into three dimensions: economic, strategic, and other. The strategic dimension was identified as the most important, while the criteria “strategic goals achievement” and “return on investment” were found to be the most relevant. Practical implications- A comprehensive framework including a definitive set of the most prominent, useful evaluation criteria was established which enables both scholars and practitioners to assess export performance. Originality/value-The current study attempts to fill the gaps in the literature by presenting a comprehensive framework for export performance measurement.
Issue date (year)
2020
URI
https://etalpykla.vilniustech.lt/handle/123456789/147959
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  • Straipsniai Web of Science ir/ar Scopus referuojamuose leidiniuose / Articles in Web of Science and/or Scopus indexed sources [7946]

 

 

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