International Expansion Selection Model by Machine Learning - A Proprietary Model

Ping Chi Hsieh, Der Juinn Horng, Hong Yi Chang

Research output: Contribution to journalArticlepeer-review


This study aims to explain a simple but crucial complex problem often faced by multinational enterprises: why multinational companies choose to enter the markets of certain countries. Accordingly, this study developed an international expansion selection model by using the machine learning method. The priority targets for enterprises' international expansion and the strategic country groups for classification can be identified on the basis of ideas expressed in three primary business concepts, namely 'market attractiveness', 'enterprise' resources and capabilities' and 'customer-oriented approach'; the identified priority targets and strategic country groups are useful for multinational enterprises when designing different configurations for limited resources and can ultimately assist the business managers with making international business decisions. Models can elucidate the complexity behind enterprise decisions. By contrast, strategic grouping based on simple rules can aid the managers to make instantaneous decisions and respond according to the changing market. This study constructed an exclusive strategic model based on the international expansion strategy selection modes adopted by a leading Taiwan enterprise in electronics industry and the unique characteristics possessed by this enterprise.

Original languageEnglish
Pages (from-to)217-236
Number of pages20
JournalComputer Journal
Issue number2
StatePublished - 1 Feb 2022


  • complexity
  • international expansion
  • machine learning
  • resource-based view


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