Abstract:
The study seeks empirical identification of factors underlying the successful export decision process of firms. Data from a cross-sectional field study were collected using a structured mail survey to 700 randomly selected small and medium-sized manufacturing firms in India. Particularly, the international market is affected by more complex and dynamic factors than domestic marketing; frequently being exposed to serious external uncertainties such as foreign market environment (i.e. trade barrier, political, economical, social, and cultural risks), as well as internal risks from within the organization itself. This study develops a structural equation model (SEM) to predict the export success of market entry mechanism. Through a comparative analysis of SEM with a multiple regression analysis and artificial neural network (ANN), SEM shows a more accurate prediction of performance because of its intrinsic ability to consider various risk variables in a systematic and realistic way. In addition, the use of SEM allows for visually depicting the paths of how those complicated variables are interrelated so as to promote the clear understanding of the complex system and its underpinned causes that critically affect the export performance success.
