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Abstract
This dissertation focuses on the concept of liability of foreignness (LOF) and explores whether a multinational enterprise (MNE) can reduce this implied cost by explicitly stating the country of origin (COO) on its product label. Prior research studies have focused on the manufacturing country as the COO, but this study focuses on both the country that designed the product and the country that ultimately manufactured it. Empirical research has shown that foreign organizations incur additional costs when entering a local market. These costs primarily stem from unfamiliarity by the organization with the local market and the local consumers with the company. The study aims to explore whether an organization can reduce these implied costs in a new market by either designing or manufacturing its product in countries that are seen positively by local consumers.
Specifically, an experiment was conducted to test whether the product country image (PCI) positively or negatively affects the willingness to buy said product; consumer cosmopolitanism (COS), ethnocentrism (CET), and materialism (MAT) are treated as antecedents to PCI. Age, gender, education, and country development status are treated as moderators to PCI; product type and brand image are control variables.
A fictitious brand called Raeden was created to test the willingness to buy earphones (in-ear headphones) introduced into the local market. This study will add to the literature on LOF, location choice, and consumer preference. By understanding the degree of COS, CET, and MAT of the local population, an organization can position itself for success.
Similarly, if management understands which production/design country gives it the best advantage in the local market, it might wish to manufacture/design the product in that location. The study uses previously established instruments to test and measure the constructs quantitatively. The data was collected through an electronic survey administered through Amazon MTurk. The analysis was mainly done using a structural equation model and analysis of variance.