The UN categorises forty nine countries of the world as least-developed nations because of their low gross national income (GNI) per capita, weak human assets and high degree of economic vulnerability (UNCTAD, 2013). In particular, developing countries are classified into lower-middle income and low-income countries, and LDCs fall into the latter category (World Bank, 2007). According to UN- OHRLLS (2014; p25), ‘‘these countries are generally characterised by low per capita income, low human capital development, and structural bottlenecks that hinder economic growth and human development. They tend to be susceptible to external shocks, such as in terms of trade and financial flows, and internal shocks, including those related to climate and conflict, given their inability to prevent or ensure against these’’. Therefore, it is argued that LDCs not only differ markedly from developed nations in terms of economic characteristics, but also they are considered as a discrete
One of the salient features of LDCs is that the share of agriculture sector in both gross domestic product (GDP) and employment is substantial. Although the majority of developing countries are agrarian (Todaro & Smith, 2003), the share of agriculture in GDP has declined, while there has been an increase in the share of the industrial sector during the past decade of this century (UNCTAD, 2013). Promoting economic growth, reducing poverty and eliminating vulnerabilities of LDCs through several strategies and support measures stemming from national and major international governance institutions are evident in the development literature. While these countries have employed several strategies and support measures in their development pursuits, three forms of initiatives i.e., import substitution3, export promotion and creating an economic environment which is conducive to private enterprise, are particularly prominent (e.g. Acs & Virgill, 2009).
Yet, entrepreneurship in LDCs is often constrained by several adverse conditions e.g., poorly performing government institutions, insecure property rights, lack of law and order, corruption, policy unpredictability, and limited access to public services (Altmann, 2010). Despite various adversities, evidence suggests that export activities undertaken by private firms play a critical role in the economic growth and development of many of these countries. For example, Olugbenga et al (1996) in the context of 12 sub-Saharan African countries have shown that stimulating economic growth is dependent upon an outward-looking strategy of exports expansion. Similarly, Akhter (2015) found a positive association between the export activities and economic growth of Bangladesh. Governments in developing countries have realised that competing beyond national borders is not an option; rather it is an economic necessity (e.g. Rutashobya & Jaensson, 2004). A review of the literature suggests that governments in many of these countries have responded by coming up with policy and administrative reforms to encourage international engagement of domestic firms. Deregulations and privatisation of key economic sectors and industries can be attributed as critical policy reforms initiatives undertaken by many governments of LDCs. The policy initiative involving the promotion of entrepreneurship in
development mechanism in recent years (World Bank, 2005; cited in Acs & Virgill, 2009; p4). Although entrepreneurship and international growth aspiration of LDCs’ firms are often constrained by various complexities, there has been very limited research exploring the factors affecting the rapid internationalisation of firms in this context.
1.5.2 Research Design and Method
Given the shortcoming highlighted above, the present study aims to develop and test a BGF emergence model in the context of an LDC. To achieve the aim of this study, data was collected from Bangladesh which is one of Asia’s least-developed nations. In particular, this study is an empirical investigation of firms involved in exporting from Bangladesh to international markets. The population is selected from the main economic industry in Bangladesh (i.e. the apparel industry). Firms were selected from the Bangladesh Garments Manufacturers & Exporters Association (BGMEA) and Bangladesh Knitwear Manufacturers & Exporters Association (BKMEA) directories. BGMEA and BKMEA are the two apparel industry associations in Bangladesh. Given the cross-sectional nature of the study, the present study includes those firms in the sample that were located in the capital city Dhaka and its suburbs. 2767 exporting firms were identified from BGMEA and BKMEA directories that were located in the Dhaka region during the time of the survey. Evidence suggests that several firms were closed due to financial and other management issues (Faroque & Takahashi, 2012). Of 2767 exporting firms, 10% were selected randomly to participate in the survey, which resulted in 277 firms. A total of 200 survey questionnaires were received from which 41 were eliminated from the analysis for a variety of reasons, for example questionnaires with missing values and respondents who do not have strong relationships with the founders. As a result 159 valid questionnaires were analysed, yielding a response rate of about 58%.
Since the aim of the present study is to develop and test a BGF emergence model, a quantitative method is adopted with application of the survey questionnaire instrument. The survey questionnaire was administered during the last quarter of 2013. Prior to administering the survey, the questionnaire
founders to obtain the data. However, it was not possible to reach all founders for a variety of reasons including their workloads, retirement and bereavement. Therefore, in those cases where the founders were not available, top executives (i.e. general managers and export managers) who had close contact with the founders were targeted as respondents. It is assumed that top executives who had close contact with the founders are most likely to be knowledgeable about the owners and the overall business circumstances. To confirm the extent of closeness, executives were asked to specify their relationship with the founders on a seven point Likert-scale (Question 15 in Section 1). Finally, collected data was analysed statistically using Statistical Package for Social Science (SPSS) software. In particular, the proposed hypotheses were tested through the application of a hierarchical multiple regression modelling technique. This statistical technique has been used extensively in those BGF studies where researchers intend to examine the cause and effect relationships among variables of interest (e.g. Kuivalainen et al., 2007; Mascherpa, 2011; Preece et al., 1999; Zhang et al., 2012).