Volume 24 Issue 1 Article 1 March 2022 The Effects of Institutions on Emerging Market Firms’ International Assignment Location Decisions Iris Koleša University of Ljubljana, Faculty of Social Sciences, Ljubljana, Slovenia, iris.kolesa@fdv.uni-lj.si Anže Burger University of Ljubljana, Faculty of Social Sciences, Ljubljana, Slovenia, anze.burger@fdv.uni-lj.si Michael Dickmann Cranfield University, Cranfield School of Management, Cranfield, UK, m.dickmann@cranfield.ac.uk Follow this and additional works at: https://www.ebrjournal.net/home Part of the International Business Commons Recommended Citation Koleša, I., Burger, A., & Dickmann, M. (2022). The Effects of Institutions on Emerging Market Firms’ International Assignment Location Decisions. Economic and Business Review, 24(1). https://doi.org/ 10.15458/2335-4216.1294 This Original Article is brought to you for free and open access by Economic and Business Review. It has been accepted for inclusion in Economic and Business Review by an authorized editor of Economic and Business Review. ORIGINAL ARTICLE The Effects of Institutions on Emerging Market Firms' International Assignment Location Decisions Iris Kolesa a, Anze Burger a,*, Michael Dickmann b a University of Ljubljana, Faculty of Social Sciences, Ljubljana, Slovenia b Cranfield University, Cranfield School of Management, Cranfield, UK Abstract We investigate international assignment (IA) location decisions of emerging market firms as determined by the institutional contexts of their home and host countries. Using an institutional perspective, assignment patterns of the entire firm population in Slovenia to either other emerging or developed host countries in Europe are analysed. The findings show that both institutional quality and distance influence expatriation flows in firms from a low quality institutional context. These firms expatriate more to markets with high quality institutions and choose host countries with higher rather than smaller institutional distance for their IAs. We refine institutional theory with respect to host and home country institutional determinants of expatriation decisions by taking into consideration the particular features of emerging markets and their firms e separately and compared to developed markets and their firms. Keywords: Geographic labour mobility, Labour management, International assignments, Location choice, Internation- alization, Institutional theory, Emerging markets JEL classification: F2 Introduction W ith globalisation, firms have recorded anupsurge of international business activities (Baskaran et al., 2011). Operating across nation states has put immense pressure on international- ising businesses and their internationally mobile employees that have to adjust to multiple and diverse economic, political, legal, and social contexts (Black, Mendenhall & Oddou, 1991; Brookes et al., 2011; Zaheer, 1995). Characteristics of and differ- ences in institutional environments have been identified as some of the main barriers to business internationalisation (Hilmersson & Jansson, 2012) that also affect international staffing decisions by firms (Conti, Parente & de Vasconcelos, 2016; Gaur, Delios & Singh, 2007). Institutions as determinants of internationalisation strategies and the related staffing approaches are particularly relevant in emerging markets and for emerging market firms (Buckley & Tian, 2017; Chan, Isobe & Makino, 2008; Moreira & Ogasavara, 2018). This is because these firms' unfavourable domestic institutional environ- ments co-shape their capacities to engage in (inter- national) business and staffing and propel them to search for alternative ways to develop their competitive advantages compared to the often internationally more experienced firms from more stable and resource-rich developed market envi- ronments (see e.g. Buckley, Devinney & Louviere, 2007). Their host institutional environments also necessitate certain strategic adjustments e espe- cially when these environments are institutionally dissimilar to those at home (see e.g. Benito & Gripsrud, 1992). The concept of ‘emerging market economies’ refers to low-income, rapid-growth countries using eco- nomic liberalisation and adoption of a free-market system as the primary engine of growth (Hoskisson et al., 2000). While substantial work has examined the Received 10 April 2020; accepted 30 July 2020. Available online 17 March 2022 * Corresponding author. E-mail addresses: iris.kolesa@fdv.uni-lj.si (I. Kolesa), anze.burger@fdv.uni-lj.si (A. Burger), m.dickmann@cranfield.ac.uk (M. Dickmann). https://doi.org/10.15458/2335-4216.1294 2335-4216/© 2022 School of Economics and Business University of Ljubljana. This is an open access article under the CC-BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/). internationalisation and international staffing of developed market firms (see e.g. Ando & Paik, 2013; Chan et al., 2008; Gaur et al., 2007), little research has investigated the global expansion of emerging mar- ket firms and their related international staffing practices (for an exception see e.g. Zhu et al., 2018). Beyond a few authors (e.g. Ando & Paik, 2013; Gaur et al., 2007; Moreira & Ogasavara, 2018), there has also been limited research into home and host countries' institutional environments and their separate or combined impact on international as- signments (IAs). This is surprising, given the specific characteristics of emerging markets determining their firms' features and the stark differences be- tween emerging and developed markets that are likely to affect firms' international business and IA decisions (Buckley & Tian, 2017; Peng, Wang & Jiang, 2008; Scullion, Collings & Gunnigle, 2007). Our research sets out to address this gap and investigates emerging market firms' international staffing de- cisions as determined by home and host country institutional contexts. Emerging market economies are marked with weak, scarce, inadequate, unpredictable, volatile, uncodified, and poorly enforced institutions (Ahl- strom & Bruton, 2006; Chan et al., 2008) that can be detrimental to business performance (McMillan, 2008; Meyer et al., 2009). The market and institu- tional imperfections in emerging economies propel emerging market firms to (1) develop particular ownership advantages, such as flexibility, economic use of resources, home country embeddedness, and business, ethnic, and institutional relationship management and networking skills for access to resources controlled by others (Buckley et al., 2007; Jain, Lahiri & Hausknecht, 2013; Madhok & Key- hani, 2012); (2) take advantage of emerging market specific location advantages, such as cheap labour and natural resources (Buckley & Tian, 2017); and (3) capitalise on the home experiences-based resources (including the capability to recruit, shape, and motivate cost-effective employees and the knowl- edge of and the ability to operate in institutionally unstable and weak business environments) (Jain et al., 2013; Zeng & Williamson, 2007). The labour market deficiencies in emerging mar- kets in particular also impact the emerging market firms' international staffing and international assignment management. More specifically, they make it more challenging. Several factors support this claim. First, emerging market firms are marked with short internationalisation histories and predominantly domestic governance and career development (Jaklic, 2007; Meyer & Xin, 2018; Tung, 2007), which restricts the individuals' awareness of international career opportunities and reduces their willingness to expatriate as well as limits the firms' power relative to the internationally mobile recruits. Second, a negative country of origin image renders emerging market firms less competitive in their battle for best talent against developed market firms (see e.g. Alkire, 2014; Pettigrew & Srinivasan, 2012). Emerging market firms thus often use alternative international staffing practices, such as recruitment of host-country nationals with prior work experi- ence in the firm's country of origin or members of the diaspora living in the host country (Meyer & Xin, 2018). Third, because of the limited resources for investments in employee development and mobility, as well as underdeveloped human re- sources management business function and prac- tices in emerging market firms (see e.g. Svetlik et al., 2010),1 international assignments in these are likely to be limited in number (see e.g. Luo & Tung, 2007) and international assignees are likely to be required to master multiple and interdisciplinary dimensions of doing business (Svetlicic, 2006). International staffing and IAs in particular have nonetheless been recognised as a primary tool for addressing institutional differences between home and host markets (Collings, Scullion &Morley, 2007; Gaur et al., 2007) also for emerging market firms. With IAs, firms can control and coordinate their internationally dispersed operations, and thereby better balance the classic ‘global integration versus local responsiveness’ dilemma in international business (Caligiuri & Colakoglu, 2007). IAs enable firms to fill positions when (adequately skilled or sufficient) local labour is not available; facilitate knowledge development, sharing, and transfer (Edstr€om & Galbraith, 1977; Minbaeva & Michai- lova, 2004); and assist coordination of an enterprise's network by linking its internationally dispersed units through different forms of control (e.g. direct surveillance, socialisation of host employees, and development of internal informal communication networks e depending on the type of investment, development stage, and level of localisation of a host unit (Harzing, 2001)). However, several authors suggest that firms from emerging markets may follow a different approach to implementing and managing expatriation compared to firms from developed economies (Caligiuri & Bonache, 2016; Horwitz & Budhwar, 1 These firms are also affected by an overall lack of skilled employees in their domestic environments (Khanna & Palepu, 2000; Tung, 2007). 2 ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 2015). Yet, Briscoe (2014) laments the paucity of research of expatriation from emerging markets. While there are some studies in the international business literature that investigate IAs from emerging market countries (mostly China) to other emerging markets, those studies focus predomi- nantly on talent and trust issues (Jackson & Horwitz, 2017; Li & Wang, 2010). They largely overlook institutional context-related factors; even though economic, political, and legal institutions have a strong impact on corporate success (Akkermans, Castaldi & Los, 2009; Hall & Soskice, 2001). A better understanding of the conditions for expatriation from emerging markets to both other emerging and developed markets is needed, as this could help us explore the role of institutions in international staffing and business internationalisation from such contexts instead of solely from developed markets and by developed market firms (Conti et al., 2016; Dabic, Gonzalez-Loureiro & Harvey, 2015). In our paper, we thus look at the impact of institutions in emerging markets on international assignment de- terminants during business internationalisation. This allows us to test institutional theory for inter- national staffing decisions in emerging market and emerging market firm contexts as well as develop practical implications for general and human re- sources managers in emerging market firms for their more effective and efficient international business and international staffing decision-making. These are summarised in the discussion and con- clusions section. As called for by Jaklic, Raskovic and Schuh (2018), our research concentrates on the region of Central and Eastern Europe (CEE), which includes Albania, Bulgaria, Croatia, the Czech Republic, Hungary, Poland, Romania, the Slovak Republic, Slovenia, Estonia, Latvia, and Lithuania (OECD, 2001). We focus on Slovenia within this under-researched emerging markets region (Trąpczynski & Gorynia, 2017) and explore its firms' IAs to emerging and developed market economies in order to add to our understanding of the impact of institutions on global assignment patterns.2 We study employee movements across European Union (EU) countries, the European Economic Area (EEA) e i.e. Lichten- stein, Iceland, and Norway; and Switzerland due to the common legal principle of employee mobility across these states' borders. Thus, it is not the legal inhibitors but rather the market as well as institu- tional forces that influence firms' expatriation de- cisions (Favell & Hansen, 2002). We address the following research question: What is the impact of institutions on emerging market (Slovenian-based) firms' decisions to implement international assignments in emerging (CEE) compared to developed (European non- CEE) markets? We base our theoretical framework on institu- tional theory (c.f. DiMaggio & Powell, 1983; Scott, 1995) as a framework particularly well-suited to studying firms' IA location choices due to its contextual focus. We contribute to the institutional and international business literature through researching firms' IA location decisions in three ways. First, we expand our knowledge of inter- nationalisation and expatriation patterns of emerging market firms. Against the prediction of the institutional literature that firms are more likely to send expatriates to countries with weak in- stitutions in order to manage risk and uncertainty, we find that emerging market companies assign their staff predominantly to states that are charac- terised by strong and stable institutional contexts. This nuances our understanding and application of institutional theory. Second, we advance expatria- tion and international business theory by empha- sising the importance of diverse institutional contexts. We outline some of the challenges of weak institutions and identify the role of commercial diplomat. I.e. we argue that international assignees engage in activities usually pertaining to commer- cial diplomacy, such as trade policy-making and business support activities (see e.g. Naray, 2008; Saner & Yiu, 2003); and facilitate business through co-designing the business environment that firms operate in. Third, we provide an empirical advance by identifying different patterns in relation to firms assigning employees to emerging and developed markets. Overall, we call for a more holistic research approach that explores individual (micro), organ- isational (mezzo), and broad institutional (macro) elements in investigating global assignment flows and patterns. 1 Institutions as determinants of firms' international assignment location decisions A highly popular framework to categorise organ- isational assignment motives is that of Edstr€om and 2 We acknowledge that the CEE region is highly diversified: in terms of the relative size, importance, and performance, developmental trajectories and levels of economic and socio-cultural development, as well as human resources management (HRM) conceptualisation, institutionalisation, and practice in individual countries (see e.g. Brewster, Buciuniene &Morley, 2010; McCann & Schwartz, 2006; Morley, Minbaeva &Michailova, 2012). Since there are some institutional differences also within the EU, we suggest that CEE countries are nonetheless institutionally more comparable to one another than to non-CEE EU member states. ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 3 Galbraith (1977). A first category distinguishes control and coordination reasons, where assignees diminish uncertainty and agency problems. A sec- ond category points to filling skill gaps, where firms cannot find adequate resources in the local market and use assignees from other markets instead. A third category identifies global business capability development so that the internationally assigned individuals and their colleagues may become the global leaders of the future. Other authors have added knowledge transfer motives as a further dimension (Hocking, Brown &Harzing, 2004). These assignment motivations are based on corporate goals but they largely neglect the broader institu- tional context that influences firms' assignment location decisions. We use institutional theory to explain why firms from emerging market economies might utilise IAs and whether they are more likely to send expatriates to other emerging or developed markets. 1.1 Institutional quality and international assignments Institutions are more or less codified (Ahlstrom & Bruton, 2006) ‘rules of the game’ (North, 1990) that determine social relationships, actors' roles in them, and standards and expectations for legitimate action by actors in a certain context (Ahlstrom & Bruton, 2006; Ando & Paik, 2013). One of the key roles of institutions is to reduce uncertainty through restricting firms' strategic options in a specific context (Friel, 2011; Meyer et al., 2009). When in- stitutions are inadequate or poorly enforced, firms tend to rely on other uncertainty reduction tools, such as international assignments, instead (Berry, 2017; Moreira & Ogasavara, 2018). ‘Poor institutions’ is a concept related to the quality and stability of regulatory provision. Poor institutions can be seen to exist when the enforcement of norms, regula- tions, and regulatory provisions is weak (Buonanno et al., 2015). This lower institutional quality creates costs and problems that may be especially pertinent where institutions are more recent and less devel- oped e i.e. in many emerging market economies (Dunning & Lundan, 2008; Lombardo, 2000). Institutions can be deconstructed into economic, political, legal, and social institutions. Economic institutions refer to market intermediaries that determine the incentives for and constraints on economic actions (Chan et al., 2008; North, 1990). Political institutions are comprised of governments and the constraints they impose on actors through different policies (Chan et al., 2008). Legal in- stitutions refer to distinct legal systems that govern specific forms of social behaviour within the overall legal system (Ruiter, 2001). Social institutions include a set of positions, roles, norms, and values that generate relatively stable and regular patterns of human behaviour in recurrent situations aimed at sustaining viable societal structures (Schotter, 1981 in Langlois, 1986; Turner, 1997). The expatriation and international management literature has often concentrated on cultural differ- ences and thereby social institutional context factors (Caligiuri, 2012; Haslberger, Brewster & Hippler, 2013). However, recent studies have shown that these institutions may not explain the firm's inter- national business-related decisions (including those on international staffing) well. Harzing and Pudelko (2016) are particularly critical of the concept of cul- tural distance as the central measure of social in- stitutions in international business. They empirically show that the differences in home and host country contexts rather than (cultural) distance between them have greater power in explaining the firm's choice of market entry mode. They describe cultural distance as “nothing more than a proxy for factors that really matter” (Harzing & Pudelko, 2016, p. 10, original emphasis). Brookes et al. (2011) come to a similar conclusion in their empirical study on the determinants of organisational HRM practices, whereas Kazlauskait _e et al. (2013) present a similar case for non-culture related determinants of HRM practices in CEE countries. We thus focus on eco- nomic, political, and legal institutions that impact assignment choices and neglect the socio-cultural institutions that act as their proxy. Combined or individually, these three groups of institutions determine the level of and variation in foreign affiliate performance as well as international staffing practices (Chan et al., 2008; Gaur et al., 2007). When addressing economic institutions, au- thors argue that poor availability of and access to credible local informants about a foreign business environment in less developed markets can be compensated for by firms' participation in informal networks (e.g. business groups) and through rela- tionship building (Khanna & Palepu, 1997; Peng, 2000, 2003; Peng & Heath, 1996). As trustworthy boundary spanners (i.e. connectors and mediators) between enterprise units (Ando & Paik, 2013; Reiche, Harzing & Kraimer, 2009) as well as between various organisations in multiple countries, inter- national assignees can play a key role in relationship building. They are socialised into and trusted by the firm (Belderbos & Heijltjes, 2005; Tan & Mahoney, 2006). In addition, international assignees possess parent firm knowledge (Harzing, Pudelko & Reiche, 2016; Reiche et al., 2009) and can transfer this to local 4 ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 operations (Chang, Gong & Peng, 2012; Gaur et al., 2007) and back. Overall, expatriates are useful in minimising agency problems and other un- certainties amplified through distance and poor in- stitutions (Berry, 2017). Extant research shows that firms are thus more likely to assign employees to volatile economies, which are short of skilled local labour (Khanna & Palepu, 2000; Tung, 2007). How- ever, most studies on international assignments in emerging market contexts focus on developed market firms assigning their employees to emerging markets (e.g. Beddi & Mayrhofer, 2010) rather than on emerging market firms assigning their em- ployees abroad (for an exception see Zhu et al., 2018). We test the following hypothesis specifically for emerging market firms:  H1a: A lower quality of economic institutions in the host country is positively related to the use of international assignments by emerging market firms. In terms of political institutions, (perceived) po- litical risk increases the level of information pro- cessing that occurs between the affiliate and corporate headquarters (Boyacigiller, 1990). It aug- ments the need for stronger control and coordina- tion mechanisms (Staw, Sandelands & Dutton, 1981) and leads to higher instances of staffing units with international assignments (Ferner, Quintanilla & Sanchez Runde, 2006; Kanter, 1977). In contrast, if political institutions are well developed, there is a local pool of skilled (public) professionals with whom the organisation can work. The firm is also less likely to assign employees abroad with the aim of interacting with the government (Gaur et al., 2007). We thus propose that:  H1b: A lower quality of political institutions in the host country is positively related to the use of international assignments by emerging market firms. In relation to the legal institutional environment of the assignee host country, transparency of laws and their adequate enforcement are the key determinants of doing business in a particular market. Poor legal institutions imply poor protection of intellectual property rights and costly corruption (Chan et al., 2008). Berry (2017) argues that international assignees can limit the unintended knowledge spillovers occurring during firm internationalisation due to poor institutional protections for intellectual prop- erty. We add to this, and argue that international assignees can also act as commercial diplomats (lobbying for institutional change in a foreign market on the firm's behalf) in environments with poor legal institutions. Boddewyn (1988) and Boddewyn and Brewer (1994) suggest that corruption may even create opportunities for foreign firms to engage in political behaviour e a role that may be performed by assignees. We propose that:  H1c: A lower quality of legal institutions in the host country is positively related to the use of international assignments by emerging market firms. In summary, we propose that poor institutions promote the assignment of parent-country na- tionals in subsidiaries for their inter-organisational networking role, for commercial diplomacy, and for (knowledge) control purposes. Given that the aca- demic literature has concentrated on cultural dif- ferences between countries and their impact on expatriation (Dickmann, Suutari & Wurtz, 2018), it is crucial that our research assesses the hitherto neglected economic, political, and legal institu- tional pressures on firms' international staffing decisions. 1.2 Institutional distance and international assignments International firms do not exist in one national institutional environment, but rather operate in at least two contexts (Xu, Pan & Beamish, 2004) e and encounter pressures for compliance with both (Rugman & D'Cruz, 1993), thereby bridging insti- tutional distance. Phillips, Tracey, and Karra (2009, p. 343) define institutional distance as “a measure of the differences in the cognitive, regulative and normative institutions that characterize the relevant organizational fields in the home and host envi- ronments and the degree of institutional uncertainty in the host country.” Normally, firms are most cognisant of their domestic institutional environ- ments. Since no two markets are identical, inter- nationalisation aimed at the exploitation of the firm- specific resources and location-specific advantages of a particular host country (Dunning & Lundan, 2008) always presents a certain level of (institu- tional) uncertainty. Differences in home and host institutional environments thus necessitate (addi- tional) learning about the new environments (Benito & Gripsrud, 1992) in order to reduce uncertainty (Perkins, 2014). Here, we do not refer only to the institutional distance between home and host markets, but also to the institutional distance between the country of ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 5 the new foreign entry and the closest country in which the firm is already active. Hutzschenreuter, Kleindienst and Lange (2014) describe this feature of internationalisation and internationalisation learning as the added distance. Biased by the ‘les- sons’ already learnt, firms are expected to agglom- erate their international activities in additional foreign markets that are similar to their home environment over time (Barkema & Vermeulen, 1997). Only once firms gain more experience can they re-combine the acquired knowledge in order to use it in new (also more distant) environments. As the firms' (institutional) knowledge base expands, so does the range of their future internationalisation choices (Cyert & March, 1963; Perkins, 2014). We argue that international assignment patterns will reflect the cumulative and gradual nature of learning as well. When the differences between firms' home and host environments are large, as is the case for busi- nesses operating in both emerging and developed economies, the opposing institutional pressures can result in potentially conflicting business practices (Brouthers, Brouthers & Werner, 2008) and increased transaction costs due to the strategic adjustments and learning investments needed (Carlson, 1974; Eriks- son et al., 1997). It is likely that emerging market firms will focus their international assignment efforts on a group of institutionally similar markets (either individually or as a region) to diminish the learning costs (Boeh & Beamish, 2012). Zaheer, Schomaker and Nachum (2012) argue that addressing the question of how two entities (e.g. markets) differ, and not merely focusing on how much they differ, could prove more insightful for researching the impact of institutions on interna- tional business. They suggest that, when analysing the impact of institutional differences on inter- nationalisation and international staffing, the di- rection (rather than solely the magnitude) of distance should also be considered (Zaheer et al., 2012). This means that institutional distance may have a different impact depending on whether an emerging or developed market firm is entering an emerging or a developed market (Beugelsdijk, Ambos & Nell, 2018). For emerging market firms, other emerging mar- kets classify as institutionally proximate markets, where emerging market firms have the advantage of possessing operational knowledge in dealing with institutional weaknesses, such as poorly functioning capital, labour, and information markets (Banerjee, Prabhu & Chandy, 2015; Khanna & Palepu, 2000). These markets nevertheless present a certain level of uncertainty for emerging market firms due to the frequent changes in their institutional environments (Ahlstrom & Bruton, 2006; Trąpczynski & Gorynia, 2017). Developed markets, on the other hand, are classified as institutionally distant markets (see also Phillips et al., 2009) with the already well-developed institutions that emerging market firms have little or no direct experience with (Banerjee et al., 2015). We thus argue that from the perspective of emerging market firms, developed markets rather than other emerging markets present greater risks, un- certainties, and market entry costs. Emerging mar- ket firms' unfamiliarity with the more developed contexts can increase the uncertainties of these firms operating in such environments. We thus posit that:  H2: Emerging market firms are more likely to implement international assignments to emerging markets compared to developed markets. Contrary to this hypothesis, Ando and Paik (2013) find a positive relationship between institutional distance and the absolute number of parent-country nationals assigned to the subsidiary, but discover a negative relationship between institutional distance and the ratio of parent-country nationals to sub- sidiary employees. The authors attribute these ‘mixed’ findings to firms (1) overcoming a lack of legitimacy by employing more locals and at the same time (2) maintaining control over foreign op- erations by increasing the absolute number of parent-country nationals in institutionally distant markets. However, since these findings are based on data on developed market firms, they may not apply to emerging market firms internationalising into distant developed markets, as legitimacy and con- trol issues in the institutionally more developed markets are different from the ones in emerging market economies (McMillan & Woodruff, 2002). In addition, even if emerging market firms faced the same staffing challenges as developed market firms in the institutionally distant economies, they would have limited capacities to address them. This is because emerging market firms are faced with shortages of international managers (Meyer & Xin, 2018) and a general difficulty in hiring skilled em- ployees (Khanna & Palepu, 2000; Tung, 2007). 2 Methods In our study, we focus on a single emerging market home country (Slovenia). We analyse its entire firm population's international staffing de- cisions to destination countries in other emerging and developed markets in EU member states as well as Lichtenstein, Switzerland, Iceland, and Norway. Such an approach allows for analysis of the 6 ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 institutional determinants of firms' international assignment location decisions not only in terms of institutional quality and distance, but also in terms of institutional direction. It is also consistent with Zaheer et al.’s (2012) recommendation on fixing one entity as the focal entity and defining all other en- tities of interest with respect to the focal entity in the analysis in order to incorporate direction in research. CEE countries are regarded as emerging market economies and non-CEE European coun- tries as the institutionally more developed economies. The selection of Slovenia as the focal (home) market is purposeful and based on the theory- building potential of the case. Businesses from small, open economies demonstrate a higher pro- pensity to internationalise (Bellak & Cantwell, 1998; Svetlicic, Rojec & Trtnik, 2000). We find Slovenia, a small country, to be particularly suitable for ana- lysing foreign assignment patterns, because it has a very open economy in terms of trade (exports represent 78% and imports 69% of GDP) and has relatively large inward and outward FDI stock (31% and 14% of GDP, respectively) (2016 data from Bank of Slovenia [Banka Slovenije], 2017). In addition, as a small emerging market economy, Slovenia is rela- tively under-researched.3 A further reason to choose Slovenia was data access that provided the oppor- tunity to explore the entire firm population in a country with respect to actual IA patterns. 2.1 Data and methodology The empirical study uses national data from several separate datasets. Data on IAs record expa- triates' change in the country of residence and are gathered by the Health Insurance Institute of Slovenia. Data for 2015 include a list of all firms with IAs and the total number of assignments per firm. Data for 2016 additionally include the number of different employees sent abroad and the number of assignments to each host country. Information on IAs is reported solely for EU member states as well as Lichtenstein, Switzerland, Iceland, and Norway. In 2015, IAs to these countries were recorded by 4882 firms operating in Slovenia (excluding sole proprietors). The dynamics of the expatriate land- scape can be inferred from the growth to 5529 assigning businesses in 2016. Despite data being limited to a region of host countries, the European context provides a basis for a more homogeneous environment in terms of regulatory regime related to factor mobility and international business. Firm- level data on the entire population of enterprises in Slovenia are collected yearly by the AJPES Agency (i.e. Agency of the Republic of Slovenia for Public Legal Records and Related Services). We use detailed balance sheets and income statements of companies for the period of 2015e2016. These data are expressed in euros and deflated using the appropriate producer and consumer price indices with the baseline price level of 2016. For 2015 and 2016, the dataset includes 65,220 and 65,603 firms, respectively. We link these two data sources with detailed data on trade in goods from the Slovenian Customs Administration, and data on trade in ser- vices and firm-level foreign direct investment data from the Bank of Slovenia. Our approach to studying the patterns of IAs is primarily focused on the extensive margin of as- signments by looking into decisions of firms to send employees into a particular country. Country-spe- cific information on IAs is only available for 2016. To study the determinants of IA decision, we apply a binary response model where our dependent vari- able is dichotomous with yic ¼ 1 if firm i sent at least one employee to country c in year 2016 and yic ¼ 0 otherwise. We therefore expand our dataset to allow each firm to assign an employee to each of the available 31 host countries. The conditional proba- bility is given by: Pðyic¼1jxi;xc;xicÞ¼Fðb0þxibIþxcbCþxicbICþuicÞ ð1Þ where F( ) is a specified function (logistic distribu- tion cdf in logit, standard normal cdf in probit, or cdf of the extreme value distribution in a complemen- tary log-log model), xi is the vector of firm-specific explanatory variables, xc is comprised of host- country-specific determinants, and xic is a set of variables that vary across firms as well as across markets. We report the results from logit estimates with standard errors clustered by firms. In addition, we use a probit and a complementary log-log model as a robustness check, since some studies show that the latter perform better than logit or probit for rare 3 We classify Slovenia as an emerging market economy based on (1) the poor quality of institutions in the country, (2) its political instability, (3) its regional affiliation to Central and Eastern Europe (CEE) and the related emerging market country image, and (4) it belonging to coordinated market economies that are characterised by institutionalised rather than market-based coordination (see also Jaklic, Kolesa & Rojec, 2015, 2016, 2017, 2018; Feldmann, 2006; Meyer & Peng, 2016). In other words, rather than grounding our classification of countries in economic indicators of the level of devel- opment in a country, we look at institutional factors, which is consistent with the focus of the study on the institutional context as the central part of the analysis at the macro level. ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 7 events data such as ours (see Calabrese & Osmetti, 2013).4 We include a broad set of control variables beyond those that test Hypotheses 1e2, because excluding them would produce omitted-variable bias. For example, omitting the information on firms' geographical patterns of exports, imports, and FDI would falsely attribute their effects on IAs to host country institutional quality or IA agglomeration forces. The vector of firm-level regressors xi includes: total factor productivity (TFP) as a measure of firm productivity, estimated according to the Ackerberg, Caves and Frazer (2015) method, a logarithm of employment (emp) and a logarithm of revenue to ac- count for firm size, a dummy for exporters (I(exporter)), the share of exports in total revenue (export share), a foreign ownership indicator (inFDI ), and a dummy for outward foreign direct investment (outFDI ) to account for firms' integration in global value chains, a logarithm of average wage per employee (avgwage) as a proxy for human capital, the capital-labour ratio (K/L) to control for relative factor intensity in production, the debt-to-assets ratio (debt/ asset) to account for financial indebtedness, return on assets (ROA) as ameasure of profitability, the share of intangibles in total assets (intangibles/assets) as aproxy for firm tacit knowledge, firm age, a dummy for firms established before 1994, when the available dataset begins, region dummies, and 2-digit NACE industry dummies. Apart from firm-level regressors that are constant within each firm spell, we include host- country-specific variables (xc) that vary within the firm spell but are identical within each host-country unit. These include the log of host country population to account for market size and the log of its GDP per capita to control for level of development and pro- duction cost. Finally, the firm-country-specific set of variables (xic) includes information on firm i's exports of goods to host country c, its imports of goods, ex- ports of services, imports of services, outward FDI to country c, and foreign ownership over firm i from country c. Initially, these variables enter the model in binary form, followed by specification using loga- rithmic values of these variables. We test Hypothesis 1(aec) (that lower quality of economic, political, and legal institutions in the host country increases the probability of IAs) by including the level of host country's institutions as measured by five Worldwide Governance Indicators (WGI): (i) Regulatory Quality as a proxy for eco- nomic institutions; (ii) Political Stability and Absence of Violence, (iii) Government Effectiveness, and (iv) Control of Corruption as proxies for politi- cal institutions; and (v) Rule of Law as a proxy for legal institutions. The hypothesis is corroborated if the coefficients on the institutional indicators are statistically significant and negative. To test Hypothesis 2 that firms are more likely to implement IAs to emerging markets compared to developed markets, we add a CEE dummy and a set of interaction terms between IA determinants and the CEE dummy (CEE*xi; CEE*xc; CEE*xic) to the above specification (1). Hypothesis 2 will be corroborated if the coefficient on the CEE dummy is statistically significant and positive. Coefficients on interaction terms will identify the differences in the pattern of IAs between CEE and non-CEE host countries. 2.2 Results We begin by presenting simple summary statistics for firms with IAs in years 2015 and 2016 in com- parison to the population of firms and in contrast to exporters, foreign-owned firms, and firms with foreign subsidiaries abroad (Table 1). The median firm using IAs is on average 3.5 times larger in terms of employment, 4.8 times larger in revenue, pays an 85% higher average wage per employee, and gen- erates 63% higher value added per employee than the population median firm. These are useful comparative data that do not exist in the typical IA research that predominantly looks at management patterns (Dowling, Festing & Engle, 2013). Assigning firms are also much more likely to export, have considerably higher export intensity, exhibit higher profitability, and experience a better total factor productivity. They perform better compared to foreign-owned firms and exporters (except in terms of labour productivity). Firms assigning employees to CEE countries have better performance indicators than firms posting their employees to non-CEE countries. This is consistent with previous research arguing that only the most productive firms can overcome the high transaction costs related to doing business in less stable and (perceivably) riskier en- vironments (Rasciute & Downward, 2017). Half of IAs are used by companies from the con- struction sector (51.2%), followed by the manufacturing industry (35.5%) (Fig. 1). Because of specificities of IAs in construction (these IAs are far less concerned with control or knowledge acquisi- tion and transfer), we omit this sector from the remaining part of the analysis. 4 The results are similar and thus omitted. They are available upon request. 8 ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 Most of the IAs outside of construction are directed to Slovenia's largest trade partners or neighbours. The CEE region hosts only 6.1% IAs from Slovenia in 2016 (Fig. 2). Also, a vast majority of assigning firms (74.5% in 2015 and 75.5% in 2016) implement more than one IA per year (by excluding sole proprietors this percentage increases further and exceeds 80%). We now present the results of the analysis of firms' decisions about the location of IAs (Table 2). The results in columns (1) and (2) show specifica- tions with a full set of firm-level, host-country-level and firm-country-specific variables. In column (1), we use a binary type of firm-country-specific vari- ables, indicating only whether a firm exports, im- ports or has direct investments in a given host country. In column (2), we test whether not only the presence but also the extent of international busi- ness linkages with a host country influences the decision to assign an employee to that country. To this end, we use the logarithm of the value of ex- ports, imports, and FDI stocks instead of the dichotomous indicators. Sending at least one employee to a particular host country is positively associated with firm size in terms of employment, export status and export share, average wage per Table 1. Comparison of firms with international assignments and other internationally engaged enterprises in Slovenia, 2015e2016. ln(emp)# ln(rev)# Exporter Ex share ln(wage)# VA/emp# ROA TFP Age Int Assign 1.95 12.69 77.8% 48.1% 9.54 17,339 5.1% 4.03 7.8 N ¼ 5049 (1.30) (2.30) (0.416) (0.423) (1.01) (19,589) (18.1%) (6.31) (7.2) Assign to CEE 2.77 13.94 76.5% 35.8% 9.84 24,822 6.3% 3.34 11.6 N ¼ 526 (1.45) (1.90) (0.424) (0.391) (0.63) (19,577) (12.0%) (6.08) (7.8) Exporters 1.15 12.64 100.0% 40.1% 9.48 20,043 4.7% 0.35 10.6 N ¼ 39,961 (1.24) (1.98) (/) (0.388) (3.19) (133,948) (17.4%) (3.72) (7.83) iFDI 0.94 12.78 63.6% 36.4% 9.46 22,374 1.9% 0.65 9.7 N ¼ 15,759 (1.69) (5.27) (0.481) (0.424) (4.59) (866,488) (0.21%) (3.80) (7.5) oFDI 3.17 15.34 80.4% 35.3% 10.10 39,033 4.0% 0.60 17.3 N ¼ 1039 (2.00) (3.49) (0.397) (0.362) (2.76) (147,236) (11.7%) (3.57) (6.0) Total 0.69 11.13 33.0% 13.3% 8.92 10,629 1.4% 0.009 9.6 N ¼ 121,150 (1.06) (4.42) (0.470) (0.292) (4.36) (201,552) (18.8%) (4.31) (7.8) Note: # report median values, otherwise average values of the variables are stated. Standard deviations are in parentheses. ln(emp) is log of employment, ln(rev) is log of revenue, Exporter is exporter dummy, Ex share is share of exports in total revenue, ln(wage) is log of average wage per employee, VA/emp is value added per employee, ROA is return on assets, TFP is total factor productivity estimated by Ackerberg et al. (2015) procedure, Int Assign are firms with international assignments, iFDI are foreign-owned firms, oFDI are firms with outward foreign direct investment and Total is the entire population of firms in 2015 and 2016. Source: own calculations. 16.0% 2.5% 12.1% 4.9% 13.2% 3.6% 34.6% 2.6% 4.3% 4.9% 1.4% C-25 C-28 C-33 C-rest F-41 F-42 F-43 G M N Other Fig. 1. Distribution of firms with international assignments by in- dustry, 2015e2016. Source: own calculations. Note: The artwork de- picts the number of assignments in an industry as a share in the total number of assignments in 2015 and 2016. C-25 ¼ Manufacture of fabricated metal products; C-28 ¼ Manufacture of machinery and equipment; C-33 ¼ Repair and installation of machinery and equip- ment; C-rest ¼ Rest of manufacturing; F-41 ¼ Construction of buildings; F-42 ¼ Civil engineering; F-43 ¼ Specialised construction activities; G ¼ Wholesale and retail trade; M ¼ Professional, scientific and technical activities; N ¼ Administrative and support service activities. 48.2% 24.8% 6.8% 4.3% 4.2% 2.6% 1.8% 1.5% 3.8% 2.0% DE AT BE IT HR NL CH FR other non-CEE other CEE Fig. 2. Geographical distribution of firms with international assign- ments by host country, 2016. Source: own calculations. Note: In artwork, grey depicts countries belonging to the CEE group (construction sector is omitted). ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 9 Table 2. Decision to post employees to an individual host country. (1) (2) (3) (4a) (4b) (5a) (5b) Logit Logit Logit bnonCEE bCEE bnonCEE bCEE Firm-level variables: TFP 0.00159 0.00441 0.00114 0.000302 0.00489 0.00694 0.0125 (0.0312) (0.0312) (0.0315) (0.0318) (0.0366) (0.0319) (0.0365) ln(emp) 0.516*** 0.523*** 0.525*** 0.548*** 0.421*** 0.554*** 0.450*** (0.0526) (0.0518) (0.0527) (0.0508) (0.104) (0.0505) (0.102) ln(revenue) 0.112*** 0.110*** 0.109*** 0.124*** 0.0214b 0.119*** 0.00312b (0.0258) (0.0256) (0.0259) (0.0256) (0.0668) (0.0256) (0.0633) I(exporter) 0.683*** 0.712*** 0.686*** 0.690*** 0.570*** 0.711*** 0.607*** (0.124) (0.123) (0.124) (0.127) (0.220) (0.126) (0.220) export share 1.005*** 0.988*** 1.019*** 1.153*** 0.406**a 1.142*** 0.408**a (0.122) (0.122) (0.122) (0.121) (0.206) (0.121) (0.205) inFDI 0.447** 0.419** 0.441** 0.518*** 0.238 0.468*** 0.282 (0.176) (0.175) (0.177) (0.171) (0.275) (0.168) (0.284) outFDI 0.573** 0.589** 0.553** 0.573** 0.439 0.562** 0.515 (0.254) (0.254) (0.253) (0.248) (0.425) (0.245) (0.430) ln(avgwage) 0.191** 0.190** 0.190** 0.130 0.617***a 0.128 0.613***a (0.0840) (0.0840) (0.0844) (0.0853) (0.182) (0.0853) (0.182) K/L 0.220*** 0.218*** 0.219*** 0.219*** 0.189*** 0.217*** 0.186*** (0.0299) (0.0297) (0.0300) (0.0303) (0.0676) (0.0302) (0.0678) debt/asset 0.182** 0.177** 0.183** 0.164** 0.359** 0.160** 0.349** (0.0782) (0.0786) (0.0786) (0.0766) (0.166) (0.0772) (0.169) ROA 0.635*** 0.626*** 0.637*** 0.611*** 0.854** 0.597*** 0.894** (0.216) (0.216) (0.217) (0.220) (0.411) (0.220) (0.411) (intang/assets)2 2.224 2.479 2.057 2.056 1.005 2.251 1.940 (4.078) (4.036) (4.130) (3.853) (7.968) (3.815) (7.730) intangibles/assets 4.076 4.229* 3.982 3.939 3.610 4.058* 4.108 (2.539) (2.557) (2.549) (2.402) (4.328) (2.413) (4.473) Age 0.0367*** 0.0364*** 0.0362*** 0.0418*** 0.00563a 0.0412*** 0.00699a (0.00773) (0.00776) (0.00775) (0.00771) (0.0136) (0.00771) (0.0137) I(old) 0.0263 0.0104 0.0259 0.0132 0.1548 0.000874 0.132 (0.164) (0.165) (0.165) (0.166) (0.252) (0.166) (0.253) Host-country-specific variables: CEE dummy 2.325*** 14.92 18.60 (Hypothesis 2) (0.165) (17.81) (17.93) ln(distance) 1.874*** 1.900*** 1.919*** 2.128*** 1.413** 2.166*** 1.342** (0.0753) (0.0749) (0.0640) (0.0970) (0.587) (0.0976) (0.587) regulatory quality 0.768*** 0.771*** 0.813*** 0.0357 1.748 0.0325 1.575 (Hypothesis 1a) (0.242) (0.246) (0.208) (0.217) (1.979) (0.219) (1.989) political stability 0.100 0.120 0.692*** 1.217*** 2.330** 1.249*** 2.458** (Hypothesis 1b) (0.163) (0.165) (0.159) (0.200) (0.977) (0.202) (0.993) gov. effectiveness 1.215*** 1.293*** 0.438* 0.684 1.023 0.753* 1.056 (Hypothesis 1b) (0.202) (0.201) (0.239) (0.427) (0.659) (0.430) (0.666) contr. of corruption 0.575*** 0.578*** 0.707*** 1.684*** 1.562** 1.736*** 1.697** (Hypothesis 1b) (0.171) (0.173) (0.183) (0.301) (0.683) (0.305) (0.688) rule of law 0.716*** 0.769*** 0.103 0.292 2.096 0.296 2.385 (Hypothesis 1c) (0.179) (0.180) (0.193) (0.361) (1.637) (0.364) (1.652) ln(population) 0.862*** 0.880*** 0.694*** 0.821*** 0.251a 0.835*** 0.245a (0.0524) (0.0531) (0.0450) (0.0639) (0.153) (0.0647) (0.153) ln(GDP p.c.) 0.555*** 0.572*** 1.304*** 1.540*** 0.492 1.572*** 0.127 (0.0797) (0.0798) (0.141) (0.189) (1.860) (0.192) (1.882) Firm-country-specific variables:ǂ goods EX to cntry 0.451*** 0.0404*** 0.410*** 0.319*** 0.641*** 0.0268*** 0.0695***a (0.0922) (0.00915) (0.0922) (0.0937) (0.184) (0.00907) (0.0178) goods IM from cntry 0.000296 0.0133* 0.0658 0.0859 0.0506 0.0209** 0.0202 (0.0701) (0.00778) (0.0702) (0.0756) (0.157) (0.00828) (0.0169) serv. EX to cntry 0.725*** 0.0887*** 0.709*** 0.766*** 0.271 0.0885*** 0.0538 (0.187) (0.0169) (0.191) (0.198) (0.334) (0.0176) (0.0331) serv. IM from cntry 0.768*** 0.0550*** 0.770*** 0.746*** 0.968*** 0.0544** 0.0719** (0.218) (0.0208) (0.223) (0.225) (0.309) (0.0212) (0.0318) outFDI to cntry 0.884*** 0.0356 0.851*** 0.163 1.031** 0.0357 0.0510 (continued on next page) 10 ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 employee, profitability, labour intensity, and indebtedness. Human capital reflected in higher average wages affects the international transfer of employees positively, implying that IAs can serve as a channel of knowledge transfer. Next, expatriation is more prevalent among labour intensive firms where person-to-person interaction is more essen- tial. The intangible assets of a firm have a non-linear effect on expatriation, initially decreasing the prob- ability of IAs at lower shares of intangible assets, while increasing it at higher shares.5 This could be explained by the dual role of IAs in knowledge transfers. Firms with lower tacit knowledge use in- ternational transfers to acquire knowledge from abroad, while firms with abundant intangible assets use their expatriates to transfer and augment knowledge through inter- and intra-organisational networks (Bj€orkman, Barner-Rasmussen & Li, 2004; Minbaeva & Michailova, 2004). Moving to host country-level determinants, we observe that traditional gravity model variables perform as expected: market size and level of development increase the odds of sending em- ployees to a destination country, while geographic distance between Slovenia and host country de- creases them. Where economic institutions as measured by the WGI regulatory quality index are of higher quality, the probability of IAs is higher. A better quality of legal institutions (as assessed by the WGI rule of law index) similarly attracts more IAs. The quality of political institutions in a host country matters as well: the better control of corruption in a country attracts IAs more often, yet there is no effect of political stability in the pooled sample of both CEE and non-CEE host countries. The only institu- tional quality index that exhibits a negative associ- ation with IAs is the government effectiveness index. Where the quality of public services, the quality of the civil service and the degree of its in- dependence from political pressures is lower, there is a higher probability that firms assign their em- ployees. This might mean that firms believe that IAs can be an effective instrument for protecting firm assets and interests in more unfavourable environ- ments with higher policy instability. It may also imply that emerging market firms asses that they are capable of influencing host country institutions in other emerging markets through international assignees as commercial diplomats. Our results thereby indicate that commercial diplomacy is linked to poor political (rather than economic) in- stitutions. All in all, our results partially confirm Hypothesis 1b, that the host countries with a lower quality of political institutions attract more IAs. On the other hand, Hypotheses 1a and 1c are rejected, as emerging market firms are more likely to assign their employees to host countries with a higher quality of economic and legal institutions. Turning to the last group of determinants, which are firm- and host-country-specific, reveals that firms that export goods to a country, export services to a country, or import services from a country are significantly more likely to assign their employees there. From specification (1) in Table 2, we see that Table 2. (continued) (1) (2) (3) (4a) (4b) (5a) (5b) Logit Logit Logit bnonCEE bCEE bnonCEE bCEE (0.323) (0.0265) (0.323) (0.410) (0.450) (0.0331) (0.0355) inFDI from cntry 0.201 0.00467 0.149 0.233 0.410 0.00203 0.0207 (0.211) (0.0161) (0.213) (0.221) (0.823) (0.0171) (0.0532) constant 19.94*** 20.23*** 2.119 4.963 5.298 (1.606) (1.620) (2.102) (3.289) (3.317) N 1,035,183 1,034,951 1,035,183 1,035,183 1,034,951 Log likelihood 11,350 11,191 11,109 11,020 10,966 Region FE yes Yes yes Yes Yes Industry FE yes Yes yes Yes Yes Note: Dependent variable is dummy variable for firm sending at least one employee on an international assignment to a given host country in 2016. Standard errors clustered at firm-level are in parentheses. ***, **, * indicate a significance level of 1%, 5% and 10%, respectively. Columns (4) and (5) report results from the CEE interaction specification b0 þ b1CEEþ Xb2 þ ðCEE *XÞb3, where (4a) and (5a) report coefficients b2 for non-CEE countries and (4b) and (5b) report coefficients b2 þ b3 for CEE countries and the corresponding standard error of the sum. a (b) in columns (4b) and (5b) indicates variables for which the corresponding b3 on the interaction term CEE*X is statistically significant at 1% (5%) level. ǂ specifications in columns (1), (3) and (4) use binary indicators for firm-country-specific variables, while (2) and (5) use logged values of these variables. Hypotheses 1e2 denote variables that test Hypotheses 1e2 respectively. Source: own calculations. 5 This conclusion follows from calculating marginal effects of intangibles on the probability to assign at different values of the share of intangible assets in total assets. ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 11 the exporting of goods to a country increases the odds of posting an employee there by 57%, export- ing services to a country by 106%, and importing services from a country raises the assignment probability by 116%. Having subsidiary in a country increases the probability of IAs, conditional on being an outward foreign direct investor. Combining the coefficients on ‘outFDI’ and ‘outFDI to a country’ yields that for foreign direct investors the odds of an IA to a host country increase by 36% if they have a subsidiary in that country. Conversely, foreign direct investors with no subsidiary in a country have a 44% lower probability of posting an employee to this country compared to firms without outward FDI. Slovenian multinationals are thus much more bound within their existing network of subsidiaries abroad in posting IAs than firms without foreign direct investment abroad. Foreign ownership, on the other hand, reduces the odds of IAs, especially to countries from which none of the foreign owners of the Slovenian subsidiary origi- nates. This may be because the direction of IAs within multinationals is more prevalent in the di- rection from headquarters to subsidiaries. Unfortu- nately, we have no data on inbound assignments to test this. In specification (2), where we use the values of export, import and FDI linkages between the firm and potential host country, the results confirm a positive association between IAs and ex- ports of goods and services to a country and imports of services from a country. In contrast to the dummy variable specification in column (1), the value of outward and inward FDI stock is not relevant in explaining the probability to assign workers to a specific host country. In column (3) of Table 2, we augment specification (1) with a CEE dummy that distinguishes CEE countries from non-CEE European countries. Once we control for firm-level, country-level, and firm- country-specific factors, firms have a 90% lower probability of assigning employees to CEE countries compared to non-CEE countries. The inclusion of the CEE dummy does not affect the firm-level and firm-country-specific variables much, but increases the effect of political stability and diminishes the effects of government effectiveness and the rule of law. Comparing CEE with non-CEE host counties (columns (4a) and (4b)) suggests that revenue and average wage are more influential predictors for IAs to the CEE region (the interaction terms CEE*xi are positive and statistically significant). Conversely, the export intensity of a firm and the size of host country are less important for IAs to the CEE region. These differences between the two groups of host countries are corroborated in specification (5), where we use logarithmic values of firm-country- specific variables instead of simple dichotomous indicators from specification (4). Once we allow for different partial effects of each of the regressors in specifications (4) and (5), there is no significant preference anymore in favour of IAs to the non-CEE region (both CEE dummies turn insignificant). Country size and geographic distance from Slovenia matter less for IAs to CEE host countries. Two additional differences between CEE and non-CEE host countries are identified by specifications (4) and (5). First, a firm's export of services to a non-CEE country increases the odds of IAs to this region but does not influence IAs to CEE countries. Second, the previously identified association between the pres- ence of a foreign subsidiary and IAs to a country is applicable only in CEE host countries. In summary, the results reject Hypothesis 2 claiming that emerging market firms are more likely to imple- ment IAs to other emerging markets. 3 Discussion and conclusions In this paper, we study the differences in assign- ment-related decisions made by emerging market firms internationalising into either emerging or developed economies. Building on institutional theory, we use a contextualised approach to study- ing IAs. Based on data for the entire firm population in a selected CEE country (Slovenia), we provide one of the first empirical assessments of country- level determinants of IA implementation and loca- tion choices by emerging market firms. In our analysis, we specifically stress the under-researched differences in determinants of emerging market firms' decisions to utilise IAs in CEE markets compared to non-CEE markets. Emerging market firms from Slovenia expatriate more strongly to countries with high institutional quality. Our results with respect to Hypothesis 1 show that emerging market businesses are more likely to use IAs in environments with high quality economic, political, and legal institutions e even after con- trolling for their existing trade and investment network. This is contrary to our expectations that firms would send more assignees to emerging markets in order to reduce uncertainty (Berry, 2017; Boyacigiller, 1990; Moreira & Ogasavara, 2018). Emerging market firms from low quality institu- tional contexts, such as Slovenian enterprises, may be more used to, or more comfortable with, insti- tutional uncertainty and may rely less on control and coordination IAs (Edstr€om & Galbraith, 1977). Instead, firms from emerging markets may be 12 ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 strongly focussed on knowledge acquisition and the reverse transfer of insights through IAs (Fang et al., 2010; Hocking et al., 2004; Lazarova & Tarique, 2005; Zhu et al., 2018) that they can gain in countries with high quality economic, political, and legal in- stitutions. Firms from emerging markets with low quality institutions may also benefit more in terms of their learning from expatriating into markets with high quality institutions compared to enterprises that originate in a context with high quality in- stitutions. Overall, we build on Zaheer et al. (2012) to nuance the institutional literature with respect to IAs from low quality institutional contexts and refine the insights of the international business literature in relation to the influences of institutional quality on assignment objectives (Edstr€om & Gal- braith, 1977; Hocking et al., 2004; Reiche et al., 2009). Beyond legal and economic context factors, we get mixed results for the impact of political institution indices on the utilisation of IAs: while better control of corruption in a country attracts IAs, there is no effect of political stability (e.g. security) on the firms' likelihood to assign in the pooled sample of both CEE and non-CEE host countries. The only institu- tional quality index that exhibits the expected negative association with IAs is the government effectiveness index. This implies that specific as- pects of political stability have different effects on the firms' likelihood to assign. While assignees cannot nullify the problem of corruption, they can act as an effective instrument for protecting firm assets and interests in environments with a low quality of public services, low quality of civil service, and with a high degree of political pressures. We argue that assignees can have the role of working towards creating a favourable business environment for a firm in the host country and establishing the firm's legitimacy abroad. Ru€el and Visser (2014) describe this as commercial diplomacy. Our find- ings give a more nuanced understanding of the institutional host context, which allows us to identify commercial diplomacy reasons for expatriation. Thus, we propose a subtle addition to the roles of expatriates outlined by Baruch et al. (2013), who depict a set of variables that shape the roles of ex- patriates. These range from the IA type and dura- tion to cultural differences and tasks dimensions. We suggest that an assignee as a commercial diplomat needs to understand and navigate the dynamic and weakly enforced institutional context of the host country. As such, assignees as commer- cial diplomats may use the poor institutional envi- ronment to the advantage of the firm through negotiation or delaying tactics in relation to some of the institutional requirements and dynamics. The role of commercial diplomat and its dependence on the quality of the institutional context adds nuance to the expatriation literature. One of the practical implications would be to select assignees factoring in these and other role profiles and prepare them for these tasks in advance of expatriation. Emerging market firms from Slovenia expatriate more strongly to institutionally dissimilar countries. In rela- tion to Hypothesis 2, our data shows that e against what the institutional literature would predict e emerging market firms are more likely to send ex- patriates to developed countries and less likely to other emerging markets. Once we control for firm- level, country-level, and firm-country-specific fac- tors, firms are 90% less likely to assign employees to CEE countries compared to non-CEE countries. This indicates that despite the historic connections be- tween Slovenia and other CEE markets in Europe, these connections do not result in a greater likeli- hood to assign to CEE markets. In fact, firms oper- ating in Slovenia are more likely to assign to non- CEE countries. The reasons may include that (as the more developed environments) non-CEE countries often embody better learning opportunities and are institutionally less difficult and taxing for assignees (Bhagat et al., 2002; Caligiuri & Bonache, 2016). Based on our research results, we strengthen our conclusion that firms use (although overall less) IAs for control and coordination purposes in emerging host markets, but they are more driven by learning and leadership development motives in developed host countries (see also Zhu et al., 2018). Our work thus refines the expatriation literature (Baruch, Steele & Quantrill, 2002; Edstr€om & Galbraith, 1977; Mayrhofer, 2001) by showing that the broad insti- tutional context and not just organisational rationale seems to be important for major expatriation flows. Our findings suggest that, when analysing the impact of institutional differences on international- isation and international staffing, the direction (rather than solely the magnitude) of distance should be considered (Zaheer et al., 2012). Firms from one emerging market, Slovenia, choose higher institutional distance locations presumably to strengthen learning effects and (reverse) knowledge flows by IAs. Institutional distance may have a different impact depending on whether an emerging or a developed market enterprise is entering an emerging or a developed market (Beu- gelsdijk et al., 2018). Overall, our work refines the understanding of institutional influences on inter- national staffing patterns, nuances the insights into the expatriation patterns of firms embedded in low quality institutional contexts, and adds to the un- derstanding of the effects of institutional distance. ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 13 We reiterate that it is not only the institutional context that is important for IA-related decisions. It is also the administrative heritage of firms (Bartlett & Ghoshal, 1989), the experience of enterprises handling low quality institutional contexts, and further business drivers that impact the firms' expatriation decisions. For instance, the expatriation literature has long identified knowledge acquisition and individual interests as key drivers of IAs (Dickmann et al., 2008). This suggests that a more holistic assessment of IA drivers and decisions needs to include individual, organisational, and institutional elements. Overall, our contribution re- fines institutional theory and its application to in- ternational business in general and expatriation in particular. Managerial Relevance. We have argued above that firms from emerging markets e at least where we looked at the assignment patterns of all firms from Slovenia e expatriate more strongly to countries with high institutional legal and economic quality and, against our predictions, to host countries that are more institutionally dissimilar. In terms of a managerial contribution our findings have implica- tions for the pre-assignment, expatriation, and post- assignment phase. During pre-assignment, firms would do well to factor in how expatriation candi- dates cope with uncertainty and learning depending on the institutional environment of the home and host markets in their global mobility selection criteria and decision-making. Our findings thus support prior calls for organisations to coordinate their talent and global mobility management more strongly when faced with large institutional dis- tances between home and host markets (Cerdin & Brewster, 2014). This would also allow firms to prepare expatriates for IAs to emerging markets differently than assignees for IAs to developed markets. The on-assignment support and commu- nication mechanisms implemented by organisations could also depend on the institutional quality of host environments. Where emerging market firms expatriate to locations embedded in high quality institutions in developed countries, host teams could be prepared to be supportive and to facilitate the assignee's learning (Toh & DeNisi, 2005). We have seen that knowledge acquisition and transfer is important for emerging market com- panies' choice of assignment locations. Thus, during and post an assignment, it is important to create a receptive learning atmosphere and to encourage home organisation knowledge absorption and use (Lazarova & Tarique, 2005; Oddou, Osland & Bla- keney, 2009). In addition, given the developmental nature of these assignments, organisations should develop strong on-assignment and post-assignment retention mechanisms (Dickmann et al., 2018). Limitations. Despite its numerous insights for both academia and practitioners, our study has several limitations, which present an opportunity for further research. First, we use a single-country database that does not allow for comparisons of potential differences in IA-related decisions made by firms from both emerging and developed mar- kets. Future research could thus explore assign- ment-related decisions in all possible directions based on the level of host and home country insti- tutional development. Second, future research could consider different ownership structures of firms in their IA location choices and the resulting firm performance as well as the impact of subsidiary role (Chung et al., 2015) or network interrelatedness (Bartlett & Ghoshal, 1986; Boyacigiller, 1990). Third, research into the outcomes of assignment-related decisions (which may be different for emerging and developed mar- kets) is hindered due to the lack of longitudinal data on IAs. A longitudinal approach would provide in- sights into the dynamics of firms' decisions regarding international employee mobility e discovering which purposes IAs are used for at what stages of firm/market development and whether this is also location-determined. As institutions also change over time, the dynamic impact of institu- tional factors on international staffing should also be considered by future research on the topic e providing insights on whether over time interna- tional staffing strategies by emerging and developed market firms are converging or diverging further (see e.g. Friel, 2011). Theoretically, we refine the evolving understand- ing of global mobility and its institutional embedd- edness. While most of the global mobility literature focusses on individual and organisational reasons for IAs (Dickmann et al., 2008), we identify macro- level contextual factors such as the quality of eco- nomic, political, and legal institutions. Moving beyond micro (individual) and mezzo (organisa- tional) perspectives has already been called for by the emerging literature on macro-talent flows (Khilji, Tarique & Schuler, 2015). While our study shows that the main principles suggested by the institutional theory are applicable to international employee mobility, we refine the theoretical insights with respect to institutional quality (also by type of institution) and distance. The literature indicates that firms predominantly use IAs into emerging markets to reduce risks and fill skill gaps. In contrast, our data shows that firms from emerging market economies have stronger 14 ECONOMIC AND BUSINESS REVIEW 2022;24:1e18 expatriation patterns into developed countries, presumably for developmental and knowledge transfer reasons. Our work enables researchers to draw up a more detailed IA-decision model that can capture broader expatriation flows into institutional systems rather than focusing on small sub-groups of assignees. 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