The Interplay of Formal Institutional and Cultural Distances and the Financial Performance of Foreign Subsidiaries in Latin America

Abstract

We investigate how formal institutional distance (FID) moderates the cultural distance (CD) and financial performance relationships of foreign subsidiaries of firms. Following recent research, we estimate the asymmetric effects of CD by considering its size and direction towards host countries on the opposite poles of each cultural dimension’s scale. We propose that a limited understanding of the formal institutions in the host country, as measured by the magnitude and direction of the FID, can positively moderate the CD–performance relationship. This is mainly because foreign subsidiary firms may be more reliant on their capacity to navigate the less formal (and more implicit) aspects of the host country’s institutional environment, such as their ability to cope with the CD. We use foreign subsidiary data from the Orbis database, which includes 22 developed and 22 developing home countries and over 1400 foreign subsidiaries operating in 10 of Latin America’s largest economies (host countries) from 2012 to 2015 (a period of 3 years). Findings confirm the asymmetric effects of CD; however, by considering the direction of FID, our findings reveal that the more FID is directed towards host countries that are less developed, the more significant the effects of CD on financial performance. These findings contribute to our knowledge of how formal and informal institutional distances interact by showing that the greater the FID towards less developed host countries, the more pronounced the effects of CD.

1. Introduction

Cultural distance is well anchored in the International Business (IB) literature and has evolved through several different periods, showing how much this construct has influenced research in this field. However, its effects on international entry modes, performance, and even FDI distribution still raise great questions. There is an ever-growing concern regarding a possible mismatch between the theoretical arguments, methodological procedures, and empirical results found in distance-related studies (Dow 2017; Verbeke et al. 2017). In fact, Shenkar et al. (2020) show that studies have been trying to rescue the distance metaphor by providing remedies to deal with several of its shortcomings. Therefore, in order to advance the knowledge of distance, our attention should be steered towards identifying the conditions that explain the different outcomes described in the literature. In this article, we aim to contribute to this debate and examine more specifically the relationships between formal institutional distance (FID) and cultural distance (CD), and particularly how their interaction affects the financial performance of foreign subsidiaries.

When it comes to the implications of CD, the majority of studies emphasize its negative effects (Beugelsdijk et al. 2018). However, there are a growing number of studies pointing to the asymmetric implications of CD. Depending on the direction, the effects of CD can be positive or negative (Correa da Cunha et al. 2022a; Magnani et al. 2018; Selmer et al. 2007). The directionality of formal institutional distance (FID) has been extensively supported by theoretical arguments and empirical evidence showing that the quality of formal institutions in the host country reduces transaction costs and impacts financial performance positively (Correa da Cunha et al. 2022b; Klasing 2013; Maseland 2013; Zaheer et al. 2012; Hernández and Nieto 2015).

When considering how formal and informal institutions interact, North (1990, p. 47) posits that formal institutions can be “enacted to modify, revise, or replace informal constraints”. In fact, studies have shown that when operating in host countries with institutional voids, the effects of CD on the financial performance of foreign subsidiary firms tend to increase (Correa da Cunha et al. 2022c). In this study, we argue that the greater the FID between the home and host countries, the more difficult it becomes to adapt to the formal norms and regulations in the host country’s environment. This causes foreign subsidiary firms to rely more on their ability to cope with cultural differences. Thus, the higher the FID, the more significant the effects of CD on the financial performance of foreign subsidiary firms. In that sense, the main goal of this study is to investigate how FID moderates the effects of CD on the financial performance of emerging market firms. We address the following research question: To what extent does FID moderate the relationship between CD and the financial performance of foreign subsidiary firms?

We test our assumptions using data from the Orbis database and a sample that includes over 1450 foreign subsidiaries, with approximately 1200 from developed countries and 250 from emerging markets operating in the 10 largest economies in Latin America, over a period of 3 years ranging from 2013 to 2015. Latin America provides a relevant context for this study due to “societal, cultural, and economic characteristics that make the region an ideal ‘natural laboratory’ to build and test management theories” (Aguinis et al. 2020, p. 615). Furthermore, the data includes 168 pairs of different home and host countries, which allows testing the impact of distances (Franke and Richey 2010) and making comparisons regarding the implications of distances for the financial performance of foreign subsidiaries from developed countries and from emerging markets.

Our findings contribute to the debate on how formal and informal institutional distances interact and impact the financial performance of foreign subsidiary firms by showing that the asymmetric effects of CD tend to increase only when FID is towards less developed host countries. These results indicate that when the foreign host country environment provides less support from formal institutions compared with the home country, foreign subsidiaries are likely to rely on their ability to cope with the less formal and less strict nature of cultural differences (i.e., Cultural Distance). In that sense, by considering the direction of FID, our findings reveal that the higher the FID towards less developed host countries, the more significant the effects of CD on financial performance.

This paper is organized into five major sections. Following the introduction, Section 2 presents the theoretical background and hypotheses to be tested. Section 3 focuses on our research method and approach to model estimation. Results are presented in Section 4, while in Section 5, we conclude by highlighting our main contributions, limitations, and opportunities for future research.

2. Theoretical Background and Hypotheses

Behavioral factors affecting the internationalization of firms were first introduced by Uppsala scholars. Johanson and Wiedersheim-Paul (1975) and Johanson and Vahlne (1977) introduced the concept of “psychic distance” (Beckerman 1956) to represent the sum of factors preventing the flow of information between the multinational firm and the foreign market. According to the Uppsala model, the internationalization of firms is affected by several factors, including differences in language, culture, political systems, level of education, and economic development (Johanson and Vahlne 1977).

In International Business (IB) literature, distance is a popular metaphor that represents the degree of dissimilarity between countries. Despite the huge popularity of distance studies in IB, Verbeke et al. (2017, p. 1) state that the “knowledge of distance, in terms of conceptual specification and consequences for IB practice, is incomplete and sometimes ambiguous”. In that sense, we might be on the wrong track in regard to our knowledge of distance (Shenkar 2012a; Zaheer et al. 2012).

In order to address these critiques, it is important to review how the notion of distance evolved in the IB literature. Initially, scholars introduced the broad concept of psychic distance to represent the sum of factors preventing the flow of information between the multinational firm and the foreign market (Johanson and Vahlne 1977; Johanson and Wiedersheim-Paul 1975). Being too broad and, therefore, difficult to operationalize, the contributions of Hofstede (1980) and Kogut and Singh (1988) offered a more practical alternative for computing the differences between countries by adopting the CD construct. However, CD is a much narrower perspective that focuses on the “extent to which the shared norms [ideas, beliefs] and values in one country differ from those in another” (Drogendijk and Slangen 2006, p. 362). As the arguments in the majority of CD studies derive from the transaction cost theory, which attributes a liability character to distances (Zaheer 1995), there is a tendency to highlight the negative effects (Stahl and Tung 2015; Beugelsdijk et al. 2018).

Although CD became extremely popular on the IB research agenda, Shenkar (2001) criticized several of its underlying assumptions and indicated that institutional distance (Kostova 1996) could be a viable alternative to deal with some of these issues. Early studies adopting the institutional distance construct argued that the higher the distance, the more difficult (and costlier) it is to transfer organizational practices to a foreign host country (Kostova 1999; Kostova and Zaheer 1999). Institutions can be categorized as ‘regulative, normative, and cognitive structures that provide stability and meaning to social behavior’ (Scott 1995, p. 33).

Formal institutions relate to the regulatory pillar, whereas informal ones represent the normative and cognitive structures of a society (Peng et al. 2009). Culture is part of the informal that serves as the foundation for formal institutions (Peng et al. 2009). In that sense, “formal rules are created by the polity, whereas informal norms are part of the heritage that we call culture” (North 1990, p. 37).

By considering the interdependence among the levels of formality in the institutional framework, we argue that when focusing on a single perspective in isolation (e.g., CD and FID), studies provide an incomplete (and impaired) assessment of the differences between the two countries. In that sense, rather than rejecting the distance metaphor, we build on the contributions of several important previous studies and follow the recommendation by Shenkar et al. (2020, p. 9), which indicates that in order to advance the knowledge of distance, “focus should now turn towards specifics, that is, the conditions under which the impact will be positive or negative, the mechanisms involved, and the process through which the benefits and drawbacks are activated”. We contribute to this debate by focusing on how FID moderates the asymmetric effects of the dimensions of CD on the financial performance of foreign subsidiary firms.

2.1. The Asymmetric Effects of Cultural Distance

Since its introduction, distance has been used to explain the additional challenges and the resulting costs associated with conducting business in a distant foreign country (Johanson and Vahlne 1977; Johanson and Wiedersheim-Paul 1975). Thus, distance can be perceived as a liability (Zaheer 1995), which creates friction (Shenkar et al. 2008; Shenkar 2012b) as it increases transaction costs and affects the financial performance of foreign companies in a negative way.

More recently, however, while the vast majority of CD studies still focus on the negative effects of CD (Beugelsdijk et al. 2018), there is a growing number of studies pointing to the asymmetric implications of CD by considering the size and direction of CD (Correa da Cunha et al. 2022a; Magnani et al. 2018; Selmer et al. 2007). Additionally, it is important to consider that the different dimensions of national culture can affect performance in specific and distinct ways. In fact, studies have shown that some dimensions of national culture might be more important and have a greater impact, while others might have little or no impact at all (Maseland et al. 2018; Hofstede 1989).

In this study, we follow this approach and adopt the directional CD measure developed by Correa da Cunha et al. (2022a), which accounts for the size and direction of the distance towards host countries in each (opposite) pole of the cultural dimensions’ scales. Therefore, we consider that the direction of the specific dimensions of CD is likely to affect the financial performance of foreign subsidiaries in specific and distinct ways. In order to test these assumptions, we present the following hypothesis:

H1. 

The effects of CD on the financial performance of foreign subsidiary firms are specific to each dimension of national culture and asymmetric depending on the direction towards host countries at each pole of the cultural dimension’s scale.

2.2. FID Moderating the Relationship between CD and Performance

In addition to investigating the effects of CD, we address the moderating effects of formal institutional distance (FID) on the relationship between CD and the financial performance of foreign subsidiary firms. FID represents the degree of dissimilarity in terms of regulatory aspects of the institutional environments in the two countries (Kostova 1999; Kostova and Zaheer 1999).

Institutions are “the rules of the game in a society or, more formally, are the humanly devised constraints that shape human interaction. In consequence, they structure incentives in human exchange, whether political, social, or economic”. (North 1990, p. 3). Institutions are strong “if they support the voluntary exchange underpinning an effective market mechanism” and weak “if they fail to ensure effective markets or even undermine markets” (Meyer et al. 2009, p. 63). Studies have shown that formal institutions are among the several factors that impact the internationalization of emerging market firms (Correa da Cunha et al. 2022d).

The directionality of FID is well established in IB research (Hernández and Nieto 2015; Konara and Shirodkar 2018). Studies have shown that developed country firms are at an advantage when FID is directed towards more developed host countries, while emerging market firms know how to deal with institutional voids when operating in less developed host countries (Correa da Cunha 2019; Correa da Cunha et al. 2022b; Cuervo-Cazurra and Genc 2011).

By focusing on the institutional framework (North 1990; Scott 1995), we analyze the interplay of cultural and formal institutional distances. Institutions can be defined as ‘regulative, normative, and cognitive structures that provide stability and meaning to social behavior’ (Scott 1995, p. 33). While formal institutions relate to the regulatory pillar, informal ones refer to the normative and cognitive structures of a society (Peng et al. 2009). In that sense, formal rules are created by the polity, whereas informal norms are part of the heritage that we call culture (North 1990, p. 37).

According to North (1990), formal and informal institutions can interact in a complementary or suppressive manner. Institutional complementarity refers to a condition in which “the presence (or efficiency) of one [institution] increases the returns from (or efficiency of) the other” (Hall and Soskice 2001, p. 17). Alternatively, the suppressive relationship refers to a condition in which the formal rules may be “enacted to modify, revise, or replace informal constraints” (North 1990, p. 47). In the same way, Pejovich (1999, p. 170) provides an “interaction thesis” that proposes the following outcomes: “(1) Formal institutions suppress, but fail to change informal institutions; (2) Formal rules directly conflict with informal rules; (3) Formal rules are either ignored or rendered neutral; and (4) Formal and informal rules cooperate—as in cases where the state institutionalizes informal rules that had evolved spontaneously”.

According to Pejovich (1999, p. 171), “when formal rules conflict with the prevailing informal rules, the interaction of their incentives will tend to raise transaction costs and reduce the production of wealth in the community”. In addition, North (1990, p. 91) states that “formal rules change, but the informal constraints do not. In consequence, there develops an ongoing tension between informal constraints and the new formal rules, as many are inconsistent with each other”. In that sense, we argue that when foreign subsidiary firms operate in host countries that are distant in terms of formal institutions (i.e., greater FID), the lack of familiarity with the formal institutions in the host country is likely to increase the effects of CD as foreign subsidiaries will rely more heavily on their ability to deal with the less strict and more tacit aspects of the host country’s institutional environment. In order to test these assumptions, we hypothesize:

H2. 

FID moderates positively the effects of CD on the financial performance of foreign subsidiary firms.

Next, in Figure 1, we present the general framework of this study.

3. Methodology and Data

In order to examine the hypotheses, a quantitative approach utilizing panel data is employed. Panel data, also known as longitudinal data or cross-sectional time-series data, involves observations of the same units over multiple time periods (Park 2011; Kennedy 2008). The utilization of panel data in this study is particularly suitable due to the dynamic and rapidly changing institutional conditions in Latin American countries. By analyzing the patterns and relationships among the variables over various time periods, it is possible to investigate the effects of these volatile conditions on the relationships among the variables included in this study.

Data is from the Orbis database and includes over 1450 foreign subsidiaries, with approximately 1200 from developed countries and 250 from emerging markets operating in the 10 largest economies in Latin America over a period of 3 years ranging from 2013 to 2015. Latin America provides a relevant context for this study due to “societal, cultural, and economic characteristics that make the region an ideal ‘natural laboratory’ to build and test management theories” (Aguinis et al. 2020, p. 615). Furthermore, the diversity in our data, which includes 168 pairs of different home and host countries, provides the means to discuss the effects of distances (Franke and Richey 2010) and make comparisons regarding the implications of distances on the financial performance of foreign subsidiaries from developed countries and from emerging markets.

In order to compare the effects, we separated the data into sub-samples, including foreign subsidiary firms from developed countries and from emerging markets. The subset of emerging markets consists of 22 home countries, out of which 8 are from regions outside of Latin America. Within this subset, there are 177 foreign subsidiaries from Latin America and 73 subsidiaries from other emerging markets outside the region. On the other hand, the subset of developed countries comprises a total of 23 home countries and includes 10 distinct host countries located in Latin America. Thus, both samples are equally diversified in terms of the number of home and host countries, which makes the comparison of the results more equitable.

3.1. Dependent Variable

Financial Performance (Profit Margin)

In this study, subsidiary financial performance is measured using profit margin. In turbulent contexts such as emerging markets, sustaining the company’s profit margins becomes even more challenging and reflects management’s effectiveness at investing in projects that add value (Chopra and Mier 2017). Profit margin becomes particularly relevant for this study, and it has been extensively employed in the literature (Hitt et al. 1997; Venkatraman and Ramanujam 1986). Furthermore, the profit margin is less susceptible to the influences of different asset valuations that result from the time of investment or depreciation (Geringer and Hebert 1989; Contractor et al. 2003). When comparing firms in different industries, profit margin provides a more equitable alternative to measure firm performance as firms in different sectors use assets differently. Therefore, financial performance is measured in terms of the subsidiary’s profit margin, which was obtained from the Obis database.

3.2. Independent Variables

3.2.1. The Direction of the Distances

We follow the approach proposed in previous research (Correa da Cunha 2019; Correa da Cunha et al. 2022b; Hernández and Nieto 2015; Konara and Shirodkar 2018) and use a dummy variable (i.e., a true or false condition) to compute distances in opposite directions separately. We use “LH” (Low-High) for distances when the score in the home country is lower in comparison to the score in the host country and “HL” (High-Low) when the score in the home country is higher in comparison to the score in the host country.

Cultural Distance Measurements

CD is measured using Hofstede’s 4 original dimensions, which include Power Distance (PDI), Individualism vs. Collectivism (IDV), Masculinity vs. Femininity (MAS), and Uncertainty Avoidance (UAI). The selection of Hofstede’s model was primarily based on its established validity, reliability, and proven utility across various contexts and time periods (Hofstede 2001; Deephouse et al. 2016; Kirkman et al. 2006; Li and Parboteeah 2015; Oyserman et al. 2002). Furthermore, for the specific case of Latin America, this framework offers the most comprehensive coverage compared to other models (Shi and Wang 2011; Correa da Cunha et al. 2022a).

Formal Institutional Distance (Moderator Variable)

FIDs are measured using the World Governance Indicators (Kaufmann et al. 2009), which are closely related to the normative and regulatory pillars and have been extensively employed by different authors (Wernick et al. 2009; Gani 2007; Globerman and Shapiro 2003; Mengistu and Adhikary 2011; Stein and Daude 2001) to represent the formal institutional framework of societies. The WGI includes the following 6 variables: Voice and Accountability (VOICE), Political Stability and Absence of Violence (POL), Government Effectiveness (GOV), Regulatory Quality (REG), Rule of Law (RULE), and Control of Corruption (CC), which represent “the traditions and institutions by which authority in a country is exercised” (Kaufmann et al. 2011, p. 4). The data was collected from the World Bank website (World Bank 2021).

Due to the high correlation among the World Governance Indicator variables, the moderation tests are performed using the composite index calculated as the arithmetic mean of the 6 FID variables (in each direction). Thus, the variable FID_Direction is calculated for FID in the HL and LH directions.

$$\mathrm{FID}\_{\mathrm{Direction}}_{\mathrm{i}}={\displaystyle \sum }_{\mathrm{i}=1}^6\frac{{\left({\mathrm{I}}_{\mathrm{ij}}-{\mathrm{I}}_{\mathrm{iu}}\right)}^2}{{\mathrm{V}}_{\mathrm{i}}}$$

(1)

In Equation (1), i stands for the distance dimension; j represents the score for the home country; u is the score for the host country, V stands for the variance of each dimension of the index.

3.3. Moderation Tests

The moderation tests are performed according to Hayes (2013) by analyzing how different (and possible) values of the moderator variable (FID) affect the relationship between CD and the financial performance of foreign subsidiaries. Therefore, the moderator variable is computed by adding and subtracting 1 std. deviation from the FID_HL and FID_LH variables. We compute the interaction terms for the different levels of the FID variables (i.e., 1 std. deviation up and 1 std. deviation down) in each direction and multiply them by each CD variable. Only the results for which moderation was verified are reported.

3.4. Control Variables

Controls include industry sector (1 = industry and 0 = service) and Industry Annual Growth using the ISIC Rev.3. (International Standard Industrial Classification of All Economic. Activities, Rev.3) classification. The data for the host country’s industry sector growth was collected from the Organization for Economic Co-operation and Development (OECD) website for each of the host countries and years and matched to the ISIC codes from the Orbis database. Previous studies have shown that industry sector growth has a positive impact on firm profitability (Hay et al. 1991). Firm resources were measured in terms of size, as larger firms have access to superior resources. Size is measured using Total Assets reported annually by the firms and collected from the Orbis database. Studies have shown that larger firms have access to more resources, which allows them to overcome market disruptions (Hannan and Freeman 1984). Furthermore, larger companies tend to attract more qualified human capital, which, in the case of a multinational company, includes hiring managers with international experience (Correa da Cunha 2019).

4. Results and Discussion

In order to determine the appropriate estimator, preliminary tests were conducted. The Hausman test results indicated that the Random Effects estimator is consistent and therefore selected for further analysis. Additionally, White’s test indicated the presence of heteroscedasticity, which was corrected using heteroskedasticity-consistent covariance estimation as suggested in the econometrics literature (Andrews 1991; MacKinnon and White 1985; White 1980). Moreover, Lu and White (2014, p. 178) indicate that “a now common exercise in empirical studies is a “robustness check,” where the researcher examines how certain “core” regression coefficient estimates behave when the regression specification is modified in some way, typically by adding or removing regressors”. Moreover, when estimating firm performance, it is important to acknowledge the potential for endogeneity, as there may be factors not directly contemplated in the empirical model that are likely to influence the outcome variable. Endogeneity is formally defined (Hill et al. 2021) as the observed predictor x correlating with the unobserved residual u (i.e., elements that affect the outcome variable that are not included in the list of predictor variables in the regression equation). We address issues of endogeneity in our tests by including the relevant predictors of firm performance (i.e., control variables) and by performing the tests and comparing the results using sub-samples separated according to the origin of the firms, whether they are from emerging markets or developed countries.

By adopting a highly diversified sample and performing tests with foreign subsidiaries from developed countries and emerging markets separately, we are able to test our assumptions and reduce the issue of conflating the effects of cultural distance and country profiles (Franke and Richey 2010). However, the inclusion of different industry sectors in our data requires us to employ a simplified model to test our hypotheses. While there are many factors known to influence firm performance, such as capital structure, R&D expenditures, corporate governance, the characteristics of its managers (Bertrand and Schoar 2003; Himmelberg et al. 1999), international experience and entry mode (Johanson and Vahlne 1977; Zaheer 1995; Kogut and Singh 1988), the ability to cope with different institutional environments in the host country (Cuervo-Cazurra and Genc 2011; Ramamurti and Singh 2009; Correa da Cunha et al. 2022a), and the degree and type of internationalization approach (Correa da Cunha et al. 2023); the literature indicate that the importance of each of these factors depends on the type of industry. In that sense, in addition to including the appropriate controls to test the effects of CD and FID, we adopt a sampling approach that allows us to test and compare our findings across sub-samples with distinct characteristics in regard to the home country context. The strength of our results was verified as the size and signal for the coefficients and the characteristics of the models remained stable when new predictors were included (i.e., base model compared with results for the models including the CD variables) and across the sub-samples, including all foreign subsidiary firms, only subsidiaries from developed countries, and only subsidiaries from emerging markets.

To examine the potential advantage of foreign subsidiary firms from Latin America compared to those from other emerging markets outside the region, a dummy variable (Latin American Firm) was incorporated into the models exclusively involving emerging market firms. This dummy variable serves to assess whether foreign subsidiary firms from Latin America demonstrate any distinct benefits or advantages in comparison to their counterparts from other emerging markets outside the region. Next, we present the results, starting with the models that test the implications of CD, followed by the models testing moderation.

4.1. The Asymmetric Effects of Cultural Distance Dimensions on Financial Performance

Table 1. The asymmetric effects of CD on the financial performance of foreign subsidiary firms in Latin America. Dependent variable: profit margin.

	Full Sample (Base Model)	Full Sample (Base Model + CD Variables)	Foreign Subsidiaries from Developed Countries (Base Model)	Foreign Subsidiaries from Developed Countries (Base Model + CD Variables)	Foreign Subsidiaries from Emerging Markets (Base Model)	Foreign Subsidiaries from Emerging Markets (Base Model + CD Variables)
Const	9.020 ***	8.333 ***	10.320 ***	10.332 ***	2.701	7.714 ***
	(1.513)	(1.081)	(0.786)	(1.131)	(2.888)	(3.331)
	[0.000]	[0.000]	[0.000]	[0.000]	[0.350]	[0.021]
Industry Annual Growth	−12.956	8.782	−13.782	13.532	6.290	−0.932
	(14.170)	(13.713)	(17.949)	(22.301)	(19.134)	(17.311)
	[0.361]	[0.521]	[0.443]	[0.544]	[0.742]	[0.957]
Foreign Subsidiary Size (Total Assets)	2.20 × 10−7 ***	2.31 × 10−7 ***	2.20 × 10−7 ***	2.51 × 10−7 ***	2.75 × 10−7 ***	3.67 × 10−7 ***
	(0.000)	(4.26 × 10−8)	(0.000)	(4.21 × 10−8)	(0.000)	(1.33 × 10−8)
	[0.001]	[0.000]	[0.003]	[0.000]	[0.045]	[0.006]
Industry or Service (Dummy)	−1.244	−1.092	−1.336	−0.612	−1.415	−0.837
	(1.082)	(0.687)	(1.182)	(0.769)	(2.711)	(1.371)
	[0.250]	[0.114]	[0.258]	[0.426]	[0.602]	[0.543]
Developed Country Firm (Dummy)	1.258	1.202
	(1.506)	(1.251)
	[0.404]	[0.336]
Latin American Firm (Dummy)					7.748 **	1.632
					(3.127)	(2.651)
					[0.013]	[0.539]
PDI_LH		1.170 ***		0.801 ***		1.822 ***
Towards high Power Distance host countries		(0.201)		(0.212)		(0.297)
		[0.000]		[0.000]		[0.000]
PDI_HL		0.440		29.521 **		−0.638
Towards low Power Distance host countries		(0.735)		(14.101)		(0.785)
		[0.549]		[0.036]		[0.416]
IDV_LH		2.012		54.910		2.352
Towards Individualistic		(7.772)		(95.614)		(7.362)
host countries		[0.796]		[0.565]		[0.749]
IDV_HL		−0.295 **		−0.431 ***		−4.253 **
Towards Collectivist		(0.133)		(0.142)		(1.223)
host countries		[0.027]		[0.002]		[0.001]
MAS_LH		−0.332 **		−0.481 ***		0.576
Towards Masculine		(0.134)		(0.137)		(0.642)
host countries		[0.014]		[0.000]		[0.369]
MAS_HL		2.052 ***		1.874 ***		2.632 *
Towards Feminine		(0.434)		(0.461)		(1.37)
host countries		[0.000]		[0.000]		[0.055]
UAI_LH		−0.734 ***		−0.124		−0.693 *
Towards high Uncertainty Avoidance host countries		(0.141)		(0.236)		(0.388)
		[0.000]		[0.600]		[0.075]
UAI_HL		−4.651 ***		−12.510 **		−1.382
Towards low Uncertainty Avoidance host countries		(1.452)		(3.311)		(1.312)
		[0.001]		[0.000]		[0.293]
N	4226	4226	3545	3545	681	681
Adj. R2	0.007	0.030	0.007	0.032	0.021	0.118
p-value(F)	0.000	0.000	0.000	0.000	0.000	0.000

Notes: * p < 0.10; ** p < 0.05; *** p < 0.01. Standard errors are in parentheses, and p-values are in brackets.

presents the main results for the effects of CDs on the financial performance of foreign subsidiary firms in Latin America.

Results in Table 1 support hypothesis H1 and confirm that the effects of CD are asymmetric as they depend on the direction and characteristics of the specific cultural dimensions. Furthermore, industry sector and Industry Annual Growth do not affect financial performance in a significant way, while firm resources measured in terms of total assets affect performance in a positive way. Additionally, the results for the base model including only emerging market firms show a significant positive impact for the Latin American dummy variable, indicating that having a foreign subsidiary in Latin America has a positive impact on performance. For all of the sub-samples, when the CD variables are introduced, the explanatory capacity of the models improves, indicating that CD is an important determinant of foreign subsidiary performance.

4.2. The Moderating Effects of FID on the CD and Performance Relationship

The results for the moderation tests are presented next. Only significant results were reported. Due to the contextual characteristics of this study, which is set to investigate the case of foreign subsidiary firms operating in the context of emerging markets (Latin American host countries), the moderating effects were only identified for FID towards less developed host countries (FID_HL direction). These findings partially confirm hypothesis H2 and reveal that when foreign subsidiary firms operate in host countries with less developed formal institutions compared with the home country, the positive and negative effects of CDs tend to increase.

Next, we present the specific moderating effects of FID on each dimension of CD. We start by presenting the results for the sample, including foreign subsidiaries from developed countries, and then the results for foreign subsidiaries from emerging markets.

4.2.1. Moderating Effects of FID on the Relationship between CD and the Performance of Foreign Subsidiaries from Developed Countries

Table 2. The moderating effects of FID towards less developed host countries in the relationship between the Masculinity vs. Femininity dimension of CD and performance (dependent variable: profit margin).

	FID_HL and Masculinity LH (CD towards More Masculine Host Countries)				FID_HL and Masculinity HL (CD towards More Feminine Host Countries)
	FID_HL Decreased by 1 Std. Deviation		FID_HL Increased by 1 Std. Deviation		FID_LH Decreased by 1 Std. Deviation		FID_HL Increased by 1 Std. Deviation
	Base Model	Moderation	Base Model	Moderation	Base Model	Moderation	Base Model	Moderation
Const	11.100 ***	11.002 ***	13.112 ***	14.903 ***	10.301 ***	10.711 ***	12.221 ***	11.214 **
	(0.680)	(0.686)	(1.270)	(1.371)	(0.695)	(0.697)	(1.272)	(1.310)
	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]
Industry Annual Growth	8.560	17.310	8.561	16.602	22.800	14.601	22.814	14.802
	(22.221)	(21.503)	(22.211)	(21.500)	(21.910)	(21.814)	(21.931)	(21.801)
	[0.700]	[0.421]	[0.700]	[0.441]	[0.299]	[0.503]	[0.299]	[0.498]
Foreign Subsidiary Size (Total Assets)	2.82 × 10−7 **	2.86 × 10−7 **	2.82 × 10−7 **	2.87 × 10−7 **	2.79 × 10−7 **	2.55 × 10−7 **	2.79 × 10−7 **	2.54 × 10−7 **
	(5.70 × 10−8)	(5.22 × 10−8)	(5.70 × 10−8)	(5.22 × 10−8)	(5.01 × 10−8)	(4.80 × 10−8)	(5.01 × 10−8)	(4.81 × 10−8)
	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]
Industry or Service (Dummy)	−1.031	−1.840 **	−1.032	−1.811 **	−1.640 **	−2.110 **	−1.641 **	−2.120 **
	(0.785)	(0.777)	(0.785)	(0.777)	(0.785)	(0.784)	(0.785)	(0.784)
	[0.191]	[0.018]	[0.191]	[0.020]	[0.036]	[0.007]	[0.036]	[0.007]
MAS_LH	−0.277 **	−0.905 ***	−0.277 **	−3.180 ***
CD towards more Masculine host countries	(0.133)	(0.184)	(0.133)	(0.551)
	[0.037]	[0.000]	[0.037]	[0.000]
MAS_HL					1.110 **	−0.761	1.110 **	2.360 ***
CD towards more Feminine host countries					(0.451)	(0.555)	(0.451)	(0.555)
					[0.014]	[0.171]	[0.014]	[0.000]
FID_HL	−0.321 **	−0.270 **			−0.300 **	−0.236 *
(decreased by 1 std. deviation)	(0.129)	(0.124)			(0.121)	(0.124)
	[0.013]	[0.030]			[0.013]	[0.057]
FID_HL			−0.321 **	−0.265 **			−0.300 **	−0.241 *
(increased by 1 std. deviation)			(0.129)	(0.124)			(0.121)	(0.124)
			[0.013]	[0.033]			[0.013]	[0.052]
MAS_LH × FID_HL (decreased by 1 std. deviation)		0.343 ***
		(0.0615)
		[0.000]
MAS_LH × FID_HL (increased by 1 std. deviation)				0.349 ***
				(0.0627)
				[0.000]
MAS_HL × FID_HL						−0.477 ***
(decreased by 1 std. deviation)						(0.119)
						[0.000]
MAS_HL × FID_HL								−0.491 ***
(increased by 1 std. deviation)								(0.118)
								[0.000]
N	3545	3545	3545	3545	3545	3545	3545	3545
Adj. R2	0.011	0.019	0.011	0.019	0.014	0.016	0.014	0.017
p-value(F)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

Notes: * p < 0.10; ** p < 0.05; *** p < 0.01. Standard errors are in parentheses, and p-values are in brackets.

presents the positive moderating effects of FID towards less developed host countries (FID_HL) in the relationship between the Masculinity vs. Femininity dimension of CD and the financial performance of foreign subsidiary firms from developed countries. The base models include only the first-order components, while the interaction models include the interaction term (i.e., the product of the CD variable and the FID variable increased and decreased by one std. deviation).

Results for the Masculinity vs. Femininity dimension of CD confirm hypothesis H2, as FID_HL moderates positively the effects of this dimension of CD on financial performance. These findings provide a complementary view of the results for the effects of CD presented in Table 1, as they highlight that the negative effects associated with CD towards host countries with more Masculinity (MAS_LH) increase when FID towards less developed host countries increases (i.e., high values of FID_HL). The positive moderation is verified by the change in the coefficient for the effects of MAS_LH, which is −0.905 (p-value < 0.01) at low values for FID_HL (i.e., shorter distances, which are calculated by subtracting one std. deviation), and it increases to −3.180 (p-value < 0.01) when one std. deviation is added to the FID_HL variable. The adjusted R-squared also confirms the moderation, as there is a significant improvement when the interaction term is introduced.

Additionally, FID towards less developed host countries moderates the effects of CD towards more feminine host countries (MAS_HL). However, as the direct effects of CD towards more feminine host countries are positive, the positive moderating effects of FID_HL cause the effects of MAS_HL to change to −0.761 (non-significant) when FID_HL are small, and the effects increase to a positive 2.360 (significant, p-value < 0.01) when one std. deviation is added to the FID_HL variable.

The change in the effects of the Masculinity vs. Femininity dimension of CD on the performance of foreign subsidiaries from developed countries supports hypothesis H2, as there is a significant increase in the effects corresponding to greater FID towards less developed host countries. These findings suggest that FID towards less developed countries can either increase the negative effects of CD towards more masculine host countries or increase the positive effects associated with CD towards more feminine host countries. Therefore, the moderating effects of FID on the Masculinity vs. Femininity dimension of CD show that when the quality of formal institutions in the host country is lower, the financial performance of foreign subsidiary firms becomes more dependent on the cultural characteristics of the host country.

Next, in

Table 3. The moderating effects of FID towards less developed host countries in the relationship between the Uncertainty Avoidance dimension of CD and performance. Dependent variable: profit margin.

	FID_HL and Uncertainty Avoidance LH (CD towards High Uncertainty Avoidance Host Countries)				FID_HL and Uncertainty Avoidance HL (CD towards High Uncertainty Avoidance Host Countries)
	FID_HL Decreased by 1 Std. Deviation		FID_HL Increased by 1 Std. Deviation		FID_HL Decreased by 1 Std. Deviation		FID_HL Increased by 1 Std. Deviation
	Base Model	Moderation	Base Model	Moderation	Base Model	Moderation	Base Model	Moderation
Const	10.703 **	9.661 **	12.722 **	12.441 **	11.517 **	11.423 **	13.910 **	14.802 **
	(0.719)	(0.819)	(1.242)	(1.301)	(0.703)	(0.719)	(1.260)	(1.341)
	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]
Industry Annual Growth	19.810	30.800	19.821	29.425	13.001	17.917	13.002	21.711
	(22.610)	(22.613)	(22.652)	(22.622)	(22.301)	(22.300)	(22.302)	(22.423)
	[0.380]	[0.173]	[0.380]	[0.193]	[0.560]	[0.422]	[0.560]	[0.334]
Foreign Subsidiary Size (Total Assets)	2.86 × 10−7 **	2.85 × 10−7 **	2.86 × 10−7 **	2.93 × 10−7 **	3.04 × 10−7 **	3.29 × 10−7 **	3.04 × 10−7 **	3.22 × 10−7 **
	(5.47 × 10−8)	(5.51 × 10−8)	(5.47 × 10−8)	(5.46 × 10−8)	(5.74 × 10−8)	(5.59 × 10−8)	(5.74 × 10−8)	(5.63 × 10−8)
	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]
Industry or Service (Dummy)	−1.311 *	−1.540 **	−1.312 *	−1.453 *	−1.660 **	−1.671 **	−1.663 **	−1.617 **
	(0.782)	(0.778)	(0.782)	(0.777)	(0.780)	(0.785)	(0.780)	(0.788)
	[0.094]	[0.048]	[0.094]	[0.063]	[0.034]	[0.034]	[0.034]	[0.042]
UAI_LH	−0.151	0.273	−0.151	−0.478 **
CD towards high Uncertainty Avoidance host countries	(0.177)	(0.289)	(0.177)	(0.224)
	[0.392]	[0.345]	[0.392]	[0.033]
UAI_HL					−11.101 **	−6.671 *	−11.121 **	−3.640
CD towards low Uncertainty Avoidance host countries					(2.481)	(3.572)	(2.481)	(5.840)
					[0.000]	[0.062]	[0.000]	[0.533]
FID_HL (decreased by 1 std. deviation)	−0.312 **	−0.245 **			−0.375 **	−0.434 **
	(0.117)	(0.119)			(0.120)	(0.129)
	[0.007]	[0.039]			[0.002]	[0.001]
FID_HL (increased by 1 std. deviation)			−0.312 **	−0.241 **			−0.375 **	−0.513 **
			(0.117)	(0.118)			(0.120)	(0.128)
			[0.007]	[0.042]			[0.002]	[0.000]
UAI_LH × FID_HL (decreased by 1 std. deviation)		0.127 **
		(0.0553)
		[0.021]
UAI_LH × FID_HL (increased by 1 std. deviation)				0.112 **
				(0.0545)
				[0.041]
UAI_HL × FID_HL (decreased by 1 std. deviation)						−0.929 **
						(0.419)
						[0.026]
UAI_HL × FID_HL (increased by 1 std. deviation)								−0.513
								(0.393)
								[0.192]
N	3545	3545	3545	3545	3545	3545	3545	3545
Adj. R2	0.010	0.011	0.010	0.011	0.016	0.032	0.016	0.030
p-value(F)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

Notes: * p < 0.10; ** p < 0.05. Standard errors are in parentheses, and p-values are in brackets.

, we present the moderating effects of FID on less developed host countries in the relationship between the Uncertainty Avoidance dimension of CD and the financial performance of foreign subsidiaries from developed countries.

Table 3 shows that when FID towards less developed host countries increases, the effects of the Uncertainty Avoidance dimension of CD in the LH (i.e., towards host countries that score higher) change from 0.273 (non-significant) to a negative −0.478 (p-value < 0.01). By comparing these results (Table 3) with the negative effects found for UAI_LH in Table 1 (−0.734, p-value < 0.01), these findings partially support hypothesis H2 as the negative effects of CD towards host countries that score high in terms of Uncertainty Avoidance increase when combined with higher FID towards less developed host countries.

On the other hand, the moderation effects of FID-HL in the Uncertainty Avoidance dimension of CD towards host countries that score lower in this dimension of CD change from a significant −6.671 (p-value < 0.01) when one std. deviation is subtracted from FID_HL to −3.640 and non-significant effect when one std. deviation is added to the moderator variable. These findings reveal that the interaction of FID and CD can result in different effects depending on the specific characteristics of the cultural dimension.

4.2.2. Moderating Effects of FID on the Relationship between CD and the Performance of Foreign Subsidiaries from Emerging Markets

Table 4. The moderating effects of FID towards less developed host countries in the relationship between the Power Distance dimension of CD and the performance of foreign subsidiaries of emerging market firms. Dependent variable: profit margin.

	FID_HL and Power Distance LH (CD towards High Power Distance Host Countries)
	FID_HL Decreased by 1 Std. Deviation		FID_HL Increased by 1 Std. Deviation
	Base Model	Moderation	Base Model	Moderation
Const	3.414 *	4.012 **	2.201	1.730
	(1.856)	(1.962)	(2.881)	(2.910)
	[0.065]	[0.041]	[0.446]	[0.552]
Industry Annual Growth	9.792	10.433	9.792	10.102
	(22.324)	(22.411)	(22.321)	(22.324)
	[0.660]	[0.643]	[0.660]	[0.650]
Latin American Firm (Dummy)	5.085 **	5.291 **	5.082 **	5.357 **
	(1.939)	(1.942)	(1.934)	(1.942)
	[0.009]	[0.006]	[0.009]	[0.006]
Foreign Subsidiary Size (Total Assets)	2.82 × 10−7	1.99 × 10−7	2.82 × 10−7	1.81 × 10−7
	(2.20 × 10−7)	(1.80 × 10−7)	(2.20 × 10−7)	(1.63 × 10−7)
	[0.201]	[0.269]	[0.201]	[0.269]
Industry or Service (Dummy)	0.256	−0.238	0.256	−0.243
	(1.805)	(1.793)	(1.801)	(1.771)
	[0.887]	[0.894]	[0.887]	[0.891]
PDI_LH	1.673 **	−0.428	1.676 **	5.953 **
CD towards high Power Distance host countries	(0.531)	(0.944)	(0.531)	(1.473)
	[0.002]	[0.651]	[0.002]	[0.000]
FID_HL	0.190	0.331
(decreased by 1 std. deviation)	(0.323)	(0.377)
	[0.556]	[0.380]
PDI_LH × FID_HL		−0.902 **
(decreased by 1 std. deviation)		(0.355)
		[0.011]
FID_HL			0.190	0.352
(increased by 1 std. deviation)			(0.323)	(0.374)
			[0.556]	[0.346]
PDI_LH × FID_HL				−1.062 **
(increased by 1 std. deviation)				(0.381)
				[0.005]
N	681	681	681	681
Adj. R2	0.023	0.163	0.023	0.142
p-value(F)	0.000	0.000	0.000	0.000

Notes: * p < 0.10; ** p < 0.05. Standard errors are in parentheses, and p-values are in brackets.

shows the results for FID towards less developed host countries, moderating the effects of the Power Distance dimension of CD on the performance of emerging market firms.

The moderating effects of FID in the relationship between the Power Distance dimension of CD and the financial performance of foreign subsidiaries from emerging markets presented in Table 4 support hypothesis H2. Results show that the effects of CD towards high Power Distance host countries change from a non-significant –0.428 corresponding to smaller FID towards less developed host countries (i.e., when one std. deviation is subtracted from the FID_HL variable) to a positive 5.953 and significant effect when FID towards less developed host countries is increased by one std. deviation. In addition to the increase in the effects of CD corresponding to greater FID towards less developed host countries, the explanatory capacity of the models (adjusted R-squared) increases from 0.023 to 0.163 and 0.142 for the models including the interaction terms. According to Hayes (2013), both conditions confirm the positive moderating effects of FID in the relationship between CD and performance.

Therefore, our findings reveal that the greater the FID towards less developed host countries, the higher the positive returns associated with CD towards high Power Distance host countries on the performance of foreign subsidiaries from emerging markets. These results show that the ability of foreign subsidiary firms from emerging markets to obtain positive returns from their ability to accommodate the effects of CD on high Power Distance host countries is constrained by the quality of formal institutions in the host country.

The findings provide partial support for hypothesis H2 by highlighting that the higher the FID towards less developed host countries, the more pronounced the effects of CD on the financial performance of foreign subsidiary firms. By considering the direction of FID, these results suggest that foreign subsidiary firms are more exposed to the positive and negative effects of CD when operating in host countries with less supportive formal institutions.

5. Conclusions

5.1. Theoretical Implications

We contribute to advancing knowledge of how cultural and formal institutional distances affect the financial performance of foreign subsidiary firms by investigating how FID moderates the relationship between CD and performance. By considering the direction of CD and FID, we highlight the asymmetric effects of CD, which are moderated positively by FID towards less developed host countries. These findings are consistent with North (1990, p. 47), who posited that formal institutions are “enacted to modify, revise, or replace informal constraints”, as they show that when foreign subsidiaries operate in host countries characterized by weak formal institutions, the positive and negative effects of CD are likely to increase. In that sense, we provide empirical evidence that foreign subsidiary firms are likely to rely more on their ability to cope with the more tacit characteristics and implications of CD when formal institutions in the host country are ineffective.

5.2. Practical Implications

By addressing the interaction hypothesis, our findings reveal that FID towards less developed host countries increases the effects of CD on the financial performance of foreign subsidiary firms in specific ways. Being aware of these implications can help firms identify alternatives to compensate for the lack of formal institutional support when operating in less developed host countries in order to accommodate the effects of CD more positively. For instance, in regard to the effects of the Masculinity vs. Femininity dimension of CD, our results show that not only do the negative effects on the performance of foreign subsidiaries from developed countries associated with CD towards more masculine host countries increase, but also that the positive effects associated with CD towards more feminine host countries also increase with greater FID towards less developed host countries. Furthermore, it is shown that the negative effects associated with CD towards high Uncertainty Avoidance host countries on the performance of foreign subsidiary firms from developed countries tend to increase with greater FID towards less developed host countries. When CD is towards low Uncertainty Avoidance host countries, greater FID towards less developed host countries causes the relationship between CD and performance to turn non-significant. These findings indicate that CD towards high Uncertainty Avoidance host countries requires “more formal laws and informal rules controlling the rights and duties of employers and employees” (Hofstede et al. 2010, p. 209), whereas greater FID towards less developed host countries seems to cause the effects of CD towards low Uncertainty Avoidance countries to have a lower and non-significant effect. Moreover, it can be concluded that FID towards less developed host countries makes it more difficult to implement and enforce contracts (Claessens and Van Horen 2008; Lumineau and Malhotra 2011), which in turn increases the negative effects associated with CD towards high Uncertainty Avoidance on the performance of foreign subsidiaries from developed countries.

When it comes to the moderating effects of FID on the relationship between CD and the financial performance of foreign subsidiaries from emerging markets, our findings reveal that when in less developed host countries, these firms seem to take advantage of their expertise in high Power Distance contexts. Although studies indicate that “the use of power should be subject to laws and to the judgment between good and evil. Inequality is considered basically undesirable; although unavoidable, it should be minimized by political means” (Hofstede et al. 2010, p. 78). Our findings show that when in less developed host countries, foreign subsidiaries from emerging markets rely more on their expertise to accommodate in a positive way the effects of CD in high Power Distance host countries.

5.3. Limitations and Direction for Future Research

Despite the contributions, we consider that our study has some limitations that provide fertile ground for future research. First, our data enabled us to verify the effects of the different dimensions of CD on host countries with distinct (opposite) characteristics; however, we consider that despite being important, CD provides a restricted view of how countries differ in terms of informal institutions. In that sense, future research could broaden the discussion by including different aspects of informal institutions, such as social ties and the level of regional embeddedness, among others. Second, as the main contribution of this study relates to how FID moderates the relationship between CD and performance, future studies could strengthen our findings by investigating how FIDs towards more developed host countries might moderate in a negative way (i.e., suppress) the effects of CD. Thus, we believe that the power of formal institutions to moderate the effects of informal institutional constraints is likely to depend on country profiles and the ability of foreign subsidiary firms to cope with such environments. In order to reduce the issues of conflating distance and profile effects, this study included firms from several home countries and from different sectors. Future research can strengthen our findings and conclusions by testing these relationships on firms operating in specific industries and by testing the implications of several factors that may complement the analysis of the determinants of firm performance in these industries. Furthermore, future studies could explore the diverse institutional settings in different contexts to explore the complex systems of how such moderation operates and how firms’ ownership advantages can interfere with such relationships.