Antecedents and performance effect of managerial misperception of institutional differences

Journal of World Business 55 (2020) 101018

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Antecedents and performance effect of managerial misperception of institutional differences

T

Clarissa E. Webera, , Dominik Chahabadia,b, Indre Maurera ⁎

a b

University of Goettingen, Faculty of Economic Sciences, Platz der Goettinger Sieben 3, 37073 Goettingen, Germany Macquarie University, Macquarie Business School, Department of Management, 4 Eastern Road, NSW 2109, Australia

ARTICLE INFO

ABSTRACT

Keywords: Managerial misperception Country differences Institutional differences Bounded rationality Information-based view

This study examines managerial misperception of institutional differences between countries—the deviation of managers’ perceived differences from actual ones. Drawing on a bounded-rationality perspective and an information-based view, we theorize about the effect and contextual antecedents of managerial misperception of country differences. Examining data from 186 managerial assessments confirms a negative relationship between managerial misperception and firms’ host-country performance, providing evidence for the relevance of this construct for international-management research and practice. Furthermore, in line with our theory, we find support for a direct impact of variables determining information-access opportunity and information-processing complexity as contextual antecedents of managerial misperception.

1. Introduction Differences between countries are a fundamental element of international-management research and practice (Aharoni & Brock, 2010; Shenkar, 2001; Zaheer, Schomaker, & Nachum, 2012). Often referred to as the “distance” between countries, differences in language, culture, politics, or rule of law are of special interest in this field of business research (Håkanson & Ambos, 2010; Hutzschenreuter, Kleindienst, & Lange, 2015) because of their influence on various aspects of firms’ operations (Berry, Guillén, & Zhou, 2010; Child, Rodrigues, & Frynas, 2009; Dow & Larimo, 2009). Concepts of distance include cultural (e.g., Kogut & Singh, 1988), institutional (e.g., Xu & Shenkar, 2002), and psychic distance (e.g., Johanson & Vahlne, 1977), to name some of the most prominent. These types of distance (and the differences they represent) have been shown to significantly influence firm performance in international markets (e.g., Dikova, 2009; Evans & Mavondo, 2002), entry-mode decisions (e.g., Harzing, 2003; Hennart & Larimo, 1998; Tihanyi, Griffith, & Russell, 2005), market choices (e.g., Ellis, 2008; Pogrebnyakov & Maitland, 2011), headquarters-subsidiary relationships (e.g., Baaij & Slangen, 2013; Dellestrand & Kappen, 2012), and cross-border inter-organizational relations (e.g., Barkema & Vermeulen, 1997; Luo, 2002). Prior research has conceptualized and measured differences between countries in two ways: as actual and perceived differences. The focus of most studies is on actual differences between countries and they

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use exogenous measures from sources such as the World Economic Forum and Hofstede’s World Value Survey to operationalize distance between countries when testing effects of country differences on outcome variables (e.g., Berry et al., 2010; Dow & Karunaratna, 2006; Kogut & Singh, 1988). In recent years, however, an increasing number of studies has challenged this dominant approach and has shifted to conceptualizing and measuring the distance as perceived by managers (Dow & Larimo, 2009), empirically relying on primary measures of distance (e.g., Brouthers, 2002; Dow, 2009; Evans & Mavondo, 2002; Håkanson, Ambos, Schuster, & Leicht-Deobald, 2016). As recent studies (e.g., Beugelsdijk, Ambos, & Nell, 2018; Brouthers, 2013) have pointed out, the choice between actual distance (and exogenous measures) or perceived distance (and perception-based measures) depends on what is being studied. Particularly when analyzing the impact of country differences on managers’ decision making, perceived differences are more suitable, since managers base their decisions on perceptions of the environment and not on actual conditions (Baack, Dow, Parente, & Bacon, 2015; Sousa & Bradley, 2006). The debate on the use and usefulness of actual versus perceived distance evidently implies that the two differ (Håkanson & Ambos, 2010; O’Grady & Lane, 1996). Because managers’ time and cognitive capacity is limited—that is, because their rationality is bounded (Simon, 1955, 1957)—their perceptions of differences between homeand host-country environments will likely never be completely accurate. We refer to this deviation between actual and perceived

Corresponding author. E-mail address: [email protected] (C.E. Weber).

https://doi.org/10.1016/j.jwb.2019.101018 Received 10 August 2018; Received in revised form 29 June 2019; Accepted 2 August 2019 1090-9516/ © 2019 Elsevier Inc. All rights reserved.

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differences as managerial misperception of country differences. While deviations of perceptions from actual conditions have been the subject of research in various fields of management, such as in studies on managers’ (mis-)perceptions of their own organizations (Payne & Pugh, 1976), of competitive environments (De Chernatony, Daniels, & Johnson, 1993), of risk (Bromiley, McShane, Nair, & Rustambekov, 2015), of network resources (Grundvåg-Ottesen, Foss, & Grønhaug, 2004), and of potential partners (Hallen & Pahnke, 2016), little attention has been paid to the phenomenon of managers’ misperception of country differences in their firms’ international activities (Håkanson & Ambos, 2010). However, since perceptions of country differences directly influence managerial decision making (Anderson & Paine, 1975; Dow & Larimo, 2009), taking these deviations in perceptions from actual conditions into consideration is critically important for international-management research when trying to understand why and how decisions are formed and how they relate to outcomes. As Håkanson and Ambos (2010: 208) state, studies on these managerial misjudgments of country environments are “badly needed” in order to understand the associated consequences of misperception for internationalizing firms and to move research in the field forward. As a first step in this direction, we start from an institutional perspective on country environments and draw on a contextual boundedrationality perspective with an information-based view (Cohen, Bingham, & Hallen, 2018; Hallen & Pahnke, 2016) to theorize and test (a) how managerial misperception of country differences impacts firm performance, and (b) how contextual antecedents impact a manager’s degree of misperception. We test our hypotheses on 186 managerial assessments of differences between home and host countries from a data set of firms in the German renewable-energy industry, which is heavily populated by SMEs. This context is particularly suitable for our study because these relatively small German technology-focused firms usually have only one manager responsible for the firm’s international decision making. Thus, this setting allows us to very neatly test the relationship between managerial misperception, its contextual antecedents, and its influence on a firm’s performance. The analyses support our hypotheses. Our study contributes to management literature in two ways: First, we put forward and shed light on the theoretically important construct of managerial misperception of country differences, which expands the explanatory scope of how country differences matter for outcomes in international management and allows us to better understand the processes and outcomes of managerial decision making. Second, by extending the bounded-rationality approach using an informationbased view, we respond to recent calls to study “when, how, and why” (Baack et al., 2015: 952) individual perceptions of country differences deviate from actual conditions.

internationalizing firms to gain legitimacy in their host countries, because it is harder to understand country specificities and adapt decisions and strategies accordingly (Kostova & Zaheer, 1999; Salomon & Wu, 2012). Thus, the institutional perspective on country differences is strongly connected to managerial perceptions (even though this connection is often not explicated)—and implies that these perceptions will likely not be perfect. In order to embrace this assumption more explicitly, we next draw on the concept of bounded rationality to explain the underlying reasons why actual and perceived institutional differences diverge. 2.2. Bounded rationality and the assessment of country environments Grounded in behavioral approaches (Cyert & March, 1963; Simon, 1955), research by Aharoni (1966) and scholars of the Uppsala school (e.g. Johanson & Vahlne, 1977; Johanson & Wiedersheim-Paul, 1975) acknowledged early on that internationalization decisions and managers’ accompanying assessments of given conditions are always restricted by cognitive and temporal limits (Håkanson & Ambos, 2010). Although managerial misperception of country differences has so far been scarcely considered, the general acknowledgement that managerial assessments in internationalization processes are impacted by bounded rationality and its consequences is an implicit assumption in the field (Maitland & Sammartino, 2015). Assessing the characteristics of host countries and their differences from a given home country is an integral part of internationalization processes because it precedes managers’ decisions about how to operate in host-country environments. Such assessments require both extensive information gathering and substantial cognitive processing (Håkanson & Ambos, 2010; Williams & Gregoire, 2015). Yet, as human beings, managers are subject to bounded rationality: they possess limited knowledge, memory, and attention span (Simon, 1955, 1957). These limitations increase the cost of acquiring, accumulating, and applying knowledge and information (Baer, Dirks, & Nickerson, 2013) because they restrict managers’ ability to absorb information and process complex problems (Cyert & March, 1963). As a consequence, individuals tend to satisfice: that is, when making complex decisions or assessments they reduce the time and cognitive effort spent gathering information and sometimes rely on heuristics instead (March, 1978; Simon, 1956). Even though heuristics may help managers when collecting additional information is difficult or when making an assessment is overly complex, this approach may be fallible or simply not available (March & Simon, 1958; Tversky & Kahneman, 1974). As recent studies on bounded rationality and managerial misperception show (e.g., Cohen et al., 2018; Hallen & Pahnke, 2016), satisficing depends on the cost of collecting any additional piece of information, and thus on how easily information can be accessed as well as on how much complexity is involved. We adopt this information-based view, and argue that managers who have an opportunity to easily access required information (information-access opportunity) have decreased cognitive demands when assessing differences between countries, which results in their being able to make better assessments (Cohen et al., 2018). Furthermore, we assume that increased complexity within the assessment or the extent of a manager’s overall tasks (information-processing complexity) increases the cost of collecting and processing information, which results in individuals conducting less extensive information collection and processing (Garicano & Wu, 2012; Hambrick, Finkelstein, & Mooney, 2005). In line with Clark, Li, and Shepherd (2018) we argue that more complex information-processing demands aggravate the problem of limited time and cognitive resources and therefore hamper accurate assessments of country differences. Next, we explain and hypothesize how misperception of country differences relates to a firm’s performance in a respective host country. After that, we theorize about contextual antecedents of managerial misperception that determine information-access opportunity and information-processing complexity.

2. Theory and hypotheses 2.1. Conceptualizing differences between countries: the institutional perspective The concept of institutional distance—differences in the institutional environments of two countries—is probably the most established way of conceptualizing differences between countries in contemporary international-management research (Salomon & Wu, 2012; Xu & Shenkar, 2002). The concept originates from Kostova (1996), and was built on Scott’s (1995) conceptualization of institutional environments as consisting of regulative, normative, and cultural-cognitive elements. Regulative elements refer to laws and regulations, normative elements refer to values and norms prevalent in a country, and cultural-cognitive elements refer to general taken-for-granted assumptions of “how things are done” in a respective environment (Gaur & Lu, 2007). The institutional perspective has produced several important insights into the topic of country differences. Most importantly, it argues that high levels of institutional differences between countries make it more difficult for 2

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2.3. Managerial misperception and host-country performance

country, who serves as a primary external basis for information access (Hitt, Dacin, Levitas, Arregle, & Borza, 2000; Li, Poppo, & Zhou, 2010; Makino & Delios, 1996). With regard to the internal resource endowment, the basic argument is that larger firms have greater and more diverse resources available to deal with complexity and are therefore more successful abroad (Shrader & Simon, 1997; Stinchome, 1965; Sui & Baum, 2014). These resources can be, for example, financial assets and, especially, knowledge and experience (Acedo & Florin, 2006; Aldrich & Auster, 1986). Smaller firms, however, may not have sufficient financial and knowledge resources to properly manage the complexity of operating internationally. This circumstance is especially true for SMEs, whose general scarcity of resources turns size into an important driver of a firm’s internal resource endowment (Li, Qian, & Qian, 2012b). In the complex process of assessing a host country’s environment and differences between home and host country, managers in larger firms can draw on the knowledge and information available within the firm without themselves collecting and acquiring them from scratch. This access to an internal information and knowledge base informs a manager’s perception and judgment and thus makes knowledge processing easier and more comprehensive, thereby alleviating the perils of satisficing. Easier access to information also frees a manager’s valuable time and capacity (Elbanna & Child, 2007), which can then be used to add to and broaden the existing knowledge base, further honing the accuracy of a manager’s perception. Additionally, routines and standardized procedures in larger firms may improve a manager’s provision and use of existing knowledge and information (Bingham & Eisenhardt, 2011). Finally, the better internal resource endowment of larger firms also facilitates access to outside information because the availability of financial resources enables the manager to hire consultants or employ boundary spanners (“buying knowledge”) (Haunschild & Beckman, 1998). Smaller firms with limited resources, by contrast, lack these options (LiPuma, Newbert, & Doh, 2013) and managers will have to collect information themselves, which consumes both time and cognitive capacity and, in turn, mitigates the accuracy of their perceptions. Accordingly, we hypothesize:

A major reason for the interest in managerial misperception of environmental conditions is the core assumption of management research that strategic decisions need to be properly adapted to given environments (Hambrick & Mason, 1984; Venkatraman, 1989). A “fit” between environment and managerial decisions is crucial for a firm’s performance and survival because it enables strategies associated with these decisions to fully take effect. Building upon this assumption, international-management research has argued and shown that in order to be successful in a given host country, firms need to adapt their internationalization strategies, such as the entry mode chosen or retail strategy pursued, to align with host-countries’ institutional environments and to adjust for the differences between home and host countries (Brouthers, 2002; Kostova, Roth, & Dacin, 2008; Meyer, Estrin, Bhaumik, & Peng, 2009). Yet, such adaptations as well as the underlying decisions are based on a manager’s perception of environmental conditions (and not on actual ones) (Baack et al., 2015; Sousa & Bradley, 2006). We posit that the degree of inconsistency between actual and perceived institutional differences will directly impact the fit between decisions and environmental conditions. Managers whose misperception is high will take less informed—and likely inapt—decisions. Strategies chosen and implemented based on misperceived country differences are unlikely to be adequately adapted to the host-country’s actual institutional environment, and thus performance outcomes will be inferior (Brouthers, 2013; Evans, Mavondo, & Bridson, 2008). We therefore hypothesize that a less accurate judgment of differences between the home and host country will ultimately hamper firm performance in this host country. Accordingly, we posit: Hypothesis 1. There is a negative relationship between a manager’s misperception of differences between home and host country and a firm’s host-country performance. 2.4. Contextual antecedents of managerial misperception: Informationaccess opportunity and information-processing complexity

Hypothesis 2a. There is a negative relationship between a firm’s size and a manager’s misperception of differences between home and host country.

Correctly assessing a foreign environment and its differences from a home country is a challenging task and requires extensive information gathering and substantial cognitive processing (Håkanson & Ambos, 2010; Williams & Gregoire, 2015). While managerial misperception of country differences will always be present to a certain degree (Mezias & Starbuck, 2003; Nadkarni & Barr, 2008; Sutcliffe, 1994), the degree of misperception is influenced by contextual antecedents that are the foundation on which assessments are built—and also impact how they are built (Hallen & Pahnke, 2016; Schwens & Kabst, 2011). These antecedents relate to two core aspects of the bounded-rationality problem: the first is the degree of information access (information-access opportunity), and the second is the level of complexity associated with an assessment (information-processing complexity) (Clement, 1999; Mezias & Starbuck, 2003).

In addition to the internal basis of information access, a manager’s information-access opportunity is also determined by external relationships (Hallen & Pahnke, 2016). For a manager, access to local knowledge and information is crucial when making decisions (Makino & Delios, 1996). Local knowledge is primarily accessible from local key partners, who are often a manager’s most important source of countryand market-specific knowledge (Ellis, 2000; Yli-Renko, Autio, & Sapienza, 2001). Absorbing knowledge from a native source is especially valuable because it is first hand (Jonsson & Lindbergh, 2010; Lu & Beamish, 2006) and strongly impacts a manager’s understanding of a given environment. A key partner not only taps into a deep and broad base of local knowledge and information, but is also available to interpret and explain whenever needed (Li et al., 2010). A host-country partner can also act as a boundary spanner and translator when knowledge and information are complex and tacit, and difficult for a manager to assess and interpret (Eriksson, Johanson, Majkgard, & Sharma, 1997). A key partner in a host country, thus, is a valuable external basis for a manager’s access to information, both qualitatively and quantitatively (Hitt et al., 2000; Yan & Gray, 1994). In addition to the information a host-country partner provides, the relationship itself and the interaction and communication with a local partner often help managers learn about home- and host-country differences (Griffith, Myers, & Harvey, 2006; Tsang, 2002). This combination provides fast and efficient ways to make an informed assessment, thereby alleviating a manager’s problem of limited time and cognitive capacity and the perils of satisficing. Thus, we hypothesize:

2.4.1. Information-access opportunity Information-access opportunity is an essential factor determining how strongly managers’ bounded rationality influences the quality of their assessments. Ample access to information will lead to lower levels of managerial misperception because under these conditions an assessment can be made more easily and results in more efficient use of time and cognitive resources (Hallen & Pahnke, 2016). According to prior literature, the information-access opportunity of a manager responsible for international activity is primarily determined by two factors: first, by a firm’s resource endowment, and thus its size, which defines a manager’s internal basis for information access (Acedo & Florin, 2006; Sui & Baum, 2014); and second, by the availability of local knowledge, which is typically acquired via the key partner in a host 3

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Hypothesis 2b. There is a negative relationship between the access to localpartner knowledge and a manager’s misperception of differences between home and host country.

internationalization activities, which implies a great degree of heterogeneity in how these activities need to be carried out and thereby translates to a high level of overall heterogeneity in a manager’s cumulative tasks (Khavul, Pérez-Nordtvedt, & Wood, 2010; Vermeulen & Barkema, 2002). The more geographic regions a manager is responsible for, the greater the amount of information about characteristics of regions and countries a manager needs to collect and process to accurately assess differences between the home country and each individual host country (Ghoshal & Bartlett, 1990; Hitt, Hoskisson, & Kim, 1997; Lin, 2012). Because the accuracy of managers’ perceptions is a function of time and cognitive capacity they can afford to invest in supervising and monitoring operations in a single country, a high international scope leaves them with relatively little time and cognitive capacity to learn about every individual country in-depth and will therefore lead to a higher degree of misperception (Arrow, 1974; Baer et al., 2013; Kumar, 2009). Managers in these situations will then be more likely to quickly satisfice and rely on easily available heuristics (Tversky & Kahneman, 1973).1 Even though heuristics may be a fast and efficient way to assess or to make a decision, assessments and decisions based on heuristics may not be accurate. Being responsible for many heterogeneous regions, managers have less time to benefit from learning effects and any inferences they make may be especially error prone, because they may overlook subtle but essential differences (O’Grady & Lane, 1996). Therefore, the greater the number of geographic regions included within a manager’s task, the less capacity a manager has to collect and process information and knowledge of a single country, thus increasing his or her misperception. We therefore hypothesize:

2.4.2. Information-processing complexity Complexity of information processing is a major parameter of the bounded-rationality problem: Because situations and settings to be assessed are opaque, ill-structured, and multilayered, assessments are difficult even for managers in well-endowed firms and with access to local knowledge. The degree of this difficulty depends on the two substantial sources of complexity that inhibit accurate assessments: (1) the complexity of the individual assessment, meaning the ambiguity and uncertainty inherent in it; and (2) the overall complexity of an individual’s task, meaning the extent of work that has to be managed in a finite time frame (Calori, Johnson, & Sarnin, 1994). The inherent complexity of assessments challenges a manager’s available capacity and may affect the quality of a manager’s work (Garicano & Wu, 2012; Hambrick et al., 2005). Opaque conditions entangled with interrelations require from a manager more capacity to accurately assess them than those that are relatively easy to engage with and understand. A common source of such complexity is the actual cultural distance between the home and host country (Hutzschenreuter & Horstkotte, 2013; Kogut & Singh, 1988). The greater the cultural distance between the home and host country—that is, the more heterogeneity between cultures—the more complex business operations become for the internationalizing firm in the host country (Evans et al., 2008; Johanson & Vahlne, 1977). With increasing cultural distance it becomes increasingly difficult for managers to identify, assess, and interpret information about a host country (Dow & Larimo, 2009; Sousa & Bradley, 2006) because every cultural setting requires that managers must possess a specific cognitive understanding of how a given context works before they can properly assess and interpret knowledge and information. Without this cognitive basis, a manager cannot thoroughly understand host-country characteristics (Johanson & Vahlne, 1977; Zeng, Shenkar, Lee, & Song, 2013). Furthermore, the greater the cultural distance and the more difficult it is for a manager to understand an environment and recognize the differences between it and a home country, the more susceptible managers may be to use heuristics and satisfice with easily available information (Tversky & Kahneman, 1974). Yet, because heuristics do not necessarily account for subtle but important differences, they may be fallible in this context (Gavetti, Levinthal, & Ocasio, 2007; March, 1978). In contrast, environments with common cultural elements help a manager to interact, communicate, and interpret the behavior of hostcountry individuals and firms, to acquire knowledge from them, and to gain a better understanding of the country’s environmental context (Håkanson & Ambos, 2010). Accordingly, we argue that as cultural distance increases, a manager’s ability to accurately evaluate differences between the home and host country decreases. We therefore hypothesize:

Hypothesis 3b. There is a positive relationship between the international scope of a manager’s task and a manager’s misperception of differences between home and host country. 3. Data and method 3.1. Sample and data collection To test our hypotheses, we used data that we collected on the renewable-energy industry in Germany in 2013 and 2014 as part of a larger research project on internationalization. This data set includes responses from a large survey questionnaire and publicly available archival country data. The renewable-energy industry is particularly suitable for our research, since international activity in the industry is high, and the range of target host countries for these activities is broad (Lehr, Lutz, & Edler, 2012; Tan & Mathews, 2015). In addition, the German renewable-energy industry consists of a very high proportion of SMEs, and frequently only one manager is responsible for making international decisions. This setting is therefore an appropriate one to examine managerial misperception of country differences as well as the firm-level performance effects and contextual antecedents. Because no comprehensive register contained all the firms relevant

Hypothesis 3a. There is a positive relationship between the extent of cultural distance and a manager’s misperception of differences between home and host country.

1 Some studies consider international scope to be a proxy for international experience, which might result in the assumption that the greater scope and experience, the lower a manager’s misperception. However, most of these studies consider scope as the number of countries a firm operates in rather than broader regions. Given that firms often choose to enter markets that are similar to ones they have previously entered (Johanson & Vahlne, 1977), there may be associated learning effects when entering new countries, where inferences drawn from experience in one country can be applied to a relatively similar neighboring one. Here, however, we consider scope as the number of international geographic regions in which a firm operates, such as Sub-Saharan Africa or Latin America. Countries within such regions are relatively similar, whereas regions are very heterogeneous. We therefore follow the reasoning of Barkema and Drogendijk (2007) and argue that learning effects do not necessarily apply across geographic regions.

The degree of information-processing complexity is not only impacted by the inherent complexity of a singular given task, but also by the extent of a manager’s overall tasks. The more diverse and complex these overall tasks and assignments, the less capacity a manager has for every individual task (Hambrick et al., 2005). A manager’s international scope thus significantly determines how much time and cognitive capacity he or she can devote to a specific country. International scope refers to the number of the geographic regions where a manager has to carry out international tasks, such as Germanic Europe or Southern Asia (Hashai, 2011; Li, Qian, & Qian, 2012a). A high international scope signifies a broad geographical dispersion of a manager’s 4

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3.2.1. Dependent and independent variables Managerial misperception of country differences is a composite construct that measures the deviation of a manager’s perceived institutional differences from the actual institutional differences. We separately measured actual and perceived institutional differences. We conducted a thorough literature review to identify items that adequately reflect institutional country environments (see Appendix C for a complete list of items and respective sources). The chosen items mainly reflect the selections made by Gaur and Lu (2007), Chao and Kumar (2010), and Dow and Larimo (2009). All items are included in report data from the World Economic Forum (i.e., Global Competitiveness Report), IMD (i.e., World Competitiveness Yearbook), and the Hofstede Value Survey. The items reflect different facets of countries' institutional environments that are considered as relevant for internationalizing firms, particularly with regard to their regulative, normative, and cultural elements. We also included items that we deemed as most relevant to the renewable-energy industry. In doing so, we respond to recent calls to avoid oversimplifying distance measurements and to account for industry particularities (Brouthers, 2013; Caprar, Devinney, Kirkman, & Caligiuri, 2015; Dow & Larimo, 2009). Using the Global Competitiveness Report and the World Competitiveness Yearbook, we selected six items aimed at measuring regulative elements of a country's institutional environment, and seven items reflecting normative elements of a country's institutional environment. For cultural elements we relied on Hofstede’s cultural dimensions (Drogendijk & Slangen, 2006; Gaur, Delios, & Singh, 2007; Hofstede, Hofstede, & Minkov, 2010) and included one item for each of the five cultural dimensions (power distance, masculinity, individualism, uncertainty avoidance, and long-term orientation). Our final list included a total of 18 items. All values obtained were converted to a five-point Likert scale to assure homogeneity across report values. We took the absolute difference between each host-country and respective home-country value (Dow & Karunaratna, 2006):

to our study, our first step was to identify the population. Our starting point was a large governmental database of all firms related—in the broadest sense—to the renewable-energy industry in Germany. This database, however, included many firms with only domestic operations as well as other actors connected to, but not active in, the broader field, such as banks that provide financing for renewable-energy projects. We therefore had to carefully review and eliminate firms from this database. To validate the database, we also consulted additional sources such as membership registries of all major industry associations and clusters as well as exhibitors’ lists of industry trade fairs and industry events. In total, 4,682 firms were manually screened and checked for sample membership. To ensure comparability among sample firms, firms included in the sample had to meet the following criteria: (1) be for-profit; (2) be German owned; (3) derive the majority of their revenues from the renewable-energy sector (e.g., solar, wind, bioenergy); and (4) undertake business activities in at least one foreign market. We identified 488 firms that met these sample criteria. To better understand the specific industry characteristics and managers’ assessments of country differences, in 2013 we conducted a qualitative pre-study by interviewing 23 managers and industry representatives. We then constructed a questionnaire in German, which mainly contained established scales from previous literature. Independent research assistants translated original items from English to German and back several times to ensure validity (Brislin, 1980). Once translated, we conducted a pre-test of the questionnaire with 18 respondents from industry and academia. We personally contacted all firms in our database to identify the most suitable respondent in the respective firm and to explain the objective of our study. Our respondents had to be key decision makers for their firms’ international activities. Depending on the firm’s structure, these key decision makers included chief executive officers, managing directors, and heads of business development or international sales departments. On average, respondents had 12.8 years of experience in international business and had worked 6.9 years for their respective firm. These numbers validate the suitability of the selected respondents, as they suggest a high level of expertise (Poppo, Zhou, & Ryu, 2008; Schilke & Cook, 2015). The questionnaire was distributed and answered via multiple formats: online, by e-mail using an editable PDF document, by mail, by fax, and over the phone. Our data-collection phase yielded 251 completed questionnaires, which represents a response rate of 51.4%. We had to exclude questionnaires from firms operating in certain countries because we used secondary data (see below) that was not available for a small number of countries. Furthermore, because the questionnaire was long, respondents were not required to fill out every section of it. Our final sample for the present study therefore included 186 managerial assessments of market entries in 43 different countries. Firms in this final sample are on average 17.7 years old, employ 134 people, and derive 45% of their revenue abroad in about 12 different countries.

DAgjn = |(DAgn – DAjn)| DAgjn indicates the actual (A) difference between Germany (g) and a given host country (j) of one specific item (n) out of the 18 items reflecting a country’s environment. DAgn represents the n-item score for Germany, whereas DAjn represents the n-item score for the host country. The process for operationalizing perceived country differences was similar, the main difference being the data sources (i.e., primary vs. secondary data). The regulative and normative items included in the country reports are identical to the items in our questionnaire. Managers were asked to indicate their perceptions of a country’s environment in terms of a specific item for both home and host country on a five-point Likert scale. The regulative and normative country differences were then calculated in the same manner as the actual country differences. In order to operationalize the five Hofstede dimensions for the cultural elements of institutional environments, we adopted the measurement provided by Furrer, Liu, and Sudharshan (2000). These authors used a four-item scale for each cultural dimension based on a description provided in Hofstede’s work (1991). Similar to Furrer et al. (2000), we calculated an index of the average scores of each cultural dimension. The score for each dimension was used to subtract the home- from the host-country value, using the absolute value to obtain the perceived cultural difference between countries for each cultural dimension. We calculated the perceived difference between countries as follows:

3.2. Measurement of variables We used the established pick-any approach (Holbrook, Moore, & Winer, 1982) and asked respondents to choose one of their firm’s market entries and the respective host-country activities for which they were personally responsible, and to answer all questions related to this host country. While this pick-any approach is common, managers might choose to answer questions about countries they are especially familiar with or where their international activities are particularly successful. However, judging from our pre-test and the personal contact we had with all managers participating in our study, we did not identify any pattern in managers’ choices of countries. Moreover, our data shows no respective patterns, which also indicates that our respondents did not selectively choose particular countries.

DPgjn = |(DPgn – DPjn)| DPgjn indicates the perceived (P) difference between Germany (g) and a given host country (j) of a specific item (n). DPgn represents the manager’s n-item score for Germany, whereas DPjn represents the manager’s n-item score for the host country. 5

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For the overall misperception construct, we subtracted the individual item values for the actual and perceived country differences. The absolute value of this subtraction represents managerial misperception for each specific item. The sum of all absolute values of misperception between actual and perceived differences resulted in a unique composite score, expressing the overall misperception of the manager. Our approach for capturing managerial misperception (albeit in another context) is similar to the one Hallen and Pahnke (2016) used in their study. Our misperception construct is algebraically expressed by the following formula:

managerial misperception [H2a-3b]). We tested Hypothesis 1 using several control variables because firm's host-country performance can be subject to a large variety of influences (Shrader, 2001). First, we controlled for firm size. Controlling for a firm’s size helped to account for performance effects based on different levels of potential scopes of action (Dikova, 2009; Gaur et al., 2007). Since this variable is an independent one in the second regression, we operationalized firm size as described above. We also used firm age as a control variable, since older firms may have more experience conducting domestic and international business (Acedo & Florin, 2006; Li et al., 2012a), and this experience might influence performance outcomes. We measured age in its logarithmic form using the difference between year of foundation and year of survey (2014). Furthermore, we controlled for the firm’s international intensity (Fernhaber, Gilbert, & McDougall, 2008) by using the ratio of the firm’s foreign sales to total sales (Delios & Beamish, 1999; Fernhaber et al., 2008). International intensity was included as a control variable because an internal emphasis on international business may influence the international performance of a firm (Lu & Beamish, 2006). Because prior literature has shown that the mode of market entry can influence a firm’s performance in a host country (Brouthers, 2002; He et al., 2013; Hutzschenreuter & Horstkotte, 2013), we dummy-coded the respective entry modes, with 0 to indicate non-equity entry modes and 1 to indicate equity entry modes, using the criteria outlined by Pan and Tse (2000). Finally, we controlled for market opportunities arising from a country’s economic conditions, which evidently may impact a firm’s performance in this country (Shrader, 2001). We adapted the five-item scale used by Agarwal and Ramaswami (1992) to measure market potential. We used a second set of control variables to account for any potential influences on a manager’s misperception of country differences (Hypotheses 2a through 3b). First, we controlled for the firm’s international intensity (Fernhaber et al., 2008) as well as the firm’s timespan of international operations (Brouthers & Brouthers, 2001; Chao & Kumar, 2010), since both variables may be associated with organizational learning and could thereby also impact a manager’s misperception (Evans et al., 2008). The operationalization of international intensity has been described above. We measured the firm’s timespan of international operations by the number of years. Furthermore, we controlled for sub-industries (Coeurderoy & Murray, 2008; Filatotchev, Liu, Buck, & Wright, 2009) and created dummy variables (solar, wind, bioenergy, and others) to account for sub-industry specific differences across managers. Managers could also differ in their background depending on the type of firm, which is why we controlled for this effect by differentiating between service (coded as 1) and manufacturing (coded as 0) firms (Brouthers, 2002). Lastly, we controlled for a manager’s international experience to account for learning effects, which might improve his or her processing ability and enable feedback loops to create new knowledge (Hutzschenreuter & Horstkotte, 2013; Maitland & Sammartino, 2015). We measured international experience of the manager as the number of years a manager has been working internationally, which in many prior studies (e.g., Fernhaber et al., 2008; Li et al., 2012b) is considered a suitable reflection of a manager’s international experience, and included it in the form of its natural logarithm.

18

Misperception of country differences =

( DAgjn

DPgjn )

n=1

The scale to measure firm’s host-country performance was adapted from He, Brouthers, and Filatotchev (2013). The scale (see Appendix B) consists of four items measuring the firm’s overall market performance in the specific host country in terms of profitability, sales growth, satisfaction with performance, and achievement of the firm’s strategic objectives (Cronbach’s α = 0.89). Because the entry modes of respondent firms differ across our sample, our overall market-performance item was measured independent of mode. Firm size is an important driver of its internal resource endowment (Audia & Greve, 2006) and indicates managers’ available opportunities to access and process information (Clement, 1999). In line with prior research, we measured firm size as the natural logarithm of the number of worldwide employees (e.g., Brouthers & Brouthers, 2001; Chao & Kumar, 2010; Gaur & Lu, 2007). We measured access to local-partner knowledge by adapting items of Yli-Renko et al. (2001) to the context of international renewable-energy firms, asking about three kinds of knowledge acquisition from the local key partner (i.e., the most important local partner firm): knowledge of the country in general, knowledge of the market in this country, and knowledge of technical requirements in this country (see Appendix B for a complete list of the nine items). We then aggregated knowledge acquisition as the mean value of these items (Cronbach’s α = 0.89). International scope is the geographic dispersion of international activity the manager is responsible for. Similar to previous research (e.g., Khavul et al., 2010; Li et al., 2012b), we used geographic regions for our measurement based on cultural clusters identified by Gupta, Hanges, and Dorfman (2002). Regions included were: (1) Anglo cultures, (2) Latin Europe, (3) Nordic Europe, (4) Germanic Europe, (5) Eastern Europe, (6) Latin America, (7) Sub-Saharan Africa, (8) Arab cultures, (9) Southern Asia, and (10) Confucian Asia. Respondents were provided with a list of these regions and were asked to indicate the regions they operate in. Regions where a firm was present were coded 1 and regions without presence, 0. The values were subsequently summed up. In order to measure cultural distance, we used Kogut and Singh’s (1988) composite index and included dimensions of culture from Hofstede’s World Value Survey data: power distance, masculinity, individualism, uncertainty avoidance, and long-term orientation (Hofstede et al., 2010). Since its introduction, this index has gained wide acceptance in international management literature (Cuypers, Ertug, Heugens, Kogut, & Zou, 2018) and has been applied to a large number of cross-country studies (e.g., Brouthers & Brouthers, 2001; Hutzschenreuter & Voll, 2007; Tihanyi et al., 2005). We chose a composite index of cultural distance because it corresponds to our general theoretical argument that increased cultural differences between home and host country foster managers’ misunderstandings and thus impact their misperception (Beugelsdijk et al., 2018).

4. Analyses and results Table 1 provides information on the means, standard deviations, and correlations of all variables included in our models. We checked for multi-collinearity by calculating variance inflation factors (VIF). Since the highest VIF is 2.00, which is well below the traditional threshold of 10, we do not expect multi-collinearity to be a problem (Neter, Kutner, Nachtsheim, & Wasserman, 1996). Because we measured independent and dependent variables using different data sources, including quasi-objective measures (international scope, firm size) subjected to external cross-validation, we do not consider common-method variance to present a problem in our analysis

3.2.2. Control variables Because our hypotheses require two different models, we used two sets of control variables depending on the respective dependent variable (first, firm's host-country performance [H1]; and second, 6

Journal of World Business 55 (2020) 101018

−0.14 −0.12 −0.15* 0.32** 0.15* 0.07 0.04 −0.08 0.02 0.07 0.03 −0.14 0.07 0.11 −0.07 0.09 5.14 0.96 1.55 0.76 0.83 2.52 30.50 11.58 0.94 0.50 0.69 0.50 0.46 0.40 0.20 0.47 0.75 13.77 3.18 3.50 3.50 1.53 4.12 44.79 9.64 2.40 0.48 3.66 0.45 0.30 0.20 0.04 0.68 2.31

0.07 0.15* −0.09 0.00 0.28** −0.07 −0.09 −0.18* 0.12 −0.05 0.02 0.09 −0.10 0.05 0.04

0.08 −0.10 0.45** 0.08 0.30** 0.41** 0.19** 0.12 −0.03 −0.04 0.07 0.01 −0.16* 0.03

−0.06 0.05 −0.01 0.08 0.03 0.03 0.14 −0.01 −0.09 0.06 0.11 −0.12 0.13

0.09 0.21** 0.03 −0.02 0.02 0.25** 0.08 −0.03 −0.05 −0.02 0.03 0.03

0.23** 0.35** 0.41** −0.06 0.12 0.12 −0.17* 0.07 −0.05 −0.36** 0.11

0.15* 0.03 −0.04 0.09 0.10 −0.18* 0.06 0.03 −0.04 0.20**

0.61** −0.03 0.11 −0.16* −0.06 0.32** −0.12 −0.16* 0.13

0.02 0.02 −0.11 −0.01 0.29** −0.27** −0.12 −0.03

−0.04 0.12 0.09 −0.22** −0.05 0.12 0.05

0.01 −0.02 0.01 0.01 0.08 0.05

−0.60** −0.46** −0.19** −0.07 0.02

−0.33** −0.14 0.23** 0.05

−0.11 −0.11 −0.14*

−0.14 0.13

−0.16*

(Chang, van Witteloostuijn, & Eden, 2010; Podsakoff, MacKenzie, Jeong-Yeon, & Podsakoff, 2003). This assertion is particularly true because the misperception construct is a complex indicator variable consisting of a mixture of both questionnaire and archival data. Thus, we would find it implausible for a respondent to identify the underlying idea of our models and the relationships among them. Even so, as an added precaution, we implemented procedural and statistical remedies to prevent common-method bias. First, we clearly communicated to respondents that their anonymity would be protected. Furthermore, we spatially separated items of dependent and independent variables in our questionnaire (Podsakoff et al., 2003). Second, we conducted Harman’s one-factor test (Podsakoff & Organ, 1986) to empirically check for common-method bias. We found that no single factor explained more than 22% of the total variance in the variables. To account for a possible non-response bias, we employed t-tests to check for differences between early and late respondents (Armstrong & Overton, 1977). We found no significant differences and we can therefore rule out non-response bias by assuming that late respondents are more similar to non-respondents than they are to early respondents (see also Slater and Atuahene-Gima (2004)). Furthermore, since we were personally in contact with each manager, we asked non-responding managers why they did not participate and found no systematic pattern. We employed ordinary least squares (OLS) regressions to test our hypotheses. Because the respondents may have entered identical host countries, our data includes multiple observations for some countries. Thus, our observations could potentially suffer from non-independence, violating traditional regression assumptions (Abdi & Aulakh, 2012). To account for this issue, we employed cluster-robust standard errors identified by the host country in our regression analyses. Table 2 reports the coefficient (Coef.), standard error (S.E.), and pvalue (p) results for the OLS analysis testing Hypothesis 1. Table 3 reports results for Hypotheses 2a to 3b. In both Tables 2 and 3, Model 1 displays the base model, which includes only the control variables, while in Model 2 independent variables were added to the control variables. Hypothesis 1 posits a negative impact of a manager’s misperception of country differences on a firm’s host-country performance. Results in Table 2 support the hypothesized relationship, showing a significant negative relationship between misperception (b = -0.15, p = 0.05) and a firm’s host-country performance. Hypothesis 2a argues that there is a negative relationship between a firm’s size and a manager’s misperception of differences between home and host country, which is also supported (b = -0.63, p = 0.01). Similarly, Hypothesis 2b is supported, showing a significant negative relationship between access to localpartner knowledge (b = -1.01, p = 0.03) and a manager’s misperception. Results further support Hypothesis 3a, which posits a positive relationship between cultural distance and a manager’s misperception of country differences (b = 1.80, p = 0.02). Lastly, Table 2 OLS regression results: Firm’s host-country performance. Model 1

1. Managerial misperception 2. Firm’s host-country performance 3. Firm size (ln) 4. Access to local-partner knowledge 5. Cultural distance 6. International scope 7. International intensity 8. Timespan of int. operations 9. Firm age (ln) 10. Entry mode (equity) 11. Market potential 12. Sub-industry - Solar 13. Sub-industry - Wind 14. Sub-industry - Bioenergy 15. Sub-industry - Others 16. Type of firm (service) 17. Manager's int. exp. (ln) * p < .05 ** p < .01 n = 186

1 S.D. Mn. Variables

Table 1 Means, standard deviations, and correlations.

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

C.E. Weber, et al.

Coef. Firm size (ln) Firm age (ln) International intensity Entry mode (equity) Market potential Managerial misperception Constant R2 Adjusted R2 F value

Model 2

S.E.

p

Coef.

S.E.

p

0.09 −0.16 0.01*** −0.37** 0.10

0.04 0.09 0.00 0.12 0.11

0.05 0.08 0.00 0.01 0.33

2.69*** 0.14 0.11 7.57***

0.47

0.00

0.07 −0.16 0.01*** −0.36** 0.12 −0.15* 2.66*** 0.16 0.13 7.37***

0.04 0.09 0.00 0.11 0.10 0.08 0.49

0.08 0.08 0.00 0.01 0.25 0.05 0.00

*

n = 186, * p ≤ 0.05 (2-tailed), ** p ≤ 0.01 (2-tailed), *** p ≤ 0.001 (2-tailed). 7

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independent variable but do not lead to changes in the dependent variable, aside from the indirect route via the independent variable (Larcker & Rusticus, 2010). Accordingly, an instrument variable is correlated with the independent variable, but not with the error term of the regression equation. In our first endogeneity test we used the strength of the relationship with the key partner as an instrument variable—a variable associated with the access to partner knowledge (e.g., Hansen, 1999) but not directly with a manager’s misperception. The variable was measured with two items adapted from Reagans and McEvily (2003) stating: “We have a very close relationship with this partner firm.” and “We communicate very often with this partner firm.” When using the estat endog command in Stata, both the Durbin and the Wu-Hausman statistics were not significant (Durbin: p = 0.71; Wu-Hausman: p = 0.72). Accordingly, the null hypothesis stating that an OLS estimator of the same equation would yield consistent estimates cannot be rejected and alleviates a concern of endogeneity (Baum, Schaffer, & Stillman, 2007). We further checked for endogeneity while clustering the error terms of observations that are related to a common country. Again, the robust score test did not show any significant effect (p = 0.73). Accordingly, the use of OLS is preferable to the use of a two-stage least-squares estimator, since the OLS estimator is more efficient when endogeneity is not present (Nakamura & Nakamura, 1981). We further checked the validity of our instrument using the estat firststage command in Stata. The significant Fstatistics—with 24.64—exceeds the recommended value of 8.96 (Stock, Wright, & Yogo, 2002), thereby indicating a reliable instrument. Since the largest rejection rate of a nominal 5% Wald test (16.38) was also lower, we can conclude that our instrument is not weak. For the misperception variable we used international scope as an instrument variable, which is positively associated with misperception (as we argued and found in the first model), but not directly associated with the performance in a specific market, which is only indirectly influenced by a firm’s international scope via a manager’s misperception and associated decision-making quality. Again, both the Durbin and the Wu-Hausman statistics were not significant, thereby alleviating concerns of endogeneity (Durbin: p = 0.32; Wu-Hausman: p = 0.33). Similarly, when checking for endogeneity while clustering the error terms of observations that are related to a common country, the robustscore tests did not show any significant effects (p = 0.38). The validity of the instrument was reflected in a significant F-statistic of 12.11 when using the estat firststage command, which exceeds the recommended value of 8.96 as well as the Wald-test rate at the 15% level. In addition to these statistical remedies, we also addressed the relationship between access to local-partner knowledge and misperception in our interviews (Reeb et al., 2012), which did not reveal any cause for concern. Having performed these quantitative and qualitative remedies, we do not expect endogeneity to be a concern in our models.

Table 3 OLS regression results: Managerial misperception of country differences. Model 1

International intensity Timespan of international operations Sub-industry - Wind Sub-industry - Bio Sub-industry - Others Type of firm (service) Manager's international experience (ln) Firm size (ln) Access to local-partner knowledge Cultural distance International scope Constant R2 Adjusted R2 F value

Model 2

Coef.

S.E.

p

0.00 0.01

0.01 0.03

−1.21 0.56 2.17 −0.10 0.57

0.63 1.15 2.39 0.71 0.60

***

12.40 0.03 0.00 1.10

1.33

Coef.

S.E.

p

0.74 0.83

−0.01 0.00

0.01 0.02

0.28 0.87

0.06 0.63 0.37 0.89 0.34

−0.95 1.18 3.30 0.13 0.67

0.68 1.07 2.56 0.58 0.58

0.17 0.28 0.20 0.82 0.26

−0.63** −1.01*

0.21 0.45

0.01 0.03

1.80* 0.74 0.44* 0.20 *** 13.74 2.41 0.20 0.15 2.42*

0.02 0.04 0.00

0.00

n = 186, * p ≤ 0.05 (2-tailed), ** p ≤ 0.01 (2-tailed), *** p ≤ 0.001 (2-tailed).

Hypothesis 3b, proposing a positive relationship between the international scope and misperception (b = 0.44, p = 0.04) is also supported. 4.1. Additional analyses 4.1.1. Robustness test When choosing our method, we also considered using structural equation modeling (SEM) instead of OLS. However, since latent variables are not core to our theorizing and testing (except for access to local-partner knowledge and firm’s host-country performance, which were measured via multi-item scales), and considering that a relatively small number of observations (n = 186) may strongly impact a structural model (Hair, Black, Babin, & Anderson, 2010; Kline, 2015), using SEM seems unwarranted in our case. We did, though, replicate our analyses using SEM as a robustness test and found essentially the same results as we did in the OLS regression with regard to coefficient estimates and significance levels, with even slightly improved significance levels for the effect of access to local-partner knowledge (p = 0.01), the effect of cultural distance (p = 0.00), and the effect of the international scope (p = 0.01) on misperception, respectively. Fit values were satisfactory for the misperception model (CMIN = 1.50; CFI = 0.98; RMSEA = 0.05) as well as for the performance model (CMIN = 1.24; CFI = 0.99; RMSEA = 0.04). The results were present when separately calculating the two models: that is, first the effects of antecedents on misperception, and second, the effect of misperception on host-country performance; and also when estimating all relationships in one model. We therefore consider our SEM results a valid robustness test to our OLS results (Byrne, 2010).

5. Discussion and conclusion The objective of this paper was to shed light on managers’ misperception of institutional differences between home and host countries, which is the deviation of managers’ perceived institutional differences from the actual institutional differences. Taking the boundedrationality perspective as a starting point, we build on the assumption that managerial assessments of differences between home and host countries never perfectly reflect actual environmental conditions because an individual’s time and cognitive capacity are limited (Baer et al., 2013; Cyert & March, 1963). We theorize that managerial misperception of institutional differences negatively relates to a firm’s performance in a respective host country and find empirical support, providing evidence for the relevance of the construct. Furthermore, we argue that the level of misperception depends on a manager’s opportunities for easily accessing and processing information (Hallen & Pahnke, 2016; Schwens & Kabst, 2011). Our empirical results support the proposition that information-access opportunity (as reflected in firm

4.1.2. Endogeneity To address a potential concern of endogeneity, we conducted additional tests. A concern of endogeneity might result from two relationships in our models: First, it could be present in the relationship between the access to local-partner knowledge and managerial misperception, where the acquisition of knowledge could be a result of a low degree of misperception. Second, a manager’s decision to enter a particular country could be an underlying unobserved factor that affects both a manager’s misperception of country differences as well as the performance in this host country. We therefore conducted endogeneity tests with instrument variables (Reeb, Sakakibara, & Mahmood, 2012; Schilke & Cook, 2015). The property of an instrument variable is such that any changes in this variable are associated with changes in the 8

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size and access to local-partner knowledge) is associated with lower misperception of institutional differences, whereas information-processing complexity (as reflected in the actual cultural distance between home and host country and the international scope of a manager’s overall tasks) is associated with higher misperception.

return to the traditional assumption of international-management research: that all international-business activity depends on the rationally bounded, individual decision maker. On a broader level, our study responds to an increasing research interest in a micro-foundations perspective on the decision-making manager in international-management research (e.g., Aharoni, Tihanyi, & Connelly, 2011; Ambos, Cesinger, Eggers, & Kraus, 2019; Maitland & Sammartino, 2015). While the concept of the manager as a rationally bounded decision maker has been an underlying assumption in international-management research from the start, the field has long suffered from an ignorance of managerial cognition and decision making, and at times has even fully ignored the manager’s role in internationalization processes (Aharoni et al., 2011; Harzing, 2003). Explicating the notion of managerial misperception of country differences and examining its consequences and antecedents is a further step forward within this evolving field.

5.1. Contributions The major contribution of our study is to put forward and shed light on a theoretically important construct that—despite its intuitive relevance—has been so far widely neglected by international-management research: managerial misperception of country differences, a construct “badly needed” to move international-management research forward, according to Håkanson and Ambos (2010: 208). While the literature on perceived distance has inherently recognized differences between actual and perceived distance, and that managerial perceptions impact decision making (Evans et al., 2008; O’Grady & Lane, 1996), to the best of our knowledge there is little conceptual—let alone empirical—consideration of the gap between the two. Our study transforms the notion of deviations between actual and perceived country differences into a theoretically manifest and empirically measurable construct. Our study is particularly important for two sub-streams of international-management research: (1) research on the effects country differences have on performance outcomes and on decision making, and (2) research on the antecedents of managerial (mis-)perception of country differences. First, we add to research on the effects of country differences in general and of perceived country differences in particular. By providing theoretical arguments and empirical evidence on the effect of managerial misperception of country differences on a firm’s performance in a respective host country, we can conclude not only that perceptions of country differences in themselves matter, but also that the quality of a manager’s perceptions of country differences matters in terms of outcomes. Our findings thus substantiate that managerial misperception is a crucial explanatory construct that must be considered when trying to understand how country differences impact performance outcomes of internationalizing firms. This notion enlarges and complements the explanatory scope of country differences beyond the traditional focus on actual and perceived differences in contemporary internationalmanagement research. Our study also adds to research studying how and why managers make specific decisions. Although perceived differences have been clearly shown to be important for decision making (Sousa & Bradley, 2006), we can only fully understand managerial decision-making when considering managerial perceptions against the backdrop of actual conditions. Using managerial misperception as an explanatory factor in future international-management studies will thus also allow for investigation of the frequently observed—but rarely examined—divergence between strategies that are considered optimal in theory and those that are actually chosen in practice (Benito, Petersen, & Welch, 2009; Brouthers & Hennart, 2007). Secondly, using a contextual bounded-rationality approach to study the antecedents of managerial misperception of country differences responds to calls to study “when, how, and why” individual-level perceptions of country differences “might deviate from the traditionally employed national-level indices” (Baack et al., 2015: 952). Specifically, by adopting an information-based perspective, we are able to study the role of the contextual antecedents that determine information-access opportunity and information-processing complexity and thereby impact the degree of managerial misperception. This perspective allows us integrating the findings of prior research—studying how contextual factors impact international activity on an organizational level (e.g., Li et al., 2012a; LiPuma et al., 2013)—into our micro-perspective on the decision maker, and thus responds to recent calls to do so (Hutzschenreuter, Pedersen, & Volberda, 2007). While earlier studies have typically glossed over the role these contextual factors play in an individual decision-maker’s cognitive processing, we put the individual manager front and center and thereby

5.2. Limitations and future research Despite these contributions, there are some limitations to our study that may pave the way for potential approaches in future research. First, while we assume that managerial perceptions are biased, we do not explicitly consider the impact of specific cognitive biases on managerial misperception, a consideration beyond the scope of this study. However, since biases inherent to an individual manager’s cognition will directly and variously impact managerial misperception, they provide many opportunities for future research to examine them and their distinct impact on managerial misperception of country differences. While initial studies consider specific biases in the context of perceptions of country differences (Baack et al., 2015; Dow, 2009), these perceptions have not yet been considered in relation to actual differences. Second, our examination of contextual antecedents offers various opportunities to extend research on these antecedents. In particular, it would be interesting to examine how individual manager characteristics impact the degree of misperception. Our control variable for a manager’s international experience shows no significant effect on a manager's misperception, but other types of experience may impact individuals’ assessments, such as prior work experience, openness, or intellectual ability. Clark et al. (2018) have recently examined the role of country familiarity, which provides additional paths for exploring misperception against the backdrop of cognitive processes. Furthermore, it would also be interesting to look at learning processes (both on the individual and the firm level) when more closely examining managerial misperception of institutional differences. Third, we focus on misperception of institutional differences between countries, which we measure with a comprehensive and literaturebased collection of items covering different facets of institutional environments. However, while prior research has emphasized that institutional environments and institutional differences between countries are pivotal (Gaur & Lu, 2007; Kostova & Zaheer, 1999), this focus limits the generalizability of our findings to some extent. Misperception will only have an effect on performance outcomes when the underlying information is relevant for decision making. While we are able to show that information on institutional specificities of countries matter, we cannot draw conclusions with regard to other facets of country environments. Thus, it would be important for future research to disentangle which facets of country environments are relevant for outcome variables, and thus which inaccurate assessments are problematic.2 Fourth, there are some limitations in our data, which is cross-sectional. Longitudinal data would have allowed us to more precisely identify causal relationships. Future empirical research would therefore benefit from longitudinal designs. Additionally, we only look at managers from one home country (Germany) within one industry 2

9

We particularly thank one of our reviewers for pointing out to us this notion.

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shows that managers’ evaluations of institutional differences between countries are more accurate in larger organizations, when access to localpartner knowledge is available, when levels of actual cultural distance are low, and when the scope of international activity is small. These are factors over which a manager has not necessarily full control. However, our findings imply that managers may actively influence the perils of their bounded rationality. For example, managers in small organizations may counterbalance this setting by putting particular effort into building a trusting host-country partnership that provides rich access to localpartner knowledge. Furthermore, managers can also seek help from export programs provided by their home countries and from investment programs in their host countries, thereby enabling a better information access. Such programs are particularly designed to decrease information asymmetry and increase managers’ understanding of host-country environments as well as the differences between respective countries.

(renewable energy), which is largely populated by SMEs. While these restrictions of the sample may limit the generalizability of findings, they also increase internal validity, given that internationalization processes can vary across industries and may be influenced by macroenvironmental factors in the home country (Coviello & Jones, 2004). Still, future research should consider other home countries as well as other industries to verify the generalizability of the results. Some of our variables would also benefit from improved measurements. In particular, we measured the international scope of a manager’s tasks as the number of international regions the firm operates in. Based on our qualitative pre-study and our pre-test, we know that this is an appropriate measurement to capture the scope of our respondents’ task complexity for our specific sample of relatively small firms, where there is typically one manager responsible for international decision making. However, this measurement would not be appropriate for other settings, such as samples of large MNEs, where specialized country managers make decisions for only one region or even one country. Accordingly, for specialized managers, another measurement would be needed, which could, for example, be achieved easily by directly asking respondents to define the scope of their individual international task. Lastly, our measurements of actual differences between countries (derived from the Global Competitiveness Report of the World Economic Forum, the World Competitiveness Yearbook of the IMD, and the Hofstede Value Survey), which we used to calculate managerial misperception, are—strictly speaking—also based on perceptions, since they originate from surveys of large samples of respondents. However, the validity of this data has been extensively tested (Chakrabarti, Gupta-Mukherjee, & Jayaraman, 2009; Drogendijk & Slangen, 2006). Furthermore, average perceptions across large samples tend to converge with real values and the country-level data used provides the closest feasible and current approximation of “actual” values of countries’ environments (Liska, 1990; Schwartz, 1999). We are therefore confident that these sources are valid ones for capturing actual differences between countries. Aside from the implications that arise from the above-mentioned limitations, we would like to highlight one additional avenue for future research. Building on extant studies (e.g., Evans & Mavondo, 2002) that investigate the impact of high- and low-distance perceptions (independent of actual conditions), it would be interesting to explore differences among over- and underestimation of distance as well as the respective performance effects and antecedents. Prior research has shown that higher distance perceptions may lead to improved performance (“distance paradox”). Given the results of our study, we suggest that the positive effect of high distance perceptions found in prior research may be contingent on the relationship between actual and perceived differences. For example, if distance is actually very low but is perceived as high, and if a great deal of resources are invested to account for this situation (such as initiating costly safeguards in partnerships), then these investments are unlikely to foster performance. Instead, they might hurt performance, as they are overly costly, complex, and not adapted to given requirements. On the other hand, when actual high distance is also perceived as high—implying a low misperception—performance will most likely benefit. Accordingly, an investigation of distinct antecedents and performance effects of over- and underestimation of distance would be a fruitful research area for future research in international-management studies.

5.4. Concluding remarks We believe that evaluating managerial misperception of institutional differences between countries increases our understanding of country differences in management research. Especially when analyzing the impact of country differences as they relate to internationalization behavior and outcomes, taking managerial misperception into account will be necessary to produce meaningful results. We therefore hope to encourage more research on this topic, particularly on theoretical extensions, conceptual refinements, and empirical exploration. The relationship between a manager’s misperception of differences between home and host country and a firm’s performance in this host country is relatively straightforward, and we are therefore confident that this relationship can be easily replicated and extended. The same is true for the relationship between managerial misperception and its antecedents. We believe that our study may prove a valuable starting point for investigating various research questions in internationalmanagement research focused on managerial decision making and decision outcomes and hope to see more studies in this field in the future. Funding The research project was supported by grants from the Dr.-WernerJackstädt Foundation. The funding source had no involvement in the conduction of research or preparation of the article. Declaration of Competing Interest None. Acknowledgements We very gratefully acknowledge the support and helpful feedback by our Editor Paula Caligiuri and our anonymous reviewers. Furthermore, we very gratefully acknowledge feedback on our manuscript (or previous versions of it) by Louis Dau, Lars Håkanson, Hendrik Wilhelm, Constanze Weber, as well as participants of the research seminar at the University of Goettingen, the Strategic Management Society Annual Conference 2016 in Berlin, the Paper Development Workshop of the International Management Division at the Academy of Management Annual Meeting 2016 in Anaheim, the European International Business Academy Conference 2016 in Vienna, and the Academy of Management Annual Meeting 2017 in Atlanta.

5.3. Managerial relevance Our paper is of interest to practitioners, especially managers of SMEs. First, it raises awareness of the problem of managerial misperception by showing how misperception may affect performance outcomes. Second, it Appendix A. Countries in the sample

Australia, Austria, Belgium, Brazil, Bulgaria, Canada, Chile, China, Colombia, Croatia, Czech Republic, Denmark, Finland, France, Greece, Hungary, India, Indonesia, Ireland, Italy, Japan, Jordan, Latvia, Malaysia, Mexico, Netherlands, Peru, Philippines, Poland, Portugal, Romania, Russian Federation, Slovenia, South Africa, Spain, Sweden, Switzerland, Thailand, Turkey, Ukraine, United Arab Emirates, United Kingdom, United States. 10

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Appendix B. Multi-item scales and reliability Firm’s host-country performance (α = .89) During the last three years the selected host market… 1. …has been very profitable. 2. …has achieved a rapid sales growth. 3. …has very satisfactory performance. 4. …has achieved our company’s initial strategic objectives. Access to local-partner knowledge (α = .89) Acquisition of market knowledge 1. We were able to obtain a tremendous amount of knowledge on the renewable-energy market in the host country from this partner firm. 2. We were able to obtain a tremendous amount of knowledge on the market requirements and development in this country from this partner firm. 3. We get most of our valuable knowledge on the specific requirements of the foreign renewable-energy market from this partner. Acquisition of technical knowledge 1. We were able to obtain a tremendous amount of technical feedback from this partner. 2. We were able to obtain a tremendous amount of knowledge on technical requirements in this foreign market from this partner firm. 3. We get most of our valuable information on the specific technical requirements of this foreign market from this partner. Acquisition of country knowledge 1. We were able to obtain a tremendous amount of knowledge on this country from this partner firm. 2. We were able to obtain a tremendous amount of knowledge on doing business in this country from this partner firm. 3. We get most of our valuable information on the peculiarities of this country from this partner firm. Market potential (α = .75) In the selected host market, what do you think is… 1. …the market potential for renewable energy? 2. …the growth potential of renewable energy? 3. …the general acceptability of renewable energy? 4. …the attitude of the government toward the renewable-energy industry? 5. …the attitude of the government toward foreign firms in general?

Appendix C. Items included in the misperception construct Original items Values of the following items were obtained for both Germany and the selected host country. Items were used to capture actual environmental conditions as well as respondents' perceptions (on five-point Likertscale).

Source of items Number in parentheses indicates the item number in the respective report.

Items related to regulative country environment To what extent does anti-monopoly policy promote competition? Intellectual property rights are adequately enforced. How efficient is the legal framework for private businesses in settling disputes? How would you characterize corporate activity? The legal and regulatory framework encourages the competitiveness of enterprises. Technological regulation supports business development and innovation.

Scott (2008); Gaur and Lu (2007) Global Competitiveness Report 2014-2015 (6.03) IMD World Competitiveness Yearbook 2014 (4.3.22) Global Competitiveness Report 2014-2015 (1.10) Global Competitiveness Report 2014-2015 (6.02) IMD World Competitiveness Yearbook 2014 (2.3.08) IMD World Competitiveness Yearbook 2014 (4.2.20)

Items related to normative country environment Adaptability of government policy to changes in the economy is high. Transparency of government policy is satisfactory. Bureaucracy hinders business activity. Bribing and corruption do exist. Ethical practices are implemented in companies. Health, safety & environmental concerns are adequately addressed by management. Qualified engineers are available in the labor market.

Gaur and Lu (2007); Chao and Kumar IMD World Competitiveness Yearbook IMD World Competitiveness Yearbook IMD World Competitiveness Yearbook IMD World Competitiveness Yearbook IMD World Competitiveness Yearbook IMD World Competitiveness Yearbook IMD World Competitiveness Yearbook

Items related to cultural country environment

Berry et al. (2010); Dow and Larimo (2009); Furrer et al. (2000) Hofstede World Value Survey

Power distance Inequalities among people are both expected and desired. Less powerful people should be dependent on the more powerful. Inequalities among people should be minimized. There should be, and there are to some extent, interdependencies between less and more powerful people. Masculinity Money and material things are important. Men are supposed to be assertive, ambitious, and tough. Dominant values in society are the caring for others and preservation. Both men and women are allowed to be tender and to be concerned with relationships.

Hofstede World Value Survey

Individualism Everyone grows up to look after him/herself and his/her immediate family only. People are identified independently of the groups they belong to. An extended family member should be protected by other members in exchange for loyalty. People are identified by their position in the social networks to which they belong.

Hofstede World Value Survey

Uncertainty avoidance High stress and subjective feeling of anxiety are frequent among people. Fear of ambiguous situations and of unfamiliar risks is normal. Uncertainty is a normal feature of life and each day is accepted as it comes. Emotions should not be shown.

Hofstede World Value Survey

Long-term orientation Willingness to subordinate oneself for a purpose is normal.

Hofstede World Value Survey

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(2010) 2014 (2.3.09) 2014 (2.3.11) 2014 (2.3.13) 2014 (2.3.14) 2014 (3.4.02) 2014 (3.4.09) 2014 (4.2.15)

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C.E. Weber, et al. People should be perseverant toward long-term results. Traditions should be respected. Social obligations should be respected regardless of cost.

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