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date: 28 July 2021

The Uppsala Model in the Twenty-First Centuryfree

The Uppsala Model in the Twenty-First Centuryfree

  • Jan-Erik VahlneJan-Erik VahlneCentre for International Business Studies, School of Business, Economics and Law, University of Gothenburg

Summary

When it was developed in 1977, the Uppsala internationalization process model (Uppsala model for short) had three basic premises: process ontology, behavioral assumptions, and the presence of uncertainty. Multinational business enterprises (MBEs), among all actors, were in their infancy, and their future could not be known. Later on, the model was extended to cover the evolution of the MBEs, with factors such as internationalization, globalization, and the development of characteristics prompting changes and making them possible. Likewise, the knowledge concept was substituted for by capabilities, operational and dynamic, fitting well the other concepts of the model. The neoclassical view of the firm as an independent unit on the market is considered unrealistic. Instead, firms, MBEs, and small and medium enterprises are seen as embedded in networks with other cooperating and competing actors. The mechanisms of the 2017 version, though, are the same as in the original version. Hopefully, the latest version can be used as a tool within the scope of the “theory of the firm” research and as a platform for more studies on causal mechanisms, later to be applied in normative conclusions. It follows that static cross-sectional statistical methods are not fully satisfactory. Application of dynamic analytical methods requires investment in longitudinal data collection, which is costly, and has to be performed by institutions rather than individuals. A dream is that the Uppsala model can be used as a stepping stone in the construction of realistic macro-level studies of the economy.

Subjects

  • Business Policy and Strategy
  • International Business
  • Marketing

Introduction

The title of this article was suggested by the editors of this research encyclopedia and thankfully accepted, as it is enormously flattering in the sense that it presupposes that the Uppsala internationalization process model will “survive” and be of interest for some time into the future. This article, therefore, not only summarizes the changes that the model has undergone so far but also expresses some wishes concerning future research.

As the model was developed in the 1970s, this article pays some attention first to its inception, and then to its 2020 version, while identifying the revisions accumulated throughout the years. The article concludes by offering possibilities of future directions.

Birth of the Uppsala Model

The postwar decades, above all the 1950s and 1960s, experienced rapid economic growth due to technological development and international exchange, trade, and foreign investment. Internationalization received a lot of interest from academics, both at departments of economics and business. Economists in search of explanations to macro-level stocks and flows of foreign direct investment built models based on neoclassical microeconomics assumptions. Accordingly, these models were static in character. The argument was, and still is, that due to market failure transactions were internalized (Buckley & Casson, 1976; Dunning, 1977). In business administration, it was closer to our understanding of the world of commerce to take the totality of the business of the multinational business enterprise (MBE), at home and on foreign markets, into consideration.1

Research at the department of business studies, University of Uppsala, Sweden, very much initially had a descriptive intention, such as “what, when and where”, guided by what was observed rather than starting out with theoretically based hypotheses. Case studies and a large written survey of all Swedish MBEs were performed (Hörnell & Vahlne, 1970, 1972; Johanson, 1966; Johanson & Wiedersheim-Paul, 1975). Findings during the 1960s revealed that decisions on modes of operation in foreign markets were not independent of each other but rather followed upon each other in a sequence very similar across MBEs, industries, and foreign markets. This phenomenon was called the “establishment chain” (Johanson & Vahlne, 1977). Furthermore, it was found that the internationalization process began in markets close to the home market in psychic distance terms. Psychic distance was defined as factors impeding on ability to collect and understand information on foreign markets (Vahlne & Wiedersheim-Paul, 1972). We found that the internationalization process started in markets psychically close to home, and in each market, commitments were gradually increased. Accordingly, we defined our task as not to explain internationalization, but to describe and explain the process of internationalization. Nevertheless, in retrospect and answering the question “why,” the commitments of the MBEs make it possible to explain internationalization.

Applying a process perspective was not alien to researchers from business schools (Aharoni, 1966) or to those looking for explanations to foreign direct investment other than capital theory (Gruber et al., 1967). Several academics at U.S. business schools had made observations of internationalization processes, but they did not try to explain the dynamics of the process (Behrman, 1969; Knickerbocker, 1973; Vaupel, 1971).

Relying upon general theories of the firm (Cyert & March, 1963; Penrose, 1959) the interpretation of the findings were that MBEs are striving to exploit opportunities perceived to exist in foreign markets by increasing the commitments and in so doing keep the uncertainty below an acceptable level (Johanson & Vahlne, 1977). It was not a matter of optimization but of reaching a satisfactory outcome in Cyert and March (1963) fashion (satisficing). Right from the beginning bounded rationality was assumed. It was obvious that microfoundations, such as decision-making style, and contextual characteristics could affect MBE behavior.

The dynamics of the model of the internationalization process we made evident by differentiating between state and change variables, affecting each other as shown in figure 1. Learning affected market knowledge. The changed stock of knowledge in turn affected decisions and changed commitments, leading to a higher level of commitment; based on data from the 1950s and 1960s a decreasing commitment was never observed. This is an important conclusion which already has been changed. Obviously, researchers’ viewpoints also depend on the context in which they work. Commitment was defined as the size of resources at stake times the degree to which the resource could be used for an alternative purpose. This definition ties in with later definitions of risk, as the volume of resources may be lost if “things go wrong” (Figuera-de-Lemos et al., 2011; March & Shapira, 1987). This definition of risk is not consistent with the dominant definition, that is, the probability of an event occurring in the future.

Figure 1. The Uppsala model, 1977 version.

Source: Johanson & Vahlne, 1977.

Learning, we found, is a byproduct from performance of operations in foreign markets, called current activities (Johanson & Vahlne, 1977). Active search was rarely performed, as “enough” was learned from experience, presumably contributing to the path dependence. However, objective knowledge (i.e., knowledge that was learned from lectures, books, and government sources) was to some extent necessary. Experiential learning is highly context-specific, and that is why it cannot be easily transferred. It was also found that experiential learning has internal and external dimensions: middlemen and subsidiary heads need to have knowledge of the principal’s or headquarters’ strategy (Johanson & Vahlne, 1977). Acquisitions to gain market knowledge (i.e., experiential learning by the acquired firm) has some limitations.

Stocks of knowledge and commitments was assumed to constitute units of relevance for the individual foreign market. On this point, Sweden had been affected for some time by the way the economic statistics, Swedish and international, were structured with the nation as the basic unit. An example is export and import statistics. Later, Sweden realized that the relevant network, that is the aggregate of actors of importance to the focal MBE, was in focus for the focal firm (Johanson & Vahlne, 2009).

The 2020 Version of the Uppsala Model

The model has been through several iterations of which the most important has been detailed in Vahlne (2020). This article describes the 2020 version and disregards the changes that have been made to it. Likewise, many of the references supporting the changes have not been included. The article first emphasizes on ontological views and then examines the model and the assumptions on which the model rests. Finally the applications of the model made so far are observed.

Ontology

Right from the beginning it was evident that MBEs and company managers in general are “continually in a state of becoming” (Langely et al., 2013, p. 5). Businesses exist in a context of more or less rapid change in which they go through in an evolutionary process which is open-ended (Hernes, 2014). Likewise Nelson and Winter (1982, p. 10) saw evolution as processes of long-term and progressive change. Such evolutionary processes are not only mostly path-dependent and cumulative, but revolutionary change may also happen (Sydow et al., 2009). Believing that it is not possible to fully explain evolutionary processes, as there so many factors and so many causal relationships to pay attention to, our epistemology has been based on the ontological view of the reality subscribed to: dynamic interplay (Vahlne & Johanson, 2013, 2017).

Context

By definition, as the Uppsala model describes and explains how MBEs manage their ongoing business and in parallel prepares for the future, uncertainty becomes a central contextual aspect. It is generally believed that the possibility to calculate risks is rare and uncertainty is the more common case: the future cannot be known (Knight, 1921). Still, the Knightian type of uncertainty, with extreme ambiguity and complexity, is not necessarily the most common, but it occurs. Sarasvathy (2001) proposed alternatives, such as effectuation (i.e., under extreme uncertainty) and causation (i.e., under a low level of uncertainty), and these alternatives are highly relevant. Predictions in Knightian uncertainty are less relevant because experienced entrepreneurs act from what they are able to control and they exploit contingencies (Schweizer et al., 2010). This view comes close to Knight’s view, which is that those best fitted to cope with extreme uncertainty are those with experience from that sort of context (Figuera-de-Lemos et al., 2011). The degree of uncertainty can be lowered by reconfiguring the focal project (Vahlne et al., 2017). Some individuals will take on the role of uncertainty absorbers which the following statement by a former AB Volvo president makes clear: “Business wants what is brave and innovative as long as it does not imply risk. . . . Everything should be predictable. The establishment and the owners dislike the unforeseen. Then spokesmen can talk in rather solemn words about risk-willingness, entrepreneurship and drive. But when they see it, they do not like it” (Gyllenhammar, 2014, pp. 76–77, authors’ own translation). MBEs, and some individuals, have to live with the unavoidable uncertainty.

As acting on contingencies is an unavoidable aspect of managing under uncertainty, in modeling the process, whether it is through internationalization or evolution, the environment cannot possibly be neglected. There is considerable overlap between Sarasvathy’s effectuation model and the Uppsala model, including acting on contingencies, as Sarasvathy et al. (2014) argued. The importance of combining the experientially acquired skills of the entrepreneur, or the entrepreneurial manager, with the resources available via the network is crucial for success (Schweizer et al., 2010). Hence, the Uppsala model is applicable for both large MBEs and SMEs (Chandra et al., 2020).

The uncertainty dimension of the context may make efforts to behave rationally futile. Emotions and cognition play an important role, as one cannot know the future; complexity and ambiguity make it impossible to be “rational” (Kahneman, 2003; Levinthal, 2011). Therefore, it makes sense to think about the impact of microfoundations on the Uppsala model, finding out that decisions to change radically are avoided but that small, incremental, and accumulated commitments can lead to radical change (Vahlne, 2020).

Another general contextual dimension is the network character of the business environment: “no firm is an island,” but firms are all connected to other actors via more or less tight relationships (Snehota, 1990). This is strongly opposing the neoclassical view of firms as independent actors. It seems that the network view has come to dominate micro-level theory of the firm (Johanson & Vahlne, 2009). Firms are embedded in networks of relations, strongly affecting all activities, from operations to development of future competitive advantages (Dyer & Singh, 1998). Companies at both ends of a fruitful relationship benefit from mutual commitment and joint productivity, and effectiveness improves (Blankenburg Holm et al., 1999; Morgan & Hunt, 1994). Joint knowledge development is beneficial for innovation and competitiveness, thereby contributing to heterogeneity between firms (Agarwal et al., 2009).

It takes time to build such relationships. Strength in establishing relationships, then, becomes a critical microfoundation, a dynamic capability (Vahlne & Bhatti, 2019). Insidership in a relevant network is an asset, and the establishment of relationships should consequently be seen as an investment and a commitment. Insiders have an advantage, and hence outsiders suffer from a “liability of outsidership” (Johanson & Vahlne, 2009).

Once established, relationships are of importance for many aspects of management, particularly for discovery and development of opportunities such as choosing which market to enter, what mode of entry to apply, and with what partners to engage (Coviello & Munro, 1997; Johanson & Vahlne, 2003). It also follows that interdependence may become too strong and can hamper development of the focal firm in the case of “over-embeddedness” (Uzzi, 1997), implying that no “disturbing” but potentially forward-leading information is received. Firms need both strong and weak links (Granovetter, 1985).

Following from the network view of the economy is that evolution is really a matter of co-evolution with partners in the network, including actors at the macro, micro and milli-micro levels (Ghoshal & Moran, 1996).

Assumptions

Right from the start it was essential to assume bounded rationality, given the closeness to management and behavioral theory of the firm (Cyert & March, 1963). It was also natural, for example, to see problemistic search and the criterion of satisfactory performance as realistic behaviors. Gradually, (implicit) assumptions of rational behavior were substituted for by behaviorally based assumptions (Vahlne & Johanson, 2014). “We have paid a big price for the uncritical acceptance of neo-classical theory” (North, 1990, p. 131). Assumptions in this case include heterogeneity, more or less constant change, and transactions not being isolated events but rather a detail of long, lasting relationships. Studying why MBEs exist of less interest than knowing how and why they evolve. Coordination and governance have gradually come to depend less on hierarchical means but more on “soft mechanisms” (Hedlund, 1986; Martinez & Jarillo, 1989). The MBE itself can be understood as a network (Bartlett & Ghoshal, 1989). Capabilities are more critical than resources. Multinationality can be seen as an accumulation of international experiences and is embedded in human and relational capitals (Dunning & Lundan, 2008; Kirca et al., 2012). A summary of the assumptions subscribed is offered in Dosi and Marengo (2007).

The Model

The construction of the 1977 version of the model was such that it has been possible to keep the structure and mechanisms up until today and hopefully in the future. This is due to the fact that the model is extremely parsimonious, general, and axiomatic in character (see figure 2). Process of knowledge development and commitments progress and affect each other via the state variables. These mechanisms are similar to these at work in the “structuration theory” formulated by Giddens (1984) and the institutionalization theory as formulated by Barley and Tolbert (1997). The action, and more particularly the change variables, have an impact on the state variables, which in turn affect the change variables. This makes the model fully consistent with thoughts on the symbiosis between stability and change; the two concepts support each other. Routines sow the seeds of change by allowing for experiential learning, giving rise to perception of opportunities for change. Exploration and exploitation are not forces working against each other but rather are necessary for each other, in the sense that it is during performance of business activities (i.e., exploitation) that new opportunities may be discovered (Farjoun, 2010; Feldman & Portland, 2003; March, 1991). However, path dependence may lead to a “lock-in,” leading to rigidity (Sydow et al., 2020).

Figure 2. The Uppsala model, 2020 version.

Source: Vahlne, 2020.

Change Variables

The commitment processes are investments (or de-investments) in physical resources and/or intangibles making the focal organization changing the state variable degree of commitment. The commitment can have different objects: a market (Johanson & Vahlne, 1977), a network partner, or a particular project (Johanson & Vahlne, 2009). Furthermore, it has a forward orientation mirroring an intention. Implemented commitments affect performance. Depending on the context, it may make sense to distinguish between decision processes and implementation processes, or between reconfiguration and change of coordination (Vahlne et al., 2011; Vahlne & Ivarsson, 2014). The criterion for deciding on a certain commitment is the relationship between the value of the focal opportunity and the risk. The risk is then defined as the value of resources at stake (it is not a probability) (Figuera-de-Lemos et al., 2011; Johanson & Vahlne, 1977). This in line with the findings from March and Shapira (1987) and Sarasvathy (2001).

As for the other change variable—knowledge development—it was originally seen as just experiential learning. Forsgren (2002) found it of importance to include it alongside active search, imitation, and acquisition. It is also important to realize that the knowledge that is needed does not exist; it has to be developed, which explains therefore why creation is seen as an aspect of knowledge development. For example, at the beginning of a new supplier–customer relationship, knowledge about what adjustments are required to find a good fit between the customer needs and the supplier’s offer is needed. This new knowledge will lead to an improved product from the customer’s point of view. Knowledge development therefore manifests itself in routines, as new knowledge leads to different behaviors (Brown & Duguid, 1991; Johanson & Vahlne, 2009; Nelson & Winter, 1982).

Finally, Nahapiet and Ghoshal (1998) and Morgan and Hunt (1994) added trust building to the list of components of knowledge development. Existence of mutual trust between parties seems to be necessary to create innovative knowledge. In hindsight, trust building also requires pledges of commitments in a process over time (Boersma et al., 2003; Madhok, 2006). Trustful relationships may also produce knowledge on valuable opportunities for both parties, and perhaps other network members (Chetty & Agndal, 2007). Such knowledge is, by no means, public, but confined to the parties involved.

State Variables

The original “knowledge” is replaced by capabilities: operational and dynamic. A capability is the ability to use a resource for a particular purpose (Katkalo et al., 2010). Operational, or ordinary, capabilities are the abilities to perform normal business activities such as production and marketing. Dynamic capabilities are the abilities to reconfigure more or less continuously resources to improve the operational capabilities, which perform better or adjust to a changing environment (Eisenhardt & Martin, 2000; Teece, 2007, 2014; Teece et al., 1997). The concept of capability is used instead of knowledge or resource because “resources are akin to stocks, capabilities are hinting at process” (Katkalo et al., 2010, p. 1176).

A capability is an absolute concept. A capability may or may not constitute a firm-specific advantage (FSA) is a relative concept, relative to actual or potential competitors (Dunning & Rugman, 1985). An FSA is considered necessary to overcome the liability of foreignness to be able to invest sustainably in a foreign market (Hymer, 1976). However, it is not the individual FSA that matters but the strength of the totality, the “package” of all FSAs (and firm-specific weaknesses). Over time, the relative value of both the total package and the individual FSAs may change, which is known as an advantage cycle (Johanson & Vahlne, 1990; Sandén & Vahlne, 1976). Consider, for example, the Swedish MBE Sandvik, which has long lost its FSA based on steel-processing technology but has stayed in business thanks to its strong customer relations, making it possible for the firm to develop new technology (Johanson & Vahlne, 2009). Alternatively, Almódovar and Rugman (2015) found that insidership compensate for low levels of research and development (R&D). The advantage cycle, an FSA followed by another one, is a critical element in the effort to develop the Uppsala model to explain MBE evolution more generally.

The second category of state variables includes commitments and performance. Commitments are manifested either as resources specifically targeted for a purpose, leading to asset specificity (Williamson, 1975), or intangibly by contracts, promises, or elements in MBE strategy. Performance is the result of previous action in dimensions relevant to the research problem at hand. In a network version, the dimension network position is used while in the study of globalization it is the degree of globalization.

MBE Evolution

Having started out by explaining the process of internationalization, the interest then moved on to the study of globalization and MBE evolution in its totality (Vahlne & Johanson, 2017), in an effort to bring together the process and strategy content. As mentioned, certain capabilities may constitute advantages, allowing the MBE to compete sustainably in foreign markets and even to pursue a complete sustainable evolution. The processes behind the existence of items of the advantage package constitute the advantage cycle. One such item of the advantage package, perhaps historically the most important, is superior technology, developed by performance of an R&D process. A large study of R&D processes concluded that the characteristics of processes, such as uncertainty, dynamics and incremental commitments, open-endedness, trial and error, and building and exploiting trustful relationships, were always present (Van de Ven et al., 1999). Similar findings were reported by Pavitt (1991), Dosi (1982), and Janssen et al. (2015). The consistency of the findings on internationalization and globalization, and hence with the Uppsala model, is strong. The processes behind strategy-making shows similar characteristics (Minzberg & Waters, 1985) as do processes behind organizational development (Baum & Rao, 2004; Van de Ven & Hargrave, 2004). Findings like these, and the axiomatic properties, support the paradigmatic character of the model (Håkansson & Kappen, 2017; Santangelo & Meyer, 2017; Vahlne, 2020). The model cannot be falsified, only evaluated as more or less useful as a base for developing testable propositions. So far, it has been applied in areas such as entrepreneurship, emerging-market MBEs, and strategic management, on top of internationalization and globalization (Vahlne, 2020).

The Coming Eighty Years…

There are several avenues for research that will hopefully be explored in the future: (a) the paradigmatic shape can be exploited by using the shape as a platform onto which models with detailed causal relationships are built; (b) these causal relationships should be tested; (c) it would be great if findings based on the Uppsala model, being accepted as a valuable part of the theory of the firm, can be used in efforts to construct macro-level models for countries or regions relying upon more realistic assumptions than what seems to be the case today.

Developing Models with Causal Relationships

Early findings seemed to indicate that “the more experience the heavier commitments” (Hörnell et al., 1972, p. 64; Johanson & Vahlne, 1977, p. 8). Later we found that this deterministic view was not true (Vahlne & Johanson, 2017). The context of the “golden” postwar period, with rapid economic growth leading to increasing demand for Swedish engineering systems that were applied for restoring and expanding infrastructure, led to the wrong conclusion: sales growth was strongly positive and hence commitments were increased continuously with hardly any exceptions. In more balanced contexts, increased experience may of course lead to an opposite decision: the focal MBE, realizing that the future is not promising enough to warrant increased commitment, may perhaps decrease de-internationalization, for example. This view is consistent with the contingent nature of the model (Figuera-de-Lemos et al., 2011).

The Economist (2020, p. 59) offered an example: experiences from an extreme negative shock, like the COVID-19 pandemic, may leave “economic scars” and strongly affect beliefs about the future. A similar shock can well happen to a management team of an MBE for some time, hampering future development. Studying the microfoundations of the model could be fruitful. One such area is the way managers cope with uncertainty.

It seems there is a lot of potential in studying the impact from microfoundational impacts on knowledge development, or lack thereof, as a base for the development of the dynamic capabilities of the MBE.

Likewise, the model concludes that increasing commitments lead to perceived needs to learn and develop new knowledge. Foreign investments may trigger a search to identify more about the advantageous consequences for the knowledge acquirer (Aharoni, 1966; Ivarsson & Vahlne, 2002). However, these relationships need to be detailed and varied. Likewise, what new knowledge triggers change of commitments? The potential for developing the model is large.

Testing Causal Relationships

The essence of the Uppsala model is the dynamic character of the relationships; the state and the change variables have an impact on each other continuously as processes progress over time as shown in figure 2. Even today, most empirical studies are static in nature. However, why one sees so few applications of dynamic statistical methods does not mean that they do not exist but that there is very little suitable data. What are needed are not just materials found in annual reports but more penetrating data on, for example, capabilities, both operating and dynamic, performance and commitments, and knowledge development and commitment processes, all longitudinally over time. To invest in such data collection requires commitment from both a number of MBEs and a research institution as data must be collected for several years in a row. Presumably, running executive programs over a series of time periods could provide an opportunity for collecting such data, and the results of the analysis could be rewarding for the participating MBEs.

Normative Conclusions

Successfully testing the Uppsala model could lead to conclusions pertaining to credible normative managerial advice. It has already been suggested that mutually developed relationships characterized by trust and commitments produce dynamic innovations, efficiency, and effectiveness (Morgan & Hunt, 1994; Nahapiet & Ghoshal, 1998). Findings concerning the very speedy internationalization process of Swedish IT companies seem to indicate that experiential learning and trust-building are critical ingredients in sustainable internationalization and MBE evolution (Vahlne & Johanson, 2002). There is presumably no tradeoff between the wish for high speed and the need for satisfactory learning and trust-building; the latter should guide action to avoid (very) poor performance.

From Micro to Macro

Since the beginning of the 21st century, macro-economists have struggled to make the assumptions on which their models rest more realistic, that is, affected by findings in “behavioral economics.” According to one observer, these efforts are likely to end successfully, and the prefix “behavioral” can be dropped (Gabaix, 2020).

One such effort aims to understand how the 2007 financial crises was based on the difference between “rational expectations” and empirically based expectations of micro-level agents using the credibility of central banks’ forward guidance on interest rates (Proano & Lojak, 2020). Rational expectations are too far from how actors in practice behave. In Driscoll and Holden (2014), who avoided the rational expectations of assumption, argued that micro-level actors were believed to choose an equilibrium strategy, in practice assuming coordinated expectations. Limited cognitive capacity to absorb information leads to a high level of uncertainty (Driscoll & Holden, 2014), and uncertainty often leads to imitation, as it is perceived as better to be one in a crowd than sticking out as a loser (Eliasson, 1991). An exogenous shock may accordingly change heterogeneous expectations into waves of pessimism, leading to a downward deflationary spiral (Hommes & Lustenhouwer, 2019). Obviously, heterogeneity between actors cannot uncritically be assumed.

“Animal spirits” is a concept invented by Keynes and is used periodically by some of those interested in how human psychology drives the economy (Akerlof & Schiller, 2009). Such animal spirits, implying nonrational expectations, have been shown, among other things, to explain business cycle fluctuations (Dées & Zimic, 2019). Those nonrational expectations may be formed via experiential, adaptive learning (Aquirra & Vasquez, 2020). An animal spirit implies that human beings are partially myopic, which is one of the reasons why they are unable to anticipate future events accurately (Gabaix, 2020). Franke and Westerhoff (2017) stated that there is indeed unreducible uncertainty and that “we endeavor to conform with the behavior of the majority” (p. 1166). “The New Keynesian theory is proud of its ‘microfoundations’” (Franke & Westerhoff, 2017, p. 1163). Sentiments based on gut feelings are more reliable in explaining at least long-term expectations. Still the efforts to make the microfoundations more reliable are in their infancy, and more theorizing is needed (Spiegler, 2019).

However, modernizing macroeconomics is not only about paying attention to the psychological characteristics of human beings. It can also help to differentiate between micro-level actors (e.g., individual firms) and the structure of business (e.g., networks). Baqaee and Fahri (2019) set out to “challenge the notion that the microeconomic details of the production structure are irrelevant for macroeconomics” (p. 1156). Such factors include network linkages, microeconomic elasticities of substitution, and microeconomic returns to scale. Baqaee and Fahri (2020) later confirmed that the differences between individual firms have explanatory value for the rate of growth of the economy.

There are definitely similarities between some assumptions concerning the micro level built into the new Keynesian models and the findings from theory of the firm (Cyert & March, 1963; Johanson & Vahlne, 1977; Penrose, 1959; Vahlne & Johanson, 2017). Examples include experiential learning (about the credibility of central banks’ forecasts), the importance of networks, returns to scale (to fund increased investments in R&D), inertia in reacting to environmental change, and heterogeneity between actors.

However, there is more to it, as more firm-level findings could potentially be used to develop assumptions for macro models, with due respect to the difficulties involved in the aggregation. For example, some of these assumptions may be hard to quantify.

The main aspect of the context in which firms operate is uncertainty due to, more or less, rapid environmental change and liabilities of foreignness, outsidership, and complexity (Hymer, 1976; Johanson & Vahlne, 2009; Vahlne & Johanson, 2021). Findings have indicated that firms cope with uncertainty by progressing in small steps, mainly in a path-dependent fashion, learning from experience, and co-evolving with other actors with which they have relations (Johanson & Vahlne, 2009). Not having much knowledge makes firms, to some extent, depend on trust when committing resources involves other parties. It is hard to plan accurately, and some firms consequently stopped budgeting in the traditional sense (Wallander, 1999) because managers were relying more on the budget than adjusting their activities to environmental changes. Experienced entrepreneurs seem to prefer to act from what is known, rather than from a plan, in the fashion found by Sarasvathy (2001).

Animal spirits must be the reason for the statement made by Nelson and Winter (2002): “How can the same organizations be so impressively competent from one perspective and so strikingly ´bounded´ in their rationality?” (p. 29). In other words, the natural sciences offer possibilities to optimize, while the socially constructed reality, being too complex and dynamic, only lends itself to temporary, satisficing solutions.

It is appropriate to refer to Nelson and Winter for another reason: it seems that the existence of a general equilibrium is still assumed (Baqaee & Fahri, 2020; Driscoll & Holden, 2014). As there is no equilibrium but ongoing dynamic change, efforts have to made to build macro models assuming such a context (Nelson & Winter, 1982).

Concluding Remarks

Advanced statistical analytical methods are needed; however, in some research areas there is too much focus on the application of highly sophisticated statistical methods on problems with meagre theoretical underpinning and hence with little theoretical contribution as a result. Qualitative studies should be mixed with theoretical development in an abductive fashion to build a “stronger base” from which hypotheses for statistical examination can be deducted.

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Notes

  • 1. To make clear that a multinational firm differently has been defined from the neoclassical multinational enterprise (MNE), the denomination of multinational business enterprise (MBE) is used in this article to stress exchange rather than production, process rather than structure, network context rather than independence, and decentralization rather than hierarchical organizational structure (Johanson & Vahlne, 2009).