When We Are Happy, We Are the Same—Emotions as a Boundary Condition for the Impact of Cultural Differences on Strategic Decisions

The effects of cultural differences have been widely studied in the domains of international management (for a review, see López-Duarte et al. 2016), organizational behavior (for a review, see Tsui et al. 2007), and strategic management (e.g., Nielsen and Nielsen 2011; Song et al. 2002). Especially in the context of strategic decision making (i.e., decisions that are characterized by high levels of complexity, uncertainty, and ambiguity; Schwenk 1995), cultural differences affect executives’ choices (Dimitratos et al. 2011) and firm performance (Li et al. 2001).

Most research that analyzes the effect of cross-cultural differences on strategic decisions is rooted in the values-based approach to culture (Li et al. 2017). In other words, it distinguishes among national cultures based on Hofstede’s (1980) value dimensions and compares strategic decisions among members of different cultural groups. This research has shown, for example, that firms in countries with higher levels of uncertainty avoidance, collectivism, and power distance tend to exhibit more corporate diversification (Savitz et al. 2016). Bachmann et al. (2016) find that certain cultural values—especially higher uncertainty avoidance and lower levels of individualism and masculinity, as assessed on the country level in nine countries—moderate the positive effect of strategic planning on the firm’s entrepreneurial orientation. Dimitratos et al. (2011) analyze the impact of cultural values on the strategic decision-making process in firms from four countries and find a negative association between power distance and decentralization as well as positive relationships between individualism and lateral communication and between uncertainty avoidance and rule formalization in the strategic decision-making process. In a study of top managers from 20 countries, Geletkanycz (1997) shows that individualism, power distance, uncertainty avoidance, and long-term orientation are associated with openness to change. However, for two of the four cultural values, the relationship is the reverse of the anticipated direction. Barr and Glynn (2004) attribute differences in executives’ strategic-issue interpretation to differences in uncertainty avoidance in their countries of origin. Specifically, they suggest that executives from countries characterized by high uncertainty avoidance tend to perceive strategic issues as less controllable. However, they do not find any effects for other cultural values.

Overall, research that analyzes the impact of national cultures on strategic decisions based on Hofstede’s (1980) values-based approach has been criticized, as it cannot comprehensively explain the effects of cultural differences observed in the extant research (Tung and Verbeke 2010; Oyserman and Lee 2008; Shenkar 2001). In particular, the values-based approach assumes that culture is defined by fixed dispositions (i.e., static cultural values that hardly change over time; Beugelsdijk et al. 2015). However, inconclusive findings on the effects of cultural differences on strategic decisions suggest that such effects are—at least in part—context-dependent (i.e., when the strategic context changes, the impact of culture on a strategic decision might change; Chiu et al. 2000).

To account for these deficits in our extant knowledge, psychological research on culture and decision making has suggested a dynamic constructivist approach to culture (Hong and Chiu 2001). This approach describes culture as a loose network of knowledge structures and folk theories that result from long-established differences in social organization and social practices, and proposes that these structures mediate social behavior (Hong 2009). Cultural differences manifest themselves in, for example, the social norms, values, and cognitive styles that are shared among the members of a cultural group and guide their decision-making behavior (e.g., Yates and de Oliveira 2016). For instance, when making decisions, Westerners have been found to rely on a more analytical thinking style that is more object-focused and based on the assumptions that the world is stable and predictable (Ji et al. 2008; Miyamoto et al. 2006). East Asians, in contrast, are more likely to apply a more holistic thinking style, rooted in the assumptions that contradictions can coexist and that change is a constant phenomenon (Ji 2005; Li et al. 2014).

Notably, the dynamic constructivist approach proposes that cultural dispositions do not always affect the behavior and decision making of members of a cultural group, and that these effects are not always of the same magnitude. In addition, it suggests that cultural norms, values, and cognitive styles are stored in the memory of the members of a cultural group, where they become available and accessible as part of an interconnected, associative cognitive network (Briley et al. 2014). Whether a member of a cultural group applies these norms, values, and cognitive styles in a specific situation depends on their perceived relevance to the focal task, i.e. the subjective assessment of their applicability in the specific context (Hong 2009). This implies that the effects of cultural norms, values, and cognitive styles on individual behavior in general and decision making in particular may surface, disappear, or even reverse if the behavioral context changes (Chiu et al. 2000).

Research has identified several boundary conditions that determine when certain cultural norms, values, and cognitive styles are activated and affect the behavior and decision making of members of a cultural group. Hong et al. (2000) show that activation can be achieved through cognitive priming based on culture-related stimuli, such as pictures of cultural symbols. In an experiment involving French and Korean consumers, Choi (2020) finds that (independent versus interdependent) self-construal priming reduces the cultural differences between members of these two cultural groups. Briley, Morris, and Simonson (2000) show that East Asian consumers are more willing to accept compromises when they are asked to provide reasons for their choices, while North American participants prefer compromises to a lesser extent when they are forced to provide such reasons. These authors argue that the need to justify a choice activates the more holistic cognitive style that is inherent in East Asian cultures, while in North Americans it brings the more analytical thinking style that characterizes Western cultures to the surface. While extant research adopting the dynamic constructivist approach to culture focuses on cognitive drivers of the activation of cultural norms, values, and cognitive styles, psychological research on culture and decision making suggests that emotions might also serve as a boundary condition for the impact of culture on individual behavior and decision making (Kitayama et al. 2006).

Based on psychological foundations, researchers in the strategic decision-making field have started to explore the effect of emotions on strategic decisions (e.g., Døjbak Håkonsson et al. 2016; Hodgkinson and Healey 2011; Huy 2011). Emotions are defined as discrete, intense, and short-lived adaptive responses to environmental demands (Scherer and Ekman 1984; Elfenbein 2007). Initially, research on emotions in the strategic decision-making context has focused on valence-based conceptualizations of emotions, i.e. on positive vs. negative emotions. For example, Døjbak Håkonsson et al. (2016) have associated positive emotions with more explorative strategies, while Amabile et al. (2005) have found a positive effect of such emotions on creativity in the workplace. Negative emotions, in contrast, have been linked to insensitive communication and problem avoidance (Maitlis and Ozcelik 2004).

Based in particular on the appraisal tendency framework (Lerner and Keltner 2001), more recent research in the strategic decision-making field has started to analyze the effects of discrete emotions, such as anger, fear, and happiness, on the strategic decision-making process (e.g., Meissner et al. 2021; Neumann and Wulf 2022). The appraisal tendency framework posits that discrete emotions trigger specific motivational and cognitive processes—so-called appraisal tendencies—that determine how that emotion impacts judgement and decision-making (Han et al. 2007). For example, happiness has been associated with appraisals of elevated certainty and individual control (Smith and Ellsworth 1985), which—in a Western context—has been linked to more optimistic assessments of risk (Lerner and Keltner 2001) and more heuristic information processing (Forgas 1998).

However, psychological research on culture and emotions indicates that the appraisal tendencies, that are associated with specific emotions, might differ across cultures due to specific cultural affordances (Kitayama and Marcus 1999). The concept of cultural affordances reflects folk theories, social practices, and schemas, that have been shared within a cultural group over generations (Kitayama et al. 2007) and that provide specific meanings to emotional experiences, thus triggering different appraisal tendencies for the same emotion across cultures (Kitayama et al. 2006). For example, individuals from East Asian cultures have been found to experience socially engaging emotions, such as pride, more strongly than Westerners, who experience disengaging emotions, such as anger, to a stronger extent (Kitayama et al. 2006). Matsumoto et al. (2008) find a particularly strong effect of cultural affordances for high-activation, positive emotions such as happiness.

These arguments are supported by findings in the strategic decision-making field, where research has shown that emotions affect cognition and thinking styles (Hodgkinson and Healey 2008, 2011), information processing (Seo and Barrett 2007; Staw and Barsade 1993), and the perception and interpretation of strategic issues (Mittal and Ross 1998). Neumann and Wulf (2022) report that emotions, such as fear and happiness, impact the strategic issue interpretation—as one element of the strategic decision-making process—of German and Chinese managers in different ways. They find that Chinese managers are affected in their interpretation of strategic issues by happiness as well as fear while German managers are only affected by fear. Overall, research in the strategic decision-making field indicates that emotions, such as happiness, might change the effects of cultural differences on the strategic decision-making behavior of Western and East Asian managers.

Psychological research on culture and decision making has highlighted differences in the decision-making behavior of East Asian and Western decision makers. For example, Chinese executives have been found to exhibit a more holistic thinking style, which acknowledges the existence of contradictions and of change as a constant phenomenon (Ji 2005; Li et al. 2014), while German decision makers tend to adopt a more object- and stability-focused analytical cognitive style (Ji et al. 2008; Miyamoto et al. 2006).

Furthermore, Chinese decision makers process significantly more information and do so in a more integrated manner (Kühnen and Oyserman 2002; Oyserman and Lee 2008). At the same time, they tend to be less likely to ignore important pieces of information (Choi et al. 2003). On the other hand, Western decision makers typically rely on heuristics when processing information, which results in less attention to detail (Buchtel and Norenzayan 2008; Nisbett et al. 2001). Therefore, in decision-making processes, Western managers are more likely to selectively focus on important information, while more holistic, East Asian executives tend to engage in broader information processing (Li et al. 2015).

Consequently, Chinese executives consider a wider range of factors as relevant in decision situations (Li et al. 2016; Ng and Hynie 2014) and develop a broader set of alternative arguments when making strategic decisions (Kühnen and Oyserman 2002; Oyserman and Lee 2008). For this reason, East Asian decision makers tend to allocate resources more broadly than their Western counterparts (Li et al. 2018). Given the above arguments, we propose that when asked to choose among a number of strategic investment alternatives, Chinese executives will find positive and negative aspects in all options at hand, resulting in a more diversified allocation of strategic resources, while the opposite holds true for German decision makers. We therefore posit:

Happiness is an emotion that is frequently experienced in the context of strategic decision making (Hermalin and Isen 2000). Psychological research on emotions and decision making indicates that specific emotions are associated with different appraisal tendencies (Lerner and Keltner 2001) and that these appraisal tendencies might change due to cultural affordances (Kitayama et al. 2006). Specifically, positive emotions, such as happiness, have been linked to changes in information processing in the context of strategic decisions (Staw and Barsade 1993). Initial findings from psychological studies in Western and East Asian contexts have highlighted how analytical (Western) and holistic (East Asian) thinking styles might change in a happy emotional state (Au et al. 2003; Matsumoto and Wilson 2008).

In a study in an East Asian context, rather than exhibiting holistic strategic decision-making behavior, participants in a happy emotional state engaged in more selective information processing, and adopted a more superficial and quick processing style than participants in a control group with a neutral emotional state (Au et al. 2003). Au et al. (2003) attribute this reversal of cultural disposition to the energizing effect of happiness, which induces overconfidence as well as a higher propensity to simplify, to prematurely rely on heuristics, and to take risks (Schwarz and Clore 1983; Wyer et al. 1999).

Similarly, decision makers in a Western context have been shown to deviate from their cultural disposition when in a happy emotional state. In a study of diagnostic decisions in a Western cultural setting, Isen et al. (1991) find that happy decision makers processed a broader, more complex set of information than a control group. Staw and Barsade (1993) show that happy decision makers tend to more broadly support their judgments with data and achieve higher decision quality. These findings are attributed to the energizing effect of happiness that leads Western managers to dive more deeply into decision tasks, which triggers a broader, more thorough information search (Staw and Barsade 1993; Isen and Baron 1991). Similar results have been reported in group settings (Bramesfeld and Gasper 2008).

Based on these findings, we argue that happiness changes the strategic investment behavior of Chinese and German executives in different ways. Specifically, Chinese executives asked to choose among a number of strategic investment alternatives become more selective and focused, which results in more focused strategic investments. In contrast, German executives become likely to adopt a broader, more integrative approach to their information search, which results in greater diversification of their strategic investments. Overall, we predict that happiness—because of its opposite effects on information processing and risk-taking in different cultural contexts—moderates the relationship between culture and investment allocation in a such way that differences in decision-making behavior are reduced or even disappear. Hence, we posit:

To test our hypotheses, we conducted a lab-in-the-field experiment involving 97 Chinese and 90 German executives who were participants in executive programs at one Chinese and one German university, respectively. We selected Chinese and Germans, as they have been shown to be representative of East Asian and Western cultures (Yates and de Oliveira 2016). Bicultural individuals were excluded from the experiments to avoid biased results, as they may exhibit divergent choice behaviors based on their two cultures (Mok and Morris 2010; Wang 2008). Overall, the sample consisted of executives between 22 and 65 years of age with 2 to 44 years of work experience. Of the executives, 59% held general management positions, 10% were top managers, and 31% occupied specialized management positions.

Design. In line with prior research in the fields of strategy (Croson et al. 2007) and management (Koudstaal et al. 2016), we conducted a lab-in-the-field experiment, which combines the advantages of field studies with the controlled setup of laboratory studies (Schwenk 1982). We used a post-test-only control group design in which we randomly assigned participants to either the treatment or the control condition. To avoid social desirability bias, we did not inform participants about the goal of the research prior to the experiment (Grimm 2010).

We conducted the experiment in person with an experimenter present for the duration of the study. At the beginning of the experiment, participants in the treatment group were asked to watch a movie clip intended to induce happiness. Movie clips are frequently used in emotion research (Bramesfeld and Gasper 2008; Fredrickson and Branigan 2005; Lerner and Keltner 2001) and seem particularly effective for inducing emotions (Lazar and Pearlman-Avnion 2014). The movie clip that we used to induce happiness showed a dance scene from the movie 500 Days of Summer. Subjects in the neutral condition were presented with a neutral movie clip of a scene in which a sheet of paper is held out of a car window and is blowing in the wind. Both movie clips have been suggested by Schaefer et al. (2010). They include almost no dialogue, which helps prevent language priming and barriers (Lindquist et al. 2006). To further test the validity of this emotion-induction method, we conducted a pre-study in China and Germany, which confirmed that the videos were effective for eliciting a neutral emotional state (control group) and a happy emotional state (happy group), as intended.

The treatment group included 93 subjects (48 Chinese and 45 German), while 94 participants were randomly assigned to the control group (49 Chinese, 45 German). After watching the emotion-inducing movie clip, participants moved on to an in-basket exercise in which we tested their strategic investment decisions. All questions as well as the case study used in the experiment were translated from English into German and Chinese using a back-translation procedure. This method has frequently been applied in cross-cultural studies and has been shown to produce highly valid results (Brislin 1970; Lechuga and Wiebe 2011; van de Vijver & Leung 1997).

Procedure. We started our experiment with the same introduction for the treatment and control groups. After the introduction, all participants completed a short questionnaire that focused on the control variables used in the study. For our in-basket exercise, participants were then presented with a hypothetical business situation and asked to work through a series of documents, memos, and emails before making a final decision (Kesselman et al. 1982). By providing participants with a number of informational items, in-basket tasks allow for the study of managers’ abilities to handle complexity and ambiguity. Thus, in-basket tasks simulate the ill-structured problems that strategic decision makers face in their daily work (Woodside et al. 2016). Given their rich context, in-basket tasks are regarded as particularly well suited for studies of strategic decision making (Tse et al. 1988; Woodside et al. 2016). As such, they have frequently been utilized in research on decision making (Connelly et al. 2004; Estrada et al. 1997, 1994; Staw and Barsade 1993; Tse et al. 1988).

For our experiment, we used the in-basket case study “Adam & Smith Inc.” (A&S) which was initially developed by Staw (1976) and later expanded by Tosi et al. (2003). The case first provides participants with a short description of the situation facing A&S, a large international manufacturing company that has been experiencing declining profits. In the second step, each participant is asked to act as the head of business development for A&S. He or she is presented with several memos and emails, and with financial information showing that the board of directors has identified a lack of research and development (R&D) efforts as one of the main reasons for the company’s recent decline in profits. Finally, after reviewing all information, each participant is asked to decide how to allocate an additional R&D budget of USD 20 million among the company’s three divisions. Participants are advised to make the allocation decision based on the projected absolute cumulative profitability per division. In this case, the Medical Industrial Products Division shows the highest projected cumulative profits (see Appendices A and B for further details).

To test whether our experimental groups were successfully randomized, we compared our subgroups with regard to participants’ age, gender, hierarchy, work tenure, and academic degree. Neither the comparison of the German group with the Chinese group nor the comparison of the happy group with the neutral group revealed any differences in these variables, suggesting successful randomization (Tables 1 and 2).

To ensure that our Chinese and German subgroups displayed information-processing differences, we analyzed both groups’ holistic tendencies (Nisbett et al. 2001). An analysis of variance (ANOVA) with culture as the between-subjects factor supports our arguments and is in line with prior research in the field. We found a significant difference between Chinese and German managers (F = 6.386; p = 0.013) with a medium effect size (d = 0.53; r = 0.26) (Cohen 1988), with the Chinese participants (\(\overline{x}\) = 5.59) being more holistic than the German participants (\(\overline{x}\) = 5.15) (See Fig. 1).

To ensure that we successfully induced happiness in our treatment group, we conducted manipulation checks for our self-reported measure of valence and the SCR measure of arousal. For valence, we found significantly higher values for happiness (German: F = 33.459; p = < 0.0005; Chinese: F = 100.490; p = < 0.0005) in both the German (happy: \(\overline{x}\) = 4.87; neutral: \(\overline{x}\) = 3.03) and the Chinese groups (happy: \(\overline{x}\) = 6.07; neutral: \(\overline{x}\) = 2.36). In line with prior research that has used movie clips to induce emotions (Bramesfeld and Gasper 2008), we observed very large effect sizes in both groups (Germans: d = 1.23; Chinese: d = 2.06) (Cohen 2008).

For the SCR, we found significant differences (F = 6.073; p = 0.015) between the happy (\(\overline{x}\) = 0.15) and the neutral groups (\(\overline{x}\) = 0.10) in our study. The effect size was small (d = 0.40; r = 0.20) (Cohen 1988). Moreover, among the Chinese participants, differences between the happy (\(\overline{x}\) = 0.18) and the neutral (\(\overline{x}\) = 0.12) group were significant (F = 4.027; p = 0.048) with a small effect size (Chinese: d = 0.45; r = 0.22) (Cohen 1988). For the German group, we observed higher values of arousal in the happy group (\(\overline{x}\) = 0.12) than in the neutral group (\(\overline{x}\) = 0.07) but these differences were not statistically significant (F Welch = 3.221; p = 0.077). Overall, however, we conclude that happiness was successfully manipulated in the experiment.

To test Hypothesis 1, which suggests that Chinese decision makers diversify their strategic investments more than German executives, we compared both the amount invested in the division with the highest cumulative projected profitability (i.e., the Medical Industrial Products Division) and the standard deviation (SD) of investments across all alternatives. We ran two separate ANOVAs with culture as the between-subjects factor for the 94 participants in our control groups (Lechuga and Wiebe 2011; Li et al. 2016). Tables 3 and 4 show the respective results.

For R&D investments in the division with the highest cumulative projected profitability, we find a significant difference between German and Chinese managers (F Welch = 34.801, p = < 0.0005), with Germans making more investments in the division (\(\overline{x}\) = 15.98) than Chinese participants (\(\overline{x}\) = 9.56). In line with Hypothesis 1, this indicates that Chinese executives seek more diversified strategic investments. The effect size is large (d = 1.23; r = 0.53) (Cohen 1988) (Table 3). For our second measure of strategic investment, the SD of investments across all alternatives, we also find significant differences between the groups (F = 27.445; p = < 0.0005). More specifically, Chinese executives distributed their investments more (\(\overline{x}\) = 3.40) than German executives (\(\overline{x}\) = 6.90). The effect size is again large (d = 1.08; r = 0.48) (Table 4). Thus, both analyses offer support for Hypothesis 1.

Hypotheses 2a predicts that the strategic investment decisions of Chinese executives become more focused when the managers are in a happy emotional state. To test this hypothesis, we ran ANOVAs with emotion as the between-subjects factor for the Chinese subgroups (i.e., neutral versus happy). For R&D investments in the division with the highest cumulative projected profitability as the dependent variable, the results show that the happy group invested significantly more in this alternative (\(\overline{x}\) = 11.79) than the neutral group (\(\overline{x}\) = 9.56) (F = 4.756; p = 0.032). In this case, the effect size is small (d = 0.45; r = 0.22) (Cohen 1988). The results are shown in Table 5. For our second measure of strategic investment, the SD of investments across all alternatives, the results point in the proposed direction, with happy Chinese executives making more focused strategic investments (\(\overline{x}\) = 4.34) than managers in the neutral group (\(\overline{x}\) = 3.40). However, this difference is not significant (F = 2.32; p = 0.131). Thus, our results offer partial support for Hypotheses 2a.

Hypothesis 2b predicts that the strategic investment decisions of German executives become more diversified when those executives are in a happy emotional state. To test this hypothesis, we ran ANOVAs with emotion as the between-subjects factor for the German (neutral versus happy) subgroups. For R&D investments in the division with the highest cumulative projected profitability as the dependent variable, the results show that the happy group (\(\overline{x}\) = 13.33) invested significantly less in this alternative than the neutral group (\(\overline{x}\) = 15.98) (F = 4.334; p = 0.040). The effect size is small (d = 0.44; r = 0.22) (Cohen 1988). The results are shown in Table 6. For our second measure of strategic investment, the SD of investments across all alternatives, the results point in the proposed direction, with happy German executives making more diverse strategic investments (\(\overline{x}\) = 5.67) than German managers in the neutral group (\(\overline{x}\) = 6.90). However, the differences is not significant (F = 2.64; p = 0.108). Thus, our results offer partial support for Hypotheses 2b.

Hypothesis 2c predicts that happiness moderates the relationship between culture and strategic investments, such that cultural differences between the Chinese and German groups diminish in a happy emotional state. To test this hypothesis, we followed prior research examining the interaction of culture and emotion (Hunsinger et al. 2012; Mok and Morris 2010) and used a 2 × 2 factorial design with culture (German versus Chinese) and emotion (happy versus neutral) as factors, and both R&D investments in the Medical Industrial Products Division and the SD of investment as dependent variables. For R&D investments in the Medical Industrial Products Division, the analysis reveals a significant main effect of culture (F = 24.136; p < 0.0005) with a medium effect size (d = 0.72; r = 0.34) (Cohen 1988), but no main effect of emotion (F = 0.065; p = 0.799). At the same time, the analysis points to a significant interaction effect of culture and emotion (F = 9.056, p = 0.003) (Table 7). We obtain similar results for the SD of investments, our second measure of strategic investment. Culture has a highly significant main effect (F = 24.730; p < 0.0005) with a medium effect size (d = 0.73; r = 0.35) (Cohen 1988), while no significant main effect of emotion occurs (F = 0.088; p = 0.767). Again, the analysis shows a significant interaction effect of culture and emotion (F = 5.002; p = 0.027) (Table 8). These results offer support for Hypothesis 2c.

We also plotted the interactions for both the invested amount and the SD of investments. These plots are depicted in Figs. 2 and 3.

To further support the robustness of our findings, we used ANOVAs to analyze whether cultural differences disappear between the subgroups of happy Germans and happy Chinese. For R&D investments in the division with the highest projected absolute cumulative profitability, we find no significant difference between the German (\(\overline{x}\) = 13.33; SD = 6.47) and Chinese subgroups (\(\overline{x}\) = 11.79; SD = 5.12) (F Welch = 1.609; p = 0.208). Similarly, when analyzing the mean SD of investments, no significant difference (F = 3.470; p = 0.066) emerges between the German (\(\overline{x}\) = 5.67; SD = 3.70) and Chinese subgroups (\(\overline{x}\) = 4.35; SD = 3.13). These results, which are shown in Tables 9 and 10, offer further support for Hypothesis 2c.