Get Those Global Experiences!: Intrapersonal and Interpersonal Outcomes of Creative Thinking in Conflict Resolution

Abstract

To investigate differential effects of multicultural interactions (MIs) and exposures (MEs) and to test Maddux et al.’s new structural model of multicultural experience, this research examines the impact of MIs and MEs on intrapersonal versus interpersonal creative thinking. Study 1 tests the associations of MIs and MEs with creative thinking in idea generation and conceptual conflict resolution. Study 2 examines MIs’ and MEs’ relationship with creative thinking in applied conflict resolution (i.e., international business negotiation), with closed-mindedness as a mediator. Results show that MIs (but not MEs) were positively associated with self-reported (intrapersonal) measures of creative thinking in conflict resolution (CTCR), whereas MEs (but not MIs) were positively associated with creative thinking (interpersonal) outcomes in realistic, business conflict resolution contexts. Closed-mindedness fully mediated the former and partially mediated the latter association.

Keywords

creative thinking multicultural experience creative conflict resolution AI negotiation closed-mindedness

Introduction

The field of cross-cultural management has gained significant prominence in the post-pandemic era, fueled by globalization and technological advances that facilitate cross-cultural interactions. As society grapples with global challenges such as climate change and cross border conflicts, the importance of multicultural experiences (MCEs) in shaping individual, interpersonal, and organizational outcomes has become increasingly evident. However, while research on MCEs has expanded recently (e.g., Donohue, 2022; Fürst & Grin, 2023; Puente-Diaz et al., 2019; Xu & Flambard, 2022; Zhang et al., 2023), there remains a need to further investigate the differential effects of multicultural interactions (MIs) versus multicultural exposures (MEs) on creative thinking in various contexts, particularly in conflict resolution.

Research indicates that MCEs positively influence individuals’ creative thinking and outcomes (see Maddux et al., 2021 for a systematic review). Aytug, Kern, and Dilchert (2018) distinguished between MCEs involving social interactions and those lacking personal interactions. Supporting a sociocultural approach to creative cognition, Aytug, Rua, et al. (2018) found that MIs, rather than exposures, enhance divergent thinking, with cognitive flexibility as the mediating mechanism.

To date, this represents the only empirical investigation to examine the distinct associations between an individual’s ME and MI levels and creative thinking. Furthermore, Aytug, Rua, et al. (2018) examined MCEs related to creative thinking solely in idea generation, an intrapersonal activity. However, there remains a gap in empirical research concerning creative conflict resolution, an interpersonal outcome, in relation to an individual’s MCEs, including both MI and MEs. This study attempts to fill this gap in our theoretical understanding which has implications for advancing theory in the negotiation and cross-cultural management literature as well as potentially creating avenues for training to improve important outcomes such as divergent thinking and conflict resolution performance.

In 2021, Maddux et al. published a systematic review on the impact of MCEs on intrapersonal, interpersonal and organizational outcomes, introducing a new theoretical framework of MCE called the Structure-Appraisal Model of MCEs.¹ Within this framework, the structural model of MCEs proposed that “deeper multicultural experiences produce integrative processes that transform intrapersonal cognition, whereas broader multicultural experiences activate comparative processes that influence interpersonal attitudes and behaviors” (p. 345). To further investigate the differences between MEs and MIs, as found in previous research (Aytug, Rua, et al., 2018; Maddux et al., 2021), this research examines the relationship between MIs and MEs and intrapersonal and interpersonal outcomes of creative thinking. We present two studies: The first study investigates the differential associations of MIs and MEs with creative thinking in idea generation and examines the relationships between MIs and MEs with creative thinking about conflict situations (i.e., intrapersonal context), while the second study examines the relationship between MIs and MEs in a conflict resolution context (i.e., interpersonal context).

In the following sections, we examine the conceptual separation between MIs and MEs, along with their varying relationships with divergent thinking in individual idea generation tasks. Drawing on the structural model of MCEs (Maddux et al., 2021), we propose that MIs and MEs will exert distinct influences on creative thinking in intrapersonal (e.g., idea generation) and interpersonal (e.g., negotiation) contexts. Finally, we present two studies designed to test our hypotheses, followed by a discussion of the results and their implications for the literature on MCEs, creativity and conflict resolution and future research as well as implications for practitioners and educators.

Defining and Measuring MCE and Its Sub-Dimensions

MCE refers to past and present exposures to and interactions with foreign cultural elements and individuals (Aytug, Kern, & Dilchert, 2018; Leung et al., 2008). The contemporary conceptualization of this construct distinguishes between multicultural “exposures” (MEs) and “interactions” (MIs). MEs involve “instances in which a person observes elements or members of different cultures without interacting with them,” whereas MI entails “experiences that consist of verbal or non-verbal communication and reciprocal action or influence between the person and members of foreign cultures” (Aytug, Kern, & Dilchert, 2018: pp. 2–3). For example, exposure to different cultures may occur through observing foreign art, reading about diverse cultures or watching foreign media, whereas cross-cultural interactions may involve working, socializing, dating or corresponding with individuals from different cultural backgrounds.

Maddux et al.’s (2021) systematic review of MCEs’ effects on various outcomes revealed that deeper versus broader types of MCEs may have distinct relationships with intrapersonal outcomes (e.g., creativity, entrepreneurship, psychological adjustment, personality, and individual performance), interpersonal outcomes (e.g., trust, communication competence, morality, and intergroup bias) and organizational outcomes (e.g., leadership, internationalization, organizational performance). In the literature, MCEs have been operationalized in various ways, such as international experiences, multicultural background, multilingualism, multicultural networks, and participation in multicultural groups. Maddux et al. (2021) proposed that while deeper MCEs are linked to enhancements in intrapersonal outcomes, broader MCEs are associated with improvements in interpersonal outcomes. More specifically, deeper MCEs tend to involve immersive cross-cultural experiences that enhance intrapersonal cognition, whereas broader MCEs tend to facilitate comparative processes that influence interpersonal behaviors. However, so far, individual-level MEs and MIs have not been separately measured to compare their associations with intrapersonal and interpersonal outcomes.

Despite the conceptualization of MCE as a “multidimensional” construct requiring separate classification of its distinctive elements (cf. Maddux et al., 2009; Narvaez & Hill, 2010; Rich, 2009), much of the MCE research has relied on proxies such as international experience, multicultural heritage, and multilingualism for operationalization, leading to a confounding of distinctive types of MCEs. The development of a multidimensional MCE scale, the Multicultural Experience Assessment (MExA),² has enabled the separate measurement of MEs and MIs (Aytug, Kern, & Dilchert, 2018).

Intrapersonal and Interpersonal Outcomes of Creative Thinking

Creative thinking outcome can be described as an intrapersonal outcome if the individual is engaged in such intellectual creative development of ideas and approaches on their own, without interactions with or input from others. This intrapersonal creative thinking may take place in different contexts, for example, an individual listing creative uses of a product or developing creative approaches for an upcoming negotiation. In both examples, the individual engages in creative thinking alone and the outcomes will be intrapersonal rather than interpersonal. However, sometimes creative thinking process involves more than one individual, such as in brainstorming sessions or team decision making contexts. In these types of interpersonal contexts, creative thinking outcomes are described as interpersonal outcomes because the resulting ideas or decisions reflect multiple individuals’ input and cognition following an interpersonal communication and evaluation process. Thus, the outcomes cannot be attributed to one individual’s individual thinking skills, but they become measures of interpersonal communication and cognitive discussions. The current research focuses on both intrapersonal and interpersonal outcomes of creative thinking, specifically in the contexts of idea development and conflict resolution.

MIs Versus MEs in Relation to Creative Thinking

The creative cognition approach, as established in creativity research (Hao et al., 2015; Runco, 2003; Sowden et al., 2015), posits that surpassing ingrained cognitive limitations and retrieving atypical knowledge structures directly fosters increased divergent thinking and creativity (cf. Chrysikou et al., 2016; McCaffrey, 2012; Runco, 2003). According to schema theory, exposure to new cultures can cause an individual to change their existing schemas, create new ones, and integrate the experience into their cognitive structure (Shea & Wulf, 2005). This contact with other cultures, leads to long-term “cognitive unfreezing” (Crisp & Turner, 2011), or the dismantling of mental rigidity and expanded cognitive structures, resulting in amplified creative outputs.

The sheer volume of stimuli present in social environments overwhelms individuals (Ip et al., 2006), exceeding their capacity for comprehensive processing. Consequently, individuals formulate cognitive schemas and heuristics to streamline environmental interpretation and stimulus processing (Bruner, 1957; DiMaggio, 1997; Markus & Kitayama, 1991). Given that distinct cultural groups cultivate different meaning systems and cognitive schemas (Chao et al., 2015), individuals from diverse cultures rely on disparate sets of shared perspectives, assumptions, practices, and values.

Culturally ingrained mental schemas, becoming persistently accessible, automatically shape perceptions, thus imposing cognitive limitations (Briley & Wyer, 2001; DiMaggio, 1997; Fiske & Linville, 1980). However, aligning with the creative cognition approach, accessing typically inaccessible schemas triggers a conceptual expansion, enhancing divergent thinking (Ip et al., 2006; Ward et al., 2002). Therefore, individuals capable of accessing diverse cultural schemas tend to transcend rigid cognitive constraints, employ a wider range of cognitive structures, and demonstrate heightened creativity. Put simply, MCEs broaden individual mental schemas (Endicott et al., 2003; Kharkhurin, 2011), thereby fostering divergent thinking and creativity (Leung et al., 2008; Ward, 1994).

When delved into different types of MCEs, we can argue that MIs (compared with MEs) should have a stronger positive effect on cognitive and creative development. The foundation for this argument lies in the sociocultural and social learning theories, which propose that human cognitive development occurs primarily through social engagement (Cole, 2005; Tenenberg & Knobelsdorf, 2014). Because learning is a social process, individuals develop skills through cultural interactions (Huong et al., 2024). These social contexts create opportunities for dialogue and exchange that directly foster learning and cognitive growth (Johnson & Johnson, 2009; John-Steiner & Mahn, 1996). In particular, in cross-cultural interactions, interpersonal interactions increase knowledge exchange, which promotes the incorporation of diverse insights into the decision making process, fostering innovation (Makela & Brewster, 2009; Teigland et al., 2009). Thus, social and cultural interactions play a pivotal role in individual learning and cognitive development (Daniels et al., 2007; Gredler & Shields, 2008; Tindale & Stawiski, 2010).

While MCEs encompass both passive exposure and active interaction, it is the latter—MIs—that are theorized to yield more substantial cognitive benefits (Aytug, Rua, et al., 2018). Through direct social engagement, individuals access knowledge and behavioral patterns that would otherwise remain culturally distant or inaccessible (Cole, 2005; Gochenour & Janeway, 1993; Rogoff, 1990). For instance, engaging in conversation with a colleague who observes religious fasting practices creates a deeper cultural understanding than passively watching media coverage of Ramadan celebrations. Interactions require active listening, interpretation, and response, leading to deeper engagement and understanding of the custom. Engaging with individuals on the topic of Ramadan also requires understanding their viewpoints, challenging one’s own assumptions and fostering cognitive flexibility, which can lead to the creation of a new cognitive framework. The direct experience of the religious practice could also introduce perspectives that contradict existing schemas, causing a cognitive reevaluation and adaptation. This interactive and immersive experience contrasts with the more passive viewing of the ceremony, which would arguably lead to a more superficial understanding, confirmation bias, or lack of a new cognitive framework that might break down existing schemas (Rogoff, 2003; Wertsch, 1984).

To date, empirical investigation into the differential effects of MIs and MEs on creative thinking has been limited. A notable exception is Aytug, Rua, et al.’s (2018) work, which measured individual levels of MIs and MEs to explore their associations with creative divergent thinking in the context of individual idea generation. Findings revealed a positive correlation between MIs (but not MEs) and the fluency and flexibility of generated ideas, suggesting that active engagement fosters the production of more and more varied ideas. However, somewhat surprisingly, MIs were not found to be related to the originality of these ideas, a result that warrants further investigation given the theoretical expectation within the creative cognition approach that richer cognitive structures should facilitate the generation of novel concepts.

Recognizing the importance of further understanding the relationship between MIs and creative thinking, particularly regarding originality and in different contexts, the current research aims to build upon the work of Aytug, Rua, et al. (2018). Using a different sample of professionals (managers) and employing a distinct idea generation task, we seek to provide further evidence regarding the association between individual levels of MI and various aspects of creative thinking. Specifically, we hypothesize:

Hypothesis 1: Individual level of MI will be positively associated with individual level of creative thinking in idea generation: number of ideas developed (H1a), number of idea categories (H1b), and the originality of the ideas (H1c).

Hypothesis 2: Individual level of ME will not be significantly associated with individual level of creative thinking in idea generation: number of ideas developed (H2a), number of idea categories (H2b), and the originality of the ideas (H2c).

Creative Thinking in Conflict Resolution

Creative thinking in conflict resolution (CTCR) entails finding innovative solutions to conflicting demands that benefit all parties involved. While conflict resolution approaches can be measured at an intrapersonal level (i.e., survey questions or responses to scenarios regarding conflict), actual creative thinking during conflict resolution is an interpersonal outcome driven by communication and interaction. In this study, we aimed to explore how MIs and MEs are associated with CTCR, considering both individual and interpersonal outcomes.

In interpersonal conflicts, parties often have diverging or opposing demands that they seek to fulfill (De Dreu et al., 2000a). Many times, parties fail to realize the integrative opportunity, where everyone’s needs can be met via creative, tailored solutions (Fisher et al., 2011; Lax & Sebenius, 1986; Thompson, 1990). Creativity is central to this collaborative exploration of the potential deals where all parties’ priorities are satisfied in unique ways (Carnevale, 2006; Isidori et al., 2023). CTCR involves devising strategies to reconcile seemingly divergent or contradictory demands in a way that satisfies both parties via collaborative behaviors, such as problem-solving, information exchange, and perspective taking (Kersten, 2001; Thompson, 1991). As Rothman (1997) notes, “[c]onflicts can be creatively transformed when adversaries come to learn, ironically perhaps, that they may fulfill their deepest needs and aspirations only with the cooperation of those who most vigorously oppose them” (p. xiii).

Much conflict resolution research provide empirical support that collaborative problem-solving is how people achieve creative conflict outcomes (c.f. Maddux & Galinsky, 2009), team innovation (c.f. De Dreu, 2006), and higher integrative agreements (i.e., high pay-offs for both parties; c.f. De Dreu et al., 2006; also see meta-analysis by De Dreu et al., 2000b). The literature extensively discusses creative and collaborative problem-solving approaches in conflicts (e.g., Brett & Thompson, 2016; Fisher et al., 2011; Malhotra & Bazerman, 2007; Ury, 2007). Creative results in conflict resolution can only be achieved through being open to hearing the other party’s perspectives and interests and being willing to collaborate and exchange favors based on differential priorities and needs (e.g., pay-off structures) of the parties. Parties demonstrating creative thinking and problem-solving in conflict resolution explore issues openly, seek to identify the interests underlying the other party’s demands, develop a sense of other party’s needs and pay-off structure, communicate effectively, and consider multiple perspectives to meet everyone’s preferences, increasing pay-off for both parties (i.e., high joint value; Carnavale, 2006; De Dreu, 2006). When parties resist premature concessions and engage in such information exchange, they develop insights about each other’s benefits and pay-offs (De Dreu et al., 2000a), based on which they can make creative give-and-take decisions, finding unique and innovative solutions with high joint gains (i.e., value creation for both parties; Carnavale, 2006; De Dreu et al., 2006).

According to Maddux et al.’s (2021) structural model of MCE, deeper MCEs, which overlap with the deeper-level MIs as proposed by Aytug, Kern, and Dilchert (2018, such as having intimate friendships with people from different cultures or living abroad), tend to influence intrapersonal outcomes like creativity, while broader MCEs, which overlap with the broader MEs as proposed by Aytug, Kern, and Dilchert (2018; a range of exposures across cultural environments) impact interpersonal processes such as communication competence. To expand this model, we propose that deeper-level MIs will be associated with intrapersonal creativity approaches to conflicts (e.g., one’s divergent thinking or intentions about a conflict situation), whereas broader MEs will be linked to creative thinking with interpersonal outcomes (e.g., creative, integrative conflict resolution):

Hypothesis 3a: Individual level of MI (but not ME) will be positively associated with individual level of self-reported (intrapersonal) creativity approach to conflicts.

Hypothesis 3b: Individual level of ME (but not MI) will be positively associated with individual level of creative thinking in realistic conflict resolution context.

Mediating Role of Closed-Mindedness

Closed-mindedness denotes a cognitive state where individuals exhibit resistance to new information, leading to a false sense of certainty (Kruglanski, 2004). This state impedes the willingness to consider alternative perspectives and fosters a desire to shield one’s ideas from scrutiny (Webster & Kruglanski, 1994). Individuals with high levels of closed-mindedness not only display reluctance to embrace novel ideas but also tend to become entrenched and unyielding in their viewpoints (Kruglanski, 2004). Consequently, closed-mindedness exerts influence over an individual’s cognitive and interpersonal processes, impacting their creativity and social interactions. From a creative cognition perspective (Smith et al., 1995), clinging to habitual viewpoints and resisting to different ideas and cognitive frameworks are sure ways to disable cognitive and creative development. While diversity of views brings about innovation by integrating previously inaccessible concepts in exciting ways (McKay et al., 2020), closed-mindedness toward different views, perspectives, behaviors, and values will confine the individual within their habitual cognitive frameworks, reducing their divergent thinking and creativity.

MCEs show people that different cultures utilize new methods, ways, and knowledge. People who get to engage with individuals from other cultures (e.g., work colleagues or school parents) or espies different cultural behaviors (on TV or via observation at a supermarket) may come to realize, in their own safe environment, that a tool can be used in different ways, a behavior may imply different things, or same emotions can be expressed in different manners. This realization and the cognitive growth derived from MCEs, both cross-cultural interactions and exposures, may reduce an individual’s tendency to block different ideas and to exhibit complete confidence in their existing knowledge. In fact, there is empirical support for a negative association between MCE and closed-mindedness (e.g., Narvaez & Hill, 2010). Therefore, we propose that:

Hypothesis 4: Individual level of MI (H4a) and ME (H4b) will be negatively associated with individual level of closed-mindedness.

Individuals with high closed-mindedness tend to reject foreign ideas and novel perspectives and rely heavily on stereotypes while making judgments. This increases the chances of missing newly introduced information (De Dreu et al., 1999) and hurts individuals’ information exchange, perspective taking, and divergent thinking, overall diminishing creativity. In addition, a creative, problem-solving approach in conflicts creates high ambiguity due to large amounts of information processing while searching for creative solutions. Closed-minded people try to avoid such ambiguity by locking in on information, using stereotypes and sticking with initial demands (De Dreu et al., 1999), which lower the creativity of the outcomes. Thus, in both individual idea generation and interpersonal conflicts, one’s psychological openness and willingness to entertain different approaches or opinions (i.e., lower closed-mindedness) may explain the MCE-creative thinking relationship.

Hypothesis 5: Individual level of closed-mindedness will be negatively associated with individual level of creative thinking in idea generation.

Hypothesis 6: Individual level of closed-mindedness will be negatively associated with individual level of creative thinking in conflict resolution.

Hypothesis7: Individual level of closed mindedness will mediate the relationship between MI and creative thinking in idea generation.

Hypothesis 8a: Individual level of closed mindedness will mediate the relationship between MI and creativity approach to conflict resolution.

Hypothesis 8b: Individual level of closed mindedness will mediate the relationship between ME and creative thinking in realistic conflict resolutions.

Empirical Research

Pilot Study

The goal of the pilot study was to develop and validate a brief, intrapersonal measure of CTCR to be used in Study 1.

Method

Item Selection

Following the literature review of creative, flexible and divergent thinking in the conflict resolution context, three items were selected for inclusion with regards to flexible problem solving (e.g., “I am willing to work at creative solutions to problems”; adopted from Martin & Rubin, 1995) and four items were selected with regards to creative thinking in conflicts (e.g., “I try to negotiate and adopt a give-and-take approach to problem situations”; adopted from Adkins, 2006). Selecting the items from published work in the area of creative thinking and problem solving in conflict contexts helped assure the content validity of this measure.

Participants, Procedure, and Measures

Two-hundred and thirty Amazon Mechanical Turk workers were recruited for a 15-min online survey for $1 honorarium toward their account. Two did not fill out the survey; sample size was 228³ (68% male; mean age = 33.78, sd = 8.82, range: 18 – 69).

Survey included the 7-item measure of CTCR (α = .79), 7-item measure of collaborative conflict resolution style (α = .78; Kilmann, 2009; Kilmann & Thomas, 1977) to test for convergent validity, 10-item measure of the cultural dimension of power distance (α = .84; Yoo et al., 2011) to test for discriminant validity, and 13-item creativity measure (α = .89; George & Zhou, 2001; Zhou & George, 2001) to test for criterion-related validity. Participants rated their agreement with each of the construct statements using a 5-point Likert-type scale, where 1 = strongly disagree, 3 = neither disagree nor agree, 5 = strongly agree. Items were presented in a randomized order. Participants were reminded to answer the questions indicating how they usually are / behave rather than how they think they should be / behave.

Results

Table 1 presents the descriptive statistics and correlations. Results revealed no statistically significant gender differences in CTCR [t (226) = −2.03; p = .28].

Table 1.

Means, Standard Deviations and Correlations Among Measures in Pilot Study (N = 228).

Variables	M	SD	1	2	3	4	5	6
1. Age	33.78	8.82	1
2. Sex	-	-	−.07	1
3. CTCR^a	4.12	0.58	.04	.13*	1
4. Collaboration	4.10	0.56	−.04	.12	.86**	1
5. Power distance	3.30	0.84	−.28**	−.08	.22**	.31**	1
6. Creativity	4.10	0.57	.02	.14*	.84**	.80**	.23**	1

CTCR = Creative thinking in conflict resolution.

p < .01. *p < .05.

Exploratory Factor Analysis

Table 2 presents the factor loadings of the seven CTCR items, employing principal component analysis. All item loadings were higher than .400 as expected (Ford et al., 1986), ranging between .583 and .748. Scree plot revealed a single-factor structure, with only one factor’s Eigenvalue above 1 (i.e., 3.108, explaining 44.40% of variance).

Table 2.

Factor Loadings in Exploratory Factor Analysis in Pilot Study (N = 228).

Items	M	SD	CTCRFactor loading
CTCR1. I explore issues with others so as to find solutions that meet everyone’s needs.	4.18	0.81	.623
CTCR2. I try to negotiate and adopt a give-and-take approach to problem situations.	4.06	0.89	.695
CTCR3. When there is disagreement, I gather as much information as I can and keep the lines of communication open.	4.13	0.91	.657
CTCR4. I try to see conflicts from both sides.	4.16	0.83	.583
CTCR5. I am willing to work at creative solutions to problems.	4.07	0.90	.748
CTCR6. I am willing to listen and consider alternatives for handling a problem.	4.18	0.83	.646
CTCR7. I can find workable solutions to seemingly unsolvable problems.	4.05	0.91	.699

Note. Extraction method is principal component analysis.

Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) was conducted using structural equation modeling in LISREL 12.4 (Jöreskog & Sörbom, 2023). While comparative fit index (CFI) and normed fit index (NFI) over .95 indicate a good fit, standardized root mean squared residual (SRMR) that is smaller than .08 and root mean squared error of approximation (RMSEA) value of less than .06 indicates a good fit (Hu & Bentler, 1999). Figure 1 presents the resulting path diagram. All factors’ loadings were acceptable, ranging between .49 and .70. Chi-square was 11.51 with 14 degrees of freedom (p = .65), indicating that the tested single-factor model has a perfect fit. The chi-square to degrees of freedom ratio was 0.82, NFI was .967, CFI was 1.000, SRMR was .027, and RMSEA was 0.00, all supporting the conclusion that the model has a great fit and that the 7-item CTCR measure has a single-factor structure.

Internal Consistency

The 7-item CTCR had an acceptable reliability (α = .79). As expected, the item-to-total correlations were high (i.e., all above .40). In addition, item-to-total statistics revealed that the internal consistency of the scale would decrease if any of the retained items were deleted.

Convergent, Criterion-Related, and Discriminant Validities

Following Cohen (1988), correlations smaller than .1 were accepted as trivial, correlations between .1 and .3 were accepted as small, correlations between .3 and .5 were accepted as moderate, and correlations that are equal to or bigger than .5 were accepted as large. The CTCR scores had a large positive association with scores of the converging construct, collaborative style in conflict resolution (r = .86), supporting convergent validity. The CTCR scores also had a large, positive correlation with creativity scores (r = .84), supporting CTCR’s criterion-related validity. In addition, although the correlation between CTCR and power distance scores was not trivial as expected, it was still small (r = .22). Also, CTCR’s correlation with power distance was much smaller than its correlations with the converging and criterion-related constructs.

All in all, these findings provided support for CTCR’s single-factor structure, acceptable reliability, and convergent, discriminant, and criterion-related validities.

Study 1

The goal of the first study was twofold: (a) To further test the relationship between MCE and creative thinking in ideation (H1-2), using a different question and a different sample from previous research; (b) Examine our hypotheses that level of MCE would predict higher CTCR framework (H3) and closed-mindedness will play a mediating role (H5-8a).

Method

Sample and Procedures

Two hundred⁴ full-time managers (81% male) were recruited via Prolific panel for a 15-min personal experiences survey for which they were reimbursed $5 via their Prolific accounts. Participants’ mean age was 41.2 years (SD = 10.8, range: 24–70). Eighty-six percent were White, 4.5% were Asian, 4% were Black, 2% were Hispanic, and 4% were Other. They reported 12 different cultures as their dominant culture, including the United States (32.2%), United Kingdom (59.6%), Ireland (1.5%), Finland, India, Nepal, South Korea (1% each), Australia, Morocco, Nigeria, Romania, and Zimbabwe (0.5% each). The typical participant reported having a multicultural exposure about once a year (M = 2.32, SD = 0.92) and reported having a multicultural interaction about once a month (M = 3.30, SD = 1.23).

Measures

Multicultural Experience

MCE was measured via the psychometrically validated instrument Multicultural Experience Assessment (α = .87; Aytug, Kern, & Dilchert, 2018), that measures MEs and MIs separately. Multicultural exposure subscale (α = .86) had six exposure items (e.g., How frequently do you watch foreign TV channels? How frequently do you read books about foreign people?) and multicultural interaction subscale (α = .88) had four items (e.g., How frequently do you talk to people from different cultures? How frequently do you communicate via writing with people from different cultures?), using a 6-point Likert-type scale (1 = never, 2 = annually, 3 = monthly, 4 = weekly, 5 = daily, 6 = multiple times a day). Overall, the multicultural experience score is the average of interaction and exposure scores. Exposure and interaction items were presented in randomized blocks, in which items were also randomized.

Closed-Mindedness

Closed-mindedness was measured via eight randomized items of the closed-mindedness subscale of the Need for Closure Scale (Webster & Kruglanski, 1994), using a 5-point Likert-type scale where 1 = strongly disagree, 5 = strongly agree. Cronbach’s α was .63. Although this was lower than the desired .70 level, an alpha between .61 and .65 is considered acceptable for social sciences research (Taber, 2018), especially when the number of items is small (van Griethuijsen et al., 2015).

Creative Thinking in Idea Generation

Participants were given 2 min to list as many uses for a cardboard box as possible (Guilford’s Alternative Uses Test, 1967). The listed ideas were used to calculate three creative thinking measures: fluency (i.e., the total number of unduplicated ideas), flexibility (i.e., the number of different categories of ideas), and originality (i.e., the novelty level of the ideas). Two independent coders assessed the listed ideas for fluency and flexibility. Inter-coder agreement was 97%. Coders discussed and resolved all remaining disagreements.

To measure the originality of the ideas, we adopted a slightly revised version⁵ of the originality calculation used by Aytug, Rua, et al. (2018; adapted from James, 1995). First, the frequency of occurrence of each idea across the entire sample was counted. Then, each idea listed by the participant was divided by the total number of occurrences of that idea category in the whole sample. This provided an originality coefficient for each idea. Note that the less frequent an idea, the higher was its originality. Finally, for each participant, the originality coefficient for each of their ideas were summed up to determine the individual’s originality score.

Creative Thinking in Conflict Resolution (Intrapersonal Measure)

Participants were asked to rate their agreement with the seven items that were tested in the Pilot Study. Items were presented in a randomized order, and used a 5-point Likert-type scale, where 1 = strongly disagree, 3 = neither disagree nor agree, 5 = strongly agree. Cronbach’s α was .74.

Results

Table 3 presents means, standard deviations, and correlations of the measures⁶. Results revealed no gender differences in terms of creative thinking in idea generation or conflict resolution [t(198) = −1.295, p = .098 for flexibility; t(198) = −1.544, p = .062 for fluency; t(196) = −1.310, p = .096 for originality; t(198) = −0.142, p = .44]. The overall level of MCE was significantly correlated with fluency and originality, and the fluency scores were significantly correlated with multicultural interaction and exposure levels.

Table 3.

Means, Standard Deviations and Correlations Among Measures in Study 1 (N = 198).

Variables	M	SD	1	2	3	4	5	6	7	8	9
1. Multicultural experience^a	2.80	0.91	1
2. Multicultural exposure^a	2.32	0.92	.79**	1
3. Multicultural interaction^a	3.29	1.23	.89**	.41**	1
4. Creative thinking / Fluency	7.78	3.36	.20**	.16*	.18*	1
5. Creative thinking / Flexibility	5.29	1.70	.09	.06	.10	.78**	1
6. Creative thinking / Originality	0.06	0.03	.14*	.14	.11	.84**	.82**	1
7. Closed-mindedness	2.55	0.49	−.19**	−.07	−.23**	−.08	−.09	−.05	1
8. Creative conflict resolution	4.02	0.49	.18*	.06	.22**	.01	−.06	−.04	−.59**	1
9. Age	41.18	10.82	−.09	−.02	−.11	−.08	−.09	−.07	−.06	.08	.1

Multicultural experience score is computed using the interaction and exposure scores.

p < .01. *p < .05.

Table 4 presents the multiple regression analyses to examine the relationships of different MCE types with creative thinking in idea generation and conflict resolution. Age was not significantly correlated with any MCE or creative thinking measure or close mindedness; however, we controlled for age in the analyses due to previous research that revealed associations between aging and cognitive and creative outcomes (Gopnik et al., 2017; Ross et al., 2023).

Table 4.

Multiple Regression Analyses Examining the Relationships Among MCEs, Creative Thinking (in Idea Generation and Conflict Resolution), and Closed-Mindedness (Study 1).

Variables	Models 1–3DV: Fluency in ideation	Models 4–6DV: Flexibility in ideation	Model 7–9DV: Originality in ideation	Model 10–12DV: Creative thinking in conflict resolution	Model 13–15DV: Closed-mindedness
Constant	8.75 (0.94)**	5.87 (0.47)**	0.07 (0.01)**	3.89 (0.14)**	2.65 (0.14)**
Age	−0.24 (0.22)	−0.14 (0.11)	0.00 (0.00)	0.00 (0.01)	−0.00 (0.00)
Constant	6.55 (1.23)**	5.38 (0.63)**	0.05 (0.01)**	3.55 (0.18)**	3.00 (0.18)**
Age	−0.02 (0.22)	−0.13 (0.11)	0.00 (0.00)	0.01 (0.00)	−0.00 (0.00)
Multicultural exposure	0.37 (0.28)	0.04 (0.15)	0.00 (0.00)	−0.01 (0.04)	0.01 (0.04)
Multicultural interaction	0.35 (0.21)	0.10 (0.11)	0.00 (0.00)	0.09 (0.03)**	−0.10 (0.03)**
R ²	0.04	0.02	0.02	0.06	0.06
Constant	4.42 (2.01)	3.20 (1.02)**	0.03 (0.02)	3.09 (0.29)**	3.46 (0.29)**
Age	−0.20 (0.22)	−0.01 (0.11)	0.00 (0.00)	0.00 (0.01)	−0.00 (0.00)
Multicultural exposure	1.42 (0.84)	1.12 (0.42)**	0.02 (0.01)^†	0.21 (0.12)	−0.22 (0.12)
Multicultural interaction	0.92 (0.48) ^†	0.69 (0.24)**	0.01 (0.01)	0.22 (0.07)**	−0.22 (0.07)**
Exposure × Interaction	−0.27 (0.20)	−0.27 (0.10)**	−0.00 (0.00)	−0.06 (0.03) ^†	0.06 (0.03)*
Total R²	0.05	0.05	0.04	0.08	0.08
	Models 16–17DV: Fluency in ideation	Models 18–19DV: Flexibility in ideation	Model 20–21DV: Originality in ideation	Model 22–23DV: Creative thinking in conflict resolution
Constant	8.75 (0.94)**	5.87 (0.47)	0.07 (0.01)**	3.89 (0.14)**
Age	−0.02 (0.02)	−0.01 (0.01)	0.00 (0.00)	0.00 (0.00)
Constant	10.41 (1.60)**	6.81 (0.81)**	0.08 (0.02)**	5.45 (0.20)**
Age	−0.03 (0.02)	−0.02 (0.01)	0.00 (0.00)	0.00 (0.00)
Closed-mindedness	−0.63 (0.49)	−0.35 (0.25)	−0.00 (0.01)	−0.59 (0.06)**
Total R²	0.01	0.02	0.01	0.35

Note. Table presents unstandardized regression coefficients with standard errors in parentheses. Statistically significant models are bolded.

p < .01. ^†p = .050 to .055.

Models 1–9 tested the associations between MCE types and creative thinking scores in idea generation. Model 3 (R² = 0.04, p = .04) results showed that MIs (B = 0.92, p = .055) were marginally significant predictors of the number of ideas developed, whereas MEs (B = 1.42, p = .91) and interaction of MIs and MEs (B = −0.27, p = .18) were not. Thus, the main effect of the MIs was not qualified by the interaction effect. Model 6 (R² = 0.04, p = .04) showed that MIs (B = 0.69, p < .01), MEs (B = 1.12, p < .01) and the interaction of MEs and MIs (B = −0.27, p < .01) were all significant predictors of the flexibility scores. Model 9 (R² = 0.04, p = .13) was not significant, thus replicating previous research findings (see Aytug, Rua, et al., 2018) that MIs (B = 0.01, p = .09) and MEs (B = 0.02, p = .055) are not significant predictors of the originality of the ideas developed. These findings supported H1a, H1b, H2a, and H2c, but not H2b and H1c, leading us to continue the examination for H7 (regarding mediation in MI—creative thinking in idea generation relationship) with fluency and flexibility measures only.

Models 10–12 tested the associations between MCE types and creativity approach in conflict resolution context. Model 12 (R² = 0.08, p < .01) results showed that MIs (B = 0.22, p < .01) were significant predictors of creativity approach in conflict resolution, while MEs (B = 0.21, p = .08) were not. In addition, the interaction of MIs and MEs (B = −0.06, p = .50) were marginally significant, showing an interaction effect on CTCR. These results support H3a regarding the effect of MIs on CTCR, thus leading us to continue our examination of the mediation model in H8a.

Models 13–15 tested the associations between MCE types and closed-mindedness. Model 15 (R² = 0.08, p < .01) showed that MIs (B = −0.22, p < .01) and the interaction of MEs and MIs (B = −0.22, p < .05) were significant predictors of closed-mindedness, while MEs were not (B = −0.22, p = .07), substantiating H4a but not H4b, once again encouraging us to retain H7 and H8a (regarding interactions).

The observed R² figures in the significant models reveal that MCEs and their interactions can explain about 5% of the variance in creative thinking in ideation (i.e., fluency and flexibility) and 8% of the variance in CTCR. These are significant, but unsurprisingly small effect sizes, given the variety of factors that impact creative thinking (such as personality differences, emotional intelligence, creative self-efficacy, environmental and life experiences, and biological factors; c.f. Grajzel et al., 2023; Richardson et al., 2022; Richter et al., 2012; Sundquist & Lubart, 2022; Zaidel, 2014).

Models 16–21 tested the predictive role of closed-mindedness for creative thinking in idea generation. Results revealed that closed-mindedness was not a significant predictor of any of the measures of creative thinking in ideation, thus H5 is not supported, also eliminating H7.

Models 22–23 tested the predictive role of closed-mindedness for CTCR. Model 23 (R² = 0.35, p < .01) revealed that closed-mindedness (B = −0.59; p < .01) is a significant predictor of creative thinking in conflict, explaining 35% of the variance in this variable. These findings support H6, and thus we could test the remaining mediation hypothesis, H8a.

We tested the mediating role of closed mindedness in the association of MI and creative approach to conflict resolution (H8a) using PROCESS macro of SPSS (Hayes, 2022). Table 5 shows the unstandardized regression coefficients (B) with Standard Errors (SE) and confidence intervals (in parentheses). As was in model 12, MIs emerged as significant predictors of CTCR (H3a). However, when MI and closed-mindedness were added together in the model, the effect of MI lost its significance whereas the closed-mindedness—creative thinking association was significant (see Table 5 and Figure 2). The bias-corrected bootstrap 95% confidence interval (CI) indicated that the indirect effect through closed mindedness was significant for creative approaches to conflict resolution (B = −0.57; SE = .06; 95% CI = [−0.68, −0.45]). The Sobel Test provided further support for the mediation effect of closed-mindedness (Z = 3.06, SE = 0.02, p < .01). These results indicate that closed mindedness is a mediator between MI and CTCR, supporting H8a. Overall we found that MCEs explained 6% of the variance in closed-mindedness (p < .01), and that MCEs and closed-mindedness, together, explained 36% of the variance in creative thinking in conflict (p = .00).

Table 5.

Regression Analyses Examining the Mediating Role of Closed-Mindedness in Multicultural Interaction—Creative Thinking in conflict Resolution (H4c; Study 1).

	DV: Closed-mindedness (mediator)			DV: Creative thinking in conflict (Y)
Variables	B	SE	95% CI	B	SE	95% CI
Constant	3.00	0.18	[2.65, 3.35]	5.24	0.23	[4.78, 5.70]
Age	−0.01	0.01	[−0.01, 0.02]	0.00	0.00	[−0.00, 0.01]
Multicultural exposure	0.01	0.04	[−0.07, 0.09]	−0.01	0.03	[−0.08, 0.06]
Multicultural interaction	−0.98	0.03	[−0.16, −0.04]	0.04	0.03	[−0.01, 0.09]
Closed-mindedness	−0.57	0.06	[−0.68, −0.45]
R ²	0.06**			0.36**

Note. Creative thinking in conflict = Creative thinking in conflict resolution.

Effects are significant when the bias corrected 95% confidence interval (CI) does not contain zero (in bold).

p < .01.

To summarize, Study 1 results showed that (a) MIs positively predicted fluency and flexibility scores (supporting H1a-b), and MEs had a significant effect on the flexibility scores (disputing H2b), (b) MIs positively predicted CTCR (supporting H3a), and (c) closed-mindedness fully mediated the relationship between MIs and creative approach to conflict resolution (supporting H4a, H6, and H8a).

Study 2

Study 1 was survey research, focusing on intrapersonal outcomes. The goal of Study 2 was to test the hypotheses regarding creative thinking in a realistic conflict resolution context (H3b, H4a-b, H6, and H8b) using a conflict resolution simulation.

Method

Sample and Procedures

One hundred full-time managers were recruited via the Prolific panel for a 30-min online study, for which they were reimbursed $5 via their Prolific accounts. Five individuals did not complete the study, resulting in a sample size of 95 individuals (49.5% female) with a mean age of 41.4 (SD = 12.6, range: 21–74). Seventy-five percent were White, 14.7% were Asian, 7.4% were Black, 1.1% were Hispanic, and 2.1% were Other. They reported 16 different cultures as their dominant culture, including United Kingdom (66.3%), United States (9.5%), Ireland (5.3%), Nigeria (4.2%), Pakistan, Philippines (2.1%), Bangladesh, China, Hungary, India, Italy, Lithuania, Poland, South Africa, Spain and Sri Lanka (1.1%). The typical participant reported having a multicultural exposure about once a month (M = 2.92, SD = 1.19) and reported having a multicultural interaction about once a week (M = 3.99, SD = 1.39).

After taking a 5-min Qualtrics survey, participants were directed to an online platform, iDecisionGames, where they accessed role materials describing a conflict situation necessitating a negotiation with another party. Participants played the role of the President of a Latin American company Rio Copa and had to negotiate via instant messaging with the Vice President of Business Development of a larger international corporation that wants to acquire Rio Copa. This opponent was played by ChatGPT. At the heart of the conflict were four unresolved issues that had to be discussed: Financing terms, non-compete period, number of family employees retained, and the contingent liability for the workers’ health. Once the discussion was over, participants were redirected to Prolific for compensation.

Measures

Multicultural Experience

MCE (α = .92), multicultural interaction (α = .92) and exposure (α = .91) were measured the same way as in Study 1.

Closed-Mindedness

Closed-mindedness (α = .70) was measured the same way as in Study 1.

Creative Conflict Resolution

The design of the conflict resolution exercise allowed trade-offs based on differential priorities for the parties, if only they could exhibit creative, problem-solving approaches and manage to identify underlying interests and make corresponding trade-offs. Thus the more creative they were, the higher their joint outcome would be. Given the participants negotiated with AI, their creative thinking in this conflict situation would result in an outcome with a higher integrative potential (i.e., achieving a higher percentage of the highest joint outcome possible). Thus, the integrative potential of the reported outcome was used as a measure of individual’s creative thinking in this conflict resolution scenario as the AI was not to come up with its own creative offers, but only respond to the level of creativity by the respondent, controlling for the other party’s creativity level for each interaction.

Based on the exercise pay-off schedules for both parties, the most integrative deal possible could bring 7,500 points to the parties in conflict. The creative potential of the deal was calculated by dividing the obtained points by 7,500, resulting in a percentage. The higher the percentage, the more creative the solution was.

Results

Table 6 presents means, standard deviations, and correlations of the measures. Results revealed no gender differences in creative potential of the deal [t(93) = −0.73, p = .24].

Table 6.

Means, Standard Deviations and Correlations Among Measures in Study 2 (N = 95).

Variables	M	SD	1	2	3	4	5	6
1. Multicultural experience^a	3.46	0.13	1
2. Multicultural exposure^a	2.92	1.19	.86**	1
3. Multicultural interaction^a	3.99	1.39	.90**	.55**	1
4. Integrative potential	0.77	0.10	.16	.28*	.02	1
5. Closed-mindedness	2.49	0.54	−.30**	−.33**	−.21*	−.32**	1
6. Age	41.38	12.59	−.43**	−.35**	−.40**	−.05	−.22*	1

Multicultural experience score is computed using the interaction and exposure scores.

p < .01. *p < .05.

The overall MCE level was not significantly correlated with the creative potential of the deals. When MCE was broken down into MEs and MIs, only ME was found to be significantly and positively correlated with the creative potential. Closed-mindedness was negatively and significantly correlated with each of the MCE, MI and ME measures. Age was found to be significantly and negatively correlated with the overall MCE, MEs and MIs, closed-mindedness, and the creative potential; thus, we controlled for age in all analyses.

Table 7 presents the multiple regression analyses testing the relationships of different MCE types with closed-mindedness and creative potential of the deals (H3b). Model 2 results showed that MEs (B = 0.03, p < .01), but not MIs (B = −0.01, p = .14), had a main effect on the creative potential, supporting H3b. Moreover, Model 5 results revealed that MEs (B = −0.13, p = .02), but not MIs (B = −0.00, p = .97) were significant predictors of the level of closed-mindedness, supporting H4b but not H4a. Overall MCEs explained 12% of the variance in creative potential of the deals (p < .01) and 12% of the variance in closed-mindedness (p < .05). These findings provided evidence for H3b and H4b regarding MEs.

Table 7.

Multiple Regression Analyses Examining the Relationships Among MCE Types, Creative Potential of the Conflict Resolution Outcome, and Closed-Mindedness (Study 2).

Variables	Models 1–3DV: Creative potential	Models 4–6DV: Closed-mindedness
Constant	0.79 (0.36)**	2.11 (0.19)**
Age	0.00 (0.00)	0.01 (0.00)*
Constant	0.73 (0.06)**	2.69 (0.32)**
Age	0.00 (0.00)	0.01 (0.01)
Multicultural exposure	0.03 (0.01)**	−0.13 (0.05)*
Multicultural interaction	−0.01 (0.01)	−0.00 (0.05)
R ²	0.10	0.12
Constant	0.79 (1.00)	2.69 (0.52)**
Age	−0.00 (0.00)	0.01 (0.01)
Multicultural exposure	0.01 (0.03)	−0.13 (0.17)
Multicultural interaction	−0.03 (0.02)	−0.00 (0.10)
Exposure × Interaction	0.00 (0.01)	0.00 (0.04)
Total R²	0.11	0.12
Variables	Models 7–8DV: Creative potential
Constant	0.73 (0.06)**
Age	0.00 (0.00)
Multicultural exposure	0.03 (0.01)**
Multicultural interaction	−0.01 (0.01)
Constant	0.86 (0.08)**
Age	0.00 (0.00)
Multicultural exposure	0.03 (0.01)*
Multicultural interaction	−0.01 (0.01)
Closed-mindedness	−0.05 (0.02)*
Total R²	0.16

Note. Table presents unstandardized regression coefficients with standard errors in parentheses. Statistically significant models are bolded.

p < .01. *p < .05.

Models 7–8 were conducted to test the main effect of closed-mindedness on the creative potential of the deals (H6), controlling for age, ME and MI. Model 8 results showed that closed-mindedness (B = −0.05, p = .01) was a significant predictor of the creative potential of the deal, and that one’s level of closed-mindedness explained 16% of the creative potential of their deal (p < .01). These findings support H6.

We continued to test the mediating role of closed-mindedness in exposures-creative potential relationship (H8b). The mediation analyses conducted via PROCESS macro of SPSS (Hayes, 2022) are presented in Table 8.

Table 8.

Mediation Analyses Examining the Role of Closed-Mindedness in the Association Between MCE and Creative Potential of the Conflict Resolution Outcome (Study 2).

	DV: Closed-mindedness (mediator)			DV: Creative potential (Y)
Variables	B	SE	95% CI	B	SE	95% CI
Constant	2.68	0.32	[2.05, 3.32]	0.86	0.08	[0.71, 1.02]
Age	0.01	0.04	[−0.10, 0.10]	0.00	0.00	[−0.00, 0.00]
Multicultural exposure	− 0.13	0.05	[−0.24, 0.02]	0.03	0.01	[0.01, 0.05]
Multicultural interaction	−0.00	0.05	[−0.10, 0.10]	−0.01	0.01	[−0.03, 0.00]
Closed-mindedness	−0.05	0.02	[−0.09, −0.01]
R ²	0.12**			0.16**

Note. Creative conflict res. Style = Creative conflict resolution style.

Effects are significant when the bias corrected 95% confidence interval (CI) does not contain zero (in bold).

p < .01.

Mediation analyses showed that when ME and closed-mindedness were regressed together on the creative potential of the deal, the effects of both closed-mindedness and ME were significant (see Figure 3). The bias-corrected bootstrap 95% CI indicated that both the direct effect of ME (B = 0.03; SE = 0.01; 95% CI = [0.01, 0.05]) and the indirect effect through closed mindedness (B = −0.05; SE = 0.02; 95% CI = [−0.09, −0.01]) were significant for creative potential of the deal. These findings showed that closed-mindedness partially mediated the relationship between MEs and creative potential, providing partial support for H8b. The Sobel Test provided further evidence of a partial mediation effect of closed-mindedness (Z = 1.80, SE = 0.003, p = .07). Overall MCEs explained 12% of the variance in closed-mindedness (p < .01), and that MCEs and closed-mindedness together explained 16% of the variance in creative potential of the deals (p < .01).

To summarize, Study 2 results showed that (a) MEs are positively associated with creative potential of deals (H3b), (b) MEs negatively predicted closed-mindedness (H4b) whereas closed mindedness negatively predicted the creative potential of the deal (H6), and (c) closed-mindedness partially mediated the relationship between MEs and CTCR (partial support for H8b).

Discussion

Implications for Research

Following up on the previous research on the multidimensionality of MCEs (Aytug, Kern, & Dilchert, 2018, Aytug, Rua, et al., 2018), the current research investigated how ME and MI have respective impacts on creative thinking within the paradigms of idea generation and conflict resolution. The results from Study 1 underscore the differential dynamics at play regarding intrapersonal creative idea generation outcomes, with MIs being associated with fluency and flexibility, whereas MEs being associated with flexibility only.

Combining the creative cognition approach with sociocultural theory and structural model of MCE, we argued that MEs and MIs both have functional contributions to an individual’s creativity; however, the specific mechanisms via which ME and MI relate to creativity skills and outcomes will differ. Results showed that MIs (but not MEs) were positively associated with self-reported (intrapersonal) creativity approach to conflicts, whereas MEs (but not MIs) were positively associated with creative thinking in realistic conflict resolution contexts, providing the first empirical evidence for Maddux et al.’s (2021) theorizing regarding deeper and broader level MCEs and their specific impact on creativity. Such nuanced delineations pave the way for a deeper understanding of the numerous ways in which MCEs shape cognitive and behavioral responses, enriching our understanding of cross-cultural dynamics in organizational contexts.

Our findings contribute to the literature by providing further support that MEs and MIs are distinct components that have differential relationships with cognitive and interpersonal proclivities and outcome variables. In addition, this is the first research that examined specific levels of individual MIs and MEs with respect to their associations with CTCR. To test the structural model of MCE, we measured creativity in conflict via both intrapersonal and interpersonal methods, resulting in the identification of their differential connections with MIs and MEs. Our findings supported the structural model of MCE by signaling that deeper (MIs) MCEs relate to intrapersonal outcomes, whereas broader (MEs) MCEs relate to interpersonal outcomes, although much future research is necessary.

Furthermore, we studied the mediating role of closed-mindedness within three relationships: MI—creative thinking in idea generation, MI—creative approach to conflict, and ME—creativity of conflict resolution outcomes. Results showed that one’s level of closed-mindedness did not predict creative thinking in idea generation, but fully mediated the relationship between MI and an individual’s creative approach to and intentions about conflicts. In addition, closed-mindedness partially mediated ME—creativity level of negotiation outcomes. More research is needed to further examine this relationship.

Practical Implications

This research presents practical implications for both higher education institutions as well as organizations and organizational players. Universities have started focusing on creativity and innovation in recent years, specifically due to higher education institutions having to take on a more entrepreneurial role with the economic, cultural and other macro-environmental challenges as well as global conflicts that are felt across the world (Gaspar & Mabic, 2015). This focus led to initiatives such as the “Creativity in Higher Education Project,” which was created by the European University Association to identify and provide higher education institutions with best practices and operational recommendations to foster creativity (European University Association, 2007). With research pointing to its effectiveness in improving creativity and innovation (Guaman-Quintanilla et al., 2023; Pratomo & Wardani, 2021; Won et al., 2019), design thinking is one of the strategies adopted by higher education in their pursuit of helping students become more creative. The findings from the current research point to the potential of leveraging study abroad programs, in addition to design thinking training, in helping with the mission of enhancing creating among college students. Currently, study abroad programs have shown positive relationships with students’ cognition in areas such as global mindedness and intercultural interest, knowledge, awareness; affective implications regarding intercultural sensitivity as well as behavioral implications for cross-cultural and adaptability and intercultural communication (Goldstein, 2022). Given the impact of MIs on intrapersonal creativity both in idea generation and conflict management, there might be additional benefits to encouraging students to attend short-term or long-term study abroad programs. Furthermore, universities might want to reassess the course selections they offer and provide more courses about other cultures in different fields such as visual arts, music, literature, and so on given the positive impact MEs have on interpersonal creativity in conflict situations.

Companies, similar to higher education institutions, are feeling the need for creative employees and teams more than ever (Mumford et al., 2012) due to a global business landscape, constant technological shifts, fierce competition, and frequent restructuring, yet, despite understanding its value, fostering creativity remains to be a challenge for most organizations (Agars et al., 2012; Sirková et al., 2014). As a result, similar to universities, organizations have also been keen on developing their employees’ creativity. In fact, reports from Eurostat (2013) evaluating data from 23 European countries suggest creativity training to be perceived as one of the top three methods for improving creativity with 56.8% of organizations across 19 countries utilizing innovation related training (Birdi, 2016; McKay et al., 2024; Organization for Economic Co-operation and Development [OECD], 2010). The majority of these programs focus on teaching the different stages in the creative process as well as introducing divergent thinking strategies (McKay et al., 2024) whereas cross-cultural training is mostly reserved for expatriates to increase cultural awareness with the intent to help them adjust to living and working in different cultures (Forster, 2000). Given the importance of MEs in creativity in interpersonal conflict management, it might be beneficial for organizations to consider extending these cross-cultural training to the remainder of their employees. Since these training programs are already mostly developed, this might also mean a relatively low-cost solution for a high priority topic for many organizations.

Furthermore, organizations could benefit immensely from understanding the differential impacts of MEs and MIs on creativity. To date, three perspectives in creativity regarding conflict management have been identified: Person, process, and product (Carnevale, 2006). While the person perspective involves basic human cognitions, the process perspective pertains to the underlying factors that elicit processes of problem construal and problem solving (Carnevale, 2006), which can both be coined as intrapersonal level. Product perspective, on the other hand, is a result of social conflict with creativity in this sphere showing itself in the forms of compromise, log rolling, modifying the resource pie, expanding the resource pie, bridging the interests, cutting the costs, compensation, superordination (Carnevale, 2006), which are all interpersonal acts. Given the results of the current research, as organizational players strive to improve in the three perspectives of creativity regarding conflict management, they might want to consider adding MIs and MEs into their regimen to show promise in all three areas. In addition, by fostering a culture of inclusivity and facilitating meaningful cross-cultural interactions, organizations can nurture a diverse workforce primed for innovative problem-solving and adaptive conflict resolution.

Limitations and Future Directions

Similar to previous findings, we found no association between levels of ME/MI and originality of ideas generated (although we used a different task and a somewhat different conceptualization of originality). However, while previous research reported that MEs had no significant association with flexibility measure, we found that individual level of ME predicted flexibility. Further research is needed to illuminate MCE—originality and flexibility connections.

This research utilized the Structure component of Maddux et al.’s (2021) new framework of Structure-Appraisal Model of MCEs and focused on the effects of structural differences of MCEs. However, another interesting part of this framework is the Appraisal component that focuses on the positive versus negative appraisal of MCEs as a determinant of the effects of MCEs. Authors suggest that positive versus negative appraisal may determine, regardless of whether the experience qualifies as an ME or MI, if the experience will result in any individual or interpersonal impact, and that structure and appraisal may even have interactive effects. For example, while investigating the effects of negative MCEs on intergroup bias, Affinito et al. (2023) conducted supplementary analyses, where they coded participants’ negative experiences as interactions or exposures. Authors reported that negative MIs had a stronger effect on intergroup bias than negative MEs. Thus, future research is needed to study structural and appraisal aspects of MCEs together with regards to creativity and examine their potential interactive effects on intrapersonal and interpersonal outcomes of creative thinking.

Although in this research we preferred to use a psychometrically validated instrument (i.e., MExA) as our main MCE measure, Affinito et al.’s (2023) methodology (i.e., collecting participants’ write-ups about their MCEs) and operationalization (i.e., coding texts as MI or ME) can be another way of measuring MIs and MEs. Future creativity research that uses different ME and MI measures will be very beneficial in observing whether our results are robust using different MCE operationalizations. In Study 1, our sample is quite male-dominant. Although we tried to strike a balance with the Study 2 sample (which included equal percentages of males and females), Study 1 results should be examined with male dominated sample in mind. In addition, in a realistic conflict resolution context, further examination of transcripts of negotiation communication between the parties could be helpful in studying the relationship between different types of MCEs and the specific negotiation tactics that increased the creativity of the deals. Future research is necessary to illuminate the underlying negotiation behaviors, tactics, and dialogue related to MCE.

In this research we presented that some types of MCEs are positively associated with creative thinking. However, due to using correlational design instead of experiments, we cannot make inferences about the direction of causality. Future investigators are encouraged to conduct pre-registered experiments to rule out potential reverse-causality explanations, such as “creative thinking” or “low level of closed-mindedness” causing individuals to seek out certain types of MCEs (vs. vice versa). Such experimental design can also help better align the findings with other MCE research that utilized experiments. For example, in an experiment, participants may be asked to recall their MEs versus MIs, followed by a measurement of close-mindedness and/or creativity (similar to paradigms by Affinito et al., 2023; Lu et al., 2017; Maddux & Galinsky, 2009).

The 8-item closed-mindedness scale used in this research had Cronbach’s alpha of .63 and .70 in Studies 1 and 2. Although an alpha between .61 and .65 is considered acceptable for social sciences research (especially when the number of items is small), our findings should be interpreted within this context. Future researchers are encouraged to utilize different measures of closed-mindedness to test its associations further. Finally, more empirical research is needed to further illuminate the intricacies of MEs and MIs, as each interaction also involves a level of exposure.

Conclusion

In conclusion, the presented research contributes to our understanding of the MCE-creativity relationship in conflict resolution, paying specific attention to the two types of MCEs (MEs and MIs) and with a focus on the impact of each dimension on individuals’ creativity at an intrapersonal and interpersonal level. The findings from this research have significant cognitive and practical implications for higher education and students as well as businesses and their employees that operate in a world without borders.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Zeynep G. Aytug

Notes

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