SOAR as a Mediator of the Relationship Between Emotional Intelligence and Collaboration Among Professionals Working in Teams: Implications for Entrepreneurial Teams

Abstract

A majority of ventures are started by entrepreneurial teams rather than individuals. More than half of team-based new venture failures are believed to be due to problems with the entrepreneurial team. Collaboration among entrepreneurial team members is important for increasing the likelihood of successful venture outcomes. We investigated collaboration in professionals working in teams using survey methodology. Results found a framework for collaborative dialogue, SOAR (strengths, opportunities, aspirations, and results), mediates the relationship between emotional intelligence and team collaboration. We discuss practical recommendations to increase the strength of the relationship between emotional intelligence and collaboration to increase entrepreneurial team performance. For example, behavioral coaches are recommended to use dialogical exercises to help team members develop emotional intelligence competencies of awareness and regulation of emtions in self and others. Entrepreneurs are recommended to create teams that build on member strengths and aspirations, and identify opportunities for achieving measurable positive results.

Keywords

emotional intelligence collaboration SOAR entrepreneurial teams context mediation analysis

An entrepreneurial team is a team consisting of two or more individuals who hold shares in a firm, and who work actively on the strategic direction and decision making in the venture during the early developmental phase of the venture (Khan, Breitenecker, & Schwarz, 2014, 2015). A majority of ventures are started by entrepreneurial teams rather than individual entrepreneurs (Schjoedt, Monsen, Pearson, Barnett, & Chrisman, 2013; West, 2007). Of the roughly 40% of new ventures that fail within the first year, more than half of the failures are believed to be due to problems with the entrepreneurial team (Eisenhardt, 2013; Kaplan & Strömberg, 2004). Research suggests the way in which entrepreneurial team members collaborate with each other is important for determining successful venture outcomes (Chowdhury, 2005; Gundry, Ofstein, & Monllor, 2016; Mol, Khapova, & Elfring, 2015). This article examines how a framework for collaborative dialogue, SOAR (strengths, opportunities, aspirations, and results), mediates the relationship between emotional intelligence and team collaboration in a quantitative empirical study in a sample of U.S. professionals working in teams. Results of our research have important implications for increasing collaboration among entrepreneurial team members through emotional intelligence and open dialogue leading to successful entrepreneurial outcomes.

A team approach is considered beneficial for meeting such entrepreneurial objectives as creativity, innovation, and new product development because of knowledge sharing and collaboration between team members (Dayaram & Fung, 2012; Gundry et al., 2016; Jassawalla & Sashittal, 1998; McDonough, Kahnb, & Barczaka, 2001; Zhang, Venkatesh, & Brown, 2011). Collaboration involves people working together toward a common goal (Slater, 2005). In teams, collaboration among team members is a critical factor in leveraging effectiveness of entrepreneurial teams (DeCusatis, 2008; Romero, Galeano, & Molina, 2008, 2009). For example, collaboration has been shown to predict innovation and entrepreneurial mind-set in entrepreneurs working together on common projects (Hoang & Antoncic, 2003) and in social entrepreneurs working together on new social ventures (Sharir & Lerner, 2006).

Research on collaboration in teams identifies social interactions among team members as a primary characteristic of effective teams (Hattori & Lapidus, 2004). Social interactions are enhanced through emotional intelligence (Kerr, Garvion, Heaton, & Boyle, 2006). Emotional intelligence is defined as a set of emotion-processing competencies involving awareness and management of emotions in self and others (Mayer & Salovey, 1997). Emotional intelligence in teams involves team members recognizing, regulating, and managing emotions in themselves and in others (Mayer, Salovey, & Caruso, 2004). Research highlights the positive effect of emotional intelligence (Druskat & Wolff, 2001; Goleman, 2006; Jordan & Ashkanasy, 2006; Mount, 2006; Sala, 2006) and collaboration (Dietrich, Eskerod, Dalcher, & Sandhawalia, 2010; Hattori & Lapidus, 2004; Romero et al., 2008, 2009; Whitaker, 2009) on team effectiveness.

One aspect of collaboration reviewed in the literature as important for increasing team effectiveness is the use of collaborative strategies that draw upon the capacity of team members for collaborative dialogue through shared strengths of team members and the dynamic opportunities available to the team (Bushe, 2013). A framework for collaborative dialogue that supports collaboration among team members through shared understanding and a commitment to action is SOAR (Stavros, Cooperrider, & Kelley, 2007). SOAR involves a strengths-based and opportunity-focused inquiry on the aspirations and desired results for the team (Stavros & Cole, 2013). In support of research on the positive effects of open communication and collaboration on innovation in entrepreneurial teams (Khan, Breitenecker, Gustafsson, & Schwarz, 2015), we consider SOAR as a framework for creating a reservoir of positivity to frame issues from a solution-oriented perspective that generates collaborative dialogue focused on new ideas, innovations, and the best in people and teams to emerge (Bushe, 2007, 2013; Cooperrider, Whitney, & Stavros, 2008; Goleman, Boyatzis, & McKee, 2009; Stavros & Cole, 2013; Stavros & Wooten, 2012).

The purpose of this article is to advance research on the role of collaboration in teams. To this end, we investigate emotional intelligence as a positive predictor of collaboration in U.S. professionals who have work team experience. Next, we investigate SOAR as a mediator of the positive impact that self-perceptions of emotional intelligence have on self-perceptions of team member collaboration. As a mediator, SOAR helps explain how or why emotional intelligence influences collaboration. With mediation analysis, we can gain insight about the mechanism of action of predictors of collaboration (Gunzler, Chen, Wu, & Zhang, 2013). We believe SOAR provides a dynamic framework for dialogue to optimize the positive effects of team member emotional intelligence on collaboration. We believe this research is important for increasing the effectiveness of entrepreneurial teams through emotional intelligence, SOAR, and collaboration.

Conceptual Framework and Hypotheses

Emotional Intelligence and Team-Based Collaboration

Today’s business climate is characterized by increased use of work teams for entrepreneurial objectives, such as innovation and new product development (Dayaram & Fung, 2012; Gudry et al., 2014; Jassawalla & Sashittal, 1998; McDonough et al., 2001; Zhang et al., 2011). Emotional intelligence adds value to team-based performance in terms of negotiating and resolving conflict (Anand & Udayasuriyan, 2010; Blattner & Bacigalupo, 2007; Jordan & Troth, 2004). Research suggests entrepreneurs’ emotional intelligence has a positive impact on the growth of new ventures, especially among team members who are collaborating (Kerr et al., 2006; Yitshaki, 2012).

Collaboration in teams involves social interaction among team members in terms of integration, compromise, and open communication (Aram & Morgan, 1976; Rahim, 1983a, 1983b; Romero et al., 2008, 2009). Integration and compromise involve the development and integration of positive behaviors to support collaborative strategies that enhance team capabilities (Rahim, 1983a, 1983b; Romero et al., 2008, 2009). Team capabilities are also enhanced through communication among team members and resource sharing to reach team goals (Aram & Morgan, 1976).

Collaboration and emotional intelligence are linked through inclusion of differing points of view among team members (Shaw & Lindsay, 2008). Inclusion in teams draws upon team members’ capacity for collaboration and an ongoing commitment to the development of collaborative strategies within a team (Shaw & Lindsay, 2008). Within a work team, such as an entrepreneurial team, members who have high emotional intelligence are aware of the emotional climate in the team. This leads to open and inclusive discussions on shared goals (Mita & Debasis, 2008; Romero et al., 2009). Collaboration and emotional intelligence are especially important in entrepreneurial teams because they help team members to dispel the status quo in favor of innovations. To this end, we expect that there is a significant positive relationship between team member’s self-perception of emotional intelligence and team member’s self-perception of collaboration.

Hypothesis 1: Emotional intelligence has a positive impact on collaboration among team members.

The SOAR Framework and Collaborative Dialogue

SOAR is a “strengths-based framework with a participatory approach to strategic analysis, strategy development, and organizational change” (Stavros & Saint, 2010, p. 380). As shown in Figure 1, the SOAR framework emphasizes strengths, opportunities, aspirations, and results. The SOAR framework is inherently team oriented, collaborative, and inclusive, and seeks to involve all team members in a collaborative dialogue (Stavros & Cole, 2015). SOAR increases collaborative dialogue through generative, solution-oriented communication among team members to frame issues in terms of strengths, opportunities, aspirations, and desired results to build a positive future (Stavros et al., 2007; Stavros & Wooten, 2012).

Figure 1.

The SOAR framework.

SOAR begins with an inquiry into what works well, followed by the identification of possible opportunities for growth. SOAR helps team members identify strengths, build on what is working well, and discuss team goals, strategic initiatives, and enabling objectives. SOAR also enables team leaders to plan strategies and methods to meet team objectives, define team outcome metrics aligned with team goals and objectives, and discover innovative team opportunities. SOAR has the potential to promote team members’ freedom to imagine an innovative, creative, and collaborative future in which a strengths-based strategy or strategic plan is implemented that is dynamic and enabling of positive outcomes. SOAR is a framework for collaborative dialogue and strengths-based information exchange that encourages all team members to collaborate on a desired future. Table 1 aligns the SOAR framework with specific activities that act as enablers for successful collaboration among team members (Stavros, Cooperrider, & Kelley, 2003).

Table 1.

Strategic Inquiry–Appreciative Intent: Inspiration to SOAR.

Planning processes	SOAR elements	SOAR activities
Strategic inquiry	Strengths	What are we doing well? What are our greatest assets?
Strategic inquiry	Opportunities	What are the best possible market opportunities? How do we best partner with others?
Appreciative intent	Aspirations	To what do we aspire? What is our preferred future?
	Results	What are the measurable results?What do we want to be known for?

Note. SOAR = strengths, opportunities, aspirations, and results.

Emotional intelligence competencies are closely linked to SOAR, insofar as emotionally intelligent team members are inclusive with collaborative dialogue and strengths-based information exchange. To help understand the role of SOAR in helping to explain how emotional intelligence has a positive impact on collaboration in team member, we tested SOAR as a mediator of the relationship between emotional intelligence and collaboration (Gunzler et al., 2013). Testing for mediated effects involves testing for the significance of indirect effects between the independent variables (IVs) and dependent variables (DVs; MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002), and to this end, we expect that there will be a significant indirect effect of SOAR on the relationship between emotional intelligence and collaboration.

Hypothesis 2: SOAR mediates the relationship between team member’s self-perceptions of emotional intelligence and team member’s self-perceptions of collaboration.

Method

Research Design

We used a quantitative cross-sectional design with mediating variables to evaluate SOAR as mediator of the relationship between emotional intelligence and collaboration in a sample of professionals who reported working in teams. To test the positive impact of emotional intelligence on collaboration (Hypothesis 1), we regressed collaboration on emotional intelligence. To test the mediational effect of SOAR on the relationship between emotional intelligence and collaboration (Hypothesis 2), we tested the indirect effect of SOAR on the relationship between emotional intelligence and collaboration using a mediation path model (Preacher & Hayes, 2008). We invited LinkedIn Group members with self-reported team experience to participate in an electronic survey that measured demographic characteristics, emotional intelligence, collaboration, and SOAR.

Research Variables

This study investigated three study variables: emotional intelligence, collaboration, and SOAR. Emotional intelligence is operationally defined as team member self-perceptions of awareness and management of emotions in self and others (Mayer & Salovey, 1997), and collaboration is operationally defined as team member self-perceptions that integration, compromise, and communication occur in the team (Aram & Morgan, 1976; Rahim, 1983a, 1983b). SOAR is operationally defined as team member self-perceptions of strengths, opportunities, aspirations, and results (Cole & Stavros, 2013, 2014; Stavros & Cole, 2013; Stavros et al., 2007). Figure 2 presents the study model in which emotional intelligence is an IV that affects the DV, collaboration, and SOAR is a mediator (MED) of the relationship between emotional intelligence and collaboration.

Figure 2.

Study model: SOAR as a mediator of the relationship between emotional intelligence and team-based collaboration as a function of team role (leaders vs. members).

Study Sample

The study sample was obtained by distributing invitations to participate across a wide range of U.S. professionals who work in teams in industry, academia, and government via LinkedIn groups in the following study areas: emotional intelligence, leadership, appreciative inquiry, team work and team effectiveness, strategic planning, change management, project management, academia, financial management, general business management, and several industrial organizations. Individuals who voluntarily consented to participate in the study served as the unit of analysis for the study. The survey was administered over a 4-week period via the eSurvey website SurveyMonkey. A total of N = 308 respondents provided voluntary consent to participate in the electronic survey and provided responses to more than 90% of the survey items. Research participants in this study were protected according to the federal requirements specified by the Department of Health and Human Services’ Code of Federal Regulations, 45 CFR 46. In accordance with federal requirements, approval to conduct research with human participants was obtained from the university institutional review board (IRB).

Measures

The survey instrument consisted of 42 questions divided into four sections: (a) emotional intelligence (16 questions), (b) collaboration (nine questions), (c) SOAR (12 questions), and (d) demographics (five questions). Emotional intelligence was measured by the 16-item Work Group Emotional Intelligence Profile–Short Form (WEIP-S; Jordan & Lawrence, 2009). The WEIP-S measures respondent competency in four emotional intelligence abilities helpful for understanding how emotional intelligence works in teams (Mayer & Salovey, 1997): self-awareness, self-management, other awareness, and other management. Collaboration was measured by the nine-item Team Collaboration Questionnaire, an original measure of collaborative activity among team members, adapted from Aram and Morgan (1976) and Rahim (1983a, 1983b), that measured three factors: integration, compromise, and communication. Participants self-rated both the emotional intelligence and the collaboration items using a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). SOAR was measured by the 12-item SOAR Profile (Cole & Stavros, 2013, 2014), a self-report measure of SOAR-based strategic thinking comprised of items scored using a 10-point Likert-type scale (1 = never, 10 = always) and arranged in four factors: strengths, opportunities, aspirations, and results. Demographic questions asked respondents about their gender, age, ethnicity, education, and role in teams (leader, member)

Data Analysis

Survey data were entered into Excel via SurveyMonkey. Data were transferred from Excel to Minitab version 17 for reliability analysis and inferential quantitative statistical analysis to test Hypothesis 1. Reliability analysis was conducted by obtaining Cronbach’s alpha values for the study measures; Hypothesis 1 was tested using linear regression of collaboration regressed on emotional intelligence (controlling for demographic characteristics). In linear regression, a significant regression coefficient infers the predicted change in the DV for a one-unit change in the IV. Data were also transferred to Mplus version 7 for confirmatory factor analysis (CFA) and path analysis. CFA was used to evaluate the construct validity of the study measures by testing the model fit of higher order CFAs conducted on the survey items that measured emotional intelligence, collaboration, and SOAR. Hypothesis 2 was tested using a mediation path model. In path models, only the structural relationships between the observed variables are modeled (i.e., composite scores for emotional intelligence, collaboration, and SOAR were used). In a mediation path model, mediation is inferred by a significant indirect effect of the mediator on the relationship between the IV and the DV. When using composite scores in a mediation path analysis, bootstrapped confidence intervals are generated for the indirect effect (5,000 bootstrapped sampled were used; Preacher & Hayes, 2008). For each statistical procedure, all available data were used. Study participants in this study provided data for both the IV (emotional intelligence) and the DV (collaboration). When data for both the IV and DV are collected from the same source, common method variance (CMV) may occur. CMV was tested using exploratory factor analysis (EFA).

Results

Demographic Characteristics of the Sample

Table 2 reports the demographic characteristics of the sample. As shown, the sample (N = 308) was essentially equally distributed among males and females. In contrast, age, ethnicity, education, and team role were not equally distributed among age groups, ethnicities, educational experience, and team role. More than half of the respondents were 45 to 64 years of age, more than three quarters were White, about two thirds obtained a graduate degree, and more than half reported serving as the team leader when working in teams.

Table 2.

Characteristics of Sample by Gender, Age, Ethnicity, Education, and Team Type.

Characteristic	n	%
Total sample	308	100.0
Gender
Female	152	49.4
Male	131	42.5
No response	25	8.1
Age
18-24	13**	4.2
25-34	35	11.4
35-44	54	17.5
45-54	80	26.0
55-64	80	26.0
65-74	22	7.1
75+	0	0.0
No response	24	7.8
Ethnicity
Asian/African American	34**	11.1
Other	14	4.5
White	236	76.6
No response	24	7.8
Education
High school/associate	17**	5.5
Bachelor	51	16.6
Master	217	70.4
No response	23	7.5
Team role
Leader	175**	56.8
Member	108	35.1
No response	25	8.1

Note. Sample frequency is expressed as % of all participants, N = 308.

p < .01, chi-square test for equality of distribution.

Reliability and Validity

Reliability and validity of the scales used to measure emotional intelligence, collaboration, and SOAR are presented in Tables 3, 4, and 5, respectively. Reliability was evaluated using Cronbach’s alpha test of internal consistency (Cronbach, 1951). As shown, Cronbach’s alphas for all study measures in all participants, in team leaders and in team members, ranged from .722 to .909, indicating acceptable reliability. Construct validity was evaluated using CFA. Tests of model fit were supportive of construct validity, with all measures satisfying the goodness-of-fit indices used to evaluate CFA: chi-square/df ratio less than 2, root mean square error approximation (RMSEA) < 0.08, comparative fit index (CFI) > 0.900, and all factor loadings significant at p < .05 (Cheung & Lau, 2008).

Table 3.

Reliability and Validity of the WEIP-S.

Emotional intelligence items	M ^a	SD	α	Factor^b
EI Full Scale (16 items)	5.32	0.79	.893
Self-awareness (awareness of own emotions) four items	4.76	1.36	.888	0.524
I can explain the emotions I feel to team members	5.14	1.49		0.840
I can discuss the emotions I feel with other team members	4.85	1.56		0.920
If I feel down, I can tell team members what will make me feel better	4.27	1.62		0.642
I can talk to other members of the team about the emotions I experience	4.76	1.58		0.812
Self-management (management of own emotions) four items	5.96	0.84	.805	0.655
I respect the opinion of team members, even if I think they are wrong	6.00	1.06		0.636
I can overcome my frustration with other team members	5.60	1.11		0.624
I try to see all sides of a disagreement before I come to a conclusion	6.07	1.01		0.818
I give a fair hearing to fellow team members’ ideas	6.18	1.00		0.791
Other awareness (awareness of others’ emotions) four items	5.10	1.11	.886	0.646
I can read fellow team members “true” feelings, even if they try to hide them	5.10	1.30		0.862
I am able to describe accurately the way others in the team are feeling	5.03	1.26		0.890
I can gauge true feelings of team members from their body language	5.20	1.22		0.785
I can tell when team members don’t mean what they say	5.12	1.22		0.685
Other management (management of others’ emotions) four items	5.47	0.99	.903	0.856
My enthusiasm can be contagious for members of a team	5.54	1.16		0.847
I am able to cheer team members up when they are feeling down	5.47	1.10		0.818
I can get fellow team members to share my keenness for a project	5.46	1.08		0.754
I can provide the “spark” to get fellow team members enthusiastic	5.41	1.13		0.855

Note. Psychometric properties conducted on EI data from N = 308 study participants. Tests of model fit for CFA: χ² = 141.532, df = 98, p = .003, RMSEA (90% CI) = 0.039 [0.023, 0.052], CFI = 0.984. WEIP-S = Workgroup Emotional Intelligence Profile–Short Form, 16 items; EI = emotional intelligence; CFI = comparative fit index; CFA = confirmatory factor analysis; RMSEA = root mean square error of approximation; CI = confidence interval.

Mean of items within scale where each item is measured on a 7-point Likert-type scale; 1 = strongly disagree, 7 = strongly agree.

Factor loading scores from CFA significant at p < .05 unless otherwise noted as non-significant (ns).

Table 4.

Reliability and Validity of the Team Collaboration Questionnaire (Nine Items).

Collaboration items	M ^a	SD	α	Factor^b
Collaboration Full Scale (nine items)	5.86	0 .73	.853
Integration (three items)	6.19	0.86	.909	0.888
I investigate an issue with my team to find acceptable solution	6.24	0.92		0.852
I integrate my ideas with my team to come up with a joint decision	6.10	0.96		0.853
I work with my team to find solutions to problems that satisfy our needs	6.24	0.91		0.951
Compromise (three items)	5.36	1.12	.849	0.467
I try to find a middle course to resolve an impasse	5.18	1.39		0.674
I negotiate with my team so that a compromise can be reached	5.53	1.19		0.968
I use “give and take” so that a compromise can be made	5.43	1.25		0.732
Communication (three items)	6.03	0.77	.721	0.903
I consider suggestions of team members to maximize team effectiveness	6.17	0.82		0.723
I share my expertise to satisfy the needs of my team	6.14	0.93		0.746
I share my ideas with the team concisely	5.79	1.09		0.668

Note. Psychometric properties conducted on collaboration data from N = 308 study participants. Tests of model fit for CFA: χ² = 35.695, df = 22, p = .033, RMSEA (90% CI) = 0.046 [0.013, 0.073], CFI = 0.990. CFI = comparative fit index; CFA = confirmatory factor analysis; RMSEA = root mean square error of approximation; CI = confidence interval.

Mean of items within scale where each item is measured on a 7-point Likert-type scale; 1 = strongly disagree, 7 = strongly agree.

Factor loading scores from CFA significant at p < .05 unless otherwise noted as nonsignificant (ns).

Table 5.

Reliability and Validity of the SOAR Profile (12 Items).

SOAR items	M ^a	SD	α	Factor^b
SOAR Full Scale (12 items)	8.00	1.05	.861
Strengths (three items)	7.96	1.27	.722	0.893
Strengths	8.53	1.42		0.759
Assets	7.13	1.85		0.573
Capabilities	8.26	1.42		0.588
Opportunities (three items)	8.40	1.26	.795	0.887
Opportunities	8.26	1.53		0.793
Ideas	8.62	1.37		0.706
Possibilities	8.31	1.57		0.754
Aspirations (three items)	7.52	1.54	.739	0.949
Aspirations	7.24	1.83		0.821
Desires	7.01	1.95		0.822
Values	8.30	1.90		0.679
Results (three items)	8.13	1.37	.790	0.539
Results	8.41	1.49		0.844
Completed tasks	7.57	1.88		0.584
Outcomes	8.41	1.49		0.854

Note. Psychometric properties conducted on SOAR data from N = 308 study participants. Tests of model fit for CFA: χ² = 88.345, df = 49, p = .001, RMSEA (90% CI) = 0.055 [0.036, 0.073], CFI = 0.970. SOAR = strengths, opportunities, aspirations, and results; CFI = comparative fit index; CFA = confirmatory factor analysis; RMSEA = root mean square error of approximation; CI = confidence interval.

Mean of items within scale where each item is measured on a 10-point Likert-type scale; 1 = never, 4 = rarely, 7 = often, 10 = always.

Factor loading scores from CFA significant at p < .05 unless otherwise noted as nonsignificant (ns).

CMV

Harman’s single-factor test (Sharma, Yetton, & Crawford, 2009) was used to test CMV, which is defined as “the amount of spurious correlation between variables that is created by using the same method, often a survey, to measure each variable” (Craighead, Ketchen, Dunn, & Hult, 2011, p. 578). This test was used to estimate CMV in the study by testing whether the items that measured the student IV (emotional intelligence) and DV (collaboration) were found to measure one factor according to an EFA. Evidence for CMV occurs when only a single factor emerges from the EFA. In contrast, if multiple factors emerge from the EFA, the conclusion is that the IVs and DVs can be considered to be independent (i.e., no CMV). Results of an EFA found multiple factors emerged, thereby refuting the presence of CMV in the study.

Inferential Statistics

Hypothesis 1

As shown in Table 6, emotional intelligence was found to be a significant predictor of team member self-perceptions of collaboration after controlling for gender, age, ethnicity, education, and team role (β = 0.472, p < .01), with emotional intelligence accounting for approximately 26% of the variance in collaboration. Also shown in Table 6 is the regression of collaboration on the four emotional intelligence factors controlling for gender, age, ethnicity, education, and team role. As shown, self-management and other management were found to be significant predictors of team collaboration, with the regression coefficient higher for self-management (UnBeta = 0.442, p < .01) than for other management (β = 0.100, p < .05). The four emotional intelligence factors accounted for approximately 38% of the variance in collaboration.

Table 6.

Collaboration Regressed on Demographic Characteristics and Emotional Intelligence.

	Collaboration
	Demographic characteristics			Emotional intelligence full score			Emotional intelligence factors
	β	SE	Z	β	SE	Z	β	SE	Z
Constant	5.767	0.330	17.45	3.452	0.385	8.95	2.526	0.385	6.56
Gender	−0.141	0.088	−1.59	−0.088	0.078	−1.12	−0.117	0.072	−1.62
Age	0.059	0.036	1.64	0.034	0.032	1.06	0.035	0.030	1.17
Ethnicity	−0.019	0.120	−0.16	−0.138	0.106	−1.30	−0.182	0.100	−1.83
Education	0.046	0.050	0.91	0.042	0.044	0.96	0.039	0.041	0.96
Team role	−0.152	0.091	−1.68	−0.044	0.080	−0.55	−0.059	0.076	−0.77
Emotional intelligence				0.472**	0.052	9.11
Self-awareness							0.014	0.030	0.47
Self-management							0.442**	0.051	8.71
Other awareness							0.063	0.040	1.60
Other management							0.100*	0.049	2.04
R ^2a	3.8%			26.3%			37.7%
Change in R²				22.5%**			33.9%**

Note. Unstandardized regression coefficient beta, change in R².

R² adjusted for the number of predictors in the model.

p < .05. **p < .01.

Hypothesis 2

Table 7 and Figures 3 and 4 present the results of mediation path analysis used to test Hypothesis 2: SOAR is a mediator of the emotional intelligence–collaboration relationship in team members. As shown, the indirect effect of emotional intelligence predicting collaboration through SOAR was significant (β = 0.110, p < .05), suggesting SOAR is a mediator of the emotional intelligence–collaboration relationship. Investigating the indirect effects of emotional intelligence predicting collaboration through the four factors of SOAR found strengths (β = 0.049, p < .05), aspirations (β = −0.49, p < .05), and results (β = 0.043, p < .01) were mediators of the emotional intelligence–collaboration relationship.

Table 7.

Mediation by SOAR of EI Affecting Collaboration: All Participants.

Effect	IV	MED	β	SE	Z	p	Bootstrap^a		BC bootstrap^b
Effect	IV	MED	β	SE	Z	p	Lower	Upper	Lower	Upper
All participants
Total direct	EI		0.486	0.074	6.543	.000**	0.333	0.629	0.342	0.636
Path a		SOAR	0.617	0.098	6.317	.000**	0.432	0.815	0.433	0.820
Path b		SOAR	0.179	0.055	3.273	.001**	0.072	0.285	0.065	0.280
Path c’	EI		0.376	0.099	3.796	.000**	0.177	0.564	0.193	0.577
Indirect	EI	SOAR	0.110	0.045	2.444	.015*	0.035	0.196	0.034	0.210
Total indirect			0.110	0.045	2.444	.015*	0.035	0.196	0.034	0.210
Total direct	EI		0.487	0.075	6.506	.000**	0.343	0.629	0.346	0.636
Path a		Strengths	0.552	0.114	4.869	.000**	0.336	0.781	0.334	0.779
		Opportunities	0.699	0.110	6.339	.000**	0.485	0.923	0.492	0.932
		Aspirations	0.818	0.152	5.377	.000**	0.529	1.121	0.525	1.115
		Results	0.385	0.120	3.207	.001**	0.159	0.629	0.162	0.634
Path b		Strengths	0.089	0.041	2.161	.031*	0.008	0.170	0.007	0.168
		Opportunities	0.062	0.041	1.489	.136	−0.018	0.143	−0.020	0.141
		Aspirations	−0.061	0.029	2.078	.038*	−0.119	−0.005	−0.121	−0.007
		Results	0.112	0.028	3.930	.000**	0.053	0.164	0.053	0.164
Path c’	EI		0.402	0.095	4.233	.000**	0.212	0.580	0.224	0.590
Indirect		Strengths	0.049	0.025	1.966	.049*	0.004	0.106	0.005	0.107
		Opportunities	0.043	0.030	1.436	.151	−0.013	0.105	−0.011	0.107
		Aspirations	−0.049	0.023	2.151	.031*	−0.096	−0.004	−0.102	−0.009
		Results	0.043	0.016	2.655	.008**	0.015	0.077	0.018	0.085
Total indirect			0.085	0.043	1.966	.049*	0.010	0.182	0.011	0.182

Note. Unstandardized regression coefficient beta; 5,000 bootstrapping samples. SOAR = strengths, opportunities, aspirations, and results; EI = emotional intelligence; BC = bias corrected; IV = independent variable; MED = mediating variable.

Bootstrap confidence intervals (95%).

Bias-corrected bootstrap confidence intervals (95%).

p < .05. **p < .01.

Figure 3.

Test of SOAR as a mediator of the EI–collaboration relationship in team leaders.

Figure 4.

Test of strengths, opportunities, aspirations, and results as multiple mediators of the EI–collaboration relationship in team members.

Discussion

The way in which entrepreneurial team members collaborate with each other is important for determining successful venture outcomes (Chowdhury, 2005; Gundry et al., 2016; Mol et al., 2015). This study investigated collaboration in a sample of professionals working in teams. First, this study suggests emotional intelligence is a significant predictor of collaboration in team members primarily through management of emotions in self and others. These results support previous research on the positive effects of emotional intelligence and collaboration on team performance (Dietrich et al., 2010; Druskat & Wolff, 2001; Goleman, 2006; Hattori & Lapidus, 2004; Jordan & Ashkanasy, 2006; Mount, 2006; Romero et al., 2008, 2009; Sala, 2006; Whitaker, 2009). Second, study results suggest SOAR mediates the effect that emotional intelligence has on collaboration, primarily through strengths, aspirations, and results. These results suggest a framework for collaborative dialogue may help explain how emotional intelligence has a positive impact on collaboration.

Implications for Practice and Recommendations

Results of this study have important implications for increasing collaboration among entrepreneurial team members through emotional intelligence and open dialogue leading to successful entrepreneurial outcomes. This study first focused on investigating the positive effects of emotional intelligence on collaboration among individuals working in teams. Collaboration among team members increases the likelihood that team members working together will accomplish more than that which could be accomplished by the individual members acting alone (Gray, 1985; Romero et al., 2008, 2009). Team members who acquire emotional intelligence to develop awareness and management of emotions in themselves and others have an immediate advantage compared with those lacking in emotional intelligence abilities (Gohm, 2004). Study results suggest achieving collaborative goals in entrepreneurial teams can actually be influenced by an individual’s awareness and management of emotions in themselves and others. The significance of this implication is important to entrepreneurial teams seeking to start a successful venture within some framework of time, cost, and performance.

Entrepreneurs concerned with increasing collaboration in work teams are recommended to increase emotional intelligence abilities in their team members. Behavioral coaches are recommended to use open discussions, exercises, dialogue, role-play, diaries, and one-to-one feedback to help team members identify team-based biases, hot button issues, and resolve conflicts in diverse settings by developing emotional intelligence competencies of awareness and regulation of emotions in self and others (Dulewicz & Higgs, 2004; Gardenswartz, Cherbosque, & Rowe, 2009).

Next, this study focused on considering SOAR, a framework for collaborative dialogue, as a mechanism for how emotional intelligence has a positive impact on collaboration. We believe the results of this study help to understand SOAR as a putative mechanism for how emotional intelligence affects team-based collaboration. For entrepreneurial teams, shared vision, purpose, and respect for each other’s roles are necessary to achieve breakthrough results. The SOAR framework has the potential to build strong and dynamic relationships, and it may help team members to understand the importance of working collaboratively to develop strategy, measurable objectives, and methods to achieve a visionary future based on strengths and opportunities. The manifestations of SOAR, exemplified in self-reflection, mutual understanding, and a consideration for the collaborative team as a whole, help team members exchange ideas, aspirations, and desired results (Stavros & Hinrichs, 2009).

These results provide a focus for practical recommendations to increase the strength of the relationship between emotional intelligence and collaboration to increase entrepreneurial team performance. For example, to help increase the positive effects of emotional intelligence on collaboration in entrepreneurial teams, entrepreneurs should create teams that build on team member strengths and aspirations, and identify opportunities for achieving measurable positive results. Education and training in SOAR competencies will help team members learn about SOAR and strengths-based strategic thinking. When individuals are working in a team context, especially when collaborating on innovation or new product development, an SOAR-based framework for collaborative dialogue may have the best likelihood of maximizing the impact emotional intelligence has on collaboration.

SOAR-based collaborative dialogue occurs “when people collectively discover or create new things that they can use to positively alter their collective future” (Bushe, 2007, p. 33). For example, entrepreneurial team members can have conversations about the strengths of the new venture (“What is working well?”), current ideas for creative solutions or innovations (“What can we possibly create together?”), and current possibilities that would benefit from creative solutions or innovations (“What does this possibility look like?”). Next, collaborative and inclusive conversations on any individual, team, and/or new venture strengths as they relate to possibilities for solutions or innovations (“What are our strengths as these relate to this possibility?”), opportunities that would benefit from solutions or innovations (“What opportunities appear ?”), aspirations of a future the team desires (“Who will we be—the vision—where are we going?”), and measurable results indicating progress toward a goal or objective that the team wants to complete (“What are we trying to achieve?”). The SOAR framework would conclude with appraisal of the team’s behavior (“Who are we—what purpose do we serve—what value do we add?”) and a plan for the next strategic dialogue (“What actions will you commit to? What resources are needed?”).

Study Limitations and Future Directions

This study has potential limitations that should be considered. First, individual research participants served as the unit of analysis for this study. Accordingly, study results are limited to individual team member data rather than aggregated team-level data on perceptions of emotional intelligence and team-based collaboration. Study results are also limited to the cross-sectional nature of the data, which were collected at one moment in time. Future research should aggregate team member data at the level of the team to generate team-level data. The use of team-level data may help with understanding the relationship between emotional intelligence and collaboration at the team level. Future research should study emotional intelligence, collaboration, and SOAR using longitudinal data to understand the interrelationship among these constructs over time. Future research should also obtain data on emotional intelligence, SOAR, and team collaboration among actual entrepreneurial teams working on new ventures. Finally, future research should seek to determine whether other variables in addition to SOAR may explain the positive effect that emotional intelligence has on collaboration. For researchers, identifying additional mediating variables may provide even greater opportunity for increasing the success of entrepreneurial teams.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Matthew L. Cole, PhD, is an associate professor at Lawrence Technological University’s College of Business and Information Technology and Founder of PRONEWS LLC. He teaches undergraduate and graduate courses in business statistics, principles of management, human resource management, entrepreneurship, and organization development and change. His research focuses on positive organizational scholarship, SOAR, teams, and research methods in business.

John D. Cox, DM, is a manager of cross-functional product design and development programs at FCA. He is involved with product & process quality improvement initiatives, vehicle program management, vehicle safety and regulatory compliance, advanced technology R&D (PHEV), and component and vehicle assembly operations. He is also in charge of developing and supervising work teams.

Jacqueline M. Stavros, DM, is a full professor at Lawrence Technological University’s College of Business and Information Technology, and Appreciative Inquiry Advisor at Flourishing Leadership Institute. Her passion is working with others to discover their SOAR capacity (strengths, opportunities, aspirations and meaningful results) for positive change and applying appreciative inquiry (AI) in everyday conversations to lead self and others.

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