The effect of Diversity on Team Social Integration

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(1)The effect of Diversity on Team Social Integration By Lin, Bing-Shing. A Thesis Submitted to the Graduate Faculty in Partial Fulfillment of the Requirements for the Degree of. MASTER OF BUSINESS ADMINISTRATION. Major: International Human Resource Development. Advisor : C. Rosa Yeh, Ph. D.. National Taiwan Normal University Taipei, Taiwan July 2016.

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(3) ACKNOWLEDGEMENTS The road has come to an end for my post-graduate life. There are a lot of people I would like to thank. First, I would like to thank my family for without them I would not be here right now and I would not have the patience and motivation to continue. They have helped me through this journey since day one and I cannot thank them enough. Second, I would like to thank my thesis advisor Dr. Rosa Yeh, for without her guidance I would not have finished this thesis. She is a kind and patient person who is always open to any suggestions and will always try and make time for her students. I really appreciate her time and effort in guiding me through this path. Third, the other professors of International Human Resource Department, Dr. Tony Shih, Dr. Jane Lin, Dr. Steven Lai, Dr. Vera Chang. They are some of the best professors I have ever had. They are knowledgeable and smart and know how to get you thinking and keep yourself motivated, I cannot thank them enough. Last, I would like to thank the staff of the IHRD office and my fellow classmates. To the staff of IHRD, I would like to thank Ms. Tracy Lee who was actually the first person I met in IHRD. She is a very selfless person who is ready to help anyone at anytime even though she is busy. She is kind and understanding and will be there if you need someone to talk to. To my classmates, they are some of the best classmates one could ask for. I have learned a lot from them and will cherish the moments we had together. I wish everyone a prosperous. and. successful. future. in. whatever. that. made. be..

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(5) ABSTRACT There have been many researches done on diversity and performance or work outcomes but not on team social integration as the dependent variable. In the world today globalization is becoming a phenomenon that is happening to all countries over the world. People are moving out of their comfort zones and going to other countries for work or living. For organizations this present a need to understand about diversity and how it impacts teams and how it can be used to improve their performance. This research examined two areas of diversity and its' effect on team social integration. Diversity is divided into two areas perceived surface-level and perceived deep-level. The data was collected from students via hard copy survey questionnaire and online survey. It examined the participants perception of team members within their team/group and how it affects team social integration. This used a quantitative analysis using convenient sampling of 207 participants of which they were students in universities in Taiwan. The results found that perceived surface-level diversity had a negative relationship and negative impact on team social integration, while on the other hand, perceived deep-level diversity had a negative relationship but no impact on team social integration. Keywords: Perceived surface-level diversity, Perceived deep-level diversity, Team social integration. I.

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(7) TABLE OF CONTENTS ACKNOWLEDGEMENTS ABSTRACT .............................................................................................. I TABLE OF CONTENTS ......................................................................... II LIST OF TABLES ..................................................................................IV LIST OF FIGURES .................................................................................. V CHAPTER I INTRODUCTION .............................................................. 1 Background of Study................................................................................................................... 1 Problem Statement ...................................................................................................................... 2 Rationale of Study ....................................................................................................................... 3 Research Purpose ........................................................................................................................ 3 Research Questions ..................................................................................................................... 3 Scope of Study ............................................................................................................................ 4 Definition of Terms ..................................................................................................................... 4. CHAPTER II LITERATURE REVIEW.................................................. 6 Team Social Integration .............................................................................................................. 6 Diversity ...................................................................................................................................... 9 Surface-level Diversity................................................................................................................ 9 Deep-level Diversity ................................................................................................................. 13. CHAPTER III METHODOLOGY ........................................................ 18 Research Framework ................................................................................................................. 18 Research Hypothesis ................................................................................................................. 19 Research Procedure ................................................................................................................... 19 Research Design ........................................................................................................................ 21 Method of Data Analysis........................................................................................................... 24 Measurements............................................................................................................................ 26 Validity and Reliability ............................................................................................................. 27. CHAPTER IV DATA ANALYSIS AND FINDINGS .......................... 35 Pearson's Correlation Analysis .................................................................................................. 35 Hierarchical Regression Analysis ............................................................................................. 38 Summary of Analysis Results ................................................................................................... 41 II.

(8) CHAPTER V CONCLUSIONS AND DISCUSSIONS ........................ 43 Conclusions ........................................................................................................................... 43 Research Implications............................................................................................................ 44 Practical Implications ............................................................................................................ 45 Research Limitations ............................................................................................................. 45 Suggestions for Future Research ........................................................................................... 46. REFERENCE .......................................................................................... 47 APPENDIX A QUESTIONNAIRE ....................................................... 52. III.

(9) LIST OF TABLES Table 3.1. Descriptive Statistics on Sample Characteristics .................................................... 23 Table 3.2. Index on Model Fit ................................................................................................. 26 Table 3.3. Exploratory Factor Analysis (Pilot Test) ...................................................................... 28 Table 3.4. KMO and Bartlett's Test (Pilot Test) ............................................................................ 29 Table 3.5. Team Social Integration Model Fit Summary ............................................................. 30 Table 3.6. Multi Group Comparison for Cross-validation of Measurement Model TSI .......... 31 Table 3.7. Team Social Integration Variable Items ....................................................................... 31 Table 3.8. Perceived Deep-level Diversity Model Fit Summary ................................................. 33 Table 3.9. Perceived Deep-level Diversity Variable Items .......................................................... 33 Table 3.10. Cronbach's Alpha .................................................................................................. 34 Table 4.1. Means, Standard Deviation(SD) and Correlation Coefficient among Variables .... 37 Table 4.2. Results of Hierarchical Regression Analysis: Variable level ................................. 39 Table 4.3. Results of Hierarchical Regression Analysis: Perceived Surface-level Diversity Dimensions as Independent Variable....................................................................................... 40 Table 4.4. Results of Hierarchical Regression Analysis: Team Social Integration Factor 1 as Dependent Variable ................................................................................................................. 41 Table 4.5. Hypotheses Testing Results Summary.......................................................................... 42. IV.

(10) LIST OF FIGURES Figure 3.1. Research framework ............................................................................................. 18 Figure 3.2. Research procedure .............................................................................................. 20 Figure 3.3. Team social integration CFA measurement Model ............................................... 30 Figure 3.4. Perceived deep-level diversity CFA measurement model..................................... 32. V.

(11) CHAPTER I INTRODUCTION The aim of this chapter provides a basis of the research. It discusses different topics such as the background of the study, study objective, purpose of study, research question, significance of study and definition of terms. Background of Study In this day and age, the world is becoming more connected. Globalization is becoming a big part of the world and it looks like it isn't going to stop. It greatly influences demographics within the workplace. A few decades ago the trend wasn’t as popular for people to go cross borders to other countries and working, but with a global recession happening and people scrambling for jobs, it made people move to other countries just to have a job. A multi-cultural global workforce seems to be the new way of thinking about diversity as there are more diverse employees in companies, for example, in the US workforce alone about 40% of employees are minorities as of 2009 (Johnson, 2011). Successful companies have recognized the need and importance of diversity in the workplace and will continue to make huge efforts to manage diversity in the workplace, there are benefits which are gained such as, different opinions, broader range of service (e.g. language and cultural understanding) and different experiences and talents. There are also some challenges which come with diverse workforce such as, communication and employees resistant to change (Greenberg, 2009). The key concern for companies and employers, is to achieve financial results by bringing together people from different backgrounds culturally or ethnically (Kokemuller, 2015). The last few decades has seen a change in the workplace from individual jobs in a company work structure to work structured around teams and the technologies that connect members of a team together (Kozloswki and Bell, 2003). According to Lau (2013), teams are an important part of the organization and being able to work in a team and be effective is very important for productivity, morale and employee retention. Since the world is becoming more globalized and the workforce has become more diverse, organizations have been using teams to their advantage, so now is a good time to learn as much as we can about how teams can affect performance and viability over time (Mohammeed & Angell, 2003; Offerman & Gowing, 1990). 1.

(12) When you have teams you could either have conflict or cohesion between team members. Teams or groups with higher cohesion may have higher performance but those with lower cohesion may have lower performance and more conflict (Kaymak, 2011). According to Polzer et al. (2002), groups with high interpersonal congruence were positively affected by diversity, but for those that had lower interpersonal congruence diversity affected them negatively. Polzer et al. (2002) further explained that diversity affected teams who had high interpersonal compatibility which enhanced their task performance and in the end social integration. There have been a few research on diversity and cohesion and social integration; some had positive results while others had negative results. Sargent and Chen's (2001) study found that, diverse groups reported higher levels of task performance and task efficacy at the end of their assignment. They found that, diversity decreases barriers within members in a team, promotes cohesion, social integration and creates communication. While Pelled (1996) observed that diversity in their work teams resulted in intragroup conflict and lower performance. Social integration is important for teams, as it shows how well they connect together on a personal level. If they do not get along or do not have good rapport then it seems that it affects the cohesiveness of the team and the performance in general.. Problem Statement There were many studies done on surface-level (demographic) and deep-level diversity. There is a distinct difference between the two, surface-level relates to more of the things you are able to notice at first glance in an individual, such as gender, race/ethnicity and age. While deep-level elements are those which are not easily seen, such as, one's personality, values and attitudes (Harrison et al., 2002). Harrison et al. (2002) found that few empirical investigations focused on one deeplevel diversity dimension, values, and its effect on social integration. Newell et al. (2008), examined diversity and found that there have been mixed results between the relationship of deep-level diversity and team performance. They also found that diversity can increase performance by supplying different sources of information but, on the other hand, decrease performance by impacting team social integration. As the world becomes more interconnected and globalized than it has ever been, more research is needed to find out whether these variables have an effect on team social integration.. 2.

(13) Rationale of Study There are a few reasons for this study. There have been a few studies done on diversity and dependent variables such as performance or work outcomes but not much done on team social integration as the dependent variable. In this study team social integration was used as the dependent variable to examine the relationship between diversity and team social integration. There have been mixed reviews from the results, some show a positive relationship or effect and others show a negative relationship or effect. Therefore, this study was done to empirically test whether diversity has an effect on team social integration and whether it is positive or negative. Another reason is the use of student teams in Asia, specifically whether or not student teams in an Asian setting differ from the ones in other studies which were mostly done in a Western setting. Therefore, it is important to investigate whether or not perceived surfacelevel and perceived deep-level diversity had an effect on team social integration using an Asian sample.. Research Purpose The purpose for doing this study is for the researcher to give more contribution to the theory of how surface-level and deep-level variables will affect team social integration. This research will try to examine how the elements of these variables affect students working in teams and groups. This study will examine how individuals interact with each other, whether the relationship will increase or decrease based on certain elements of surface-level and deep-level diversity and if it affects team social integration.. Research Questions There has not been a lot of research done on whether surface-level and deep-level diversity have an effect on team social integration so for this study the following questions will be submitted for evaluation: 1.. Will Perceived Surface-level diversity have an effect on Team Social Integration?. 2.. Will Perceived Deep-level diversity have an effect on Team Social Integration?. 3.

(14) Scope of Study The study is about whether or not perceived surface-level and perceived deep-level diversity has an effect on team social integration. The sample size of this study was limited to undergraduate and post-graduate students in Taiwan. They may be in any area of study and from any school. They should however, have previous team/group experience and have at least three members in the group as two members do not equal a group. This team/group experience is not limited to only business or management majors, this could be of any discipline. The study targeted students' perception on each individual in their team/group based on items in the survey questionnaire. There are three main variables which are examined, perceived surface-level diversity, perceived deep-level diversity and team social integration. Since there are a lot of dimensions of the two different types of diversity not all are chosen. The dimensions chosen are based mainly on the literature and previous research.. Definition of Terms Team Social Integration Team Social integration, is a multifaceted phenomenon which demonstrates how strong the individuals in a group are when put against different variables such as attractiveness towards one another and satisfaction with one another (O'Reilly et al., 1989). According to Harrison et al. (2002), social integration is a construct which has elements of cohesiveness and satisfaction with individuals, has positive social interaction and the team experience is enjoyable.. Diversity Diversity pertains to individual differences inside a team in terms of race/ethnicity, attitudes, personality, age and gender, these differences are categorized into surface-level or deep-level attributes (Russo, 2012).. Surface-level Diversity "Surface-level diversity is used to describe characteristics such as age and gender which are easily visible to others" (Van Vianen et al., 2004, p. 698). Instead of surface-level diversity, it is sometimes also seen as demographic diversity, because they are more easily noticeable or observable to others on "surface level" (Pelled, 1996).. 4.

(15) Deep-level Diversity: According to Harrison et al. (1998), deep-level diversity refers to how different individuals are in a team in terms of different characteristics: such as personality, values and attitudes. Team members also differ from each other in terms of KSA, knowledge skills and abilities (Rink & Ellemers, 2010).. 5.

(16) CHAPTER II LITERATURE REVIEW This chapter will give an overview of the literature of each of the following variables and how they relate to each other, perceived surface level diversity, perceived deep level diversity and team social integration. First is an overview of what team social integration is, followed by the different types of diversity.. Team Social Integration Definition of Team Social Integration According to some researchers, social integration is a multifaceted phenomenon which demonstrates how strong the individuals in a group are when put against different variables such as attractiveness towards one another and satisfaction with one another (O'Reilly et al., 1989). According to Harrison et al.. (2002), social integration is a construct which has elements of cohesiveness and satisfaction with individuals, has positive social interaction and the team experience is enjoyable. Usually elements of team social integration are the most commonly researched variables as outcomes in diversity studies. Social integration is an elementary part of group functioning and a primary affective dimension of social integration is group cohesiveness. Social integration is the degree to which team members are linked psychologically or attracted towards interactions with one another in terms of a common goal (Harrison, 2002; O'Reilly, Caldwell, and Barnett, 1989). The measures of social integration have been well established and it is known that social integration itself may be affected by the relative similarities of individuals in a group (O'Reilly III, C. A., Caldwell, D. F., & Barnett, W. P. (1989). Similarities in attitudes as an example have also been known to promote group cohesion significantly (Good and Nelson, 1971). There have been some support for the association between social integration and similarity in demographic attributes such as race and age (Tsui and O'Reilly, 1989). This research will follow its own definition of team social integration that is, team social integration is the degree to which members within a group connect with each other, and the relationship may be affected by surface level and deep level diversity.. 6.

(17) Previous Studies of Team Social Integration Social integration has been studied by many researchers before mainly as outcome variables. Other variables which may affect social integration are: demography (Smith et al., 1994), team and task performance (Harrison et al., 2002). According to Smith (1994), he found that demography does affect team social integration and social integration does affect performance in a positive way. In the researchers study, he used three models, (1) a demography model, (2) process model and (3) intervening model. In the different models team demography accounts entirely for the performance outcomes, in the process model also directly affects performance outcomes and the intervening model in that the effects of top management team on performance are entirely due to the effects of demography. So observe that team demography does affect team social integration which in turn affects performance positively. Another study done by O'Reilly (1989) sets to find out the relationship between group demography, social integration and individual turnover. As the results suggest that heterogeneity in group tenure has low but positively significance with group social integration which in turn negatively affects individual turnover. "Social integration prevails in a group if their bonds of attraction unite its members" (Blau, 1960, p.545). In Blau's (1960) study he found that individuals who want to be included in another's group or team, are under the pressure of having to impress the other members of the group, so this results in competition which would give rise to more defensive tactics which can block social integration. Surface level (age, sex, race/ethnicity) and deep level diversity (values, attitudes) have positive effects on group social integration. As time goes by and group spend more time with each other, surface level in the beginning is high but turns low and becomes less important while on the other hand, deep level diversity which includes values and attitudes, becomes stronger (Harrison et al., 1998). There has also been some studies on E-Identities or Virtual Team and how diversity affects team social integration and performance. The literature and results show that, Virtual Teams are being used by organizations but there are some challenges, such as those teams may never meet face-to-face. Results in general show that, deep level attributes can be influenced through the use of e-identity profiles which provide some support for the idea that it is able to minimize social tension from deep level diversity but at the same time gain the benefits from actual diversity (Newell, 2008). 7.

(18) O'Reilly (1989) examined between group demography, social integration and turnover and found that, demography and social integration helped reduce employees turnover. According to Kaymak (2011), ensuing studies could be done and analyzed to determine whether individuals of a group/team feel the same way about the level of group cohesion. Gully et al. (1995) suggested further research between cohesion and performance should be done to provide richer descriptions of the task setting, so it may allow other researchers that follow to examine subsets of the theoretically meaningful variables in group contexts.. Components of Team Social Integration According to a study by Newell et al. (2008), team social integration is one of the most common if not the most commonly studied of all team processes. Some of the elements of team social integration they used were cohesiveness, the Job Descriptive Index and willingness to work together in the future. In the end they found that overall social integration and team performance are positively correlated. O'Reilly, Caldwell and Barnett (1989) studied social integration and its effect on turnover. For their components of social integration they included cohesiveness index by Seashore (1954), respondents satisfaction assessed with Job descriptive index and group index of social integration. In the end the results showed that, social integration as a grouplevel construct affects the individuals turnover rates. Harrison et al (1998 & 2002) focused on group cohesiveness and team social integration respectively. Harrison et al. (1998), focused on group cohesiveness and group functioning as their main outcome. In the end, they found out that over time their predictors of cohesive/social integration were supported and that deep-level variables over time were more valuable than surface-level in determining social integration. As for Harrison et al. (2002), it was on the effect of surface-level and deep-level variables on team social integration and how that affects performance. The elements of social integration included cohesiveness, satisfaction, fairness of team practices and willingness to work with the members of your group in another project. The results showed that the analysis for each were high and that team social integration has correlation to team performance. In conclusion, there seems to be different opinions from researchers on the different elements that can be used to measure team social integration, such as cohesiveness and. 8.

(19) satisfaction (Harrison et al., 1998 & 2002; O'Reilly, Caldwell, and Barnett, 1989; Rico et al., 2007).. Diversity Diversity is the understanding that every person, every individual is different/unique. It makes people recognize each others' differences. Diversity refers to individual differences within a team in terms of race/ethnicity, attitudes, personality, age and gender, these differences are categorized into surface-level or deep-level attributes (Russo, 2012). It also means having respect for each other's differences such as disability, education and national origin. This study will focus on two different levels of diversity, surface-level and deep-level. There are some theories which share that individuals are attracted to people in terms of personal characteristics. Such as, the similarity-attraction theory which imply that individuals are more attracted to other people in terms of values, attitudes and personality (Russo, 2012). As a consequence, they tend to communicate, interact, and cooperate more frequently only with those people because they perceive this interaction as safe, easy, and satisfying (Osbeck, L. M., Moghaddam, F. M., & Perreault, S. (1997). Tajfel (1979) also proposed a theory called social identity theory. This theory proposed that the groups that people belong to are an important source of one's pride and self-esteem. It means that groups give us a sense of social identity because humans are social beings, gives us a sense of belonging in the social world. So if people seems to like each other and get along well with each other, there seems to be improved cohesion and integration which in turn seems to improve their performance in contract to having conflicts in teams or groups.. Surface-level Diversity Definition of Perceived Surface-level Diversity According to Harrison et al. (1998), perceived surface-level diversity is described as the contrast among team members in overt demographic characteristics. These characteristics which are usually reflected as physical observable features. In surface-level homogeneous groups, members are more likely to think that they possess identical information about the task, but in surface-level diverse teams/groups, the members are more likely to expect there are differences in the information that they know (Antonio et al., 2004; Phillips & Loyd, 2006). So perceived surface-level diversity triggers the expectation that. 9.

(20) deep-level diversity will be present in groups which serves to legalize the surfacing of unique information. Perceived surface-level diversity describes characteristics of a person which are easily visible to others (Van Vianen et al., 2004, p.698). Instead of perceived surface-level diversity, it is sometimes also seen as demographic diversity, because they are more easily noticeable or observable to others on "surface level" (Pelled, 1996). According to Harrison, (1998) and Jackson et al. (1993), demographic characteristics are immutable and instantly observable and measurable in simple and valid ways. So what this is saying is that surface level diverse groups differ from homogenous groups and they bring about the expectation that deep-level diversity will be present in groups. So from the definitions above this study will follow a similar definition that surfacelevel diversity is the characteristics which are observable and/or reflected in the physical features of an individual.. Previous Studies of Perceived Surface-level Diversity Different research has used different sub-dimensions for perceived surface-level diversity and for different outcome variables. Spickerman et al. (2013) used age, gender, size of organization and job position for their study. They used these elements for exploring effects on behavior in foresight, using a Delphi method in their research. Spickermann et al. (2013) found that age had a moderating effect on the relationship between environmental value characteristics and the panelists' response behaviors. Williams and O'Reilly (1998) focused on perceived surface-level diversity and they used a meta analysis of organizations and reviewed over 80 different studies for their research. Results show that diversity in groups has negative effects on social integration, communication and conflict, which means diverse groups are more likely to have less integration, less communication and more conflict. While according to Tsui and O'Reilly (1989) who examined age, gender, race, education and job tenure and how this has an effect on subordinates' performance from the perspective of their superiors. The researchers looked at these different elements and how a supervisor-subordinate relationship was in terms of performance and how well they knew their roles and how much conflict there was between the two (Dyad). They found that an increase in dissimilarity in superior-subordinate. 10.

(21) demographic characteristics is associated with lower effectiveness as perceived by superiors and less personal attraction on the part of superiors for subordinates. Age, gender and race/ethnicity were all studied in Harrison et al. (1998; 2002) and Knippenberg and Schippers (2007). Harrison et al. (1998; 2002) looked more on group cohesion, team social integration and performance as outcomes. While Knippenberg and Schippers (2007) looked more at a review of literature for over 8 years of studies. The results showed that there was a negative relationship between demographic diversity and team integration which diminished over time as it may take members time to develop knowledge, skills and abilities required to elaborate different perspectives. This means they need time to get along and get a feel for "who knows what". There are different kinds of research done for perceived surface-level or relational demography diversity by different researchers. Some use different elements for different outcomes and sample, such as employees and work team performance and others on student performance and cohesion.. Components of Perceived Surface-level Diversity There are different elements of perceived surface-level diversity, most studies use the same three main ones(gender, age, race/ethnicity) while others have included others for specific studies(tenure, education, functional background diversity). In previous studies there have been different elements to measure perceived surfacelevel diversity. Marital status is a surface level or demographic element which has not been examined much in previous research, even though it is also easily recognized in this day and age(i.e., wedding rings) (Harrison, 2002). According to Tsui and Gutek (1999) marital status clearly marks different social level between individuals, which may prompt negative bias such as, stereotype and perhaps even different interpersonal affiliations. According to Mohammed and Angell (2004), perceived surface level diversity typically involves an individuals' age, gender or ethnicity. Although individuals are able to categorize themselves in different ways, demographic attributes are easily seen. Other research on person or individuals have already established gender or race forms a person's perception of another. Usually in past studies, diversity has mainly focused on gender, age, race/ethnicity, tenure and education which seem to be the fundamental basis of diversity research (Kippenberg et al., 2004; Williams & O'Reilly, 1998). 11.

(22) Williams and O'Reilly (1998) studied different variables including the normal age, sex and race/ethnicity. They included organizational tenure and background differences which included education and functional specialty. All variables for demography were examined on two dimensions: group process and performance. According to Van Vianen et al. (2004) they also focused on surface and deep level diversity on expatriates adjustment and used age and gender for their surface-level elements as they said these variables are easily detectable but they are an important part of an expatriates' experience. So the general consensus is that, perceived surface-level diversity refers to the characteristics of a person which is easily visible to others or easily observable such as age, sex, race/ethnicity. This study chose to continue with the study of age, sex, and race/ethnicity for elements of surface-level diversity. Though their effects are inconsistent, they have had a long history in this area of study (Harrison, 2002; Riordan, 2000). According to Tsui and Gutek (1999) they are also immediately recognizable and useful to assign others to tacit social categories.. The Effect of Surface-level Diversity on Team Social Integration Riordan (2000) looked at demography (age, gender, race/ethnicity) or perceived surface-level diversity (according to other researchers) and found all three elements are correlated with social integration or the dimensions of cohesiveness and satisfaction. The researcher also found that in his literature review, not all researchers found that these elements were positively related to social integration or its sub-dimensions, and other studies have found that it was negatively related to social integration. According to O'Reilly (1989), they did not find a significant relationship between surface-level age and social integration, which was measured through work group cohesiveness and satisfaction between employees. Jackson et al. (1991) also did not find age to have significant relationship between workers. Harrison et al. (1998) found in their research of perceived surface-level diversity(age, gender, race/ethnicity) was that interaction and performance between homogeneous and heterogeneous groups were similar at the beginning but over time heterogeneous groups improved drastically over homogeneous groups and in the end so did the performance and interactions improve. As for Harrison et al. (2002), the researchers found that though perceived surface-level diversity diminishes after a short period of time it still is an important aspect of interactions as it is the first observable aspect of a person when people meet for the first time. As time passes, also in Harrison et al. (1998) perceived deep12.

(23) level diversity becomes more important and the combination of perceived deep-level and perceived surface-level diversity have a positive relationship to team social integration. There have been some negative results from other researchers such as Pelled (2006), who also found out that team diversity seems to have a negative impact on team social integration and team work in small group research. Horwitz and Horwitz's (2007) study examined that temporary teams in a hospital setting which varied in racial composition showed more conflict than racial homogeneous ones. For the present study, perceived surface-level diversity will still use the subdimensions of age, gender and race/ethnicity. This study adopts Harrison et al.'s (2002) argument that elements of perceived surface-level diversity affects team social integration, as seen by the hypotheses: Hypothesis 1. Perceived surface-level diversity will affect team social integration. Deep-level Diversity Definition of Perceived Deep-level Diversity Perceived deep level diversity has been studied by many researchers each with their own way of describing it. According to Harrison et al (1998), perceived deep-level diversity refers to how different individuals are in a team in terms of different characteristics: personality, values and attitudes. Team members also differ from each other in terms of knowledge, skills and abilities (Rink & Ellemers, 2010). Perceived deep-level and perceived surface-level diversity are very different from each other. Perceived surface-level deals with more demographic characteristics which are explained over a brief exposure (e.g sex, age, race), while deep level variables are much different, refering to more of the underlying characteristics such as attitudes, values and personality of an individual (Bell, 2007). According to Phillips et al. (2006) surface-level diversity includes variables such as race/ethnicity and deep-level diversity refers to more of an individual's experiences, preferences and/or values. The same can be said for these authors, deep-level alludes to one's own values and attitudes and how it is different from other members in a particular group (Jackson et al., 1995; Harrison et al., 2002).. 13.

(24) Perceived surface level or some researchers call it demographic attributes, are those that are immutable or fixed, unable to be changed over time, and that can be easily detected within a short time of interaction with an individual. While deep-level or personal attributes are mutable or liable to change, and are those psychological and interpersonal characteristics(e.g status, knowledge, behavioral style) which can change as a result of socialization process (Jackson et al., 1993). Both of these attributes can influence the team process, both of these are associated with some kind of characteristic behavior. People in the short term categorize other individuals based on what they can see on the surface, sex, race, age, while it is harder to see what is under the surface hence, deep-level diversity (Jackson et al., 1993). So according to these definitions of perceived deep-level diversity, this research will follow its own definition that deep-level diversity is how one differs from another in the same group, based on their personal differences such as values, knowledge, attitudes and personality.. Previous Studies of Perceived Deep-level Diversity There has been many studies done on perceived deep-level diversity, some of them have been done on samples of employees in the workplace and others as undergraduate students in universities. Harrison et al. (1998) continued the research on surface and perceived deep-level diversity(PDD). What they examined was that perceived deep-level diversity (personality, values) over time were more important than surface-level on group cohesiveness, in a sample of employees working in a hospital. Harrison and colleagues (2002) again looked at the two types of diversity. Looking at the same elements of both variables (age, gender and personality, values) respectively but this time expanded their outcome variable to include team social integration which was linked to team performance as a whole. Because team cohesiveness was a component of team social integration it added more contribution for their study. They found that in the beginning surface-level is important for forming a bias and stereotype for individuals but as they spent more time, deep-level values became more important and positively affected team social integration more than surface-level. The sample looked at were undergraduate and graduate students.. 14.

(25) Newell et al. (2008) expanded their study on surface-level and perceived deep-level diversity to include Virtual Teams. They examined perceived deep-level diversity and how it affected team social integration, and subsequently effect of team social integration on performance. They found that team social integration does positively affect team performance and there is a decrease in how perceived deep-level diversity affects social integration, in a sample of students. Liao et al. (2006) examined how perceived deep-level dissimilarity impacts on job attitude, turnover, helping and work withdrawal. They found that extraversion and agreeableness for perceived deep-level diversity held up to their hypothesis testing in both their sample testing. Their hypothesis testing found that socially oriented personality elements of Extraversion and Agreeableness are more related to an individual's interpersonal comparison between himself/herself with other group members. Liao et al.'s (2006) research model only explain a fair amount of difference in perceived deep-level dissimilarity, indicating that personality dispositions do not account for the full picture. Mohammed and Angell (2004) examined perceived surface and perceived deep-level diversity. Perceived deep-level diversity elements which were looked at were Extraversion and Time Urgency. The study was done on student project teams in a longitudinal design with the moderating effect of team process and relationship conflict. They found that team process was able to weaken the effects of perceived deep-level diversity (time urgency) on relationship conflict.. Components of Perceived Deep-level Diversity Different researchers have used different variables to study perceived deep-level diversity. Harrison et al. (1998) measured cohesion using satisfaction with work and satisfaction with supervisor, the study sample were employees of a medium private hospital. As for Harrison et al. (2002), the researchers' study focused more on students, more specifically undergraduate students. Harrison et al. (2002) used students as their sample, therefore, different measures were used to measure their deep-level diversity and social integration (e.g. personality, values and attitudes). Chang (2009) examined individuals' differences in teams using perceived personality, values and attitudes as measures on the outcome of work groups.. 15.

(26) Bell's (2007) meta-analysis revealed specific variables under perceived deep-level diversity which include personality factors (five-factor model of personality), values and abilities. These were used to identify deep-level variables which were related to team performance (Bell, 2007). In that study, some Big Five personality variables that were significant are, extraversion, agreeableness, conscientiousness and openness to experiences which had a moderate relationship with team performance. But these were done mostly in a lab setting so it may differ when in a field setting. Mohammed and Angell (2004) also compared perceived surface and perceived deep level diversity, for their deep level variables they focused on extraversion and time urgency. Extraversion refers to individuals tendencies to be sociable, assertive and talkative. Time urgency refers to different members perception of deadlines, time awareness and rate at which a task must be performed and completed. According to Barrick and Mount (1991) and Harrison et al. (2002), out of the Big Five dimensions, conscientiousness was the most consistent and most strongly related to the performance of an individual. But Liao et al. (2008) said that conscientiousness does not offer a clear prediction as how it will influence an individuals' dissimilarity perception so they used it as a control variable. They instead focused on extraversion, agreeableness and neuroticism and the results showed that both extraversion and agreeableness are more dependably related to a person's interpersonal comparison between his or herself with the other members on deep-level characteristics, while neurotic people generally have a negative view of the world and thus may not feel they are more different from other team members but tend to have a negative job attitude overall. Chang (2009) examined diversity on work group outcomes, results showed that diversity could hinder the development of in-group relationships. Based on literature presented, this study will follow Harrison et al. (2002), Chang (2009) and Liao et al. (2008), to investigate on the effect of perceived deep-level diversity element (values) affecting team social integration. Values was chosen as the deeplevel diversity element because it differentiated itself from other elements since personality and attitudes are somewhat similar and each person's value is different.. The Effect of Perceived Deep-level Diversity on Team Social Integration Perceived deep-level diversity has been done by different researchers on a number of topics, such as, perceived deep-level diversity (PDD) on team social integration and performance (Newell et al., 2008). Newell et al. (2008) found that for their PDD elements 16.

(27) (general deep-level attributes, task-relevant attributes) negatively impacted social integration. They observed that their sample, Virtual Teams, distinguished between the different attributes, which may be due to the fact that they do not meet face-to-face and only meet virtually. They also found that, it is possible to influence perceptions of deep-level diversity which influences team work through e-identity profiles. According to Saji (2004), they found that it is important for diversity in teams which achieved better results. Increased social integration was a result of task meaningfulness and task outcome knowledge. There was higher correlation between perceived-level diversity and task related elements than value related or personality related elements. Harrison et al. (1998) and Harrison et al. (2002) have found that perceived-deep level diversity (personality, values and attitudes) at the beginning actually had a negative relationship with how groups get along, but as time went by, as they spent more time with each other, the relationship became the opposite, meaning that they had a positive relationship. One reason why this could happen, the authors found, is that they had not enough time to learn about the other members' personality/ values or they did not show and wanted to mask their real personality until a later time, this could affect team social integration at the beginning but improve over time. For Liao et al. (2006), they controlled effects for actual and perceived surface-level and deep-level diversity and found that it was negatively related to someone's overall job attitude. Since not all studies mentioned above followed the same sample this study will use the sample of students and translate that into how it may affect them in the workplace. So this study will adopt Harrison et al.'s (2002) argument that perceived deep-level diversity on values will affect team social integration. Below is the hypothesis: Hypothesis 2. Perceived deep-level diversity will affect team social integration. 17.

(28) CHAPTER III METHODOLOGY This chapter will introduce the methods and instruments that will be used to conduct this study. This chapter will also include the research framework, procedure, design, data collection and measurements.. Research Framework Figure 3.1 Research Framework. This showed the relationship between the variables in this study. There are two independent variables, perceived surface-level (including age, gender and race/ethnicity) and perceived deep-level diversity (values) and one dependent variable, team social integration (including team cohesion). All the variables mentioned above have all been proposed and reviewed in the literature review in chapter two. In this study, the researcher followed previously used instruments which have been tested and proven to be valid and reliable.. Perceived Surfacelevel Diversity Team Social Integration. Perceived Deeplevel Diversity. Figure. 3.1. Research framework. 18.

(29) Research Hypothesis. Hypothesis 1. Perceived Surface-level diversity will affect team social integration Hypothesis 2. Perceived Deep-level diversity will affect team social integration. Research Procedure This study has 10 steps in the research procedure to be conducted. This section shows the figure of research procedure and explains the steps of the procedure. In first step the, researcher identified the population or sample interested and the problem that is occurring in the society. Next the researcher examined and reviewed the literature to find out what are the variables and elements which claim to affect the problem positively. After reviewing the literature and identifying out the variables, the next step was be to develop the research topic look and develop the purpose and the importance of the research. The research framework and hypothesis were developed based on the literature review and modified where needed. The instruments used to measure the variables were identified through the literature used in the study. None of the measurements were modified but will be modified if necessary. A pilot test was done to measure the validity and reliability of the measurements. After the pilot test the instruments was reviewed and modified where necessary. Next, we collected data for the main study and ran the analysis for the data collected. Last, we gave the conclusion and some suggestions for future studies. Below is the figure 3.2 will show the Research Procedure.. 19.

(30) Step 1: Identify problem and population interested Step 2: Review of literature Step 3: Develop research topic and purpose Step 4: Develop research framework and hypothesis Step 5: Develop research instruments. Step 6: Conduct pilot test Step 7: Revise instrument Step 8: Collect data Step 9: Perform data analysis Step 10: Develop conclusion and suggestions. Figure 3.2. Research procedure. 20.

(31) Research Design This section talks about the overall design of the study. This study carried out a quantitative research by means of survey questionnaire. This was used to collect the data on measures of perceived surface-level and perceived deep-level diversity and team social integration. Participants filled out a questionnaire assessing their perceived level of the different diversity and team social integration. Statistical analysis tools was carried out to arrive at the study's findings and conclusion.. Sampling and Data Collection A cross-sectional design was used by collecting data from participants from schools in Taiwan. The participants that were investigated are students, to be more specific, undergraduate and graduate students. The students were from mainly northern Taiwan (e.g. Taipei city, New Taipei City, Taoyuan, Keelung, Hsinchu) and some from other cities around Taiwan. The participants were expected to have previous team or group experience in school from team assignments or group projects. The participants could have been in any discipline in any department, as long as they had previous team experience which was not less than one month and at least three members in the team was the acceptable criteria for the study. The study targeted students' perception on each individual in their team/group based on items in the survey questionnaire. This study used convenient sampling. Data were collected from internet and social media as well as hard copy questionnaires. Online and social media included Face Book and Google surveys.. 21.

(32) Sample Profile For the full study, a total of 227 questionnaires were returned (175 online, 52 hardcopy). After removing questionnaires because of missing sections and not meeting the criteria, if participants had less than 1 month experience in a group they did not meet the criteria, a total of 207 questionnaires were useable for the study, 18 respondents had less than 1 month experience and 2 had missing sections. The demographics of the participants are described below. The majority of people who answered were between 18 and 27 years of age, that is 77.8% of the total participants, also there were 2 missing data for age. As for gender there were almost double the amount of females to male who responded, male 35.7%, female 64.7%. The majority of people were of Asian background 81%. As for the number of people in each group, there was quite a spread of number, 3-person group = 4.3%, 4-person group =19.3%, 5-person group = 16.9%, 6-person group = 23.2 % and 6(+)person group = 36.2 %. As for the class type, there were four types which stood out among the rest, Freshmen = 20.3%, Seniors = 16.4%, Master-first years = 21.2% and Mastersecond years = 27.5%. The majority of people spent more than 4 months in a particular group at 65.2% and the majority of people had many experiences being in a team or group environment at 56.5%. There were students from 57 majors because of so many majors, only half of the percentage were included which included MBA's, Banking/Finance/Statistics, applied English, engineering, tourism and management and information management. A full summary of the sample characteristics is shown below in Table 3.1.. 22.

(33) Table 3.1. Descriptive Statistics on Sample Characteristics (N=207) Item Category Frequency Age 0 2 18-22 79 23-27 82 28-32 31 33-37 8 38-42 3 43-48 2. Percentage (%) 1 38.2 39.6 15.0 3.9 1.4 1.0. Gender. Male Female. 74 133. 35.7 64.3. Race/Ethnicity. Asian North American Central and South American European African Middle East. 168 3 18. 81.2 1.4 8.7. 8 9 1. 3.9 4.3 0.5. Size of Team. 3 persons 4 persons 5 persons 6 persons 6+ persons. 9 40 35 48 75. 4.3 19.3 16.9 23.2 36.2. Class Type. Freshman Sophomore Junior Senior Master-First Year Master-Second Year Master-Third Year and Above. 42 9 2 34 44 57 19. 20.3 4.3 1.0 16.4 21.3 27.5 9.2. Length of time in team. 1-2 Months. 30. 14.5. 3-4 Months More than 4 months. 42 135. 20.3 65.2. 11 30 49 117. 5.3 14.5 23.7 56.5 (Continued). Times been in a team Once Few times (2-3) Lots of times (4-5 Many times (6+). 23.

(34) Table 3.1. (Continued) Item Category Major MBA Banking/Finance/Statistics Applied English Engineering Tourism and Management Information Management. Frequency 40 20 12 12 11 10. Percentage (%) 19.3 9.7 5.8 5.8 5.3 4.8. Method of Data Analysis Descriptive Statistics Since this study did not use random sampling method, descriptive statistics helped to calculate the important features of the data such as sample mean, mode, standard deviation (SD), demographics and others. Descriptive statistics was very helpful for the study as it helped to summarize and describe the important features of the data collected.. Factor Analysis The study conducted Exploratory Factory Analysis (EFA) in SPSS and Confirmatory Factor Analysis (CFA) in AMOS for construct validity of the measurements. EFA was used to differentiate properties in the data collected. It was also used to check for common method variance (CMV). Harmon's single factor test is observed in EFA, this was used to check for common method variance (Podsakoff & Organ, 1986). CMV comes about when two or more measures derive from the same source. Some recommendations to minimize CMV include reordering scale, while varying the measurement scales. On the other hand CFA is a statistical tool used to observe relationships among latent variables (Jackson, Gillaspy Jr., & Purc-Stephenson, 2009) and evaluates the study's hypothesis. To utilize CFA the researcher was required in advance to hypothesize a number of factors and identify whether or not those factors were correlated. In sum, CFA tests whether the data collected matches the theorized measurement model of a variable.. Correlation Analysis In this study, Person's Correlation analysis was used to test the relationship between variables. This method results in correlation coefficients which enables the observation of. 24.

(35) how significant one variable is related to another variable. This allows for the observation of positive significance or negative significance and strengths between the variables.. Hierarchical Regression Analysis Hierarchical regression is a tool used for analysis when variance on a criterion variable is being explained by predictor variables that are correlated with each other (Lewis, 2007). So hierarchical regression was used to test the hypothesis in the study and check if there are other predictors which may affect the dependent variable.. Structural Equation Modeling (SEM) Structural equation modeling or SEM is a statistical procedure that is used to test and estimate causal relationships (Jackson et al., 2009). This technique uses both causal assumptions and statistical data. The data that was collected for this study was analyzed using AMOS, which is a type of SEM in SPSS. The difference with AMOS is that it automatically includes estimation of variances for all your independent factors. It also allows for CFA and creating path diagrams (Byrne, 2013). AMOS uses the maximum likelihood estimation as the default feature (Byrne, 2001). Deep-level diversity and Team social integration were ran independently in AMOS for CFA. The outputs which had the highest values for interest included χ2/df, RMR, GFI, AGFI, RMSEA, CR and AVE to examine the measurement models goodness of fit. The χ2/df refers to the chi-square divided by degrees of freedom. RMR is the root mean square residual which is an indicator of how much estimated covariance and variances are different from the observed ones. GFI or goodness of fit is a value that analyzes the proportion of variance that is accounted for by the projected population covariance. AGFI or the adjusted goodness of fit is the index of adjusted GFI. RMSEA or root mean square error of approximation compares the lack of fit to the saturated model (Hooper, Coughlan, & Mullen, 2008). Below is Table 3.2 which shows the criteria and acceptable cutoffs for the model fit. Surface-level diversity was not ran in SPSS AMOS as it is a non-latent variable.. 25.

(36) Table 3.2 Index of Model Fits χ2/df. Root mean square error or approximation (RMSEA). Good fit 2-5 0≤2 <.08 0 ≤ .05. Acceptable fit <5. Author's notes. .08 - .1 .05 ≤ .08. > .95 > .95. 0 - 1.0 > .90. < .03 indicates excellent fit. .08 ≤ .10 (mediocre fit); >.10 poor fit. The higher the value the better the model fit. Goodness-of-fit (GFI). Adjusted-goodness-of-fit (AGFI) Root mean square residual (RMR). > .90 .90 > .90 > .85 < .05 ≤ .08 The smaller the 0 indicates perfect value the better the fit. fit Note. Summary based on Hooper, Coughlan, and Mullen (2008) (top rows) and Schermelleh-Engel, Moosbrugger, and Müller (2003) (bottom rows). Adopted from Cleveland (2015).. Measurements The questionnaire used in this study used different measurements for each variable. The next section goes into detail each instrument of measurement that was either adopted or adapted. Below are the descriptions of each of the measurement and written in order as presented in the full scale study.. Team Social Integration (TSI) For the dependent variable it was adopted using Carron, Widmeyer and Brawley's (1985) team cohesion questionnaire which included 9 questions. The statements in the questionnaire asked respondents to rate their level of cohesion and satisfaction in their team experience. An example statement is, "our team is united in trying to reach goals for performance". Items were scored on a 7-point Likert scale (1 = Strongly Disagree; 7= Strongly Agree). The internal consistency of the measure was acceptable ranging from .63 to .81 (Carron, Widmeyer & Brawley, 1985).. Perceived Surface-level Diversity Perceived Surface-level diversity measures was adopted using Chang's (2009) measurements. This measurement asked respondents to rate their level of difference in terms 26.

(37) of age, gender and race/ethnicity in their team experience. An example statement is, " How diverse do you think your team members are to you in terms of age". If , for example, the group/team had a total of six members including the rater, the rater will answer this five times with his/her perception of that team member in relation to their age/gender/race or ethnicity, the responses would then be averaged to have an overall individual-level measure of perceived variability (Chang, 2009). The items were scored on a 5 point Likert scale (1= not at all different; 5= very different).. Perceived Deep-level Diversity The index of perceived deep-level diversity was adopted from Chang (2009) to operationalize diversity. The measurement asked respondents to report on a 6-point scale ranging from very much like them to not like them at all scale regarding how similar they thought they were on average to their group members (1 = very much like them; 6 = not like them at all). They were given 5 statements and each statement described a person in which they had to report how similar they were to their group member. An example statement is "It is important to them to be in charge and tell others what to do. They want people to do what they say". The internal consistency for the measurement was high in previous studies and. accepted. Similar to perceived-surface level indices, the rater would indicate based on their perspective how different the individual is compared with themselves.. Control Variables There were nine demographic questions in total and out of the nine, three questions were used as control variables. Team size according to Harrison et al., (2002), Mohammed & Angell, 2004), Newell et al. (2008), Liao et al. (2008) and Chang (2009) is used as a control variable in this study. A larger group may have more potential for more heterogeneity and size may influence cohesion and performance. Mohammed and Angell (2004) examined length of time in a team and times been in a team as control variables as the sample included undergraduate and graduate students. These two variables are also included in this study as control variables. Validity and Reliability Construct validity and content validity were used to measure validity in the study. Content validity refers to the extent at which a questionnaire reflects the indented domain of content, which means the instruments measure what they are meant to measure. Content validity was established for all measurements while the instruments were either adopted or 27.

(38) adapted from previous studies. A pilot test with a sample of 42 was conducted to check the validity and reliability of the measurements for the main study. This helped to improve the study's design before the main research was carried out. While doing the pilot test and the main study, exploratory factor analysis (EFA) was used to examine the factor structure and the threat of common method variance (CMV). Construct validity was also carried out in the main study using confirmatory factor analysis (CFA). The results of both EFA and CFA are reported below. Reliability analysis was also run for both the pilot and the main study. Cronbach's alpha reliability test was used to measure the internal consistency of the measurements.. Exploratory Factor Analysis Exploratory factor analysis was conducted to observe the factor and cross factor loadings of the measurement items in the study. Using EFA, a Harmon's single factor test was done on the items to observe common method variance for each survey which was answered by individual sources, the unrotated variance accounted for was 24.17% which is below 50% as suggested by Podsakoff et al. (2003). In the pilot test, Team social integration and Deep-level diversity were ran through EFA and there were 4 factors extracted with an eigenvalue larger than 1 and a cumulative variance of 72.05%, the Kaiser-Meyer Olkin (KMO) was used to measure the adequacy of the sample and it had a value of 0.678 and the Barlett's test of Sphericity was .000 which is significant. In the pilot test the deep-level variables were grouped together so they measured the component well meaning that the items explained the measurement well and were not cross-loading into other variable items and team social integration was not grouped as well as deep-level diversity, which was an indication that the respondents saw team social integration as more as a multi-dimensional construct, below in table 3.3 and 3.4 is a table showing the Kaiser-Meyer Olkin and the rotated factor loadings respectively. Table 3.3. KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Approx. Chi-Square Bartlett's Test of Sphericity df Sig.. 28. .678 313.448 91 .000.

(39) Table 3.4. Exploratory Factor Analysis (EFA):Team Social Integration and Deep-level Diversity(Pilot Test) Factors Items 1 2 3 4 Deep-level 5 .842 Deep-level 2 .815 Deep-level 1 .806 Deep-level 4 .792 Deep-level 3 .774 Team social integration 9 .867 Team social integration 8 .812 Team social integration (R) 6 .651 Team social integration (R) 7 .838 Team social integration 5 .651 Team social integration (R) 3 .628 Team social integration (R) 2 .515 Team social integration 1 .907 Team social integration (R)4 .614 Note. Extraction Method: Principal Component Analysis. Note. (R) = A Reverse Question.. Confirmatory Factor Analysis Confirmatory factor analysis was ran on each set of items separately through AMOS. The results determined whether any modification is needed to improve the model fit. The purpose of CFA is to find if the data fit the theoretical model measurement. After running the items through CFA, it was then examined whether which items should be deleted to meet the criteria. After the removing of items the modified list of items were ran again through CFA. If the new list met the criteria of the model fit, it would normally be ran against another collection of data to cross validate. Though, items in this research could not undergo this procedure because of time and resource constraints. Nonetheless, the study's data sample was randomly separated into two groups and cross validated in this method as suggested by other researchers (e.g. Blunch, 2013; Browne, 2000), which yielded a sample comparison of model fit output. CFA for team social integration. The results from the EFA showed that 3 factors were classified into 3 dimensions for Team social integration. The data was categorized and sorted in CFA based on the classifications and dimensions from the pilot test EFA. In CFA, factor 1 had questions TSI 9, TSI 8 and TSI(R)6, factor 2 included questions TSI(R) 7,. 29.

(40) TSI(R) 2, TSI 5 and TSI(R) 3 and factor 3 included questions TSI 1 and TSI(R) 4. Out of the nine items, two were deleted by examining the modification indices (M.I) in CFA. TSI 5 question had high M.I with different questions so the model fit would improve if it is deleted. TSI 9 also had high M.I with other questions and would improve the model fit if deleted. A summary of the original and modified model fit is shown below in table 3.5 and figure 3.3 shows the standardized regression weights for the modified items and other important values.. Figure 3.3. Team social integration CFA measurement model. Table 3.5. Team Social Integration Model Fit Summary TSI χ2 df P χ2/df RMR Full items (list 9) Modifi ed items (7). GFI. AGFI. RMSEA. AVE. CR. 286.431. 27. .000. 10.61. .18. .77. .61. .22. .40. .83. 59.345. 14. .000. 4.24. .07. .92. .84. .13. .50. .87. 30.

(41) After removing the two questions the model fit improved and all the other criteria improved such as GFI (.921), AGFI (.842), χ2/df (4.24). Since the measurement model was modified based on data instead of a theory, the researcher conducted a cross-validation of the modified measurement model. The cross-validation was achieved by splitting the sample randomly into two groups and performing a multi-group comparison on the modified team social integration measurement model. The result of the multi-group comparison of team social integration items was shown in table 3.4. The p-values show insignificances indicating constraining the two randomly split samples as equal does not significantly worsen the model fit. The modified measurement model was successfully cross-validated with two samples. To see a list of the items of team social integration which were deleted, refer to table 3.5 Table 3.6. Multi Group Comparison for Cross Validation of Measurement Model TSI DF. CMIN. P. NFI Delta-1. IFI Delta-2. RFI rho-1. TLI rho2. 4. .521. .971. .002. .002. -.044. -.051. Measurement intercepts. 11. 9.772. .551. .030. .033. -.072. -.082. Structural weights. 14. 10.801. .702. .034. .037. -.090. -.103. Measurement residuals. 21. 15.540. .795. .048. .053. -.117. -.135. Model Measurement weights. Table 3.7. Team Social Integration Variable Items Item Description TSI 1 Our team is united in trying to reach its goals for performance TSI 2 I’m unhappy with my team’s level of commitment to the task TSI 3 Our team members have conflicting aspirations for the team’s performance TSI 4 This team does not give me enough opportunities to improve my personal performance TSI 5 Our team would like to spend time together outside of work hours TSI 6 Members of our team do not stick together outside of work time. Status. SDW .36*** .34*** .76***. Deleted (Continued). 31.

(42) Table3.7. (Continued) Item TSI 7 TSI 8 TSI 9. Description Members of our team would rather go out on their own than get together as a team For me this team is one of the most important social groups to which I belong. Some of my best friends are in this team.. Status. SDW .73*** .25**. Deleted. Note. SDW = Standardized Regression Weights. CFA for perceived deep-level diversity. CFA of the 5 items of perceived deep-level diversity yielded acceptable indices for the goodness-of fit index; χ2/df (15.09), RMR( .04), GFI(.97), AGFI(.92), RMSEA(.09), AVE(.43) and CR(.73). Below is figure 3.4 showing the perceived deep-level variable measurement model and table 3.8 showing perceived deeplevel diversity model fit summary. Also table 3.9 shows the perceived deep-level variable items.. Figure 3.4. Perceived deep-level diversity CFA measurement model.. 32.

(43) Table 3.8. Perceived Deep-level Diversity Model Fit Summary χ2 χ2/df PDD df P RMR Full items 15.099 5 .000 3.02 .04 (list 5) Note. PDD= Perceived Deep-Level Diversity. GFI. AGFI. RMSEA. AVE. CR. .97. .92. .09. .68. .73. Table 3.9. Perceived Deep-Level Diversity Variable Items Item Description Deeplvl1 It is important to them to be in charge and tell others what to do. They want people to do what they says Deeplvl2 Thinking up new ideas and being creative is important to them. They like to do things in their own original way Deeplvl3 It's very important to them to show their abilities. They want people to admire what they do Deeplvl4 Having a good time is important to them. They like to “spoil” themselves Deeplvl5 They like surprises and is always looking for new things to do. They think it is important to do lots of different things in life Note. SDW = Standardized Regression Weights. SDW and t-value .54. .70***. .77***. .58*** .67***. Alpha Coefficient Test To measure internal consistency, an alpha's coefficient test is necessary to measure the reliability for each variable. Cronbach's Alpha is the test ran on the measurement items. After the items were ran through CFA the items were then ran through IBM SPSS Cronbach's Alpha to check the internal consistency reliability. Team social integration and perceived deep-level diversity passed the acceptable threshold of .70 for Cronbach's Alpha while perceived surface-level diversity did not meet the criteria. The perceived surface-level diversity questions were formative so not appropriate to put them through an internal consistency test. There are some researchers which say there is a rule of thumb about the acceptable. range. of. the. alpha. value,. .90=excellent,. .80=good,. .70=acceptable,. .60=questionable, .50=unacceptable (Gliem & Gliem, 2003). So the 0.61 value for surfacelevel diversity could be acceptable in some studies. The Cronbach's Alpha results are shown in Table 3.10.. 33.

(44) Table 3.10. Cronbach's Alpha Variables Team Social Integration Perceived Surface-level diversity Perceived Deep-level diversity. Cronbach's Alpha 0.715 0.614 0.788. 34.

(45) CHAPTER IV DATA ANALYSIS AND FINDINGS This chapter shows the outcome of the various data analysis conducted for the study. Pearson's Correlation Analysis was used to examine the association between the variables and Hierarchical Regression Analysis was used to test the relationship between the hypotheses.. Pearson's Correlation Analysis Pearson's correlation analysis was conducted to examine the association between each pair of variables in this study, and the results showed both expected and unexpected findings in table 4.1. Results showed that there was a significant positive correlation between perceived surface-level age and perceived deep-level diversity (PDLD) (r= .27, p<.01), perceived surface-level gender and PDLD (r= .15, p< .05) and perceived surfacelevel diversity race/ethnicity and perceived deep-level diversity (r= .21, p< .01) thus conveying that students may have a bias or stereotype when working with people who come from a different background. There was a significant negative correlation between perceived surface-level diversity and Team Social Integration (r= -.20, p< .01). There was also a negative correlation between perceived deep-level diversity and Team Social integration, but it is not significant (r= -.13, n.s), a negative correlation between Surface-level diversity age and TSI (r= -.15, p<.05), a negative correlation between Surface-level diversity gender and TSI (r= -.13, n.s) and a significant negative correlation between Surface-level diversity race/ethn and TSI (r= -.18, p< .01). Table 4.1 shows that both independent variables have a positive correlation with each other but both have a negative correlation with the dependent variable team social integration, also that perceived surface-level diversity was negatively correlated and had a negative significant relationship with team social integration (r= -.21, p< .01) whereas perceived deep-level diversity did not. One of the control variables, length of time in a team, is positively correlated with how many times you have been in a team. Length of time in a team is also positively correlated with team social integration (r= .18, p<.01). So it seems the longer you spend in a team environment with the group members, the better the integration will be. The other control variables do not seem to affect the dependent variable at all so there is no significant relationships between them. Even though there are some studies which show a positive correlation between surface level, deep level diversity and team social integration, according to Harrison et al. (1998) and Harrison et al. (2002) surface-level diversity at the beginning 35.