Am I seen the way I am?

Am I seen the way I am?

The Effect of Age Stereotyping on Relationship Quality and Knowledge Transfer in an Age-diverse Work Team

Master thesis

MSc Human Resource Management,

University of Groningen, Faculty of Economics and Business

Rita Simonavičiūtė S2539284 Planetenlaan 451 9742HR Groningen Phone: 0650733787 E-mail: r.simonaviciute@student.rug.nl

Supervisor: Dr. Floor Rink

January 18, 2015

Abstract

This study investigated whether negative a priori age stereotyping reduces relationship quality and consequently obstructs knowledge transfer process within age-diverse work team. Data were gathered using an online survey where respondents (N=109) were presented with a pre-test, measuring their implicit age stereotyping, followed by a scenario-based questionnaire about remaining variables of the study. The data were analysed using SPSS software. Results reveled age stereotyping does not diminish the quality of the relationship among members of the age-diverse team and that age diversity does not obstruct knowledge transfer. However, the investigation also revealed that perceived individual differences, an extra variable used in this study, increase knowledge transfer as well as relationship quality within age-diverse team. These findings imply that age diversity and age stereotyping do not have such as negative impact on knowledge transfer within work teams as expected. This research thus sheds a new light for future research and offers new perspectives for companies about how to manage age-diverse work teams.

Keywords: age diversity, age stereotyping, relationship quality, knowledge transfer, age-diverse work-team; perceived individual differences

TABLE OF CONTENTS

THEORETICAL FRAMEWORK AND HYPOTHESES ... 6

Knowledge transfer and ageing workforce ... 6

Age diversity in a workplace ... 7

A Social Identity theory and knowledge transfer in an age-diverse team ... 9

Relationship quality and knowledge transfer in an age-diverse team ... 10

Age stereotyping and knowledge transfer in an age-diverse team ... 11

METHOD ... 13

Design and participants ... 13

Measures ... 16

RESULTS ... 19

Summary and Results ... 24

Theoretical Implications ... 25

Limitations and Future Research Directions ... 26

Practical Implications ... 29

Final conclusion ... 29

REFERENCES ... 31

Demographic ageing of the working population is a known fact in today’s knowledge-driven economies. Organizations feel the demographic change in terms of later retirement and an increase in older workers as well as a shortage and need of younger qualified employees (Baltes, Finkelstein, Kunze, Boehm & Bruch, 2011). Consequently, the increasing heterogeneity in teams (age diversity) leads to challenges for companies (Ellwart, Bündgens & Rack, 2013). Research demonstrates that age-diversity of a workforce in organizations lowers relationship quality amongst employees (Krueger & Rothbart, 1988) because of their age differences. As a result, relational problems can then obstruct the transfer of knowledge between older and younger employees (Stam, 2009; Rink & Jehn, 2010). For example, even though older employees possess knowledge and experience useful within groups, they will not share it unless positive relations among members are prevalent and different types of contributions are appreciated (Shore, Chung-Herrera, Dean, Ehrhart, Jung, Randel & Singh, 2009). This is especially true, if age stereotyping affects the relationship quality among age-diverse team members, since it influences the strength of the relationship between employee age and outcomes for employees and organizations (Posthuma & Campion, 2009, p. 18).

employees might be influenced by age stereotypes they hold against each other..

One suitable and well-established approach to investigate the above-introduced problem is the social identity theory. Social identity refers to the part of individuals’ self-concept that is derived from membership in certain social groups and think of themselves in terms of those groups (Tajfel, Biling, Bundy & Flament 1971; Rink & Jehn, 2010). According to the social identity theory, social criteria (age, in the case of this study) divide people into ‘us’ and ‘them’, into in-groups and out-groups and shape intergroup behaviour (Tajfel et al., 1971). This theory, thus, helps to explain why age-diverse workforce might suffer from relationship problems and, as a result, is expected to obstruct the transfer of knowledge between older and younger employees (Krueger & Rothbart, 1988, Rink & Jehn, 2010; Van Selm & Van der Heijden, 2013). Moreover, based on this theory, one can also predict that the extent to which employees hold stereotypes about their different age group colleagues determines the strength of the relationship among those individuals. Employees who do not hold strong stereotypical beliefs about different age group members of their team, may not experience the relationship problems caused by age differences as severely as those who do hold clear stereotypical beliefs. The key goal of this study is thus to examine how age stereotyping affects relationship quality and knowledge transfer in age-diverse work teams.

Moreover, it will provide companies in both private and public sectors with an opportunity to learn about the conditions under which age stereotyping influences the relationship quality among their age-diverse employees. Increased understanding of the above-stated issues will, in turn, help companies to manage their age-diverse human resources effectively and to reach competitive advantage.

Theoretical Framework and Hypotheses

In this section of my study, a theoretical framework of the current research will be drawn. The concepts used will be introduced, defined and analyzed and the hypotheses will be raised.

Knowledge transfer and ageing workforce

In today’s organizations, knowledge is regarded to as a highly critical resource that forms a basis of a firm’s competitive advantage (Argote & Ingram, 2000). An organization willing to transfer critical knowledge is an organization able to retain this knowledge and to improve its workforce (Stevens, 2010). Knowledge transfer can be defined as “the process through which one unit (e.g. group, department, or division) is affected by the experience of another” (Argote & Ingram, 2000, p. 151; Inkpen & Tsang, 2005, p. 148; Watson & Hewett, 2006, p. 142)

databases (Hau & Evangelista, 2007). Tacit knowledge is seen as unique work-related knowledge and skills that are difficult to explicitly formalize or regulate and is residing within an employee (DeLong, 2004; Stam, 2009).

As knowledge-intensive work today is much more interdisciplinary, often requiring the integration of expertise across a wide range of subjects (DeLong, 2004, p. 16) it makes knowledge itself more complex and in turn more difficult to transfer (Stam, 2009). Another obstacle to knowledge transfer besides knowledge complexity is intense ageing of the workforce (DeLong, 2004). Between 1992 and 2012, the proportion of working-age population (15-64 years) in the EU-27 increased by 0.5 percentage points, while the proportion of older population (aged 65 and above) increased by 3.7 percentage points (European Commission, 2013). Needless to say, the increasing ageing of the workforce is relevant not only for European Union, but is a global issue. The unavoidable retirement raises important issues for firms, both in terms of the replacement of retirees as well as the knowledge transfer involved (Ebrahimi, Saives & Holford, 2008). Organizations might face a serious knowledge shortage and knowledge loss that will threaten the organizations’ ability to make knowledge productive and this ability is becoming more dependent on the capabilities of older employees (DeLong, 2004; Stam, 2009). In order to avoid these issues and maintain the knowledge productivity within the organization, it is necessary to enable successful knowledge transfer between younger and older workers.

Age diversity in a workplace

determining best the methods to transfer knowledge. As noted by Ellwart et al. (2013, p. 951), across multiple studies age diversity is referred to as “the degree to which age related characteristics are objectively different or subjectively perceived as different between people within the same age group” (Van Knippenberg & Schippers, 2007; Harrison & Klein, 2007; Van Dick, Van Knippenberg, Hagele, Guillaume & Brodbeck, 2008).

Ageing individuals possess various kinds of knowledge and “know-how”, which Ebrahimi et al. (2008, p. 129) see as an “incorporated individual memory of a network of resources that is inscribed within their tacit knowledge and can be activated depending on their role in the organization”. They also state that it is the life experience of older workers, their in-depth knowledge of different professional environments (network of contacts), their knowledge of the culture of these environments (knowing how to deal with whom) that provides them with more tacit knowledge than younger workers. As a result of these above mentioned specific competencies, ageing employees have differentiated aptitudes to “understand issues, interpret information, connect various information and data, integrate knowledge, and finally, connect and coordinate knowledge carriers” (ibid).

However, because of this complexity of the tacit knowledge (Fang, Yang & Hsu, 2013) as well as retirement and turnover risk of older employees, companies around the globe encounter the fear of “knowledge loss” (Liyanage, Elhag, Ballal & Li, 2009: 118). Bae & Koo (2008: 230) explain that this loss is a result of the incomplete transfer of knowledge in a social network (e.g. company, among colleagues), where knowledge is lost unintentionally or becomes distorted during the knowledge transfer process. Therefore, age diversity becomes an issue that needs to be taken into account in order to ensure the fluent transfer of knowledge.

A Social Identity theory and knowledge transfer in an age-diverse team

Knowing that age diversity might affect knowledge transfer within multigenerational work team negatively, we still need to find out under which conditions it is the case. In order to investigate the above stated situation, the social identity theory will be used.

Social identity theory refers to the part of individuals’ self-concept that is derived from membership in certain social groups (Tajfel et al., 1971). Social identity includes the aspects of an individual’s self-image that derive from the social categories to which he/she belongs, as well as the emotional and evaluative consequences of this group membership, encompassing salient group classifications (Ashforth & Mael, 1989; Hornsey, 2008). In other words, when individual identifies with or is categorized as members of a social aggregate, he/she is more likely to define him/herself with regard to his/her membership of that group (Kane et al., 2004). There is substantial evidence that group members also view their group (in-group) members more positively than out-groups members (Hewstone, Rubin & Willis, 2002). People evaluate in-group members as trust-worthier, more honest, loyal, cooperative, and valuable to the group than out-group members. As a result of these evaluations, individuals may feel more comfortable sharing knowledge with groups with whom they share a social identity than with groups with whom they do not share social identity.

more intergenerational conflict they experience with younger workers and the more they are inclined to retire early (Desmett & Gaillaird, 2008).

Relationship quality and knowledge transfer in an age-diverse team

According to Nonaka (1994), tacit knowledge cannot be transferred through formal learning and training, but only by means of shared and collaborative experiences, and requires participation and “doing together”, implying that the transfer of knowledge will be difficult to achieve if the relationship among workers is suboptimal (Taüber et al., 2013). This notion has already been supported empirically: meta-analytic research shows that relational aspects are among the most important predictors for tacit knowledge transfer between employees (ibid). The three aspects most commonly associated with relationship quality are tie strength, trust and feeling valued (Foos, Schum & Rothenberg, 2006; Van Wijk, Jansen & Lyles, 2008).

Tie strength shows how close a relationship between two employees is. Previous researchers operationalized the tie strength as a combination of closeness and interaction frequency (Granovetter, 1973; Hansen, 1999; Marsden & Campbell, 1984), meaning that frequent communication will increase closeness and consequently the tie strength which will then lead to greater transfer of tacit knowledge (Van Wijk et al., 2008).

Feeling valued, one more component of relationship quality, could be seen as shared representations, interpretations and value systems (Täuber et al., 2013). In other words, this component reflects shared norms and values that facilitate a common understanding of collective goals and proper ways of acting in a social system (Tsai & Ghosal, 1998). Feeling valued stimulates tacit knowledge transfer because it promotes mutual understanding and provides a crucial bonding mechanism the helps different actors to integrate knowledge (Van Wijk et al., 2008).

In conclusion, in order to ensure a fluent knowledge transfer within multigenerational team, the relationship quality among older and younger workers is of key importance and should be characterized by above-enlisted aspects, namely, mutual trust, respect and valuing each other. This leads me to propose the following hypothesis:

Hypothesis 1b: The relation between age diversity and the transfer of knowledge is mediated

by the relationship quality.

Age stereotyping and knowledge transfer in an age-diverse team

The remaining goal of this study is to discover under which circumstances these above mentioned relations are more salient. I expect that a priori age stereotypes held against workers who belong to different age groups moderate the relation between age-diversity and the relationship quality amongst their heterogeneous members, possibly leading to obstruction of the transfer of knowledge, in case age stereotyping is negative.

inaccurate, or distorted opinions about people based on their membership in a particular group (Fiske & Neuberg, 1990). They are mostly preconceived ideas, or unfounded assumptions and incorrectly infer that all members of that group are the same (Fiske & Taylor, 1991). Table 1 depicts some most common age stereotypes held against both older and younger workers. It is important to note that in Table 1 stereotypes of one age group (e.g. older workers) are relative in comparison to other age group (e.g. younger workers) and vice versa. As can be seen, more negative age stereotypes are held against older people and more positive stereotypes are accounted for younger ones (Eichhorst et al., 2013; Hummert, 1990; Ng & Feldman, 2012).

--- Insert Table 1 about here ---

aggravate the transfer of tacit knowledge in age-diverse teams (Tillsely & Taylor, 2001). I therefore raise a hypothesis reflecting the expected effect moderator has in this study:

Hypothesis 2: Negative age stereotyping has a negative impact on the relation between age diversity and relationship quality.

In a nutshell, this study expects that the relation between age diversity and knowledge transfer is negative and is mediated by the relationship quality among younger and older workers. Moreover, age stereotyping moderates the relationship between age diversity and relationship quality, so that when age diversity is high and the team members hold strong a

priori related stereotypes against each other, the relationship quality within an

age-diverse team and subsequently the transfer of tacit knowledge, should decrease even more. When age diversity is lower or absent, the relationship quality among the younger and older employees will be better and the transfer of knowledge will not be obstructed, regardless of whether the members of that team hold strong a priori age stereotypes. The conceptual model of this study is depicted in the Figure 1.

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Method Design and participants

specifics of my survey, I expected a rather high dropout rate. I therefore approached as many people as possible, which led to a total of 259 participants who have filled in the survey. Of these individuals, only 154 participants (63%) completed the whole survey (determined on the basis of listwise deletion, Fields (2009)). However, 29.4% of those 154 failed the manipulation check. Therefore, after removing outliers and excluding the missing values, final sample N = 109. Of this final sample, 62.3% was female (Mage of all N = 26.44, S.D. = 5.51), 74,1% held a university degree (35.2% Bachelor’s and 38.9% Master’s). 57.9% worked full-time and had 1 – 3 years of work experience (42.65%) the rest of the sample was more experienced. Most (36.1%) of the working participants held “operational staff” position and worked for large (50 or more employees) organizations (46.7%%).

Implicit age stereotyping. To distinguish participants’ a priori age stereotyping status (the moderator of this research) I measured implicit attitudes towards older and younger people using the Age implicit association test (Age-IAT, Nosek, Smyth, Hansen, Devos, Lindner, Ranganath, Smith, Olson, Chugh, Greenwald & Banaji, 2007). During a first task of the adapted test, participants had to choose whether a word (out of a 16 words list) appearing on the screen belonged to a “good” category, e.g. “happy”, “wonderful”, or a “bad” category, e.g. “agony”, “horrible”. During the second task participants had to decide whether a picture of person showed on a screen belonged to an “old” category, or a “young” category. There were 12 pictures in total (3 with old females, 3 with young females, 3 with young males and 3 with old males).

bellow the category “young” while in the task 4, the category “good” was placed just bellow “young” answer category and category choice “bad” just bellow the “old” picture category. The respondents were explicitly asked to make their answer choices during all tasks as quickly as possible, since it was essential for calculation of the implicit age stereotyping measure.

I operationalized my independent variable (age diversity) as one factorial between subjects. I divided it between two cases (age diversity present or age diversity absent). A moderator (implicit age stereotyping) was a continuous measure.

Manipulation of age diversity. Participants were asked to imagine they were part of work team and had been working together with other team members for quite some time. They all were responsible for reaching a common goal. Depending on condition participants further learned that they were working in a team consisting of members who were all of the same age (age homogeneous condition), or in a team consisting of members who were all of a different age (age diversity condition). For complete descriptions of the scenarios, see Appendix A. This manipulation was checked at the final end of the questionnaire with the following question: “Was the team in their scenario case heterogeneous or homogeneous with respect to team members’ age?” (1 = Yes, 2 = No). 70.6% of the total sample answered this check correctly. The participants who have failed the manipulation check were left out of all the analyses.

Measures

Implicit age stereotyping. The implicit age stereotyping measure was calculated as follows. First, the mean values (M) of the last click records of tasks 3 (where picture choice category “old” was implicitly associated with the word choice category “good”) and task 4 (where category “old” for assigning pictures was implicitly associated with the category “bad” for assigning words) were found. Then the mean timing values of task 3 were subtracted from those of task 4; see the formula below.

Implicit age stereotyping = Mtask 3 last click time – Mtask 4 last click time

It is important to note that positive values of this measure indicate that respondents hold negative age stereotypes towards old people, i.e. participants spent more time assigning pictures or words to the correct category when “old” was associated “good”. You can access my full test using the following link:

https://groningen.qualtrics.com/SE/?SID=SV_6stK2oedoCWfuAJ

Relationship quality. The mediator of this study was measured by 12 items (α all variables = .93; adapted from Costa & Anderson (2010), Marsden & Campbell (1984), Tyler & Blader (2002) and Täuber et al. (2013), that captured mutual trust (4 items), social tie strength (2 items), and feelings of being valued (6 items). An example item of trust is “I would trust my team members”. An example item of tie strength is “I would frequently interact with my team members” and an example item of feeling valued is “I would feel valued during interaction with my team members”. A full list of all items is presented in Appendix B. Participants were asked to evaluate all items on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Some examples of the statements given to the respondents were: (feeling valued scale) and “.” (trust scale).

it was discovered that the items loaded on two components rather than three; a trust scale (α = .86, N = 3) and a feeling valued scale (α = .93, N = 9). The two items that previously formed a social tie strength scale loaded on the feeling valued scale as well as one item from trust scale (see the results of this factor analysis in Appendix C). Therefore, I will use the complete relationship quality scale as well as the separate trust and feeling valued scales for further analyses.

Knowledge transfer. The dependent variable of this study was measured by 10 items (αall variables = .82; adapted from Holste & Fields (2010, p. 132); Grutterink, Van der Vegt, Molleman & Jehn, 2012). The items were measured using a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Some example statements: “I would fully collaborate with any of my team members, in order to let them better understand and learn from my work.” and “I think that in my team, other members have accurate view of what I know.”

I conducted a third Varimax rotated component factor analysis for all items of relationship quality and knowledge transfer together in order to check whether the mediator and dependent variable of this study were clearly distinct from each other. The results revealed that they were indeed distinct from each other, however knowledge transfer items did not load on one factor, but four. I then ran a fourth Varimax rotated component factor analysis, setting a 2 factor criteria (forcing items to load on 2 components). It revealed that all items of relationship quality loaded fully on one factor, and all but two items of knowledge transfer loaded fully on the other factor. I therefore decided to exclude these 2 overlapping items from knowledge transfer measure. The full results of the Rotation Component Matrix

of the above described factor analyses can be found in Appendix D.

Perceived individual differences. As another way to test the manipulation, I have added an extra scale to check whether respondents actually perceive older individuals as different from younger ones. I saw it interesting to investigate because previous research showed that work teams where members perceive each other as distinct individuals, see diversity as beneficial and are even able to take advantage of it (Brewer & Brown, 1998; Homan, Hollenbeck, Humphrey, Van Knippenberg, Ilgen & Van Kleef, 2008; Homan, Green, Jehn & Koning, 2010). In order to measure the PID, a 6-item scale was adapted from Täuber et al. (2013), using a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree), α = .71. Some statement examples: “I think older and younger workers differ from each other in general.” and “I think that some professional competences are only acquired with age.”

Explicit age stereotyping. Since implicit age stereotyping is a continuous, subjective variable, it is quite difficult to establish and measure it. I therefore added an extra measure as second option to capture the possible effect that age stereotyping has on the other variables of this study. Participants were asked to choose specific “temperatures” on two feeling thermometer scales. One thermometer scale depicted respondents’ feelings about younger people, the other, feelings about older people, where 0° represented cold or unfavorable, 50° meant neutral, and 99° signified very warm or favorable feelings. Participants also completed two 5-item (ugly–beautiful, bad–good, unpleasant–pleasant, dishonest–honest, awful–nice) semantic differential measures, using a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree), α = .92. They rated young people on one semantic differential and older people on the other. Attitudes towards younger and older people were computed as the mean across the 5 items with higher means indicating more positive attitudes. Both thermometer scales and semantic differential measures were based on Hummert & Mellott (2002, p. 486).

at. I decided to control for age because I expect that age stereotyping will differ along the different age groups of participants. I chose for gender as a control variable because I was interested whether it would have any influence on age stereotyping and I have not come across this factor in a previously research on age stereotyping. Regarding education level, I expect that the higher education level of the participants is, the less they hold a priori age stereotypes. Same is expected about company size; the larger the organization, the less likely, I expect, are the employees to hold age stereotypes against their colleagues because they are simply used to working in highly age-diverse teams and share knowledge amongst themselves. Working position was used because people in higher position may be less willing to transfer knowledge to people with a lower position and vice versa (Wang & Noa, 2010).

Results

--- Insert Table 2 about here ---

Knowledge transfer. To test whether the relation between age diversity and knowledge transfer is negative (H1a), I conducted a multiple regression analysis. In the first step of the analysis I entered the control variables (model 1). In the second step of the analysis I added age diversity and a priori age stereotyping as separate independent variables into the equation (model 2). For this purpose, all values of the predictors were standardized (see Fields, 2009). In the final stage of the multiple regression analysis, I added the interaction term between age diversity and implicit age stereotyping (model 3). The results are presented in Table 3.

The analysis, however, revealed no significant main effect of age diversity on knowledge transfer (Β = -.08, SE = .08, t = -.99, p = .32,) and no moderation effect (interaction term of age diversity x implicit age stereotyping) either (Β = .16, SE = .13, t = -1.23, p = .22). Therefore, I conclude that hypothesis 1a is not supported. None of the control variables had a significant effect on knowledge transfer either (see Table 3).

--- Insert Table 3 about here ---

relationship quality scale. In the subsequent regressions (model 2 and model 3), these variables were entered as standardized predictors of the separate components of relationship quality (i.e., trust and feeling valued respectively). The first regression revealed no main effect of age diversity (Β = -.13, SE = .0,8, t = -1.61, p = .11), no main effect of implicit stereotyping (Β = -.06, SE = .17, t = -.35, p = .73,) and no interaction effect between age diversity and implicit stereotyping (Β = -.02, SE = .14, t = -.12, p = .91) on relationship quality.2 The regression analyses on the separate components also yielded no significant main or interaction effects (see Table 4). Therefore, I conclude that implicit age stereotyping does not reduce the relationship quality within age-diverse work team and hypothesis 2 is thus not supported.

--- Insert Table 4 about here ---

Mediation analysis. Given that there is no relationship between age diversity and knowledge transfer to begin with, I could not further test for moderated mediation of relationship quality (H1b). However, as seen in Table 2, relationship quality and knowledge transfer were significantly correlated. Therefore, even though results presented above show

____________________________________________ 2

that relationship quality has not mediated relation between age diversity and knowledge transfer, I did additionally run another linear regression analysis and found a significant positive effect of relationship quality on knowledge transfer (Β = .60, SE = .07, t = 8.38, p = .00). This means that when relationships among age-diverse work team members are good, it does increase knowledge transfer within that team.

Supplementary Analyses. Since the main model analyses did not reveal any main or interaction effects of age diversity and a priori age stereotyping on the relationship quality and knowledge transfer within the age-diverse team, I got curious whether any of the extra measurements I have used, namely, perceived individual differences and explicit age stereotyping could have a significant effect on these variables.

Perceived individual differences. Looking at the correlations between all study variables (see Table 2), we see that perceived individual differences variable significantly correlated with knowledge transfer (r = .23, p < .01). Therefore, I ran a linear regression to test whether perceived individual differences had a direct effect on knowledge transfer within a work team. In contradiction to the prior research, linear regression analysis revealed the presence of a slight positive effect on knowledge transfer (Β = .18, SE = .08, t = 2.27, p =.03). This means that perceived individual differences (or perceived age diversity) within a work team leads to more knowledge transfer. Previous research supports this effect. According to Homan, Greer, Jehn & Koning (2010), when people, implementing intellectual tasks, hold positive diversity beliefs they perceive the diversity within their work team in terms of individual differences and are more willing to cooperate, share their knowledge with each other.

analysis to investigate whether perceived individual differences had an effect on relationship quality. The results also showed a slight significant effect (Β = .18, SE = .09, t = 2.01, p = .05). This means that perceived individual differences slightly improve the relationship among age-diverse work team members.

Finally, since both perceived individual differences and relationship quality were positively related to knowledge transfer, I wondered whether relation perceived individual differences could be taken for independent variable in place of age diversity where relationship quality mediated their relation. I ran a SPSS PROCESS bootstrapping macro for simple mediation, model 4. However the results showed no indirect effect (B= .08, Boot SE = .05, LL95%CI = .00 (exact value -.0035), UL95%CI = .19); this means that relationship quality does not mediate the relation between perceived individual differences and knowledge transfer.

Explicit age stereotyping. To investigate whether explicit age stereotyping could be a possible moderator of the relation between age diversity and relationship quality, series of linear regression analyses was performed. The results showed no main effect of age diversity on relationship quality, (Β = -.13, SE = .08, t = -1.63, p = .11) no effect of explicit stereotyping on relationship quality (Β = .00, SE = .08, t = 0.4, p = .97) and no interaction effect (Β = .04, SE = .08, t = .48, p = .64).

addressing the explicit attitudes towards younger and older people and respondents might have tried to hide their potential age stereotyping.

Discussion Summary and Results

Contrary to the previous research, which suggested that age diversity reduced relationship quality within age-diverse team and in turn obstructed knowledge transfer (DeLong, 2004; Krueger & Rothbart, 1988, Shore et al., 2009; Stam, 2009; Van Selm & Van der Heijden, 2013), current investigation demonstrated that age diversity does not have a negative effect on knowledge transfer. In fact, this study shows that age diversity has no significant effect on it at all. Consequently, the relationship quality among age-diverse work team members does not mediate the relation between age diversity and knowledge transfer, because that relation does not exist. Additionally, age stereotyping (both implicit and explicit) has no moderation effect on the relation between age diversity and relationship quality. To summarize, age diversity of a work team does not obstruct its knowledge transfer and age stereotyping does not diminish the quality of the relationship among members of that team.

Theoretical Implications

The findings presented in this study offer important theoretical implications for the understanding of knowledge transfer in age-diverse work teams. First, since demographic ageing has gained a spotlight in analyzing the future development of organizations and their workforce, new theory-based empirical studies about the ways to deal with multigenerational personnel are required, together with proposals about how to address these issues (Hertel et al., 2013). My investigation attempted to satisfy this need. It showed that age-diversity does not pose a threat to knowledge transfer and does not make relationships among different age work team members worse, which is important for organizations to consider while forming the composition of the work teams.

Moreover, my study satisfied the need of objective measurement of age stereotyping, suggested by Posthuma & Campion (2009) in a following way. I have used a measurement of implicit age stereotyping for my main analyses. This measurement is objective because it captures a priori age stereotyping, the stereotyping that people hold against other people whom they do not know and with whom they are not subjectively related. This study, however, also reveals some pitfalls for the future research to consider.

Limitations and Future Research Directions

It is important to note that some limitations were encountered while conducting this research. First, the age-IAT test that I used was not the original one. Due to financial circumstances, I could not purchase the licensing of the original test. Instead, I have created one on Qualtrics platform myself. I used the same concept, formula and have adapted all the tasks that were used in original age-IAT. However, in the original test participants had to just click a button on a keyboard to make a choice, while taking the test I have created, they had to click on their chosen answer using a mouse. This cost more time and effort and might have not captured the implicit age stereotyping as accurately as the original test would have. Since participants spent more time making answer choices, they might have cognitively corrected their age stereotyping attitudes, making them less visible and thus more difficult to capture. Therefore, future researchers should either use the original age-IAT test, developed by Nosek et al. (2007), or develop a new, more advanced one themselves in order to make sure that implicit age stereotyping, is truly captured since it might have resulted in the significant effect of implicit age stereotypes on relationship quality and in turn knowledge transfer in age-diverse work team.

the scenarios might have been not substantial enough to make participants imagine being a part of an actual work team. Therefore, future researchers should either use more persuasive scenarios or a totally different approach to measure the impact of age diversity on knowledge transfer within age-wise heterogeneous and homogenous work teams. For example, it would be interesting to implement a field study; it might show different results as the participants from actual work team have daily communication with their colleagues of different ages.

Third, the insignificance of moderating effect might imply that perhaps future research should not use age stereotyping as a moderator between age diversity and relationship quality of the work team, but investigate the direct effect it has on knowledge transfer as an independent variable instead. There is some previous research claiming that the willingness of all age groups of employees to contribute to the transfer of knowledge gets effected negatively by age stereotyping (Blauth, McDaniel, Perrin C. & sPerrin P. B., 2011). Gellert & Schalk (2012), on the other hand, found that age-related attitudes influence perceived relationship quality as well as outcome quality positively; whereas age itself was found to be not relevant for the perception of relationships (Uhl-Bien, 2006). Future research that delves into age stereotyping (and not age diversity) as an independent variable with respect to knowledge transfer and then investigates whether this relation is mediated by relationship quality within a work team is needed. It would make a step further into understanding when age stereotyping has a negative effect, and under which circumstances it holds a positive impact on relationships and knowledge transfer within age-diverse team and might even provide a solution on how to reduce the influence of in-group/out-group attitudes on knowledge transfer (Wang & Noe, 2010).

team and its knowledge transfer. Schyns, Kroon & Moors (2007) found that employee characteristics, such astheir personality and needs (Felfe & Schyns, 2006; Schyns & Felfe, 2006) or theirimplicit leadership theories (Awamleh & Gardner, 1999), had an impact on the perception of relationship quality with others. Moreover, employees' personal characteristics may also influence the extent to which they share knowledge for different purposes. As found by Wang & Nao (2010), willingness to impress their supervisors motivates new employees to share knowledge more than senior, longer working employees. According to Bock & Kim (2002), individuals' expectations of the usefulness of their knowledge and a belief that sharing that knowledge would improve their relationship with colleagues is related to knowledge transfer intentions and behaviors. Therefore, it would be interesting and beneficial to know how exactly and which personal employees’ characteristics affect relationship quality and in turn impede or accelerate knowledge transfer.

2013). Therefore, rather than focusing on creating groups in certain compositions, companies should focus on improving/changing beliefs about diversity in order to achieve greater knowledge transfer within a work team.

Practical Implications

Even though main hypotheses of this study were not supported, it still benefits companies in both private and public sectors by creating awareness that age stereotyping does not necessarily make relationships among age-diverse employees worse and neither does age diversity itself. In fact, this study encourages managers and leaders of the organizations to be aware that age stereotyping and age diversity has less effect on relationships and knowledge transfer within multigenerational team than it was previously expected. Companies therefore should rather focus on creating a working atmosphere, which would welcome age diversity and individual differences and would view it as a positive aspect of the global workforce rather than an obstacle to knowledge transfer. For instance, if company used practices rewarding long tenure, it would suggest that age is valued in that company, which in turn would reduce the potential for age stereotyping against older people (Posthuma & Campion, 2009).

Final conclusion

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TABLE 1. Most common a priori age stereotypes held against older and younger people Negative age stereotypes held against older

workers

Positive age stereotypes held against older workers

• less motivated,

• generally less willing to participate in training and career development and more difficult to train,

• more resistant and less willing to change, • less trusting and prejudiced,

• less qualified or productive, • less flexible,

• less adaptable to new technologies, • less healthy,

• old-fashioned, • humorless, • conservative, • more expensive, and • more bitter and miserly.

• more experienced,

• more stable and dependable,

• more reliable, honest and trustworthy, • more loyal and committed,

• more effective, and • more wise and intelligent, • comes to terms with their life, • more patriotic,

• less likely to miss work or turnover quickly.

Negative age stereotypes held against younger workers

Positive age stereotypes held against younger workers

• more greedy, selfish, complaining, • more suspicious, demanding, snobbish, • more naive,

• more bored, emotionless or sad,

• unable to communicate, rambling of speech, • more dependent, fragile

• poor drivers,

• poorer or live on fixed income • incapable of handling job.

• concerned about the future, • liberal, mellow,

• knows a great deal, • wise and capable, • interesting, • courageous, • happy, • healthy, • enjoys live, • useful,

• active and alert, • loving,

• understanding and supportive, • generous and volunteer more.

TABLE 2: Descriptive statistics and Pearson zero-order correlations among the study variable M S.D. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 1. Age 26. 13 5.2 1 2. Gender 1.38 .49 .16 1 3. Level of education 4.88 1.51 .12 -.07 1 4. Position at work 3.99 2.33 -.34** _{.05 -.27}** ₁ 5. Company size 2.52 1.45 -.20* .07 -.12 .54** 1 6. Age Diversity 1.62 .49 -.11 .00 .21* -.01 .00 1 7. Relationship Quality 5.52 .84 .04 -.17 -.01 -.03 -.02 -.15 1 8. Knowledge Transfer 5.48 .81 -.06 -.16 .12 -.11 -.03 -.05 .57** 1

9. Implicit Age Stereotyping .39 1.93 -.62** _{-.11 .21}* _{.09 .01 .08 -.08 .16 1}

10. Explicit Age Stereotyping .02 .82 -.22* .00 .09 -.06 .00 .10 -.05 .15 .15 1

11. Perceived Individual Differences 4.69 .89 .21* .24* .00 -.04 .00 -.04 .19 .24* -.22* .07 1

TABLE 3: Multiple Regression Analysis Results for Knowledge Transfer

Knowledge Transfer

Model 1 Model 2 Model 3

Predictor B SE B SE B SE Controls Age -.02 .02 -.01 .02 -.01 .02 Gender -.24 .17 -.24 .17 -.26 .17 Level of education .05 .06 .04 .06 .03 .06 Position at work -.05 .04 -.05 .04 -.06 .04 Company size .03 .07 .04 .07 .04 .07 Main effects Age diversity -.08 .08 -.07 .08

Implicit age stereotyping .11 .11 -.06 .18

Interactions

Age diversity x Implicit

age stereotyping -.16 .13

TABLE 4: Regression Analyses Results for Relationship Quality Dependent Variable (RQ) Dependent Variable (Trust) Dependent Variable (Feeling valued)

Model 1 Model 2 Model 3

Predictors B SE B SE B SE

Main effects

Age Diversity (AD) -.13 .08 -.02 .07 -.07 .07

Implicit Age Stereotyping (IAS) -.06 .17 -.11 .11 -.16 .10 Interactions Interaction Variable 1 (AD*IAS) -.02 .14 -.09 .11 -.11 .10

FIGURE 1. Conceptual Model of this Study

Appendices

Appendix A.Scenarios used in this study

Heterogeneous scenario

Imagine the following situation:

You are working in a work team at company X. Together with other team members you are responsible for a complex task, which requires problem solving. You all have been working in this team for quite some time and are very interdependent in order to achieve collective

goals. The composition of the team has been decided by your manager. Your team thus consists of 6 members and is highly diverse in terms of age. This means that three members are relatively younger while the other three members are relatively older (see

figure bellow). So you are very different from each other in this respect.

Appendix A.Scenarios used in this study

Homogeneous scenario

Imagine the following situation:

You are working in a work team at company X. Together with other team members you are responsible for a complex task, which requires problem solving. You all have been working in this team for quite some time and are very interdependent in order to achieve collective goals. The composition of the team has been decided by your manager. Your team consists of

6 members and is highly homogeneous in terms of age. This means that all members are of similar age (see figure bellow). So you are very similar to each other in this respect.

Appendix B. Survey questions used to measure study variables RELATIONSHIP,QUALITY,measuring,items, Strongly) disagree) Disagree) Slightly) Disagree) Neither) Agree)nor) Disagree) Slightly) Agree) Agree) Strongly) Agree)

I would trust my team members. ! ! ! ! ! ! !

I would rely on my team members. ! ! ! ! ! ! !

I would have complete confidence in my team members ability. ! ! ! ! ! ! ! That issues and problems would be discussed openly in this team. ! ! ! ! ! ! !

I would frequently interact with my team members. ! ! ! ! ! ! !

I would feel that working relationships with my team members are close. ! ! ! ! ! ! ! I would feel valued during the interaction with my team members. ! ! ! ! ! ! !

I would feel that my team members value my input. ! ! ! ! ! ! !

I would feel respected during the interaction with my team members. ! ! ! ! ! ! !

I would feel completely accepted by my team members. ! ! ! ! ! ! !

I would feel that my team members respect my efforts. ! ! ! ! ! ! !

I would feel that other team members see me as a full team member. ! ! ! ! ! ! !

KNOWLEDGE,TRANSFER,measuring,items, Strongly) disagree) Disagree) Slightly) Disagree) Neither)Agree) nor)Disagree) Slightly) Agree) Agree) Strongly) Agree)

I would allow any of my team members to observe me, in order for them to

better understand and learn from my work. ! ! ! ! ! ! !

would fully collaborate with any of my team members, in order to let them

better understand and learn from my work. ! ! ! ! ! ! !

I would willingly share my new ideas with my team members. ! ! ! ! ! ! !

I would willingly share my personal rules of thumb and insights into our

common task. ! ! ! ! ! ! !

I would willingly share the latest rumors going around the team, if I thought

them to be important. ! ! ! ! ! ! !

I would be willing to learn from personal work experience of my team

members. ! ! ! ! ! ! !

I would be willing to pass on my personal work experience in this work

team. ! ! ! ! ! ! !

I think that in my team, other members are aware of my knowledge and

expertise. ! ! ! ! ! ! !

I think that in my team, other members know in detail what I know and

what I am capable of. ! ! ! ! ! ! !

PERCEIVED,INDIVIDUAL,DIFFERENCES,measuring, items, Strongly) disagree) Disagree) Slightly) Disagree) Neither) Agree)nor) Disagree) Slightly) Agree) Agree) Strongly) Agree)

I think older and younger workers differ from each other in

general. ! ! ! ! ! ! !

I think there is a clear distinction between older and younger

workers when they work together. ! ! ! ! ! ! !

In my opinion, younger workers are perceived to be very

different from older workers. ! ! ! ! ! ! !

In my opinion, no matter what effort one makes, a younger worker will never be thought of in the same way as an older worker.

! ! ! ! ! ! !

I think that some professional competences are only acquired

with age. ! ! ! ! ! ! !

In my opinion, older workers are the best people to train or

Appendix C.Factor Analyses results for RQ items

Pattern Matrixa

Component

1 2

I would trust my team members. .042 .864 I would rely on my team members. -.026 .881 I would have complete confidence

in my team members ability. .103 .793 That issues and problems would be

discussed openly in this team. .540 .232 I would frequently interact with

my team members. .809 -.135

I would feel that working relationships with my team members are close.

.875 -.107 I would feel valued during the

interaction with my team members. .897 -.064 I would feel that my team members

value my input. .822 .073

I would feel respected during the

interaction with my team members. .758 .134 I would feel completely accepted

by my team members. .787 .028

I would feel that my team members

respect my efforts. .743 .157

I would feel that other team members see me as a full team member.

.632 .201 Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.

a. Rotation converged in 4 iterations. Rotated Component Matrixa

Component

1 2

I would trust my team members. .290 .841 I would rely on my team members. .231 .834 I would have complete confidence

in my team members ability. .328 .794 That issues and problems would be

discussed openly in this team. .575 .407 I would frequently interact with

my team members. .721 .147

I would feel that working relationships with my team members are close.

.791 .197 I would feel valued during the

interaction with my team members. .824 .245 I would feel that my team members

value my input. .793 .351

I would feel respected during the

interaction with my team members. .752 .388 I would feel completely accepted

by my team members. .748 .296

I would feel that my team members

respect my efforts. .744 .405

I would feel that other team members see me as a full team member.

.653 .409 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.