Understanding the Motivational Benefits of Knowledge Transfer for Older and Younger Workers in Age-Diverse Coworker Dyads: An Actor–Partner Interdependence Model

Abstract

The growing age diversity in organizations in most industrialized economies provides opportunities to motivate both older and younger workers by enabling them to benefit from each other through knowledge transfer. In this study, we integrate self-determination theory with socio-emotional selectivity theory to argue that the alignment between workers’ age and their roles in knowledge transfer can generate motivational benefits for them. More specifically, we argue that receiving knowledge from coworkers (i.e., actor knowledge receiving) is more closely aligned with younger workers’ goal priorities, while having coworkers receive one’s knowledge (i.e., partner knowledge receiving) is more closely aligned with older workers’ goal priorities. We expect that these motivational benefits manifest in younger and older workers’ need fulfillment at work, which can shape their subsequent intention to remain with the organization. We used an actor-partner interdependence model to test our hypotheses with time-lagged data from a sample of 173 age-diverse coworker dyads, and found support for most of our hypotheses. The age-specific motivational perspective that we adopt has implications for self-determination theory and research on knowledge transfer and mentoring.

Full text

Understanding the Motivational Benefits of Knowledge Transfer for Older and Younger
Workers in Age-diverse Coworker Dyads: An Actor-Partner Interdependence Model
Anne Burmeister
Rotterdam School of Management, Erasmus University
Mo Wang
University of Florida
Andreas Hirschi
University of Bern
Author Notes
Anne Burmeister, Rotterdam School of Management, Erasmus University. Mo Wang,
Department of Management, Warrington College of Business, University of Florida. Andreas
Hirschi, Work and Organizational Psychology, University of Bern. Correspondence regarding
this article should be addressed to Anne Burmeister, Erasmus University, Postbus 1738, 3000
DR Rotterdam, Netherlands. Emails should be sent to: burmeister@rsm.nl.
Informal publication: The ideas in this manuscript have been presented at the Academy of
Management Meeting 2019 in Boston in a divisional paper session.
Funding information: This research was supported by a research grant awarded to Anne
Burmeister by the Swiss National Science Foundation (SNF), and a research grant awarded to
Andreas Hirschi by the Swiss State Secretariat for Education, Research and Innovation
(SERI). Mo Wang’s work on this research was supported in part by the Lanzillotti-McKethan
Eminent Scholar Endowment.
© 2019, American Psychological Association. This paper is not the copy of record and
may not exactly replicate the final, authoritative version of the article. Please do not
copy or cite without authors' permission. The final article will be available, upon
publication, via its DOI: 10.1037/apl0000466

Running head: AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 2
Understanding the Motivational Benefits of Knowledge Transfer for Older and Younger
Workers in Age-diverse Coworker Dyads: An Actor-Partner Interdependence Model
Abstract
The growing age diversity in organizations in most industrialized economies provides
opportunities to motivate both older and younger workers by enabling them to benefit from
each other through knowledge transfer. In this study, we integrate self-determination theory
with socio-emotional selectivity theory to argue that the alignment between workers’ age and
their roles in knowledge transfer can generate motivational benefits for them. More
specifically, we argue that receiving knowledge from coworkers (i.e., actor knowledge
receiving) is more closely aligned with younger workers’ goal priorities, while having
coworkers receive one’s knowledge (i.e., partner knowledge receiving) is more closely
aligned with older workers’ goal priorities. We expect that these motivational benefits
manifest in younger and older workers’ need fulfillment at work, which can shape their
subsequent intention to remain with the organization. We used an actor-partner
interdependence model to test our hypotheses with time-lagged data from a sample of 173
age-diverse coworker dyads, and found support for most of our hypotheses. The age-specific
motivational perspective that we adopt has implications for self-determination theory and
research on knowledge transfer and mentoring.
Keywords: socio-emotional selectivity theory, self-determination theory, work
motivation, employee retention, mentoring, actor-partner interdependence model

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 3
Due to demographic change, workforces are currently more age-diverse than ever
before, which leads to an increased level of social interactions among employees with
pronounced age differences (Finkelstein, Truxillo, Fraccaroli, & Kanfer, 2015). Interactions
among employees who belong to different age groups can yield both challenges and
opportunities: On the one hand, employees may experience conflict because they categorize
employees from other age groups into out-group members who compete for resources (North
& Fiske, 2015). On the other hand, older and younger employees can benefit from each
other’s non-redundant knowledge through knowledge transfer (Gerpott, Lehmann-
Willenbrock, & Voelpel, 2017). Knowledge transfer is a communicative process during
which at least two individuals interact such that one individual can receive and utilize the
knowledge that was shared by another individual after retrieving it from memory (Grand,
Braun, Kuljanin, Kozlowski, & Chao, 2016).
While the cognitive benefits of knowledge transfer, for example, with regard to
problem-solving, creativity, and performance, are well documented (e.g., Gilson, Lim,
Luciano, & Choi, 2013; Mesmer-Magnus & DeChurch, 2009), our understanding of
consequences of knowledge transfer in age-diverse workforces is currently limited in two
important ways. First, we know that older and younger workers are motivated by different
aspects of their work (Fasbender, Burmeister, & Wang, in press; Mor-Barak, 1995; M. Wang,
Burlacu, Truxillo, James, & Yao, 2015). Older workers tend to seek opportunities to be
generative toward younger coworkers, while younger workers seek opportunities for
knowledge acquisition (Henry, Zacher, & Desmette, 2015; Kooij, Lange, Jansen, Kanfer, &
Dikkers, 2011). As such, neglecting these motivational differences between age-diverse
employees may lead to incomplete conclusions in examining the consequences of knowledge
transfer. Second, organizations can only benefit from knowledge transfer if employees are
motivated to remain and exert their future efforts at their current organization (Gegenfurtner,
Veermans, Festner, & Gruber, 2009; Maurer & Lippstreu, 2008). Therefore, it is important to

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 4
understand which aspects of knowledge transfer motivate age-diverse employees to remain
with their organization. Taken together, we argue that taking an age-specific motivational
perspective is essential to advance our understanding of the consequences of knowledge
transfer.
Our focus on taking a motivational perspective to understand the effects of knowledge
transfer between age-diverse employees also contributes to the mentoring literature.
Mentoring involves the transfer of knowledge from more experienced workers (i.e., mentors)
to less experienced workers (i.e., protégés), which can result in benefits for the protégés, such
as learning and organizational commitment (Lankau & Scandura, 2002). At the same time,
mentors can experience gratification and recognition from the mentoring relationship (Eby,
Durley, Evans, & Ragins, 2006), which has been described as rejuvenating (Hunt & Michael,
1983). However, the mentoring literature is largely silent in offering understanding about
how age differences between the mentor and protégé may shape the benefits of knowledge
transfer. For example, studies examining the effects of age differences between mentors and
protégés have exclusively focused on mentoring relationship formation or mentoring
activities as outcomes (e.g., Allen & Eby, 2003; Feldman, Folks, & Turnley, 1999;
Finkelstein et al., 2003; Ghosh, 2014; Whitely, Dougherty, & Dreher, 1992). Thus,
understanding how age may shape the motivational benefits that older and younger
employees derive from knowledge transfer has potential to advance the mentoring literature
as well.
In the current study, we integrate self-determination theory (SDT; Deci & Ryan, 1985,
2000) with socio-emotional selectivity theory (SST; Carstensen, 1991, 2006; Carstensen,
Isaacowitz, & Charles, 1999; Lang & Carstensen, 2002) to understand how different aspects
of knowledge transfer elicit motivational benefits for older vs. younger workers in terms of
their need fulfillment at work and their subsequent intention to remain with the organization
(i.e., employees' desire to continue to work for their current organization; Armstrong-Stassen

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 5
& Ursel, 2009). In particular, we examine actor knowledge receiving (i.e., one receives
knowledge from an age-diverse coworker) and partner knowledge receiving (i.e., an age-
diverse coworker receives one’s knowledge) as distinguished age-specific avenues through
which younger vs. older coworkers fulfill their basic needs (i.e., autonomy, competence, and
relatedness), which, in turn, increase their intention to remain.
With our study, we aim to make three main contributions. First, we integrate SDT
with SST to conceptualize actor and partner knowledge receiving as different avenues
through which younger and older employees realize motivational benefits in interactions with
age-diverse coworkers. Using SST, we provide nuance to SDT by addressing the previously
untested claim in SDT that the universality of the three basic needs does not mean that “their
avenues for satisfaction are unchanged across the life span” (Ryan & Deci, 2000, p. 75). We
provide an age-specific substantiation of this idea by theorizing that younger employees
experience actor knowledge receiving as motivating, while older employees perceive partner
knowledge receiving as motivating. Second, we examine outcomes rather than antecedents
and motivational rather than cognitive benefits of knowledge transfer to advance research in
this domain. Our perspective thus complements the current understanding of this dyadic
process which mainly focused on how knowledge transfer could be facilitated (e.g., Argote,
McEvily, & Reagans, 2003; S. Wang & Noe, 2010) and the cognitive benefits of knowledge
transfer (Mesmer-Magnus & DeChurch, 2009; Van Wijk, Jansen, & Lyles, 2008). Third, we
contributfe to the literature on employee retention and mentoring by focusing on knowledge
transfer as an important driver of intention to remain with the organization. Intention to
remain is an important outcome in age-diverse workforces, as organizations tend to be
concerned about older workers’ desire to retire and younger workers’ frequent job changes
(Biemann, Zacher, & Feldman, 2012; M. Wang & Wanberg, 2017; Wöhrmann, Fasbender, &
Deller, 2017). Further, knowledge transfer represents a specific component of mentoring
relationships and understanding how knowledge transfer leads older and younger employees

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 6
to connect more closely to their organizations can advance the limited insights on the role of
age in mentoring.
An Age-Specific Perspective on the Motivational Benefits of Knowledge Receiving
Both SDT and SST are theories of motivation that enable us to explain why
employees experience certain actions as motivating. SDT as a general theory of human
motivation proposes that humans have three basic psychological needs—autonomy,
competence, and relatedness (Deci & Ryan, 1985, 2000). Autonomy needs at work refers to
the desire to feel a sense of volition and psychological freedom when interacting with the
work environment. Competence needs at work describes workers’ desire to feel effective in
interacting with the work environment. Relatedness needs at work represents the desire of
workers to feel connected to others at work and have close relationships. Importantly, SDT
suggests that the three basic psychological needs are universal and essential for psychosocial
functioning (Deci et al., 2001; Deci & Ryan, 1985; Gagné & Deci, 2005). Supporting the
universality argument, positive effects of autonomy, competence, and relatedness needs
fulfillment on employee work engagement, well-being, and performance have been reported
across studies (Baard, Deci, & Ryan, 2004; Deci et al., 2001; van den Broeck, Ferris, Chang,
& Rosen, 2016).
SST as a life span development theory of motivation (Carstensen, 1991; Carstensen et
al., 1999; Carstensen, 2006; Lang & Carstensen, 2002) proposes that younger individuals
typically view time as open-ended, while older individuals perceive time as constrained,
which subsequently affects their goal priorities (Fasbender et al., in press; M. Wang, Burlacu
et al., 2015). Accordingly, younger individuals tend to prioritize instrumental or knowledge-
related goals, enacted for example through accumulating knowledge. In line with these
theoretical premises of SST, meta-analytical evidence showed that younger workers reported
higher growth-related motives (i.e., to which extent one values opportunities for advancement
and learning at work; Kooij et al., 2011) than older workers. To contrast, older individuals

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 7
focus on goals to gain positive socio-emotional experiences, enacted for example through
generativity striving (Lang & Carstensen, 2002). Generativity refers to helping and
establishing the next generation through, for example, passing on one’s knowledge (Erikson,
1963; McAdams & Logan, 2004). Supporting this theoretical expectation based on SST,
research showed that older workers are motivated by jobs that allow them to support future
generations (Mor-Barak, 1995; van den Oetelaar, 2011).
The integration of SDT and SST enables us to advance an age-specific perspective on
the motivational benefits of knowledge receiving that manifest via the fulfillment of the three
basic psychological needs. More specifically, SST allows us to theorize why older and
younger workers might experience different actions as self-determined and need fulfilling
(Ryan & Deci, 2000). We theorize that younger employees experience actor knowledge
receiving as motivating based on their knowledge-related goal priorities, while older
employees perceive partner knowledge receiving as motivating based on their socio-
emotional and generative goal priorities (Lang & Carstensen, 2002). Our arguments about the
different need fulfillment benefits that younger vs. older employees derive from actor vs.
partner knowledge receiving are thus based on the match between age-specific goal priorities
and one’s role during knowledge transfer. As such, we use SST to conceptualize actor and
partner knowledge receiving as distinguished age-specific avenues through which younger
and older employees realize motivational benefits as specified in SDT via interactions with
age-diverse coworkers. Our conceptual model is depicted in Figure 1.
*** Please insert Figure 1 about here ***
Hypotheses Development
Knowledge Receiving and Need Fulfillment at Work for Younger and Older Workers
With regard to actor knowledge receiving, we hypothesize that its motivational
benefits are more likely to manifest among younger workers. First, we expect a positive
relation between actor knowledge receiving and autonomy need fulfillment for younger

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 8
workers because they are likely to view the acquisition of knowledge as a way to exercise
volition and experience a sense of agency in responding to work-related demands. Previous
research has shown that younger workers with relatively limited work experience tend to
internalize their role as knowledge recipients (Burmeister, Fasbender, & Deller, 2018) and
are motivated to accumulate knowledge to be able to gain more autonomy in their work
environment (Truxillo, Cadiz, Rineer, Zaniboni, & Fraccaroli, 2012; van den Oetelaar, 2011).
Receiving valuable knowledge from older coworkers might therefore be a welcome
opportunity for younger workers to enlarge their repertoire in responding to work-related
demands, thereby facilitating their psychological freedom.
Second, younger workers are likely to perceive knowledge receiving as a means to
fulfill their needs for competence based on their focus on knowledge-related goals
(Carstensen et al., 1999). Accordingly, younger workers ought to feel more effective and
competent in interacting with the work environment as a result of receiving knowledge from
their older coworkers (Canning, 2011; van den Oetelaar, 2011; Warr, 2001). This should
especially be the case, as older workers often possess not only useful task-specific
knowledge, but also valuable organization-specific knowledge, including knowledge about
social networks and the political landscape in the workplace (Gerpott et al., 2017; M. Wang,
Kammeyer-Mueller, Liu, & Li, 2015). This knowledge can be critical for younger workers to
enlarge their knowledge reservoir and engage more competently with their work
environment.
Third, we expect that younger workers feel more connected due to knowledge
receiving. Research showed that younger workers are motivated to develop social
relationships at work when these have the potential to yield instrumental benefits, such as
knowledge access (Inceoglu, Segers, & Bartram, 2012; Truxillo, Cadiz, & Rineer, 2017). As
receiving valuable knowledge from older coworkers provides younger workers with the
opportunity to grow their knowledge reservoir, younger workers should be more likely to

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 9
engage in social interactions with older coworkers. This ought to create more opportunities
for younger workers to deepen their social relationships with older coworkers and facilitate
feelings of relatedness at work (Beal, Cohen, Burke, & McLendon, 2003).
Hypothesis 1: For younger workers, actor knowledge receiving is positively
associated with their (a) autonomy, (b) competence, and (c) relatedness need
fulfillment at work.
With regard to partner knowledge receiving, we hypothesize that older workers are
more likely to experience need fulfillment when their age-diverse coworkers receive
knowledge from them. First, we expect a positive relation between partner knowledge
receiving and autonomy need fulfillment for older workers, because older workers are likely
to perceive providing knowledge as an opportunity to exercise volition in acting on their
goals to be generative toward others (Carstensen et al., 1999; Erikson, 1963; Lang
& Carstensen, 2002; McAdams & St. Aubin, 1992). Research has shown that older workers
actively craft their jobs in ways that allows them to share their knowledge with younger
coworkers (van den Oetelaar, 2011). Accordingly, having the opportunity to enable younger
coworkers to receive their knowledge should facilitate older workers’ experience of agency
and psychological freedom, as knowledge providing is a discretionary behavior and enacts
autonomy at work (Bartol, Liu, Zeng, & Wu, 2009; Cabrera, Collins, & Salgado, 2006).
Second, older workers are likely to perceive partner knowledge receiving as a means
to fulfill their needs for competence based on achieving their goal to be generative toward
others (Erikson, 1963; McAdams & St. Aubin, 1992; Mor-Barak, 1995). In particular, older
workers tend to feel competent and satisfied at work when they have opportunities to utilize
their existing knowledge and skills (Canning, 2011; Warr, 2001). Enabling younger
coworkers to benefit from their knowledge can be viewed as one way to utilize their
knowledge, thus contributing to older worker competence need fulfillment. In addition, recent
research suggests that older workers perceive themselves as the “go-to” person for knowledge

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 10
and expertise based on their generativity motives (Burmeister, Fasbender et al., 2018).
Accordingly, knowledge reception by younger coworkers should be especially rewarding
because it verifies older workers’ self-image of being valuable knowledge providers.
Third, we expect a positive relation between partner knowledge receiving and
relatedness need fulfillment at work for older workers, because the process of partner
knowledge receiving may create an opportunity for older workers to deepen their social
connection with their younger coworkers, which aligns well with their focus on gaining
positive socio-emotional experiences (Carstensen et al., 1999; Erikson, 1963; McAdams
& St. Aubin, 1992). In particular, to successfully transfer knowledge, both knowledge
providers and recipients need to engage in high-quality communication and commit to a
shared goal (Burmeister et al., 2015; Grand et al., 2016; Kwan & Cheung, 2006), both of
which are likely to enhance the socio-emotional experience and contribute to a sense of
relatedness for older workers. Indeed, previous research has shown that being generative is
one important means for older workers to strengthen their existing social ties and experience
relatedness (Truxillo et al., 2017).
Hypothesis 2: For older workers, partner knowledge receiving is positively associated
with their (a) autonomy, (b) competence, and (c) relatedness need fulfillment at work.
Knowledge Receiving and Intention to Remain for Younger and Older Workers
In line with existing research on the positive effects of need fulfillment at work, we
expect autonomy, competence, and relatedness need fulfillment at work to facilitate both
older and younger coworkers’ intention to remain with the organization. Autonomy,
competence, and relatedness need fulfillment at work signal to workers that working for their
current organization enables them to achieve personal growth and well-being (van den
Broeck et al., 2016), thus positively affecting their intention to remain with the organization
(Armstrong-Stassen & Schlosser, 2011; Gagné & Deci, 2005). Based on our theorizing about
the different motivational benefits that older and younger coworkers derive from actor vs.

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 11
partner knowledge receiving, and the expected association between need fulfillment at work
and intention to remain, we derive mediation hypotheses to link actor vs. partner knowledge
receiving to intention to remain.
Hypothesis 3: For younger workers, actor knowledge receiving is positively
associated with their intention to remain via their (a) autonomy, (b) competence, and
(c) relatedness need fulfillment at work.
Hypothesis 4: For older workers, partner knowledge receiving is positively associated
with their intention to remain via their (a) autonomy, (b) competence, and (c)
relatedness need fulfillment at work.
Method
Sample and Procedure
Our sample consisted of age-diverse coworker dyads who were employed in the
German-speaking region of Switzerland. Master students in psychology at a university in the
German-speaking region of Switzerland used their social networks to recruit age-diverse
coworker dyads that were co-located, had at least one face-to-face contact per week, and had
an age difference of at least 10 years (the younger coworker in each dyad could not be older
than 35 years in age, while the older coworker could not be younger than 45 years in age).
The data presented in this article were part of a broader data collection effort on interactions
between age-diverse coworkers, and this is the first publication from this dataset. In
conducting this research, we followed APA’s ethics code, and the study received ethics
approval from the ethics commission of the psychology institute at the University of Bern
(no. 2014-10-1051882). The 180 dyads that signed up voluntarily for this study together with
their respective partner received an email including a link to the online questionnaires. In
total, 173 dyads provided data, resulting in an effective response rate of 96 percent. To
alleviate common method bias, we measured knowledge receiving at Time 1, and need

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 12
fulfillment at work and intention to remain with the organization at Time 2, with a time-lag of
four weeks in-between.
The average age difference between dyad members was 26.60 years (SD = 6.42, Min.
= 12, Max. = 42). Of the younger workers, 60 percent were female, they were on average
28.12 years old (SD = 4.18), and they had an average organizational tenure of 3.78 years (SD
= 3.49). Of the older workers, 51 percent were female, they were on average 54.73 years old
(SD = 5.89), and they had an average organizational tenure of 16.21 years (SD = 11.82). The
age-diverse coworker dyads worked in diverse industries.
Measures
Younger and older coworkers provided self-ratings on all study variables. We used
the translation-back-translation procedure to translate the English items into German. If not
indicated otherwise, all measures used a 7-point response scale ranging from 1 (strongly
disagree) to 7 (strongly agree).
Knowledge receiving. We measured knowledge receiving with the 4-item scale from
Wilkesmann, Wilkesmann, and Virgillito (2009). A sample item is “I learn a lot by asking my
colleague.” Cronbach’s alphas were .86 (younger coworkers) and .87 (older coworkers).
Need fulfillment at work. We measured autonomy, competence, and relatedness need
fulfilment at work each with the 4-item scales from Chiniara and Bentein (2016)on a scale
ranging from 1 (very dissatisfied) to 7 (very satisfied). Sample items were “The degree of
freedom I have to do my job the way I think it can be done best”; “The feeling of being
competent at doing my job”; “The positive social interactions I have at work with other
people.” Cronbach’s alpha values ranged between .78 and .90.
Intention to remain. We measured intention to remain using the 3-item scale by
Armstrong-Stassen and Ursel (2009). A sample item is “I expect to continue working as long
as possible in this organization.” Cronbach’s alphas were .92 (younger coworkers) and .95
(older coworkers).

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 13
Control variables. First, we controlled for organizational tenure (in years) of
participants because research showed that workers with longer tenure tend to be more
attached and loyal to their organizations (Cohen, 1993; Mathieu & Zajac, 1990). Second, we
controlled for (a) perception of partner as mentor (i.e., “To which extent do you perceive your
colleague as a mentor?”; 1 = to a very limited extent, 7 = to a very large extent), (b) dyad
gender difference (i.e., 0 = no gender difference in dyad members, 1 = gender difference in
dyad members), and (c) dyad tenure (i.e., “How many years have you known your colleague
for?”), as these variables reflect the social relationship between older and younger coworkers
and might affect the outcomes of their knowledge transfer interaction (Burmeister, van der
Heijden, Yang, & Deller, 2018).
Analytic Strategy
We used the actor-partner interdependence model (APIM; Kashy & Kenny, 2000;
Kenny, 1996; Kenny, Mannetti, Pierro, Livi, & Kashy, 2002) to test our hypotheses. The
APIM acknowledges the non-independence of individuals nested within dyads and can be
used to simultaneously model both actor and partner effects (Bakker & Xanthopoulou, 2009;
Hahn, Binnewies, & Dormann, 2014; Hahn & Dormann, 2013; Halbesleben & Wheeler,
2015).1
To estimate the APIM, we followed the structural equation modeling (SEM)
framework using path analysis (Garcia, Kenny, & Ledermann, 2014). We tested all our
hypotheses in the same path analytic model. To account for the non-independence of dyad
members, we specified dyadic covariances for the independent variable (i.e., knowledge
receiving) and for the error terms of mediators (i.e., need fulfillment at work) and the
dependent variable (i.e., intention to remain; Ledermann, Macho, & Kenny, 2011). To test the
significance of the indirect effects specified in Hypotheses 3 and 4, we used Monte Carlo
bootstrapping method to create 95 percent confidence intervals (CI) around the point
estimates of the indirect effects to account for possible deviations from normality of

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 14
parameter estimates (Preacher & Hayes, 2008). Data analyses were performed with the
package lavaan in R version 3.5.3 (R Core Team, 2017).
Results
Table 1 displays the means, standard deviations, and intercorrelations of the studied
variables. To establish the empirical distinguishability of our multi-item measures, we ran
confirmatory factor analyses (CFA). We compared our ten-factor model (younger workers’
knowledge receiving, autonomy need fulfillment at work, competence need fulfillment at
work, relatedness need fulfillment at work, intention to remain, and older workers’
knowledge receiving, autonomy need fulfillment at work, competence need fulfillment at
work, relatedness need fulfillment at work, intention to remain) to a six-factor model
(younger workers’ knowledge receiving, need fulfillment at work, and intention to remain,
and older workers’ knowledge receiving, need fulfillment at work, and intention to remain).
The ten-factor model (χ2 = 919.99, df = 620, p < .01, CFI = .91, RMSEA = .06, SRMR = .07),
in which autonomy, competence, and relatedness need fulfillment at work were modeled as
separate factors, fit the data significantly better than the six-factor model (χ2 = 1350.66, df =
650, p < .01, CFI = .79, RMSEA = .09, SRMR = .09; Δχ2 = 430.67, Δdf = 30, p < .001).2
Hypotheses Tests
As can be seen in Table 2 and Figure 2, Hypothesis 1a, 1b, and 1c were supported as
actor knowledge receiving was positively associated with younger workers’ autonomy need
fulfillment (γ = 0.21, SE = 0.11, p = .048), younger workers’ competence need fulfillment (γ
= 0.21, SE = 0.10, p = .034) and younger workers’ relatedness need fulfillment (γ = 0.30, SE
= 0.12, p = .010). To further substantiate these findings, we compared our hypothesized
model in which the actor effects differed for older and younger workers, with a constrained
model in which the actor effects were set to be equal for older and younger coworkers.
Supporting our hypotheses, we found that our hypothesized model fit significantly better than
the constrained model (Δχ2 (3) = 8.01, p = .046).

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 15
We also found support for Hypotheses 2a, 2b, and 2c as partner knowledge receiving
was positively associated with older workers’ autonomy need fulfillment (γ = 0.30, SE =
0.09, p = .001), older workers’ competence need fulfillment (γ = 0.25, SE = 0.07, p < .001),
older workers’ relatedness need fulfillment (γ = 0.19, SE = 0.09, p = .031). To further
substantiate these findings, we compared our hypothesized model in which the partner effects
differed for older and younger workers, with a constrained model in which the partner effects
were set to be equal for older and younger coworkers. Supporting our hypotheses, we found
that our hypothesized model fit significantly better than the constrained model (Δχ2 (3) =
9.43, p = .024).3
To test Hypothesis 3, we examined the indirect effects of actor knowledge receiving
on younger workers’ intention to remain via younger workers’ (a) autonomy, (b) competence,
and (c) relatedness need fulfillment at work. The estimated mediating effect through
autonomy need fulfillment was 0.14 (95% CI [.002, 0.314]), thus supporting Hypothesis 3a.
We did not find support for Hypothesis 3b, as the 95 percent CI [-.043, .122] of the indirect
effect through competence need fulfillment included zero. However, Hypothesis 3c was
supported as the estimated mediating effect through relatedness need fulfillment was 0.07
(95% CI [0.003, 0.178]).
Finally, we tested Hypothesis 4. The estimated mediating effect of partner knowledge
receiving through autonomy need fulfillment was 0.12 (95% CI [.019, .264]), providing
support for Hypothesis 4a. Hypothesis 4b was not supported because the 95 percent CI [-
.045, .158] of the indirect effect via competence need fulfillment included zero. However, the
estimated mediating effect through relatedness need fulfillment at work was 0.07 (95% CI
[.001, .152]), thus providing support for Hypothesis 4c.
Discussion
In this study, we aimed to decipher the different avenues through which older and
younger employees generated motivational benefits from knowledge transfer. We found that

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 16
the alignment between employee age and roles in knowledge transfer elicited motivational
effects: Actor knowledge receiving generated motivational benefits for younger employees,
while partner knowledge receiving generated motivational benefits for older employees.
Theoretical and Practical Implications
The results of our study have three main theoretical implications. First, our integration
of SDT (Deci & Ryan, 1985) with SST (e.g., Carstensen, 2006) advances the understanding
of different antecedents of need fulfillment at work from a life span perspective. We move
beyond the insights that contextual characteristics, such as autonomy and competence
support, are beneficial for need fulfillment (Gagné, 2003; La Guardia & Patrick, 2008) and
demonstrate that engagement in knowledge transfer as a specific work behavior can be need
fulfilling. Importantly, we further advance insights on antecedents of need fulfillment by
substantiating the claim that the avenues through which individuals fulfill their needs change
across the life span (Ryan & Deci, 2000). To date, we only knew that cross-cultural
differences might affect the need fulfillment process (Deci et al., 2001). By showing that
younger workers find actor knowledge receiving more need fulfilling and motivating, while
older workers find partner knowledge receiving more need fulfilling and motivating, we
provide novel insights into the extent to which age as an individual difference variable shapes
the avenues for need fulfillment.
Second, we advance research on knowledge transfer by suggesting that motivation is
not only an important predictor of knowledge transfer but can also be an outcome. To date,
researchers have focused on understanding motivation as one of the primary predictors of
knowledge transfer (Chen, Chang, & Liu, 2012; Quigley, Tesluk, Locke, & Bartol, 2007;
Siemsen, Roth, & Balasubramanian, 2008). Going beyond this research, our study points to
the theoretical plausibility that employee motivation may also be an outcome of knowledge
transfer. By adopting a motivational perspective, we also expanded the current focus on an
information-processing perspective to understand the cognitive benefits of knowledge

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 17
transfer (Marlow, Lacerenza, Paoletti, Burke, & Salas, 2018; Mesmer-Magnus & DeChurch,
2009; Okhuysen & Eisenhardt, 2002; Srivastava, Bartol, & Locke, 2006). Our findings
suggest that knowledge transfer may fulfill psychological needs of age-diverse workers, such
that our understanding of knowledge transfer may be incomplete when only focusing on its
cognitive benefits.
Third, we also contribute to the mentoring literature by deciphering how the
involvement in knowledge transfer, as a specific component of mentoring, can facilitate
motivational benefits for older and younger employees. As knowledge reception and learning
was traditionally assumed to be a natural outcome of mentoring (Lankau & Scandura, 2007),
the mentoring literature did not elaborate on the different aspects of knowledge transfer. In
addition, research on the role of age in mentoring relationships has been scarce (Finkelstein,
Allen, & Rhoton, 2003; Ghosh, 2014), and how life span-related differences in goal priorities
might shape mentoring and its outcomes had yet to be considered. With our findings, we
inform the mentoring literature by providing an age-sensitive view on the influence of
knowledge transfer on motivational benefits for both older and younger employees.
In addition, our findings have relevant implications for practitioners. First, being
involved in knowledge transfer with age-diverse coworkers seems to contribute to the
retention of both older and younger workers. Managers should therefore facilitate knowledge
transfer between age-diverse coworkers by creating opportunities for interaction.
Specifically, managers can establish training formats during which older and younger
workers learn jointly, thereby benefiting from each other’s non-redundant knowledge
(Gerpott et al., 2017). Second, as meaningful differences seem to exist between older and
younger workers with regard to whether actor or partner knowledge receiving elicits the most
pronounced motivational benefits, managers can use this insight to assign workers to age-
specific roles during knowledge transfer and mentoring to facilitate their retention. For
example, older and younger workers who have been identified as key talents and knowledge

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 18
holders and who might be at risk of leaving the organization, can be brought together in age-
diverse learning tandems.
Limitations and Future Research Directions
Our findings need to be interpreted in light of the study’s limitations. First, we only
included knowledge receiving but not knowledge sharing to operationalize knowledge
transfer. We measured knowledge receiving rather than knowledge sharing because
knowledge receiving is a more valid indicator of the successful completion of the knowledge
transfer process (Cabrera et al., 2006; Wilkesmann et al., 2009). Nonetheless, future research
could advance our study by collecting data on knowledge sharing and receiving and by
testing whether these two elements of the knowledge transfer process elicit complementary
effects.
Second, the strategy that we used for sampling might limit the generalizability of our
findings. In particular, student-generated samples tend to produce smaller effect sizes
compared to other convenience samples (Wheeler, Shanine, Leon, & Whitman, 2014), which
implies that the reported effect sizes might have been underestimated. In addition, we cannot
rule out the possibility that self-selection bias might have affected our results. However, the
reduced variance associated with a possible selection bias would mean that our study
represents a more conservative test of our hypotheses due to the potential range restriction of
variable values. Future research may alleviate these concerns by employing different
sampling strategies, for example, by randomly selecting two age-diverse coworkers from the
same work unit.
Third, even though we used a time-lagged design, our results do not allow us to make
causal statements about the relations between knowledge receiving, need fulfillment at work,
and intention to remain. Future research should employ experimental designs in which
knowledge transfer is manipulated (see for example Černe, Nerstad, Dysvik, & Škerlavaj,

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 19
2014), and subsequent effects on need fulfillment at work and intention to remain are
examined, to verify the causality argued for in this study.
Fourth, our insights into the effects of motivational benefits of knowledge transfer in
interactions of age-diverse coworkers need to be replicated. For example, the indirect effects
via competence need fulfillment were non-significant in our study. Future research needs to
replicate our results to verify the extent to which all three basic psychological needs explain
the motivational benefits derived from knowledge transfer. We hope that our findings
encourage researchers to further explore the ways in which interactions among age-diverse
coworkers influence work-related outcomes.

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 20
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Footnotes
1In the APIM framework, each variable (e.g., knowledge receiving) can elicit two type
of effects: An actor effect represents the effect of person’s X variable on that person’s Y
variable (e.g., younger workers’ knowledge receiving on younger workers’ need fulfillment at
work), while a partner effect represents the effect of a partner’s X variable on the person’s Y
variable (e.g., older workers’ knowledge receiving on younger workers’ need fulfillment at
work). In this study, this means that the variable knowledge receiving, assessed from both
younger and older dyad members, elicits four different effects on need fulfillment at work
(i.e., two actor effects: younger workers’ actor knowledge receiving on younger worker’s
need fulfillment, older workers’ actor knowledge receiving on older worker’s need
fulfillment; and two partner effects: younger workers’ partner knowledge receiving on older
worker’s need fulfillment, and older workers’ partner knowledge receiving on younger
worker’s need fulfillment).
2We also tested the measurement invariance of our measure across younger and older
coworkers by comparing two CFA models. The first CFA model (i.e., the unconstrained
model) allowed the factor loadings to differ for older and younger coworkers when specifying
the ten-factor model. The second CFA model (i.e., the constrained model) fixed the factor
loadings to be equal across older and younger workers when specifying the same model. The
model fit for both the unconstrained model (χ2 = 919.99, df = 620, p < .01, CFI = .91,
RMSEA = .06, SRMR = .07) and the constrained model (χ2 = 932.97, df = 634, p < .01, CFI
= .91, RMSEA = .06, SRMR = .07) was satisfactory. The chi-square difference test
demonstrated that the unconstrained model did not fit the data significantly better than the
constrained model (Δχ2 = 12.98, Δdf = 14, p = .528), thus providing evidence of measurement
invariance between older and younger coworkers in age-diverse coworker dyads.
3We thank an anonymous reviewer for highlighting the need to further examine the
influence of gender, dyadic gender difference, and dyad tenure. In particular, we encourage
future research to examine how gender, dyadic gender difference, and dyad tenure, as
important individual and dyadic characteristics, may shape the effects of knowledge transfer.
First, in a supplemental analysis, we tested gender as a first-stage moderator and found that
older female actors derived less motivational benefits from partner knowledge receiving.
Second, as our Table 2 suggests, dyadic gender difference had sizeable effects on older
workers’ competence need fulfillment and their intention to remain. Third, while dyad tenure
did not moderate the links between knowledge receiving and need fulfillment in another
supplemental analysis, dyad tenure might moderate knowledge transfer’s effects on other
potential outcomes. It is important to note that the hypothesized actor and partner effects of
knowledge receiving stayed robust regardless of whether or not controlling for gender, dyadic
gender difference, and dyad tenure, or the additional interaction effects mentioned above.

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 32
Table 1
Means, Standard Deviations, and Intercorrelations of the Studied Variables
Variables
M
SD
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
1. Y Organizational tenure
3.78
3.49
2. O Organizational tenure
16.21
11.82
.26**
3. Y Partner as mentor
4.52
1.61
-.16*
.02
4. O Partner as mentor
2.93
1.44
.01
-.06
-.04
5. Dyad gender differencea
0.27
0.45
-.07
.01
-.01
.01
6. Dyad tenure
4.15
5.32
.51**
.15
-.03
.05
-.10
7. Y Knowledge receiving
5.49
1.13
-.18*
-.05
.54**
.01
-.01
-.08
(.86)
8. O Knowledge receiving
4.81
1.20
.14
-.04
.17*
.27**
-.07
.11
.29**
(.87)
9. Y Autonomy NF
5.29
1.12
.02
.07
.09
.17*
-.09
.11
.12
.05
(.88)
10. O Autonomy NF
5.40
0.99
-.02
.05
.24**
-.05
-.08
.14
.32**
.14
.12
(.90)
11. Y Competence NF
5.25
0.87
.05
.00
.09
.03
-.10
.11
.17*
.02
.62**
.07
(.83)
12. O Competence NF
5.48
0.78
.02
.06
.18*
-.05
-.10
.07
.31**
.03
.12
.60**
.15
(.86)
13. Y Relatedness NF
5.08
1.20
.11
.06
.15
.08
-.13
.03
.25**
.07
.33**
-.07
.37**
.04
(.85)
14. O Relatedness NF
5.15
0.87
.03
.05
.09
.13
-.05
.11
.21**
.16
.06
.40**
.15
.41**
.10
(.78)
15. Y Intention to remain
4.46
1.55
.06
.14
.14
.04
-.16*
.16*
.09
-.07
.55**
-.04
.40**
.13
.42**
.10
(.92)
16. O Intention to remain
5.30
1.49
.04
.22**
.09
.04
.05
.18*
.05
.00
-.02
.40**
-.08
.36**
.03
.37**
.14
(.95)
Note. N = 173 dyads (346 individuals). Y = younger dyad member, O = older dyad member; NF = need fulfillment. a0 = “no dyadic gender
difference”, 1 = “dyadic gender difference”. Cronbach’s alpha displayed on diagonal in brackets. * p < .05, ** p < .01.

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 33
Table 2
Hypotheses Tests Using Path Analysis to Estimate the Actor-Partner Interdependence Model
Autonomy
need fulfillment
at work
Competence
need fulfillment
at work
Relatedness
need fulfillment
at work
Intention to remain
Estimate
SE
Estimate
SE
Estimate
SE
Estimate
SE
Younger coworkers
Intercept
-.06
.10
-.02
.08
.05
.10
4.53**
.11
Organizational tenure
-.03
.04
.003
.03
.02
.04
.03
.03
Perception of partner as mentor
.09
.06
-.01
.06
.07
.07
.08
.07
Dyad gender difference
-.18
.21
-.13
.18
-.48
.26
-.30
.23
Dyad tenure
.06
.03
.04
.03
.05
.02
.02
.02
Actor knowledge receiving
.21*
.11
.21*
.10
.30*
.12
.01
.11
Partner knowledge receiving
.04
.07
-.03
.07
-.03
.08
-.20*
.09
Autonomy need fulfillment at work
.68**
.16
Competence need fulfillment at work
.13
.17
Relatedness need fulfillment at work
.25*
.11
R2
.10
.10
.15
.42
Older coworkers
Intercept
-.001
.09
-.01
.07
-.08
.09
5.27**
.12
Organizational tenure
-.001
.01
.001
.01
-.003
.01
.02*
.01
Perception of partner as mentor
-.07
.06
-.02
.04
.09
.06
.07
.08
Dyad gender difference
-.13
.18
-.31*
.15
-.08
.17
.60**
.23
Dyad tenure
.01
.01
.02
.01
.01
.02
.01
.03
Actor knowledge receiving
.08
.07
-.06
.05
.02
.07
-.07
.12
Partner knowledge receiving
.30**
.09
.25**
.07
.19*
.09
-.15
.14
Autonomy need fulfillment at work
.40*
.16
Competence need fulfillment at work
.20
.19
Relatedness need fulfillment at work
.34*
.14
R2
.15
.15
.08
.27
Note. N = 173 dyads (346 individuals). * p < .05, ** p < .01.

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 34
Figure 1. Conceptual Model
Notes. H = hypothesis. Double-headed arrows represent the modeling of dyadic non-
independence in APIM. The following control variables were included but not displayed here
to ease readability: organizational tenure, perception of partner as mentor, dyad gender
difference, and dyad tenure.

AGE DIFFERENCES IN BENEFITS OF KNOWLEDGE TRANSFER 35
Figure 2. Coefficient Estimates of Actor-Partner Interdependence Model
Notes. Unstandardized coefficients are presented. The following control variables were
included but not displayed here to ease readability: organizational tenure, perception of
partner as mentor, dyad gender difference, and dyad tenure. Double-headed arrows represent
the modeling of dyadic non-independence in APIM in the forms of covariances (for
independent variables) or error covariances (for mediators and dependent variables). Dashed
lines represent non-significant effects. * p < .05, ** p < .01.