Originally Published:20080401.

Researchers in applied psychology and management have recently argued that mentoring relationships provide a means for firms to share knowledge, encourage learning, and build intellectual capital (Allen et al., 1997; Eddy et al., 2005; Hezlett, 2005; Lankau and Scandura, 2002; Mullen and Noe, 1999; Swap et al., 2001). Peer mentors can provide some of the same functions as traditional mentors, such as psychosocial support (e.g., talking, listening, expressing concern) and career- or job-related support (tangible assistance such as physical resources, one's time, advice, or knowledge that aids another in doing their jobs) (Kram, 1985; Young and Perrewé, 2004). Peer mentoring is an intentional one-on-one relationship between employees at the same or similar lateral level in the firm that involves a more experienced employee providing sup port and teaching new knowledge and skills to a less experienced employee (Ensher et al., 2001). Recent organizational trends, including downsizing, flattening hierarchies, and increased use of work teams, have reduced the number of senior managers in organizations available to be mentors. In this situation, newer employees may seek mentoring from experienced employees in their organization who are at the same level in the firm-a process called peer mentoring (Eby, 1997; Ensher et al., 2001).

Recent studies have examined information sharing through traditional mentoring relationships (e.g., Borredon and Ingham, 2005; Hezlett, 2005; Mullen and Noe, 1999). There is little research on the relationship between peer mentoring and knowledge sharing, although Eddy et al. (2005) examine a continuous learning environment as an antecedent to peer mentoring. The primary benefits of traditional mentoring relationships are typically career- or job-related support and psychosocial support. We would suggest that knowledge sharing is one of the primary benefits of the peer mentoring relationship (Eddy et al., 2005). The peer mentoring process is qualitatively different from traditional mentoring, and the primary difference is the level of experience and power that the mentors have. Traditional mentors are able to provide career advice, political support, access to inside information, opportunities for advances, etc. This qualitatively changes the nature of the relationship-both the content of what knowledge is shared and how that knowledge is shared. The purpose of this study is to provide an empirical test of whether peer mentoring facilitates organizational knowledge sharing and to explore whether employees can be trained to be more effective peer mentors.

CONCEPTUAL BACKGROUND AND HYPOTHESES

In knowledge-intensive firms, such as the software firm used in the present study, managers place a premium on technical competence, making job-related knowledge extremely valuable to employees and to the firm. Therefore, in the present study, we examine the sharing of job-related and technical knowledge in the peer mentoring relationship. Next we examine the strategic value of organizational knowledge before exploring how peer mentoring facilitates the sharing of knowledge between peer mentors and apprentices.

Organizational Knowledge and Peer Mentoring

Creating and sharing knowledge more effectively than competitors provides the possibility for creating competitive advantages (Boisot, 1998; Grant, 1996; Kogut and Zander, 1992; Teece, 1998). Organizational knowledge includes all the tacit and explicit knowledge that individuals possess about products, systems, and processes and the explicit knowledge codified in manuals, databases, and information systems. There are many processes that researchers have identified, but they tend to fall into one of three main categories: creating knowledge (March, 1991; Nonaka, 1994; Crossan et al., 1999), sharing knowledge (Grant, 1996; Nonaka, 1994; Szulanski, 1996) and exploiting knowledge (Boisot, 1998; March, 1991; Nonaka, 1994). There is a growing body of research on organizational knowledge examining important issues, including stocks and flows of knowledge (Bonus, 2002), absorptive capacity (Cohen and Levinthal, 1990), knowledge transfer and contingent workers (Matusik and Hill, 1998), and internal stickiness of knowledge (Szulanski, 1996). We examine the creation and sharing of knowledge in this study. In particular, we assess individuals' perceptions of knowledge creation and sharing behaviors in their teams and firm.

Considering the importance of organizational knowledge, we need to examine how peer mentoring impacts organizational knowledge. Peer mentoring is becoming increasingly common in organizations and, moreover, is receiving more attention from scholars because it may offer some unique advantages over traditional mentoring relationships (Allen et al., 1997; Eby, 1997; Eddy et al., 2005; Ensher et al., 2001). Peers can provide the same kinds of psychosocial and vocational support as traditional mentors, but they are uniquely qualified to provide job-related and technical knowledge (Eby, 1997; Ensher et al., 2001; Kram and Isabella, 1985; Young and Perrewé, 2004).

Peer mentoring provides a mechanism for sharing job-related knowledge (Allen et al., 1997, 1999; Eby, 1997; Eddy et al., 2005; Ensher et al., 2001). Knowledge workers may be with one firm for a short time or in one position within a firm for a short time, which results in relatively high turnover rates and creates a need for constantly training new employees and team members. Peer mentoring provides a valuable method for sharing knowledge when employees frequently move to new jobs, teams, or firms. Peer mentoring facilitates the sharing of knowledge from mentor to apprentice and from apprentice to mentor (Borredon and Ingham, 2005; Ensher et al., 2001; Kram, 1985; Young and Perrewé, 2000).

Much of the knowledge that peer mentors possess is tacit and learned from personal experience and from interacting with other employees. Most of the taken-for-granted knowledge of the peer mentor is not recorded in any database, procedure manual, or formal training program (Swap et al., 2001). The pace of change is so rapid in most jobs in a software firm that any formalized knowledge is quickly outdated. Therefore, these companies rely on their experienced employees to impart their knowledge to less experienced employees (Eby, 1997; Swap et al., 2001; Young and Perrewé, 2000).

Peer mentors engage in several social behaviors to share job-related knowledge, including 1) defining the peer mentoring relationship, 2) managing communication between the mentor and apprentice, 3) selecting and focusing on key information to be shared, 4) teaching to different learning styles when training, 5) assessing whether the apprentice is understanding the concepts in the training, 6) giving feedback on performance and goal attainment, and 7) developing a clear action plan for mentoring the apprentice (Eby, 1997; Kram and Isabella, 1985; Trautman, 1999). We refer to these social behaviors as "peer mentoring behaviors," and the extent to which individuals understand how to utilize these mentoring behaviors we refer to as "peer mentoring competence."

Next we examine the psychosocial processes involved in creating and sharing knowledge through peer mentoring. Peer mentoring provides an opportunity to externalize knowledge by turning tacit knowledge into explicit knowledge (Nonaka, 1994). This is a powerful form of knowledge creation and provides a key source of innovation and new ideas in firms. Peer mentors share externalized knowledge when they take time to organize their thoughts, write them down, and make explicit what they understand implicitly. When the apprentice understands the concept the mentor is sharing, the peer engages in internalization and converts explicit knowledge to tacit knowledge (Swap et al., 2001). Internalization is closely related to learning by doing (Nonaka, 1994), which the peer does while being mentored (Swap et al., 2001). Internalization occurs when a more experienced peer helps a less experienced one "interpret events, understand technology and business processes, and identify the values and norms of an organization" (Swap et al., 2001:98).

In many circumstances employees bypass the externalization and internalization processes and share knowledge by demonstrating how to do a particular procedure or solve a particular programming problem through the socialization (tacit-to-tacit knowledge) process (Nonaka, 1994; Swap et al., 2001). Within software development teams, software development engineers often demonstrate how to use a particular software tool to solve a problem. They combine verbal directions with visual demonstrations. Nonaka (1994) argues that this personal contact between employees is essential to creating new knowledge, because the more experienced software developers may be the only ones in the entire firm that understand how to use certain features of the software. Peer mentoring accelerates this process by helping mentors organize their thoughts and share relevant, appropriate knowledge in ways the apprentices can learn (Swap et al., 2001). Employees who understand how to mentor their peers and actually engage in mentoring behaviors regularly would be considered competent peer mentors. Therefore, we would expect that peers who are more effective mentors should be more effective at transferring knowledge. We tested the following hypotheses by collecting feedback from individuals, the peers they mentored and their supervisors:

Hypothesis 1A: Higher self-perceived levels of peer mentoring competence and behaviors are associated with higher self-perceived levels of knowledge creation and sharing.

Hypothesis 1B. Higher peer-perceived levels of peer mentoring competence and behaviors are associated with higher peer-perceived levels of knowledge creation and sharing.

Hypothesis 1C Higher supervisor-perceived levels of peer mentoring competence and behaviors are associated with higher supervisor-perceived levels of knowledge creation and sharing.

Managers can take an active role in facilitating effective peer mentoring through training and motivating mentors. Peer mentor training is one valuable method for increasing an employee's competence and ability to mentor peers by providing them with essential knowledge for effectively mentoring peers. Peer mentor training provides opportunities for the mentors to practice their mentoring skills-such as focusing on the important information, teaching to different learning styles, and providing clear and timely feedback-in a safe environment and receive immediate feedback. Training can also increase employees' motivation to mentor their peers by highlighting the benefits of mentoring. These benefits include 1) personal gratification and recognition, 2) new team members come up to speed more quickly and contribute to the team sooner, and 3) mentors can complete training more quickly and return to their own work, thereby making them more effective and efficient (Eby, 1997; Trautman, 1999). This study adopted Kirkpatrick's (1983) four-level model for the evaluation of training as follows: 1) reaction, 2) learning, 3) behavior changes, and 4) organizational results. This study assesses levels 2 (learning) and 3 (behavior changes). We tested the following hypothesis:

Hypothesis 2: Employees who receive peer mentor training exhibit higher levels of peer mentoring competence and behaviors than those who do not receive training.

METHOD

Participants

The participants represent the major areas of the firm and include software testers, software design engineers, program managers, usability engineers, Web services engineers, and support professionals. All of these jobs are knowledge-intensive and should benefit from improved peer mentoring competence and behaviors. Participants represented three hierarchical levels-individual contributor, team lead, and manager. All participants were full-time employees at the company headquarters.

We used a field-based quasi-experimental design with a delayed treatment control group. The research method is based on Lawler's (1977) concept of adaptive experiments. Adaptive experimental designs control for several threats to validity, including history, maturation, testing, instrumentation regression (one of the groups picked because it is extreme), and mortality. Data were collected using a Web-based survey from employees of a large Northwest software firm that participated in a oneday training course. We used a repeated measures design-training participants were surveyed three times: one week before the training, two days after the training, and again two months after the training. We assessed for a testing effect by using a modified delayed treatment control group design (Cook and Campbell, 1979). Half of the members of each training session were hrandomly assigned to the delayed treatment group, which received two surveys before the training and then surveys two days after and two months after the training. The participants in the delayed treatment control group received a survey approximately one week before the training. They then were told a few days later that there had been a problem with their first survey, and they were asked to fill out a second survey. This group then participated in the training with the other participants (see Figure I).

The total sample is 502 participants in the training course who filled out the first survey. Participants averaged 33 months at the firm, 17 percent had some college, 59 percent had an undergraduate degree, and 23 percent had a graduate degree. Time at firm was mildly positively skewed, so, this variable was converted to a normal distribution through a natural log transformation. Participants were 63.7 percent men and 36.3 percent women. This is proportional to the firm as a whole. Table 1 shows descriptive statistics and correlations for all variables.

Participation in the training was voluntary as was filling out the surveys. Given that participants volunteered their time to fill out the surveys, response rates are remarkably high. Of the 700 employees who received the training, 502 (71.7%) filled out the survey at Time 1 (before training). Of the 502 who filled out the Time 1 survey, 352 (70.1%) filled out the Time 2 (after training) survey. The delayed treatment control group consisted of 152 (30.2%) respondents randomly selected from those who filled out the Time 1 survey, and these participants received a second survey prior to the training. Of the 352 who filled out the Time 2 survey, 222 (63.1%) filled out the Time 3 (two months after training) survey. Of the 222 who filled out all three surveys, 98 (44.1%) of their managers filled out a Manager survey and 61 (27.4%) of their peers filled out a survey. There were no significant differences on demographic variables between participants who completed the survey at Time 1 versus those who did not complete the survey at Time 1. There were no differences on any variables for participants who filled out surveys at both Time 1 and Time 2 and those who responded at Time 1 only. There were also no differences between those who responded at Time 1, Time 2 and Time 3, and those who only responded at Time 1 and Time 2. Therefore, there does not appear to be a self-selection bias in the surveys.

Design and Procedure

Participants voluntarily signed up for the training and were assigned to training dates based on schedule availability. The instructors for all the courses were trained by the developer of the peer mentor training course and were not informed of the study's hypotheses. All the training courses covered the same material, using the same handouts and PowerPoint slides. There were no differences on key measures between the three trainers. Participants in the study received a one-day training course that covered basic peer mentoring skills. The training was provided in two four-hour sessions, one in the morning and one in the afternoon. The training covered the following peer mentoring topics: 1) defining the peer mentoring relationship, 2) managing communication between the mentor and apprentice, 3) how to select and focus on key information to be shared, 4) teaching to different learning styles when training, 5) assessing whether the apprentice is understanding the concepts in the training, 6) how to give feedback on performance and goal attainment, and 7) developing a clear action plan for mentoring the apprentice. Following the training, some participants were formally assigned as mentors, while others informally mentored co-workers. In either case, mentoring was not a part of their formal performance evaluation.

Participants received emails one week before the training requesting that they click on a link to a Web survey and fill out the survey. Participants who did not respond to the first email received a reminder email to encourage them to participate in the study. Participants who completed surveys at each stage of the study were entered in a drawing for a $25 gift certificate at Amazon.com. Employees who attended the training and filled out the Time 1 survey received a second email two days after the training, requesting that they again fill out a Web-based survey. Participants who did not respond to the first email received a reminder email to encourage them to fill out the survey. Participants who filled out eurveys at Time 1 and Time 2 were sent an email and asked to fill out a Web-based survey two months after the training.

Independent Assessments (Time 3). We asked participants who filled out surveys at Time 1 and Time 2 to sup ply the email addresses of one or two peers they mentored during the previous two months. An email was then sent to the peers asking them to fill out a survey about their peer mentors. As a second source of independent feedback, we sent a survey to each participant's manager. Reminder emails were sent to managers who did not respond to the first email. The surveys sent to peers and managers were directly based on the surveys sent to participants, but did not include identical items.

Manipulation Check. We conducted a manipulation check in a pilot study to assees whether the participants understood the basic content of the peer mentoring course. Forty-two participants in a pilot study filled out a five-question (with five answer options) multiple-choice quiz at the end of the training. Randomly selecting answers would result in 20 percent correct anewers. Therefore, we believe that average scores of 80 percent or greater, which are significantly greater than 20 percent, indicate that the training is communicating the key concepts and having the desired effect. Forty-two participants filled out the quiz and scored an average of 80 percent.

Measures

The survey instrument was composed of demographic items and two individual scales: 1) peer mentoring competence and behaviors and 2) organizational knowledge creation and sharing. All scale items used a five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree). All scales were developed following procedures recommended by DeVellis (1991). We pre-tested these items as part of a pilot study. The pilot study involved 100 employees of the same firm that this study was conducted at and used a pre-post-post Web-based survey design. The pilot study results indicated that the measures of peer mentoring and knowledge had Cronbach's alphas at Time 1, Time 2, and Time 3 that ranged from .81 to .92, which suggests that the scales are reliable. We selected items for the final scales based on inter-item correlations and factor structure.

Peer Mentoring. Although there are mentoring scales that have been used in prior research (e.g. Scandura, 1992), these scales only address the vocational, career, and psychosocial support functions of mentoring. There are no published scales on the technical, job-related role of peer mentors. This role is critical in helping newcomers become more effective in their jobs. Therefore, we developed a 13-item scale that measured technical peer mentoring competence and behaviors. The scale items assess participants' knowledge of the peer mentoring skills as well as their ability to use the skills. The peer mentor scale items along with their itemtotal correlations and Cronbach's alpha are presented in Table 2.

We selected the items for the final scales based on inter-item correlations and confirmatory factor analysis. We deleted one item from the peer mentor scale as a result of low item total correlation and a loading below .40 in the confirmatory factor analysis. Results were consistent across the administrations of the survey (Before, After, 2 Months After). The 13-item peer mentor scale had Cronbach's alphas of .84 at Time 1 (Before) (N = 476), .90 for the Control group (N = 144), .91 at Time 2 (After) (N = 338), and .91 at Time 3 (2 months after) (N = 200). This suggests that the scale is reliable and stable over time. Peer mentoring had a mean of 3.69 at Time 1, 3.67 for the Control group, 4.19 at Time 2 and 4.16 at Time 3. The peer mentoring measures at Time 1, Time 2, and Time 3 were significantly correlated (r > .29, p < .01), which indicates test-retest reliability.

Knowledge Creation and Sharing. We constructed a 10-item scale to measure perceptions of knowledge creation and sharing behaviors, based on items developed by Bontis (2002). The items in the Bonus (2002) study assessed stocks and flows of knowledge at the individual, group and organizational level. These items were adapted for this study to assess knowledge creation and sharing at the group and organizational level (see Table 2). Six items assessed creating knowledge (e.g., "My firm's workers constandy generate new ideas," "My firm does all it can to launch new products and services"). Four items assessed sharing knowledge (e.g., "Members of my team actively talk with each other and share knowledge"). The 10-item knowledge scale had a Cronbach's alpha of .85 at Time 1, .89 in the Control group, .89 at Time 2, and .91 at Time 3 (see Table 2). This suggests the scales are reliable and stable over time. Knowledge creation and sharing had a mean of 3.70 at Time 1, 3.71 in the Control group, 3.96 at Time 2, and 4.00 at Time 3. Knowledge creation and sharing measures at Time 1, Time 2, and Time 3 were significantly correlated (r > .51, p < .01), suggesting test-retest reliability.

As expected, a confirmatory factor analysis using Amos 4.0 (Arbuckle and Wothke, 1999) supported the fit of a two-factor model for peer mentoring and knowledge creation and sharing (Comparative fit index (CFI) and Incremental fit index (IFI) = .97, Normed fit index (NFI) and Tucker-Lewis index (TLI) = .96, Relative fit index (RFI) = .95, Root mean square error of approximation (RMSEA) = .097 (95% CI = .092 - .101)). Results of all Amos analyses are based on using raw data as input and on maximum likelihood estimation. Although a nested one-factor model provided a reasonable fit (CFI, IFI and NFI = .95, TLI and RFI = .94, RMSEA = .114 (95% CI = .110 - .114)), the two-factor model provided a superior fit (Δ X2 (1, N = 589) = 537.45, p < .0001). The two factors underlying the items were called peer mentoring and knowledge creation and sharing. Factor loadings (i.e., standardized regression coefficients) in the two-factor model for (1) peer mentoring items and their respective underlying factor ranged from .40 to .64 and (2) knowledge creation and sharing items and their respective underlying factor ranged from .51 to .71. All loadings for each factor were significant at p < .001. In the one factor model, three items loaded below .40, the RMSEA was larger than in the two-factor model, and there was no overlap in the confidence intervals for the RMSEA, confirming that the two-factor model provides a better fit.

Control Variables. We controlled for gender (0 = female, 1 = male) and time with the firm (months), which past research has suggested may impact mentoring.

Construct Validity. All items were developed for this study with the input of managers at the firm, the peer mentor training course developer and research colleagues. Items were pre-tested on a sample at the firm and feedback was incorporated into the final scales to eliminate redundant questions and clarify item wording. Items were developed following DeVellis' (1991) recommendations for scale development in order to build validity into the measures. The confirmatory factor analysis indicates that the two scales capture independent constructs, which provides support for construct validity for these two scales. The significant correlation between peer mentoring and knowledge creation and sharing supports convergent validity for the scales.

RESULTS

Hypothesis 1A, 1B, and 1C proposed that higher perceived levels of peer mentoring would be associated with higher perceived levels of knowledge creation and sharing behaviors. We tested the hypotiieses using hierarchical regression analysis (see Table 3). We conducted separate regressions for self-ratings (Hypothesis 1A), peer ratings (Hypothesis 1B), and manager ratings (Hypothesis 1C). Model 1 tested Hypothesis 1A and used Time 3 self-report data (two months after training) and regreseed the control variables on knowledge creation and sharing. The overall model did not explain a significant amount of variance (R2 = .01, F (2, 213) = .80, p> .05). None of the control variables were significant. Model 2 added peer mentoring competence and behaviors into the model, which resulted in a significant increase in the predictive strength of the model (ΔR2 = .33, ΔF(1, 212) = 107.65, p <.001). Model 2 predicted a significant amount of variance (R2 =.34, F (3, 212) = 36.68, p < .001). In support of Hypothesis 1A, peer mentoring was a significant and positive predictor of self-perceptions of knowledge creation and sharing behaviors (β = .59, p < .001). This suggests that individuals' higher perceived levels of peer mentoring contribute to higher perceived levels of knowledge creation and sharing behaviors.

In addition to self-ratings, Hypothesis 1B asked whether peers that were mentored by training participants also perceived increased levels of peer mentoring. Model 3 regressed the control variables on knowledge creation and sharing. The overall model did not explain a significant amount of variance (R2 = .003, F (2, 59) = .08, p > .05). None of the control variables were significant. Model 4 added peer mentoring into the equation, which resulted in a significant increase in the predictive strength of the model (ΔR2 = .17, ΔF (1, 58) = 12.13, p < .01). Model 4 explained a significant amount of the variance in the dependent variable (R2 = .18, F (3, 58) = 4.11, p < .05). In further support of Hypothesis 1, peer mentoring was a significant and positive predictor of perceptions of knowledge creation and sharing (β = .43, p < .01).

Hypothesis 1C asked whether managers of the training participants also perceived increased levels of peer mentoring. Model 5 regressed the control variables on knowledge creation and sharing. The overall model did not explain a significant amount of variance (R2 = .04, F (2, 100) = 2.03, p > .05). None of the control variables were significant predictors. Model 6 added peer mentoring into the model, which resulted in a significant increase in the predictive strength of the model (ΔR2 = .16, ΔF (1, 99) = 19.70, p < .001). Model 6 explained a significant amount of variance in knowledge creation and sharing (R2 = .20, F (3, 99) = 8.17, p < .001). Peer mentoring was significant and positively correlated with perceptions of knowledge creation and sharing behaviors (β = .41, p < .001), supporting Hypothesis 1. All three reports-self, peer, and manager-indicated a positive and significant relationship between peer mentoring and knowledge creation and sharing. In support of Hypothesis 1, we can thus be confident that higher perceived levels of peer mentoring contribute to higher perceived levels of knowledge creation and sharing behavior.

Hypothesis 2 predicted that peer mentor training would increase perceptions of the level of individuals' peer mentoring competence and behaviors. We tested this hypothesis with repeated measures ANOVA. The first ANOVA compared the training group before and after the training to the control group. The second ANOVA compared the peer mentoring scores for the training group at Time 1, Time 2 and Time 3. We assessed for a testing effect by using a modified delayed treatment control group design (Cook and Campbell, 1979). Half of the members of each training session were randomly assigned to the delayed treatment group. A repeated measures ANOVA comparing the control and training groups at Time 1 and Time 2 indicated that there was a significant increase in perceptions of peer mentor competence and behaviors for the training group, (F(1, 385) = 69.86, MSerror = 9.27, p < .001), such that peer mentoring levels are significantly higher after the training (see Table 4). The control group was unchanged from Time 1 to Time 2. There was a significant interaction between training and treatment, suggesting that at Time 2 there was a significant difference between the control and treatment groups, (F(1, 385) = 89.36, MSerror = 11.86, p < .001).

An examination of the means for peer mentoring competence and behaviors at Time 2 indicates that the treatment group (M = 4.19) is significantly higher than the control group (M = 3.67). This suggests that simply completing the survey two times does not increase participants' perceptions of peer mentoring competence and behaviors. In support of Hypothesis 2, it also suggests that the training significantly increases individuals' perceptions of their own peer mentoring competence and behaviors. A second repeated measures ANOVA that included Time 1, Time 2, and Time 3 indicated that there was a significant increase in perceptions of peer mentor competence and skills (F(2, 434) = 123.11, MSerror = 17.04, p < .001), such that peer mentoring levels are significantly higher after the training (see Table 5). The mean for peer mentoring increased from 3.69 at Time 1 to 4.19 at Time 2, and declined only slightly to 4.16 at Time 3. There is a significant linear effect (F(1, 434) = 132.09, MSerror = 23.20, p < .001), as well as quadratic effect (F(1, 434) = 107.52, MSerror = 10.87, p < .001), suggesting that peer mentoring levels increase after the training and remain higher two months after the training. This also suggests there is a long-term impact to the training and that participants increase their perceived levels of peer mentoring competence and behaviors as a result of the training.

DISCUSSION

Implications for Theory and Future Research

Relatively little empirical work has been done on the factors that facilitate organizational knowledge creation and sharing. This study provides an initial empirical test of the relationship between peer mentoring and knowledge creation and sharing. Results suggest that there was a significant relationship between higher perceived levels of peer mentoring competence and behaviors and higher perceived levels of knowledge creation and sharing. This supports the notion that knowledge is shared in peer mentoring relationships. Results suggest that peer mentors, as well as the apprentices they mentored, perceived a relationship between peer mentoring and knowledge creation and sharing. Facilitating peer mentoring is critical to sharing knowledge between employees and fostering knowledge creation and sharing in the organization, which has been linked to the creation of competitive advantages (Boisot, 1998; Grant, 1996).

The traditional mentoring literature has tangentially explored the link between mentoring and information or knowledge sharing (Borredon and Ingham, 2005; Hezlett, 2005). This study builds on the existing mentoring literature by examining another important form of mentoring - peer mentoring - and analyzing its impact on knowledge creation and sharing. This study provides a theoretical contribution by developing the concept of peer mentoring, but also links it to one of its potentially valuable outcomes-facilitating knowledge creation and sharing. Our results suggest that peer mentoring may be an effective way to facilitate the creation and sharing of knowledge, through its intentional linking of trained mentors with newer, less-experienced workers. While information systems and knowledge systems are one important way to store and share knowledge, the interpersonal nature of peer mentoring provides for the dynamic, continuous creation and sharing of ideas that cannot be replaced by networked computers.

This study indicates that peer mentor training can help workers increase their level of peer mentoring competence and skills. Perceived levels of peer mentoring increase immediately after the training and still are significantly higher two months later. This suggests that there may be a longer-term impact to peer mentor training and that participants increase their level of peer mentoring competence and skills as a result of the training.

Feedback from apprentices who were mentored also supports the relationship between mentoring and knowledge, suggesting that these apprentices also see knowledge being shared in the mentoring relationship. Participants' managere also perceived a positive and significant relationship between peer mentoring and knowledge creation and sharing, providing further support for the sharing of knowledge in the peer mentoring relationship.

Future research can explore additional benefits from the peer mentoring relationship, such as psychosocial support and career support. Researchers can also examine factors that facilitate and inhibit effective peer mentoring, such as the nature of the work itself, the leadership style of the team leader, the company culture, and the availability of other training. These same factors may impact how effectively the peer mentoring relationship facilitates the sharing of knowledge. Adding these variables will aid in the formation of a more comprehensive model of peer mentoring. Peer mentoring may also result in other beneficial organizational outcomes, such as lower turnover, higher performance evaluations, and more effective teams. Future research should validate the peer mentoring and knowledge creation and sharing measures.

Implications for Training and Development Programs

This study suggests that peer mentor training can help employees increase their levels of peer mentoring competence and behaviors by presenting basic peer mentoring skills, opportunities to practice the skills, and motivations for mentoring. Individuals perceived higher levels of peer mentoring competence and behaviors immediately after the training and still perceived them to be higher two montiis later. This suggests that there is a long-term impact to peer mentor training and that employees are more effective peer mentors as a result of the training. This has clear implications for training and development programs. If peer mentors can facilitate the sharing of organizational knowledge and, moreover, if employees can become more effective peer mentors as a result of training, then by implementing a peer mentor training program, firms can help peer mentors more effectively share knowledge. Additional research needs to be conducted on antecedents and consequences of effective peer mentor training, such as team dynamics, leadership styles, and performance evaluations.

Limitations

This study has potential limitations. First, given that all our variables were self-reports collected with one type of instrument, common method bias may have affected the relationships. However, data were collected at three time points and the findings were consistent across the three times. There is also no reason to believe that there is a widespread assumption by participante that higher levels of peer mentoring are related to higher levels of knowledge creation and sharing. We also collected feedback from peers and managers in addition to self-reports. Although the basic relationship between peer mentoring and knowledge creation and sharing was supported across all three relationships, the three measures were not significantly correlated. There are several reasons why this might be the case. First, the self-report, peer and manager scales are not identical. The peer and manager scales are a subset of the participant's self-report scale. Second, the samples for peers and managers were relatively small, thus creating power issues as well as unequal sample sizes. It is possible that if the samples were larger and consistent in size that a significant correlation between raters would be found. Third, the lack of agreement among raters could be due to the raters actually observing different types of change (Golembiewski and Billingsley, 1980). Fourth, current performance evaluation research that uses multiple raters has found very low correlations among self-ratings, peer-ratings, manager-ratings and subordinate-ratings (Atwater et al., 1995).

Concluding Remarks

This study suggests that firms that are able to raise their employees' levels of peer mentoring through training can increase knowledge creation and sharing in their organizations. The knowledge-based view of the firm suggests that firms that are able to increase knowledge creation and sharing can create sustainable competitive advantages. Increasing peer mentoring may help firms create competitive advantages.

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Last updated: 05/01/2008 - 03:06 PM