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The Role of E-Mentoring in Proteges' Learning and Satisfaction

December 2013
Group & Organization Management 38(6):743-774

DOI:10.1177/1059601113511296

Authors:

Suzanne C. de Janasz

Seattle University

Veronica M. Godshalk

Pennsylvania State University

Today's professionals require a network of mentors to help them navigate complex organizational and individual challenges. Consistent with current trends, a growing number of these mentor relationships will be initiated and carried out electronically, via e-mentoring. We build on existing social network research to investigate the role of e-mentoring in protege outcomes. On a sample of graduate and undergraduate students, we examine the impact of dyad characteristics (e.g., interaction frequency, pre-existing relationship, perceived similarity, relevant mentor knowledge) on e-mentoring received as well as the impact of e-mentoring on proteges' learning and satisfaction. Several dyad characteristics and e-mentoring functions received were positively associated with proteges' learning and satisfaction. Limitations and implications for future research are offered.

. Correlations Among Study Variables.

…

. Hierarchical Regression: E-Mentoring Functions as Dependent Variables (Standardized Beta Coefficients Shown).

…

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Article

The Role of E-Mentoring

in Protégés’ Learning

and Satisfaction

Suzanne C. de Janasz1

and Veronica M. Godshalk2

Abstract

Today’s professionals require a network of mentors to help them navigate

complex organizational and individual challenges. Consistent with current

trends, a growing number of these mentor relationships will be initiated

and carried out electronically, via e-mentoring. We build on existing social

network research to investigate the role of e-mentoring in protégé outcomes.

On a sample of graduate and undergraduate students, we examine the impact

of dyad characteristics (e.g., interaction frequency, pre-existing relationship,

perceived similarity, relevant mentor knowledge) on e-mentoring received

as well as the impact of e-mentoring on protégés’ learning and satisfaction.

Several dyad characteristics and e-mentoring functions received were

positively associated with protégés’ learning and satisfaction. Limitations and

implications for future research are offered.

Keywords

e-mentoring, learning, satisfaction

E-mentoring, the process of using computer-mediated communication

(CMC) technology as the primary means of communication between mentors

and protégés, has become widely used. CMC—that is, the internet, e-mail,

1IMD, Lausanne, Switzerland

2Penn State University Brandywine, Media, USA

Corresponding Author:

Suzanne C. de Janasz, IMD, Chemin de Bellerive 23, Lausanne 1001, Switzerland.

Email: Suzanne.dejanasz@imd.ch

XXX10.1177/1059601113511296Group & Organization Managementde Janasz and Godshalk

research-article2013

2 Group & Organization Management XX(X)

instant messaging, and related technologies—has changed the way we com-

municate. World-wide Internet users currently exceed two billion (665%

growth since 2000), and among the 348.3 million North Americans, more

than 78% communicate online and over 49% are Facebook users (Internet

World Stats, 2012). Given the growing number of CMC users and a business

climate characterized by layoffs, worker mobility, boundaryless careers, and

increased work demands, use of electronic means to expand one’s network of

developmental relationships is not only tenable but also critical for career

success (de Janasz, Sullivan, & Whiting, 2003; Dobrow, Chandler, Murphy,

& Kram, 2012; Higgins & Kram, 2001; Sproull & Kiesler, 1999).

Social network theory suggests that developmental relationships are nec-

essary as the context of mentoring becomes more turbulent and career actors

are more apt to draw on a variety of sources for support in their career

(Dobrow et al., 2012; Higgins, Chandler, & Kram, 2007). Ensher and Murphy

(2007) suggest that e-mentoring can boost the likelihood of initiating devel-

opmental relationships by increasing accessibility of mentors, equalizing

salient differences of partners, and decreasing emphasis on demographics

(e.g., race, age) identified through face-to-face meetings. Based on this

framework, the purpose of this study is to gauge the effects of e-mentoring on

protégés’ learning outcomes using a sample of graduate and undergraduate

students who seek e-mentors and experience e-mentoring episodes (Fletcher

& Ragins, 2007) or developmental interactions during a semester.

E-mentoring is an ongoing, mutually beneficial relationship whereby a

more experienced partner transmits mentoring functions via electronic means

to a less experienced partner (Ensher & Murphy, 2007; Godshalk, 2007).

Contrasted with traditional mentoring, e-mentoring involves far less real

face-time between mentor and protégé (Hamilton & Scandura, 2003). Despite

this difference, there is growing anecdotal and empirical evidence suggesting

that the benefits of e-mentoring compare favorably with those derived from

traditional mentoring (e.g., de Janasz, Ensher, & Heun, 2008; MentorNet,

2002, 2003; Simmonds & Lupi, 2010). The functions received in e-mentor-

ing relationships parallel those found in traditional relationships and include

career development (coaching, sponsoring, increasing exposure and visibil-

ity, and offering protection), psychosocial support (offering acceptance and

confirmation, providing counseling and friendship), and role modeling

(Kram, 1985; Ragins & Kram, 2007; Scandura, 1992). E-mentors have been

found to offer career development and psychosocial support as effectively as

face-to-face mentors, although they are not as effective in providing role

modeling (Hamilton & Scandura, 2003).

An important outcome of traditional mentoring is the protégé learning

potential. Protégés report that the expectation of learning is a key factor in

de Janasz and Godshalk 3

their involvement in formal mentoring programs (Allen & O’Brien, 2006;

Eby & Lockwood, 2005). However, informal mentoring relationships are

found to be more apt in providing for protégé learning and goal attainment

than formal relationships (Godshalk & Sosik, 2003; Ragins, Cotton, & Miller,

2000; Wanberg, Welsh, & Hezlett, 2003). Learning occurs when a mentor

guides the protégé in setting and achieving developmental goals (Lankau &

Scandura, 2002). Mentors serve as role models, encourage protégés to

become involved in learning (Allen, Russell, & Maetzke, 1997), and offer

feedback to help protégés attain their goals (Godshalk & Sosik, 2003;

Megginson, 1988; Scandura, 1992). Mentors report that they are attracted to

protégés who have a learning orientation and to relationships that are focused

on providing learning opportunities (Allen, Poteet, & Burroughs, 1997). Not

surprisingly, protégés who had a high learning goal orientation reported

greater amounts of mentoring functions received (Godshalk & Sosik, 2003).

In addition, protégés’ learning benefits have been found to include tactical

career advice as well as enhanced academic performance, professional net-

work, and job opportunities (de Janasz et al., 2008; MentorNet, 2002; Miller,

1999).

Protégé job and career satisfaction has also been linked with mentoring

(Allen, Eby, Poteet, Lentz, & Lima, 2004; Baugh & Scandura, 1999; Singh,

Ragins, & Tharenou, 2009). Protégé satisfaction is in part determined by the

amount of constructive feedback received and frequency of interactions with

the mentor (Lyons & Oppler, 2004). In sum, past research suggests a positive

relationship between mentoring received and protégé learning and satisfac-

tion. This study builds on the above noted literature by empirically investi-

gating the relationship between dyad characteristics, e-mentoring functions

received, and protégés’ learning and satisfaction.

Dyad Characteristics and E-Mentoring

Koberg, Boss, and Goodman (1998) offered a mentoring model suggesting

that dyad characteristics may affect mentoring functions received and

learning outcomes. Wanberg et al. (2003) expanded on Koberg et al.’s

model, adding mentor and protégé characteristics, such as knowledge and

skills, demographics, frequency of interaction, and experience in mentoring

relationships. Drawing on these models, this research posits that dyad fac-

tors will affect e-mentoring functions received and associated learning out-

comes. The choice of these variables is rooted in myriad literatures, most

particularly social network theory (Dobrow et al., 2012; Higgins et al.,

2007) and CMC theory (J. R. Carlson & Zmud, 1999; Walther, 1996). Kram

(1985) noted that individuals seek mentors who have similar values about

4 Group & Organization Management XX(X)

work and learning as well as those who are competent. Walther (1996)

noted that in CMC environments, when individuals exchange information,

build impressions, compare values, and provide timely feedback for each

other, highly interpersonal relationships may develop. Finally, frequency of

interaction and the existence of a previous relationship are dyad factors that

have been examined previously (Allen, Poteet, et al., 1997; Lyons & Oppler,

2004; van Emmerik, 2004a).

This study’s definition of e-mentoring builds on definitions offered by

Godshalk (2007) and Ensher and Murphy (2007). An e-mentor provides a

career development function, whereby he or she promotes professional

growth by providing challenging assignments, exposure, visibility, and pro-

tection via CMC interactions. The e-mentor also fulfills a psychosocial

function, such that she or he promotes personal growth by providing emo-

tional support, counseling, acceptance, and guidance. Finally, the e-mentor

offers role modeling functions through which the protégé identifies with and

emulates the e-mentor, who is trusted and respected, possesses expert and

referent power, and holds high standards (de Janasz et al., 2008; Gibson &

Cordova, 1999; Thibodeaux & Lowe, 1996). Even though they are not wit-

nessed first-hand, behaviors and experiences shared by a trusted e-mentor

and related via electronic exchanges provide models for protégé consider-

ation (MentorNet, 2002). These relationships are modeled in Figure 1. The

following sections will develop the study’s hypotheses. First, the relation-

ships between the antecedent dyad factors and e-mentoring functions

received are examined and relevant hypotheses developed. Then, hypothe-

ses are proffered related to the relationships between e-mentoring and

Dyad Antecedents

Enhanced skill self-efficacy

Increased course

concept application

Learning via e-mentoring

Satisfaction with e-

mentoring relationship

Career development

Psychosocial

support

Role modeling

Interaction frequency

Comfort with CMC

relationship

Relevant mentor

knowledge

Perceived similarity

Pre-existing relationship

Learning and Satisfaction E-mentoring Received

Figure 1. Dyad relationship antecedents on e-mentoring received and protégé

learning and satisfaction.

de Janasz and Godshalk 5

protégé learning and satisfaction outcomes. This study is unique and makes

a strong contribution to the literature since the CMC theories are integrated

with the social network and mentoring literature, helping us understand the

impact of e-mentoring on protégés. Finally, the study’s limitations and

implications will be discussed.

Interaction Frequency

Koberg et al. (1998) characterize mentoring as an exchange between mentor

and protégé, wherein characteristics of the interaction affect its processes and

outcomes. The frequency of interaction between mentor and protégé has been

previously analyzed (Allen, Poteet, et al., 1997; Burke, McKeen, & McKenna,

1993; de Janasz et al., 2008; Grant-Vallone & Ensher, 2000; van Emmerik,

2004a; Waters, McCabe, Kiellerup, & Kiellerup, 2002). Allen, Poteet, et al.

(1997) found a positive relationship between amount of interaction and satis-

faction with the mentoring experience. Several studies (de Janasz et al., 2008;

Eby et al., 2013; Grant-Vallone & Ensher, 2000) found frequent interaction to

be positively associated with instrumental and psychosocial support received

by protégés. Frequent interaction has been found to be related to both mentor

and protégé perceptions of success and protégé intrinsic job satisfaction (van

Emmerik, 2004a; Waters et al., 2002). Finally, interaction frequency has been

found to mediate e-mentoring program antecedents and self-efficacy out-

comes (DiRenzo, Linnehan, Shao, & Rosenberg, 2010).

The CMC literature also posits that frequency of interaction between elec-

tronic partners will build and enhance the relationship (Walther, 1996).

Online community studies have found that CMC environments enable par-

ticipants to obtain social support through frequent interaction with each other

and finding common interests (Rheingold, 1993; Wellman & Gulia, 1999).

Moreover, since online communities are based more on shared interests than

on visual cues that can lead to bias and stereotypes, these participants dis-

close more quickly and readily, thereby building the trust critical for effective

mentoring or learning relationships (Mooradian, Renzl, & Matzler, 2006;

Sproull & Kiesler, 1999; Turkle, 1995; Wellman & Gulia, 1999). As

Berscheid, Snyder, and Omoto (1989, p. 794) reasoned, “the more time peo-

ple spend together, the more opportunity they have to influence each other’s

thoughts and behaviors.” Based on these findings, it is expected,

Hypothesis 1: Interaction frequency will be positively associated with

e-mentoring functions received; that is, protégés who report spending

more time interacting with the mentor will also report greater mentoring

functions received.

6 Group & Organization Management XX(X)

Pre-Existing Relationship

Wanberg et al. (2003) examined characteristics that mentors and protégés

bring to the relationship and that impact the intimacy achieved within the

dyad. Intimacy is facilitated through acknowledgment of complementary

skills each partner brings and a pre-existing relationship often improves and

advances the relationship (Kelley et al., 1983). Given experience, history, and

time associated with building a relationship, a pre-existing relationship

allows for continued sharing, building trust and intimacy (Hinde, 1995). This

pre-existing relationship results in partners disclosing more personal infor-

mation, including divulging mistakes, and engaging in more meaningful dia-

logue (Wanberg et al., 2003). Therefore, dyad members who have previously

known each other are apt to build stronger relationships than those who begin

the e-mentoring process with individuals they know less well.

Hypothesis 2: A pre-existing relationship will be positively associated

with e-mentoring functions received; that is, protégés who report previ-

ously knowing their e-mentor will also report greater e-mentoring func-

tions received.

Perceived Similarity

Koberg et al. (1998) suggest individual differences affect traditional mentor-

ing relationships. As mentoring relationships mature, demographic similarity

becomes less important and deep-level similarity regarding attitudes, values,

and goals becomes more important (Eby et al., 2013; Ensher, Grant-Vallone,

& Marelich, 2002; Lankau & Scandura, 2002; Turban, Dougherty, & Lee,

2002). When investigating e-mentoring relationships, de Janasz et al. (2008)

found perceived similarity to be positively related to e-mentoring functions

and relationship satisfaction, while actual demographic similarity was unre-

lated. These researchers suggest that “the use of electronic means to establish

mentoring relationships reduces the salience of observable differences in

favor of value similarity even in new, early stage relationships” (de Janasz et

al., 2008, p. 406). Walther (1996) also notes that CMC relationships often

originate and persist due to the closeness of values and ideas, rather than

demographic similarity. For these reasons, it is expected,

Hypothesis 3: Perceived similarity will be positively associated with

e-mentoring functions received; that is, protégés who report greater per-

ceived similarity with their mentor will also report greater e-mentoring

functions received.

de Janasz and Godshalk 7

Relevant Mentor Knowledge

Mentor characteristics affect mentoring functions provided (Ensher &

Murphy, 1997; Koberg et al., 1998). Not surprisingly, protégés seek mentors

with enhanced abilities, knowledge, interpersonal skills, power, organiza-

tional rank, and respect (Gaskill, 1991; Olian, Carroll, Giannantonio, &

Feren, 1988). When complementary skill sets exist between mentor and pro-

tégé, mentoring relationships thrive (Wanberg et al., 2003).

Therefore, we developed a construct, relevant mentor knowledge, to assess

the protégé’s perception of how the mentor’s skill set complements the pro-

tégé’s learning needs. Protégés often enter into mentoring relationships

because they expect to learn from them (Godshalk & Sosik, 2003). It is

expected that when protégés perceive their mentors as having knowledge that

will guide their career toward success, protégés will be receptive to and ben-

efit from the psychosocial, career development, and role modeling support

offered through these relationships. Therefore,

Hypothesis 4: E-mentor knowledge relevance will be positively associ-

ated with e-mentoring functions received; that is, protégés who report

greater e-mentor knowledge relevance will also report greater e-mentor-

ing functions received.

Protégé Comfort With Establishing a CMC Relationship

This study follows Walther’s (1992) relationship development theory and J.

R. Carlson and Zmud’s (1999) channel expansion theory, which emphasize

the user’s knowledge and experience base—rather than the technology

itself—as allowing the individual to participate in increasingly rich CMC

interactions. When dyad members are comfortable with CMC technology,

they reach out and develop relationships characterized by a richness and

depth of content that compares with face-to-face relationships, despite the

absence of nonverbal cues. CMC users may invoke knowledge-building

experiences—that is, previous experience with technology, discussion topic,

organizational context, or dyad co-participant—to establish their relationship

(J. R. Carlson & Zmud, 1999). Walther (1996) suggests that when users have

time to exchange information, build impressions, compare values, and pro-

vide timely feedback, CMC allows for highly interpersonal relationships to

develop. Other researchers have found that extensive use of e-mail reduces

anxieties associated with the technology and allows for relationships to be

built (R. E. Carlson & Wright, 1993; Fuller, Vician, & Brown, 2006;

McDowell, 1998). Therefore, it is expected that

8 Group & Organization Management XX(X)

Hypothesis 5: Comfort with establishing CMC relationships will be posi-

tively associated with e-mentoring functions received; that is, protégés

who report greater comfort with CMC relationships will also report greater

e-mentoring functions received.

Relationship Between E-Mentoring and Protégé

Outcomes

Among mentoring relationship outcomes studied, protégé learning and

satisfaction are key (Wanberg et al., 2003). Several studies have investi-

gated the learning outcomes protégés accrue in traditional relationships

(Allen & O’Brien, 2006; Eby & Lockwood, 2005; Godshalk & Sosik,

2003; Ragins et al., 2000; Scandura, 1992). Other studies, focusing on

online relationship, suggest that learning and satisfaction result from the

active involvement of students via technology-mediated interactions with

highly skilled business executives (Alavi, Wheeler, & Valacich, 1995;

Alavi, Yoo, & Vogel, 1997; Arbaugh, 2005; Arbaugh & Benbunan-Fich,

2006; Fuller et al., 2006).

In light of Alavi and Leidner’s (2001) suggestion that researchers should

consider the psychological processes that impact learning, this study focuses

on three specific learning variables—skill efficacy, increased course applica-

tion, and learning via e-mentoring—as well as relationship satisfaction, as

relevant variables for analyzing the cognitive and affective outcomes associ-

ated with e-mentoring. These variables, grounded in the literature, were spe-

cially developed for this purpose.

Skill Self-Efficacy

Self-efficacy refers to an individual’s belief that he or she can successfully

perform a specific task or activity (Bandura, 1986). Individuals with high

self-efficacy have been found to outperform lower self-efficacious individu-

als on several learning and performance outcomes (Bandura & Cervone,

1986; Ford, Smith, Weissbein, Gully, & Salas, 1998; Schunk, 1991). In the

mentoring literature, Day and Allen (2002) found career development sup-

port to be positively associated with self-efficacy. Deakins, Graham, Sullivan,

and Whittam (1998) found that e-mentors enhanced protégés’ ability to

achieve. Lewis (2002) found protégés reported improved self-confidence and

were more motivated to learn after interactions with their e-mentor. Taken

together, these findings suggest that e-mentoring enhances protégés’ skill

self-efficacy.

de Janasz and Godshalk 9

Increased Course Concept Application

Learning occurs not only vicariously but also through mastery (Bandura,

1986). Researchers found that students learn best by mastering experiential

learning exercises that integrate course concepts, critical thinking, and prob-

lem solving and that using e-mail had a positive effect on learning (Fuller et

al., 2006). Studies demonstrate that interacting with a mentor or classmate

can increase protégés’ ability to assimilate course-related knowledge and that

use of e-mail to facilitate course content discussions resulted in a higher level

of mastery than that obtained by students participating in traditional class-

room discussions (Gremler, Hoffman, Keaveney, & Wright, 2000;

Taechamaneestit, 2000). Hezlett (2005) found that protégés learn primarily

through explanations from and interactions with their mentors. Lankau and

Scandura (2002) found personal learning to be associated with mentoring

functions received. Through cumulative interactions with mentors, protégés

have the opportunity to transform knowledge into higher level learning such

as comprehension and application (Bloom, 1984). Reading how management

theories play out in the workplace and engaging in follow-on e-mail-based

conversations with their e-mentor facilitates protégés’ learning either vicari-

ously or through their own mastery (Whiting & de Janasz, 2004). This learn-

ing can be measured by students reporting increased course concept

application after interactions with the e-mentor. It is expected that e-mentor-

ing will be positively associated with increased course concept application.

Learning via E-Mentoring

Individuals who are motivated to learn are more apt to participate in develop-

ment programs like e-mentoring (Allen & O’Brien, 2006; Birdi, Allan, & Warr,

1997). When participating in such programs, individuals receive mentoring

functions and are encouraged to learn new skills, develop competencies, and

master skills. Protégés paired with e-mentors have been found to gain job-

related and discipline-specific information (Single & Muller, 2001; Single &

Single, 2005). Given that asynchronous learning environments have been

found to be as effective as face-to-face collaborations (Ocker & Yaverbaum,

1999), it is expected that protégés will report increased learning as a result of

interactions with e-mentors. We therefore include learning via e-mentoring as

an outcome to assess work-related learning accrued from interactions with the

e-mentor. The following relationship is therefore expected:

Hypothesis 6: E-mentoring functions received will be positively associated

with protégé learning; that is, protégés who report greater e-mentoring

10 Group & Organization Management XX(X)

functions received will report enhanced skill self-efficacy, increased course

concept application, and greater learning via e-mentoring.

Satisfaction With E-Mentoring Relationship

Studies of traditional mentoring relationships demonstrate that both career

development and psychosocial support are positively related to quality of and

satisfaction with the relationship (Ensher et al., 2002; Godshalk & Sosik,

2000; Ragins et al., 2000; van Emmerik, 2004a). Wanberg et al.’s (2003)

review of mentoring research describes a positive link between satisfaction

with mentor and protégé job satisfaction, career satisfaction, life satisfaction,

and career commitment. Other researchers have found that satisfaction is an

outcome of distance learning relationships (Alavi & Gallupe, 2003; Arbaugh,

2000, 2005). Based on these findings, we expect that e-mentoring relation-

ships will result in protégé satisfaction:

Hypothesis 7: E-mentoring functions received will be positively associ-

ated with protégé satisfaction; that is, protégés who report greater e-men-

toring functions received will report increased satisfaction with the

e-mentoring relationship.

Method

The sample consists of 228 undergraduate/graduate respondents (58.8% and

41.2%, respectively) from three mid-sized universities on the East and West

coasts who participated in an online mentoring assignment as part of the

requirements of one of their business school courses. For the assignment,

each student had to identify a practicing manager (ideally with 10 or more

years of experience, 10 or more direct reports, and budgetary responsibili-

ties), request and obtain his or her commitment (via e-mail) to participate in

an electronic mentoring relationship, and correspond electronically (via

e-mail) on course-related concepts of greatest interest to the student over the

entire semester. One key goal of this assignment was to augment class materi-

als and discussions by facilitating electronic discussions between the student

and a practicing manager (see Whiting & de Janasz, 2004, for a complete

description). By developing and asking their mentors questions (e.g., We

learned that empowering subordinates has both risks and rewards. What is

your view? Please share an example or two that demonstrates this view.),

students were able to acquire personally relevant and valuable information

about how course concepts (e.g., human resources, leadership, international

management) played out in the workplace; how such concepts were impacted

de Janasz and Godshalk 11

by contextual factors (e.g., company size, industry, background of the men-

tor); and how course-related skills and abilities affected managers’ personal

and professional success. Most mentors provided specific, detailed answers

to students’ questions, including many personal examples, and remained

open to follow-up questions and continued contact beyond the assignment’s

required interactions.1 Finally, the students submitted their completed assign-

ment, consisting of their questions, the mentor’s answers, and an analysis and

critique of the mentor’s answers. All received satisfactory grades. Near the

end of the course (which was 7 [graduate] or 15 [undergraduate] weeks in

length), students were asked to complete a questionnaire based on their

e-mentoring experience and were offered course or extra credit for doing so.

Of the total 292 students enrolled, 228 completed the questionnaire, yielding

a response rate of 78.1%. The students/protégés who responded were not

significantly different from the total population and were primarily male

(57.5%), single (77%), and 24.1 years old (SD = 6.8). The 228 students/pro-

tégés were 71.8% Caucasian, 12.3% Asian, 5.7% Hispanic, 5.3% African

American, and 4.9% all other categories; 60.3% were employed at least part-

time while engaged in their studies.

Measures

To more closely examine e-mentoring and its outcomes, we utilized both

existing and newly created variables. Intercorrelations among the variables

used in the study are included in Table 1.

E-mentoring received. We used Scandura’s (1992) mentoring functions (a total

of 13 items comprising three functions), modifying the language to reflect

electronic as opposed to traditional relationship functions and the academic

context. For most items, we changed the word mentor to e-mentor. In addi-

tion, because of the academic context and outcomes under study, we added or

modified a few items to increase the relevance for respondents who had not

yet entered or were not currently in the workforce. For example, we added the

item “I often communicate with my e-mentor on topics that are unrelated to

school” to psychosocial support. For the career development item, “My

e-mentor provides coaching on performing effectively in work-related situa-

tions,” we inserted “academic or” before “work-related situations.” Finally,

we took our cue from de Janasz et al. (2008) in allowing for the possibility

that role modeling may occur in a virtual relationship. We believe that men-

tors’ storytelling in response to protégés’ questions such as “please tell me

about a time when” or “please tell me about your path to your current posi-

tion, including key challenges faced and how you overcame them,” can

Table 1. Correlations Among Study Variables.

Gender

Graduate = 1,

UG = 2

Same gender

(M/P) = 0,

different = 1

Same

ethnicity

(M/P) = 0,

different = 1

Perceived

similarity

Relevant

mentor

knowledge

Comfort

with CMC

relationship

Interaction

frequency

Pre-existing

relationship

with mentor

Career

development

Psychosocial

support

Role

modeling

Learning

through

e-mentoring

Increased

course

concept

application

Increased

skill self-

efficacy

Level

(1 = graduate,

2 = UG)

.024

M/P gender

(0 = same,

1 = different)

.281*** −.035

3 M/P ethnicity (0

= same,

1 = different)

.078 .086 .043

Perceived similarity .099 .004 .010 −.186**

Relevant mentor

knowledge

.206** .097 −.039 −.081 .357***

Comfort

with CMC

relationship

.202** .335*** .006 .012 .134* .219**

Interaction

frequency (total

hours per

month)

−.028 −.139* −.104 −.069 .174** .066 .060

Pre-existing

relationship with

mentor

.054 −.008 .009 −.345*** .362*** .199** −.165* .162*

Career

development

−.021 .038 −.038 −.082 .496*** .312*** .180** .272*** .237***

Psychosocial

support

.091 −.055 −.017 −.155* .521*** .298*** .087 .289*** .294*** .709***

Role modeling .157* .037 −.062 −.109 .574*** .467*** .084 .188** .384*** .556*** .590***

Learning through

e-mentoring

.131* .015 −.068 −.045 .377*** .694*** .360*** .150* .101 .455*** .389*** .480***

Increased course

concept

application

.113 −.018 −.005 −.038 .269*** .544*** .340*** −.020 .081 .274*** .299*** .376*** .649***

Increased skill self-

efficacy

.146* .006 .015 −.039 .367*** .383*** .443*** .220** .052 .533*** .480*** .393*** .636*** .480***

Satisfaction with

mentoring

relationship

.096 −.101 −.055 −.189** .530*** .579*** .195** .217** .224** .548*** .630*** .587*** .613*** .525*** .551***

Note. M/P = mentor/protégé; CMC = computer-mediated communication.

*Correlation significant at p < .05 (two-tailed). **Correlation significant at p < .01 (two-tailed). ***Correlation significant at p < .001 (two-tailed).

de Janasz and Godshalk 13

provide powerful examples of behavior that could be emulated. Whether

these stories are relayed over a face-to-face lunch meeting or by e-mail, our

belief, supported by protégés’ critiques, is that such interactions form the

basis for role modeling.

The five-item career development function (e.g., My e-mentor provides

advice on career progress) had a mean value of 3.53 (SD = 0.86) and an inter-

nal consistency reliability of .85. Psychosocial support was measured with

five items (e.g., My e-mentor provides support and encouragement). We

obtained a mean value of 3.61 (SD = 0.93) and an internal consistency reli-

ability of .89 for this variable. Three items assessed role modeling (e.g., I try

to model my behavior after my e-mentor); the mean, standard deviation, and

reliability were 3.92, 0.68, and .68, respectively.

Protégé satisfaction and learning. Protégés’ overall satisfaction with the e-men-

toring relationship was assessed using five slightly modified items from

Young and Perrewé (2000; for example, Overall, I am satisfied with my

e-mentoring relationship). The overall mean of this measure was 4.10 (SD =

0.75) and the reliability was .90. Three protégé learning variables were con-

structed and confirmed via factor analysis for this study. All items (see the

appendix) were measured using five-point Likert scales. Learning through

e-mentoring was assessed with 6 items; the mean was 3.97 (SD = 0.65) and

reliability was .87. Increased course concept application comprised three

items; the mean was 3.99 (SD = 0.67) and reliability was .80. Finally,

enhanced skill efficacy was measured with three items; the mean was 3.68

(SD = 0.77) and reliability was .81.

Dyad characteristics. The dyad characteristics utilized in the study included

interaction frequency, pre-existing relationship with mentor, perceived men-

tor/protégé similarity, perceived relevance of mentor knowledge, and com-

fort with CMC relationship. Protégés indicated how much time they typically

interacted with their mentor using electronic means. This figure ranged from

under 1 hr to over 40 hr per month with a mean of 6.0 hr. A majority of pro-

tégés already knew their mentor prior to initiating the e-mentoring relation-

ship (62.3% did vs. 37.7% who did not). Students were barred from using

family members as their mentor.

Perceived similarity was measured using a modified six-item scale previ-

ously used by Ensher and her colleagues (2002). The mean, standard devia-

tion, and reliability of this measure were 3.67, 0.85, and .83, respectively.

Two additional individual variables created for this study were assessed using

five-point Likert scales. Perceived relevance of e-mentor knowledge was

assessed using three items (e.g., My e-mentor demonstrated that he or she is

14 Group & Organization Management XX(X)

current in the topics we discussed.); the mean was 4.28 (SD = 0.58) and reli-

ability was .79. Comfort with a CMC relationship consisted of five items

(e.g., Using e-mail to communicate with my e-mentor has enabled me to

overcome any concerns I might have in approaching a stranger to ask for help

or guidance); the mean was 3.28 (SD = 0.85) and reliability was .82.

Finally, we included several control variables. In addition to gender, we

also included course level of the protégé (undergraduate and graduate). This

control was important for two reasons. First, we expected that the graduate

students (many of whom were full-time employees) would likely have a dif-

ferent sense of the importance of mentoring than the traditionally aged under-

graduate students. Second, the graduate courses were shorter (7 vs. 15 weeks);

with greater time comes the possibility for increased interaction and mentor-

ing received.

Given the issues associated with cross-gender and cross-ethnic pairs (e.g.,

Ragins & McFarlin, 1990), we included two variables that represent demo-

graphic similarity of the mentor/protégé pair. Mentor/protégé gender was cre-

ated as a dichotomous variable; 66.5% of the respondents were in same-gender

pairs. The same type of variable was created for mentor/protégé ethnicity.

Most of the protégés reported that they knew the ethnicity of their mentor

(11% reported that they did not). Among those who did, 69.5% of the respon-

dents were in same-ethnicity pairs.

Results

Table 1 displays the correlations among the study variables. Our slightly

modified versions of Scandura’s three mentoring function measures shared

strong positive intercorrelations, ranging from .56 to .71. A similar trend was

apparent in the intercorrelations among the three learning outcomes created

expressly for this study; these correlations ranged from .48 to .65.

Table 2 displays the regression results from the three models used to test

the first five hypotheses. Each of the e-mentoring functions was regressed on

the control variables, then the dyad characteristics. Hypothesis 1 was par-

tially supported. Interaction frequency was positively related to career devel-

opment and psychosocial support (βs were .176 and .190 [p < .01],

respectively), but not role modeling. Hypothesis 2 also received partial sup-

port. A previous relationship between protégé and e-mentor was positively

associated with the role modeling function (β = .177, p < .01).

Table 2 also shows that perceived similarity is positively related to e-men-

toring functions received, supporting Hypothesis 3, and is significantly

related to all three mentoring functions with p < .001. The beta coefficients

for career development, psychosocial support, and role modeling were .390,

de Janasz and Godshalk 15

Table 2. Hierarchical Regression: E-Mentoring Functions as Dependent Variables

(Standardized Beta Coefficients Shown).

Career

development ΔR2

Psychosocial

support ΔR2

Role

modeling ΔR2

Controls

Gender −.118 .010 .037 .040 .077 .053

Level (1 = graduate,

2 = undergraduate)

.009 −.041 .022

M/P gender similarity

(0 = same, 1 =

different)

.016 .000 −.069

M/P ethnic similarity

(0 = same, 1 =

different)

.047 −.031 .050

Dyad variables

Frequency of

interaction

.176** .313*** .190** .296*** .075 .393***

Prior relationship

with mentor (0 =

no, 1 = yes)

.076 .074 .177**

Perceived M/P

similarity

.390*** .411*** .407***

Perceived relevance

of mentor

knowledge

.143* .107 .266***

Comfort with CMC

relationship

.121 .019 −.027

Overall R2 of model .323 .335 .446

F-statistic 11.453*** 12.112*** 19.359***

Note. M/P = mentor/protégé; CMC = computer mediated communication.

*p < .05. **p < .01. ***p < .001.

.411, and .407, respectively. Hypothesis 4 received partial support. Protégés’

perception of the relevance of their e-mentor’s knowledge was positively

associated with the career development and role modeling functions; the beta

coefficient for career development was .143 (p < .05) and for role modeling

it was .266 (p < .001). Hypothesis 5 was not supported. Protégé comfort with

establishing and carrying out a relationship via CMC was not related to any

of the three e-mentoring functions.

Table 3 displays the output from four hierarchical regressions. Each of the

three learning outcomes and satisfaction with the mentor relationship were

regressed on the control variables, dyad characteristic variables, and e-men-

toring received. Hypothesis 6 received partial support. Career development

Table 3. Hierarchical Regression: E-Protégé Learning and Satisfaction as Dependent Variables.

Learning

through

e-mentoring ΔR2

Increased

course concept

application ΔR2

Increased

skill self-

efficacy ΔR2

Satisfaction with

e-mentoring

relationship ΔR2

Controls

Gender −.034 .032 −.080 .018 .020 .025 −.035 .065**

Level (1 = graduate, 2 =

undergraduate)

−.129** −.183** −.129* −.149**

M/P gender similarity (0 = same,

1 = different)

−.026 .023 .029 −.006

M/P ethnic similarity (0 = same,

1 = different)

.023 .033 .016 −.077

Dyad variables

Frequency of interaction .014 .529*** −.143* .365*** .054 .345*** .016 .440***

Prior relationship w/mentor (0 = no,

1 = yes)

−.062 .001 −.068 −.078

Perceived M/P similarity .015 −.028 .033 .131*

Perceived relevance of mentor

knowledge

.550*** .425*** .154** .359***

Comfort with CMC relationship .236*** .322*** .362*** .099*

Mentoring received

Career development .169* .040*** −.041 .029* .270*** .112*** .061 .119***

Psychosocial support .018 .133 .166* .313***

Role modeling .121 .158* .041 .144*

Overall R2 of model .601 .412 .482 .624

F-statistic 26.787*** 12.458*** 16.538*** 29.451***

Note. M/P = mentor/protégé; CMC = computer-mediated communication.

de Janasz and Godshalk 17

was positively associated with enhanced learning (β = .169, p < .05) and

increased skill efficacy (β = .270, p < .001). Psychosocial support was posi-

tively related to increased skill efficacy (β = .166, p < .05). Role modeling

was positively related to increased course concept application (β = .158, p <

.05). Hypothesis 7 also received partial support. E-mentor relationship satis-

faction was positively related to the psychosocial support and role modeling

functions. The beta coefficients were .313 (p < .001) and .144 (p < .05),

respectively.

Discussion

The goal of the study was to build on and extend traditional mentoring

research to investigate relationships among dyad characteristics and various

outcomes when the medium of exchange is virtual or electronic. We pre-

sumed that, as in traditional mentoring relationships, protégés would learn

and benefit even without meeting or communicating with their mentor face-

to-face. Some of the variables tested suggested that the medium of communi-

cation was not a factor. As with traditional mentoring, the more frequently

protégés interacted with their e-mentor, the greater the amount of mentoring

functions received. Specifically, the greater the interaction frequency, the

greater the career development (career-relevant advice and information) and

psychosocial support (emotional support and acceptance) received by the

protégé. However, and given that our respondents’ mentor relationships

occurred almost exclusively via e-mail, interaction frequency was not associ-

ated with role modeling. Perhaps it is difficult to model one’s behavior after

an e-mentor, particularly since many respondents (almost 38%) had not pre-

viously met with the e-mentor. A future study might examine the degree to

which protégés recognize and utilize the role modeling of mentors who (a)

started face-to-face and transitioned to virtual due to job changes, (b) started

and remained virtual, and (c) started virtual and transitioned to face-to-face.

Increasing career mobility makes job and geographic changes likely, so

understanding when, how, and in what combination communication modes

impact mentoring outcomes is important. It would also be interesting to

examine whether individual differences in abstract versus concrete thinking

or learning style (e.g., auditory, visual) would moderate this relationship.

Protégés who are more abstract thinkers or who learn best by reading might

be more able to consider their e-mentor as a role model than those who are

more concrete thinkers or visual learners.

Although role modeling was not associated with interaction frequency, it

was positively associated with the pre-existing relationship between mentor

and protégé, as predicted. Protégés who knew their e-mentor prior to the start

18 Group & Organization Management XX(X)

of their online relationship presumably chose the individual as a mentor

because they had seen him or her in past interactions and considered him or

her worth emulating. Prior role modeling may have continued virtually

through the mentor’s storytelling in response to the protégé’s questions. The

non-significant relationship between a pre-existing relationship with the

e-mentor and career development or psychosocial support may suggest that

such benefits are not contingent on prior, face-to-face interactions and per-

haps that the pre-existing relationships were not of a mentoring nature. Taken

together, these findings support those obtained from large-scale e-mentoring

programs such as MentorNet and may help explain how a protégé separated

by geographic and time constraints from his or her mentor may still receive

the intended benefits of mentoring (e.g., de Janasz et al., 2003).

Perhaps one of the more thought-provoking findings is that perceived

similarity was positively associated with the receipt of all three e-mentoring

functions, while demographic similarity was not. First, mirroring research by

Ensher and her colleagues (de Janasz et al., 2008; Ensher et al., 2002), our

findings suggest that protégés who perceive that their mentor has similar atti-

tudes, values, and goals are more likely to trust their mentor and the informa-

tion he or she conveys. For example, a protégé struggling to maintain a

balance between work and family life will be likely to heed the personal and

professional advice or behavioral example of a mentor who values both

domains and successfully manages work–life conflicts.

Second, following the work of Walther (1996), the findings suggest that

CMC relationships work because of the similarity of values more than actual

demographic similarities. E-mentoring operates much like informal mentor-

ing relationships, wherein value similarity facilitates the trust that is slower to

form in formal face-to-face mentor relationships. E-mentoring reduces nega-

tive effects associated with traditional mentoring’s face-to-face medium,

which is hindered by visual cues and stereotyping (Sproull & Kiessler, 1999;

Turkle, 1995). In this study, because protégés selected their mentor and

62.3% had pre-existing relationships, value similarity might be higher than it

would likely be in a formal mentoring program where matches are deter-

mined by a third party, such as a human resources representative. Paralleling

research on virtual teams (Martins, Gilson, & Maynard, 2004), it may be that

once trust is established, communication effectiveness and information shar-

ing in e-mentoring will equal that of traditional relationships (Alge, Wiethoff,

& Klein, 2003). These results regarding perceived similarity and e-mentoring

received support previous findings.

Protégés’ perception of the relevance of their e-mentor’s knowledge was

positively related to the career development and role modeling functions, and

this finding may unveil an important new piece in the mentoring puzzle. While

de Janasz and Godshalk 19

past research suggests the importance of complementary skill sets between

mentor and protégé (e.g., Wanberg et al., 2003), our newly developed con-

struct explained a significant amount of variance in the receipt of career devel-

opment and role modeling. One explanation arises out of formal mentoring

programs, in which mentor and protégé are matched without significant regard

to personal or professional preferences. A protégé paired with someone viewed

as out of touch will likely give little credence to the mentor’s advice or behav-

ioral modeling. By contrast, when a mentor’s knowledge and experience are

perceived as relevant to and complementary with a protégé’s particular learn-

ing needs, the protégé is more likely to accept and value such mentoring

(Allen, Poteet, et al., 1997). Taken together, these findings suggest that formal

mentoring programs need to focus on the salience of matching processes that

are not based only on personalities but also on discipline knowledge, skill sets,

and needs so that mentors offer relevant knowledge. In fact, recent develop-

ments in the practice of e-mentoring suggest that this type of matching is

effectively occurring. In 2003, Intel launched an automated mentoring website

for its 100,000 worldwide employees. According to the program developer

and manager, Kevin Gazzara, employees can log on to an internal website and

enter up to three career interests or skills they want to develop. They then

receive a list of possible mentors throughout the company; no mentor photos

are supplied, despite the potential ease of doing so. Protégés select two or

three mentors whose profiles match their needs and e-mails are generated

inviting the mentors to participate (Owens, 2006). A similar practice is used at

global accounting firm KPMG. Manny Fernandez, an audit partner-in-charge

and e-mentoring program participant, notes that the matching process has

been positive. “It has resulted in higher employee satisfaction, lower turnover

and professionals who are better aligned with the organization and feel part of

the team” (Owens, 2006, p. 106).

The prediction that comfort with the CMC relationship would be posi-

tively related to e-mentoring received was unsupported. We expected that

CMC comfort would increase the ability of protégés—particularly tradition-

ally aged undergraduates—to learn from their e-mentor because of the ease

with which they initiated and communicated throughout the e-mentoring

relationships. However, given the ubiquity of electronic communication in

the contemporary environment, this construct may no longer be relevant for

employees who have grown up in the age of the internet.

As a key purpose of mentoring is to facilitate protégé learning and devel-

opment, we were not surprised that our analysis showed e-mentoring func-

tions received predicted three different types of learning. These results were

particularly satisfying given that these learning variables were tested on stu-

dents who participated in an e-mentoring relationship over one semester, a

20 Group & Organization Management XX(X)

short duration for a mentoring relationship. Specifically, we found that

respondents reported increases in their skills/capabilities and confidence that

resulted from the career development and psychosocial support received

from their e-mentor (enhanced skill self-efficacy). By engaging in conversa-

tions with their e-mentor about business concepts and their importance in the

workplace, protégés were able not only to enhance their skill set but also their

confidence in using these skills. Our findings also demonstrate that role mod-

eling was positively related to protégés’ ability to apply course-related topics

to the business environment. Quite often, students/protégés’ questions were

framed to elicit actual experiences (e.g., “Tell me about a time you faced an

ethical dilemma . . . what happened and how did you handle it . . .?”). Mentors’

responses provide a concrete model—extending well beyond textbook defi-

nition—for protégés to emulate and apply in future situations. Our finding

supports the use of e-mentoring to enhance student learning (Whiting & de

Janasz, 2004) and reinforces the importance of e-mentoring to facilitate

knowledge acquisition and application. Finally, respondents reported

enhanced academic learning as a result of career development support and

advice received from interactions with their e-mentor. This empirical support

provides evidence that the use of e-mentoring in business environments can

help protégés recognize and bridge knowledge gaps, as anecdotal reports

suggest (e.g., Owens, 2006).

Finally, we found that the psychosocial support and role modeling that

their e-mentor provided directly and positively affected protégés’ overall sat-

isfaction with the e-mentoring relationship. If the mentor was judged as a

credible role model and was able to provide the protégé with experiences

from which the protégé could learn, then she or he would be satisfied that the

relationship met this expectation (Godshalk & Sosik, 2000). The positive link

between psychosocial support and relationship satisfaction was as expected

and reinforced similar findings (Ensher et al., 2002). Protégés who felt that

their mentor was a confidant and provided support without judgment viewed

the relationship as positive and satisfying. The fact that the career develop-

ment function was unrelated to satisfaction may be due to students’ expecta-

tions at the start of their e-mentoring relationship, which was a course

assignment as opposed to a formal program within a protégé’s organization.

Students’ first priority was to complete a project, not necessarily to experi-

ence career growth. Also, students might not have taken the opportunity to

discuss future career directions with their e-mentor or it could be that experi-

ence in the workplace provides a more solid foundation for appreciating the

role of mentoring in learning and career development. The findings that pro-

tégé learning and satisfaction were predicted—though not consistently—by

de Janasz and Godshalk 21

the receipt of mentoring functions holds much promise for the practice and

study of e-mentoring.

Implications

This study builds on traditional mentoring research and provides an empirical

examination of how mentoring can be successful in a virtual setting. Although

limited in scope, this study represents a step forward in understanding the

positive impact of e-mentoring on protégé learning and satisfaction. Using a

model that specified dyad characteristics of the relationship, the e-mentoring

functions received, and learning and satisfaction, we were able to explain

between 41% and 62% of the variation in learning and satisfaction. Even

when protégé and mentor do not meet face-to-face, benefits similar to those

of traditional mentoring accrue.

Taken together, our findings suggest that e-mentoring is a viable alterna-

tive or complement to other developmental relationships. The finding that

perceived similarity (i.e., values and attitudes) affects the receipt of e-men-

toring, whereas demographic similarity does not, provides hope for any group

that has been shown to be disadvantaged in face-to-face mentoring situations.

Past research shows that women and minorities tend to face great barriers

in—and have a great need for—developing effective mentoring relationships

in the workplace (Linehan & Walsh, 1999; Ragins et al., 2000). Furthermore,

given the increasing career mobility of employees and the ubiquity of the

internet and other electronic means for communicating, our study suggests

that e-mentoring represents a viable means to expand a protégé’s develop-

mental network. More mentors are preferable to fewer (Higgins, 2000; van

Emmerik, 2004b), and a more diverse constellation, using both virtual and

traditional communication means, is also desirable (de Janasz et al., 2003).

One implication of this finding is that e-mentoring may provide a bridge to

learning and development in cases when personality attributes or geographi-

cal distance may preclude the initiation of developmental relationships. In

their study of networking behaviors, Forret and Dougherty (2001) found that

self-esteem and extraversion were significantly correlated with proactive net-

working behaviors—of which mentoring is a typical one. Employees whose

shyness or low self-esteem predisposes them not to initiate a developmental

relationship face-to-face might find doing so online more comfortable. Over

time, and as comfort with the interactions increases, the protégé might choose

to meet with the mentor face-to-face, which might also enhance the potential

for role modeling. In addition, should one partner in a face-to-face develop-

mental dyad have to move to a new geographic location, the relationship need

not end. On the contrary, our findings suggest that knowing one’s mentor

22 Group & Organization Management XX(X)

before engaging in a virtual developmental relationship may enhance the role

modeling received. Future research should explore more fully how virtual

and face-to-face interactions affect protégé learning and development to bet-

ter understand the individual and cumulative effects of the type, frequency,

and order of interaction mode on e-mentoring effectiveness.

The use of electronic means to establish and carry out effective learning

and mentoring relationships is advantageous for several reasons. Protégés in

this study selected their mentor and asked her or him very specific questions

to learn and build on course-related concepts and knowledge. Motivation to

learn is a necessary condition for adult learning (Knowles, 1973) and since

protégés asked questions as their learning needs arose, protégés were more

likely to assimilate and retain this new knowledge received from the mentor.

Similar results have been reported in several companies using e-mentoring

programs (e.g., Francis, 2007). By deciding what development areas to work

on and finding mentors with relevant knowledge, employees at a financial

service company were able to tap into the skills and experiences of the com-

pany’s 13,000 employees scattered across the U.S. (Francis, 2007). In pro-

grams like these, the mentoring match choices were made by the employee,

not HR. When adults are able to control the e-mentoring process, from selec-

tion of mentor to interaction content and frequency, they are able to meet

their need to be independent and self-directed in the learning process

(Simmonds & Lupi, 2010). In a survey by Triple Creek that examined men-

toring participants in five organizations, 82% of respondents agreed that

web-based mentoring gave them control over how they engaged in their rela-

tionships (Francis, 2007). This control influenced their motivation and their

comfort in pursuing additional mentoring relationships. As noted by a senior

HR executive: “Once people understand this new vision of mentoring, they

can discover how to leverage development opportunities that exist all around

them” (Francis, 2007, p. 56). Whether arranged through their company or

their own efforts, employees have many simple and painless ways to connect

with potential e-mentors who possess compatible values and complementary

skill sets to facilitate their learning and career development.

Limitations and Suggestions for Future Research

One limitation centers on the reliance on self-reporting for the study. Although

this approach is not uncommon in studies of mentoring, it does allow for the

possibility of common method variance. However, there are at least three

reasons why we believe common method variance is not an issue in this

study. First, we have two predictor variables that are objectively verifiable—

frequency of interaction and prior relationship with mentor—which, despite

de Janasz and Godshalk 23

being self-reported, are relatively objective variables. Second, we ran a

Confirmatory Factor Analysis (CFA) on all the items included in the study

(Harman’s single-factor test) and found that as one variable, they only

accounted for 31.6% of the variance, suggesting (Common Method Variance)

CMV is not a factor (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).

Finally, we re-ran one of the regression analyses (with increased course con-

cept application as the dependent variable) with a marker variable (hierarchi-

cal level of the mentor); the model had a slightly lower F-value (11.579) than

the model that did not include it.

Because our sample consisted of graduate/undergraduate students, gener-

alizing the findings to full-time professionals in all professions is another

limitation. While over 60% of our respondents were employed at the time

they participated in an e-mentoring relationship, not all were full-time nor in

career-oriented positions, limiting our ability to demonstrate that the increased

skill development and learning reported would translate into applicable

workplace benefits. Future field studies in a variety of employment settings

should replicate and expand on these findings. For example, e-mentoring

may be more readily received and effective in technology-rich (or global)

organizations than in low-technology environments. Future research might

also examine the influence of relevant personality variables such as extraver-

sion and learning style, as they might further explain comfort with and learn-

ing through CMC relationships.

Finally, we recognize that relationship duration may be a limitation. That

these students worked on the e-mentoring project in courses that ranged from

7 to 15 weeks in duration is different from more traditional relationships that

range from a few months to many years (Kram, 1985). However, these find-

ings provide support that learning occurs in e-mentoring relationships even

within short timeframes, reinforcing recent mentoring literature that suggests

that individuals can receive development from a range of mentoring relation-

ships that vary in intensity, duration, and purpose (Higgins & Kram, 2001).

What may first appear as a trivial relationship may play as important a role in

protégés’ development as a longer-term, face-to-face relationship. Future

research should look at the impact of duration on the efficacy of e-mentoring

relationships.

In sum, e-mentoring has a promising future and may provide a critical

resource to the globalized workforce. By engaging virtually in a mentoring

relationship, protégés are likely to accrue similar benefits as those afforded

through traditional modes of engagement (i.e., face-to-face). While CMC

may present some limitations, our findings suggest that by connecting elec-

tronically with mentors of their choosing, protégés enhance their learning,

self-efficacy, and skills on their terms and without the need of a formal

24 Group & Organization Management XX(X)

program. Although gender or ethnic differences could present problems in

organizations, both in finding appropriate matches in the dyad and in carrying

out the relationship without prejudice (Ragins et al., 2000), our findings sug-

gest that perceived similarity is what matters in virtual relationships; actual

demographic similarity is unrelated to mentoring received. These findings

provide an important step in clarifying how dyad characteristics affect the

mentoring received and learning and other outcomes. Future research on

e-mentoring practiced by employees with reports from multiple sources may

provide a stronger mandate for and understanding of the importance of vir-

tual mentoring as a viable and effective complement to traditional forms of

mentoring.

Appendix

Items Used in Measures Developed for the Study

Enhanced Skill Self-Efficacy (3 items):

 As a result of this e-mentoring experience, I feel more confident about

my ability to initiate similar relationships with potential e-mentors.

 This e-mentoring experience has increased my sense of competence in

performing school or work-related activities.

 Interacting with my e-mentor has enabled me to master the skills nec-

essary to succeed in the workplace.

Increased Course Concept Application (3 items):

 As a result of my e-mentoring relationship, I have increased my under-

standing of course concepts beyond class materials and discussions.

 By discussing course concepts with my e-mentor, I feel more confi-

dent in my ability to apply this knowledge in my current or future

workplace.

 The insight and advice shared by my e-mentor has served to increase

my knowledge of how to work effectively with others.

Learning Through E-Mentoring (6 items):

 Things I learned through collaborating with my e-mentor will “stick”

with me for some time.

 I learned a lot through my interactions with my e-mentor.

de Janasz and Godshalk 25

 Interacting with my e-mentor helped me recognize and bridge knowl-

edge gaps.

 Interacting with my e-mentor enabled me to make real-time use of

insights gained.

 This e-mentoring relationship enabled me to learn about things that are

important to me.

 Using electronic means to interact with a business professional

enhanced my learning.

Comfort with Establishing a CMC Relationship (5 items):

 Before this experience, I felt that it would be quite difficult to obtain

an e-mentor.

 Using e-mail to communicate with my e-mentor has enabled me to

overcome any concerns I might have in approaching a stranger to ask

for help or guidance.

 As a result of this experience I am more likely to utilize electronic

means to initiate and build e-mentoring relationships.

 Using e-mail to initiate an e-mentoring relationship reduced my fear of

being rejected by the e-mentor.

 Using e-mail to ask an individual to be my e-mentor was less difficult

than if I were to make the request in person.

Perceived Relevance of Mentor’s Knowledge (3 items):

 The information presented by my e-mentor demonstrated that his/her

expertise was relevant.

 Collaborating with my e-mentor was a positive way to leverage knowl-

edge and resources.

 My e-mentor demonstrated that she or he is current in the topics we

discussed.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,

authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publi-

cation of this article.

26 Group & Organization Management XX(X)

Note

1. We suspect that a very small number of the dyads may have met face-to-face dur-

ing the assignment, even though the assignment required asynchronous, written

communication. First, 62.3% of protégés knew their mentors before the assign-

ment. Second, we encouraged protégés to maintain contact after the assignment;

some let us know that they met in person.

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Jul 2007

L. Francis

Traditional mentoring is getting a new look. The age-old developmental process now boasts a streamlined strategy fit for today's fast-paced, caffeine-hyped, and technology-addicted world. As they have with other learning and development programs, many organizations are modernizing mentoring by using the Internet to spread the practice to everyone. Not only does this allow participants to easily create and manage relationships on their own terms, but it puts them in the driver's seat of their career development. While some practitioners may still balk at the idea of web-based mentoring, there is no denying the benefits technology provides to the practice of mentoring. From mentees and mentors who can find their own matches, to administrators who can offer mentoring to scores of people, to organizations that can create pervasive cultures of sharing and learning, the impact of technology can be felt in every facet of modern mentoring.

The effect of multiple mentors on protege attitudes toward the work setting

Article

Dec 1999
J Soc Behav Pers

Review of the literature on mentoring suggests that having multiple mentors may enhance mentoring outcomes. Multivariate analysis of covariance is used to test possible effects of multiple mentors on six attitudinal outcomes - organizational commitment, job satisfaction, career expectations, role conflict, role ambiguity, and perceived employment alternatives - in a sample of 275 executives. Results of this study indicate that experiencing one or more mentoring relationships in the workplace may result in greater organizational commitment, greater job satisfaction, enhanced career expectations, increased perceptions of alternative employment, and lower ambiguity about one's work role. Role conflict may increase as the number of mentors increases beyond one, however. New areas for research suggested by these results are discussed.