Effective strategies, skills, and behaviors for networking success
The relationship between networking behaviors and the Big
Five personality dimensions Hans-Georg Wolff
University of Erlangen-Nürnberg, Nürnberg, Germany, and
Sowon Kim University of Geneva, Geneva, Switzerland
Abstract
Purpose – The purpose of this paper is to suggest a comprehensive framework to elucidate the relationship between personality and networking. Using the Five Factor Model as a framework, the paper aims to argue that traits tapping into social (i.e. extraversion, agreeableness) and informational (i.e. openness to experience) features are relevant in explaining how individual dispositions facilitate networking behaviors. Moreover, it aims to delineate structural and functional differences in networking (i.e. building, maintaining, and using contacts within and outside the organization) and to theorize how these differences yield differential relationships of personality traits with networking dimensions.
Design/methodology/approach – Online surveys were administered to two samples, from Germany and the UK, respectively (n ¼ 351). Structural equation modeling is used to test the hypotheses.
Findings – Personality traits reflecting social (extraversion) and informational aspects (openness to experience) are broadly related to networking in general. The paper also finds support for differential relationships, for example, agreeableness is related to internal, but not external networking. Both conscientiousness and emotional stability are not related to networking behaviors.
Practical implications – The findings help explain why some individuals experience more barriers to networking than others and can be used in networking trainings. Practitioners should also note that there is more than extraversion to accurately predict networking skills in selection assessments.
Originality/value – The paper provides further insights into determinants of networking, which is an important career self-management strategy. It also offers an integrative framework on the personality-networking relationship as prior research has been fragmentary. Establishing differential relations also furthers understanding on core differences between networking dimensions.
KeywordsNetworking, Personality traits, Career development, Social capital, Professional relationships, Personality
Paper type Research paper
Theories on boundaryless and protean careers suggest that interpersonal relations are an effective means to self-manage careers (e.g. Arthur and Rousseau, 1996; Briscoe et al. 2006; Hall, 1996, 2004; Gunz and Peiperl, 2007; Sullivan and Baruch, 2009) and this has sparked interest in how relationships at work impact individual careers (e.g. Higgins and Kram, 2001; Ragins and Kram, 2007; Seibert et al., 2001; Shortland, 2011; Tams and Arthur, 2010; Van Emmerik et al., 2006). One effective strategy to manage one’s career
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1362-0436.htm
The authors gratefully acknowledge the support of Steven Fleck and SHL for granting access to the Occupational Personality Questionnaire (OPQ) and supporting the data collection in the UK.
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Received 15 September 2011 Accepted 28 October 2011
Career Development International Vol. 17 No. 1, 2012
pp. 43-66 q Emerald Group Publishing Limited
1362-0436 DOI 10.1108/13620431211201328
is networking, which refers to developing and maintaining personal relationships in order to facilitate the exchange of work related resources (Forret and Dougherty, 2001; Power, 2010; Wolff and Moser, 2010). Studies show that networking is positively related to a host of vocational outcomes, for example, career success (Forret and Dougherty, 2004; Wolff and Moser, 2009), job search (Granovetter, 1973; Van Hoye et al., 2009; Wanberg et al., 2000), and job performance (Thompson, 2005).
While a large number of studies have focused on the consequences of networking, we know considerably less about the antecedents of networking behaviors, such as individual dispositions or job characteristics (Forret and Dougherty, 2001). This study examines the relationship between personality and networking. Personality is an important predictor of work outcomes such as work performance (e.g. Barrick and Mount, 2005) and career success (Ng et al., 2005), and also of work behaviors such as career strategies (Guthrie et al., 1998) and influence tactics (Cable and Judge, 2003). Although some studies have examined the relation between personality and networking, a comprehensive theoretical outline is lacking as prior research has mostly examined a piecemeal collection of personality traits or only specific networking behaviors (Forret and Dougherty, 2001; Van Hoye et al., 2009; Wanberg et al., 2000).
In the present study, we outline an integrative theoretical framework of the relationship between the Five-Factor Model of personality (FFM or the “Big Five,” Goldberg, 1990) and networking. Specifically, we propose linkages between personality and networking behaviors on two levels. First, on a general level, we propose that the core linkages between these constructs are their social and informational focus (Coleman, 1988). This proposition suggests that next to extraversion two other often neglected traits, agreeableness and openness to experience facilitate networking behaviors. Second, on a more specific level, we examine linkages between personality and specific networking dimensions as scholars have introduced multidimensional models of networking behaviors (Forret and Dougherty, 2001; Michael and Yukl, 1993; Wolff and Moser, 2006). We delineate structural and functional distinctions between these dimensions and theorize how these differences yield differential relationships of personality traits with networking dimensions. We thus examine whether dimensions of personality differentially affect particular subsets of networking behaviors. We test predictions derived from this framework in two samples of employed individuals.
Our study contributes to the literature in three main ways. First, this study furthers our understanding of the antecedents of networking and presents a comprehensive picture of the personality-networking relationship. Next to this theoretical contribution, understanding why some individuals network more than others is also an important requisite in designing trainings on networking (De Janasz and Forret, 2008; Shortland, 2011). Second, we further develop the theoretical framework of networking to examine whether personality dimensions differentially affect particular subscales of networking behaviors. This differential perspective increases our knowledge on specific types of networking and might clarify the mixed findings concerning some personality dimensions in prior research. Finally, as networking is an important construct in theories on boundaryless and protean careers, we shed light on the link between the fields of careers and personality research. Thus, by examining why some
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individuals engage in more networking than others, we offer insights into how “being” (i.e. personality) is put to work by means of “doing” (i.e. behaving) at work.
Networking Research on networking has been conducted by two streams of literature. The first stream focuses on power and politics. The general argument is that organizations are political entities where informal processes impact career paths (Ferris et al., 1994; Judge and Bretz, 1994; Wayne and Liden, 1995). Networking is an important career strategy, which serves to navigate the informal processes of the organization (see for example Kotter, 1982; Luthans, 1988). From this literature, networking consists of “socializing/ politicking and interacting with outsiders” (Luthans, 1988, p. 129). Observed behaviors include “non-work related ‘chit chat’; informal joking around; discussing rumors, hearsay and the grapevine; complaining, griping, and putting others down; politicking and gamesmanship; dealing with customers, suppliers, and vendors; attending external meetings; and doing/ attending community service events” (Luthans, 1988, p. 129).
The second stream of literature, in which this study is positioned, is careers. Because careers increasingly unfold across organizations and multiple networks (Arthur and Rousseau, 1996; Tams and Arthur, 2010) networking is considered an important strategy to create opportunities and to identify the next career move within or outside the organization. It is a legitimate activity that individuals should pursue for the sake of their careers. From this literature, networking is defined as “Individuals’ attempts to develop and maintain relationships with others who have the potential to assist them in their work or career” (Forret and Dougherty, 2004, p. 420). Both research streams define networking as an individual level phenomenon that focuses on behaviors. It is thus distinct from concepts such as social capital (e.g. Coleman, 1988), social networks (e.g. Marsden, 1990), or network resources (e.g. Bozionelos, 2003). These constructs focus on a structural level and examine the properties of an entire network, essentially dismissing characteristics of the person (e.g. Kilduff and Krackhardt, 1994).
Next to this broad perspective on networking, scholars have developed models that postulate specific subdimensions of networking behaviors (e.g. Forret and Dougherty, 2001; Michael and Yukl, 1993; Ng and Feldman, 2010). Similar to hierarchical models of personality (e.g. McCrae and Costa, 1997) networking can thus be examined on different levels, on a broad, general level and on a more specific level of subdimensions. In the present study, we use a dimensional networking model suggested by Wolff and Moser (2006) that consists of two facets. First, in line with other models (e.g. Michael and Yukl, 1993; Ng and Feldman, 2010; see also Power, 2010), this model consists of a structural facet distinguishing contacts within and outside an individual’s organization, that is, internal and external networking, respectively. In addition, the model also includes a functional facet that reflects the prototypical process of relationship development and distinguishes between building, maintaining, and using contacts. This distinction is part of most networking definitions (e.g. Baker, 1994; Forret and Dougherty, 2004; see Wolff and Moser, 2006). Crossing the two facets yields six types of networking behaviors:
(1) building internal contacts;
(2) maintaining internal contacts;
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(3) using internal contacts;
(4) building external contacts;
(5) maintaining external contacts; and
(6) using external contacts.
In the following, we will introduce a framework that delineates theoretical differences between these two facets. This closer examination of the facets forms the basis for the development of our hypotheses concerning differential relationships between the Big Five and networking behaviors.
With regard to the structural facet, we suggest that structural characteristics yield three main differences between internal and external networking. The first difference is range of potential relationship partners. Within one’s own organization, the range of potential relationship partners is somewhat restricted in comparison to outside one’s organization where ties might be formed with people from other industry sectors or lines of business. In internal networking, individuals can decide to forge or not to forge ties with members of their organization, but this pool of people cannot be replaced by another. In external networking, individuals have more discretion in the selection of contacts or the group they join, for example, a marketing association or a rotary club.
A second difference concerns accessibility. Contacts within the organization are more accessible than contacts outside the organization because of proximity. For example, individuals working in the same company building might simply drop into each other’s office or meet incidentally (e.g. Kotter, 1982). In contrast, meetings with outsiders must often be arranged or might take place outside working hours. We therefore suggest that more effort to connect is required in external than internal networking. Finally, a third difference is density, defined as the extent to which contacts of an individual know one another (e.g. Podolny and Baron, 1997). On average, density should be higher within organizations than across organizations. Within intraorganizational networks of higher density, gossip may travel faster and pose a threat to individuals’ reputation (Coleman, 1988). Losing one’s reputation as a reliable transaction partner may therefore be more damaging with regard to internal than external networking.
With regard to the functional facet, building and maintaining contacts are preconditions to using contacts (Wolff and Moser, 2010). An important characteristic of this prototypical process of relationship development is that it becomes increasingly instrumental as it develops. Building contacts includes behaviors related to initiating and making new connections. We consider this a highly social activity where social skills play an important role. Instrumentality becomes more important in maintaining contacts, as individuals choose which contacts to maintain and develop and instrumental concerns supplement sociability concerns. While socializing is an important aspect of maintaining ties, we suggest that it also includes exchange of information as for example what others are working on or news from the grapevine. The instrumental aspect is even more prevalent when individuals actively use their contacts. While they must adhere to basic social norms in such situations (e.g. asking “how are your children?”), they are in need of a particular resource and approach their contacts to ask for support. For example, unemployed individuals’ calls upon acquaintances during job search (Wanberg et al., 2000) are clearly motivated by
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instrumental needs for a job. Even though individuals must adhere to social rules, the social aspects of a relationship are most likely of minor concern to job seekers.
The Big Five and networking behaviors Traits are fundamental building blocks of personality and refer to stable patterns in the way individuals think, feel, and behave (Pervin et al., 2005). While multiple typologies of personality traits exist, the Five Factor model or Big Five has gained consensus from scholars as a model describing the most salient aspects of personality traits (Barrick and Mount, 2005). Furthermore, the Big Five has been validated across cultures (McCrae and Costa, 1997) as well as over time (Hampson and Goldberg, 2006). The five dimensions are extraversion, agreeableness, openness to experience, conscientiousness, and emotional stability. Among personality researchers there is “strong consensus” (Cuperman and Ickes, 2009, p. 667) that, on a broad level, the dimensions are relevant for specific behavioral domains (see also Ashton et al., 2002; Ashton and Lee, 2001; Borkenau and Ostendorf, 2008). Extraversion and agreeableness refer to the domain of interpersonal behavior, whereas openness to experience is relevant to individuals’ intellectual life or idea-related endeavors. Conscientiousness is relevant to “engagement in task-related endeavors” (Ashton and Lee, 2001, p. 346) and emotional stability refers to individuals’ affective experiences or feelings.
Prior research on the Big Five and networking has focused on a limited number of these traits. Our review of the literature showed that extraversion (Forret and Dougherty, 2001, Van Hoye et al., 2009; Wolff and Moser, 2006) and conscientiousness (Ferris et al., 2005; Van Hoye et al., 2009) were the most often examined traits. Only Wanberg et al. (2000) examined all five personality dimensions and networking, albeit in a sample of unemployed job seekers. While valuable, this study provides a partial picture on personality and networking for two reasons. First, unemployed individuals predominantly network to get a job, for example, by telling many people about unemployment and the targeted job type or by making a list of people that might have job leads (Wanberg et al., 2000). In contrast, employed individuals may network to obtain a range of outcomes, such as task advice, job performance, or the next promotion. Second, the measures used to assess networking of unemployed individuals are oriented towards external networking and using contacts, but do not reflect other dimensions of networking such as building or maintaining contacts. As contacts should be built well before they are put to use (Wolff and Moser, 2010) the focus on these behaviors may render an incomplete image of networking and thus its relationship with personality.
How do the Big Five dimensions affect networking behaviors? Our basic premise is that networking behavior is inherently social and often focused on the exchange of intangible resources, such as information (e.g. Burt, 2004; Luthans, 1988). Networking should therefore be related to personality dimensions that reflect this content. Specifically, we expect relationships between networking and extraversion as well as agreeableness, since they both refer to the social domain. We also expect that networking will be related to openness to experience, which refers to the informational or idea related domain. We do not expect any relationships with conscientiousness and emotional stability, which refer to task-related and feeling-related domains, respectively. In further developing our hypotheses, we first specify a broad, general hypothesis and then rely on our analyses on differences between networking facets to
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derive additional hypotheses on the differential relationship of personality traits and networking behaviors.
Extraversion Extraversion refers to individuals’ general tendency to approach social situations and individuals high in extraversion are described as gregarious, active, and assertive, whereas introverted individuals have a desire to remain in solitude (Ashton et al., 2002; Borkenau and Ostendorf, 2008). As the tendency to approach social situations is a prerequisite to networking behaviors, we predict that extraversion is associated with networking behaviors. In fact, all four studies that have examined the relationship between extraversion and networking report positive findings (Forret and Dougherty, 2001; Van Hoye et al., 2009; Wanberg et al., 2000; Wolff and Moser, 2006). Going beyond this general assumption, we hypothesize that extraversion particularly facilitates building contacts. We base this assumption on two premises. First, general descriptions of extraversion also encompass assertiveness (e.g. Goldberg, 1990), which should enable extraverted individuals to approach others to build new contacts without hesitation (Forret and Dougherty, 2001). Second, Ashton et al. (2002) provide evidence that the core aspect of extraversion is obtaining social attention. According to our analysis of the functional facet of networking, social attention is readily available from building contacts, but might be less important in maintaining and using contacts, as these behaviors do not only serve social, but also instrumental needs.
H1. Extraversion is positively related to networking behaviors.
H1a. Extraversion is more closely related to building contacts than to maintaining and using contacts.
Agreeableness While extraversion describes the extent to which individuals approach social situations, agreeableness refers to the mode of relating to others (e.g. Borkenau and Ostendorf, 2008). Individuals high in agreeableness are described as trusting and cooperative, good-natured, and tolerant. According to social capital theory (Coleman, 1988), trust and cooperation reduce transaction costs and permit a fast and effortless exchange of resources. We therefore assume that an agreeable mode of relating to others facilitates networking behaviors. Furthermore, we hypothesize that the relationship between agreeableness and networking is higher for internal than for external networking. According to our analyses of the structural facet of networking, individuals’ discretion in choosing potential contacts is more limited within organizations. Also, higher proximity and density within organizations may increase the potential for conflict and disagreement. An agreeable mode of relating to others should facilitate interaction and might enhance individuals’ positive reputation and thus their likelihood to be connected to others. Finally, we also posit that agreeableness is particularly relevant to maintaining and using contacts. Agreeableness refers to the how individuals behave in social interactions, but not to the extent of sociability, which is of higher importance for building contacts and predominantly reflected by extraversion. Within existing relationships, a cooperative and good-natured mode of relating to others fosters trust and support (Kamdar and
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van Dyne, 2007) and should thus facilitate network maintenance and also the exchange the resources (i.e. using contacts).
H2. Agreeableness is positively related to networking behaviors.
H2a. The relationship between agreeableness and internal networking is stronger than the relationship between agreeableness and external networking.
H2b. The relationship between agreeableness and maintaining or using contacts is stronger than the relationship with building contacts.
Openness to experience While extraversion and agreeableness are associated with networking due to communalities on the social dimension, we suggest that openness to experience and networking are related due to their common informational focus. Individuals high in openness to experience are curious, broad-minded, imaginative, and open to trying new techniques (e.g. Borkenau and Ostendorf, 2008; Goldberg, 1990). Ashton and Lee (2001, p. 343) suggest that openness is related to “the extent to which people engage in behaviors that tends to result in the generation or comprehension of ideas”. Likewise, an important aspect of networking is the exchange of resources such as strategic information (Podolny and Baron, 1997), information on job leads (Granovetter, 1973; Wanberg et al., 2000), good ideas (Burt, 2004), and instrumental support (Blickle et al., 2009). As both constructs focus on information, we predict that openness positively affects networking behaviors. Moreover, individuals high in openness may be specifically attracted to relationships that bring them novel ideas and experiences. We therefore propose that openness to experience might be of higher importance for external than internal networking. In line with our argument on density, Burt (2004) suggests that opinions are more homogenous within than across groups and bridging contacts provide better access to information on alternative ways of thinking. Hence, individuals who seek new and unconventional ideas and experiences may be eager to network with external contacts, from who they can obtain diverse resources. Finally, we assume that information exchange may be more available in the context of building and maintaining contacts than using contacts. Using contacts involves searching for specific information, whereas building or maintaining contacts tap into more general, broader information. In this vein, Cuperman and Ickes (2009) report that openness to experience is positively associated with the interest in interacting with a new acquaintance and the introduction of new topics for discussion. Hence, individuals high in openness to experience may prefer to build and maintain relationships rather than to use them.
H3. Openness to experience is positively related to networking behaviors.
H3a. The relationship between openness to experience and external networking is stronger than the relationship between openness to experience and internal networking.
H3b. Openness for experience is more closely related to building and maintaining contacts than to using contacts.
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Conscientiousness and emotional stability Our basic premise suggests that social and informational aspects represent the core linkage between personality and networking behaviors. We assume that conscientiousness and emotional stability do not contribute to this linkage (Cuperman and Ickes, 2009). Therefore, instead of positing hypotheses for conscientiousness and emotional stability, we will explore these relationships to provide a full picture of the relationship between the Big Five and networking.
Several studies have examined conscientiousness, but results have been mixed with positive (Ferris et al., 2005, study 1; Wanberg et al., 2000) as well as null findings (Ferris et al., 2005, study 2; Van Hoye et al., 2009). Conscientiousness refers to task-related behaviors (cf. Ashton et al., 2002; Borkenau and Ostendorf, 2008), such as being careful, thorough, responsible, perseverant, and planful. We assume that due to its task-related focus conscientiousness might only be useful for a few networking behaviors, such as keeping a list of contacts or showing perseverance in asking for job leads. However, other conscientious behaviors might stand in strong contrast to networking behaviors. For example, concerns of rightfulness might inhibit the use of informal as opposed to official channels to obtain information, or their sense of duty might keep individuals focused on their task rather than chatting away their time.
We also do not expect a relationship between emotional stability and networking. Individuals high in emotional stability are calm, relaxed, secure, and seldom feel anxious, depressed, or angry. Work in social psychology has often reported lower satisfaction in close relationships for individuals low in emotional stability (e.g. marriage, cf. Buss, 1991), but it is important to note that these individuals do form relationships. In this vein, emotional stability appears to affect strong ties, but not weak ties (Asendorpf and Wilpers, 1998) and is not related to network size (Roberts et al., 2008). As networking relations should mostly be considered weak ties (Wolff and Moser, 2006), we do not expect a relationship between emotional stability and networking behaviors.
Method Samples and procedure We use two samples, from Germany and the UK, to examine our research hypotheses. We thus follow a cross-validation strategy that goes beyond a single test of significance in a single sample. While cultural differences between Germany and the UK do exist (e.g. Hofstede, 2001), note that the Big Five dimensions represent basic, presumably universal individual dispositions (McCrae and Costa, 1997) and have been reliably replicated across cultures (Bartram et al., 2006; McCrae and Costa, 1997). Similarly, Wolff et al. (2011) have shown that the German and English networking scale versions used in this study are comparable across languages. We will, nevertheless, examine this equivalence assumption as we describe in the analyses section below.
In both samples, we assessed constructs by means of online surveys and, to increase response rate, participants were offered a personalized report of their results in the personality test used to measure the Big Five. To alleviate concerns of common method variance, we separated the assessment of the Big Five measures and the networking measures.
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German sample. We invited 1,084 members of an university based, research-oriented online-panel to participate in a study on personality. We obtained 371 complete questionnaires for a response rate of 34 percent. Just eight weeks later, we contacted 357 of these 371 respondents (some e-mail addresses were invalid or participants had quit their panel membership) to participate in another study on professional contacts and networking. We obtained 210 completed questionnaires for a response rate of 59 percent. From these 210 respondents, we selected only those respondents who were German residents, were currently employed, and had at least one year of work experience. The final size of this German sample was n ¼ 176: Respondents mean age was 40.2 years ðSD ¼ 9:3Þ and 97 (55 percent) were female (79 males). Their average work experience was 16.9 years ðSD ¼ 10:5Þ and 83 (47 percent) indicated they were in a supervisor position. Of the respondents, 87 (49 percent) had a university degree. Respondents came from a variety of business sectors, the most frequent were health service (13 percent), public sector (12 percent), professional services (6 percent), and retail (6 percent).
UK sample. We invited 3,107 respondents who had signed up to participate in online surveys by SHL, a UK-based company offering a range of instruments for personnel selection. Individuals were asked to complete two separate questionnaires for a study on how people relate to and interact with others at work. As we were unable to temporally set the two questionnaires apart we used a psychological separation by providing respondents with two separate links to access the personality questionnaire and the networking scales, respectively. We obtained 289 complete responses (9 percent) on the personality questionnaire and 268 complete responses (8 percent) on the networking part of the study. Even though response rate is low, it is comparable to other research using methods such as opt-in mailing lists or e-mail solicitation (Skitka and Sargis, 2006). We will further review this issue in our discussion section. Similar to the German sample, we selected only respondents who completed both questionnaires, were UK residents, were employed, and had at least one year of work experience, for a final sample size of n ¼ 175: The mean age of respondents was 34.9 years ðSD ¼ 9:9Þ and 99 (57 percent) were female (76 males). Their average work experience was 12.4 years ðSD ¼ 10:3Þ and 98 (56 percent) indicated they were in a supervisor position. In comparison to the German sample, more respondents (66 percent) had a college degree, a difference possibly due to differences in educational systems between the two countries. Also, the UK sample was younger ðd ¼ 20:56Þ and had accordingly less work experience ðd ¼ 20:43Þ: Note, however, that in examining relationships between variables, range restriction rather than mean differences poses a threat to analyses. An examination of the range of these variables showed no evidence of range restriction with regard to age (Germany: Range ¼ 22–62;UK : Range ¼ 19–59Þ or work experience (Germany: Range ¼ 1 2 44years;UK : Range ¼ 1 – 36 years). As a precaution, we controlled for work experience in the present analyses, omitting age, as these two variables were highly correlated (r . 0.84). Respondents most frequently worked in the public sector (12 percent), education (7 percent), retail (7 percent), or health services (6 percent).
Measures Networking. We assessed networking using Wolff and Moser’s (2006) networking scales composed of six types of networking behaviors:
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(1) building internal contacts (six items, e.g. “I use company events to make new contacts”, coefficient alpha for Germany/ UK : a ¼ 0:79=0:76Þ;
(2) maintaining internal contacts (seven items, e.g. “I catch up with colleagues from other departments about what they are working on”, a ¼ 0:79=0:71Þ;
(3) using internal contacts (eight items, e.g. “I use my contacts with colleagues in other departments in order to get confidential advice in business matters”, a ¼ 0:84=0:78Þ;
(4) building external contacts (seven items, e.g. “I accept invitations to official functions or festivities out of professional interest”, a ¼ 0:89=0:81Þ;
(5) maintaining external contacts (seven items, e.g. “I ask others to give my regards to business acquaintances outside of our company”, a ¼ 0:88=0:82Þ; and
(6) using external contacts (eight items, e.g. “I exchange professional tips and hints with acquaintances from other organizations”, a ¼ 0:88=0:81Þ:
Wolff et al. (2011) provide evidence for the equivalence of the German and English networking items and the respective scales.
Personality. We used SHL’s Occupational Personality Questionnaire 32nw (OPQw, Bartram et al., 2006) to assess the Big Five personality dimensions. The OPQw is a 230 item self-report measure used in personnel selection that consists of 32 scales describing occupationally relevant characteristics of personality. It has been specifically developed for use in different cultures and countries and is available in more than 30 languages; among these are the English and the German version used in the present study. Several studies provide evidence for the validity of this instrument (Bartram et al., 2006; Robertson and Kinder, 1993; Saville et al., 1996), which has also been used by other researchers in their substantive research (e.g. Barrick et al., 2002; Whetzel et al., 2010). Composite scores of the 32 OPQw scales can be used to obtain valid and reliable measures of the Big Five dimensions (Bartram and Brown, 2005). Composite reliabilities calculated for extraversion (Germany/UK: a ¼ 0:94=0:94Þ; agreeableness ða ¼ 0:91=0:85Þ; openness to experience ða ¼ 0:93=0:90Þ; conscientiousness ða ¼ 0:93=0:89Þ; and emotional stability ða ¼ 0:94=0:94Þ were all satisfactory.
Control variables. We used four control variables in our analyses. First, we controlled for gender ð1 ¼ male; 2 ¼ femaleÞ as small, yet consistent between country gender differences have been reported for the OPQw (Bartram et al., 2006). We also used education ð0 ¼ nocollegedegree; 1 ¼ collegedegreeÞ as a control variable as educational systems differ between the countries, which might influence results (i.e. the German Diploma is equivalent to a master’s degree and German universities have only recently started awarding Bachelor’s degrees). We also controlled for respondents’ years of work experience and whether respondents held a supervisor position ð0 ¼ nosupervisorposition; 1 ¼ supervisor position), as these have been shown to covary with personality and networking (Bartram et al., 2006; Forret and Dougherty, 2001).
Analyses Our hypotheses refer to the relationships between two sets of variables, a set of five independent personality variables (i.e. the Big Five dimensions) and a set of six dependent variables (i.e. the networking subscales) across two countries (i.e. Germany
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and the UK). To analyze this data, we use a multivariate structural model (Edwards, 2001) that we estimate by means of structural equation modeling. In this model, the set of the six networking measures is simultaneously regressed on the independent variables (our model can also be considered as a latent multivariate regression analysis, see, e.g. Jöreskog and Sörbom (1996)). This model treats the six networking measures as a variable set, and thus allows direct tests whether a personality dimension affects networking as a whole (Edwards, 2001). To compare the results from the two samples, we use a multiple group approach to estimate parameters simultaneously in a single model. By imposing equality restrictions on coefficients from the two samples, we examine whether relationships within and between variable sets are similar across the two countries.
We did not use an item level measurement model as our sample size was rather small in comparison to the number of almost 300 items. Rather, we modeled each construct as a latent variable with a single indicator, thus using a model with 15 variables (i.e. the six networking subscales, the five Big Five scales, and four control variables). Note that we therefore cannot test whether the item level measurement models of the personality and networking measures are invariant across countries in the present study. However, prior studies have provided evidence that this assumption is reasonable (Bartram et al., 2006; Wolff et al., 2011) and we do examine comparability of scale intercorrelations across samples. For the personality and networking scales, we accounted for measurement error by setting the variance of each manifest variable to one minus the reported reliability multiplied by the variance of the respective scale. We did not correct for measurement error in control variables. We assessed model fit by examining Model Chi-square and compared models by means of a Chi-square difference test (i.e. DX 2). Note that we also report other conventional fit indices (i.e. RMSEA, CFI, SRMR), but as the majority of our models fit well with regard to these indices we based our decisions on the more conservative Chi-square tests.
We use three strategies to test our hypotheses. First, as a prerequisite, we inspect the pattern of structural coefficients to examine if their values were in line with our hypotheses. Second, to examine whether a personality dimension was related to the entire set of networking variables, we restrict the six structural coefficients relating this personality dimension to the six networking behaviors to zero. A significant result indicates that relationships exist and should be taken into account. Third, several hypotheses refer to differences in the strength of relationships. We test these hypotheses by restricting the relevant coefficients to equality. As these models with equality restrictions are nested in the unrestricted models, differences in model fit can be assessed by a chi-square difference test. A significant deterioration of model fit indicates that the equality restriction is inappropriate and implies that the difference between coefficients is significant.
Results Table I shows variable intercorrelations and descriptive statistics for the two samples. Prior to testing our hypotheses, we estimated several models to examine whether the relationships between variables were comparable across countries (see Table II). Model 1 is a baseline model, where the six networking variables are regressed on all control variables and all personality dimensions. All parameters are free to vary across countries. As we use a single indicator model, this model has perfect fit and zero
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01 2
0. 03
2 0.
02 0.
07 0.
19 *
0. 10
0. 05
0. 02
2 0.
02 2
0. 02
5. E
x tr
av er
si on
2 0.
06 0.
10 2
0. 06
0. 11
– 0.
46 *
* 0.
23 *
* 0.
22 *
* 0.
59 *
* 0.
63 *
* 0.
20 *
* 0.
21 *
* 0.
34 *
* 0.
25 *
* 0.
20 *
*
6. O
p en
n es
s 2
0. 02
0. 16
* 2
0. 02
0. 11
0. 52
* *
– 0.
01 0.
12 0.
36 *
* 0.
35 *
* 0.
22 *
* 0.
10 0.
36 *
* 0.
33 *
* 0.
19 *
7. A
g re
ea b
le n
es s
0. 04
0. 23
* *
2 0.
08 2
0. 07
0. 11
0. 13
– 0.
06 0.
12 0.
18 *
0. 15
* 0.
14 2
0. 03
2 0.
03 0.
07 8.
C on
sc ie
n ti
ou sn
es s
0. 12
0. 01
0. 03
0. 09
0. 29
* *
0. 33
* *
0. 01
– 0.
32 *
* 0.
15 *
0. 14
0. 08
0. 17
* 0.
02 0.
04 9.
E m
ot io
n al
st ab
il it
y 2
0. 25
* *
0. 24
* *
0. 06
0. 17
* 0.
47 *
* 0.
40 *
* 0.
11 0.
25 *
* –
0. 47
* *
0. 21
* *
0. 15
* 0.
28 *
* 0.
20 *
* 0.
17 *
10 .
B u
il d
in g
in te
rn al
co n
ta ct
s 2
0. 10
0. 16
* 0.
04 0.
26 *
* 0.
50 *
* 0.
42 *
* 2
0. 01
0. 16
* 0.
28 *
– 0.
35 *
* 0.
22 *
* 0.
48 *
* 0.
39 *
* 0.
23 *
*
11 .
M ai
n ta
in in
g in
te rn
al co
n ta
ct s
2 0.
01 0.
14 2
0. 07
0. 15
0. 30
* *
0. 38
* *
0. 16
* 0.
03 0.
10 0.
46 *
* –
0. 57
* *
0. 46
* *
0. 49
* *
0. 47
* *
12 .
U si
n g
in te
rn al
co n
ta ct
s 2
0. 04
0. 11
2 0.
14 0.
08 0.
21 *
* 0.
19 *
0. 12
2 0.
06 2
0. 02
0. 44
* *
0. 69
* *
– 0.
38 *
* 0.
43 *
* 0.
54 *
*
13 .
B u
il d
in g
ex te
rn al
co n
ta ct
s 2
0. 03
0. 21
* *
0. 05
0. 25
* *
0. 37
* *
0. 39
* *
2 0.
02 0.
17 *
0. 17
* 0.
58 *
* 0.
50 *
* 0.
45 *
* –
0. 71
* *
0. 58
* *
14 .
M ai
n ta
in in
g ex
te rn
al co
n ta
ct s
2 0.
13 0.
20 *
* 2
0. 13
0. 21
* *
0. 30
* *
0. 32
* *
2 0.
02 0.
14 0.
07 0.
51 *
* 0.
57 *
* 0.
57 *
* 0.
77 *
* –
0. 73
* *
15 .
U si
n g
ex te
rn al
co n
ta ct
s 2
0. 06
0. 15
2 0.
24 *
* 0.
07 0.
20 *
* 0.
21 *
* 0.
10 2
0. 02
2 0.
02 0.
36 *
* 0.
54 *
* 0.
66 *
* 0.
57 *
* 0.
76 *
* –
G er
m an
y M
1. 55
0. 49
16 .8
5 0.
47 14
.9 6
13 .9
9 11
.9 3
26 .6
4 13
.4 5
2. 43
2. 71
2. 50
1. 92
2. 05
1. 98
S D
0. 50
0. 50
10 .4
5 0.
50 3.
37 3.
45 2.
76 3.
48 3.
71 0.
59 0.
50 0.
59 0.
68 0.
64 0.
64 U
K M
1. 57
0. 66
12 .3
7 0.
56 15
.7 4
15 .0
2 10
.7 9
26 .3
8 13
.4 0
2. 52
2. 73
2. 66
2. 10
2. 04
1. 88
S D
0. 50
0. 48
10 .3
2 0.
50 4.
12 3.
87 3.
37 3.
57 4.
56 0.
59 0.
44 0.
53 0.
58 0.
58 0.
55
N o te :
C or
re la
ti on
s fo
r th
e G
er m
an sa
m p
le (N
¼ 17
6) an
d th
e U
K sa
m p
le (N
¼ 17
5) ar
e b
el ow
an d
ab ov
e th
e d
ia g
on al
, re
sp ec
ti v
el y
; * p
, 0.
05 ;
* * p
, 0.
01
Table I. Descriptive statistics and correlations of study variables for German and UK samples
CDI 17,1
54
T es
t of
ov er
al l
m od
el fi
t F
it fo
r ea
ch sa
m p
le M
od el
co m
p ar
is on
X 2
D f
R M
S E
A C
F I
S R
M R
(G )
S R
M R
(U K
) M
od el
s D X
2 (d
f)
1. B
as el
in e
m od
el :
al l
co ef
fi ci
en ts
fr ee
, tw
o se
p ar
at e
m od
el s
0 0
0 1.
00 0
0 E
q u
al it
y co
n st
ra in
ts ac
ro ss
co u
n tr
ie s
2. E
q u
al v
ar ia
n ce
s an
d co
v ar
ia n
ce s
fo r
p er
so n
al it
y m
ea su
re s
an d
n et
w or
k in
g sc
al es
48 .7
1 36
0. 05
1. 00
0. 05
0. 05
2- 1
48 .7
1 36
3. E
q u
al it
y co
n st
ra in
ts on
st ru
ct u
ra l
co ef
fi ci
en ts
(p er
so n
al it
y !
n et
w or
k in
g )
ad d
ed to
m od
el 2
10 0.
79 90
0. 03
1. 00
0. 07
0. 07
3- 2
52 .0
8 54
N o te : N
(G er
m an
sa m
p le
) ¼
17 6, N
(U K
sa m
p le
) ¼
17 5.
R es
u lt
s ar
e b
as ed
on ro
b u
st m
ax im
u m
li k
el ih
oo d
es ti
m at
io n
Table II. Fit indices for structural
equation models
Networking and the Big Five
55
degrees of freedom. In Model 2, we test whether variances and covariances within each set of substantive variables, the Big Five and the networking scales, respectively, are equal across countries. Comparable relationships within each set of variables provide evidence that similar sets have been assessed in both countries and we consider this a prerequisite to a meaningful comparison of relationships across the two sets of variables (i.e. regression of networking on the Big Five). As Table II shows, Model 2 fit the data well ðX 2 ¼ 48:71; df ¼ 36; p ¼ 0:08Þ[1]. Next, in Model 3, we examine whether the structural coefficients, regressing networking on the Big Five and control variables differ for Germany and the UK. A model restricting these coefficients to equality also fit the data well ðX 2 ¼ 100:79; df ¼ 90; p . 0.10) and does not fit significantly worse than Model 2 ðDX 2 ¼ 52:08; df ¼ 54; p . 0.10). Model 3 provides evidence that relationships among as well as between the Big Five and networking measures are comparable across the two countries. Structural coefficients of Model 3 are shown in Table III. For extraversion and openness to experience, five of the six structural coefficients are positive and significant. Three of the six coefficients relating agreeableness to the networking scales are significant, yet note that the coefficient for building external contacts is significantly negative. Neither conscientiousness nor emotional stability are significantly related to the networking measures.
Two hypotheses specify relationships between extraversion and networking behaviors. H1 predicts an effect of extraversion on the set of networking variables. Inspection of Table III shows that all six coefficients are positive and in line with our hypothesis. We test this hypothesis by restricting all six coefficients between extraversion and the networking behaviors (i.e. the entire set of networking variables) to zero. The resulting model fits significantly worse than Model 3 ðDX 2 ¼ 50:69; df ¼ 6; p, 0.01), indicating that the effect of extraversion on the set of networking variables is significant. This provides support for H1. H1a refers to the functional networking
Internal networking External networking Building contacts
Maintaining contacts
Using contacts
Building contacts
Maintaining contacts
Using contacts
Control variables Gender 20.01 0.06 20.06 0.03 0.11 20.08 Education 0.06 20.01 20.04 0.19 * * 0.11 20.02 Work experience 0.01 20.05 20.15 * 0.04 20.13 * 20.26 * *
Supervisor position 0.22 * * 0.19 * * 0.12 0.11 0.10 0.09 Personality Extraversion 0.54 * * 0.07 0.22 * 0.25 * * 0.22 * * 0.16 * *
Openness 0.13 * * 0.32 * * 0.10 0.25 * * 0.27 * * 0.19 * *
Agreeableness 20.01 0.16 * * 0.14 * * 20.11 * * 20.07 0.08 Conscientiousness 20.01 20.03 20.06 0.08 0.02 20.07 Emotional stability 0.04 20.01 20.10 20.05 20.13 20.08
Note: Structural coefficients as well as variances and covariances with each set of substantive variables (i.e. personality and networking) variables were restricted to equality across countries (Model 3 from Table II). Results from common metric completely, standardized solution are shown; *p , 0.05; * *p , 0.01
Table III. Effects of control variables and personality on networking: structural coefficients of the full model
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facet and predicts that extraversion is more closely related to building contacts than to maintaining and using contacts. The pattern of coefficients (cf. Table III) supports this assumption for internal as well as external networking. We further test this hypothesis by calculating two models with equality restrictions. In a first model, we restrict coefficients of building and maintaining contacts to equality, with two equality restrictions for internal and external networking, respectively. This model fit significantly worse than the unrestricted model 3 ðDX 2 ¼ 30:91; df ¼ 2; p , 0:01Þ; indicating that that coefficients are not equal, but significantly different. In a second model, we restrict coefficients for building and using contacts to equality. This also reduced model fit significantly (compared to Model 3: DX 2 ¼ 11:49; df ¼ 2; p, 0.01). These tests provide support for H1a. In sum, we find that extraversion is positively related to networking behaviors and also more closely related to building contacts than to maintaining and using contacts.
H2 posits a positive association between agreeableness and the full set of networking behaviors. Table III shows that two coefficients, for maintaining and using internal contacts, are significantly positive. However, the relationship between agreeableness and building external contacts is significantly negative. Therefore, H2 is rejected. H2a further specifies that the relationship between agreeableness is higher for internal than for external networking. The relevant coefficients from Table III show that this assumption holds for building contacts ðg ¼ 20:01=g ¼ 20:11 for building internal and external contacts, respectively) as well as maintaining contacts ðg ¼ 0:16=2 0:07Þandusingcontactsðg ¼ 0:14=0:08Þ: To provide a formal test of this hypothesis, were restrict the three pairs of coefficients to equality, using a single model, as all three pairs of coefficients are in the predicted direction. This significantly reduces model fit (compared to Model 3: DX 2 ¼ 12:53; df ¼ 3; p , 0.01), yielding support for H2a.
H2b refers to the functional facet of networking, predicting that the relationship of agreeableness with maintaining and using contacts is higher than the relationship with building contacts. The pattern of coefficients is in line with this assumption for internal as well as external networking (see Table III, note that our hypothesis does not entail strictly positive coefficients). To test this assumption we examined two additional models. In the first model, we restricted the relationship of agreeableness with building and maintaining contacts to equality for internal and external networking, respectively. This reduced model fit, but only to a marginally significant extent (compared to Model 3: DX 2 ¼ 4:72; df ¼ 2; p ¼ 0:09Þ: In a second model, we restricted the coefficients for building contacts and using contacts to equality, again using a single model with one equality restriction for internal networking and an additional equality restriction for external networking. This significantly reduced model fit, indicating that these coefficients were significantly different (compared to Model 3: DX 2 ¼ 10:33; df ¼ 2; p , 0.01). Taken together, the two tests provide support for hypothesis 2b. In sum, we find that agreeableness is more positively related to internal networking dimensions than to external dimensions and also more closely to maintaining and using contacts, but not or negatively to building contacts.
Three further hypotheses concern the relationship between openness to experience and networking behaviors. First, H3 predicts a relationship between openness and the set of the six networking variables. Table III shows that all coefficients are positive and thus in line with this hypothesis. As a model restricting these six coefficients to zero significantly decreases model fit (compared to Model 3: DX 2 ¼ 22:89; df ¼ 6;
Networking and the Big Five
57
p , 0.01), this hypothesis is supported. Second, H3a assumes that the relationship of openness to experience with external networking is higher than with internal networking. Table III shows that coefficients for building contacts ðg ¼ 0:13=g ¼ 0:25 for building internal and external contacts, respectively) and using contacts ðg ¼ 0:10=g ¼ 0:19Þ are in the predicted direction, but coefficients for maintaining contacts are not ðg ¼ 0:32=g ¼ 0:27Þ: As this pattern is not in line with H3a, we rejected this hypothesis.
H3b predicts that openness to experience is more closely related to building and maintaining than to using contacts. The descriptive pattern of coefficients in Table III is in line with this assumption. To provide a more formal test, we calculate two models. The first model restricts coefficients for building and using contacts to equality, using two coefficients for internal and external networking, respectively. This model did not fit significantly worse than the unrestricted model 3 ðDX 2 ¼ 0:75; df ¼ 2; p ¼ 0:39Þ; indicating no significant difference between coefficients. Restricting maintaining and using contacts to equality did reduce model fit significantly (compared to model 3: DX 2 ¼ 6:73; df ¼ 2; p , 0.01). These results provide partial support for H3b, as openness to experience is more closely related to maintaining than to using contacts, but we find no difference between building and using contacts.
In two exploratory tests, we examined whether conscientiousness or emotional stability were significantly related to the set networking behaviors. However, neither restricting all six paths from conscientiousness to networking to zero (compared to model 3: DX 2 ¼ 8:09; df ¼ 6; p ¼ 0:23Þ nor restricting the paths from emotional stability to networking behaviors to zero (compared to model 3 : DX 2 ¼ 6:98; df ¼ 6; p ¼ 0:32Þ significantly reduced model fit. Thus, we find no evidence for relationships between these variables.
Overall, we find that two of the Big Five traits, extraversion and openness to experience are related to networking behaviors as a variable set. Furthermore, we find evidence for differential relationships between these two personality dimensions and networking behaviors. The relationship between extraversion and networking is stronger for building than for maintaining or using contacts. Also, the relationship between openness to experience is stronger for maintaining than for using, but not building contacts. Finally, agreeableness shows positive relationships only to internal networking.
Discussion The present study is the first to provide a comprehensive picture of the personality- networking relationship by examining the impact of the full Five Factor Model of personality on networking dimensions in samples of employed individuals. Our results thus contribute to the literature that has often focused on subsets of the Big Five, specific networking behaviors, or unemployed individuals. The broad relation between extraversion as well as openness to experience and networking behaviors supports the general proposition that the core linkages between the Big Five and networking are their social and informational content. Thus, in consistency with past studies, we demonstrate that extraversion facilitates networking behaviors (Forret and Dougherty, 2001; Wanberg et al., 2000; Wolff and Moser, 2006). More importantly, we show that in addition to this commonly reported social linkage, there exists another broad linkage between personality and networking that is based upon informational features. This
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58
finding is in line with theory on networking that highlights the exchange of task-related and strategic information, information on jobs, industry trends, and also with Burt’s (2004) notion of good ideas. Although this finding might appear intuitive in hindsight, prior studies have neglected openness to experience (and similarly agreeableness). In addition, beyond these general associations, we found support for our notion of differential relationships between personality dimensions and networking behaviors. We discuss these findings in the subsequent paragraphs, successively focusing on the five personality dimensions.
With regard to extraversion, we find a positive relationship with networking. Individuals actively seek social attention and this disposition inclines individuals to engage in interactions at work. With regard to differential relationships, extraversion is more closely related to building contacts than to maintaining and using contacts. This finding is line with our contention that the functional facet of building, maintaining, and using contacts is associated with an increasing instrumental focus on networking behaviors. Building contacts might satisfy the need for social attention of extraverted individuals (Ashton et al., 2002), but they may not necessarily focus on the more instrumental aspects of maintaining and using contacts. If extraversion is associated to the social aspects, extraversion might lead to ‘incidental networking’, that is, it particularly facilitates those networking behaviors that require little effort and simultaneously yield social attention (i.e. building internal contacts), but might of less importance for networking behaviors related to specific instrumental goals. Extraverted individuals might thus put less emphasis on the strategic choice of interaction partners. Further studies are needed to examine whether instrumental aspects (e.g. work involvement) moderate the relationship between extraversion and networking behaviors.
Another important finding is that agreeableness is positively related to internal networking, in particular to maintaining and using internal contacts, but is negatively related to building external contacts. This finding supports our notion of differential relationships of personality with dimensions of networking behaviors. It also is in line with our reasoning that agreeableness facilitates internal networking more than external networking due to the restricted discretion in choosing contacts within organizations, where being likeable is of higher importance. Also, agreeableness does not facilitate building contacts, and, in the case of external networking, can even hinder building contacts. Next to extraversion, impression management tactics (Schlenker, 1980) might be of more importance in building contacts, whereas agreeableness is of importance once the relationship has been established. Yet, given that building contacts is a prerequisite for maintaining and using contacts, further research is necessary to examine how agreeableness is related to social capital variables, in particular network size and density. As agreeableness is not, or even negatively related to building contacts, agreeable individuals might possess smaller and less diverse networks. In fact, agreeableness might even act as a suppressor in the relationship between networking behaviors and social capital variables.
Also, openness to experience was broadly related to networking behaviors. In addition, openness to experience had a stronger relationship with maintaining contacts than with using contacts. This might reflect individuals’ preference for general, yet novel information, rather than searching for information when they need it. It might also reflect an interest in others’ tasks, news, and ideas that broaden the horizon of
Networking and the Big Five
59
occupational knowledge beyond individuals’ specific work tasks, which has also been put forward in the practitioner literature on networking (e.g. Baker, 1994).
Both conscientiousness and emotional stability are not associated with networking behaviors. Individuals high in conscientiousness may focus more on their work tasks and less on relationships with coworkers in spite of their potential instrumental value. As prior findings have been mixed, this suggests that the relationship between conscientiousness and networking might depend on additional moderators. Also, emotional stability was not related to networking behaviors. In line with findings from other areas (Asendorpf and Wilpers, 1998), emotional stability does not appear to affect networking relationships. Networking relationships focus on weak ties that go beyond the formal relationships within an organization and negative effects of emotional stability might only be evident in strong tie relationships.
In sum, this discussion shows support for our contention of differential relationships between personality and networking dimensions. As agreeableness was positively related only to internal networking dimensions and the highest relationship for extraversion was with building internal contacts, it seems that the social aspects of personality matter more within than outside the organization. We suggest that discretion in selecting whom to network with, lesser effort to connect with others, as well as a greater concern due to reputation drive these relationships and further research is necessary to disentangle the impact of these mechanisms. Also, note that the relationships of extraversion and openness to experience with external networking dimensions show that personality is not irrelevant in external networking. In addition, we found differential relationships of personality with the functional facet of building, maintaining, and using contacts. These findings support our notion that individuals increasingly bear instrumental considerations in mind as they further develop their contacts. This finding also highlights that networking is a mix of social and instrumental considerations (Wolff and Moser, 2006).
The pattern of our results also suggests that the two facets are not fully independent. While our hypotheses concerned simple effects of either the structural or the functional facet, the strength of these effects varied within a facet. For example, the highest difference in relationships for agreeableness with internal versus external networking occurs for building contacts and the difference for using contacts is smaller; likewise, the difference in relationships of extraversion with building and maintaining contacts is higher for internal than for external networking. This shows that our theorizing on simple distinctions between the facets should be considered a viable starting point, yet future research should disentangle these more complex contingent effects.
Our study has practical implications for organizations and individuals in navigating the boundaryless career landscape. First, our findings provide valuable insights for trainings on networking or career self-management. Feedback on personality dimensions together with our results provide insights into which networking behaviors are more consistent with an individual’s personality dispositions. This feedback is valuable for career counselors, trainers, coaches and possibly supervisors in evaluating individuals’ networking efforts and providing counsel in how to improve their networking skills. Showing networking behaviors that are inconsistent with individuals’ dispositions is more difficult and thus requires more effort. Individuals should take this into account when they set networking goals or choose networking strategies. In such cases, goals might be adapted to reflect this
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difficulty and individuals might need more support in mastering difficult networking behaviors. Also, awareness of dispositions might allow individuals to play their strengths and accordingly attune their networking behaviors. In this vein, De Janasz and Forret, 2008, p. 664) suggest that “for those who are shy, networking can be achieved through means other than face-to-face, such as e-mail or letter”. Moreover, contrary to lay theories on networking, introverted individuals might be encouraged to network as other dispositional factors beyond extraversion facilitate networking behaviors. Finally, with regard to recruiting applicants for a position where networking skills are important, we caution HR professionals to exclusively take extraversion of applicants into account. Even though extraversion is an important disposition in predicting networking behaviors, our results suggest that considering openness to experience in addition to extraversion might enhance the predictive validity of the personnel decisions.
A potential limitation of our study is the low response rate for the UK sample. Low response rates might bias results if non-responders differ systematically in important variables from responders. As our response rate is comparable to other studies using opt-in mailing lists (Skitka and Sargis, 2006) we attribute this to problems of this particular recruitment strategy in general rather than specific problems in the present study. For example, using a similar recruitment method, Welker (2001 cf. Birnbaum, 2004) found that one third of their participants did not check their mails during the study period. Also invitations might have been classified as spam, and there existed only a weak relationship between respondent and research institution. Moreover, two points strengthen our confidence in our findings. First, sample bias is not a highly plausible alternative explanation given the fact that our findings are comparable across the two samples. This would have required sample bias to affect both samples in a similar manner in spite of differences in sampling method and response rates. Rather, this cross validation of results substantiates our findings and we consider this a distinct strength of this study. Second, other research has shown that non response in online studies appears to rarely affect substantive conclusions (Skitka and Sargis, 2006), in particular correlational findings (e.g. Göritz and Schumacher, 2000). Another limitation is that our use of self-report measures for personality as well as networking dimensions is subject to common method bias. However, we separated assessment of these constructs in our two samples, albeit by different means, and common method bias is highly unlikely to result in systematic variance across scales and countries in a manner that yields comparable results. Also, the promised personalized feedback report should have encouraged respondents to provide truthful answers.
Conclusion Since two decades, the importance of networking as a strategy to self-manage careers has been increasingly emphasized. While networking consequences have been extensively examined, studies regarding networking antecedents have been scarce. The present study examined the relationship between the Big Five traits and six networking behaviors in samples of employed individuals. Extraversion and openness to experience were related to networking behaviors as a variable set. We showed that networking behaviors are influenced by personality dimensions that refer social (i.e. extraversion, agreeableness) as well as informational content (i.e. openness to
Networking and the Big Five
61
experience). Furthermore, we found differential relationships between these traits (i.e. extraversion, agreeableness, and openness to experience) and the two networking facets (i.e. structure and function). Overall, this study contributes to our understanding of why some individuals engage more in networking than others and which personality traits facilitate what networking behaviors. In line with other studies, we provide evidence that personality matters at work.
Note
1. Note that we did not expect equal covariances between control variables and personality measures for the two countries. Control variables and relations between them might well be influenced by country differences. For example, there may exist national differences with regard to promoting women to higher positions that affect the relation between gender and supervisor position. In fact, a model that restricted variances and covariances between all predictors (control variables and the Big Five) to equality fit significantly worse than Model 2 of Table II (X 2 ¼ 118.58; df ¼ 66; p , 0.01).
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About the authors Dr Hans-Georg Wolff is a Researcher at the University of Erlangen-Nürnberg. He obtained a diploma in Psychology in 1998 at the University of Giessen and received his PhD (2004) and his Habilitation (2010) from the School of Business and Economics at the University of Erlangen-Nürnberg. His research focuses on organizational behavior, in particular social relations (networking) at work and career success, decision making, and also research methods. Hans-Georg Wolff is the corresponding author and can be contacted at: hans-georg.wolff@ wiso.uni-erlangen.de
Sowon Kim obtained her PhD in Management from HEC – University of Geneva in 2010 and is currently pursuing post doctorate studies at IESE Business School, University of Navarra in Barcelona, Spain. Her research interests include careers, networking, work-family interface, and gender diversity.
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