feedback seeking and social networking during job search

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Bogdan Yamkovenko and John Paul HatalaConceptual Model

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Theory and Conceptual Article

Feedback-Seeking and Social Networking Behaviors During Job Search: A Conceptual Model

Bogdan Yamkovenko1 and John Paul Hatala1

AbstractThis paper combines research on self-regulation, social resource theory, and weak tie theory to propose a conceptual model for why some people network more than others when searching for a job. This article explores the hypothetical relationship between social networking behaviors and self-regulatory mechanisms. Specifically, the focus is on explaining the differences in the job seeker’s feedback-seeking and networking behaviors and how they vary depending on state and trait goal orientation, motives for feedback seeking, and types of ties the job seekers connect with. A conceptual model of self-regulation and social networking behaviors presents a set of testable relationships that can be explored using correlational and experimental methods. The article also proposes specific research directions for testing the model and discusses the practical implications of the relationships.

Keywordsgoal orientation, social networking behaviors, feedback seeking, job search

In a recent editorial published in HRDR, Hill, Kuchinke, and Zinser (2013) argued that human resource development (HRD) and career and technical education are not quite ready to meet the needs of the 21st century. In addition, the authors posit that while jobs in science, medicine, and engineering are available, they go unfilled because

1Rochester Institute of Technology, NY, USA

Corresponding Author:John Paul Hatala, George Brown College, 200 King Street East, PO Box 1015, Station B, Room 490F, Toronto, Ontario, M5T 2T9.Email: [email protected]

497948 HRD13110.1177/1534484313497948Human Resource Development ReviewYamkovenko and Hatalaresearch-article2013

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Yamkovenko and Hatala 103

many candidates lack required skills. What is HRD research and practice doing to address this issue?

At the 2013 Academy of Human Resource Development (AHRD) conference a keynote speaker, Dr. Carnevale, discussed how during economic crises in the past many people who lost their jobs would often go back to the same jobs when the recovery began. Carnevale (2013) suggested that this is no longer the case because many jobs that were lost during the last crisis were low-skill jobs that may not have a place in the current economy. Therefore many job seekers may require reskilling and relearning. How can HRD help? We believe one way is to capitalize on one of HRD competencies of developing and designing an environment conducive to learning. Another way is to develop marketable skills, which include job-specific skills and interpersonal skills. But relearning as an adult may depend on self-regulation. Skill acquisition is not just about ability to learn, it also requires knowing which skills you need to learn. For that job seekers need to reach to their social resources. This problem therefore combines two fields of research and practice—self-regulation and social networking behaviors.

Since the beginning of the global economic slowdown in 2008, job search has been an important concern and often a necessity for many who have become unemployed. While the level of unemployment has been declining, it is a misleading number. This number does not include those that are not actively looking for work (Bureau of Labor Statistics, 2013). This group of people, called discouraged workers, is a part of a larger group known as workers marginally attached to workforce. The marginally attached workers are those that are not in the labor force, want work, and are available for work, while discouraged workers are those that believe that no work is available for them. Of long-term unemployed (4.7 million, or 36% of all unemployed), 2.6 million persons are marginally attached to workforce and 885,000 are discouraged workers (Bureau of Labor Statistics, February, 2013). The situation of the discouraged workers is particu-larly interesting because it may be indicative of combination of personal and situa-tional factors, some of which could be addressed by practitioners in career development fields and HRD in general.

Combining several theoretical perspectives may be a potential interdisciplinary solution to a problem of discouraged workforce, long-term unemployment, and skill upgrade to better prepare the workforce for the needs of the 21st century. This approach combines research and practice in HRD, career development, and social psychology. This article proposes a framework that unifies self-regulatory skills, social networking behaviors, and self-directed learning in an effort to explain job search success. Although there are a number of different approaches to address this phenomenon, we chose to focus on self-regulation framework due to the grounded research that has already been conducted in explaining the intricate mechanisms of how individuals seek feedback. Feedback is instrumental in skill development, learning, and monitor-ing one’s progress toward a goal, which are all important in the job search process (Ashford, Blatt, & Vande Walle, 2003). Therefore, the conceptual model developed in this article attempts to explain the feedback-seeking mechanisms that occur based on goal orientations that either facilitate or hinder social networking behaviors and the outcomes they lead to.



104 Human Resource Development Review 13(1)

This article is structured as follows: We first review the research on self-regulation and job search and discuss how self-regulatory skills, goal orientations, and implicit theories of personality interact to explain different ways people deal with uncertain and autonomous achievement situations; we then incorporate social resource theory and discuss how the social networking behaviors, quantity and types of ties people have, may depend on self-regulatory skills. Finally we combine these variables into a conceptual model, which is currently undergoing empirical testing, and which is designed to suggest practical courses of action to HRD and career development prac-titioners, to not only increase the likelihood of reemployment in the short-term but to also improve the skill set of the workforce well into the future.

HRD Relevance

This paper contributes to the research in HRD in several ways. First, in terms of career development research, which has been one of the “established focal points of human resource development” (McDonald & Hite, 2005, p. 418), it suggests an explanation to why people choose to persist and relearn or withdraw from job search. Herr (2001) suggested that career development serves the purpose of support for establishing new career directions. This implies that career development does not just occur on the job but also takes place during job search. The ability to establish a new career direction depends on one’s ability to adjust to a new job or career requirements and it is within the role of career development and HRD professionals to determine what can be done to manage this process.

Second, while self-directed learning (SDL) has a large body of literature, there is a need to add depth to this line of research (Ellinger, 2004). Among the research directions in the SDL domain, it is important to examine the influence of contextual factors on SDL. The job search context provides a very interesting and unique con-text for SDL. By using our proposed model as a framework, researchers can inves-tigate the variables that affect SDL in the context of job search and other autonomous tasks.

Finally, there has been a growing interest in HRD in the concept of social net-working behaviors and how these behaviors affect individual and organizational outcomes (e.g., Hatala, 2006; Hatala & Fleming, 2007; Storberg-Walker & Gubbins, 2007). This article attempts to explain social networking behaviors in the job search context from the standpoint of self-regulation theory. In other words, it is an attempt in HRD and the psychology literature to explain why some job seekers use network-ing and others do not. It has been shown in research (e.g., Hatala, 2007) that job seekers who network find jobs faster than those that do not. Understanding why this happens may allow HRD practitioners to develop tools and methods to help job seekers reach out to others for help in finding job leads, getting feedback on their skills and skill gaps, and obtaining support when experiencing setbacks. All this may seem counterproductive to an organizations’ efforts to retain employees; the effort will not only increase the number of individuals in the candidate pool but also increase the quality of people applying.




Job Search

It is important at the outset to define the variables critical to the job search process and specify the boundaries of this study. First, the distinction should be made between the job search and the outcomes of the job search. The most important outcome of the job search is employment status (employed versus unemployed). The employment status is often measured by asking an individual to report whether they are employed or unemployed by some predetermined time period. The other two employment outcome measures are job search duration and number of job offers (Kanfer, Wanberg, & Kantrowitz, 2001).

One of the main antecedents of these outcomes is the job search intensity, which is a common measure of the job search (Saks, 2006). Job search intensity is often mea-sured by asking an individual to indicate the frequency with which he or she engages in particular behaviors typical of the job search process (e.g., submitting resumes, going to job interviews). Job search effort is another measure of job search, and involves a self-reported perceived amount of effort exerted during the job search. Although this second measure has stronger relationships with job search outcomes, it is more vulnerable to exaggeration and impression management on the part of the respondents (Kanfer et al., 2001). In addition, the job search effort measure does not capture the variety of behaviors that are salient in the job search process. For example, in assessing the intensity of the job search process researchers can determine whether job seekers engaged in such behaviors as attending job fairs and resume writing classes, soliciting feedback on their resume characteristics, tailoring resumes and cover letters to each specific position, and reaching out to various social resources.

Often, the process of finding a job is long and arduous, and requires effort and com-mitment from the job seeker. Kanfer et al. (2001) suggest that looking for a job is equivalent to an unstructured, ambiguous, and autonomous work task. It requires sig-nificant self-regulation on the part of the job seeker. The individual must set appropri-ate goals, structure the approach to the job search task, make decisions about the intensity of effort to exert, and periodically adjust efforts and strategies (Blau, 1994). Therefore, Kanfer et al. (2001) defined job search as the outcome of a dynamic, recur-sive self-regulated process.

The self-regulated nature of the process of job search suggests that it is likely to change over time, which means that the intensity of the job search, and therefore fre-quency of various job search behaviors, can decrease, increase, or remain stable (Wanberg, Glomb, Song, & Sorenson, 2005). Wanberg et al. (2005) suggest that get-ting discouraged, adjusting the goals, and uncertainty about what to do next may all contribute to the change in job search intensity. This complexity of the job search behaviors is a function of interaction of personal tendencies, personal and social con-ditions, and desire to obtain employment (Kanfer et al., 2001).

Job search is also not a process many people are accustomed to and feel comfort-able in. Often they find themselves in the job search process unexpectedly, like after an abrupt organizational change, and must initiate and navigate the job search process on their own. Reaching out to others during this process may be instrumental not only




in finding job leads but also in dealing with setbacks and understanding what skills or knowledge must be acquired to secure the next job. It is therefore instructive to exam-ine the job search process in terms of these self-regulatory mechanisms. In the next section, we will review self-regulation research and introduce some applications of this area to the problem of job search.

Self-Regulation

Self-regulation is a purposive process of making self-corrective adjustments to stay on track (Carver & Scheier, 2012). Staying on track may imply moving toward or some-times away from a goal. Self-regulation may be conceptualized in terms of three main components: goal setting, goal operating, and goal monitoring (Burnette, O’Boyle, VanEpps, Pollack, & Finkel, 2012). Goals are a hierarchical concept. For example in the process of job search goals may be arranged from high-level goals of being a pro-vider for the family or a successful individual, to lower level goals of obtaining a posi-tion of employment, acquiring a new skill, or writing a cover letter for a specific job (Carver & Scheier, 1998). Not only is job search a self-regulated process, but it also consists of many subprocesses that are by their nature self-regulation processes.

Getting discouraged, dealing with setbacks, and adjusting goals are the elements of the complex system of self-regulatory mechanisms. Based on socio-cognitive theory, planning and forethought, reflection, self-efficacy evaluation, and self-monitoring are all important in this process (Bandura, 1997). Alternatively, Carver and Scheier’s (1981) self-control theory provides a very similar conceptualization of self-regulation pro-cesses. Both approaches are conceptually similar, but self-control theory offers a clear division of self-regulatory processes into three components: goal setting, goal operating, and goal monitoring (Figure 1). After the goal is set, people enact strategies to achieve the goal or operate the goal. As they do so the information on progress and distance from goal serves as an input function for goal monitoring, which results in strategy adjust-ment. This represents a negative feedback loop on which control theories rely. All three are enacted in the job search process, and constructs like job search intensity can be clearly linked to the goal-operating process, while other self-regulatory variables like goal orientation can be linked to goal-setting and goal-monitoring processes.

A part of the job search process may be learning new skills required to secure one’s next position of employment. Those job-seekers who are no longer in the educational system face different challenges then those who are attempting to make the transition from school to work and as a result any learning that occurs during the job search may be self-directed. SDL can take place in the formal or informal learning context (Ellinger, 2004). In addition, the SDL process has been conceptualized as a self-regu-latory process in several models (e.g., Garrison, 1997; Merriam & Caffarella, 1999). Many models that incorporate cognitive and metacognitive processes in explaining self-directed models include self-management, goal-setting, and self-reflection as important elements of SDL (Merriam & Caffarella, 1999). In other words SDL may be affected by the same self-regulatory variables we will discuss in this article.




More importantly, SDL does not have to occur in isolation, as learners can and do draw on social resources to assist them (Ellinger, 2004). They can do so in two ways: by obtaining learning resources from their contacts and by seeking feedback on the current state of their skills and progress toward goals. The feedback-seeking behavior is also rooted in self-regulation theory (Ashford & Cummings, 1983). Feedback seek-ing is part of monitoring of one’s progress toward the goal. People seek feedback based on three types of motives: instrumental, ego-boosting, and image-preserving motive. The motives result in different methods of feedback seeking, inquiry versus monitoring, and in different outcomes of the feedback. For example, when people seek feedback based on instrumental motive, they are specifically interested in direct evalu-ation of their ability and are less likely to use monitoring, or comparing themselves with others (Ashford et al., 2003).

Implicit Personality Theories and Goal Orientation

The self-regulation process outlined above in terms of goal-setting, goal-monitoring, and goal-operating phases offers a simplified picture of what happens in an achieve-ment situation. However, this process does not illuminate what affects each compo-nent and why there are differences in the way people handle each phase. One of the explanatory variables that have been considered in research is the implicit personality beliefs. Dweck and Leggett (1988) suggested that people vary in their beliefs about malleability of the human attributes. Specifically, some people see their abilities as

Figure 1. Self-regulation process based on Carver and Scheier’s (1998) control theory.Source. Adapted from Burnette et al. (2012). The path between goal setting and goal monitoring is changed from unidirectional to bidirectional to represent the possibility of adjusting or changing to goal based on goal monitoring.




fixed and some—as malleable. This difference is encompassed in what is known as entity and incremental theories of personality, respectively (Dweck & Leggett, 1988). Such beliefs affect the way people approach achievement situations, in that incremen-tal theorists believe that achieving a goal depends on exerting effort, and a discrepancy between the current state and a desired state can be reduced by ramping up the efforts. Conversely, the entity theorists believe that the achievement of a goal depends solely on their ability, and the discrepancy between the current state and a desired state is indicative of the lack of ability. Clearly, such differences may result in very different ways people set goals, operate the goals, and monitor the progress toward the goals. Implicit theories may affect the types of goals people set at the goal-setting stage, strategies they choose during the goal-operating stage, and the way they manage nega-tive emotions and expectations during the goal-monitoring stage (Burnette et al., 2012).

At the goal-setting phase, people may set one of the several different types of goals as a function of their implicit beliefs. They can set performance or learning goals, at the most basic level of distinction, and then each of these types of goals can be further subdivided into approach and avoidance types. These are known as goal orientations, and they contribute to the self-regulatory process by affecting the types of goals people set (Kanfer, 1990). Learning and performance goal orientation—two broad dimen-sions of one construct—have been shown to influence different types of performance outcomes and to evoke various types of behaviors in performance settings (e.g., Arenas, Tabernero, & Briones, 2006; Button, Mathieu, & Zajac, 1996; Sujan, Weitz, & Kumar, 1994; VandeWalle, 2001). Because of the nature of this construct, it is specifi-cally related to dispositional and situational goal preferences in achievement situations (Payne, Youngcourt, & Beaubien, 2007).

Individuals with high learning goal orientation focus on increasing their learning or task competence, seeking challenges, and persisting in the case of failure (Dweck & Leggett, 1988). In contrast, individuals with high performance goal orientation are interested in demonstrating task competence through gaining positive and avoiding negative judgments of competence. The performance-oriented individuals tend to avoid challenges, decrease their effort and persistence following failure, and fear neg-ative evaluation by others (Button et al., 1996). Performance goal orientation was later dichotomized into performance approach and performance avoidance goal orientation (VandeWalle, 1997). Although this conceptualization is interesting for the nomologi-cal studies of goal orientation, for the current purpose the distinction between learning and performance goal orientation is sufficient. Performance goals, be they approach or avoidance, are rooted in fixed perceptions of ability. Consequently, performance avoidance and approach individuals tend to assess their performance through norma-tive comparisons and may not set challenging goals (VandeWalle, 1997). This entity perception of ability and relying on normative comparisons is the key distinction between learning and performance goal orientations.

Performance goal orientation is essentially manifested in a shortsighted effort to “look good” to others (VandeWalle, 2001). Therefore, it can be surmised that goal orientation indicates whether an individual is interested in long-term success and




development or short-term attainment of an objective. Performance goal-oriented individuals select a task they know can be accomplished using what they know, because they tend to believe their skills are fixed, and are discouraged by mistakes and failure (VandeWalle, 2001). These individuals may not persevere when obstacles arise and will avoid challenging tasks. Because being discouraged by failure and criticism may curb development and lead to subpar performance, performance goal orientation may lead to goal abandonment and downward adjustment of goal difficulty.

Learning goal orientation, on the other hand, affects achievement situations differ-ently. Individuals with learning goal orientation are focused on developing new skills, attempting to understand new skills, and successfully achieving self-referenced stan-dards for mastery (Ford, Weissbein, Smith, Salas, & Gully, 1998). They prefer chal-lenging tasks, and therefore may aspire to achieve more than their counterparts with performance goals do. They believe that their efforts lead to success and exhibit greater persistence in the face of difficulties. In uncertain and new situations, learning goal orientation may help individuals deal with obstacles and view errors as learning oppor-tunities. In addition, learning-oriented individuals view negative feedback as useful information that can help facilitate skill development (Arenas et al., 2006; Ford et al., 1998). The differences in the feedback-seeking behaviors that result from different goal orientations are key to the propositions we are making in this article.

Current literature suggests that assessment of ability and task characteristics may influence goal orientation. Dweck (1986) and Vandewalle (1997) conceptualized goal orientation as a relatively stable trait-like construct. However, some studies induced learning and performance goals, thus showing that goal orientation may also be seen as a state (Kozlowski et al., 2001; Martocchio, 1994; Stevens & Gist, 1997; Van Hooft & Noordzij, 2009). The possibility of inducement of a particular goal orientation makes it an important variable in the job search context and many other HRD-related contexts that involve learning, relearning, and adapting to new circumstances. Unlike traits that are relatively stable and difficult to alter, self-regulatory mechanisms like goal orientation can be changed through interventions, which means they can be advantageous in job search training contexts. This also means that HRD and career development professionals are well positioned to affect the state goal orientation in achievement contexts, specifically in job search. Elements of training design, training delivery, approach to goal setting, and designing supportive environments within employment agencies are fruitful avenues to influence the state goal orientations, per-haps maladaptive responses triggered by trait goal orientations. In the next section we will examine current research on the role of goal orientation in job search.

Goal Orientation and Job Search

Earlier in this paper, we mentioned Kanfer’s (1990) assertion that job search is a dynamic, self-regulatory process, akin to performance in an uncertain, autonomous job task. As such, both goal orientations play an important role in this process. Van Hooft and Noordzij (2009) suggest that job search consists of a deliberative phase dur-ing which individuals process information available to them and a behavioral phase




during which the job seekers act on their intentions and attempt to achieve the goal. The deliberative phase is an intentional phase and mirrors the goal-setting phase pro-posed by Carver and Scheier (1998) and discussed above. This phase ends in the for-mation of state goal orientation, which in turn guides the behavior job seekers engage in during the process of a search for a job. This is also congruent with the theorizing by Kozlowski and Bell (2006) that contextual factors at the goal-setting phase or dur-ing task initiation create performance versus learning goal content and thus induce goal orientation states. The goal-operating phase proposed by Carver and Scheier (1998) parallels the behavioral phase discussed by Van Hooft and Noordzij (2009). Given that goal orientation is a motivational construct (Payne et al., 2007), the way in which goals are constructed with the goal orientation are those that define direction, level, and intensity of effort. This means that the behavioral phase, which comes after the deliberative phase, will be to some extent determined by the decisions made in the deliberative phase.

If an individual adopts learning goal orientation, particular behaviors may be likely, such as feedback and advice seeking, persistent attempts at solving problems, and use of various strategies. At the same time, other behaviors are less likely to occur, such as challenge avoidance and withdrawal after negative feedback (Elliott & Dweck, 1988). We also know that learning goal- and performance goal-oriented individuals select and set goals of varied difficulty (Elliott & Dweck, 1988). This means that in a job search situation, performance goal-oriented individuals may set goals of lower difficulty and lower standards for themselves. This could translate into sending out fewer resumes, making fewer contacts, or not applying to positions similar to the ones from which an individual gets rejected. These behaviors suggest lower intensity of job search and, as discussed above, lower intensity of job search behaviors leads to lower likelihood of finding a job. Therefore, performance goal-oriented individuals may be at a disadvan-tage in their job search efforts.

Lower intensity of job search may also stem from the perceptions of ability as fixed and viewing the need to increase effort as an indicator of low ability (Dweck & Leggett, 1988). Performance-oriented individuals perceive that their failures are the results of their low ability and an increase in effort will not lead to an improved per-formance. Therefore, any failure in the job search process, like a rejection letter, lack of interviews, or absence of a callback, is predictive of future failures to such individu-als. Because performance-oriented individuals attempt to avoid failures and only engage in tasks that help them display their competence to others, they may limit their job search activities, thus reducing their chances of getting an interview and eventually finding a new place of employment.

Van Hooft and Noordzij (2009) posit that the difficulty and independent nature of the job search process calls for an individual that sets challenging goals and persists at achieving these goals. Therefore, learning goal orientation and learning goal orienta-tion training may increase the job search intensity, thereby increasing the likelihood of finding a job. Because learning goal-oriented individuals attribute failure to effort, any setbacks in the job search process are attributed to low effort. The effort is then increased by analyzing and changing job search strategies (Van Hooft & Noordzij,




2009). This means that learning goal-oriented individuals may engage in a variety of job search behaviors, and adjust these behaviors if some of the behaviors or strategies are not effective. For example, after sending out resumes and not getting callbacks, learning goal-oriented individuals may expand their efforts by going to job fairs, call-ing people they know, and participating in job search educational programs.

Much of the research that examined the influences of goal orientation on important vocational, educational, and life outcomes focused on trait goal orientation (Chiaburu & Marinova, 2005; Dweck & Leggett, 1988; Vandewalle, 1997). In older studies of goal orientation, it was suggested that trait goal orientation is a trait-like construct but if a situation offers strong contextual cues about rewards, competition, effort, and evaluation standards, such cues may influence goal orientation (VandeWalle & Cummings, 1997). Van Hooft and Noordzij (2009) induced stage goal orientation while controlling for trait goal orientation. In their study, they found that a workshop that helped job seekers set learning goals resulted in higher reemployment probabili-ties and higher intentions to engage in job seeking than a workshop on setting perfor-mance goals. This finding has important implications for job search in general and for the argument that the authors of this article are developing.

Feedback Seeking

The way in which people seek and process feedback is very important in most HRD contexts. For example, seeking feedback is critical in developing emotional intelli-gence and interpersonal competence (Ashford et al., 2003). It is also instrumental in skill development, career exploration, and error identification (Russ-Eft, 2002).

Helping job seekers set learning goals rather than performance goals may reduce their focus on normative comparisons. The difference between an intrapersonal stan-dard and a normative standard may have serious implications in the job search process. People who make normative comparisons and want to avoid tasks that may expose their perceived low ability to others may refrain from important job-seeking behaviors like feedback seeking. Ashford (1989) suggested that people evaluate the costs of feedback-seeking behaviors and among these costs are ego and self-presentation costs. Negative feedback may increase perceived ego costs. Performance goal-oriented indi-viduals may refrain from seeking feedback because they may perceive the ego costs and self-presentation costs to be very high as they consider negative feedback and exposing their need for help to be an evaluation of their level of ability (VandeWalle & Cummings, 1997).

Research showed that the people differ in their motives for seeking feedback. Some individuals seek feedback to boost their ego or maintain self-image, others seek feed-back for instrumental reasons—to improve their performance (Ashford et al., 2003). In job search, feedback seeking is often an important part of the process. Job seekers who seek feedback with instrumental motives may benefit significantly from asking for feedback on their resumes and cover letters, soliciting feedback from others on their interviewing abilities and even asking for feedback from job interviewers to obtain information about the skills and experience they may be missing.




If the motive for such feedback-seeking behavior is ego boosting or image mainte-nance (Ashford et al., 2003) learning is not likely to occur. In addition, normative comparisons often expose ability and skill discrepancies between self and others, which also presents a threat to ones ego. An individual who is concerned with preserv-ing one’s image and boosting one’s ego is unlikely to reach out to others, due to the fear of exposing one’s weaknesses. Given that normative comparisons are often made by performance goal-oriented individuals, by definition, any discrepancy between self and others is attributed to lack of ability rather than effort. This may result in learning being perceived as exerting futile effort for reducing the discrepancy.

To extend the notion of feedback seeking further, similar mechanisms may operate in situations that require interaction with others in the job seekers’ network or outside of it. Many parts of the job search process, including job fairs, job search education programs, and reaching out to acquaintances to inquire about openings, may have similar ego and self-presentation costs and may be perceived by the job seeker as opportunities to expose a weakness or low ability to others. It can be concluded from the above discussion that performance goal orientation may lead to two debilitating factors in the job search—lower likelihood of feedback seeking, and therefore less SDL.

While the influence of trait goal orientation on job search intensity has been shown in several, albeit limited number of studies (e.g. Creed, King, Hood, & McKenzie, 2009; Van Hooft & Noordzij, 2009), the link between goal orientations, and feedback seeking and networking in job search has not been established. In fact, as stated earlier, we do not know why some people network more than others during the job search. However, an even more interesting link that is missing in the literature is between the state goal orientation and these variables. Kozlowski and Bell (2006) discussed how goal content, which is manifested in situational cues that either signal focus on mas-tery or performance, leads to inducing learning versus performance goal orientations. Research has also shown that setting performance goals where learning is required may not be the best strategy (Seijts & Latham, 2001). It is natural for job seekers to be focused on finding a job as soon as possible, which is in essence a performance goal. Many employment agencies may promise and focus on the same outcome, which is naturally in their best interest. Although counter intuitive, the focus on finding a job may not only be the down fall of the job seeker but the agency themselves, as their funding is heavily reliant on the satisfaction of their clients. However this does not necessarily address the long-term problem discussed at the outset, which is the prob-lem of long-term unemployment and discouraged workers, possibly caused by the gap the skills employers require and job seekers possess. Besides, during long-term unem-ployment, even high-skilled employees may experience skill atrophy, which may also require relearning and networking to keep up-to-date on what is required in the labor market (Kim & Polachek, 1994).

The value of social resource in the job process may seem apparent. But we only have a surface-level understanding of the impact of trait and state goal orientations on the networking behaviors, unless we consider social resource theory, and weak tie theory. Research suggests that many jobs are often found through some sort of




networking, which includes contacting friends, acquaintances, and family (Granovetter, 1995; Schwab, Rynes, & Aldag, 1987). In addition, there is extensive research that investigated the value of networking in industries where positions are not typically advertised in the media, and in employment among graduating college students. In both cases, the findings suggest that networking is an effective informal method of job search (Meyer & Shadle, 1994; Stevens, Tirnauer, & Turban, 1997). But not all ties in one’s network are equally instrumental in the job search, and the relationship between self-regulatory variables we have discussed so far may differ for different types of connections. To fully understand the implications of social networks for the job search process, it is instructive to review some research in this area.

A Social Network Theory Approach to Job Search

Research has suggested that an individual’s network is critical to social mobility (Dominguez & Watkins, 2003; Erickson, 1996; Lin, 2001; Stanton-Salazar & Dombusch, 1995). More specifically, individuals with higher levels of social capital have access to social resources that can be utilized to achieve a desired objective, such as searching for a job (Burt, 2001; Flap & Boxman, 2001; Lin, 2001). As a result, those people who possess effective networking skills may experience a more favorable social position within their network and consequently have a greater exposure to job related information (Blau, 1993; Brass, 1984; Lin, 2001; Mehra, Kilduff, & Brass, 2001; Pfeffer, 1991). The social position determines the potential benefits the indi-vidual may receive from their network. These benefits can be viewed as the ability to access social capital, where certain structural attributes (e.g., centrality, structural holes, strength of ties) lead to resources that will help achieve the desired objective. Therefore, an individual’s social position within a network may help to determine the utility of the network itself.

The term network typically refers to a set of objects or nodes and the mapping of the interaction and relationships between the objects (Parker, Cross, &Walsh, 2001; Wasserman & Faust, 1994). Social network theory refers to the objects as people or groups of people. By measuring the interactivity of individuals through mapping rela-tionships, researchers can uncover the dynamics that exist between and within groups.

Social capital is one example of why social network theory is studied. By under-standing the mappings connecting individuals to a set of others, we stand to learn much about how individuals use their connections to achieve desired outcomes (Coleman, 1988). From a job search perspective, actors within the network can improve behaviors or gain access to job-related information based on the connections they possess. In addition, the level of social capital helps to determine how individuals use their position within a network to accumulate power in social settings. The process in which social network theories were tested and validated involved the empirical rigor of social network analysis.

Some of the formal theoretical properties in the network perspective include central-ity (betweenness, closeness, and degree), position (structural), strength of ties (strong or weak, weighted or discrete), cohesion (groups, cliques), and division (structural holes,




partition; Scott, 2000; Wasserman & Faust, 1994). These represent the building blocks for developing and conceptualizing network theory (White, 1997).

A social network theory approach to conducting a job search (Auslander & Litwin, 1988, 1991; Specht, 1986) suggests that social networks establish norms for behavior within a group, including accelerated job-search activity. Social networks may provide information and opportunity that are relevant to becoming re-employed by supplying additional contacts

One approach to conceptualizing social capital is weak tie theory (Granovetter, 1973). In essence, the weak tie theory focuses on the characteristics of the ties between actors. The strength of weak ties theory demonstrated that job opportunities for mid-level managers were most likely to come from an individual’s weak ties versus the strong connections in their network. Strong ties consisted of close relationships (family, coworkers, close friends) that provided information that was widely shared and became quickly redundant within the clique. Granovetter (1973) viewed weak ties as a connec-tion to densely knit networks outside the individual’s direct contacts that could provide nonredundant information. It was more likely that weak ties rather than strong ties would provide a greater opportunity for new information about job leads.

On the basis of this conceptualization, examining the job seekers’ social network will help to reveal the ties an individual possesses and how they affect their job search. Those individuals that seek support from their weak tie connections are not only more likely to receive nonredundant job-related information but also to gain access to job opportunities not found in traditional sources (Yakubovich, 2005). In the job search context, weak ties could be acquaintances, contacts of close friends, recruiters, inter-viewers, and others with whom the job seeker does not interact regularly. If barriers to connecting with weak ties exist, the transition back into the labor market may be delayed. This delay can have severe implications for self-efficacy and other self-regulatory mechanisms, which, in turn, may restrict one’s ability to affectively con-duct the job search (Fort, Jacquet, & Leroy, 2011).

Goal Orientation as a Barrier

In view of the discussion of the weak ties and their instrumentality in achievement situation, it is important to consider goal orientation and goal content as a barrier to connecting with weak ties. For example, performance goal trait and state imply that individuals are unlikely to seek feedback with instrumental motives, because that would suggest they perceive that ability is malleable. Performance goal-oriented indi-viduals are by definition entity theorists and therefore seek feedback with the motives to boost ego or preserve image. Based on a conceptualization by Ashford et al. (2003), people seek feedback either by direct inquiry or by monitoring. Monitoring would be equivalent to assessing ones progress toward the goal using normative comparisons. This implies that job seekers with trait or state performance goals may monitor their progress without directly reaching out to their social resources. This effect may be attenuated by the nature of the social resources people have at their disposal. It is pos-sible that in a job search situation, a person would ask one’s close contacts, or strong




ties, for help, regardless of the goal orientation, or even goal content. But, given the weak tie theory, such contacts may not be able to provide one with the resources needed to learn new job skills or find job leads.

Given the distinction between weak ties and strong ties, we can further elaborate on the effects of trait and state goal orientation on feedback seeking and networking in the job search process. The first important distinction can be observed in the goal-operating phase and can be found in the motives for seeking feedback. Job seekers with perfor-mance goal orientation may seek feedback with ego-boosting and image-preserving motives. Exposing one’s status of unemployment may be perceived as equivalent to exposing one’s shortcomings, like lack of skills and ability. Exposing these shortcom-ings to those outside one’s immediate network may be perceived as a serious threat to one’s ego. Therefore, a performance goal-oriented job seeker would rather limit the networking and feedback-seeking behaviors to his or her closest contacts. In other words, such individual may not seek feedback from employers on interview results and performance; refrain from asking others to review and edit one’s resume—to not expose one’s perceived skill level and achievements to others; and avoid calling on acquaintances to inform them about a need for a new place of employment. All these situations may have high ego costs and may be threatening to performance goal-ori-ented individuals who are concerned about preserving their image and exposing low ability to others. Such limit may restrict one’s access not only to job leads, but also to objective assessment of one’s marketable skills, and therefore learning needs.

The second important distinction is apparent on examining the goal-monitoring phase in the self-regulation process. The goal-monitoring phase takes place after indi-viduals have already set the goals and engaged in some strategies to achieve the goal (Carver & Scheier, 1998). At this point, they can examine their progress based on two criteria—distance from the goal and the rate with which the distance is decreasing. These two criteria are known as action loop and meta loop, respectively (Carver & Scheier, 1998). Carver and Scheier (2012) also suggest that one key response to the assessment of the action and meta loops is affect. Specifically, if the distance between the current and desired state is relatively small, and if the rate with which this distance is reducing is satisfactory, positive affect is experienced. If the assessment of both loops is unsatisfactory, dejection or agitation emotions may ensue.

Burnette et al. (2012) suggest that implicit theories affect the way people process the assessment of the loops during the goal-monitoring phase. They posit that people with entity beliefs of ability, who find that the rate at which they progress toward the goal is too slow, may attribute this to the lack of ability, experience dejection, and withdraw from the activity. Conversely, people with incremental beliefs of ability may attribute this to the lack of effort, experience some agitation, but then respond in an increased effort and modification of strategies used to reach the goal. Similar relation-ship can be argued for performance versus learning goal orientation traits and states, because the goal orientation differences are attributed to implicit theories of personal-ity (Dweck & Leggett, 1988).

What does this mean for connecting with one’s weak ties? Reaching out to people who are not in the immediate network may be another source for information that




represents objective assessment of the distance from the goal and the rate of closing that distance. Given that such information may be a cause of negative affect, perfor-mance goal-oriented individuals may avoid situations that cause emotions of dejec-tion. Because any negative feedback is perceived as assessment of one’s fixed ability, and perceptions of low ability lead to dejection, which in turn leads to with-drawal and other self-defeating strategies, performance goal-oriented individuals may withdraw from job search activities before they can gain any benefits from their social resources.

A Conceptual Model of Goal Orientation, Social Networks, and Job Search

In view of the discussion of self-regulatory mechanisms, social networks, and job search research, it is clear that networking behaviors and goal orientation are impor-tant concepts to consider. Whereas research has examined the individual influences of goal orientation and networking behaviors on job search success (Van Hooft & Noordzij, 2009; Wanberg, Kanfer, & Banas, 2000), we found no studies that examined the interaction of these variables. In addition, the studies that looked at predictors of networking behaviors studied stable individual characteristics like extraversion that have a high genetic component and attitudinal variables like networking comfort (Wanberget al., 2000). Such variables, albeit informative, offer only limited help in designing an intervention to increase job search success, because traits are stable and attitudes may not influence all three motivational decisions about exerting effort, set-ting a level of effort, and persisting at that level of effort.

State goal orientations and their effect on feedback seeking presents a practitioner and researcher with an opportunity to influence the way job seekers navigate the job search without the obstacles presented by stable traits. While much of the early research focused on trait goal orientation, recent findings show that state goal orienta-tion is an important factor in an achievement situation (Kozlowski & Bell, 2006). The research on the effects of state goal orientation on trait goal orientation is still limited. But the effectiveness of the goal content interventions in experimental studies dis-cussed earlier suggests that HRD and career development practitioners can influence goal content, and therefore possibly self-regulatory behaviors during the job search process.

What emerges is a conceptual framework that may help explain two important phenomena in the job search—SDL and networking. This framework encompasses trait goal orientations, goal content, which induces state goal orientation, types of network ties, and feedback-seeking motives. All these variables are nested within the larger self-regulatory process of goal setting, goal operating, and goal monitor-ing, while accounting for the source of trait goal orientation. The model is presented in Figure 2.

The model we present here combines several unanswered research questions in self-regulation and job search research. First, it combines trait and state goal orien-tations in a specific self-regulatory context. The trait goal orientation is considered




only as a moderator. Examining this empirically may help establish how stable trait goal orientation is and whether it can be suppressed by induced goal content. While preliminary findings show that goal content affects persistence on the difficult tasks beyond the effects of trait goal orientation (Martocchio, 1994), more research is needed in this area. Second, it combines goal orientation, state, and trait, to explain feedback-seeking behaviors. Ashford et al. (2003) in their latest review on feedback seeking, suggest that goal orientation is a prime candidate for explaining differ-ences in feedback-seeking behaviors and that this relationship requires more empir-ical research. Third, it provides a theoretical explanation for differences in networking behaviors during job search, through the perspective of weak tie theory and social resources theory. Empirically testing the relationships discussed here may help explain why some individuals network more than others, and how to develop social networking skills that help individuals make the most of their social resources.

Suggestions for Research in HRD

Based on the model presented above we offer specific research questions that lend themselves well to empirical research. The first direction is to examine whether there are differences in the number and frequency of weak tie contacts among long-term job seekers based on their differences in goal orientation. This can be accomplished through either longitudinal designs or cross-sectional designs. For instance, social net-works analysis data collection techniques allow us to determine social networking behaviors using instruments called name generators (van Duijn & Vermunt, 2006). These tools ask individuals to list people with whom they interact for a particular pur-pose and with a specified regularity. The differences in responses can then be exam-ined as functions of trait goal orientations.

The authors of this study have already begun examining this question. The findings of this study have been accepted to and will be presented at the upcoming UFHRD conference, in Brighton, England, in 2013. One of the interesting findings was that higher learning goal orientation scores are associated with more weak ties. However, as the performance goal orientation score increased the number of weak ties also

Figure 2. Proposed model of self-regulation and social networking behaviors.




increased, albeit at a lower rate than for learning goal orientation scores. This finding is consistent with the mixed findings in the goal orientation research. Many conflicting findings do not allow us to draw conclusions about the importance of learning versus performance goal orientation in achievement situations, because often both lead to positive outcomes (Burnette et al., 2012).

One important criterion that often makes learning goal orientation more favorable in achievement situations than performance goal orientation is its effect on learning-related behaviors. As we argued earlier in this article, learning, and especially SDL, is required in the job search, and using social resources in this context may be instru-mental to learning. It is logical, therefore, that learning goal orientation should lead to more networking outside of one’s comfort zone, which may gradually build social self-efficacy. However, more studies are needed to establish this connection. An addi-tional approach that fits within this direction would be to study discouraged workers rather than just long-term unemployed. Discouraged workers were discussed in the beginning of this article and it would be interesting to assess the implicit beliefs, goal orientations, and networking behaviors of this group. For example, if the discouraged workers differ in implicit beliefs (entity vs. incremental) and in scores on perfor-mance and learning goal orientations, other variables need to be identified to explain their perceptions of the job market. One such variable is self-efficacy. Addressing discouragement and disillusionment from long-term unemployment involves devel-oping self-efficacy beliefs in one’s ability to overcome obstacles in the job search process. According to Bandura (1997), one of the ways self-efficacy beliefs are developed is through mastery experiences. This means that as a job seeker sets learn-ing goals and achieves small successes, his or her self-efficacy will improve, which in turn will facilitate setting higher learning goals and making progress toward employment.

The second important direction for research is to determine the effects of inducing goal orientation in the goal-setting and throughout the goal-operating stage of the job search. Studies show that goal content can be manipulated (Kozlowski & Bell, 2006). However, it is not clear how long these effects last. Job search is a long process and it is critical that the individuals do not revert to self-defeating strategies, normative com-parisons, and increased and persistent negative affect. The goals that career develop-ment practitioners and employment agency trainers set for job seekers may either induce performance or learning goals. Experimental designs may be used within the agencies to determine which conditions result in higher job search intensity, while specifically focusing on networking as one of the job search strategies. It is possible to track how often job seekers from either condition reach out to their contacts and what sort of contacts those are (weak or strong).

A third direction is to determine whether inducing goal orientation actually sup-presses trait goal orientation. Measuring trait goal orientations prior to inducing the goal content may show whether state is affected by trait or vice versa. This will also help disentangle the relative effects of trait versus state on feedback-seeking behav-iors. Given Ashford et al. (2003) statement that goal orientation should be examined as a factor that affects differences in feedback seeking, this research direction will not




only fill this gap but also expand the knowledge by considering state and trait goal orientation.

Finally, the model we proposed can be applied outside of the job search context. Feedback seeking and networking are important in many situations in the work set-ting and outside of the occupational domain. Feedback seeking is a critical variable for learning and development. While research has examined feedback seeking in lower level jobs, one area that remains unexplored is feedback seeking among mana-gerial employees. Ashford et al. (2003) discuss the phenomenon called “CEO dis-ease.” The role of senior managers often comes with little structure, a lot of ambiguity and a lot of autonomy. In some way this is very similar to a job search process. It has been shown that high-level executives do not like to seek feedback, and this often comes with high costs in terms of leader’s ability to detect errors (Morrison & Milliken, 2000). The model we present in this article can be used to explain differ-ences in feedback-seeking behaviors among leaders and whether inducing learning goal content leads to fewer errors in leader decisions. It would seem that leader per-formance criteria by definition create performance goal content and thus induce per-formance goal orientation. A question then becomes is learning goal content even possible in that level of the job? Of course, if it is not, then learning is not valuable for performance in high-level jobs; in other words, learning should have occurred prior to assuming leadership position and at this point a leader has to have skills nec-essary to perform. We believe that this assumption is not realistic, especially in the current business environment, where people and organizations find themselves con-stantly adapting to changing circumstances. Therefore testing the paths in the model proposed here presents opportunities to address many questions in HRD, related to career development and job search, leader behaviors, individual learning, and social networking behaviors.

Implications for Practice and Role of HRD

It is natural to focus on finding the job as quickly as possible and, as we said earlier, employment agencies try to help job seekers do just that. However, such an approach may induce performance goal orientation. In that case setbacks may be felt much more acutely and individuals may eventually withdraw from the process because the under-lying reason they are not successful in the job search is not addressed. Many discour-aged workers do not have the skills required in the market today and by focusing on the outcome of getting a job as soon as possible does not allow time and opportunity to identify what skills are missing.

We suggest that creating learning goal content in the early stages of job search may lead to more favorable outcomes in terms of learning, feedback seeking, and network-ing. Career development practitioners can design workshops for new job seekers that incorporate elements to induce learning goals. In addition, interventions could be set up at regular intervals during the job search that allow us to assess the progress toward goals, process negative feedback, set further learning goals, and choose new strategies for goal operating.




The first workshop would focus the job seeker on helpful job search behaviors like resume writing and looking for job leads, and also reduce the focus on competitive nature of the process, thereby increasing the chances that job seekers will focus on own skill development. In other words, this would help deal with perceptions of fixed ability and helplessness, define steps to learn what is necessary and emphasize the importance of networking, especially outside of one’s immediate network. For exam-ple, some defining characteristics of this workshop would be the explanation of the nature of one’s ability and skills and how they can be increased by targeting other jobs that allow them to develop these skills versus the job they may have been originally seeking; the discussion and practice of feedback seeking and how to process negative feedback; learning the approaches to manage negative affect; examining their network and identifying individuals that may support goal attainment; and working out a large number of strategies to achieve the goal. In subsequent interventions career develop-ment practitioners could work through specific issues encountered at goal-operating stages and goal-monitoring stages. It is very important to manage the extent to which normative comparisons are used as a source for feedback at these stages. Reducing reliance on this source of feedback will encourage continuous learning, help individu-als to interpret the setbacks in less damaging ways, and reduce dejection-related emotions.

If job seekers are taught to set proper goals, they may become more persistent in job search and cope better with the setbacks during the process, view their social network as a source of feedback and assistance, and in general be more successful in achieve-ment situations, such as a job search. Learning goal-oriented individuals may not only seek feedback from their contacts more often than performance goal-oriented indi-viduals but may also reach out to their weak ties more frequently. Setting learning goals may lead to a more structured approach to job search and may increase one’s chances to learn new marketable skills. Simple training interventions may help reduce not only the time it takes to find a job, but also the pool of unemployed. Such work-shops conducted with discouraged workers could reduce the number of people who are marginally attached to the workforce, increase their skills by encouraging SDL, and increase their social resources.

HRD should play a prominent role in addressing the fallout of the economic crisis, specifically unemployment. Job search is inextricably tied to the learning and develop-ment of an individual. As such, it provides fertile ground for HRD research and prac-tice. The cross-disciplinary nature of HRD offers an exceptional opportunity to address this situation by focusing on intervention design, goal setting, and inner workings of social networks. In addition, the research and practice of adult learning will help inform the design of training programs for job seekers that would focus on job search techniques and mastery of new skills required by the workforce of the 21st century.

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 publication of this article.

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Author Biographies

Bogdan Yamkovenko is an assistant professor at the Rochester Institute of Technology within the Human Resource Development program and an adjunct professor at the Chicago School of Professional Psychology, IO program. His academic research focuses on self-regulation, goal orientations, and their effects of performance in complex tasks.

John Paul Hatala is a Professor at George Brown College within the Career and Work Counesllor program, a senior research fellow at the University of Ottawa and an adjunct at the Louisiana State University. His academic research focuses on job search, career development, social networking behaviors, social capital in the workplace, human resource development, and learning transfer.

http://eclectic.ss.uci.edu/~drwhite/netsyl96.htm

feedback seeking and social networking during job search

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