Self-Guided Development: A proactive approach to employee development
DISSERTATION
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University
By
Alison McConnell Dachner, B.S., M.B.A
Graduate Program in Labor and Human Resources
The Ohio State University
2013
Dissertation Committee:
Jill E. Ellingson, Advisor
Raymond A. Noe
Howard J. Klein
Copyrighted by
Alison McConnell Dachner
2013
Abstract
The effectiveness of formal training and development initiatives are becoming more difficult to realize in response to more dynamic and decentralized work environments. Organizations are increasingly relying on employee initiatives to react to rapid changes at work. The current prevalence of informal learning and development in practice emphasizes the need to further explore this phenomenon. To that effect, this dissertation defines self-guided development as a set of knowledge, skill or relationship building learning activities that generate human capital, but are unstructured, voluntary and not administratively or operationally provided by the organization. Self-guided development offers a flexible and efficient method for building human capital in today's work environment.
This dissertation has two objectives. First, to embed self-guided development within the development literature as in important type of proactive behavior. Second, to define self-guided development and begin to establish its nomological network. Self- guided development should be influenced by both individual differences (e.g., proactive personality) and contextual variables (e.g., autonomy and training climate). In addition, these individual differences and contextual variables should interact such that employee's who possess traits that are likely to result in self-guided development are most likely to actually engage in self-guided development if the work environment and job support
ii expression of those traits. Self-guided development should lead to valuable firm outcomes such as higher performance and knowledge sharing. This effect should be enhanced if employees experience positive exchange relationships at work with their organization, supervisor and coworkers.
Field data was collected by surveying 103 employees at two times to examine the nature of self-guided development and test the hypotheses in this dissertation. Sixty-nine employees had data for both surveys that could be matched. Self-guided development was measured using 32 behaviors that met the criteria for being considered self-guided development. Content adequacy results supported the use of the 32 items. Results show that self-guided development was prevalent among employees. In fact, of the 32 self- guided development behaviors identified for this research, every single one was used to some extent by employees. Simple and hierarchical regression was used to test the hypothesized relationships. Both individual differences and contextual variables were found to influence engagement in self-guided development. Proactive personality and training climate each had a positive, significant relationship with self-guided development. However, there was not enough power to detect significant results for most of the other hypothesized relationships.
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Dedication
This dissertation is dedicated to Joel and Liesel who make me happier than I could have ever imagined, as well as to my parents who have always emphasized the importance of
hard work and education.
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Acknowledgments
This dissertation would not have evolved without the time and effort that Jill
Ellingson, Raymond Noe, and Howard Klein dedicated to me and this research. They have been instrumental in developing my skills as a researcher, writer, and teacher.
Their patience and support is truly admirable and has given me confidence in my ability as an academic. Each of these members of my dissertation committee have provided me with opportunities that have exceeded all expectations. For these reasons, I am forever grateful to each one of them.
The National Center for the Middle Market in the Fisher College of Business at the Ohio State University funded this research. The Center also connected me with the organization where data was collected and used as the sample in this dissertation.
Beth Polin, Brian Saxton, Willie Stormeyer, and Erin Makarius have provided more support and encouragement than I deserve during this dissertation process. Their willingness to listen to ideas and ability to assist when I hit a roadblock has never gone unnoticed. More importantly is their friendship that I can only strive to reciprocate to a similar degree.
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Vita
2000 ...... Charles F. Brush High School
2004 ...... B.S. Human Resources, The Ohio State University
2008 ...... M.B.A., Cleveland State University
2008-present ...... Graduate Research Assistance, The Ohio State University
Publications
Dachner, A.M., Saxton, B.M., & Noe, R.A. (Forthcoming) To Infinity and Beyond: Training teams for unknown and dynamic situations using a narrative approach, an example from NASA. Human Resource Development Quarterly.
Noe, R.A., Dachner, A.M., & Saxton, B.M. (2011). Team Training for Long-duration Missions in Isolated and Confined Environments: A Literature Review, an Operational Assessment, and Recommendations for Practice and Research. NASA/TM-2011-216162.
Noe, R.A., Tews, M.J. & Dachner, A.M. (2010). Learner engagement: A new perspective for enhancing our understanding of learner motivation and workplace learning. Academy of Management Annals, 4, 279 -315.
Fields of Study
Major Field: Labor and Human Resouces
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Table of Contents
Abstract ...... ii
Dedication ...... iv
Acknowledgments...... v
Vita ...... vi
List of Tables ...... xi
List of Figures ...... xii
Chapter 1: The Importance of Self-Guided Development ...... 1
Chapter 2: Defining Self-Guided Development ...... 9
Literature Review ...... 9
Employee Development prior to the 1990s ...... 9
Employee Development during the 1990s ...... 12
Employee Development in the 2000s ...... 15
The Value of Introducing Self-guided Development ...... 20
Self-Guided Development Defined ...... 22
Chapter 3: Nomological Network for Self-Guided Development ...... 27
Antecedents of Self-Guided Development ...... 27 vii
An Interactional Approach ...... 28
Proactive Personality and Self-Guided Development ...... 29
Job Autonomy and Self-Guided Development ...... 31
The Interaction between Proactive Personality and Job Autonomy ...... 32
Training Climate and Self-Guided Development ...... 34
The Interaction between Proactive Personality and Training Climate ...... 35
Outcomes of Self-Guided Development ...... 37
Self-Guided Development and Task Performance ...... 39
The Interaction between Self-Guided Development and Perceived Supervisor
Support...... 41
The Interaction between Self-Guided Development and Organization Commitment
...... 43
Self-Guided Development and Knowledge Sharing ...... 44
The Interaction between Self-Guided Development and High-Quality Relationships
...... 45
The Interaction between Self-Guided Development and Task Interdependence ...... 47
Chapter 4: Methodology ...... 49
Sample ...... 49
Study Procedures ...... 50
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Scale Development Procedure ...... 52
Measures ...... 55
Chapter 5: Analysis and Results ...... 60
The Nature and Occurrence of Self-Guided Development ...... 60
Descriptive Statistics ...... 63
Hypothesis Testing ...... 65
Antecedents of Self-Guided Development ...... 67
Results for Main Effects ...... 67
Results for the Interaction Effects ...... 69
Outcomes of Self-Guided Development ...... 70
Results for Main Effects ...... 70
Results for Interaction Effects ...... 71
Chapter 6: Discussion and Conclusion ...... 73
Discussion ...... 73
Conclusion ...... 75
Theoretical Implications ...... 75
Practical Implications ...... 77
Limitations ...... 78
Future Research ...... 81
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References ...... 84
Appendix A: Content Adequacy Results ...... 109
Appendix B: Self-Guided Development Scale Instructions and Items ...... 112
Appendix C: Survey Items ...... 115
Appendix D: Self-Guided Development Behaviors in Rank Order by Highest Mean
Value ...... 117
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List of Tables
Table 1. A comparison of data for respondents and non-respondents of Survey 1 ...... 51
Table 2. Self-guided development scale items ...... 54
Table 3. Study variable means, standard deviations, and zero-order correlations ...... 64
Table 4. Main effect antecedents of self-guided development ...... 68
Table 5. Interaction effect antecedents of self-guided development ...... 70
Table 6. Main effect of self-guided development on performance and knowledge sharing
...... 71
Table 7. Hypothesized moderated effects on performance ...... 72
Table 8. Hypothesized moderated effects on knowledge sharing ...... 72
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List of Figures
Figure 1. Self-guided development within the traditional development literature ...... 24
Figure 2. Proposed Nomological Network for Self-Guided Development ...... 28
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Chapter 1: The Importance of Self-Guided Development
Most organizations invest in training and development programs as part of a human resource (HR) strategy. The goal of such HR practices is often to gain a competitive advantage by generating human capital, an employee's knowledge, skills and abilities that enhance his/her productivity (Becker, 1964). Traditionally, the focus in research and in practice on enhancing human capital has been on creating and utilizing formal training and development activities, such as classroom instruction, on-line courses, college classes, and mentorship programs. Most employee training programs are systematically designed with specific goals, learning objectives, assessment instruments, and expectations (Chen & Klimoski, 2007). They are developed by an instructor who is responsible for identifying what should be learned, determining the most appropriate instructional methods, and evaluating the extent to which learning occurred. This type of training is beneficial for organizations, teams, and society (Aguinis & Kraiger, 2009).
Nevertheless, "formal training programs alone are insufficient to ensure organizational and individual readiness" (Tannenbaum, Beard, McNall, & Salas, 2010) for keeping up with the demands of today's complex, dynamic, and fast-paced work environment.
Within this emerging organizational landscape, views about learning are changing.
Knowledge is being created in more non-traditional, innovative, and informal ways. The methods being used are changing and learning is shifting to become largely the
1 responsibility of the learners themselves (Bell & Kozlowski, 2008; Kraiger, 2008). These changes necessitate a new perspective on how employees are trained and developed in organizations.
The need for a new, broader conceptualization of development at work arises from a series of firm- and job-related trends shaping the current workplace. These trends require employees to be resourceful and creative in finding information and solving work problems on their own. One such trend is a shift in job design from steady and routine tasks to more complex, dynamic tasks (Harrison, Johns, & Martocchio, 2000). Time constraints associated with the immediacy of new competency requirements makes traditional training and development difficult, if not impossible for certain tasks in these types of jobs. This dynamic business environment requires that employees take the initiative to refine and add to their skills on their own (Molloy & Noe, 2010). These types of jobs increase the demand for knowledge workers (SHRM, 2012), those individuals who regularly use creative-thinking and problem solving strategies to complete non- routine tasks at work (Reinhardt et al., 2011) and are better able to adapt to the changing nature of the work. Ongoing and just-in-time training is needed to facilitate learning when one’s day-to-day responsibilities change regularly.
A second trend is the flattening of organizational structures (Mohrman, Cohen, &
Mohrman, 1995). Vertical, hierarchical organizational structures have become more horizontal. These flatter organizational structures afford less opportunity for upward mobility. The absence of promotional opportunities suggests that "there is an increased focus on finding alternative ways for employees to develop their careers and continue to
2 learn" (SHRM, 2012). Furthermore, flatter work structures rely on "boundary spanning teams to coordinate work efforts, identify improvements to organization-wide processes, and make strategic decisions" (Marrone, 2010). Thus, there is a shift from more individual tasks to more collective tasks (Harrison, Johns, & Martocchio, 2000). These changes point to a need for more team-focused learning and the need for more creative opportunities for employee career development and growth.
A third trend is the increased use of advanced technology in the workplace.
Employees are expected to learn how to use emerging technologies, making employee development especially important. Technology makes it possible for individuals to complete work 'off site', or telecommute. Employee development activities (e.g., networking and mentoring) are an integral part of successful telecommuting experiences
(Cooper & Kurland, 2002). Working 'off-site' often necessities that telecommuting individuals manage their own career development. Technological advances also provide new methods for developing a workforce that minimize an organization’s reliance on traditional classroom training. Organizations have begun to adopt learning methods that emphasize learner control. Research suggests that the introduction of new technology is a catalyst for informal learning (Tannenbaum et al., 2010). E-learning is becoming increasingly popular as organizations rely on new technologies to advance training design and delivery (Schmidt & Ford, 2003). Paradise and Patel (2009) suggest that approximately 20% of learning occurs on-line; a number which is expected to increase.
Web-based training systems allow the learner to control the method (e.g., read vs. listen vs. watch), timing, and pace of training as well as the amount of practice and feedback
3 that occurs during training (Milheim & Martin, 1991). Further, one of the Top 10 HR trends of 2012, according to SHRM (2012), is the growing influence of social networking. Social networking, and technology in general, provide additional development and information sharing opportunities for employees.
Career movement adds even more complexity to the efficiency of formal training and development practices. Individuals are regularly taking new jobs (i.e., 'job-hopping') that require them to learn new knowledge and skills. According to the Bureau of Labor
Statistics, individuals will have about nine different jobs between the ages of 18 and 32
(Schawbel, 2012). People are not remaining at a job long enough to develop general human capital and advance within an organization. The pressure to perform well within one’s newly-acquired current job requires employees to focus more on firm-specific skills and often leaves them to locate the necessary work-relevant information on their own. This has made it more difficult for employees to develop and mature professionally in their career.
These organizational trends highlight the need to re-envision the way we think about employee development. Continuous learning is now crucial to the success of an organization (SHRM, 2012b). As work continues to be more dynamic and unstructured, companies are increasingly depending on employees' personal initiative to be resourceful and creative in identifying and solving problems (Crant, 2000; Frese, Fay, Hilburger,
Leng, & Tag, 1997). Indeed, the once integral roles of the organization and instructor have diminished with regard to learning and development outcomes (SHRM, 2012).
Research suggests that most learning in organizations occurs informally, through job
4 experiences and work relationships (McCauley, Ruderman, Ohlott & Morrow,1994; Roy,
2010). With an emphasis on lifelong learning, organizations are creating opportunities for employees to develop themselves independent of traditional, mandatory training and development initiatives by offering voluntary development activities, facilitating communities of practice, and accepting errors as a form of learning. In short, employees are becoming more responsible for actively pursuing opportunities to develop themselves professionally (Antonacopoulou, 2000). These trends necessitate that we push beyond thinking about only traditional human capital development behaviors to consider employee initiated development experiences.
As "employees are becoming increasingly responsible for their own career development" (SHRM, 2009), they must become more proactive in developing human capital themselves without organization investment. Proactive behavior refers to an employee's active approach at initiating and creating change to produce more favorable work situations (Griffin, Neal, & Parker, 2007). Proactive behavior reflects an individual actively taking control of his/her situation for the purpose of removing uncertainty and ambiguity (Crant, 2000). Proactive behavior has recently emerged as an important employee action in the organizational behavior literature. For example, job crafting
(Wrzneiwski & Dutton, 2001) suggests that employees can take a proactive, bottom-up approach to job design. Seeking feedback from and networking with others are other proactive behaviors that have been identified as important (De Stobbeleir, Ashford, &
Buyens, 2011; Seibert, Kraimer, & Liden, 2001). Although not yet explicitly positioned as such, proactive behaviors provide beneficial development experiences. This research
5 integrates various proactive behaviors to form self-guided development, a re- conceptualization of our understanding of employee development and a new way to think about how employees learn on the job.
As a set of actionable proactive work behaviors, self-guided development is defined as knowledge, skill, or relationship building learning activities that generate human capital, but are unstructured, voluntary, and not operationally or administratively provided by the organization. Consistent with the literature on proactive work experience, self-guided development requires that employees select, create, and/or identify learning opportunities and take personal initiative to act on those opportunities (Crant, 2000). In contrast to traditional training and development practices, these activities are not required, imposed or provided by the organization.
Self-guided development offers a flexible and efficient method for building human capital in today's work environment. Employees can use self-guided development to obtain help and information, to experience different learning perspectives, to consider alternative ways to think and behave, and make decisions about where to focus their attention (Conlon, 2003). It is through self-guided development that employees will likely uncover implicit job-relevant knowledge that is not explicitly provided by the organization. Rather than focus solely on an expensive training and development infrastructure, organizations can better manage their human capital by leveraging employee self-guided development to supplement their formal training and development practices.
This research seeks to define self-guided development and embed it within the
6 development literature as an important type of proactive behavior. Specifically, this dissertation will provide a foundation for understanding this phenomenon by defining it and establishing its nomological network. Research in training and development has firmly established that individual differences, situational differences, and their interaction influence training motivation and training outcomes. Similar to training and development research, self-guided development is expected to be the product of both individual and situational differences, as well as their interaction. The dispositional tendencies of people with certain traits should position them to engage in self-guided development.
Organizational characteristics can also influence employee involvement in self-guided development, even though self-guided development is self-controlled and not operationally or administratively supported by the organization. This research will identify how organizational characteristics, individual differences, and their interaction, influence involvement in self-guided development. Identifying work factors that facilitate involvement in self-guided development will shed light on what organizations can do to encourage self-guided development. For example, the nature of the job and organization climate may influence one's involvement in self-guided development by increasing the opportunity to engage in these development behaviors. Because the choice by employees to pursue self-guided development behaviors may be facilitated or deterred by an organization’s structures and systems, firms that identify how to encourage and support self-guided development should be better positioned to realize the benefits of such behaviors.
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This research will also identify valuable firm outcomes associated with self- guided development. Self-guided development should lead to positive outcomes because it creates knowledge that can be used and shared at work. Further, this research will identify the factors that accentuate the positive relationship between self-guided development and its outcomes. Contextual factors, such as the exchange relationships employees experience at work, tend to influence the degree to which development experiences produce positive results. Positive exchange relationships with one's organization, supervisor, and coworkers may motivate employees to transfer new knowledge and skills into their current work making it more likely that self-guided development will produce valuable work outcomes in these situations.
The remaining chapters address these issues. Chapter 2 reviews the development literature and defines self-guided development within that domain. Chapter 3 positions self-guided development within a nomological network by offering a series of hypotheses concerning its antecedents and outcomes as well as those factors that may operate to enhance these relationships. Chapter 4 describes the methods used to collect data and the analysis techniques that will be used to analyze the data. The results can be found in
Chapter 5. Chapter 6 includes a discussion section of the results and highlights the implications and limitations of this research along with future research ideas.
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Chapter 2: Defining Self-Guided Development
The main focus of this chapter is to define self-guided development. It begins with a review of the development literature. Then, a thorough definition of self-guided development is provided including examples of what is and is not self-guided development. In doing so, the chapter highlights the value of self-guided development for the employee development literature.
Literature Review
Employee Development prior to the 1990s
Employee development refers to "the expansion of an individual’s capacity to function effectively in his or her present or future job and work organization" (McCauley
& Hezlett, 2001, p. 314). Prior to the 1990s, researchers often took a narrow view of employee development as an episodic organization intervention intended to develop job- relevant knowledge and skills (Hurtz & Williams, 2009). Such episodic activities include workshops, courses, seminars and other formal professional events (London, 1989).
Researchers were interested in discovering how to design effective interventions to facilitate the transfer of new knowledge, skills, and abilities from the learning environment to the job. Theories of behavioral psychology such as reinforcement theory
(Skinner, 1953), and cognitive psychology such as social learning theory (Bandura,
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1977), were at the forefront of learning theory. Much of this research centered on systematic models of instructional design (Gagne, 1962; Goldstein, 1986). Instructional system design (ISD) develops learning interventions by identifying learner needs, determining learning objectives, and selecting training methods and evaluation criteria to ensure transfer and training effectiveness (Noe, 2010). Often referred to as the ADDIE model, the instructor was responsible for Analyzing training needs and then Designing,
Developing, Implementing, and Evaluating the training program. Goldstein (1986) was largely responsible for introducing this influential model of instructional system design to the management literature as a way to increase training transfer and training effectiveness. Although the systems approach to instructional design was initially thought to be a linear process, it quickly evolved into a dynamic process. The Armed Forces, where the systems approach originated, recognized that the parts of the model are interrelated meaning that a change during one stage of the model influences the other stages. It was further suggested that the ISD model does not occur in a linear fashion where each step is accomplished in isolation; rather activities from the various phases may occur concurrently (U.S. Army, 1984).
During this time, other training researchers began to highlight that learning activities alone may not be sufficient to promote learning, transfer, and improvement by noting that trainee performance is also influenced by innate dispositional variables, trainee motivation, and situational factors (Gagne, 1985; Kanfer & Ackerman, 1989). For example, position, job tenure, organizational tenure, and social support were all found to influence participation in and attitudes about development activities (Kozlowski & Hults,
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1987). More specifically, work began to focus on general mental ability (GMA) and motivation to learn (i.e., training motivation) as critical individual difference variables that influence the outcome of training and development interventions (Baldwin & Ford,
1988). Hunter (1986) suggested that GMA determines the speed with which learning occurs as well as the amount that is learned. Different instructional designs were determined to be effective for individuals with different levels of ability. For example,
Snow (1986) found that tight, structured lessons were more effective for individuals with low GMA, while individuals with high GMA performed better in less structured learning situations. Noe (1986) demonstrated that trainees who are motivated to learn exhibit greater interest and investment in learning, making training more effective. Noe and
Schmitt (1986) refined this result when they found that employees were more motivated to transfer their skills from the learning setting to the work setting when they experienced high job involvement. Baumgartel et al. (1984) revealed that individuals with an internal locus of control have more positive attitudes about training and transfer of training because they are more likely to perceive training as beneficial (Noe, 1986).
Dweck's (1986, 1989) research on goal orientation added a new line of thought to this stream of research. Her research suggested that individuals with a learning goal orientation, the desire to gain new skills and competencies and master new tasks, experience the most positive feelings towards training and development, are the most motivated to learn, and are most likely to transfer learned material. Further, she found that the relationship between learning goal orientation and positive training outcomes is mediated by self-efficacy, the judgments individuals make about their ability to perform a
11 defined task (Bandura, 1982). This indicated that it is self-efficacy which ultimately affects transfer of training. Kanfer and Ackerman (1989) integrated much of this prior work by grounding their training research in goal setting theory as a supplement to the cognitive and individual differences theories prevalent at that time. They found that goal setting was detrimental for trainees with low GMA in learning conditions with high cognitive demand. In addition, their work confirmed the advantage of high GMA for training performance by illustrating that trainees with more ability have an increased attentional resource capacity. Since then, research has shown that the relationship between goal setting and performance is moderated by self-efficacy such that when self- efficacy is high goal setting has a positive effect on performance, but when self-efficacy is low goal setting can be detrimental to performance (Gist, Stevens & Bavetta, 1991).
Employee Development during the 1990s
Training and development research evolved during the 1990s when constructivist theories of learning began to gain attention as primary influences on instructional design as well as training and development effectiveness. Constructivism asserted that learning is an active and social process in which the learner constructs their own knowledge from their own experiences (Kraiger, 2008). Constructivist learning environments emphasized meaningful and authentic tasks that represent reality and the complexity of the real world, and encouraged reflection on learning experiences (Jonassen, 1994). It also stressed that learning will vary across individuals even if they experience the same developmental opportunities (Morrison & Brantner, 1992). During this time, the roles of the instructor
12 and instructional design were changing. Because learners were becoming actively involved in and responsible for their own learning, instructors acted more as facilitators of learning rather than as teachers (Bauersfeld, 1995). Likewise, the role of instructional design began to be used to "structure authentic learning environments that maintain learner motivation and provide tools for learners to explore, solve problems, discover meaning, and create their understanding of how to apply knowledge in their daily lives"
(Kraiger, 2008, p. 457).
Consequently, research began to take a broader approach to employee development by considering it an ongoing, continuous process consisting of activities that could be voluntary or mandatory, formal or informal, related either to one’s current job or to long-term personal effectiveness, and carried out during work time or outside of work time (Baldwin & Magjuka, 1997; Noe, Wilk, Mullen, & Wanek, 1997). In addition to workshops, courses, and seminars, research began to focus on a broad array of learning activities in which learners could play an active role in their development including, coaching and mentoring, assessment, and on-the-job learning through challenging tasks.
Research explored the positive effects of mentoring and executive coaching because these initiatives incorporate learning tasks that are authentic and represent a real-world view of the work and its complexities. This work provided evidence that mentorship and coaching facilitate information exchange, knowledge acquisition, and access to social networks, and can significantly improve manager productivity (Dreher & Ash, 1990;
Mullen, 1994; Olivero, Bane, & Kopeehnan, 1997). In 1994, McCauley et al. formalized on-the-job learning as a development tool by creating the Developmental Challenge
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Profile to assess the developmental components of managerial jobs. This 10-dimension framework identified features of managerial assignments that foster learning and provide opportunities for development. Consistent with constructivism, the developmental components were based on the assertion that challenging job situations advance on-the- job learning.
Other research sought to understand how performance assessment functions as a development tool when employees are given feedback and encouraged to reflect on what they learned. Hazucha et al. (1993) found that managers who participated in training and development activities improved their performance as a result of multisource feedback. In addition, Walker and Smither (1999) found that when receiving upward feedback, managers were most likely to improve their performance if they discussed that feedback with their supervisor rather than just reflecting on the feedback internally. Bettenhausen and Fedor (1997) found that employee feedback produced positive results when the appraisal was perceived as being conducted as a developmental tool, rather than for administrative purposes. In a meta-analysis, Kluger and DeNisi (1996) found that the effectiveness of extremely negative feedback interventions was very low because it caused feedback recipients to abandon their goals. Self-efficacy emerged as an important antecedent here as well when studies illustrated that the outcomes associated with feedback are positive and significant when trainees have high self-efficacy (Karl,
O’Leary-Kelly, & Martocchio, 1993; London & Smither, 1995).
To integrate the various themes emerging across the development literature at that time, Noe et al. (1997) put forth a widely-used taxonomy that identified and categorized
14 development experiences into four components: employee assessment, on-the-job experience, professional relationships, and formal courses or programs (Hurtz &
Williams, 2009). Employee assessments were identified as individual evaluation techniques designed to (1) identify one's job-related strengths and weaknesses and (2) assess his/her job performance. This component of development included formal performance appraisals and 360-degree feedback as well as feedback seeking behavior initiated by the employee. On-the-job experience referred to expanding one's knowledge and skill set through exposure to the work itself. Techniques such as job rotation, job enlargement, challenging assignments, promotions, and transfers are examples of on-the- job experiences as a type of employee development. Professional relationships enhanced employee development by placing employees into partnerships to learn from one another.
Formal courses and programs constituted development which occurs through on- or off- site courses that educate employees in particular knowledge or skills. Less formal learning experiences like reading books or using other reliable resources to obtain work- relevant information were also classified as formal courses and programs.
Employee Development in the 2000s
The training and development literature of the past 10 years has transitioned even further in the direction of promoting and understanding employee responsibility for learning. Contemporary research has sought to answer questions about learner-controlled training initiatives that do not rely on traditional classroom training. For example, with e- learning being used at an accelerated pace in organizations (Schmidt & Ford, 2003),
15 researchers are attempting to identify the outcomes associated with online learning and how those outcomes relate to traditional classroom learning. Sitzmann, Kraiger, Stewart, and Wisher (2006) found that learning outcomes for trainees in online instruction versus the classroom are the same when the same instructional methods are used. In other words, trainee learning depends more on the method than the delivery media. Error management, allowing employees to diagnose and learn from their own errors, has emerged in the literature as a type of self-directed learning. Research on this type of training suggests that it can be a valuable developmental exercise; however it may only be effective for trainees with high GMA because such individuals are better able to self-regulate (Gully,
Payne, Koles, & Whiteman, 2002). Research has continued to emphasize the importance and effectiveness of on-the-job work experiences as developmental opportunities
(McCall, 2004). Barber (2004) suggested that on-the-job training provides employees with an informal learning experience that produces gains in tacit knowledge and innovation.
These examples exemplify a critical shift taking place in the way we think about training and development in the 21st century. Training theory is transitioning from learners having a passive role to learners having an active, integral role wherein they are responsible for their own learning and development. This transition away from formal, structured interventions is being spurred in part by four different lines of work that further characterize current research in employee development. First, after many years of preliminary research on issues such as frequency and content (Ashford, Blatt, &
VandeWalle, 2003), feedback seeking behavior, when employees actively inquire directly
16 about their work performance or observe others and infer their strengths and weaknesses based on comparisons (Ashford & Cummings, 1983), is gaining new prominence as an employee-initiated development experience. Through seeking feedback, employees gain information to assess their performance which then enables them to reflect on their strengths and weaknesses, seek advice, and come up with an action plan for obtaining new knowledge and skills. Renn and Fedor (2001) recently found that the quality and quantity of one's work performance was improved after engaging in feedback seeking behavior because it increased personal goal setting. De Stobbeleir, Ashford, and Buyens
(2011) examined the extent to which employees used feedback seeking as a strategy to increase creativity. They found that feedback inquiry (i.e., asking for direct feedback) was positively associated with supervisor ratings of employee creativity.
Second, indicative of McCauley et al.’s (1994) research suggesting job design can influence employee development, Wrzesniewski and Dutton (2001) introduced job crafting as a proactive, bottom-up approach to job design in which employees alter their work situation to better match their own needs, aspirations, and circumstances to their jobs. Using interviewing methods, their research identified a series of job crafting techniques that employees use to shape their work experiences by changing the behavioral, relational, and cognitive boundaries of their jobs (Wrzesniewski & Dutton,
2001). Two approaches to job crafting appear to be especially developmental. Task emphasizing involves employees changing the nature of a task or dedicating additional time and attention to a task. Job expanding involves taking on new, additional tasks
(Berg, Grant, & Johnson, 2010). Current research suggests that job crafting is positively
17 related to employee engagement, efficiency, and quality of work (Ghitulescu, 2006;
Leanna et al., 2009).
Third, researchers have begun to study informal learning (Ellinger, 2005).
Informal learning generally refers to learning which is learner initiated and controlled. It is usually intentional, but not structured. Examples of informal learning include self- directed learning, networking, coaching, and mentoring (Marsick et al., 2001). In their dynamic model of informal learning, Tannenbaum, Beard, McNall, and Salas (2010) suggested that informal learning has four components: intent to learn, engaging in experience and action, receiving feedback, and reflecting on the learning. Lohman (2005) operationalized informal learning as learning from one’s self, learning from others, and learning from non-interpersonal resources. She found that informal learning occurred most when employees had high self-efficacy, a love of learning, were committed to professional development, and had an outgoing personality. Environmental factors, such an unsupportive organization culture and inaccessibility of subject matter experts, inhibited employee engagement in informal learning.
Finally, Ng and Feldman (2010) introduced social capital development to the employee development literature as "activities of individuals aimed at developing relationships with others who have the potential to assist them in their careers" (p. 700).
Networking with others, building and maintaining relationships with important people, and using one's connections to make things happen at work are all examples of social capital development behaviors (Ng & Feldman, 2010). Social capital development is goal directed and often takes considerable effort (Ferris, et al., 2007; Ng & Feldman, 2007).
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However, research suggests that social capital development behaviors might well be worth the effort as such behaviors appear to be instrumental for career advancement
(Zippay, 2001). Having a large network enables employees to use their relationships to learn and develop themselves professionally. In fact, in a study by Seibert, Kraimer, and
Liden (2001) networking was identified as one of the most effective career management strategies.
Each of these literature streams has a common theme: a focus on employee-driven development experiences. Employees who seek feedback are actively involved in the learning process. They are in a position to recognize the capabilities they possess and are motivated to take on more challenging work. Employees who job craft develop themselves by shaping their work experience to reduce ambiguity and create a more positive working situation. This behavior generates human capital as employees learn by challenging themselves to figure out new ways to conduct a task or take on new assignments. Informal learning which occurs without an instructor, and outside of a formal learning setting (Bear et al., 2008; Cseh et al., 1999; Tannenbaum et al., 2010) is employee-driven by definition. With social capital development, employees learn as a result of their own actions as they personally invest in creating relationships with influential others.
Yet, each stream has proceeded in isolation, independent of the others. Reflecting on this research as a whole, the concepts and ideas become noticeably, intimately connected when conceptualized as examples of proactive development behavior.
Proactive behavior is defined as employees "taking initiative in improving current
19 circumstances or creating new ones; it involves challenging the status quo rather than passively adapting to present conditions" (Crant, 2000, p. 436). Proactive behavior reflects an individual actively taking control of his/her situation for the purpose of removing uncertainty and ambiguity (Crant, 2000). Research suggests that the success of an organization is increasingly dependent on employee proactive behavior (Fuller et al.
2010; Seiling, 2001). For example, Grant, Parker and Collins (2009) found that employees who engaged in certain proactive behaviors received higher performance evaluations. Similarly, Thompson (2005) found that network building, a specific type of proactive behavior, resulted in higher task performance. Seibert, Kramer and Crant
(2001) found that proactive behavior was positively associated with career satisfaction and career progression as indicated by salary growth and number of promotions.
The Value of Introducing Self-guided Development
This dissertation pulls together elements of seemingly different types of proactive development behavior to form self-guided development. Self-guided development is a compilation of proactive employee development activities. Even though it is clear that employees are becoming more responsible for their own learning and development at work, theory on employee development has failed to keep pace with this transition. Self- guided development seeks to address this deficiency by offering a framework for thinking about employee development that formalizes the evolution of training theory toward learner-centric, learner-controlled models. Offering an integrative, modern view of
20 employee-driven development activities, self-guided development contributes to the employee development literature in three ways.
First, self-guided development offers a holistic, parsimonious conceptualization of proactive development behavior. Similar to other well-known compilations of behavior such as organizational citizenship behavior or adaptive performance (e.g., Allen & Rush,
1998; Chen, Hui, & Sego, 1998; Deckop, Mangel, & Cirka, 1999; LePine et al., 2002;
Motowidlo, 2000; Pukalos et al., 2000), self-guided development fuses together various development activities in which employees determine their own learning and growth.
This provides a means to peel-away surface-level disparities that currently contrast activities such as job crafting, informal learning, or error management, to reveal a similar core. By doing so, these activities become examples of a more basic behavior, one that can then be better understood. The exploration currently taking place in the literature to understand various proactive development behaviors, as if such actions are independent, represents an important, but highly redundant line of research. Self-guided development integrates different proactive employee development behaviors within a single, theoretical framework.
Second, self-guided development unpacks the nature of proactive employee development behaviors and offers a basis for establishing a nomological network that is more generalizable. Studying these behaviors in aggregate will offer a more sophisticated understanding of proactive employee development. By starting with a clear definition of what constitutes these types of behaviors, we can more confidently build theory around these activities by hypothesizing and exploring the conditions under which self-guided
21 development emerges as well as how to maximize the outcomes of these behaviors.
Further, combining a set of behaviors that conceptually belong together reduces the likelihood of omitted variable bias. For instance, employees who engage in one type of proactive development behavior are likely to engage in other types of proactive development behavior. Accounting for only a single behavior risks incorrectly attributing a change in the dependent variable to that specific behavior when it was actually another behavior, or a combination of behaviors, that influenced the outcome.
Third, the breadth of self-guided development should afford better predictive validity when studying the relationship between employee-driven development experiences and valued organizational outcomes such as employee performance, satisfaction, and citizenship behavior that are known to be multidimensional and complex
(Law et al., 1998; Motowidlo, 2000; Ones & Viswesvaran, 1996). As Ones and
Viswesvaran (1996, p. 619) commented, “…complex and rich predictors work best” when predicting criteria that “are complex in nature with many factors combining to cause the behavior of interest”. Broader composite variables synthesize activities that are individually specific and narrow producing the capacity to account for more variance in a multi-faceted dependent variable (Hogan & Hogan, 1989).
Self-Guided Development Defined
Self-guided development refers to the proactive decision to voluntarily engage in self-identified development experiences. More specifically, self-guided development represents an actionable set of knowledge-, skill- or relationship-building learning
22 activities that generate human capital, but are unstructured, voluntary, and not operationally or administratively provided by the organization. Self-guided development can be carried out during work time or during non-work time. Because self-guided development is considered a specific type of development, its definition should be grounded in the general development literature. Using the Noe et al. (1997) taxonomy of development experiences, self-guided development encompasses activities from each of the four components. This section characterizes the nature of self-guided development in more detail using examples of activities that represent the four-part taxonomy (see Figure
1, p. 24).
Voluntary. As a proactive behavior (Crant, 2000), self-guided development requires employees to actively seek information and opportunities for improving their work. This type of development can be considered entrepreneurial in that the employee identifies and often creates the opportunity to learn. This also implies that such activities are voluntary; meaning it is not required or imposed by an organization's formal HR strategy. Rather, the individual chooses to actively participate and put forth effort in self- guided development. Ashford and Cummings (1983) argued that individuals can take a proactive role to feedback-seeking by monitoring themselves and others' behavior, and by inquiring, or asking others directly to assess their performance. Monitoring and inquiry are examples of self-guided development behaviors. When engaging in these two activities, individuals voluntarily seek out assessment information that can be used to improve their performance.
23
Experience
Formal Assessment Self-Guided Courses and Development Programs
Relationships
Figure 1. Self-guided development within the traditional development literature
Unstructured. Self-guided development is not only voluntary; it is accomplished through an unstructured learning experience. Typical employee training programs are systematically implemented following an instructional system design process. These programs have specific goals, learning objectives, assessment instruments, and expectations. Self-guided development does not include these features. The content, timing and details of self-guided development are established by the employees themselves. In other words, there are no pre-established learning objectives from an external source and employees are not accountable to anyone else for achieving personal self-guided development goals. In addition, there is no assessment or formal evaluation to 24 demonstrate that learning occurred through self-guided development, as is usually the case in structured learning settings with examinations. Self-guided development is a learning experience that occurs on an as-needed basis, can be ongoing or a one-time occurrence, and may or may not be spontaneous and naturally occurring. Thus, identifying and voluntarily participating in college courses, seminars or workshops is not self-guided development. Even online courses that are self-directed are not considered self-guided development. These types of courses may allow the learner to have some additional control and freedom over traditional learning settings. However, these learning experiences are still structured with prescribed learning objectives and a formal assessment of learning. On the other hand, when employees seek out information and find solutions to work problems on their own by using available resources (e.g., internet searches, books, social media), they are engaging in self-guided development. With these activities, employees themselves choose the content to which they will attend because there are no prescribed specifications for what should be learned.
Human Capital. Although employees have the freedom to construct their learning experience, for such activities to constitute self-guided development, those activities must result in employees gaining information that builds human capital. Human capital is an intangible asset that refers to all of the attributes, life experiences, knowledge, inventiveness, energy, and enthusiasm that a company’s employees invest in their work
(Noe, 2010). More specifically, human capital refers to an organizational resource that is created from the emergence of individuals’ knowledge, skills, abilities, relationships, and other characteristics (Lin, 2001; Ployhart & Moliterno, 2011) that enhance employee
25 success at work (Becker,1964) and are a source of competitive advantage (Barney, 1991).
This implies that joining a gardening club to network with people who provide useful information about gardening, then, is not an example of self-guided development.
However, recognizing that a gardening club member is an expert in new technology and networking with him/her to discuss how to use that new technology at work is self-guided development because this voluntary, relationship-building, unstructured learning activity generates human capital.
Not administratively or operationally supported by organization. Lastly, even though firms stand to benefit directly from it, self-guided development is not supported administratively or operationally by the organization. This means that the organization does not invest time or human resources into the development experience. The planning necessary for self-guided development to take place is not provided by the organization.
Therefore, learning and development activities sponsored or made available by the organization (e.g., job rotation or formal training and mentorship programs) are not considered self-guided development. Alternatively, seeking out and taking on additional tasks and responsibilities, experimenting with new ways to perform one's work, and modifying physical task boundaries of the job are all activities that are not administered by the organization. These on-the-job experiences reflect self-guided development.
26
Chapter 3: Nomological Network for Self-Guided Development
Self-guided development requires the construction of a nomological network to demonstrate its meaningfulness as a compilation of behaviors (Cronbach & Meehl,
1955). This chapter will use theory and past empirical evidence to offer a series of hypotheses about the antecedents, consequences and correlates of self-guided development. These hypotheses will assist in positioning self-guided development within the broader field of employee development. The hypotheses will also help confirm the structure and form of self-guided development. Positing what variables likely predict self-guided development and what self-guided development likely predicts will shed light on the nature of these behaviors and the effect that they have on how individuals perform in organizations. Figure 2 (p. 28) is the proposed model for self-guided development and its antecedents and consequences. The remainder of this chapter outlines each of the hypotheses represented in the Figure. Chapter 4 will provide the methodology for testing the hypotheses put forth.
Antecedents of Self-Guided Development
Consistent with the conceptualization of proactive behavior put forth by Crant
(2000), contextual factors and individual differences should both influence employee involvement in self-guided development. Individual differences in employee habits, traits
27
Perceived Organization Job Training Supervisor Commitment Autonomy Climate Support
Task Performance Proactive Self-Guided Personality Development
Knowledge sharing
High Quality Task Relationships Interdependence
Figure 2. Proposed Nomological Network for Self-Guided Development
and attitudes should operate as antecedents of self-guided development. For example, self-guided development should be more common among individuals with a propensity to be proactive. Self-guided development may also be more likely to emerge when employees hold certain types of jobs and work within certain types of organization cultures. Indeed, individuals should be more likely to engage in self-guided development if they perceive that the work context offers the opportunity to do so. For example, an atmosphere conducive to learning should promote more self-guided development.
An Interactional Approach
Because self-guided development is discretionary, the relationship between self- guided development and its antecedents likely operates differently under different 28 circumstances. Consistent with interactional psychology (Bandura, 1977; Jones, 1983) and the theory of person-situation interaction (Mischel & Shoda, 1995), proactive individuals who are likely to engage in self-guided development activities should be even more likely to do so when the job and environment are supportive of such behavior. Even though traits are stable, contextual features impact the extent to which individual differences are free to manifest. For example, Tharenou (2001) found that employees high in training motivation were most likely to attend training and development activities when their supervisor, organization, and peers were supportive of the training initiatives because the situation provided them with the opportunity to act consistently with their individual difference and participate in training. In the absence of behavioral expectations from the organization, employees may demonstrate a tendency toward self-guided development, but the degree to which they actually engage in these behaviors likely also depends on the extent to which the environment supports the behavior. More specifically, because individual differences are more likely to influence behavior if the situation supports expression of the trait (Tett & Burnett, 2003) and less likely to influence behavior if the situation hinders expression of the trait, contextual variables such as a supportive training climate and job autonomy should impact self-guided development by creating the opportunity for individuals with certain personality traits to express those behaviors more readily.
Proactive Personality and Self-Guided Development
Individuals with a proactive personality are more likely to engage in proactive
29 behaviors such as self-guided development. Proactive personality is defined as a stable disposition to take personal initiative in a broad range of activities and situations to influence one’s environment (Li, Liang, & Crant, 2010; Seibert, Kramer, & Crant, 2001).
Proactive personality describes a tendency to identify opportunities, make changes at work and to act on those impulses (Crant, 2000).
Self-guided development should be prevalent among individuals with a proactive personality because they are more likely to participate in discretionary development activities, seek out and identify learning opportunities, and manage their social networks.
Proactive employees fully exert themselves towards achieving work goals (Campbell,
2000). Parker (1998) found that proactive personality is positively associated with individuals’ participation in organizational improvement initiatives. Proactive employees demonstrate a willingness to get involved and take charge to identify opportunities
(Crant, 2000). They are not likely to passively wait for information and opportunities to come to them (Crant, 2000). Rather, they update their skills and improve their work on their own (Li et al., 2010; Seibert, et al., 2001). Self-guided development reflects an opportunity for individuals with a proactive personality to take the initiative to develop themselves without waiting for an organization to administer a formal learning opportunity. Their desire to take charge of their own future suggests that individuals with a proactive personality should be more likely to voluntarily seek opportunities to learn new skills and gain new knowledge. Proactive employees are more likely to create and manage their social networks (Li et al., 2010). Building relationships and networking with influential people at work are examples of self-guided development behaviors. Thus,
30
Hypothesis 1: Proactive personality will be positively related to self-guided
development.
Job Autonomy and Self-Guided Development
Certain job characteristics should facilitate engagement in self-guided development behavior. Autonomy refers to the degree of freedom, discretion and control that employees have over their work and decision-making (Campion, 1988). When jobs are autonomous, employees can use their own personal judgment when deciding how and when to complete work (Hackman & Oldham, 1976). Individuals with more autonomous jobs have fewer social boundaries and time constraints at work meaning they can work with whom they want, when they want, how they want.
Self-guided development should be more prevalent among employees with autonomous jobs. Autonomy allows employees to control how and when they do their work. This high degree of control creates the opportunity to independently seek out knowledge and skills. Research suggests that autonomy is associated with the exhibition of proactive behaviors (Grant & Ashford, 2008). Employees who experience job autonomy are empowered, if not expected, to behave in a proactive way. They are more likely to have mechanisms, tools and techniques at their disposal that will assist them in learning to accomplish tasks on their own. Job autonomy is also associated with engagement in discretionary work behaviors (Foss, Minbaeva, Pedersen, & Reinholt,
2009, Gagne, 2003). Individuals with autonomous jobs are more likely to be comfortable with seeking out information in an unstructured manner and are more likely to have
31 developed strategies for performing successfully when the steps to task execution are unclear or self-determined. Further, jobs with greater autonomy promote a broader perspective in their incumbents (Parker, Wall, & Jackson, 1997). Individuals who hold more autonomous jobs have more opportunity to see beyond the boundaries of the position to identify new or better ways of performing the work. Each of these aspects should facilitate engaging in self-guided development. It has also been demonstrated that job autonomy provides individuals with the opportunity to learn (Johns, 2010; Janz &
Prasarnphanich, 2003), and positively influences the occurrence of learning (Liu & Fu,
2011; Wielenga-Meijer, Taris, Wigboldus, & Kompier, 2012). Job autonomy allows employees to reach out to coworkers, and experiment with new ways of doing work when trying to solve a work-problem at the most appropriate and convenient time to ensure objectives are met. Individuals with these types of jobs are better positioned to actively build relationships and learn from experience. Additionally, employees with autonomous jobs are more likely to recognize their need to acquire skills and knowledge because they tend to feel a strong sense of responsibility for work outcomes and feel that their "own efforts, initiatives, and decisions” influence work performance (Hackman & Oldham,
1976, p. 258). Thus,
Hypothesis 2: Job autonomy will be positively related to self-guided development.
The Interaction between Proactive Personality and Job Autonomy
Job autonomy and proactive personality should interact to further enhance the observance of self-guided development. Dispositions influence behavior as a function of
32 the strength of the situation (Mischel & Shoda, 1995). Typically, personality is a stronger determinant of behavior in weak situations characterized by lack of structure and a weaker determinant of behavior in strong situations characterized by clear, prescribed behavioral expectations. In weak situations, employee behavior is more likely to reflect one's personality because there are fewer prescribed norms and expectations to guide behavior. This implies that job autonomy has the potential to enhance the effect of proactive personality on the observance of self-guided development. Jobs with more autonomy manifest a weak situation (e.g., Barrick & Mount, 1993; Lee et al., 1990;
Peters et al., 1982). In that context, the behavior of employees who hold those jobs is more likely to be consistent with their personality. Essentially, greater job autonomy provides employees with the freedom to devote their resources toward those behaviors that best suit their dispositional needs (Noe & Tews, Under Review). For individuals with a proactive personality, this implies that holding a more autonomous job should further enhance the likelihood that these individuals will engage in self-guided development.
Such individuals should be better able to leverage their natural tendency to voluntarily initiate work behaviors and behave proactively when learning and acquiring new skills when they hold an autonomous job. The absence of behavioral constraints releases proactive employees to take the initiative to develop themselves. Having the freedom to control when and how they do their work should facilitate their efforts to seek out and identify learning opportunities, and manage their social networks. The discretion over work execution and decision-making that characterize a more autonomous job should strengthen the willingness and ability of individuals with a proactive personality to get
33 involved, take charge and be responsible for creating opportunities to learn and grow.
Thus,
Hypothesis 3: Job autonomy will moderate the relationship between proactive
personality and self-guided development such that the relationship between
proactive personality and self-guided development will be stronger when job
autonomy is higher and weaker when job autonomy is lower.
Training Climate and Self-Guided Development
An organization's training climate plays an important role in employee learning and development experiences (Colquitt & Simmering, 1998; Hurtz & Williams, 2009).
Climate refers to the shared perceptions of employees concerning the practices, procedures, and behaviors that get rewarded and supported in a work setting (Schneider,
1985). Training climate, specifically, is defined as "the perceived support from management, work, and the organization for formal and informal training and development activities" (Tracey & Tews, 2005, p. 358). A supportive training climate helps employees prepare for development activities and achieve learning objectives
(Tracey, Hinkin, Tannenbaum, & Mathieu, 2001) and encourages easy transfer of newly acquired skills to the job (Holton, Bates, & Ruona, 2001; Rouiller & Goldstein, 1993;
Tracey, Tannenbaum, & Kavanagh, 1995).
Self-guided development should be more prevalent when organizations foster a supportive training climate. A supportive training climate provides an environment conducive for engaging in self-guided development because in this context continuous
34 learning is valued, high performance is emphasized, and employees have the opportunity to and are expected to acquire and transfer new knowledge and skills to their work. In a supportive training climate, on-the-job learning and skill acquisition are encouraged, supported and recognized by others, and "jobs are designed to promote continuous learning and provide flexibility for acquiring new knowledge and skills" (Tracey & Tews,
2005, p. 358). When people collectively value learning, self-guided development behaviors such as exchanging information and resources and collaborating with coworkers to identify better ways to get work done are more likely to occur. Moreover, the flexibility associated with a supportive training climate, as well as the emphasis on independent and innovative thinking, should promote self-guided development by creating additional opportunities for employees to experiment with ways to improve performance. For instance, self-guided development behaviors such as finding new ways to perform a job through job experiences using trial and error techniques are likely to be encouraged in a supportive training climate. Thus,
Hypothesis 4: A supportive training climate will be positively related to self-
guided development.
The Interaction between Proactive Personality and Training Climate
Similar to job autonomy, proactive personality and training climate should also interact to further enhance the observance of self-guided development. The work climate reflects and guides employee behavior, helping to ensure that employees behave in a manner that is consistent with the expectations of the organization and their coworkers
35
(Schneider, 1985). Employees with a natural tendency to engage in self-guided development may do so to a lesser extent if the climate is not conducive to such behaviors. An unsupportive training climate should hinder and weaken the extent to which individuals with a proactive personality participate in discretionary development activities, seek out and identify learning opportunities, and manage their social networks.
For example, a proactive individual may want to ask his supervisor for feedback or experiment with new ways to improve work, but may be reluctant to do so in a training climate that is not supportive because these self-guided development behaviors may not be valued. Rather than being acknowledged and rewarded for identifying ways to gain new knowledge and skills, employees in an unsupportive training climate may fear reprimand for engaging in self-guided development. In contrast, a supportive training climate should reinforce independent efforts to update skills and improve work. The emphasis on independent and innovative thinking that characterizes a supportive training climate should assist individuals with a proactive personality with their desire to take charge of their own future by highlighting the value of exploratory techniques for solving problems and supporting employee efforts to seek out learning activities that are non- traditional. Further, proactive employees intent on achieving work goals should be more likely to take the initiative to seek out ways to improve their performance when working in an environment where employees are encouraged to acquire and transfer new knowledge and skills to work (Campbell, 2000). Thus,
Hypothesis 5: Training climate will moderate the relationship between proactive
personality and self-guided development such that the relationship between
36
proactive personality and self-guided development will be stronger when the
training climate is more supportive and weaker when the training climate is less
supportive.
Outcomes of Self-Guided Development
Self-guided development should lead to valuable organization outcomes because it generates the human capital needed to realize a more knowledgeable, skillful and experienced workforce (Benson, Finegold, & Mohrman, 2004). Specifically, self-guided development should be positively associated with high levels of task performance and knowledge sharing because the new knowledge, skills and relationships created through self-guided development can be used and shared at work. Similar to its antecedents, the relationship between self-guided development and its consequences is also likely to operate differently under different circumstances. Task performance and knowledge sharing are influenced in part by both ability and motivation (London, 1997; Noe et al.,
2011). Individuals must possess the knowledge to perform well, but must also have the motivation to apply that knowledge toward the production of performance and share that knowledge with others.
After engaging in self-guided development, the extent to which employees are motivated to use and share their newly developed human capital likely depends on the nature of their exchange relationships at work. When employees have positive exchange relationships with their organization, supervisors and coworkers, those relationships should motivate employees to translate the knowledge and skills gained from self-guided
37 development into outcomes valued by the organization. Positive exchange relationships between employees and the organization are characterized by employee perceptions that because the organization is just, committed to them, and supportive of them, the organization warrants their commitment in return (Eisenberger, Fasolo, & Davis-
LaMastro, 1990; Eisenberger, Huntington, Hutchison, & Sowa, 1986). Positive exchange relationships between employees and supervisors are characterized by employee perceptions that because supervisors are supportive, caring, value their contributions, and look out for their best interest, supervisors deserve their best efforts and their willingness to fully utilize their knowledge, skills, and abilities at work (Settoon, Bennett, & Liden,
1996). Positive exchange relationships among coworkers are characterized by mutual perceptions of liking, understanding, and commitment to each other (Carmeli, Brueller, &
Dutton, 2009). These perceptions facilitate a harmonious, collaborative environment among coworkers. Social exchange theory suggests that employees with positive exchange relationships will attempt to avoid feelings of cognitive dissonance by reciprocating positive behavior (Blau, 1964; Eisenberger et al., 1986). Thus, individuals who experience positive exchange relationships at work should be more motivated to use or share their new knowledge as a means of maintaining that positive relationship. More specifically, perceived supervisor support, organization commitment, high-quality relationships and task interdependence operationalize the nature of the exchange relationships and thus should affect the extent to which self-guided development leads to improved task performance and knowledge sharing.
38
In thinking about the likely effects of positive exchange relationships, it is critical to observe that such relationships are unlikely to function as an antecedent of self-guided development. When employees feel that supervisors care about their well-being, for example, having this perception does not also imply that they will perceive the opportunity, have the opportunity, or be motivated to engage in self-guided development.
Rather, once an employee engages in self-guided development, these positive relationships increase the likelihood that the new knowledge and skills will be used or shared at work.
Self-Guided Development and Task Performance
Self-guided development should have a positive association with task performance because it enables the development of both tacit and explicit knowledge and facilitates transfer of that knowledge to the job. Job knowledge consists of work-related information processed by individuals including ideas, facts, expertise, and judgments that influence performance (Schmidt, Hunter, & Outerbridge, 1986; Wang & Noe, 2010). Job knowledge has emerged as one of the strongest predictors of job performance, even more so than ability (Hunter, 1983; Schmidt, et al., 1986). Thus, self-guided development should positively impact the quantity and quality of employee task performance because it creates an opportunity for knowledge acquisition.
Job knowledge is acquired in two forms: explicit and tacit. Explicit job knowledge is codified knowledge that can be transferred across time and space (Lam,
2000). This type of knowledge is relatively simple to obtain. It can be easily disseminated
39 and communicated to a large number of employees (Schultz, 2001). Self-guided development behaviors, such as accessing books, journals or newspapers to gain work- relevant information, should increase the level of employees’ explicit job knowledge.
Tacit job knowledge is more difficult to identify and often remains undetected in traditional learning settings. Tacit knowledge is subconsciously understood, uncodified knowledge based on experience. It may consist of mental schemas or patterns (Berman,
Down, & Hill, 2002) or fragments of already existing organizational routines (Nelson &
Winter, 1982). Berman et al. (2002) suggested that tacit knowledge is acquired through collective experience. Proactive on-the-job experiences such as collaborating with coworkers, observing experienced coworkers to solve a work problem, or asking for feedback should lead employees to gain skills and experience that are not easy to find using official or formal work resources. Because self-guided development is not constrained by set objectives or criteria, its unstructured nature supports free-form interaction allowing employees to talk through thoughts and work processes and capture ill-defined tacit knowledge.
According to the stages of learning, once tacit or explicit knowledge is obtained the learner will begin to recall that information in relevant situations and use it to perform a task (Kanfer & Ackerman, 1989). Transfer refers to the successful application of knowledge, skills, and attitudes gained in a learning context to the job (Baldwin and
Ford, 1988). Self-guided development is likely to facilitate transfer of acquired knowledge, both tacit and explicit, because it represents an opportunity for near transfer to occur. Near transfer refers to transfer of learned material to closely related contexts
40 and tasks (Royer, 1979). Employees engage in self-guided development specifically to learn something relevant to their job or to solve a work-related problem. For example, employees' may ask their peers for advice or feedback, or look something up on the internet with respect to a specific job-relevant issue. Because what is learned through self-guided development is directly applicable to work, it represents a near transfer situation. Near transfer is the most common and successful type of transfer to occur after training because it signifies a high fidelity condition, which have higher rates of transfer.
Additionally, transfer is facilitated through social support and exploratory learning
(Facteau, Dobbins, Russell, Ladd, & Kudisch, 1995; Rouiller & Goldstein, 1993; Tracey, et al., 1995). For this reason, work relationships and proactive on-the-job experiences, both examples of self-guided development, should also support knowledge transfer.
When knowledge transfer occurs, it is predictive of individual job performance (Colquitt
LePine, & Noe, 2000). Because employees use self-guided development behaviors to acquire new knowledge and skills which are readily-transferable to the workplace, self- guided development should improve performance. Thus,
Hypothesis 6: Self-guided development will be positively related to task
performance.
The Interaction between Self-Guided Development and Perceived Supervisor Support
Because a supervisor has higher status and more power, Kuvaas (2010) suggested that positive experiences with one's supervisor are necessary for development experiences to positively influence employee task performance. Further, research suggests that
41 whether or not learned information is transferred to the job and modifies behavior depends on the support received from an employee's immediate supervisor (Huczynski &
Lewis, 1980). Supervisor support theory (Eisenberger, Huntington, Hutchison, & Sowa,
1986), which is based on exchange theory (Blau, 1964) and the norm of reciprocity
(Gouldner, 1960), suggests that when employees perceive that supervisors value and support their efforts and contributions, and care about their well-being and general satisfaction at work, an implied obligation develops between the supervisor and his/her subordinates (Eisenberger et al., 1986; Settoon, Bennett & Liden, 1996; Wallace, et al.,
2006). This implied obligation establishes the basis for a positive exchange relationship between the supervisor and the subordinate that is characterized by mutual reciprocity of positive behavior. Employees who feel cared for and valued by their supervisor tend to feel an obligation to reciprocate. This felt obligation should manifest in a desire to contribute more to their work in an attempt to maintain their performance as a means of upholding their end of the exchange. This implies that employees who obtain new knowledge, skills and abilities through self-guided development will be more likely to transfer their newly developed human capital to their current job and perform well when they perceive their supervisor as supportive. In other words, perceived supervisor support should function to enhance transfer because it induces a felt obligation that motivates employees to utilize their new abilities to improve their work performance. Thus, perceived supervisor support should interact with self-guided development by strengthening its positive effect on employee task performance.
42
Hypothesis 7a: Perceived supervisor support will moderate the relationship
between self-guided development and task performance such that the
relationship between self-guided development and task performance will be
stronger when perceived supervisor support is higher and weaker when perceived
supervisor support is lower.
The Interaction between Self-Guided Development and Organization Commitment
Commitment refers to "a volitional psychological bond reflecting dedication to and responsibility for a particular target". (Klein, Molloy, & Brinsfield, 2012, p. 137).
Organization commitment, then, refers to a psychological bond between an employee and his/her organization wherein the employee makes a decision to be dedicated to the organization. Commitment research has established motivation as a primary outcome of commitment. The psychological bond evident in the choice to be committed motivates employees to engage in behaviors that support their organization. Employees who are committed will put in more effort on the organizations behalf. For example, using the new knowledge and skills gained from self-guided development to perform well represents a behavior that supports the organization. Siders, George, and Dharwadkar
(2001) found a significant interaction between job experiences and commitment, such that performance was highest when both job experience and commitment were high.
Commitment motivates employees to transfer what they learn to the job in the interest of improving their job performance (Meyer, Becker, & Vandenberghe, 2004). Employees who make the volitional choice to be committed should apply what was learned through
43 self-guided development more than non-committed employees. Thus, organization commitment should interact with self-guided development by strengthening its positive effect on employee task performance.
Hypothesis 7b: Organization commitment will moderate the relationship between
self-guided development and task performance such that the relationship between
self-guided development and task performance will be stronger when organization
commitment higher and weaker when organization commitment is lower.
Self-Guided Development and Knowledge Sharing
Self-guided development should have a positive association with knowledge sharing because it provides employees with knowledge that is beneficial to themselves and others. Knowledge sharing refers to the distribution of task information and know- how to help others solve problems, develop new ideas or improve performance
(Cummings, 2004; Pulakos, Dorsey, & Borman, 2003). Knowledge sharing generally occurs through work experiences and professional relationships (Bear, et al., 2008;
McCauley et al., 1994). Because self-guided development also occurs through experience and relationships, employees are learning in ways consistent with the occurrence of knowledge sharing. Further, because self-guided development is unstructured and not operationally supported by the organization, when employees engage in these behaviors they are likely to gain information that is not readily accessible to others. Discretionary methods for learning should promote a variety of creative tactics for seeking out
44 information. When employees uncover unique information related to task execution and work performance, that information should be viewed by others as valuable knowledge.
The possession of valuable knowledge is a necessary but not sufficient condition for knowledge sharing. It must also be the case that such individuals desire to extend that knowledge to others. The desire to share work-relevant information with coworkers should be supported by the likelihood that such individuals can offer helpful information in the future. When coworkers share information it creates a reciprocal partnership; each offers information in the expectation that others will return the favor. For example, an employee is likely to offer information and advice about a current work project because she expects to gain valuable information from those coworkers in the future. She invests in the likelihood that her coworkers will at some point be in a position to repay the debt.
Thus, the opportunity to regularly access coworkers later as a means of learning in return positions coworkers as a valuable resource. In other words, the establishment of a basis for reciprocated exchange of information with other employees sets the stage for accessing valuable information from coworkers at a future date in time. Thus,
Hypothesis 8: Self-guided development will be positively related to knowledge
sharing.
The Interaction between Self-Guided Development and High-Quality Relationships
High-quality relationships at work represent a type of positive exchange relationship in which coworkers mutually like, understand and help one another.
Employees with high-quality interpersonal relationships listen attentively to coworkers,
45 accept differences, and enjoy a more harmonious and collaborative working environment.
The quality of one’s work relationships is likely to have an important influence on the degree of knowledge sharing (Brown & Van Buren, 2007; Kraiger, 2008). Employees engage in altruistic, helping and cooperative behaviors to benefit the people at work whom they like and care about (Ilies, Fulmer, Spitzmuller, & Johnson, 2009). Knowledge sharing is a type of helping behavior. Research has shown that individuals are more likely to help coworkers with whom they have high-quality relationships (Bowler & Brass,
2006; Chiaburu & Harrison, 2008). Further, the process of knowledge sharing has an implicit social element making it dependent upon the quality and nature of human relationships in the workplace (Eraut, 2004; Kozlowski & Bell, 2007; Kozlowski &
Ilgen, 2006). When employees have high-quality relationships with others at work, those relationships bring a psychological bond that should foster their desire to share knowledge gained through self-guided development with those others. The presence of a high-quality relationship hedges against the knowledge sharing investment failing. In other words, it increases the likelihood that employees will benefit from the reciprocal partnership such that it becomes more certain that others will return the knowledge sharing favor in the future. Thus, the presence of a positive relationship among employees should enhance the degree of knowledge sharing that takes place. Further, high-quality work relationships offer an informal opportunity to share knowledge to the extent that employees with such relationships tend to interact more regularly. Sias and
Cahill (1998) interviewed 38 employees and found that as friendships got closer more high-quality information on work topics was exchanged. Thus, high-quality relationships
46 should interact with self-guided development by strengthening its effect on knowledge sharing.
Hypothesis 9a: High quality relationships will moderate the relationship between
self-guided development and knowledge sharing such that the relationship
between self-guided development and knowledge sharing will be stronger for
employees who experience better-quality relationships and weaker for employees
who experience lesser-quality relationships.
The Interaction between Self-Guided Development and Task Interdependence
Task interdependence refers to the degree to which employees must interact and rely on one another to accomplish their individual jobs (Jehn, 1995). Task interdependence binds coworkers together such that the success or failure of one has implications for the success or failure of all. Thus, task interdependence increases the amount of interaction, the intensity of interaction, and the importance of interaction among coworkers. Task interdependence represents a situation which necessitates that exchange relationships develop among coworkers regardless of personal preferences for building relationships. When effective performance requires that employees coordinate their efforts with each other, those employees should be more motivated to exchange resources because doing so serves their own respective interests. Given that self-guided development provides employees with knowledge to share, task interdependence should facilitate knowledge sharing because employees have more opportunity to share information and are required to rely on each other to perform well. In other words,
47 because collaborating with one another is required of the task, employees will be expected to share knowledge obtained through self-guided development. Under this circumstance, an employee is more likely to share the task-relevant information that they found online, for example, because successful completion of the task requires that coworkers have access to that information; they are naturally in a position to discuss new knowledge and interact with coworkers; and, they expect that coworkers will reciprocate by sharing knowledge with them. Thus, self-guided development is even more likely to have a positive influence on knowledge sharing if tasks are also highly interdependent.
Hypothesis 9b: Task interdependence will moderate the relationship between self-
guided development and knowledge sharing such that the relationship
between self-guided development and knowledge sharing will be stronger when
task interdependence is higher and weaker when task interdependence is lower.
48
Chapter 4: Methodology
This is a non-experimental research design in a field setting. Field studies offer high contextual realism when attempting to observe specific relationships and interactions among behavioral and social variables that exist (Kerlinger & Lee, 2000).
Because it represents a new way of thinking about employee work behavior, it is appropriate to use data from a non-experimental field setting to measure self-guided development and test its hypothesized relationships. Conducting this research in a field setting will demonstrate if and how these behaviors naturally occur in real organizations.
Sample
The sample consisted of a total of 103 employees from a leading developer and marketer of accessories brands and fashionable, solution-oriented products (footwear, handbags and foot care). This is a good field site for data collection because the organization has employees in multiple locations and a variety of different professional positions. This should provide sufficient variance for the contextual variables because not all employees will have the same job design, or will be working in the exact same climate. Employees in this organization are provided ample opportunities to engage in self-guided development behaviors. In fact, the organizational culture and leadership competencies suggest that the organization not only encourages, but also expects
49 employees to participate in self-guided development behaviors. These employees also have access to a computer and the know-how to complete an online survey. The sample was 60% female and 40% male. The average age was 42.5 years old and the average job tenure was 4.21 years. Sixty-two percent of the sample had at least a bachelor’s degree another 31% had completed some college courses.
Study Procedures
To initiate data collection, an organization contact within the participating company forwarded a recruitment email to all employees and explained that the organization has agreed to be involved in and is supportive of this research project.
Employees were told that the purpose of the project was to understand how, when, and why informal activities benefit the organization, and how the organization can facilitate informal human resource practices in their work environment. They were also informed that as participants they would be asked to complete two surveys at two different points in time, and that part of their company record would be accessed for additional information. Employees who agreed to participate in the research clicked on a URL link in the e-mail to gain access to the first survey (Survey 1). Prior to beginning the survey, informed consent was obtained. When responding on both surveys, employees were asked to provide their e-mail address for the purpose of linking responses from the two surveys and company records. The first survey measured the antecedent variables
(proactive personality, job autonomy, training climate, learning goal orientation) and self- guided development. Of the 128 employees invited to participate in the study, 96
50 completed Survey 1 (75.6%) during a two-week window. A comparison of respondents and non-respondents for Survey 1did not yield any significant differences in mean value for any variables (See Table 1).
Table 1. A comparison of data for respondents and non-respondents of Survey 1
Respondents Non-respondents n 96 31 Age (years) 42.5 44.6 Gender 59% female 58% female Tenure (years) 4.2 2.9 Performance 3.43 3.25 * t-test results indicated that none of the differences were statistically significant
Employees received an email about four weeks later which directed them to complete the second survey (Survey 2) by once again clicking on a URL link to gain access. Seventy-six employees completed Survey 2 during another two-week window. Of those 76 employees, 69 had also completed Survey 1. Again, a comparison of respondents and non-respondents for Survey 2 did not yield any significant differences in mean value for any variables. The second survey measured those variables expected to serve as outcomes of self-guided development and variables related to those outcomes
(perceived supervisor support, organization commitment, task interdependence, high- quality relationships, and knowledge sharing). Self-guided development was also measured a second time. Measuring self-guided development at two points in time allowed us to examine the stability of the behavior. Additionally, measuring the independent variables on Survey 1 and the dependent variables on Survey 2 allowed us to alleviate concerns about common method variance. Common method variance refers to 51 false relationships among variables resulting from similar data collection methods.
Collecting data so that the independent variable and dependent variable were gathered at different times minimized the effect of common method variance because covariance can be attributed to the constructs, rather than the measurement method (Podsakoff,
MacKenzie, Lee, & Podsakoff, 2003).
Company records were obtained from a representative of the data site. The representative provided information about participants’ age, tenure, job title, level of education, and location, as well as individual-level performance data. Sixty-nine employees (67%) provided responses to both surveys that could be matched to the company records data and used for hypothesis testing.
Scale Development Procedure
Prior to collecting data, steps were taken to construct a measure of self-guided development. Following the scale development steps recommended by Hinkin (1998) and using the definition of self-guided development, items were culled and adapted from existing literature on related concepts including development, feedback seeking behavior, job crafting, career management, proactive socialization, social capital development behavior, and informal learning. The Noe et al. (1997) taxonomy was used as a basis for organizing the compiled items and writing additional items to make certain that all four components of the taxonomy were represented in the items. This insured that self-guided development was not deficient and was conceptualized in a manner consistent with the broader employee development literature. This process resulted in a 32 item measure.
52
Next, content validity evidence to support these items as indicators of self-guided development was obtained using the approach recommended by Hinkin (1998). A naïve sample of 14 students, faculty members, and working professionals participated in a sorting task. First they were asked to read the definition of self-guided development.
Then they were asked to categorize whether or not they believed each item represented a self-guided development activity based on the provided definition of self-guided development. Items on the survey were randomized for each respondent to eliminate potential response bias that may occur from order effects. Hinkin recommends that items should only be retained if that item has an acceptable agreement index (75%). Each of the
32 items on the survey had at least 75% of these respondents categorize it as a self-guided development behavior indicating that there was agreement that all of the items represented self-guided development activities. See Appendix A for details of the content adequacy results.
The 32 self-guided development items (listed in Table 2, p. 54) were compiled to form a self-guided development scale. Participants rated the extent to which they engaged in each of the 32 behaviors using a 5-point frequency response scale (1 = not at all to 5 = to a great extent). Full survey instructions and items are in Appendix B. Item-level responses were combined into a single additive composite as an overall index of self- guided development. Calculating the score as an additive composite was considered appropriate given the conceptualization of self-guided development as a group of behaviors. Using a single composite of behaviors is consistent with other examples in the development literature wherein overall employee development is the definitional focus
53
Table 2. Self-guided development scale items
To what extent do you find information, learn, and develop skills relevant to your work by..... 1. ... seeking feedback on your performance after assignments? 2. ... introducing new approaches on your own to improve your work? 3. ... listening to a podcast or MP3? 4. ... collaborating with coworkers? 5. ... searching the internet? 6. ...watching a YouTube video or webinar? 7. ... asking others for their opinion of your work? 8. ... taking on additional tasks and responsibilities at work that are not required of you? 9. ... attending professional conferences, seminars or meetings to stay current or get ahead in your line of work? 10. ... using trial and error strategies? 11. ... scanning newspapers, professional magazines or journals? 12. ... reading books? 13. ... asking colleagues for advice? 14. ... reflecting about how to improve your work performance? 15. ... building relationships in the organization which can help to further your career progression? 16. ... spending time and effort networking with others? 17. ... changing the way you do your job to challenge yourself? 18. ... experimenting with new ways of performing your work? 19. ... using your connections and network to make things happen at work? 20. ...reflecting on your own work-related strengths and weaknesses? 21. ... observing others? 22. ... staying well connected with important people? 23. ... building relationships with influential people? 24. ... cultivating and fostering professional relationships through social media such as Facebook, Twitter, or Linkedin)? 25. ... taking a leadership role in situations where there appears to be no leader? 26. ... interacting with your supervisor to learn and help you better perform your job? 27. ...calling on colleagues and associates for support when you really need to get things done? 28. ... talking with others to obtain job relevant information? 29. ... changing minor work procedures that you think are not productive? 30. ... asking your supervisor to coach you? 31. ... spending time developing connections with others? 32. ... seeking out feedback on your performance during assignments?
(e.g., Hurtz & Williams, 2009), rather than delineating specific types of behavior. For example, past research has combined participation in a wide variety of development
54 activities such as, participation in college or continuing education courses, taking different job assignments, consulting with career counselors, and asking for feedback, into a single composite (e.g., Hurtz & Williams, 2009; Maurer et al., 2003). It is important to note, then, that self-guided development emerges from a combination of narrower components, thus functioning as a formative composite variable with individual components that may not always be highly correlated (Maccallum & Browne, 1993; Ones
& Viswesvaran, 1996).
Measures
All other study variables were measured with scales selected from the literature in their respective areas. Established measures were identified by reviewing the literature with respect to each construct and selecting a measure that was frequently used and had high reliability. Scales were also carefully evaluated to assess consistency with the way this research defines the construct. With the exception of the organization commitment scale, these measures were administered with a 5-point Likert-type response scale (1 = strongly disagree and 5 = strongly agree). Organization commitment was measured with a 5-point scale ranging from 1 (not at all) to 5 (extremely). See Appendix C for a complete list of these scales and items.
Proactive personality. Proactive personality was measured using Seibert, Crant, and Kramer's (1999) 10-item version of proactive personality (α = .78). A sample item from this scale is "I am always looking for better ways to do things".
55
Job autonomy. Autonomy was measured using Morgeson and Humphrey's (2006)
9-item measure of job autonomy (α = .93). Decision-making autonomy, work methods autonomy, and work scheduling autonomy were each assessed with 3-items. A sample item from this scale is, "This job gives me considerable opportunity for independence and freedom in how I do the work".
Training climate. Training climate was measured using Tracey and Tews' (2005)
15-item scale of general training climate. There are three dimensions of general training climate (job support, supervisor support, and organization support) represented in the measure. The authors recommend using all 15 items to reflect a one-factor, higher order measure of general training climate(α = .89). A sample item from this scale is, "gaining new information about ways to perform work more effectively is important in this organization".
Supervisor Support. Supervisor support was measured using the 8-item version of
Eisenberger et al.'s (1986) perceived organization support scale (α = .91) with the standard practice of substituting the word “supervisor” for "organization" (e.g.,
Eisenberger, Stinglhamber, Vandenberghe, Sucharski, & Rhoades, 2002; Rhoades &
Eisenberger, 2002). A sample item from this scale is, "My supervisor cares about my general satisfaction at work".
High-quality work relationships. High-quality work relationships was measured using Carmeli, Brueller, and Dutton's (2009) 7-item scale (α = .86). The scale assesses high-quality relationships among coworkers in terms of positive regard and mutuality. A sample item from this scale is "I feel that my co-workers like me".
56
Task interdependence. Task interdependence was measured using Pearce and
Gregerson's (1991) 5-item measure of reciprocal interdependence (α = .79). A sample item from this scale is, "I work closely with others in doing my work".
Organization commitment. Organization commitment was measured using Klein,
Molloy, Cooper, and Swanson's (2011) 4-item measure of commitment (α = .95), using the organization as the target of commitment. A sample item from this scale is, "How committed are you to your organization?"
Learning goal orientation. Learning goal orientation (LGO) was measured using
VandeWalle's (1997) 5-item LGO scale (α = .79). A sample item from this scale is "I enjoy challenging and difficult tasks at work where I'll learn new skills".
Knowledge sharing. Knowledge sharing was measured using de Vries, van den, and de Ridder's (2006) 4-item scale of knowledge donating (α = .84). A sample item includes, "when I’ve learned something new, I tell my colleagues about it."
Performance. Performance was measured by accessing participant performance ratings received during the past year's annual performance review. Performance reviews were conducted by each employee's direct supervisor. Employees were assessed using a
5-point scale (1= did not meet expectations to 5= exceeded expectations) on multiple objectives specific to their position as well as on nine leadership competencies. The task objectives differed in number and content based on each specific position. The leadership competencies were the same for all employees. Some examples of the leadership competencies rated are one's ability to work collaboratively, communicate clearly, solve problems, build customer relationships, pursue opportunities to grow and develop, and
57 embrace change. The ratings for the task specific competencies and the leadership competencies were combined to produce an overall rating out of a total of five points.
The organizations expectation was that most employees would receive at least a “3” rating, indicating that they met expectations.
Control Variables. An individual's need, desire, and ability to engage in self- guided development may vary based on demographic, occupational, and personality variables. Past research has suggested that certain demographic variables partially explain training motivation and participation in training and development activities (Mathieu &
Martineau, 1997; Noe et al., 1997; Tharenou, 1997b). Age, job tenure, and level of education are the most consistently controlled for "third" variables related to training and development behavior (Tharenou, 2001). Age is typically negatively related to participation in traditional training, development, and self-development activities
(Cleveland & Shore, 1992; McEnrue, 1989). Younger employees are more likely to engage in self-guided development because they are accustomed to being resourceful and learning through informal, unstructured methods, while older employees may be more hesitant and less prepared to engage in unstructured learning. Job tenure may also have a negative relationship with self-guided development because the longer someone has been in a position, the more proficient they become in their job and less necessary it becomes to engage in self-guided development to perform well. High levels of educational attainment are also likely to correlate with self-guided development because pursuing educational experiences demonstrates one's past initiative and ability to learn which should relate to their current initiative and ability to learn. In addition, LGO, or one's
58 desire to increase their competence (Dweck, 1986), has been established as a primary predictor of participation in training and development activities. A LGO exerts significant influence on learning and performance outcomes (Payne, Youngcourt, & Beaubien,
2007). Not including these variables that are expected to correlate with one's engagement in self-guided development increases error and leaves open the potential for alternative explanations for the proposed relationships. To more accurately interpret the strength of the relationships observed, age, job tenure, level of education, and LGO will each be controlled for in the analysis if it is significantly correlated with self-guided development or the hypothesized antecedent or outcome of self-guided development.
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Chapter 5: Analysis and Results
The first step after the data collection and cleaning process was complete was to identify if self-guided development occurs in practice, and if so, how frequently. The next step involved computing and examining the descriptive statistics (means and standard deviations) to better understand the nature of the data. Third, the correlations were used to understand the relationships between variables at the most basic level. Lastly, the hypotheses were tested using regression analysis.
The Nature and Occurrence of Self-Guided Development
Before considering how self-guided development relates to other variables or testing the proposed hypotheses, it is necessary to first examine occurrence rates for the
32 behaviors characterized as self-guided development to confirm their existence and prevalence. Results demonstrate that most self-guided development behaviors are quite prevalent. In fact, both surveys indicate that all 32 self-guided development behaviors were used by at least some employees suggesting that it is worthwhile to better understand these behaviors. Appendix D lists all 32 behaviors in rank order based on the highest mean value of usage.
Six behaviors were used to a large extent by a majority of employees. Two themes emerged among these most highly ranked behaviors. Specifically, employees tend
60 to learn from either relationships or reflection. Employees appear to frequently depend on their colleagues and supervisors when they need answers to work-related questions. More specifically, the three behaviors that were used to the greatest extent were, (1) collaborating with coworkers, (2) interacting with a supervisor, and (3) talking with others. Furthermore, calling on colleagues and associates for support, building relationships in the organization to help to further career progression, and asking colleagues for advice, were all self-guided development activities that were used to a very large extent.
Employees also develop themselves internally through introspection. In fact, a great deal of employees indicated that they used reflection to improve their work and develop themselves. More specifically, employees engaged in the following three self- guided development activities to a large extent, (1) reflecting about their strengths and weaknesses, (2) reflecting about how to improve work performance, and (3) observing others.
Even though all of the self-guided development behaviors were used by employees, some were used to a greater extent than others. Watching a video or webinar, listening to a podcast or MP3, and cultivating and fostering professional relationships through social media (such as Facebook, Twitter, or Linkedin), were used very little.
Reading books, scanning professional magazines and journals, and attending professional conferences were also less prevalent than the other behaviors.
The nature of self-guided development can be further understood by analyzing its stability over time. A test-retest reliability coefficient was calculated using responses to
61 the self-guided development scale on Survey 1 and Survey 2. The resulting coefficient was r = .624 (p < .01). Coefficients greater than 0.70 generally indicate that the variable measured is stable (Gliner, et al., 2000). Thus, self-guided development was only moderately stable. Because participants were asked about their general self-guided development behaviors over time, not in a certain time period, test-retest reliability was expected to be higher. There are two possible explanations for these findings. First, this finding is consistent with other research that suggests that employee behaviors are often expected to be only moderately stable over time (Sterman, Cheramie, & Cashen, 2005).
Behaviors, like performance, are likely to change in response to changes in motivation, attitude, or knowledge acquisition. Although participants were asked about their general tendencies over time, self-guided development behaviors that occurred more recently might be more salient and accessible in the respondent's memory and thus be perceived as occurring to a greater extent. Because some of the self-guided development behaviors may be substitutable for one another, it is possible that intra-individual differences between surveys resulted from the participant recalling different experiences more readily at different points in time. Second, the large number of items involved in the measure (32 items) could influence the test retest reliability (Marx, et al., 2003). As the number of items increases, the opportunity to detect differences increases as well. Past research has demonstrated that participation in sixteen different voluntary development activities, half as many as were on the survey for this study, had an acceptable test-retest reliability coefficient (e.g., r = .74; Hurtz & Williams, 2009). Although self-guided development appears to be only moderately stable, the positive, significant correlation between self-
62 guided development on the two surveys suggests that it displays some degree of consistency over time.
Descriptive Statistics
Table 3 (p.64) illustrates the means, standard deviations, and intercorrelations of all study variables. The low means and standard deviations for self-guided development as well as the information found in Appendix D suggest that although the occurrence of self-guided development is high, many of the behaviors are not being engaged in to a great extent. The means and standard deviations for self-guided development measured at two different times were quite similar (i.e., Survey 1 M = 97.4, SD = 16.2; Survey 2, M =
98.4, SD = 16.1). This reiterates that employees engage in self-guided development to a similar extent over time.
All of the proposed antecedents of self-guided-development (i.e., proactive personality, job autonomy, and training climate) and some of the control variables (i.e., job tenure, and LGO) were significantly correlated with self-guided development. The relationship between task-interdependence and self-guided development was also found to be positive and significant (r = .21, p < .10). Task interdependence was hypothesized to moderate the relationship between self-guided development and knowledge sharing such that knowledge sharing would be increased. Given the prevalence of relationship- based self-guided development, this significant correlation suggests that task interdependence might not only influences knowledge sharing after the occurrence of self-guided development, but also the occurrence of self-guided development itself.
63
Table 3. Study variable means, standard deviations, and zero-order correlations
n Mean(SD) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1. Age (yrs) 102 42.3 (11.0) 2. Education a 102 2.41 (1.1) -.06 3. Job tenure (yrs) 96 4.21 (6.7) .45** -.19 4. Learning goal 101 4.04 (.47) -.08 .20 -.24* orientation 5.Proactive 101 3.67 (.41) -.08 .26* -.20† .70** Personality 6. Job Autonomy 102 4.09 (.57) .17† .14 .15 .40** .33**
64 7. Training Climate 99 3.66 (.51) -.16 .04 -.10 .42** .37** .45** 8. SGD Survey 1 103 97.4 (16.2) -.14 .06 -.23* .50** .47** .22* .43**
9. SGD Survey 2 76 98.4 (16.1) -.09 .17 -.29* .55** .56** .09† .39** .62** 10. Supervisor 76 4.03 (.67) -.15 .32* -.15 .14 .16 .23† .33* .00 .24* Support * * 11. Org. 76 4.53 (.55) .30** .08 .14 .12 .08 .22† .22† .19 .30** .19 Commitment 12. High Quality 76 3.79 (.51) .10 -.05 .08 -.15 .07 .00 .08 .06 .15 .10 .23* relationships 13.Task 76 4.23 (.54) .18 .15 .10 .21† .11 .30* .09 .21† .39** .29* .43** .09 interdependence 14.Performance 86 3.43 (.56) .17 .25* -.03 .27* .18† .12 .19 .13 .23† .31* .07 .04 .18 15. Knowledge 76 4.03 (.52) .19† -.13 .14 .15 .28* .07 .20 .15 .42** .12 .38** .29* .25* .11 Sharing Note. ** p < .01, * p <.05, †p < .10. SGD = self-guided development. a Education 0=high school, 1= some college, 2=technical/associates degree, 3=bachelors degree, 4=masters degree N= ranged from 64-102 using all available data for each measure
With respect to the outcome variables, the bivariate relationship was significant and positive for self-guided development and task performance (r = .23, p < .10), but not knowledge sharing. Interestingly, the two variables hypothesized to moderate the relationship between self-guided development and knowledge sharing were significantly correlated with knowledge sharing. High-quality relationships correlated r = .29 (p < .05) with knowledge sharing and task interdependence correlated r = .25 (p < .05) with knowledge sharing indicating that the effect of self-guided development on knowledge sharing may operate via high-quality relationships and task interdependence. Similarly, the significant bivariate relationship between supervisor support and performance indicates that supervisor support may be a necessary condition for self-guided development to affect performance.
Job tenure and LGO were both significantly correlated with self-guided development, and thus both of these variables will be controlled for when testing all of the hypotheses. Further, education was significantly correlated with both proactive personality and performance, necessitating that education be controlled for when testing hypotheses containing these two variables. Lastly, age was significantly correlated with both job autonomy and knowledge sharing. Age will be controlled for when testing hypotheses containing these two variables.
Hypothesis Testing
All hypotheses were tested using hierarchical regression analysis (Kerlinger &
Lee, 2000). For Hypotheses 1-5, self-guided development from Survey 2 served as the
65 dependent variable; self-guided development from Survey 1 served as the independent variable for the remaining hypotheses. For each hypothesis, control variables were entered in step one, the proposed main effects in step two, and when relevant, the hypothesized interaction in step three. When testing the moderator hypotheses, the independent variables were centered to reduce multicollinearity (Cohen, Cohen, West, &
Aiken, 2003). All results were interpreted by reviewing r-squared values and the change in r-squared values to consider the amount of variance accounted for by the variables and standardized beta weights to assess the strength of each relationship. Effects which are in the hypothesized direction (i.e., positive) and statistically significant will be used as support for the research hypothesis.
A post-hoc power analysis suggested that an n = 69 offers appropriate statistical power for testing some of the hypothesized effects, but not others. With α = .05, a sample size of 69 provides adequate statistical power (1-β >.95) for testing equations with up to six predictors in the case of a large effect size (i.e., 0.35; Cohen, 1988). It does not provide adequate statistical power for detecting significance (even with the minimum number of predictors) in the case of a small or medium effect size (i.e., 0.02 or 0.15, respectively; Cohen, 1988). This means that these results are at high risk for Type II error, or failing to reject the null hypothesis when the effect size is small or medium, because the power is not adequate for detecting significant results.
The adoption of α = .05 or lower as a cutoff for determining the significance of results minimizes the risk of Type I error, or accepting a false hypothesis. Although α
<.05 is often considered acceptable, it is an arbitrary value that is not appropriate for all
66 research (Stigler, 2008). A less stringent level for determining significance is appropriate to use in preliminary research where the results are a precursor to additional research, as is the case with this study (Bartlett, et al., 2001). For this reason, α < .10 was adopted when evaluating these results as a method to increase power. With α = .10, a sample size of 69 provides adequate statistical power for detecting an effect size of .16, .20, and .23 with one, two, or three, predictors, respectively.
Interaction effects are even more demanding than main effects in terms of the sample size required to achieve adequate power. The additional power required for testing a multiplicative effect is substantially higher than for testing a main effect because of the additional measurement error associated with the interaction term (Aiken, West, &
Reno, 1991). The reliability of the product term created to test the interaction is a function of the reliabilities of the individual predictors. Because predictors have less than perfect reliability, the interaction term is even more unreliable. When moderated multiple regression is used to test an interaction, the low reliability associated with the interaction term results in wider confidence intervals, thus, decreasing statistical power (Ree &
Caretta, 2002). Consequently, a sample that is significantly larger than 69 is necessary to achieve sufficient statistical power to detect a moderated effect.
Antecedents of Self-Guided Development
Results for Main Effects
Hypothesis 1, 2, and 4 posited that proactive personality, job autonomy, and training climate would be positively related to self-guided development. Table 4 (p.68)
67
Table 4. Main effect antecedents of self-guided development
STEP 1 STEP 2 n R2 β R2 ΔR2 β Job Tenure 67 .320** -.122 .394 .074** -.132 LGO .510** .283* Education .019 -.001 Proactive Personality .356**
Job Tenure 66 .326** -.155 .326 .00 -.155 LGO .516** .516** Age .066 .179 Job Autonomy .000
Job Tenure 67 .320** -.123 .396 .076** -.109 LGO .514** .461** Training Climate .282**
presents the results of three hierarchical regression analyses wherein self-guided
development was regressed on each of these variables, after controlling for the relevant
control variables. Hypotheses 1 and 4 were supported. Both proactive personality and
training climate were significant predictors of self-guided development. The addition of
proactive personality into the regression model produced a significant change in r-
squared (ΔR2=.074). In addition, the strength of the relationship between proactive
personality and self-guided development was strong and significant (β=.356, p < .01).
Training climate also explained a significant amount of incremental variance (ΔR2=.076)
and demonstrated a relationship with self-guided development that was strong and
significant (β=.282, p < .01). Thus, both proactive personality and a supportive training
climate appear to support and facilitate employees engaging in self-guided development.
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In contrast, Hypothesis 2 was not supported. Although the bivariate relationship between job autonomy and self-guided development was significant (r = .09, p < .10), job autonomy did not emerge as a significant predictor and failed to explain a significant amount of incremental variance (ΔR2=.00) when controlling for job tenure, LGO, and age.
Results for the Interaction Effects
Hypotheses 3 and 5 proposed that job autonomy and training climate would moderate the relationship between proactive personality and self-guided development.
Table 5 (p. 70) presents the results of two hierarchical regressions wherein self-guided development was regressed on proactive personality and the interaction of proactive personality with job autonomy and with training climate, after controlling for the necessary control variables. The interaction terms failed to significantly predict self- guided development and the addition of the interaction terms into the equation did not explain a significant amount of incremental variance for job autonomy (ΔR2=.01) or training climate (ΔR2=.00). Hypotheses 3 and 5 were not supported. This analysis does offer further evidence to support Hypotheses 1 and 4 by demonstrating that even when proactive personality and training climate are included in the same regression analysis, each still produces a significant, positive, main effect with self-guided development.
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Table 5. Interaction effect antecedents of self-guided development
STEP 1 STEP 2 STEP 3 n R2 β R2 ΔR2 β R2 ΔR2 β Job Tenure 66 .327** -.153 .406 .079 -.175 .420 .014 -.182 LGO .511** .279* .292* Education .022 .000 .012 Age .064 .102 .144 Proactive Personality .372** .388** Job Autonomy -.020 -.005 Proactive Personality x -.123 Job Autonomy
Job Tenure 67 .320 -.122 .441 .121** .253 .442 .001 -.117 LGO .510** .282* .285* Education .019 .029 .023 Proactive Personality .280* .281* Training Climate .231* .230* Proactive Personality x .027 Training climate
Outcomes of Self-Guided Development
Results for Main Effects
Hypotheses 6 and 8 proposed that self-guided development would be positively related to task performance and knowledge sharing. Table 6 (p.71) presents the results of two hierarchical regression analyses wherein task performance and knowledge sharing were regressed on self-guided development, after controlling for the necessary control variables. Self-guided development did not emerge as a significant predictor of performance or knowledge sharing and failed to explain a significant amount of incremental variance (ΔR2= .017 and .019, respectively). Thus, Hypotheses 6 and 8 were not supported.
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Table 6. Main effect of self-guided development on performance and knowledge sharing
Performance STEP 1 STEP 2 n R2 β R2 ΔR2 β Job Tenure 61 .063 .062 .080 .017 .078 LGO .204 .116 Education .124 .137 SGD .157 Knowledge STEP 1 STEP 2 Sharing n R2 β R2 ΔR2 β Job Tenure 61 .089 .127 .108 .019 .126 LGO .212 .151 Age .187 .208 SGD .154
Results for Interaction Effects
Hypotheses 7a and 7b proposed that perceived supervisor support and organization commitment would moderate the relationship between self-guided development and task performance. Hypotheses 9a and 9b proposed that high-quality relationships and task interdependence would moderate the relationship between self- guided development and knowledge sharing. Tables 7 and 8 (p.72) present the results of four hierarchical regressions wherein task performance and knowledge sharing were both regressed on self-guided development and the interaction of self-guided development with the four proposed moderator variables, after controlling for the necessary control variables. All of the interaction terms failed to reach significance. Neither perceived supervisor support (ΔR2=.034 β=.19), nor organizational commitment (ΔR2=.003 β=.01) moderated the relationship between self-guided development and task performance.
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Similarly, neither high quality relationships (ΔR2=.004 β=.074), nor task interdependence
(ΔR2=.027 β=.169) were found to moderate the relationship between self-guided development and knowledge sharing.
Table 7. Hypothesized moderated effects on performance
STEP 1 STEP 2 STEP 3 n R2 β R2 ΔR2 β R2 ΔR2 β Job Tenure 61 .063 .062 .157 .093* .109 .191 .034 .100 LGO .204 .144 .149 Education .124 .058 .035 SGD .103 .111 Supervisor Support .295* .334* SGD x Supervisor .190 Support
Job Tenure 61 .063 .062 .080 .016 .080 .080 .003 .080 LGO .204 .115 .117 Education .124 .138 .137 SGD .160 .158 Org. Commitment -.004 -.001 SGD x Org. .011 Commitment
Table 8. Hypothesized moderated effects on knowledge sharing
STEP 1 STEP 2 STEP 3 n R2 β R2 ΔR2 β R2 ΔR2 β Job Tenure 67 .089 .127 .191 .102* .127 .195 .004 .132 LGO .212† .210 .202 Age .187 .179 .190 SGD .108 .111 High Quality .295* .255† Relationships SGD x High Quality .074 Relationship
Job Tenure 67 .089 .127 .125 .036 .114 .152 .027 .138 LGO .212† .124 .163 Age .187 .166 .158 SGD .121 .104 Task Interdependence .144 .154 SGD x Task .169 Interdependence
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Chapter 6: Discussion and Conclusion
Discussion
The purpose of this dissertation was to introduce self-guided development as a proactive approach to employee development and begin to establish its nomological network. Self-guided development proved to be very prevalent in the workplace, highlighting the importance of beginning to understand its antecedents and consequences.
In fact, all 32 self-guided behaviors were used by employees to at least some degree. A majority of employees used the six most common behaviors, consisting of a mix of relationship-based self-guided development as well as reflection and introspection.
Results suggest that certain individual differences and situational variables influence the occurrence of self-guided development, while others do not. Proactive personality was significantly related to self-guided development. Those individuals with a propensity to behave proactively were more likely to engage in self-guided development behaviors. This effect maintained significance even when controlling for another individual difference, LGO. LGO was included as a control variable, but might be more appropriately positioned as a primary antecedent given its strong, significant correlation with self-guided development, as well as strong theory to support LGO as a more focal independent variable. Individuals with a high LGO are more likely to engage in self-guided development because they (1) have a tendency to seek out opportunities to
73 learn in various situations (Hurtz & Williams, 2009), (2) are motivated to develop work- relevant skills, and (3) have the ability to adapt to new situations on their own, each of which increase the likelihood of self-guided development. In fact, research has shown that LGO positively relates to the use of cognitively-oriented learning strategies, motivation to learn and learning-related behaviors such as participating in development work-related activities (Colquitt & Simmering, 1998; Hurtz & Williams, 2009; Payne et al., 2007).
Training climate was also significantly related to self-guided development.
Consistent with expectations, results showed that self-guided development occurs to a greater extent when employees perceive their management, work, and organization as supportive of formal and informal training and development activities (Tracey & Tews,
2005). Supportive training climates create an environment where continuous learning is valued, high performance is emphasized, and on-the-job learning and skill acquisition are encouraged. In fact, this type of environment may not only facilitate the occurrence of self-guided development, it might also necessitate that self-guided development occurs.
Results did not support the proposed main effects between job autonomy, task performance, knowledge sharing, and self-guided development. Similarly, support was not found for any of the proposed moderator effects. However, these results should be considered inconclusive because of the lack of power to detect small to medium effect sizes and interactions. The sample was not large enough to offer sufficient statistical power to render convincing tests of these relationships, especially in the case of the hypothesized interaction effects. Researchers are frequently unsuccessful at finding
74 statistically significant moderating effects because interactions that manifest small to medium effect sizes are the most prevalent, and it is these effects that require the most power (Cohen, et al., 2003; Cronbach, 1987). Given this, it is premature to conclude that the failure to reject the null hypothesis in this study implies that these variables do not manifest meaningful relationships with self-guided development. The lack of power suggests that such a conclusion risks committing a Type II error.
Conclusion
This dissertation contributes to the development literature by re-conceptualizing the way employee development is regarded to include learner-centric, learner-controlled methods of development. Self-guided development is offered as a framework to more appropriately match the literature on employee development with how employee development is occurring in organizations today. The remainder of this chapter will address the theoretical and empirical implications, as well as the limitations associated with this research. In addition, future research directions will be put forth.
Theoretical Implications
This research advances development theory in multiple ways. First, this research represents a first step toward understanding the nature of self-guided development. By constructing a means for measuring and documenting it, this study demonstrated that self-guided development is a phenomenon that occurs in the workplace. Past research on employee development has been slow to conceptualize the innovative and creative ways in which employees have taken responsibility for their own learning and development.
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Self-guided development broadens the way we think about training and development from traditional, formal, structured interventions to informal, nontraditional methods in order to further advance the transition of training and development theory from instructor-focused to learner-focused development, wherein learners have an active, integral role and are responsible for their own learning and development.
Self-guided development integrates different proactive employee development behaviors within a single, theoretical framework. Rather than pursuing different types of proactive development behaviors in isolation as is currently being done, this research reduces the associated redundancy by examining a collection of behaviors that represent a more basic behavior. This clarification provides an initial conceptual framework for identifying what constitutes self-guided development for the purpose of building theory concerning those individual and contextual differences likely to influence its occurrence.
Further, combining a set of behaviors that conceptually belong together reduces the likelihood of omitted variable bias. Thus, this integrative view of employee development provides a holistic, parsimonious conceptualization of proactive employee development behaviors that is relevant for today's workplace.
Lastly, this dissertation contributes to the evolving literature on proactive personality. To date, research on proactive personality has progressed independent of the development literature. This research advances theory surrounding proactive personality by establishing self-guided development as an important outcome variable, thus providing a basis and need for additional exploration of this relationship. To more fully understand the relationship between proactive personality and other constructs in the
76 literature, self-guided development should not be ignored. It is possible that self-guided development is the explanatory mechanism through which proactive personality influences other outcomes.
Practical Implications
Organizations spend millions of dollars on formal training and development practices. Although these methods of development are often valuable, they are also costly, and in some cases, impossible to initiate by the organization. Moreover, formal programs alone may not be sufficient for developing employees in dynamic work environments (Tannenbaum, Beard, McNall, & Salas, 2010). This research demonstrates that self-guided development is extremely prevalent in the workplace. Employees are building their own human capital by voluntarily seeking out unstructured learning activities that are not operationally or administratively provided by the organization.
Therefore, it is in the organization's best interest to understand employee choices about unstructured learning to leverage these behaviors as part of a broader training and development strategy.
This research provides a basis for organizations to begin exploring methods for enhancing and facilitating self-guided development as a means to build human capital.
Organizations interested in promoting these behaviors can help to ensure that employees are aware of the availability of non-traditional methods for learning and developing themselves. Making informal opportunities salient will increase the occurrence of the behaviors. This mirrors traditional development research which suggests that the main
77 predictor of voluntary participation in formal development opportunities is employees being aware that the opportunities exist. Another way to promote self-guided development is to seek out employees who have a propensity to behave in a proactive manner and are LGO. This is especially true for positions that require the employee to access information and solve problems on their own. Organizations can also begin to design work roles that are supportive of self-guided development. For example, to facilitate relationship-based self-guided development behaviors, companies might restructure jobs to increase task interdependence among employees. These already naturally occurring forms of self-guided development might be more readily available to employees who work in teams or who actively engage in networking behaviors. To facilitate the use of more introspective self-guided development behaviors, organizations can encourage employees to reflect about their accomplishments, career direction, strengths and weaknesses, and performance. Companies may even consider using goal- setting initiatives as a way to encourage personal reflection as a method self-guided development. Lastly, a supportive training climate will help to facilitate the occurrence of self-guided development even further. In organizations that value learning, emphasize higher performance, and expect employees to acquire and transfer new knowledge and skills to their work, a supportive training climate ensues that promotes self-guided development.
Limitations
This dissertation is not without its limitations. The main limitation in this research is the small sample size. The resulting reduction in power to detect a significant effect
78 greatly limits the ability to draw conclusions on the basis of these data. Many of the relationships proposed are at risk for Type II error. Thus, replicating this study with a larger sample is critical for confirming or disconfirming the results observed. A larger sample would increase the statistical power and provide more interpretable results. A sample of about 200 people would be necessary for detecting both small and medium effects, as well as medium-sized interactions, with α = .05 and four predictors, as is the case in most of the analyses when accounting for control variables (Champoux & Peters,
1987; Cohen et al., 2003).
Second, the results for the relationship between self-guided development and performance might be influenced by range restriction associated with the measure of task performance. Even though overall performance ratings were scored from one to five, the range of ratings was only three to five. Most employees received a three or four. More specifically, 61% received a three, 36% received a four, and 3% received a five. Thus, there was not enough variance for precisely estimating the effect of self-guided development on task performance. This may explain why a small bivariate effect was detected in the correlation matrix for these two variables, but that effect failed to reach significance in the regression analyses after controlling for job tenure, LGO, and education.
Third, in this research proactive personality and LGO emerged as two individual differences that are both strong, positive, significant predictors of self-guided development. However, these two variables were also very highly correlated.
Specifically, the correlation between proactive personality and LGO was r = .699 (p <
79
.01). When corrected for unreliability, that value reaches r = .815 (p < .01). This suggests that individuals who have a proactive personality are also likely to have a learning goal orientation. The fact that the correlation was significant is not surprising considering both constructs represent a willingness and desire to identify and take advantages of opportunities. However, the strength of the correlation was surprising. LGO refers specifically to enjoying challenges and taking risks to promote learning, while proactive personality refers more broadly to making positive changes to life in general. Past research using the same two measurement instruments reported a correlation between proactive personality and LGO of r = .25 (p < .01) (Brown & O'Donnell, 2011).
The exceedingly high correlation found in this research indicates that there is a large amount of redundancy in responses to these measures and that inclusion of both variables in the regression model risks a high degree of multicollinearity.
Multicollinearity decreases the precision of the parameter estimates because of the shared variance accounted for by the independent variables. More precise parameter estimates with lower standard errors can be obtained by increasing power (Mason, 1991). Thus, collecting additional data and increasing the sample size may partially remedy the problem (Cohen, Cohen, Aiken, & West, 2003).
Fourth, the external validity of these results might come into question because the data come from only one organization. Additional insight would be provided by collecting data from multiple organizations to determine whether these results are generalizable to employees in different organizations, careers, locations and cultures.
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This research does alleviate some of this concern because data were collected from employees with different jobs in different locations. Nonetheless, all employees in the sample were from one organization.
Future Research
This research provides a foundation for additional research related to self-guided development. First and foremost, this study should be replicated with a larger sample for the purpose of continuing to establish a nomological network for self-guided development. The various relationships proposed require additional exploration. It would seem particularly critical to have a better understanding of if and how self-guided development influences outcomes valued by organizations. Future research can use structural equation modeling to test the fit of an entire model of self-guided development.
Testing the fit of a model with all variables in the same analysis will offer a more fine- grained, sophisticated, understanding of its nomological network and will further clarify the nature of self-guided development and its relationships with other constructs. Thus, research should continue to explore the relationships hypothesized in this dissertation to produce more conclusive results.
Second, additional antecedents should be considered. For example, other variables, like career commitment, are likely to influence engagement in self-guided development. Career commitment refers to one’s commitment or dedication to his/her career, profession or occupation (Blau, 1985). Choosing to dedicate oneself to a certain profession suggests that employees will choose to develop knowledge and skills relevant
81 to that occupation. Individuals committed to their career will allocate additional energy and effort to seek out new knowledge and skills relevant to a job with which they are committed.
Similarly, additional outcomes, like employee engagement, should also be considered. Employee engagement refers to an employee's choice to bring attention and energy to work roles and task behaviors. When employees are engaged, they are physically, cognitively and emotionally connected to work. Self-guided development likely relates to engagement because it offers a safe environment for learning that allows employees to find solutions to problems, learn, and develop themselves without the structure and pressure associated with formal learning environments and assessments.
When engaging in self-guided development, employees experience few boundaries or constraints, an experience that can foster confidence. Self-guided development increases employee dignity and self-appreciation as they successfully navigate the challenge of developing themselves and enhancing their qualifications to perform. These characteristics of self-guided development represent the psychological conditions necessary for employee engagement to result (Kahn, 1990). After partaking in self- guided development employees should be enthusiastic and feel positive about their job while also focusing a great deal of attention on their job.
Future research should also measure self-guided development repeatedly to continue to examine the nature of self-guided development and its stability over time. It would be interesting to identify if, why, and when self-guided development is more or less stable over time. This might require a longitudinal study that asks employees to keep
82 a daily log of the self-guided development behaviors they engaged in, and the reason for engaging in the behavior. Identifying the different motivators behind engagement in these behaviors might help explain its consistency, or lack thereof, over time.
The nature of self-guided development can be further understood by continuing to explore whether a univariate factor structure is appropriate, as was determined in this research. Although all 32 self-guided development behaviors share common characteristics, the items with the lowest factor loadings consisted of utilizing external resources as a tool for self-guided development. For example, scanning newspapers, reading books, using social media, watching a video or webinar and listening to an MP3 or podcast were among the items with the lowest factor loadings, and were also among the items with the lowest rank of usage. It is possible that there is something fundamentally different about these types of self-guided development, and should be further explored.
Future research should also explore whether self-guided development is only an individual level phenomenon, or whether it can occur at the team level as well. Other proactive behaviors (e.g., job crafting) have been suggested to exist at both the individual and team level (Leanna, 2009). Additional research could ask each team member about the extent to which their team engages in different self-guided development behaviors and then aggregate those scores to compare across different teams.
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References
Aguinis, H., & Kraiger, K. (2009). Benefits of training and development for individuals
and teams, organizations, and society. Annual Review of Psychology, 60, 451-474.
Aiken, L.S., West, S.G., & Reno, R.R., (1991). Multiple Regression: Testing and
interpreting interactions. Sage Publications Inc., Thousands Oak, CA.
Allen, T. D., & Rush, M. C. (1998). The effects of organizational citizenship behavior on
performance judgments: A field study and a laboratory experiment. Journal of
Applied Psychology, 83, 247–260.
Antonacopoulou, E. P. (2000). Employee development through self-development in three
retail banks. Personnel Review, 29(4), 491.
Ashford, S. J., Blatt, R., & VandeWalle, D. (2003). Reflections on the looking glass: A
review of research on feedback-seeking behavior in organization. Journal of
Management, 29, 773–799.
Ashford, S. J., & Cummings, L. L. (1983). Feedback as an individual resource: Personal
strategies of creating information. Organizational Behavior and Human
Performance, 32, 370–398.
Baldwin, T., & Ford, J. K. (1988). Transfer of training: A review and directions for future
research. Personnel Psychology, 41, 63-105.
Baldwin, T. T., & Magjuka, R. J. (1997). Training as an organizational episode:
Pretraining influences on trainee motivation. In J. K. Ford, S. W. J. Kozlowski, K.
84
Kraiger, E. Salas, & M. S. Teachout (Eds.), Improving training effectiveness in
work organizations (pp. 99–127). Mahwah, NJ: Erlbaum.
Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, N.J.: Prentice-Hall.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist,
37, 122-147.
Barber, J. (2004) ‘Skill upgrading within informal training: lessons from the Indian auto
mechanic’, International Journal of Training and Development, 8(2), 128-139.
Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of
Management, 17, 99–120.
Barrick, M.R., & Mount, M.K. (1993). Autonomy as a moderator of the relationship
between the Big Five personality dimensions and job performance. Journal of
Applied Psychology, 78, 111-118.
Bartlett, J.E. II., Kotrlik, J.W., Higgins, C.C., (2001). Organizational Research:
Determining appropriate sample size in survey research. Information Technology,
Learning, and Performance Journal, 19(1), 43-50.
Bauersfeld, H. (1995). ‘Language Games’ in the mathematics classroom: Their function
and their effects. In P. Cobb & H. Bauersfeld (Eds.), The emergence of
mathematical meaning: Interaction in classroom cultures (pp. 211-292). Hillsdale,
NJ: Lawrence Erlbaum.
Baumgartel, H., Reynolds, M., & Pathan, R. (1984). How personality and organizational-
climate variables moderate the effectiveness of management development
85
programs: A review and some recent research findings. Management and Labor
Studies, 9, 1-16.
Bear, D.J., Tompson, H.B., Morrison, C.L., Vickers, M., Paradise, A., Czarnowsky, M.,
Soyars, M., & King, K. (2008). Tapping the potential of informal learning. An
ASTD research study. Alexandria, VA: ASTD.
Becker, G. (1964). Human capital : a theoretical and empirical analysis, with special
reference to education. New York: National Bureau of Economic Research;
distributed by Columbia University Press.
Bell, B., & Kozlowski, S.W.J. (2008). Active learning: Effects of core training design
elements on self-regulatory processes, learning, and adaptability. Journal of Applied
Psychology, 93, 296–316.
Benson, G., Finegold, D., & Mohrman, S. (2004). You paid for the skills, now keep
them: Tuition reimbursement and voluntary turnover. Academy of Management
Journal, 47, 315-331.
Berg, J. M., Grant, A. M., & Johnson, V. (2010). When callings are calling: Crafting
work and leisure in pursuit of unanswered occupational callings. Organization
Science, 21, 973-994.
Berman, S. L., Down, J., & Hill, C. W. L. (2002). Tacit Knowledge as a Source of
Competitive Advantage in the National Basketball Association. Academy of
Management Journal, 45(1), 13-31.
Bettenhausen, K. & Fedor, D. (1997). Peer and upward appraisal: A comparison of their
benefits and problems. Group and Organization Management, 22, 236- 263.
86
Birdi, K., Allan, C., & Warr, P. (1997). Correlates and perceived outcomes of four types
of employee development activity. Journal of Applied Psychology, 82, 845–857.
Blau, P. M. (1964). Exchange and power in social life. New York: Wiley.
Blau, G.J. (1985). The measurement and prediction of career commitment. Journal of
Vocational Behavior, 32, 284-297.
Bowler, W.M. & Brass, D.J.(2006). Relational Correlates of Interpersonal Citizenship
Behavior: A Social Network Perspective. Journal of Applied Psychology, 91(1), 70-
70-82.
Brown, S., & O'Donnell, E. (2011). PROACTIVE PERSONALITY AND GOAL
ORIENTATION: A MODEL OF DIRECTED EFFORT. Journal Of Organizational
Culture, Communications & Conflict, 15(1), 103-119.
Brown, K.G., & Van Buren, M.E., (2007). Applying a social capital perspective to the
evaluation of distance training. In M. Stephen & E. Salas (Eds), Toward a science
of distributed learning (p. 41-63). Washington, DC, US: American Psychological
Association.
Campbell, D. J. (2000). The proactive employee: Managing workplace initiative.
Academy of Management Executive, 14, 52–66.
Campion, M. (1988). Interdisciplinary Approaches to Job Design: A Constructive
Replication With Extensions. Journal of Applied Psychology, 73(3). 467-481.
Carmeli, Brueller & Dutton (2009). Learning behaviors in the workplace- the role of
high-quality interpersonal relationships and psychological safety. Systems research
and behavioral science, 26, 81-98.
87
Champoux, J. E., & Peters, W. S. (1987). Form, effect size and power in moderated
regression analysis. Journal Of Occupational Psychology, 60(3), 243-255.
Chen, X., Hui, C., & Sego, D. J. (1998). The role of organizational citizenship behavior
in turnover: Conceptualization and preliminary tests of key hypotheses. Journal of
Applied Psychology, 83, 922–931.
Chen, G., & Klimoski, R. J. (2007). Training and development of human resources at work:
Is the state of our science strong? Human Resource Management Review, 17, 180-190
Chiaburu, D. S., & Harrison, D. A. (2008). Do peers make the place? Conceptual
synthesis and meta-analysis of coworker effects on perceptions, attitudes, OCBs,
and performance. Journal of Applied Psychology, 93, 1082-1103.
Cleveland, J. N., & Shore, L. M. (1992). Self and supervisory perspectives on age and
work attitudes and performance. Journal of Applied Psychology, 77, 469 484.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (second
edition), Hillsdale, NJ: Earlbaum Associates.
Cohen, J., Cohen, P., West, S.G., & Aiken, L.S. (2003). Applied Multiple
Regression/Correlation Analysis for the Behavioral Sciences (Third Edition).
Lawrence Erlbaum Associates, Mahwau: NJ.
Colquitt, J., LePine, J., & Noe, R. (2000). Toward an integrative theory of training
motivation: A meta-analytic path analysis of 20 years of research. Journal of
Applied Psychology, 85, 678-707.
88
Colquitt, J.A, & Simmering, M.S. (1998). Conscientiousness, goal orientation, and
motivation to learn during the learning process: A longitudinal study. Journal of
Applied Psychology, 83, 654-665.
Conlon, T.J. (2003). A review of informal learning literature, theory, and implications for
practice in developing global professional competence. Journal of European
Industrial Training, 28, 283-295.
Cooper C., & Kurland, N.B. (2002). Telecommuting, professional isolation and employee
development in public and private organizations. Journal of Organizational
Behavior, 23(4), 511-532.
Crant, J. M. (2000). Proactive behavior in organizations. Journal of Management, 26,
435–462.
Cronbach, L.J. (1987) Statistical tests for moderator variables: Flaws in analyses recently
proposed. Psychological Bulletin, 102, 414-417.
Cronbach, L., & Meehl, P. (1955). Construct validity in psychological tests,
Psychological Bulletin, 52, 4, 281-302.
Cseh, M., Watkins, K.E., & Marsick, V.J. (1999) ‘Reconceptualizing Marsick and
Watkins’s model of informal and incidental learning in the workplace’, in K.P.
Kuchinke (Ed.): Proceedings, Academy of Human Resource Development
Conference, Academy of Human Resource Development, Baton Rouge, LA, Vol. 1,
pp.349–356.
Cudeck R. (2000) Exploratory Factor Analysis. In Tinsley H.E.A, Brown S.D (ed)
Applied Multivariate Statistics and Mathematical Modeling. USA: Academic Press.
89
Cummings, J. N. (2004). Work groups, structural diversity, and knowledge sharing in a
global organization. Management Science, 50(3), 352-364.
De Stobbeleir, K., Ashford, S. J., & Buyens, D. (2011). Self-regulation of creativity at
work: the role of feedback-seeking behavior in creative performance. Academy of
Management Journal. 54 (4), 811 - 831. de Vries, R., E. , van den Hooff, B., & de Ridder, J., A. (2006). Explaining knowledge
sharing: The role of team communication styles, job satisfaction, and performance
beliefs. Communication Research, 33(2), 115-135.
Deckop, J. R., Mangel, R., & Cirka, C. C. (1999). Getting more than you pay for:
Organizational citizenship behavior and pay-for-performance plans. Academy of
Management Journal, 42, 420–428.
Dragoni, L., Tesluk, P., Russell, J., & Oh, I. (2009). Understanding managerial
development: Integrating developmental assignments, learning orientation, and
access to developmental opportunities in predicting managerial competencies.
Academy of Management Journal, 52, 731-743.
Dreher, G. F., & Ash, R. M. (1990). A comparative study of mentoring among men and
women in managerial, professional, and technical positions. Journal of Applied
Psychology, 75, 539–546.
Dweck, C.S. (1986). Motivational Processes affecting learning. American Psychologist,
41, 1040-1048.
Dweck, C. S. (1989). Motivation. In A. Lesgold & R. Glaser (Eds.), Foundations for
psychology of education (pp. 87–136). Mahwah, NJ: Erlbaum.
90
Dziuban, C. D., & Shirkey, E. C. (1974). When is a correlation matrix appropriate for
factor analysis? Psychological Bulletin, 81, 358-361.
Eisenberger, R., Fasolo, P., & Davis-LaMastro, V. (1990). Perceived organizational
support and employee diligence, commitment, and innovation. Journal of Applied
Psychology, 75, 51-59.
Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D. (1986). Perceived
organizational support. Journal of Applied Psychology, 71, 500–507.
Eisenberger, R., Stinglehaumber, F., Vandenberghe, C., Sucharski, I. L., & Rhoades, L.
(2002). Perceived supervisor support: Contributions to perceived organizational
support and employee retention. Journal of Applied Psychology, 87, 565–603.
Ellinger, A.D. (2005). Contextual factors influencing informal learning in a workplace
setting, Human Resource Development Quarterly, 16(3), 389-415.
Eraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education,
26(2), 247-247-273.
Facteau, J. D., Dobbins, G. H., Russell, J. E. A., Ladd, R. T., & Kudisch, J. D. (1995).
The Influence of General Perceptions of the Training Environment on Pretraining
Motivation and Perceived Training Transfer. Journal of Management, 21, 1.
Ferris, G. R., Treadway, D. C., Perrewe, P. L., Brouer, R. L., Douglas, C., & Lux, S.
(2007). Political skill in organizations. Journal of Management, 33, 290–320.
Foss, N. J., Minbaeva, D. B., Pedersen, T., & Reinholt, M. (2009). Encouraging
knowledge sharing among employees: How job design matters. Human Resource
Management, 48, 871-893.
91
Frese, M.. Fay, D., Hilburger. T.. Leng, K., & Tag, A. (1997). The concept of personal
initiative: Operationalization, reliability and validity in two German samples.
Journal of Occupational and Organizational Psychology, 70, 139-161.
Fuller Jr., J., Kester, K., & Cox, S. S. (2010). Proactive Personality and Job Performance:
Exploring Job Autonomy as a Moderator. Journal Of Managerial Issues, 22(1), 35-
51.
Gagne, R. M. (1962). Psychological Principles in System Development. New York: Holt,
Rinehart and Winston, Inc.
Gagné, R. M. (1985). The conditions of learning (4th ed.). New York: Holt, Rinehart &
Winston.
Gagne, M. (2003). The role of autonomy support and autonomy orientation in prosocial
behavior engagement. Motivation and Emotion, 27, 199-223.
Ghitulescu, B. (2006). Job crafting and social embeddedness at work. Unpublished
doctoral dissertation, University of Pittsburgh.
Gist, M. E., Stevens, C. K., & Bavetta, A. G. (1991). Effects of self-efficacy and post-
training intervention on the acquisition and maintenance of complex interpersonal
skills. Personnel Psychology, 44, 837-861.
Gliner, J.A., & Morgan, G.A. (2000). Research Methods in Applied Settings: An
integrated approach to design and analysis. Lawrence Earlbaum Associates Inc.,
Mahwau: NJ.
GOLDSTEIN, I. L., 1986, Training in Organizations: Needs Assessment, Development,
and Evaluation (Monterey, CA: Brooks/Cole Publishing Company) .
92
Gouldner, A. W. (I960). The norm of reciprocity: A preliminary statement. American
Sociological Review, 25, 161-178.
Grant, A. M., & Ashford, S. J. (2008). The dynamics of proactivity at work. In L. L.
Cummings & B. M. Staw (Eds.), Research in organizational behavior, Greenwich,
CT: JAI , 3–34.
Grant, A.M., Parker, S., & Collins, C. (2009). Getting credit for proactive behavior:
Supervisor reactions depend on what you value and how you feel. Personnel
Psychology, 62, 31-55.
Griffin, M. A., Neal, A., & Parker, S. K. (2007). A new model of work role performance:
Positive behavior in uncertain and interdependent contexts. Academy of
Management Journal, 50(2), 327-347.
Gully, S.M., Payne, S.C., Koles, K.L.K., & Whiteman, J.A.K. (2002). The impact of
error training and individual differences on training outcomes: An attribute-
treatment interaction perspective. Journal of Applied Psychology, 87, 143-155
Hackman, J. R., & Oldham, G. R. 1976. Motivation through the design of work: Test of a
theory. Organization Behavior and Human Performance, 16: 250-279.
Harrison, D. A., Johns, G., & Martocchio, J. J. (2000). Changes in technology, teamwork,
and diversity: New directions for a new century of absenteeism research. In G.
Ferris (Ed.), Research in personnel and human resources management (Vol. 18, pp.
43–91). Greenwich, CT: JAI Press.
93
Hazucha, J. F., Hezlett, S. A., & Schneider, R. J. (1993). The Impact of 360-Degree
Feedback on Management Skills Development. Human Resource Management,
32(2-3), 325-351.
Hinkin, T.R. (1998). A brief tutorial on the development of measures for use in survey
questionnaires. Organizational Research Methods, 1, 104-121.
Hogan, J. & Hogan, R. (1989). How to measure employee reliability. Journal of Applied
Psychology, 74, 273-279.
Holton, E.F., Bates, R.A. & Ruona, W.E. (2001). Development of a generalized learning
transfer system inventory. Human Resource Development Quarterly, 11, 333-360.
Huczynski, A. A., Lewis, J. W. (1980). An empirical study into the learning transfer
process in management training. Journal of Management Studies, 17(2), 227-240.
Hunter, J. E. (1983). A causal analysis of cognitive ability, job knowledge, job
performance, and supervisory ratings. In E Landy, S. Zedeck, & J. Cleveland
(Eds.), Performance measurement and theory (pp.257-266). Hillsdale, NJ: Edbaum.
Hunter, J. E. (1986). Cognitive ability, cognitive aptitude, job knowledge, and job
performance. Journal of Vocational Behavior, 29, 340–362.
Hurtz, G., & Williams, K. (2009). Attitudinal and motivational antecedents of
participation in voluntary employee development activities. Journal of Applied
Psychology, 94, 635-653.
Ilies, R., Fulmer, I.S., Spitzmuller, M, & Johnson, M (2009). Personality and citizenship
behavior: The mediating role of job satisfaction. Journal of Applied Psychology,
94(4), 945-959.
94
Janz, B.D., & Prasarnphanich, P. (2003). Understanding the antecedents of effective
knowledge management: The importance of a knowledge-centered culture.
Decision Sciences, 34, 351-384.
Jehn, K. (1995). A Multimethod Examination of the Benefits and Detriments of
Intragroup Conflict. Administrative Science Quarterly, 40(2), 256.
Johns, G. (2010). Some unintended consequences of job design. Journal of
Organizational Behavior, 31, 361-369.
Jonassen, D. H., (1994). Thinking technology: Toward a constructivist design model.
Educational Technology, 34(3), 34–37.
Jones, G. R. (1983) Psychological orientation and the process of organizational
socialization: An interactionist perspective. Academy of Management Review, 8,
464-474.
Kahn, W. (1990). Psychological conditions of personal engagement and disengagement
at work, Academy of Management Journal, 33, 692-724. (141) (7.42)
Kanfer, R., & Ackerman, P. L. (1989). Motivation and cognitive abilities: An
integrative/aptitude–treatment interaction approach to skill acquisition. Journal of
Applied Psychology, 74, 657–690.
Karl, K. A., O’Leary-Kelly, A.M., & Martocchio, J.J. (1993), “The Impact of Feedback
and Self-Efficacy on Performance in Training,” Journal of Organizational
Behavior, (14), 379-394.
Kerlinger, F. N., & Lee, H. P. (2000). Foundations of behavioral research, (4th
Edition). Wadsworth: Fort Worth, TX.
95
Klein, H.J., Molloy, J. C., & Brinsfield, C. T. (2012). Reconceptualizing workplace
commitment to redress a stretched construct: Revisiting assumptions and removing
confounds. Academy Of Management Review, 37(1), 130-151.
Klein, H. J., Molloy, J. C., Cooper, J. T., & Swanson, J. A. (2011). Validation of a uni-
dimensional, target-free self-report measure of commitment. Annual Meeting of the
Academy of Management. San Antonio, Texas.
Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on
performance: A historical review, a meta-analysis, and a preliminary feedback
intervention theory. Psychological Bulletin, 119(2), 254–284.
Kozlowski, S. J., & Bell, B. S. (2007). Team learning, development, and adaptation. In V.
I. Sessa, & M. Fondon (Eds.), Work group learning (pp. 15–45). New York:
Lawrence Erlbaum.
Kozlowski, S. W. J., & Hults, B. M. (1987). An exploration of climates for technical
updating and performance. Personnel Psychology, 40, 539– 564.
Kozlowski, S. W.J., & Ilgen, D.R. (2006). Enhancing the Effectiveness of Work Groups
and Teams. Psychological Science in the Public Interest, 7(3), 77-77-124.
Kraiger, K. (2008). Transforming Our Models of Learning and Development: Web-Based
Instruction as Enabler of Third-Generation Instruction. Industrial and
Organizational Psychology, 1(4), 454–457.
Kuvaas, B., & Dysvik, A. (2010) . Exploring alternative relationships between perceived
investment in employee development, perceived supervisor support and employee
outcomes. Human Resource Management Journal, 2(20), 138-156.
96
Lam, A. (2000). Tacit knowledge, organizational learning and societal institutions: An
integrated framework. Organization Studies, 21(3), 487-513.
Law, K. S., Wong, C. S., & Mobley, W. H. (1998). Toward a taxonomy of
multidimensional constructs. Academy of Management Review, 23, 741–755.
Leanna, C., Appelbaum, E., & Schevchuk, I. (2009). Work process and quality of care in
early childhood education: The role of job crafting. Academy of Management
Journal, 52(6), 1169-1192.
Lee, C., S. J. Ashford, and P. Bobko. 1990. “Interactive Effects of ‘Type A’ Behavior and
Perceived Control on Worker Performance, Job Satisfaction, and Somatic
Complaints.” Academy of Management Journal, 33, 870-881.
LePine, J., Erez, A., & Johnson, D. (2002). The nature and dimensionality of
organizational citizenship behavior: A critical review and meta-analysis. Journal of
Applied Psychology, 87, 52-65.
Li, N., Liang, J., Crant, J.M. (2010). The role of proactive personality in job satisfaction
and organizational citizenship behavior: A relational perspective.
Lin, N. (2001). Social capital: A theory of social structure and action. New York:
Cambridge University Press.
Liu, D,. & Fu, P. (2011). Motivating protégés personal learning in teams: A multilevel
investigation of autonomy support and autonomy orientation. Journal of Applied
Psychology, 96, 1195-1208.
97
Lohman, M.C. (2005). A survey of factors influencing the engagement of two
professional groups in informal workplace learning activities. Human Resource
Development Quarterly, 16, 501-527.
London, M. (1989). Managing the training enterprise. San Francisco: Jossey-Bass.
London, M (1997). Job Feedback. Lawrence Erlbaum Associated, Mahwah, NJ, 96-97.
London M., & Smither J.W. (1995). Can multi-source feedback change self-awaretiess
and behavior? Theoretical applications and directions for research. Personnel
Psychology, 4, 803-840.
Maccallum, R.C., and Browne, M.W. (1993) "The Use of Causal Indicators in
Covariance Structure Models: Some Practical Issues". Psychological Bulletin,
114(3), 533-541.
Marrone, J.A. (2010). Team Boundary Spanning: A Multilevel Review of Past Research
and Proposals for the Future. Journal of Management, 36(4), 911-940.
Marsick, V.J., & Watkins, K.E. (2001). Informal and incidental learning. New Directions
for Adult and Continuing Education, 89, 25-34.
Mason, C. H., & Perreault Jr., W. D. (1991). Collinearity, Power, and Interpretation of
Multiple Regression Analysis. Journal Of Marketing Research (JMR), 28(3), 268-
280.
Mathieu, J. E., & Martineau, J. W. (1997). Individual and situational influences on
training motivation. In J. K.. Ford, S. W. J. Kozlowski, K. Kraiger, E. Salas, & M.
Teachout (Eds.), Improving training effectiveness in work organizations (pp. 193-
221). Hillsdale, NJ: Erlbaum.
98
Maurer, T. J., & Tarulli, B. A. (1994). Investigation of perceived environment, perceived
outcome, and person variables in relationship to voluntary development activity by
employees. Journal of Applied Psychology, 79(1), 3–14.
Maurer, T.J., Weiss, E.M., & Barbeite, F.G. (2003). A Model of Involvement in Work-
Related Learning and Development Activity: The Effects of Individual, Situational,
Motivational, and Age Variables. Journal of Applied Psychology, 88(4), 707-724.
McCall, M. W. (2004). Leadership development through experience. Academy of
Management Executive, 18, 127–130.
McCauly, C. D., & Hezlett, S. A. (2001). Individual development in the workplace. In N.
Anderson, D. S. Ones, H. K. Sinangil, & C. Viswesvaran (Eds.) Handbook of
Industrial, Work & Organizational Psychology. (pp. 313-335). London: Sage
Publications.
McCauley, C., Ruderman, M., Ohlott, P., & Morrow, J. (1994). Assessing the
developmental components of managerial jobs. Journal of Applied Psychology, 79,
544-560.
McErtrue, M. P. (1989). Self-development as a career management strategy. Journal of
Vocational Behavior, 34, 57-68.
Meyer, J. P., Becker, T. E., & Vandenberghe, C. 2004. Employee commitment and
motivation: Conceptual analysis and integrative model. Journal of Applied
Psychology, 89, 991–1007.
Milheim, W., & Martin, B. (1991). Theoretical bases for the use of learner control.
Journal of Computer-Based Instruction, 18 (3), 99-105.
99
Mischel, W. & Shoda, Y. (1995). A cognitive-affective system theory of personality:
Reconceptualizing situations, dispositions, dynamics, and invariance in personality
structure. Psychological Review, 102, 246-268.
Mohrman, S.A., Cohen, S.G., & Mohrman, A.M. Jr. (1995). Designing Team-Based
Organizationd: New Forms for Knowledge Work. San Fransisco: Josey-Bass.
Molloy, J.C., & Noe, R.A. (2010). “Learning” a living: Continuous learning for survival
in today’s talent market. In S.W.J. Kozlowski & E. Salas (Eds.), Learning, training,
and development in organizations (pp. 333–361). New York: Routledge.
Morgeson, F.P., & Humphrey, S.E. (2006). The Work Design Questionnaire (WDQ):
Developing and validating a comprehensive measure for assessing job design and
the nature of work. Journal of Applied Psychology, 91(6), 1321-1339.
Morrison, R. F., & Brantner, T. M. (1992). What enhances or inhibits learning a new job?
A basic career issue. Journal of Applied Psychology, 77, 926–940.
Motowidlo, S. J. (2000). Some basic issues related to contextual performance and
organizational citizenship behavior in human resource management. Human
Resource Management Review, 10, 115–126.
Mullen, E. J. (1994). Framing the mentoring relationship as an information exchange.
Human Resource Management Review, 4, 257–281.
Nelson, R. R., & Winter, S. G. (1982). An Evolutionary Theory of Economic Change.
Cambridge, Mass: Belknap Press of Harvard University Press
Ng, T. W. H., & Feldman, D. C. (2007). Organizational embeddedness and occupational
embeddedness across career stages. Journal of Vocational Behavior, 70, 336–351.
100
Ng, T., & Feldman, D.C.(2010). The effects of organizational embeddedness on
development of social capital and human capital. Journal of Applied Psychology,
95(4), 696-712.
Noe, R..A, (1986). Training attributes and attitudes: Neglected influences of training
effectiveness. Academy of Management Review, 11, 736-749.
Noe, R. A. (2010). Employee Training and Development. 5th Edition. Boston, M.A.:
Irwin/McGraw Hill.
Noe, R., Hollenbeck, J., Gerhart, B., & Wright, P. (2011). Fundamentals of Human
Resource Management (4th edition). New York: NY McGraw-Hill.
Noe, R.A., & Schmidt, N. (1986). The influence of trainee attitudes on training
effectiveness: Test of a model. Personnel Psychology, 39, 487-523.
Noe, R.A., & Tews, M.J. (Under Review). Informal Learning among Managers: Its
Antecedents and Performance Impact.
Noe, R. A., & Wilk, S. L. (1993). Investigation of the factors that influence employees’
participation in development activities. Journal of Applied Psychology, 78, 291–
302.
Noe, R. A., Wilk, S. L., Mullen, E. J., & Wanek, J. E. (1997). Employee development:
Issues in construct definition and investigation of antecedents. In E. A. Fleishman
(Series Ed.) & J. K. Ford (Vol. Ed.), Improving training effectiveness in work
organizations (pp. 153–189). Mahwah, NJ: Erlbaum.
101
Olivero G., Bane K.D., & Kopehnan R.E. (1997). Executive coaching as a transfer of
training tool: Effects on productivity in a public agency. Public Personnel
Management, 26, 461-469.
Ones, D. S., & Viswesvaran, C. (1996). Bandwidth-fidelity dilemma in personality
measurement for personnel selection. Journal of Organizational Behavior, 17, 609-
626.
Paradise, A., & Patel, L. (2009). 2009 State of the industry report. Alexandria, VA:
American Society for Training and Development.
Parker, S. K. (1998). Enhancing role breadth self-efficacy: The roles of job enrichment
and other organizational interventions. Journal of Applied Psychology, 83, 835–
852.
Parker, S.K., Wall, T.D., & Jackson, P.R. (1997). That’s not my job: Developing flexible
employee orientations. Academy of Management Journal, 40, 899-929.
Payne, S.C., Youngcourt, S.S., & Beaubien, J.M. (2007). A meta-analytic examination of
the goal orientation nomological net. Journal of Applied Psychology, 92, 128-150.
Pearce, J.L., & Gregerson, H.B. (1991). Task interdependence and extrarole behavior: A
test of mediating effects of felt responsibility. Journal of Applied Psychology,
76(6), 838-844.
Peters, L. H., Fisher C. D., & O’Conner, E. J. (1982). “The Moderating Effect of
Situational Control of Performance Variance on the Relationship between
Individual Differences and Performance.” Personnel Psychology, 35, 609-621.
102
Ployhart, R.E., & Moliterno, T.P. (2011) "Emergence of the Human Capital Resource: A
Multilevel Model." Academy of Management Review, 36(1), 127-150.
Podsakoff, P.M., MacKenzie, S.B., Lee, J.-Y., & Podsakoff N.P. (2003). Common
Method Bias in Behavioral Research: A critical review of the literature and
recommended remedies. Journal of Applied Psychology, 88(5), 879-903.
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect
effects in simple mediation models. Behavior Research Methods, Instruments, &
Computers, 36(4), 717-731
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for
assessing and comparing indirect effects in multiple mediator models. Behavior
Research Methods, 40(3), 879-891.
Pulakos, E. D., Arad, S., Donovan, M. A., & Plamondon, K. E. (2000). Adaptability in
the workplace: Development of a taxonomy of adaptive performance. Journal of
Applied Psychology, 85(4), 612–624. doi:10.1037//0021-9010.85.4.612
Pulakos, E. D., Dorsey, D. W., & Borman, W. C. (2003). Hiring for knowledge-based
competition. In S. E. Jackson, M. A. Hitt & A. S. Denisi (Eds.), Managing
knowledge for sustained competitive advantage: Designing strategies for effective
human resource management (pp. 155-176). San Francisco: Jossey-Bass.
Ralphs, L. T., & Stephan, E. (1986). HRD in the Fortune 500. Training and Development
Journal, 40, 69-76.
Ree, M. J., & Carretta, T. R. (2002). g2K. Human Performance, 15, 3–23.
103
Reinhardt, W., Schmidt, B., Sloep, P., & Drachsler, H. (2011). Knowledge worker roles
and actions: results of two empirical studies. Knowledge and Process Management,
18.3, 150-174.
Renn, R.W., & Fedor, D.B. (2001). Development and Field Test of a Feedback Seeking,
Social Cognitive and Goal Setting Model of Work Performance. Journal of
Management, 27, 563-587.
Rhoades, L., & Eisenberger, R. (2002). Perceived organizational support: A review of the
literature. Journal of Applied Psychology, 87, 698–714.
Rouiller, J., & Goldstein, I. (1993). The relationship between organizational transfer
climate and positive transfer of training. Human Resource Development Quarterly,
4, 377-390.
Roy, J.N. (2010). Transforming informal learning into a competitive advantage. T+D, 64,
23-25
Royer, James M. (1979) Theories of the transfer of learning. Educational Psychologist,
14, 53-69.
Schmidt, A. M. & Ford, J. K. (2003). Learning within a learner control training
environment: The interactive effects of goal orientation and metacognitive
instruction on learning outcomes. Personnel Psychology, 56, 405-429.
Schmidt, F.L., Hunter, J.E., Outerbridge, A.N. (1986). The impact of job experience and
ability on job knowledge, work sample performance, and supervisory ratings of job
performance. Journal of Applied Psychology, 71, 432-439.
104
Schneider B. (1985). Organizational behavior. Annual Review of Psychology, 36, 573-
611.
Schultz, M. (2001). The uncertain relevance of newness: Organizational learning and
knowledge flows. Academy of Management Journal, 44(4), 661-681.
Schwabel, D (2012). How job hopping can hurt your career, Special to CNN.
http://www.cnn.com/2012/01/17/opinion/job-hopping-schawbel/index.html
Seibert, S. E., Crant, J. M., & Kraimer, M. L. (1999). Proactive personality and career
success. Journal of Applied Psychology, 84, 416–427.
Seibert, S. E., Kraimer, M. L., & Crant, J. M. (2001). What do proactive people do? A
longitudinal model linking proactive personality and career success. Personnel
Psychology, 54, 845–874.
Seibert, S. E., Kraimer, M. L., & Liden, R. C. (2001). A social capital theory of career
success. Academy of Management Journal, 44, 219–237.
Seiling, J. G. 2001. The Meaning and Role of Organizational Advocacy: Responsibility
and Accountability in the Workplace. Westport, CT: Quorum Books.
Settoon, R.P., Bennett, N., & Liden, R.C. (1996). Social Exchange in organizations:
perceived organizational support, leader-member exchange, and employee
reciprocity.
Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental
studies: New procedures and recommendations. Psychological Methods, 7(4), 422-
445.
105
Sias, P. M, & Cahill, D.J. (1998). From coworkers to friends: The development of peer
friendships in the workplace. Western Journal of Communication, 62(3), 273.
Siders, M.A., George, G., & Dharwadkar, R. (2001). The Relationship of Internal and
External Commitment Foci to Objective Job Performance Measures. The Academy
of Management Journal, 44(3), 570-579.
Sitzmann, T.M., Kraiger, K., Stewart, D.W., & Wisher, R.A. (2006). The comparative
effectiveness of web-based and classroom instruction: A meta-analiysis. Personnel
Psychology, 59(3), 623-664.
Skinner, B.F. (1953). Science and Human Behavior. New York: Macmillan.
Snow, R.E. (1986). Individual differences and the design of educational programs.
American Psychologist, 41(10), 1029-1039.
Society for Human Resource Management (2009). Future insights: The top trends
according to SHRM’s HR subject matter expert panels. Alexandria, VA.
Society for Human Resource Management (2012). Future insights: The top trends
according to SHRM’s HR subject matter expert panels. Alexandria, VA.
Society for Human Resource Management (2012b). Dulles SHRM: Your chapter of
choice. Herndon, VA.
Sterman, M.C., Cheramie, R.A., Cashen, L.H. (2005). The Impact of job complexity, and
performance measurements on the temporal consistency, stability, and test-retest
reliability of employee job performance ratings.
Stigler, S. (2008). "Fisher and the 5% level". Chance, 21(4): 12.
106
Tannenbaum, S.I., Beard, R., McNall, L.A., & Salas, E. (2010). Informal learning and
development in organizations. In S.W.J. Kozlowski & E. Salas (Eds.) Learning,
training, and development in organizations: 303-332. New York, NY: Routledge.
Tett, R.P., & Burnett, D.D. (2003). A personality trait-based interactionist model of job
performance. Journal of Applied Psychology, 88, 500-517.
Tharenou, P. (1997a). Organizational, job and personal predictors of employee
participation in training and development. Applied Psychology: An International
Review, 46, 111-134.
Tharenou, P. (1997b). Determinants of participation in training and development. In C. L.
Cooper & D. Rousseau (Eds.), Trends in organizational behavior (pp. 15—28).
New York: Wiley.
Tharenou, P. (2001). The relationship of training motivation to participation in training
and development. Journal of Occupational and Organizational Psychology, 74,
599-621.
Thompson, J. A. (2005). Proactive personality and job performance: a social capital
perspective. The Journal of Applied Psychology, 90, 5, 1011-7.
Tracey, J.B., Hinkin, J.R., Tannenbaum, S.I., & Mathieu, J.F.(2001). The influence of
work characteristics and the work environment on varying levels of training
outcomes. Human Resource Development Quarterly, 12, 5-24.
Tracey, J.B., Tannebaum, S.I., & Kavanaugh, M.J. (1995). Applying trained skills on the
job: The importance of the work environment. Journal of Applied Psychology, 80,
239-252.
107
Tracey, J.B., & Tews, M.J. (2005). Construct validity of a general training climate scale.
Organizational Research Methods, 8, 353-374.
U.S. Army Field Artillery School (1984). A System Approach To Training. ST -
5K061FD92. Washington, DC: U.S. Government Printing Office.
VandeWalle, D. (1997). Development and validation of a work domain goal orientation
instrument. Educational and Psychological Measurement, 57, 995-1015.
Walker, A.G. & Smither, J.W. (1999). A five-year study of upward feedback: What
managers do with their results matters. Personnel Psychology. 52. 393-423.
Wallace, J. C., Popp, E., & Mondore, S. (2006). Safety climate as a mediator between
foundation climates and occupational accidents: a group-level investigation.
Journal of Applied Psychology, 91(3), 681-688.
Wang, S., & Noe, R.A., (2010). Knowledge sharing: A review and directions for future
research. Human Resource Management Review, 20, 115-131.
Wielenga-Meijer, E. A., Taris, T. W., Wigboldus, D. J., & Kompier, M. J. (2012). Don't
bother me: learning as a function of task autonomy and cognitive demands. Human
Resource Development International, 15(1), 5-23.
Wrzesniewski, A., & Dutton, J. E. (2001). Crafting a Job: Revisioning Employees as
Active Crafters of Their Work. Academy of Management Review, 26, 2, 179-201.
Zippay, A. (2001). The role of social capital in reclaiming human capital: Longitudinal
study of occupational mobility among displaced steelworkers. Journal of Sociology
and Social Welfare, 28, 99–119.
108
Appendix A: Content Adequacy Results
To what extent do you find Number of people who Number of people who information, learn, and develop categorized the item as a categorized the item as not skills relevant to your work type of SGD a type of SGD by...... 1. seeking feedback on your 14 performance after assignments? 2. introducing new approaches 14 on your own to improve your work? 3. listening to a podcast or 14 MP3? 4. collaborating with 14 coworkers? 12 2 5. searching the internet? 6. watching a YouTube video 14 or webinar? 7. asking others for their 14 opinion of your work? 8. taking on additional tasks 12 2 and responsibilities at work that are not required of you? 9. attending professional conferences, seminars or 14 meetings to stay current or get ahead in your line of work? 10. using trial and error 13 1 strategies? 11. scanning newspapers, 14 professional magazines or journals? 14 12. reading books? 13. asking colleagues for 14 advice?
109
To what extent do you find Number of people who Number of people who information, learn, and develop categorized the item as a categorized the item as not skills relevant to your work type of SGD a type of SGD by...... 14. reflecting about how to 13 1 improve your work performance? 15. building relationships in the organization which can help 14 to further your career progression? 16. spending time and effort 14 networking with others? 17. changing the way you do 13 1 your job to challenge yourself? 18. experimenting with new 14 ways of performing your work? 19. using your connections and 14 network to make things happen at work? 20. reflecting on your own work- 14 related strengths and weaknesses? 14 21. observing others? 22. staying well connected with 13 1 important people? 23. building relationships with 13 1 influential people? 24. cultivating and fostering professional relationships 14 through social media such as Facebook, Twitter, or Linkedin)? 25. taking a leadership role in 14 situations where there appears to be no leader? 26. interacting with your 13 1 supervisor to learn and help you better perform your job?
110
To what extent do you find Number of people who Number of people who information, learn, and develop categorized the item as a categorized the item as not skills relevant to your work type of SGD a type of SGD by...... 27. calling on colleagues and associates for support when 12 2 you really need to get things done? 28. talking with others to obtain 14 job relevant information? 29. changing minor work 14 procedures that you think are not productive? 30. asking your supervisor to 14 coach you? 31. spending time developing 13 1 connections with others? 32. seeking out feedback on your 14 performance during assignments? Note. n = 14; SGD = self-guided development.
111
Appendix B: Self-Guided Development Scale Instructions and Items
THOUGHTS ABOUT YOUR LEARNING BEHAVIOR
The following statements relate to your learning behavior. Take a moment to think about the extent with which you engage voluntarily in the following self-controlled knowledge, skill and relationship building activities to improve your work, help solve work-related problems, or learn something new for work. Using the rating scale below, fill in the number that best describes the extent to which you engage in the following behaviors.
Please note: We are not asking about the extent to which you engage in formal/structured training and development activities provided or required by your organization. Please exclude these activities when responding.
Not at Small Certain Large Great To what extent do you find information, learn, all extent extent extent extent and develop skills relevant to your work by...... 1. seeking feedback on your performance after assignments? 2. introducing new approaches on your own to improve your work? 3. listening to a podcast or MP3? 4. collaborating with coworkers? 5. searching the internet? 6. watching a YouTube video or webinar? 7. asking others for their opinion of your work? 8. taking on additional tasks and responsibilities at work that are not required of you? 9. attending professional conferences, seminars or meetings to stay current or get ahead in your line of work? 112
Not at Small Certain Large Great To what extent do you find information, learn, all extent extent extent extent and develop skills relevant to your work by...... 10. using trial and error strategies? 11. scanning newspapers, professional magazines or journals? 12. reading books? 13. asking colleagues for advice? 14. reflecting about how to improve your work performance? 15. building relationships in the organization which can help to further your career progression? 16. spending time and effort networking with others? 17. changing the way you do your job to challenge yourself? 18. experimenting with new ways of performing your work? 19. using your connections and network to make things happen at work? 20. reflecting on your own work-related strengths and weaknesses? 21. observing others? 22. staying well connected with important people? 23. building relationships with influential people? 24. cultivating and fostering professional relationships through social media such as Facebook, Twitter, or Linkedin)? 25. taking a leadership role in situations where there appears to be no leader? 26. interacting with your supervisor to learn and help you better perform your job? 27. calling on colleagues and associates for support when you really need to get things done?
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Not at Small Certain Large Great To what extent do you find information, learn, all extent extent extent extent and develop skills relevant to your work by...... 28. talking with others to obtain job relevant information? 29. changing minor work procedures that you think are not productive? 30. asking your supervisor to coach you? 31. spending time developing connections with others? 32. seeking out feedback on your performance during assignments?
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Appendix C: Survey Items
Variable Author(s) Items
Proactive personality 1. I am constantly on the lookout for new ways to improve my life 2. Wherever I have been, I have been a powerful force of constructive change 3. Nothing is more exciting than seeing my ideas turn into reality 4. If I see something I don't like, I fix it 5. No matter what the odds, if I believe in something, I will make it happen. 6. I love being a champion for my ideas, even against others' opposition 7. I excel at identifying opportunities 8. I am always looking for better ways to do things 9. If I believe in an idea, no obstacle will prevent me from making it happen 10. I can spot a good opportunity long before others can.
Autonomy 1. The job allows me to make a lot of decisions on my own. 2. The job provides me with significant autonomy in making decisions. 3. The job gives me a chance to use my personal initiative or judgment in carrying out the work. 4. The job allows me to make decisions about what methods I use to complete my work. 5. The job gives me considerable opportunity for independence and freedom in how I do the work. 6. The job allows me to decide on my own how to go about doing my work. 7. The job allows me to make my own decision about how to schedule my work. 8. The job allows me to decide on the order in which things are done on the job 9. The job allows me to plan how I do my work
Training climate. 1. Gaining new information about ways to perform work more effectively is important in this organization. 2. Job assignments are designed to promote personal development. 3. Learning new ways of performing work is valued in this organization. 4. Work assignments include opportunities to learn new techniques and procedures for improving performance. 5. There is a strong belief that continuous learning is important to successful job performance. 6. Supervisors give recognition and credit to those who apply new knowledge and skills to their work. 7. Supervisors match associates’ needs for personal and professional development with opportunities to attend training. 8. Independent and innovative thinking are encouraged by supervisors. 9. Top management expects high levels of performance at all times. 10. Top management expects continuing technical excellence and competence. 11. There is a performance appraisal system that ties financial rewards to use of newly acquired knowledge and skills.
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Variable Author(s) Items
Training climate 12. This organization offers excellent training programs. (continued) 13. Employees are provided with resources necessary to acquire and use new knowledge and skills. 14. There are rewards and incentives for acquiring and using new knowledge and skills in one’s job. 15. This organization rewards employees for using newly acquired knowledge and skills on the job.
Supervisor Support 1. My supervisor values my contribution to its well-being 2. My supervisor fails to appreciate any extra effort from me. 3. My supervisor would ignore any complaint from me. 4. My supervisor really cares about my well-being. 5. Even if I did the best job possible, my supervisor would fail to notice. 6. My supervisor cares about my general satisfaction at work. 7. My supervisor shows very little concern for me. 8. My supervisor takes pride in my accomplishments at work.
High-quality work 1. I feel that my co-workers like me relationships 2. I feel that my co-workers and I try to develop meaningful relationships with one another 3. I feel that my co-workers understand me 4. The relationship between my co-workers and myself is based on mutuality 5. We are committed to one another at work 6. There is a sense of empathy among my co-workers and myself 7. I feel that my co-workers and I do things for one another.
Task interdependence 1. I work closely with others in doing my work 2. I frequently must coordinate my efforts with others. 3. My own performance is dependent on receiving accurate information from others. 4. The way I perform my job has a significant impact on others. 5. My work requires me to consult with others fairly frequently.
Organization 1. How committed are you to your organization? Commitment 2. To what extent do you care about your organization? 3. How dedicated are you to your organization? 4. To what extent have you chosen to be committed to your organization?
Knowledge sharing 1. When I’ve learned something new, I tell my colleagues about it. 2. I share information I have with my colleagues. 3. I think it is important that my colleagues know what I am doing. 4. I regularly tell my colleagues what I am doing.
LGO 1.I am willing to select a challenging work assignment that I can learn a lot from 2. I often look for opportunities to develop new skills and knowledge 3. I enjoy challenging and difficult tasks at work where I'll learn new skills 4. For me, development of my work ability is important enough to take risks 5. I prefer to work in situations that require a high level of ability and talent
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Appendix D: Self-Guided Development Behaviors in Rank Order by Highest Mean Value
To what extent do you find information, learn, and develop skills relevant to your work Not Certai by...... Mean at all Small n Large Great collaborating with coworkers? 3.67 1% 6.7% 26.9% 54.8% 10.6% interacting with your supervisor to learn and help you better perform your job? 3.6 0% 8.9% 28.7% 55.4% 6.9% talking with others to obtain job relevant information? 3.57 1% 5.9% 40.6% 39.6% 12.9% reflecting about how to improve your work performance? 3.52 1% 10.8% 33.3% 45.1% 9.8% calling on colleagues and associates for support when you really need to get things done? 3.51 1% 6.9% 0.6% 42.6% 8.9% building relationships in the organization which can help to further your career progression? 3.45 4% 13.9% 30.7% 36.6% 14.9% asking colleagues for advice that might help you to perform your job better? 3.4 1% 9.9% 44.6% 37.6% 6.9% reflecting on your own work- related strengths and weaknesses? 3.39 1% 12.9% 44.6% 29.7% 11.9% introducing new approaches on your own to improve your work? 3.37 0% 9.8% 47.1% 39.2% 3.9% observing others? 3.27 2% 16.2% 38.4% 39.4% 4% changing minor work procedures that you think are not productive? 3.24 1% 14% 50% 30% 5% taking a leadership role in situations where there appears to be no leader? 3.23 3.9% 15.7% 38.2% 38.2% 3.9%
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searching the internet? 3.21 3.9% 21.4% 35.9% 27.2% 11.7% taking on additional tasks and responsibilities at work that are not required of you? 3.16 1.9% 17.3% 48.1% 27.9% 4.8% staying well connected with important people? 3.13 4% 21.8% 35.6% 34.7% 4% building relationships with influential people? 3.11 5% 25.7% 28.7% 34.7% 5.9% spending time and effort networking with others? 3.1 0% 28.4% 38.2% 28.4% 4.9% using your connections and network to make things happen at work? 3.06 3% 28.7% 34.7% 26.7% 6.9% seeking feedback on your performance after assignments? 3.04 2.9% 22.3% 45.6% 26.2% 2.9% spending time developing connections with others? 3.02 4% 23.8% 44.6% 21.8% 5.9% asking others for their opinion of your work? 3.01 3.9% 24.3% 45.6% 19.4% 6.8% experimenting with new ways of performing your work? 2.98 1% 23.8% 55.4% 15.8% 4% seeking out feedback on your performance during assignments? 2.96 5.9% 25.7% 38.6% 25.7% 4% changing the way you do your job to challenge yourself? 2.94 2% 24.8% 53.5% 16.8% 3% asking your supervisor to coach you? 2.84 5.9% 31.7% 39.6% 17.8% 5% using trial and error strategies? 2.76 5.9% 33.3% 43.1% 13.7% 3.9% attending professional conferences, seminars or meetings to stay current or get ahead in your line of work? 2.69 12.7% 33.3% 29.4% 21.6% 2.9% scanning newspapers, professional magazines or journals? 2.67 11.9% 37.6% 26.7% 18.8% 5% reading books? 2.61 9.9% 35.6% 37.6% 16.8% 0% cultivating and fostering professional relationships through social media such as 2.24 25.7% 39.6% 22.8% 8.9% 3% 118
Facebook, Twitter, or Linkedin)?
watching a YouTube video or webinar? 2.13 32.4% 38.2% 16.7% 9.8% 2.9% listening to a podcast or MP3? 1.72% 54.4% 26.2% 14.6% 2.9% 1.9%
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