MASTER THESIS
MSc Business Administration - Leadership and Management University of Amsterdam, Faculty of Economics and Business
Thesis supervisor: Dr. Merlijn Venus
Author: Marie-Christine Felser Student Number: 11085487
Date of Submission: 26.08.2016
Version: Master Thesis, Final
The relation between vision communication and support for change:
How vision content, core self-evaluations and affective commitment to
change influence the effectiveness of visions of change.
ABSTRACT
Vision communication has been recognized to be instrumental for leading organizational change to success. Nevertheless, there is little consensus on what characterizes an effective vision of change and how visions mobilize employees towards change. With the objective of advancing the current state of research, this study compares two distinct types of visions and examines whether they foster support for change. Namely, visions highlighting the opportunities of the change initiative are contrasted with visions emphasizing the continuation of the organizational identity. Furthermore, core self-evaluations and affective commitment to change are proposed to influence the effectiveness of both visions of change. Hypotheses were tested using data from 106 data pairs, which had been collected by distributing questionnaires in organizations that were currently or in the near future undergoing change. This study found support for the presumption that visions of continuity positively influence the extent to which followers engage in change-supportive behaviors. However, the remaining hypotheses had to be rejected due to lack in evidence. Furthermore, methodological limitations, theoretical and practical implications as well as directions for future research are discussed.
Keywords: Vision communication, organizational change, vision of opportunities, vision of continuity, support for change, core self-evaluations, affective commitment to change.
1. Introduction ... 1
2. Theoretical Background ... 4
2.1. Organizational Change ... 4
2.2. Support for Change ... 5
2.3. The Role of Leadership ... 7
2.4. Visions of Change ... 9
2.5. Core Self-Evaluations ... 14
2.6. Affective Commitment to Change ... 17
3. Research Method ... 22
3.1. Procedure ... 22
3.2. Sample ... 23
3.3. Measures ... 24
4. Data Analysis and Results ... 27
4.1. Analytical Strategy ... 27 4.2. Correlation Analysis ... 28 4.3. Direct Relationship ... 29 4.4. Moderation ... 31 4.5. Mediation ... 32 4.6. Moderated Mediation ... 35 5. Discussion ... 37
5.1. Summary of the Findings ... 37
5.2. Theoretical Implications ... 38
5.3. Limitations ... 42
5.4. Directions for Future Research ... 44
5.5. Practical Implications ... 47
5.6. Conclusion ... 48
References ... 49
Appendix ... 59
1 1. INTRODUCTION
Newspapers have been cluttered for years with headlines such as “Credit Suisse merges fixed income with equities in Asia Pacific” (Azhar & Chatterjee, 2016, July 6) or “Microsoft Reorganizes Office Group to Focus on Common Tasks” (Bass & Chang, 2016, June 14). This demonstrates the significant role that organizational change plays in today’s business world. Fierce competition, technological innovations, cost pressures or higher customer requirements are examples of reasons why so many organizations need to reconsider their methods of operation (Rousseau & Tijoriwala, 1999). Despite the great attention that the area of change management has received by practitioners, a number of studies show that the majority of organizational change initiatives still fail nowadays. For example, a survey conducted by McKinsey revealed that only 3% of business executives rated their change projects as a complete success, while 27% and 37% of the respondents perceived their programs only to be mostly and somewhat successful, respectively (McKinsey & Company, 2006, June).
To probe the causes of why so many organizations fail to succeed at managing change, researchers have examined the topic of organizational change more closely over the last few decades. A fundamental finding has been that the success of change in the workplace depends considerably on employees’ attitudes towards the change (Miller, Johnson, & Grau, 1994) and their willingness to support the initiative (Jimmieson, Peach, & White, 2008). Consequently, affective responses to change and change-oriented behaviors have been the subject of much research (e.g. Ford, Ford, & D'Amelio, 2008; Kim, Hornung, & Rousseau, 2011; Rafferty, Jimmieson, & Armenakis, 2013). Acknowledging that leadership assumes an essential role in influencing employees’ reactions to change (Shamir, 1999; Yukl, 2010), scholars have also directed their attention to numerous leader behaviors and leadership styles (e.g. Bommer, Rich, & Rubin, 2005; Conger & Kanungo, 1987; Stam, van Knippenberg, & Wisse, 2010). Following the notion that vision communication constitutes one of the key aspects of outstanding
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leadership (Stam, Lord, van Knippenberg, & Wisse, 2014), academics agree that conveying a compelling vision is crucial for leaders in encouraging employees to support organizational change (Yukl, 2010) and thus, in generating change success (Kotter, 1995).
In spite of this assumed importance, however, literature on vision articulation in the context of change is still limited. Some researchers have proposed distinct definitions of visions of change (e.g. Bommer et al., 2005; Stam et al., 2010; Venus, Stam, & van Knippenberg, 2016); nevertheless, there is little clarity about what employees actually perceive as an appealing and inspiring vision (Fiol, Harris, & House, 1999; Yukl, 2010). Furthermore, the concept of vision has mainly been discussed to date as part of more complex studies that, for instance, investigated broader leadership styles (e.g. Conger & Kanungo, 1987). Hence, it is difficult to conclude from these studies that vision communication in itself motivates employees towards change (Venus et al., 2016). Moreover, there is little understanding of the underlying processes that are responsible for stimulating vision realization (Yukl, 2010). Due to the only small amount of studies that focus exclusively on vision (e.g. Griffin, Parker, & Mason, 2010; Stam et al., 2014; Venus et al., 2016), this field of research requires further investigation.
With the objective of extending the current state of knowledge, the present study examines if conveying a vision of change is essential in boosting employees’ support for change and if this effectiveness varies under different circumstances. For this, two different types of visions of change are taken into consideration. On the one hand, there are visions that are characterized by the existence of favorable opportunities. These visions of opportunities are expected to mobilize followers towards change since they promote, among others, the realization of a new and beneficial future as well as the avoidance of deficiencies of the status quo (e.g. Bommer et al., 2005; Stam et al., 2010). On the other hand, there are visions that highlight the continuity of the organizational identity (Venus et al., 2016). These visions of continuity build on the premise that employees resist change due to identity concerns (e.g. van Knippenberg & Hogg,
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2003), as they relate to the values and norms of the organization to reduce personal uncertainties (Hogg, 2007). Hence, visions of continuity are likely to motivate change support since they assure continuation of the basis of followers’ self-concept (Venus et al., 2016). As both types of visions are assumed to be effective, this study proposes their impact to be contingent on the level of employees’ core self-evaluations. These illustrate how positively or negatively people think of themselves (Judge, Bono, Erez, & Locke, 2005). It is expected that employees with high core self-evaluations prefer to hear visions of opportunities to engage in change-supportive behaviors, while followers with low core self-evaluations find visions of continuity more appealing. This study investigates another condition as a potential influencing factor. Namely, affective commitment to change (e.g. Herscovitch & Meyer, 2002) is proposed to mediate the positive relation of vision communication and change support. Again, core self-evaluations are expected to influence the extent to which visions of change foster affective commitment to change, which in turn would affect the level of support for change.
This study contributes to the existing literature in several ways. Focusing on vision communication as an individual concept enables this study to explore whether visions of change influence the level of employee’s support for change. Finding evidence for this relation would strengthen the assumption that vision communication is crucial for successfully implementing change. Furthermore, by considering distinct types of visions, the present study advances the current understanding of what characteristics constitute an effective vision of change. Building on previous definitions of visions of change, a new concept is introduced that revolves around the occurrence of opportunities. Additionally, two widely differing conceptualizations of visions are contrasted for the first time to see if employees prefer to hear one over the other. Ultimately, this study sheds light on conditions that may intensify the effectiveness of these visions of change. In particular, it provides insights into whether the success of both visions depends on personal characteristics and affective responses to change.
4 2. THEORETICAL BACKGROUND
2.1. Organizational Change
According to Van de Ven and Poole (1995, p. 512), “change … is an empirical observation of difference in form, quality, or state over time in an organizational entity. The entity may be an individual's job, a work group, an organizational strategy, a program, a product, or the overall organization”. Due to the growing number of changes in the workplace, researchers have increasingly concentrated their attention on the topic of organizational change.
Since change initiatives may be very complex and challenging for organizations, researchers have sought to advance the general understanding by probing the fundamentals of change (e.g. Dunphy & Stace, 1988; Huy & Mintzberg, 2003; Weick & Quinn, 1999). Dunphy and Stace (1988), for example, viewed change from an evolutionary perspective and distinguished between incrementalism and transformation. Originally, organizational change was seen as incremental, planned and orderly, where minor modifications progressively add up to a large-scale change over a long period of time. This theory was appropriate for environments characterized by stability and growth, which facilitates full anticipation of external forces and prospective conditions. However, due to the fast changing, dynamic environment and growing external pressures, organizations nowadays have to increasingly face transformational changes. These rather discontinuous environmental conditions limit mangers’ ability to predict the future precisely and to fully prepare for economic, political or technological developments. Thus, unexpected events often force organizations to implement extensive changes in a fast and transformative manner in order to ensure competitiveness and survival (Dunphy & Stace, 1988).
To help leaders manage the complexities of such transformational changes and to guide them through the implementation process, researchers have developed several change management models. One of the most established ideas stems from Kotter (1995) who argues that organizations need to follow eight subsequent steps. These phases may not be skipped, and
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possibly consume a vast amount of time. Kotter urges organizations to raise awareness of the need to change, to form a powerful group of change supporters, to create and communicate a vision, to remove barriers and empower employees, to define intermediate objectives for maintaining motivation and commitment, to consolidate accomplished advancements while generating further change, and to entrench new behaviors and attitudes (Kotter, 1995).
Even if organizations attempt to implement change smoothly by adopting certain change management models and activities, the consequences of such initiatives are usually quite big for its members. Therefore, organizations commonly expect their employees to resist introduced change initiatives, and believe that change agents need to overcome this negative reaction (Ford et al., 2008). However, employees do not inherently oppose change; in fact, they fear the unknown and adverse effects such as lower status, pay or comfort (Dent & Goldberg, 1999). Moreover, scholars found that leaders themselves might intensify the resistance of employees with their personal behaviors, beliefs and expectations (Ford et al., 2008). Consequently, a few academics call for discarding the traditional notion of resistance, for guiding future research in a more targeted direction and for acknowledging that employees and managers are both contributors to resistance (Dent & Goldberg, 1999; Ford et al., 2008). Following this appeal to leave behind the one-sided perspective of resistance to change, this study aims for highlighting the great influence that employees may actively exert on the success of organizational change instead. For this reason, the present research examines the concept of
Support for Change more closely.
2.2. Support for Change
Employee support, both in form of positive attitudes and behaviors, has been recognized to play an important role in ensuring the success of organizational change (Kim et al., 2011). The area of change-supportive psychological states has received much research attention thus far, which is why quite a few theoretical concepts exist such as commitment to change (Herscovitch
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& Meyer, 2002), readiness for change (Rafferty et al., 2013), or openness to change (Miller et al., 1994). Moreover, researchers have explored some change-oriented behaviors, for example adaptive behavior that displays the coping and adjustment process of employees (i.e., adaptive performance; Pulakos, Arad, Donovan, & Plamondon, 2000), or proactive behavior that captures the implementation of individually initiated improvements (i.e., proactivity; Griffin, Neal, & Parker, 2007). However, the literature on behavior that individuals actively engage in to contribute to organizational change is still quite scarce (Kim et al., 2011).
To fill this research gap, Kim et al. (2011) developed the construct of change-supportive behavior. This describes the “actions employees engage in to actively participate in, facilitate, and contribute to a planned change initiated by the organization or, more precisely, the organization’s management” (Kim et al., 2011, pp. 1667-1668). With this definition, the authors emphasize that employees may take an active part in leading change efforts to success. Therefore, the study differs from previous research in such that it concentrates on actual behavior instead of attitudes or intentions, on active cooperation as opposed to passive or responsive activities, and on planned change rather than self-initiated or spontaneous change (Kim et al., 2011).
Since the success of organizational change strongly depends on employee contribution (Oreg & Berson, 2011; Oreg, Vakola, & Armenakis, 2011; Shin, Taylor, & Seo, 2012), it is important to identify how individuals can be motivated to engage in change-supportive behavior. Researchers have already demonstrated that, for instance, information about the change, participation in the change process, change-specific self-efficacy, social relationships in the workplace and organizational commitment serve as driving factors for employees (e.g. Coyle-Shapiro, 1999; Iverson, 1996; Jimmieson, Terry, & Callan, 2004; Madsen, Miller, & John, 2005; Miller et al., 1994; Rousseau & Tijoriwala, 1999; Wanberg & Banas, 2000). Moreover, leadership is considered to play a key role in shaping employee’s affective and
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behavioral responses to change (Shamir, 1999; Yukl, 2010). Consequently, scholars have increasingly turned their attention to different leader behaviors and leadership styles in the context of organizational change (e.g. Bommer et al., 2005; Eisenbach, Watson, & Pillai, 1999; Ford & Ford, 2012; Gilley, Gilley, & McMillan, 2009; Herold, Fedor, Caldwell, & Liu, 2008). 2.3. The Role of Leadership
Leadership describes the way leaders shape follower outcomes through their individual behaviors. Consequently, a relationship between leadership and change success is assumed in such a way that the approach, behaviors and activities of leaders applied during organizational change have an impact on employees’ perception of and receptiveness to the change (Ford & Ford, 2012). Due to this prevailing assumption, prior research attempted to contribute to the understanding of what leadership aspects are central to generating employee support. So far, two distinct approaches have been adopted that are rooted either in the change management or in the leadership literature (Ford & Ford, 2012; Herold et al., 2008).
On the one hand, scholars have explored specific behaviors that leaders should engage in particularly during change efforts. These activities, if performed correctly and thoroughly, are believed to help leaders achieve positive change outcomes irrespective of the usual leadership style (Ford & Ford, 2012; Herold et al., 2008). For instance, communicating appropriate and sufficient information about the change is assumed to be instrumental in generating change acceptance, as it raises awareness for the need to change and addresses employees’ concerns. Furthermore, behaviors such as coaching employees to enhance personal strengths and work on weaknesses, allowing them to participate in and actively contribute to the change, recognizing and rewarding activities aimed at advancing the change, and promoting collaboration between team members are also associated with successful change (Gilley et al., 2009).
On the other hand, researchers have looked at different leadership styles to determine which are more suitable for the situation of organizational change. In general, leadership styles are
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relatively stable, and used continually under regular and irregular circumstances. Due to certain features, however, some styles prove to be more effective in enacting change than others (Ford & Ford, 2012; Herold et al., 2008). For instance, transformational, charismatic and visionary leadership are considered as promising approaches (e.g. Bommer et al., 2005; Conger & Kanungo, 1987; Kirkpatrick & Locke, 1996; Stam et al., 2010). Indeed, since Bass and Riggio (2006, p. 225) commented that “transformational leadership is, at its core, about issues around the processes of transformation and change”, authors have particularly focused on transformational leadership and its effectiveness in the course of change. Accordingly, such leaders are able to “transform or change the basic values, beliefs, and attitudes of followers” (Podsakoff, MacKenzie, Moorman, & Fetter, 1990, p. 108) and thus, create willingness and capability for supporting organizational change. To achieve this, transformational leaders develop and express appealing visions about the future. They convey high performance expectations, and encourage employees to collaborate and to reach group goals. They attempt to stimulate followers intellectually and to act as role models. Furthermore, being supportive and attentive to the needs and concerns of employees represents another characteristic that enables such leaders to generate positive follower responses (Bommer et al., 2005).
These findings advance the current knowledge about how to manage organizational change successfully. Nevertheless, scholars have observed that the literature on leadership and organizational change is still insufficient, incoherent and in disagreement. Therefore, academics call for a higher integration of both bodies of literature and for more empirical research (e.g. Eisenbach et al., 1999; Ford & Ford, 2012; Herold et al., 2008; Wren & Dulewicz, 2005). Yet, both streams of research share the similarity of ascribing high importance to communication in general and the articulation of a vision in particular. This may be attributed to the notion that vision communication “holds the dubious honor of being both one of the most crucial and one of the most mysterious aspects of leadership” (Stam et al, 2014, p. 1172). However, despite the
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common assumption that vision communication is instrumental for mobilizing followers towards change (Yukl, 2010), it is difficult to draw reliable conclusions about the relation between vision articulation and support for change (Venus et al., 2016). That is because authors have mostly discussed the construct of vision only implicitly within the broader area of communication (e.g. Gilley et al., 2009), or explicitly just as one component of many within a more complex conceptualization such as transformational leadership (e.g. Bommer et al., 2005). Furthermore, predominant literature is lacking a clear understanding of how to frame visions of change appropriately (Fiol, Harris, & House, 1999; Yukl, 2010), and how exactly such visions motivate followers to act (Stam et al., 2014). Therefore, this study attempts to advance the current state of research by scrutinizing what characteristics constitute an inspiring vision of change and what conditions may influence its effectiveness.
2.4. Visions of Change
Within the literature of transformational, charismatic and visionary leadership, authors proposed several general definitions for vision (e.g. Bennis & Nanus, 1985; Conger & Kanungo, 1998; Kouzes & Posner, 1987). Notwithstanding slight differences, most of these definitions refer to the mental image that a leader developed about the organization’s future (Stam et al., 2014; van Knippenberg & Stam, 2014). By conveying this idea, leaders aim to encourage followers to achieve collective goals and move together towards a future state (e.g. Bennis and Nanus, 1985; Conger & Kanungo, 1998; House & Shamir, 1993; Kirkpatrick & Locke, 1996; Kouzes & Posner, 1987; Stam et al., 2010; Zaccaro & Banks, 2001). Hence, vision articulation may serve as a means to generate inspiration, motivation, commitment and identification with this mental image (Berson, Shamir, Avolio, & Popper, 2001; Eisenbach et al., 1999). Since organizational change implies the transition of the organization towards a new future (van de Ven & Poole, 1995) and relies on commitment and support (Kim et al., 2011), vision communication is considered to be crucial for bringing about change success.
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To steer the organization into a new direction, visions of change need to be formulated in an inspiring and motivating manner (Berson et al., 2001). However, it remains unclear which content employees feel attracted to the most (Fiol, Harris, & House, 1999; Yukl, 2010). Many scholars posit that visions need to highlight to what extent the organization will differ from the status quo after the change (Conger & Kanungo, 1987; Whelan-Berry & Somerville, 2010). Therefore, authors commonly propose that visions need to promote an attractive, desirable and better future, or emphasize the existence of prospective opportunities and positive challenges (e.g. Berson et al., 2001; Bommer et al., 2005; Conger & Kanungo, 1987, 1998; House & Shamir, 1993; Kouzes & Posner, 1987; Shamir, House, & Arthur, 1993; Shamir & Howell, 1999; Stam et al., 2010). In contrast, visions may also illustrate a variation to the status quo by stressing the shortcomings of the current situation. Additionally, effective visions ought to warn of failures or undesirable situations that would happen in case of inaction (e.g. Stam et al., 2010; Conger & Kanungo, 1987, 1998; Bruch, Shamir, & Eilam-Shamir, 2007; Kotter, 1995). Taken together, the above-mentioned descriptions of visions of change are characterized by breaking with the past and discouraging existing identities (Fiol, 2002; Venus et al., 2016). Another key feature that these perspectives share is the existence of an opportunity: to reach a better future, to embrace favorable circumstances, to overcome an intolerable status quo, and to prevent future hazards. Therefore, this study uses from now on the term Vision of Opportunities to refer to and integrate these opportunity-based views.
A vision of opportunities is likely to inspire and motivate employees to engage in change-supportive behavior due to the great emphasis on the future, and its optimistic, inspirational and confident nature. Its articulation indicates that the organization is striving for the advancement of current conditions and the achievement of future successes (Bommer et al., 2005). It provides orientation and transparency of long-term goals (e.g. Berson et al., 2001; Shamir et al., 1993). Moreover, it causes dissatisfaction with the current situation and addresses employees’ fear of
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failures (e.g. Conger & Kanungo, 1987, 1998; Kotter, 1995; Stam et al., 2010). Following Vroom’s (1964) expectancy theory of motivation, employees are expected to actively support the change initiative since they await positive outcomes that are of great value to them (Kim et al., 2011). Vision communication elicits this perception in such a way that it highlights the benefits that the new future holds. Moreover, employees will feel a touch of challenge, which may also incite individuals’ support (e.g. Conger & Kanungo, 1987, 1998). Additionally, a vision of opportunity conveys the need for change, the perception of which is a critical driver of support for change (e.g. Conger & Kanungo, 1987, 1998; Kotter, 1995). The lack of such felt need would yield the impression that the change is redundant and disturbing (Bommer et al., 2005). Finally, the delivery of a vision of opportunity may instill change support, as employees are likely to attempt averting pain of future losses (Stam et al., 2010). As a consequence, this study proposes the following hypothesis:
Hypothesis 1A: There is a positive relationship between Vision of Opportunities and Support for Change.
Due to the general acceptance that visions of opportunities play a key role in inspiring followers towards change, such visions of change have become prevalent in organizations. Nevertheless, organizational change efforts are still highly susceptible to failure as a result of employees’ resistance (e.g. Bovey & Hede, 2001). Even if employees are aware of the urgency to change, if they perceive the change to be in line with personal interests, or if they endorse the advancement of the organization, employees often refuse to accept the change (Kotter & Schlesinger, 1979; Oreg, 2003; Reger, Gustafson, Demarie, & Mullane, 1994; Venus, 2013; Venus et al., 2016). Social identity approaches of organizational change suggest that this resistance arises from the threat that change poses to the organization’s identity (e.g. van Knippenberg & Hogg, 2003). This notion builds on the fact that employees incorporate organizational values and norms into their own self-definition (Ashforth & Mael, 1989; Haslam,
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2004; Hogg & Terry, 2000). Hence, organizational membership induces employees to base their self-concept not only on their self-image emerging from individual knowledge, beliefs and feelings, but also on the key features and activities of the organization (Banaji & Prentice, 1994; Shamir, 1999; Venus, 2013; Venus et al., 2016). Since individuals generally value self-consistency (Sani, 2008; Shamir, 1991), employees may respond to organizational change with resistance, as they fear the change to be a danger to the continuity of their self-definition (e.g. Hogg & Terry, 2000; Rousseau, 1998; van Knippenberg & Hogg, 2003; van Knippenberg, van Knippenberg, & Bobbio, 2008). In spite of the findings that followers fear identity losses and regard continuity as important, researchers have focused on change approaches that promote a break with the current organizational identity (e.g. de-identification strategies; Fiol, 2002; identity ambiguity; Corley & Gioia, 2004). Likewise, scholars recommend visions of opportunities that also emphasize discontinuity (Venus, 2013; Venus et al., 2016).
Recognizing this dissonance, Venus and colleagues (Venus 2013; Venus et al., 2016) have conceptualized a new form of vision of change that underlines the importance of collective continuity. Within their research, the authors found evidence for the effectiveness of this type of vision and thus, enhanced the understanding of what elements characterize an inspiring vision of change. Accordingly, they introduced the concept of Vision of Continuity that defines an inspiring vision as one, “which is able to assure followers that whatever is going to change, those aspects that constitute the organizational identity remain unchanged” (Venus, 2013, pp. 89-90). Since change and continuity may seem contradictory at first, the authors advice leaders to formulate a vision of continuity in such a way that change refers to practices and characteristics that are not essential to the organizational identity, whereas continuity is preserved concerning those features that define the collective (Venus, 2013; Venus et al., 2016).
The articulation of a vision of continuity is considered to be highly conducive to generating follower support, given that resistance to change emerges from identity concerns. The emphasis
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on both change and continuity “increase[s] followers’ perceived sense of collective continuity (Sani, 2008) – the sense that over time the key features of the organizational identity will be preserved” (Venus et al., 2016, p. 4). Following uncertainty identity theory (Hogg, 2007), as part of social identity theory (e.g. Hogg & Terry, 2000), this is of importance because employees assimilate cognitively with their organization primarily to decrease subjective uncertainty. This is attributed to the organization providing its members with a social guideline in terms of expectations, thoughts, feelings and actions (Hogg, 2007). Taken together, the communication of a vision of continuity is expected to foster employee contribution as it diminishes the fear of an inconsistent self-concept and preserves the self-uncertainty-reduction function. Building on the work of Venus and colleagues (Venus, 2013; Venus et al., 2016), this study hypothesizes the following:
Hypothesis 1B: There is a positive relationship between Vision of Continuity and Support for Change.
The first objective of this study was to examine which features characterize an effective vision of change. As outlined above, there are two divergent streams of research either promoting the existence of advantageous opportunities, or emphasizing the preservation of core features of the organizational identity. Scholars argue for the effectiveness of both types, which poses the question of whether their motivational force depends on different circumstances. This leads to the second aim of this study, which is to shed light on conditions that may affect the appeal of these visions of change. Taking a closer look at both visions of opportunities and visions of continuity, the success of these visions appears to depend on the self-evaluation and concept of organizational members. Therefore, this study proposes individual’s core self-evaluations to influence to what extent visions of change mobilize followers towards change. This concept seems relevant as it represents the fundamental appraisal that individuals make about themselves (Judge, Locke, & Durham, 1997).
14 2.5. Core Self-Evaluations
Judge et al. (1997) introduced the concept of Core Self-Evaluations, which encompasses the “fundamental evaluations that people make about themselves and their worthiness, competence, and capability” (Judge et al., 2005, p. 258). It represents a broad, higher-order personality trait that is composed of four more specific traits: esteem, generalized self-efficacy, neuroticism, and locus of control (Judge et al., 2005). Self-esteem denotes the subjective value that individuals attribute to themselves as a person resulting from the emotional assessment of their own self-worth (Harter, 1990). Generalized self-efficacy depicts the performance quality of a person in all kinds of situations, and refers to the belief in one’s own capability to cope with difficulties and overcome obstacles in everyday life (Locke, McClear, & Knight, 1996). Neuroticism describes the tendency of people to have negative attitudes and to emphasize undesirable features of the self (Watson, 2000). Finally, locus of control refers to the perception of one’s ability to actively influence the occurrence of events (Rotter, 1966). Consequently, these central appraisals provide the basis for individuals’ self-concepts, and represent an essential cause of why people differ from each other (Judge & Bono, 2001; Judge & Kammeyer-Mueller, 2011). Moreover, core self-evaluations subconsciously affect individuals’ behaviors and their perceptions of the environment (Bono & Judge, 2003).
Contingent on the underlying assessments of the self, individuals score differently on the overall core self-evaluations concept. Generally, people who have high core self-evaluations display high levels of self-esteem and generalized self-efficacy. They possess low levels of neuroticism, which some scholars also label as high emotional stability. Finally, their locus of control is internal, which means that they perceive themselves to be in control of life. Overall, individuals scoring high on core self-evaluations hold a very positive and confident self-view (Judge, Erez, Bono, & Thoresen, 2003). They are satisfied with themselves and believe to deserve respect and appreciation (Judge & Kammeyer-Mueller, 2011). Furthermore, these
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people are optimistic and enthusiastic in nature, and have affirmative feelings towards themselves (Judge et al., 2003). This positivity yields higher job satisfaction and the perception of work to be exciting and meaningful (Judge et al., 2005). Moreover, they tend to be goal-oriented, hardworking and eager to take on responsibilities, which often manifests in the pursuit of high performance and the attainment of career success (Judge, 2009; Judge & Bono, 2001; Judge & Kammeyer-Mueller, 2011). High core self-evaluations also help individuals to handle uncertain and difficult situations more effectively in such a way that they feel capable of resolving problems. They tend to complain less, exhibit greater persistence and stay motivated to overcome obstacles. Additionally, people construe their work environment as consisting of fewer threats; in fact, they tend to interpret challenges as opportunities and try to take advantage of every situation. Finally, they are less susceptible to psychological strain, worries, doubts and stress (Judge & Kammeyer-Mueller, 2011).
By implication, individuals scoring low on core self-evaluations are characterized by low levels of self-esteem and generalized self-efficacy, by high levels of neuroticism and by an external locus of control. This implies that individuals value themselves very little and do not perceive themselves as worthy of respect. People are less able to exert good performance steadily and have difficulties to deal with unfavorable situations or obstacles. Moreover, they are predisposed to negative feelings such as anxiety, fear, stress, frustration and concern, as well as to focus on their flaws as a person (Judge & Bono, 2001; Watson, 2000). They also tend to feel rather useless, helpless and ineffective, and believe in their inability to actively control happenings in their lives. Additionally, the occurrence of challenges is usually perceived as unfair and increases the feeling of powerlessness and the fear of failure (Locke et al., 1996; Peterson & Seligman, 1984). Consequently, individuals with low core self-evaluations tend to have a negative and insecure self-image.
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Taking account of the above-mentioned characteristics, visions of opportunities are likely to be more successful in generating support for change when communicated to employees that score high on core self-evaluations. Due to the fact that such individuals possess very positive and strong self-concepts, they seem less dependent on organizational values and norms as a basis for their self-definition and less imbued with self-uncertainty. Therefore, they are less likely to incorporate elements of the organizational identity into their own identity. This leads to the assumption that such individuals perceive change not as a threat, but rather as a chance for advancement. Consequently, visions emphasizing the continuation of the organization’s essence are expected to be less appealing for employees with high core self-evaluations. Instead, visions of opportunities are more likely to inspire followers to take action during change. This is expected due to their aspiration of high performance and career success, their resilience in times of uncertainty and their enthusiasm about embracing opportunities. The focus on a better future, favorable situations, current deficiencies and potential threats may trigger their ambition to make progress and to derive benefits from the change. Regarding this argumentation, the following hypothesis is suggested:
Hypothesis 2A: The positive relationship between Vision of Opportunities and Support for Change is moderated by Core Self-Evaluations, so that this relationship is stronger for higher values of Core Self-Evaluations.
In contrast, visions of continuity are likely to be more appealing to those employees who score low on core evaluations. Such individuals seem to have rather weak and critical self-concepts and appear to experience a great amount of self-uncertainty. Drawing on uncertainty identity theory (Hogg, 2007), those employees are more likely to adopt the values and norms of their organizations. Consequently, followers with low core self-evaluations are expected to be particularly prone to resistance emerging from the fear that change threatens the organizational identity and thus, endangers the consistency of their self-definition (social
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identity approaches of organizational change; e.g. van Knippenberg & Hogg, 2003). In this situation, visions of continuity are more likely to generate support for change, as they dispel employees’ concerns through assuring that the key features of the organization remain untouched. Another aspect speaking for the use of visions of continuity refers to people’s difficulty of coping with demanding situations. Such individuals tend to be intimidated by new challenges and opportunities, and are likely to perceive themselves as doomed to failure. Hence, the conveyance of a vision that emphasizes new opportunities is likely to trigger anxiety and to risk opposition. Therefore, visions of opportunities seem to be less attractive under this circumstance. Accordingly, this study proposes the following hypothesis:
Hypothesis 2B: The positive relationship between Vision of Continuity and Support for Change is moderated by Core Self-Evaluations, so that this relationship is stronger for lower values of Core Self-Evaluations.
In addition to the expectation that core self-evaluations affect the efficacy of change visions, another condition seems to be crucial for mobilizing followers towards change. Previous research inferred “that affective responses to change typically precede the extent to which employees will adopt and engage in supportive behaviors throughout the implementation process” (Jimmieson et al., 2008, p. 238). Therefore, this study suggests affective commitment to change to mediate the relation between vision communication and support for change. 2.6. Affective Commitment to Change
Conner (1992) claims that commitment to change is “the glue that provides the vital bond between people and change goals” (p. 147). This is in line with the general acceptance of scholars that commitment is an important driving force behind generating support for change (e.g. Armenakis, Harris, & Feild, 1999; Coetsee, 1999; Conner, 1992; Conner & Patterson, 1982; Klein & Sorra, 1996). Therefore, some researchers integrated commitment to change into their theoretical models (e.g. readiness for change; Armenakis et al., 1999; innovation
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implementation; Klein & Sorra, 1996). Nevertheless, the literature on that topic is still quite scarce. Existing studies offer little information on the definition or measurement of commitment to change. Likewise, its assumed effectiveness is lacking convincing empirical evidence (Herscovitch & Meyer, 2002).
Recognizing this shortcoming, Herscovitch and Meyer (2002) proposed a multidimensional construct of commitment to change and analyzed its relation to support for change. They define “commitment to change as a force (mind-set) that binds an individual to a course of action deemed necessary for the successful implementation of a change initiative” (Herscovitch & Meyer, 2002, p. 475). Criticizing the common view of commitment to change as a unidimensional model, the authors built their conceptualization on previous studies of commitment that were not related to the context of organizational change. These models distinguish between three different components: affective, continuance and normative commitment (e.g. organizational commitment; Meyer & Allen, 1991; workplace commitment; Meyer & Herscovitch, 2001). Accordingly, Herscovitch and Meyer (2002) suggest that commitment to change emerges from three different motivations: (1) employees believe in the value of the change and anticipate its advantages (affective commitment to change); (2) they recognize the costs that are linked to refusing support for change (continuance commitment to change); and (3) they feel bound to contribute to the change (normative commitment to change). Hence, followers engage in change-supportive behavior, “because they want to, have to, and/or ought to” (Herscovitch & Meyer, 2002, p. 475).
Furthermore, Herscovitch and Meyer (2002) posit that, depending on the level of commitment to change, individuals can move on a continuum of resistance, compliance, cooperation and championing. Resistance describes the denial of the change initiative, whereas compliance refers to the fundamental agreement with change requirements. Employees engaging in cooperation are willing to collaborate and accept modest sacrifices. Finally,
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championing concerns behaviors such as advertising the value of the change and making substantial personal sacrifices in order to ensure the success of the change initiative. The authors found that all forms of commitment yield compliance, but only normative and affective commitment lead to cooperation and championing (Herscovitch & Meyer, 2002). Although all behaviors concern support for change in one way or another, Kim et al. (2011) argue that only the dimension of championing refers to active employee contribution.
As noted before, affective commitment to change is expected to influence the relation of vision communication and support for change. In line with the common assumption of scholars and building on the evidence of Herscovitch and Meyer (2002), this study supposes affective commitment to change to be an important antecedent of support for change. Moreover, it is suggested that the articulation of a vision of change is like to induce such commitment. The focus is particularly on Affective Commitment to Change since a positive correlation to championing was found, which is the most contributory behavior an employee may engage in (Herscovitch & Meyer, 2002) and equals the concept of change-supportive behavior (Kim et al., 2011). Furthermore, affective commitment to change seems especially susceptible to the content conveyed by visions of opportunities and visions of continuity.
Affective commitment to change evolves from the perception that the change is valuable and yields benefits for the organization. However, employees might not perceive the change initiative as favorable or necessary right from the beginning. Therefore, a vision of opportunities is likely to create and reinforce this perception since it emphasizes the advantages of the change. The expression of an attractive future, existing opportunities, shortcomings of the status quo or potential threats underline why the change initiative is essential for the organization. Consequently, vision communication is likely to instill followers with the belief that the change is of high value for the organization, which, in turn, will generate affective commitment to change. Since positive feelings and thoughts towards the change are assumed
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to intensify the willingness to support the change, it is expected that affective commitment to change increases change-supportive behaviors that employees conduct. Moreover, following previous argumentation, this study suggests that the impact of vision communication on affective commitment to change is likely to be higher when conveyed towards individuals scoring high on core self-evaluations. Since they are expected to be highly receptive to visions of opportunities, they are likely to create high levels of commitment to change and thus, engage in more change-supportive behaviors. Therefore, the following hypotheses are suggested:
Hypothesis 3A: The positive relationship between Vision of Opportunities and Support for Change is mediated by Affective Commitment to Change.
Hypothesis 4A: The interaction between Vision of Opportunities and Core Self-Evaluations on Support for Change will be mediated by Affective Commitment to Change, so that Vision of Opportunity will interact with high levels of Core Self-Evaluations in influencing Affective Commitment to Change, which in turn will have a positive impact on Support for Change.
Similarly, the communication of a vision of continuity is expected to generate affective commitment to change as well. As previously mentioned, employees tend to base their self-concept on organizational values and norms to reduce subjective uncertainty (uncertainty identity theory; Hogg, 2007). Therefore, individuals are likely to perceive the change to threaten the consistency of their self-definitions, which is why they are expected to oppose and to develop negative affects towards the change. Since the key characteristic of this type of change vision is the emphasis on the continuity of the features that define the organizational identity, it is expected that its articulation is likely to allay the worries of employees. Consequently, this study suggests that employees, once their fears have been distracted, become open to the idea of the change. Hence, a vision of continuity is expected to reassure concerned followers and in doing so, to alter their opinion of the change in terms of benefits and value. Thus, employees are likely to transform their negative into positive affects towards the change, which enables
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the development of affective commitment to change. Once again, this research proposes affective commitment to change to precede support for change. This effect is expected to be even higher for individuals with low core self-evaluations, since they tend to experience higher self-uncertainty and rely more on their organization’s identity. In this case, the conveyance of a vision of continuity is likely to be more vital for the creation of commitment to change and support for change. Accordingly, these hypotheses follow:
Hypothesis 3B: The positive relationship between Vision of Continuity and Support for Change is mediated by Affective Commitment to Change.
Hypothesis 4B: The interaction between Vision of Continuity and Core Self-Evaluations on Support for Change will be mediated by Affective Commitment to Change, so that Vision of Continuity will interact with low levels of Core Self-Evaluations in influencing Affective Commitment to Change, which in turn will have a positive impact on Support for Change.
Figure 1 represents the conceptual framework underlying this study. It provides a brief summary of the expected relationships and corresponding hypotheses.
Figure 1. Conceptual Framework
22 3. RESEARCH METHOD
3.1. Procedure
This study forms part of a broader thesis project that generally addresses the topic of leadership and organizational change. Four students with individual thematic focal points collaborated to obtain data from a wide range of organizations in the Netherlands, Germany and Hungary. The data collection was conducted from the middle of April 2016 until the end of May 2016. Since data was gathered only at one point in time, the study is cross-sectional in nature. Moreover, the sample was attained using convenience sampling due to the difficulty of getting access to organizations and the high level of reluctance of respondents. This strategy was accompanied by snowball sampling as participants were asked to forward the survey information to further potential candidates. Since the snowball sampling was not monitored by any means, it is not possible to calculate a precise response rate. The survey addressed employees and their direct supervisors who were currently undergoing organizational change or had already been informed about a change in the near future. That change may concern the whole organization, but also only a particular department or team. However, it was important that the introduced change altered the way of working of affected employees to some extent.
Two distinct questionnaires, one for employees and one for direct supervisors, were developed within the online software Qualtrics (see Appendix A & B). Subsequently, these surveys were administered via email and in person. Generally, both questionnaires dealt with the employee in the context of the organizational change. While supervisors were asked to rate the employee’s behavioral support, employees ought to assess their personalities as well as their perceptions of and reactions to the organizational change. Moreover, the supervisor questionnaires included an open question about the type of change, and the employee questionnaires contained several questions regarding demographics such as gender, age, tenure or industry. As this study builds on the collection of data pairs, participants were asked to
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conceive of individual and unique codes together with their counterparts to enable subsequent matching of the respective questionnaires. Supervisors were allowed to evaluate more than one employee; nevertheless, they had to fill in individual questionnaires per follower. Moreover, both types of questionnaires were created in English and subsequently translated into German, Dutch and Hungarian to facilitate distribution in multiple countries, but to reduce the risk of misunderstanding because of insufficient language skills. In doing so, the back-translation technique was applied. To check for understanding, attractiveness and duration of the questionnaires, a short pilot study was conducted before the official administration.
During the data collection, a few strategies to maximize the likelihood of responses were applied. For example, since respondents needed to know quite some information prior to participating in the survey, an appealing power point presentation was distributed instead of a traditional cover letter (see Appendix C). Moreover, participants were provided with the possibility to receive the results of the conducted studies after the completion of the thesis project. Furthermore, anonymity and confidentiality were assured within the power point presentation as well as the introduction section of the questionnaires to reduce fear of negative implications and to increase honesty in responding to the questions.
3.2. Sample
In total, 115 direct supervisors and 112 employees responded to the survey request. Of these returned questionnaires, 106 data pairs were able to be properly matched; the remaining surveys had to be neglected due to unsuccessful coding. 34 dyads pertain to the Hungarian, 41 data pairs to the German, 30 couples to the Dutch and 1 pair to the English questionnaires. Reorganization of the company, extension of responsibilities and tasks, mergers and acquisitions, or implementation of new IT-systems are examples of changes that take place in the participating organizations. Additionally, data pairs come from a broad range of industries such as automotive, energy, IT, financial services, health or agriculture. Deriving from the employees’
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questionnaires, 33 participants indicated the Netherlands, 39 participants Germany and 34 participants Hungary as their country of residence. Furthermore, 54 females and 52 males took part in the survey. Employees range in age from 21 to 64 years with an average of 38.07 years1. They have been with their company for an average of 9.10 years and have received guidance from their supervisors for averaging 4.46 years. Moreover, they work on average 37.64 hours per week and are in direct contact with their supervisors on averaging 3.73 days a week. 3.3. Measures
Considering that this study is part of a thesis project and data were collected to serve multiple research papers, the employee questionnaires comprise several variables that are not relevant for this study. Therefore, only those variables referring to the current model are taken into consideration in the following sections. All constructs utilized a 5-point Likert scale ranging from 1 (‘strongly disagree’) to 5 (‘strong agree’), except for the questions regarding the demographics, the type of change and the coding.
Vision of Opportunities. This measure was assessed using three self-developed items and
pertained to the employee questionnaire. Examples of items are the following: “My direct supervisor makes clear how his/her vision deviates from the current situation” and “My direct supervisor regularly communicates that there is a necessity to change the team’s current situation”. The Cronbach’s Alpha for this scale is α = 0.779.
Vision of Continuity. This measure was assessed utilizing the three-item scale developed by
Venus et al. (2016) and was placed in the employee questionnaire. Examples of items are the following: “My direct supervisor often communicates in his/her vision that our organization in the future will be a continuation of what we stand for” and “My direct supervisor regularly
1 One participant was excluded from this calculation as ‘5’ was indicated as the current age. Including this
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communicates that it is important that our organization will maintain its identity”. The Cronbach’s Alpha for this scale is α = 0.777.
Core Self-Evaluations. This measure was assessed adopting the 12 items as used by Judge
et al. (2003) and belonged to the employee questionnaire. Six out of the 12 items are counter-indicative and examples are the following: “I am confident I get the success I deserve in life” and “Sometimes I feel depressed”. The Cronbach’s Alpha is α = 0.769.
Affective Commitment to Change. This measure was assessed using three items out of the
four-item scale developed by Herscovitch and Meyer (2002). It was placed in the employee questionnaire and examples of items are the following: “I believe in the value of this change” and “This change is a good strategy for this organization”. The Cronbach’s Alpha is α = 0.904.
Support for Change. This measure was composed of 14 items in total. Of these, three items
were taken from the four-item scale of Fedor, Caldwell and Herold (2006), four items were adopted out of the six-item scale of Herscovitch and Meyer (2002), and seven items were utilized that Venus (2013) developed. It pertained to the supervisor questionnaire and therefore, items were modified to fit the context. Examples of items are the following: “The employee fully collaborates with implementing the current or future plans” and “The employee is willing to promote the vision of change with enthusiasm”. The Cronbach’s Alpha is α = 0.948.
Control Variables. From the demographical information of the employee questionnaire,
‘days of direct contact with supervisor per week’ and ‘tenure’ were selected as control variables. These are expected to influence the relations suggested by the current model. First, it is assumed that the more often employees and supervisors are in direct contact, the more possibilities exist for the supervisor to spread the idea of the change through vision communication. This might affect the extent to which followers understand the rationale and the urgency of the change and thus, to which they accept and support the change. Second, it is presumed that the longer employees work at an organization, the likelihood of identifying and cognitively assimilating
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with this organization is higher. This might have an impact on the extent to which employees perceive the change to be a threat to their personal identity and thus, to which they feel attracted to a vision of continuity. Both control variables were measured with single items: “How many days per week do you have direct contact with your supervisor (e.g. meeting, call, email)?” and “How many years do you work in your current company?”.
All variables have been validated before except for the scale of VOP2, which has only been developed for this study. To see whether both vision constructs clearly differ from each other and to check for similarities between the individual items VOP 1,2,3 and VCO 1,2,3, a factor analysis has been conducted. After running a principal axis factoring analysis (PAF), the applicability of the data set was examined. Since the Kaiser-Meyer-Olkin measure is above 0.6 (KMO = 0.655) and the Bartlett’s test of sphericity is significant with χ² (15) = 204.797, p < 0.001, the data set is adequate and the correlations are large enough for the PAF. To see how many factors need to be retained, the eigenvalues of each component in the data were examined. With an eigenvalue of 2.15 and 2.08, only two components meet the Kaiser’s criterion of eigenvalues being above 1. Moreover, these components explain together 57.91% of the variance. Furthermore, the scree plot confirmed the Kaiser’s criterion by showing a decline after the second factor. Consequently, two factors were extracted and rotated with an Oblimin with Kaiser normalization rotation. This leads to the following factor loadings after rotation that are shown in Table 1. The bundling of the first three items on the same factor and the second three items on another factor suggests that factor 1 represents VOP and factor 2 represents VCO. Thus, VOP and VCO represent two distinct constructs.
2 The following abbreviations will be used subsequently to refer to the underlying variables:
VOP (Visions of Opportunities), VCO (Visions of Continuity), CSE (Core Self-Evaluations), ACC (Affective Commitment to Change), SFC (Support for Change) and Contact (days of direct contact with supervisor per week).
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Table 1. Factor loadings after Oblimin with Kaiser normalization rotation.
Item
Rotated Factor Loadings
VOP VCO
My direct supervisor makes clear how his/her vision deviates from the current situation.
0.52 -0.03 My direct supervisor regularly communicates that there is a necessity to
change the team’s current situation.
0.93 0.06 My direct supervisor’s vision for the team emphasizes that in the future the
team should be in a different position than it currently is.
0.77 -0.02 My direct supervisor often communicates in his/her vision that our
organization in the future will be a continuation of what we stand for.
0.21 0.77 My direct supervisor often communicates in his/her vision that our
organization in the future will be a continuation of our organization now.
-0.05 0.84 My direct supervisor regularly communicates that it is important that our
organization will maintain its identity.
-0.13 0.62
Eigenvalues 2.15 2.08
% of Variance 29.98 27.93
Factor loading over 0.40 appear in bold.
4. DATA ANALYSIS AND RESULTS
4.1. Analytical Strategy
After downloading the data from the online data collection program Qualtrics, the data file was prepared for analysis in IBM SPSS Statistic Version 24. Since data pairs were collected in multiple countries, the first step was to merge the different data files into one overall data set. When creating the questionnaires in Qualtrics, the option to force responses was chosen, meaning that every question had to be answered before submitting the data. This is why the data set does not show any missing values. Thus, no cases had to be excluded or replaced. Moreover, the data file was screened for errors by running the ‘Frequencies’ analysis.This step revealed that all values lie within the range of possible values and results were entered correctly. Some items had been negatively phrased to avoid response bias. Therefore, the counter-indicative items needed to be recoded so that all items could build an overall variable.
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Subsequently, the total scale scores were computed by generating the mean of all items that constitute the respective scale.
Moreover, the reliability of all scales was analyzed. This indicates to what extent the variables would produce consistent results when replicating the study. All scales show high reliability since the Cronbach’s Alpha values are above 0.70 (VOP α = 0.779; VCO α = 0.777; SFC α = 0.948; CSE α = 0.769; ACC α = 0.904). For VOP, VCO, SFC and ACC, the corrected item-total correlation values are above 0.30, demonstrating that all individual items correlate with the total score of the respective scale. Moreover, deleting single items would not increase the scales’ reliability considerably (Δ < 0.10). When checking the corrected item-total correlation for CSE, one item showed a value lower than 0.30 (CSE 3 = 0.265), while the remaining items were all above. However, CSE 3 was not deleted from the overall scale, since this would not lead to a rise of the Cronbach’s Alpha value.
4.2. Correlation Analysis
A correlation analysis was conducted in order to examine the strength and directions of the relations between the variables. Table 2 provides an overview of the means, standard deviations, correlations and reliability scores of VOP, VCO, CSE, ACC, SFC, Tenure and Contact. Taking a closer look at the variables, almost all correlation coefficients range between -0.2 and 0.2. This indicates that there is hardly any or just a slight relation between the variables, for example VOP and SFC only correlate by r = 0.043, or VOP and ACC by r = 0.136. Though the highest correlations in this study, VCO and SFC (r = 0.226*), ACC and SFC (r = 0.264**), as well as ACC and CSE (r = 0.293**) also only display a tendency to positive relation. These low correlations are likely to have implications for the results of the subsequent hypotheses testing.
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Table 2. Means, Standard Deviations, Correlations and Reliability Scores.
Variable M SD 1 2 3 4 5 6 7 1. Tenure 9.10 9.56 - 2. Contact 3.74 1.57 -0.058 - 3. VOP 3.22 0.89 0.052 0.051 (0.779) 4. VCO 3.31 0.83 0.129 0.197* 0.001 (0.777) 5. CSE 3.98 0.46 -0.002 0.029 -0.150 0.094 (0.769) 6. ACC 3.77 0.91 -0.134 0.157 0.136 0.131 0.293** (0.904) 7. SFC 3.76 0.74 -0.095 0.085 0.043 0.226* 0.044 0.264** (0.948)
*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).
4.3. Direct Relationship
To test hypothesis 1A, a hierarchical multiple regression analysis was conducted. The aim was to assess the ability of VOP to predict levels of SFC, after controlling for the influence of tenure and contact. In the first step of the hierarchical multiple regression, the two control variables were entered as predictors: tenure and contact. This model was statistically insignificant with F (2, 103) = 0.80; p = 0.452 and explained 1.5% of variance in SFC. After the entry of VOP at Step 2, the total variance explained by the model as a whole was 1.7%. However, the model was insignificant with F (3, 102) = 0.60; p = 0.620. The introduction of VOP explained insignificantly additional 0.2% of variance in SFC, after controlling for tenure and contact (R² Change = 0.002; F (1, 102) = 0.199; p = 0.656). Checking the standardized coefficients, none of the three predictor variables made a statistically significant unique contribution to the prediction of SFC. This leads to the rejection of hypothesis 1A. There seems to be no positive relationship between VOP and SFC. Table 3 shows the results of the analysis. It reports the R, R² and the amount of change in R² as well as the unstandardized coefficient B, the standard error SE, the standardized coefficient β and the t-value.
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Table 3. Hypothesis 1A - Hierarchical Regression Model of SFC.
R R² R² Change B SE β t Step 1 0.124 0.015 Tenure -0.007 0.008 -0.090 -0.922 Contact 0.037 0.046 0.079 0.811 Step 2 0.131 0.017 0.002 Tenure -0.007 0.008 -0.093 -0.942 Contact 0.036 0.046 0.077 0.782 VOP 0.037 0.082 0.044 0.447 Dependent Variable: SFC.
For hypothesis 1B, another hierarchical multiple regression analysis was performed to test the predicting ability of VCO in relation to levels of SFC. Again, it was controlled for the influence of tenure and contact. The results of the analysis are displayed in Table 4. After entering both control variables in the first step, the overall model explained 1.5% of variance in SFC and was not statistically significant with F (2, 103) = 0.799; p = 0.452. After including VCO in Step 2, the model as a whole explained 6.8% of the total variance and was insignificant with F (3,102) = 2.468; p = 0.066. However, the addition of VCO explained significantly further 5.2% of variance in SFC, after controlling for tenure and contact (R² Change = 0.052; F (1, 102) = 5.731; p = 0.018). In the final model, only VCO made a unique statistically significant contribution with a positive beta coefficient of β = 0.236; p = 0.018. This supports hypothesis 1B and that VCO shares a positive relationship with SFC.
Table 4. Hypothesis 1B - Hierarchical Regression Model of SFC.
R R² R² Change B SE β t Step 1 0.124 0.015 Tenure -0.007 0.008 -0.090 -0.922 Contact 0.037 0.046 0.079 0.811 Step 2 0.260 0.068 0.052* Tenure -0.010 0.007 -0.124 -1.277 Contact 0.015 0.046 0.031 0.316 VCO 0.212 0.088 0.236* 2.394
Dependent Variable: SFC; Rounding differences may occur for R² Change. Statistical significance: * p < 0.05.
31 4.4. Moderation
Hypothesis 2A describes the moderation effect of CSE on the positive relation between VOP and SFC, implying that with higher values of the moderator the relation will be stronger. Although no significance for this positive relationship was found, a moderator analysis was performed. This is because high CSE may be the essential condition for enabling VOP to influence the level of SFC. To test hypothesis 2A, an interaction term between VOP and CSE was computed. Subsequently, a hierarchical multiple regression analysis was conducted to investigate the statistical significance of this interaction term. The control variables tenure and contact, VOP and CSE were all inserted as predictors in Step 1, while the interaction term of VOP and CSE was entered in Step 2. Regression results can be found in Table 5. After adding the interaction term, the overall model explained 3.5% of the total variance and was not significant with F (5, 100) = 0.727; p = 0.604. Furthermore, including the interaction term explained insignificantly additional 1.6% of variance in SFC (R² Change = 0.016; F (1, 100) = 1.611; p = 0.207). With β = -1.097; p = 0.207, the interaction term of VOP and CSE did not make a statistically significant unique contribution to explaining SFC. Consequently, this study did not find any evidence that CSE influences the strength of the relation between VOP and SFC. This leads to the rejection of hypothesis 2A.
Table 5. Hypothesis 2A - Hierarchical Regression Model of SFC.
R R² R² Change B SE β t Step 1 0.140 0.020 Tenure -0.007 0.008 -0.093 -0.942 Contact 0.035 0.047 0.075 0.761 VOP 0.043 0.083 0.051 0.515 CSE 0.078 0.159 0.049 0.491 Step 2 0.187 0.035 0.016 Tenure -0.007 0.008 -0.089 -0.901 Contact 0.033 0.047 0.071 0.719 VOP 0.936 0.709 1.123 1.321 CSE 0.739 0.545 0.463 1.358 VOP x CSE -0.219 0.172 -1.097 -1.269
