LITERATURE REVIEW
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BISH-2.pdf
Leader vision and diffusion of HR policy during change
Adelle Bish School of Management, Queensland University of Technology,
Brisbane, Australia Cameron Newton
Department of Management, Queensland University of Technology, Brisbane, Australia, and
Kim Johnston School of Advertising, Marketing and Public Relations,
Queensland University of Technology, Brisbane, Australia
Abstract Purpose – This paper utilizes diffusion of innovation theory in order to investigate and understand the relationships between human resource (HR) policies on employee change-related outcomes. In addition, the purpose of this paper is to explore the role of leader vision at different hierarchical levels in the organization in terms of the relationship of HR policy with employee change-related outcomes. Design/methodology/approach – This quantitative study was conducted in one large Australian government department undergoing major restructuring and cultural change. Data from 624 employees were analyzed in relation to knowledge of HR policies (awareness and clarity), leader vision (organizational and divisional), and change-related outcomes. Findings – Policy knowledge (awareness and clarity) does not have a direct impact on employee change-related outcomes. It is the implementation of policies through the divisional leader that begins to enable favorable employee outcomes. Research limitations/implications – Future research should employ a longitudinal design to investigate relationships over time, and also examine the importance of communication medium and individual preferences in relation to leader vision. Originality/value – This research extends the application of diffusion of innovation theory and leader vision theory to investigate the relationship between HR policy, leader vision, and employees’ change-related outcomes. Keywords Human resource management, Organizational change, Diffusion, Leadership, Human resource policy, Leader vision Paper type Research paper
Change and innovation is part of organizational life. Whether the change is employee or leader led (Daft, 1978), managing the change process often requires the introduction of new policies to encourage the adoption of new behaviors (Morris, 2008), positive adjustment to change (Oreg et al., 2011), and to reduce overall employee anxiety and stress (Ning and Jing, 2012). Organizational policies establish appropriate new standards of how employees are expected to behave (e.g. codes of conduct) and explain how performance, in relation to standards and goals, will be managed (e.g. managing unsatisfactory performance). Furthermore, human resource (HR) policies support organizational systems (Molineux, 2013), guide organizational members in what is expected in the workplace (Lawler, 2003), and align the people management activities within the organization with the overall business strategy (Boxall and Purcell, 2003).
Journal of Organizational Change Management
Vol. 28 No. 4, 2015 pp. 529-545
© Emerald Group Publishing Limited 0953-4814
DOI 10.1108/JOCM-12-2013-0248
The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/0953-4814.htm
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Such policies facilitate incremental and transformative change and, optimally, favorable employee responses, including organizational commitment and job satisfaction (Bowen and Ostroff, 2004). For a new policy to be effective, it needs to be communicated so that employees are both aware and clear of how the policy relates to them in their role (Kiefer, 2005).
Communication is widely recognized as being central to any change process, yet the role of leaders in the process of implementing and communicating HR policy to support organizational change is not well understood (see Canary et al., 2013). Using Rogers’ (1962, 1995) innovation adoption model, this study explores how a new policy direction is communicated within a social setting as part of a broader organizational restructuring program. Specifically, our aim is to investigate the role of leader vision in determining relationships between HR policy and employees’ change-related outcomes.
Theoretical framework The way new ideas are communicated within a social system can be examined within Rogers’s (1995) innovation adoption model. The innovation adoption model is widely used in organizational research (e.g. Nelson et al., 2010). In HR, innovation adoption studies have explored organizational change and innovation in healthcare (Macfarlane et al., 2011), the relationship of communication processes and new ways of working (Wing and More, 2005), and the importance of context in the processes of change and innovation (Dopson et al., 2008). The innovation adoption model is “an information- seeking and information-processing activity in which an individual obtains information in order to gradually decrease uncertainty about the innovation” (Rogers, 1995, pp. 20-22). An innovation is “an idea, practice, or object perceived as new” within a social system (Rogers, 1995, p. 36). An innovation in the context of this study is operationalized as a new policy direction that is intentionally introduced to effect change with the expectation of positive outcomes for the organization. The social system is the employee groups within an organization working to achieve a common goal (Rogers, 1995).
The concept of diffusion underpins the process of communication among the members of a social system (Rogers, 1995), and consists of five time-ordered steps; knowledge, persuasion, decision, implementation, and confirmation. Effective implementation of new policies must include communication strategies and proactive attempts to facilitate employee understanding (Canary et al., 2013; Wilson et al., 2004). Understanding is often achieved via frequent communication among HR, leaders, and subordinates (Frenkel et al., 2013), and training (Bond and McCracken, 2005). While use of the new idea, or adoption of new policy, is the key goal for the organization, this paper focusses on the factors that have been found to influence organizational knowledge, persuasion, and decision-making stages, as it is not clearly understood how this occurs within organizations. Therefore, this study focusses on the influences of the first three steps of the process: knowledge, persuasion, and outcomes (decision).
Policy knowledge Organizational knowledge underscores the capacity of organizational members to “draw distinctions in the process of carrying out their work, in particular concrete contexts, by enacting sets of generalizations” (Tsoukas, 2005, p. 128). Rogers (1995) argues that individuals, or decision-making units, gain knowledge when they learn “of the innovation’s existence and gain some understanding of how it functions” ( p. 20).
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Policy knowledge therefore is operationalized in this study as policy awareness: the extent that employees are aware of standards and performance policies. The detailed knowledge an employee possesses about how each policy relates to them in their role is operationalized as policy clarity. Studies have demonstrated that a lack of awareness of policies can lead to adverse outcomes for employees specifically in relation to change and adjustment (e.g. Wise and Bond, 2003). Conversely, greater clarity of performance and standards policies has been shown to have positive effects on employee outcomes (e.g. favorable change attitudes, job satisfaction, and intention to stay) (Wilson et al., 2004). Overall, studies have shown relatively consistent main effects between higher levels of policy awareness and policy clarity and better levels of adjustment and general change well-being outcomes during organizational change.
Several studies guide expectations regarding policy clarity and employee outcomes. Ning and Jing (2012) found work related expectations were positively influenced by the amount of information provided to employees. Jimmieson et al. (2004) found information about change indirectly related to employees’ psychological well-being and job satisfaction. We argue individual level job information is similar to the concept of policy clarity which is achieved at the individual level when an employee knows what is expected of them in their role and how each particular policy relates to their role performance:
H1. Higher perceived awareness of standards and performance policies will be related to more favorable employee outcomes (general change well-being, job satisfaction, workplace distress, and intentions to leave).
H2. Higher perceived clarity of standards and performance policies will be will be related to more favorable employee outcomes (general change well-being, job satisfaction, workplace distress, and intentions to leave).
Persuasion: the role of the leader Leaders are central to any change effort (Miller, 2002). Rogers (1995) argues interpersonal communication plays an important role in supporting the evaluation stage of a new idea allowing more specific information to be provided. While knowledge of intervening variables in the HR policy-change-related outcomes relationship is limited (Guest, 2011), leaders act as “agents” in this relationship, as they implement HR policies and are responsible for “bringing the policy to life” (Purcell and Hutchinson, 2007). Rogers (1995) suggests at the persuasion stage, and especially at the decision stage, individuals seek to reduce uncertainty. Leader communication during change has been linked to higher commitment to change (Conway and Monks, 2008), and reduced emotional exhaustion (Ning and Jing, 2012), as employees seek explanations of how organizational changes impact their area (Molineux, 2013). Frenkel et al. (2013) found employees’ perceptions of positive relations with leaders were positively related to employees’ job satisfaction and intention to quit. Therefore, a leaders role in implementing policy warrants further investigation. More specifically, leader vision, the capacity of a leader to articulate an “idealized picture of the future based around organizational values” (Rafferty and Griffin, 2004) is an important determinant in effective change management as leaders need to be able to communicate the strategic vision (Barratt-Pugh et al., 2013).
At the organizational level, while leader vision can set the direction for the organization overall, it may be too distal to truly influence and interact with the awareness and clarity of HR policies and therefore change outcomes. However, divisional leader vision may represent a more proximal or local point of reference for awareness and clarity of policy.
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Drawing on organizational identification theory (Ashforth and Mael, 1989), a proximal interpretation of HR policies and leadership may increase employee identification and reduce ambiguity. We hypothesize more proximal leader vision will have greater impact in facilitating awareness and clarity of new HR policies as well as in the reduction of the potential adverse effects of these policies on change- and adjustment-related outcomes for employees (Zaccaro and Banks, 2004):
H3. Perceived organization leader vision will be related to more favorable employee outcomes (general change well-being, job satisfaction, workplace distress, and intentions to leave).
H4. Perceived divisional leader vision will be related to more favorable employee outcomes (general change well-being, job satisfaction, workplace distress, and intentions to leave).
H5. Perceived divisional leader vision will moderate the policy (awareness and clarity) – employee change-related outcomes (general change well-being, job satisfaction, workplace distress, and intentions to leave) relationship, such that the relationship between policy awareness and clarity and change-related outcomes will be more favorable when perceived divisional leader vision is higher.
H6. Perceived organization leader vision will not moderate the policy (awareness and clarity) – employee change-related outcomes (general change well-being, job satisfaction, workplace distress, and intentions to leave) relationship.
Method Participants One large government department with nine divisional groupings undergoing a major structural change was engaged. The focus of the restructure was to improve department productivity, with some reduction of non-essential services, consistent with the ongoing development of a performance-based culture in the Australian public sector (O’Donnell, 1998). HR policies relating to employee behavior, performance, and standards had been revised as part of this redesign effort to provide more consistent support for leaders, and increase productivity and accountability. An organization- wide survey resulted in 624 useable responses (response rate ¼ 48 percent); of whom 63 percent were female. Overall, 61 percent were aged between 26 and 45 (range: 18-65) and mean organizational tenure was 3.57 years (SD ¼ 1.73). Participants came from all hierarchical levels including direct client contact (21 percent), policy and planning (20 percent), administrative support (18 percent), and management (13 percent).
Procedure The researcher spoke directly with supervisors and employees about the survey a month prior to its distribution, and e-mail reminders were sent to all employees encouraging participation prior to and during the two-week survey period. Invitations and a paper-based survey form with a reply-paid envelope were sent to employees via internal mail.
Measures The focal variables included HR policies (awareness and clarity), perceptions of divisional and organizational visionary leadership, and employee adjustment variables
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(change well-being, job satisfaction, intentions to leave, and workplace distress). Age, gender, and negative affectivity were included as control variables given their theoretical relevance to some of the dependent variables.
Standards and performance polices(awareness and clarity). Perceptions of policy awareness and clarity were measured using 18 policy descriptors that were informed by the organization’s policy manual and HR director. Participants were asked to rate each policy in terms of both their awareness of the policy and the clarity of the policy on a scale ranging from 1 (not at all) to 5 (a great deal).
First, for each of the awareness and clarity ratings, an exploratory factor analyses (EFA) using principal axis factoring and oblique rotation was conducted using SPSS to investigate the presence of any underlying factors in the policy items. For both models (clarity and awareness), two factors were revealed relating to standards policies (e.g. Standards and Guidelines – Internet Policy) and performance policies (e.g. managing unsatisfactory performance policy). See Table I for factor loadings excluding low and cross-loading items.
Two confirmatory factor analyses (CFA) were conducted, using AMOS 18 (Arbuckle, 2003), to assess the fit of the two-factor policy models (i.e. one model for awareness and one for clarity) to the data based on the exploratory factor analysis results. Maximum likelihood estimation was employed in both analyses (Gerbing and Anderson, 1985). Missing data were inspected and considered to be missing at random and, as such, an expectation-maximization algorithm was used to replace missing data via the missing value analysis function in SPSS (Allison, 2002). After several modifications were made (“workplace harassment policy” was removed from both the awareness and clarity models due to low standardized estimates) fit indices relating to the CFAs revealed a reasonable fit of both models to the data with parameters mostly equivalent or slightly better than the lower-bound criteria for acceptance (Hu and Bentler, 1999) (Clarity model: CFI ¼ 0.97, NFI ¼ 0.97, RMSEA ¼ 0.08, SRMR ¼ 0.06; Awareness model: CFI ¼ 0.98, NFI ¼ 0.97, RMSEA ¼ 0.07, SRMR ¼ 0.06). Table I displays the policies included in the final measures.
Standardized estimates (factor loadings)
HR policy Clarity
(standards) Clarity
(performance) Awareness (standards)
Awareness (performance)
Standards and guidelines (internet) 0.95 (0.88) 0.92 (0.87) Standards and guidelines (electronic mail) 0.94 (0.88) 0.93 (0.85) Workplace health and safety 0.66 (0.78) 0.61 (0.69) Managing unsatisfactory performance 0.86 (0.85) Rehabilitation 0.82 (0.84) Recognition of achievement 0.78 (0.81) Official misconduct 0.84 (0.79) 0.83 (0.78) Employee exit 0.80 (0.78) 0.83 (0.71) Grievance 0.80 (0.76) 0.75 (0.59) Work and family 0.81 (0.73) 0.78 (0.71) Performance management 0.73 (0.87) Highest item SMC 0.89 0.74 0.87 0.69 Lowest item SMC 0.44 0.62 0.37 0.53 Notes: SMC, squared multiple correlation. Exploratory factor analysis factor loadings appear in parentheses. Items with cross and low loadings excluded from table
Table I. Exploratory and
confirmatory factor analysis of policy
classifications
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Leader vision. Leader vision was assessed using three items from Griffin et al. (2010). Items included “The leader creates an exciting and attractive image of where the organization is going”. Leader vision was assessed at the organizational and divisional levels with items adapted to reflect the hierarchical level of the leader. Responses ranged from 1 (strongly disagree) to 5 (strongly agree).
General change well-being. General change well-being was measured using three items the Queensland Public Agency Staff Survey (QPASS) developed by Hart et al. (1996) to investigate organizational stress and the quality of working life. An example item is “change has been stressful for you”. Responses are made on a five-point scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Job satisfaction. Perceptions of job satisfaction were measured using Warr et al.’s (1979) three-item scale. The scale was designed to measure how employees’ levels enjoyment, satisfaction, and happiness with their job in general with an example scale ranging from 1 (e.g. I am not happy) to 5 (e.g. I am extremely happy).
Workplace distress. Employee workplace distress was measured using three items from the QPASS developed by Hart et al. (1996). Responses to items such as “there is a lot of tension in this work unit” are made on a five-point scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Intentions to leave. Respondent’s intentions to leave the organization were assessed using a three-item scale developed by Fried et al. (1996). An example item includes “Do you seriously intend to resign from your job in the near future?” with items rated from 1 (definitely not) to 5 (definitely yes).
Negative affectivity. Brief et al. (1988) highlight that a way to limit the potential unwanted effects of negative affectivity is to control for the impact of this variable on stress and well-being measures in the organizational context. Negative affectivity was assessed using an abbreviated version the 20-item Positive and Negative Affect Schedule scale developed by Watson et al. (1988). Five items were used, for example: “How often over the past month you have experienced the following feelings while at work: Feeling Tense” and were rated from 1 (not at all) to 7 (all the time).
Gender and age. Gender (male/female) and age were controlled for in all analyses in light of research demonstrating differences in perceptions of focal variables assessed in this study (e.g. Chandraiah et al., 2003).
Results Preliminary data analyses Descriptive data (means and standard deviations) and inter-correlations are displayed in Table II and show that most correlations among the independent variables were low to moderate. Two correlations among predictors were high, but below Nine, indicating that collinearity should not be a problem (Tabachnick and Fidell, 2001). However, tolerance and variance inflation factors were requested in the regression analyses to rule out multicollinearity. As all tolerance levels were greater than ten, and all were less than ten, multicollinearity was not considered an issue (Hair et al., 2009). The reliability of scales was assessed using Cronbach’s coefficient α. All 11 scales were judged to be reliable and results are reported in Table II.
As individual responses were nested within nine divisional groupings, the extent that the proportion of variance in each of the focal variables was due to group differences was examined by computing the intraclass correlation coefficient (ICC (1)). From a one-way random-effects ANOVA model, the ICC (1) was calculated
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V ar ia bl es
M ea n (S D )
1 2
3 4
5 6
7 8
9 10
11
1 A w ar e pe rf or m an ce
2. 88
(0 .9 5)
(0 .9 0)
2 A w ar e st an da rd s
3. 99
(0 .7 4)
0. 53 **
(0 .8 6)
3 C la ri ty
pe rf or m an ce
2. 95
(0 .9 9)
0. 85 **
0. 48 **
(0 .9 3)
4 C la ri ty
st an da rd s
3. 93
(0 .8 5)
0. 45 **
0. 79 **
0. 52 **
(0 .8 7)
5 D iv is io na l le ad er
vi si on
3. 49
(1 .0 1)
0. 19 **
0. 22 **
0. 20 **
0. 21 **
(0 .9 2)
6 O rg an iz at io na l le ad er
vi si on
3. 37
(1 .0 1)
0. 22 **
0. 25 **
0. 21 **
0. 23 **
0. 70 **
(0 .8 9)
7 G en er al
ch an ge
w el l-b
ei ng
2. 63
(0 .7 1)
0. 26 **
0. 16 **
0. 27 **
0. 15 **
0. 44 **
0. 38 **
(0 .8 8)
8 Jo b sa ti sf ac ti on
4. 92
(1 .3 8)
0. 13 **
0. 19 **
0. 16 **
0. 18 **
0. 37 **
0. 37 **
0. 32 **
(0 .8 8)
9 W or kp
la ce
di st re ss
2. 85
(0 .8 6)
− 0. 08
− 0. 08
− 0. 09 *
− 0. 11 **
− 0. 33 **
− 0. 27 **
− 0. 30 **
− 0. 40 **
(0 .7 3)
10 In te nt io ns
to le av e
2. 40
(1 .0 4)
− 0. 08
− 0. 04
− 0. 06
− 0. 02
− 0. 19 **
− 0. 20 **
− 0. 23 **
− 0. 52 **
0. 24 **
(0 .7 5)
11 N eg at iv e af fe ct iv it y
3. 15
(1 .3 6)
− 0. 01
− 0. 09 *
− 0. 04
− 0. 10 *
− 0. 22 **
− 0. 14 **
− 0. 17 **
− 0. 36 **
0. 57 **
0. 27 **
(0 .8 9)
12 A ge
5. 32
(2 .0 9)
0. 19 **
0. 14 **
0. 17 **
0. 08
0. 05
0. 04
− 0. 04
0. 05
− 0. 06
− 0. 20 **
− 0. 11 **
N o te s:
C ro nb
ac h ’s (1 95 1)
α re lia bi lit y co ef fi ci en ts
ap pe ar
in th e di ag on al .* p o
0. 05 ;* *p
o 0. 01
Table II. Descriptive data
for focal variables
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(Bliese, 2000). A minimum value of at least ten is generally required for aggregation of a variable to the group-level (Bliese, 2000). For the divisional level analysis, no variable was characterized by an ICC (1) value that exceeded ten. Given that the effect of the group is unlikely to influence the results, it was considered appropriate to examine the data at the individual level of analysis and not control for divisional membership in the analyses.
Common method variance Harman’s single-factor test was used to assess the potential effects of common method variance (CMV) (Podsakoff et al., 2003). An EFA on all single items revealed 11 factors with the first factor only accounting for 32 percent of total variance. Additionally, the model was duplicated in AMOS with all items loaded onto an additional latent CMV factor. Only 1 percent of shared variance was accounted for by this latent factor. These results suggest that CMV was not a threat in the present study. Lastly, as per Spector’s (2006) recommendations, theoretically relevant control variables were included in the model (e.g. age, gender, and negative affectivity), which also reduces chance of CMV issues.
Hierarchical moderated regression analyses Hypotheses were assessed via four hierarchical multiple regression analyses (see Table III). Predictor variables were mean-centered in order to circumvent problems relating to multicollinearity between the main effects and two-way interactions (see Aiken and West, 1991). Control variables were entered on Step 1, main effects ( policy awareness, policy clarity, and visionary leadership variables) on Step 2, and interaction terms (e.g. Policy × Visionary leadership) on Step 3. As per Table III, entry of the policy and visionary leadership variables accounted for a significant increment in variance on all four focal variables: general change well-being (R2 ch. ¼ 0.15, F(9, 497) ¼ 23.00, po0.01), job satisfaction (R2 ch. ¼ 0.08, F(9, 506) ¼ 18.85, po0.01), workplace distress (R2 ch. ¼ 0.04, F(9, 507) ¼ 33.83, po0.01) and intentions to leave (R2 ch. ¼ 0.02, F(9, 506) ¼ 8.20, po0.05).
Failing to support H1 and H2, the results revealed that policy awareness and clarity were not directly related to more favorable levels of employee change-related outcomes. Partially supporting H3, the results revealed that organizational leader vision was a significant predictor of higher levels of general change well-being ( β ¼ 0.14, po0.05) and job satisfaction ( β ¼ 0.22, po0.01), and lower levels of intentions to leave ( β ¼ −0.15, po0.01). Partially supporting H4, divisional leader vision was related to higher levels of general change well-being ( β ¼ 0.31, po0.01) and job satisfaction ( β ¼ 0.11, po0.05), and lower levels of workplace distress ( β ¼ −0.17, po0.01). Entry of all eight interactions as a set in each regression neared significance in variance explained on job satisfaction (R2
ch. ¼ 0.02, F(17, 498) ¼ 10.99, po0.10), but not for general change well-being, workplace distress, or intentions to leave (see Table III). Overall, six significant or near-significant interaction effects were revealed with respect to leader vision. As per Aiken and West (1991), these interactions were plotted at one SD below and above the mean.
Divisional leader vision. Five interactions were found with respect to divisional leader vision. Four of these interactions were related to general change well-being. First, awareness of performance policies and clarity of standards policies interacted with divisional leader vision on general change well-being ( β ¼ 0.20, po0.05, and
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β ¼ 0.24, po0.05, respectively). Figure 1 reveals that those perceiving higher divisional leader vision experienced significantly higher general change well-being as awareness of performance policy increased (B ¼ 0.26, t(503) ¼ 2.87, po0.05). On the other hand, awareness of performance policies had no significant effect on levels of change well- being when divisional leader vision was low (B ¼ −0.03, t(503) ¼ −0.39, ns). Similarly, Figure 2 shows that those perceiving higher divisional leader vision experienced more favorable general change well-being as perceived clarity with respect to standards policies increased (B ¼ 0.18, t(503) ¼ 1.85, p ¼ 0.06).
Awareness of standards policies also interacted with divisional leader vision to influence levels of change well-being ( β ¼ −0.18, po0.10). Figure 3 reveals that change well-being reduced as awareness of standards policies increased for those perceiving high divisional leader vision (B ¼ −0.20, t(503) ¼ −1.80, p ¼ 0.07). Conversely, change well-being significantly improved as awareness of standards policies increased for those perceiving low divisional leader vision, although the slope was not significant (B ¼ 0.16, t(503) ¼ 1.40, ns).
The results reveal that clarity of performance policies and divisional leader vision interacted to predict change well-being ( β ¼ −0.15, po0.10). For those perceiving high divisional leader vision, change well-being did not change as a function of clarity of performance policies (B ¼ −0.02, t(503) ¼ −0.21, ns) (Figure 4). Conversely, change
Independent variables
Job satisfaction
( β)
Intentions to leave ( β)
Workplace distress ( β)
General change
well-being
Step 1 – control variables Gender 0.07 −0.13** 0.06 0.01 Age −0.01 −0.17** 0.04 −0.08 Negative affect −0.37** 0.22** 0.60** −0.19** Adj. R2 0.14** 0.09** 0.32** 0.03**
Step 2 – main effects Aware performance −0.04 −0.12 −0.05 0.16 Aware standards 0.07 0.04 0.09 −0.02 Clarity performance 0.09 0.08 0.01 0.11 Clarity standards −0.02 0.05 −0.09 −0.05 Divisional vision 0.11* −0.02 −0.17** 0.31** Organizational vision 0.22** −0.15** −0.05 0.14* R2 ch. 0.08** 0.02* 0.04** 0.15**
Step 3 – interaction terms Aware perform × Division vision −0.07 −0.06 −0.03 0.20* Aware standard × Division vision −0.02 0.03 0.10 −0.18*** Clarity perform × Division vision −0.07 0.16 0.01 −0.15*** Clarity standard × Division vision 0.08 0.03 −0.16*** 0.24* Aware perform × Organizational vision 0.22* −0.01 0.01 −0.06 Aware standard × Organizational vision 0.00 0.05 −0.01 0.14 Clarity perform × Organizational vision −0.01 −0.11 −0.11 −0.02 Clarity standard × Organizational vision −0.11 −0.05 0.12 −0.13 R2 ch. 0.02*** 0.02 0.01 0.02 Notes: *po0.05; **po0.01; ***po0.10
Table III. Hierarchical multiple regression analyses
on employee adjustment outcomes
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well-being improved significantly when employees perceived low divisional leader vision and higher clarity of performance policies (B ¼ 0.18, t(499) ¼ 2.15, po0.05).
Lastly, clarity of standards policies interacted with divisional leader vision to predict levels of workplace distress ( β ¼ −0.16, po0.10). Figure 5 reveals that levels of workplace distress were significantly lower for those perceiving high divisional leader vision and higher clarity of standards policies (B ¼ −0.27, t(503) ¼ −2.45, po0.05). Alternatively, levels of workplace distress did not improve for those perceiving low divisional leader vision (B ¼ −0.10, t(503) ¼ −1.60, ns).
Organizational leader vision. Awareness of performance policies interacted with organizational leader vision on job satisfaction ( β ¼ 0.22, po0.05). Job satisfaction improved as awareness of performance policies was higher and organizational leader was perceived as visionary, although this slope was not significant (B ¼ 0.21,
1
1.5
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3.5
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Low Clarity Standards Pol High Clarity Standards Pol
G e n e ra
l C h a n g e W
e ll-
b e in
g
Low Div. Leader Vision
High Div. Leader Vision
Figure 2. Two-way interaction of clarity of standards policy and divisional leader vision on general change well-being
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Figure 1. Two-way interaction of awareness of performance policy and divisional leader vision on general change well-being
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t(503) ¼ 1.09, ns) (Figure 6). Those perceiving low organizational leader vision reported significantly lower levels of job satisfaction as awareness of performance policies increased B ¼ −0.40, t(503) ¼ −2.16, po0.05).
Discussion This study aimed to understand the relationships between knowledge of different HR policies on employee change-related outcomes and the role of leader vision at different hierarchical levels in terms of the HR policy – employee change-related outcomes relationship in a public organization. Applying a diffusion of innovation framework, this study represents a new focus for research in the policy area and allows for greater differentiation when considering policy. Distinguishing between knowledge as policy awareness and policy clarity, allows for greater levels of analysis and consideration in
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Low Aware Standards Pol High Aware Standards Pol
G e n e ra
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e ll-
b e in
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High Div. Leader Vision
Figure 3. Two-way interaction
of awareness of standards policy and
divisional leader vision on general change well-being
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1.5
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Low Clarity Performance Pol
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b e in
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High Div. Leader Vision
Figure 4. Two-way interaction
of clarity of performance policy
and divisional leader vision on general change well-being
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policy debates particularly in terms of investigating the implementation of policy. When investigating the effectiveness of policy implementation we can explore the relative contribution of policy awareness and clarity as two distinct contributors to effectiveness.
Two discussion points arise with respect to the main effects. First, no main effects were found for policy, indicating that awareness and clarity of policies (e.g. performance and standards) do not have a direct impact on employee change- related outcomes. This result is consistent with Rogers (1995) diffusion of innovation theory and supports, in this context, that policy in itself is not necessarily responsible for employee outcomes in times of change, but rather their implementation through
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Low Clarity Standards Policy
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W o rk
p la
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is tr
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Figure 5. Two-way interaction of clarity of standards policy and divisional leader vision on workplace distress
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Jo b
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Low Org. Leader Vision
High Org. Leader Vision
Figure 6. Two-way interaction of awareness of performance policy and organizational leader vision on job satisfaction
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organizational leader vision or divisional leader vision is what begins to create favorable employee outcomes. This is also consistent with previous findings of the importance of the employee’s appraisal process in determining positive outcomes (Brockner and Wiesenfeld, 1996). While the broader underlying mechanisms explaining the relationships between HR policies and employee outcomes are not well established (Guest, 2011), our findings support the view that perceptions of the leader form part of this process. Second, leader vision at both levels was found to have a favorable influence on employee change-related outcomes. Interestingly, organizational level leader vision was related to more global satisfaction and intentions to leave the organization variables, whereas the more proximal (divisional) leader vision was related to more proximal/individual outcomes for employees (i.e. distress and well-being). While not expected, this result shows that leader vision at different levels of the organization is important in different ways. However, from a change perspective, vision of more proximal leaders may be more important in ensuring policies can be utilized as a change management technique.
Six significant interactions revealed the importance of leader vision in terms of change-related outcomes, with five interactions related to proximal divisional leadership. For three interactions, those perceiving high divisional leader vision experienced more favorable change well-being or distress as policy awareness of performance and clarity of standards increased, while those perceiving low leader vision reported less favorable results on these indicators. This finding is consistent with Ashforth and Johnson’s (2001) view that generally lower order identifications are more salient in terms of employee related outcomes and related to the role that divisional leaders play in implementing policy (Purcell and Hutchinson, 2007). Interestingly, two interactions found those perceiving high divisional leader vision did not report more favorable change well-being as awareness of standards and clarity of performance increased. Indeed, low perceivers were better off in these cases, although they still reported lower levels of well-being than high perceivers of divisional leader vision. A possible explanation for this is that in these cases the influence of the divisional leader was more influential and acted as a buffer so that the changes in awareness and clarity did not change employee outcomes.
The one significant interaction for organization leader vision on job satisfaction demonstrates that the distal leader vision is also an important consideration with respect to more distal outcomes. We would expect that at the organizational level the vision that is articulated sets the scene in terms of standards and performance expectations across the organization and that this plays a part in employee outcomes.
Theoretical and practical implications Our findings bolster both the theoretical and practical understanding of the leader’s role as one of the contextual factors in effectively managing change in public organizations. As argued by Kuipers et al. (2014), the nature of leadership in the public sector is different. For instance, leadership occurs in a political context and is highly influenced by the hierarchical nature of the organization. The present study highlights clearly the relative roles and potential impacts of leader vision at different hierarchical levels, and especially divisional levels in a policy change environment. More specifically, the importance of the divisional leader role is confirmed in both communicating policy information clearly and effectively, and their influence in employee interpretation and outcomes. This outcome and finding supports the application of diffusion of innovation theory (Rogers, 1995) to the investigation of public
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sector policy change management. Last, the results clearly highlight the importance of development of leaders at all levels of public sector organizations with specific regard to visioning skills.
Limitations and future directions A number of limitations and future research directions are relevant to this study. First, this study was cross-sectional and therefore mood states and dispositional variables could make results difficult to interpret (see Podsakoff et al., 2003). This issue was mitigated by the use of theoretically relevant control variables (see Spector, 2006) and tests for CMV to explore whether CMV was an issue. Future research should employ a longitudinal design and investigate the relationships over time. This would allow for investigation of longer term effects of leader vision on the policy-employee change-related outcomes relationship. Future research could also examine the importance of communication medium and individual preferences as it can be assumed that divisional leaders vision is conveyed in a variety of ways and some methods may in fact have a greater impact than others (e.g. face to face, e-mail, social media) for individuals and groups.
Summary Using Rogers’ (1995) diffusion of innovation theory focussing on the influences on first three steps of the process: knowledge, persuasion, and decision (outcomes), this study explored employees’ knowledge of a new idea (HR policy) within a social setting and the relationship between HR policy and leader vision to understand employees’ change- related outcomes. Overall, we did not find support for our prediction that policy awareness and clarity would relate to higher levels of general change well-being and employee change-related outcomes; instead, we found support for the moderating role of divisional leader vision.
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About the authors Dr Adelle Bish is a Senior Lecturer in the School of Management at the Queensland University of Technology, Brisbane, Australia. She teaches in the areas of human resource management practices and organizational behavior to undergraduate and postgraduate students. Adelle’s research interests include the influence of human resource practices on employee performance, contextual performance, and exceptional performance in the workplace. Dr Adelle Bish is the corresponding author and can be contacted at: [email protected]
Cameron Newton is Professor in the School of Management at the Queensland University of Technology, Brisbane, Australia. He teaches quantitative research methods and organizational psychology to undergraduate and postgraduate students. Cameron’s research interests include organizational culture, occupational stress, biofeedback using heart rate variability, and stress interventions.
Dr Kim Johnston is a Senior Lecturer in the School of Advertising, Marketing and Public Relations at the Queensland University of Technology, Brisbane, Australia. She teaches in the area of corporate and internal communication, public relations, and issues management. Kim’s research interests include organizational knowledge structures, organizational culture, engagement and workplace communications.
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