The current issue and full text archive of this journal is available at www.emeraldinsight.com/0262-1711.htm
Executive coaching
Executive coaching
The effect of working alliance discrepancy on the development of coachees’ self-efficacy Louis Baron, Lucie Morin and Denis Morin
847
Universite´ du Que´bec a` Montre´al, Montre´al, Canada Abstract
Received 4 July 2010 Revised 26 July 2010 Accepted 13 October 2010
Purpose – Despite its growing popularity in applied settings, executive coaching has to date received little attention in empirical research, especially in regard to the coaching process. This paper aims to investigate the effect of working alliance rating discrepancies on the development of coachees’ self-efficacy, a key outcome in leadership development. Design/methodology/approach – The paper reports on a pre- post-test study of a leadership development program taking place in a large North American manufacturing company. Data were collected from two samples: managers receiving coaching over an eight-month period and internal certified coaches. In total, 30 coach-coachee dyads were analyzed. Findings – Results from an analysis of covariance did not support the authors’ hypothesis, by indicating that coachees having worked with a coach who underestimated the working alliance, in relation to his or her coachee, experienced more growth in self-efficacy than coachees who worked with a coach who either accurately estimated or overestimated the working alliance. Practical implications – The results sugges that coaches should coach with an “ongoing and deliberately maintained doubt as their only certainty”. The importance for coaches to be sensitive to signs of what the coachee is experiencing, and to take the initiative to verify the coachee’s comfort level with the way coaching is proceeding is addressed. Originality/value – This study intended to delve deeper into the complexities of the coaching process by linking a key coaching process variable, the relationship, to coaching outcomes. Keywords Executive coaching, Coaching relationship, Working alliance, Discrepancy, Self-efficacy, Management development, Leader ship Paper type Research paper
Introduction Executive coaching has come to play a key role in the field of leadership and management development (O’Leonard, 2009; Bono et al., 2009). A recent survey from the Conference Board of Canada (Hughes and Campbell, 2009) revealed that 72 percent of organizations surveyed use coaching to support leadership development. However, despite its growing popularity in applied settings, this developmental intervention has to date received little attention in empirical research. Few rigorous quantitative empirical studies have been conducted, and most of them have focused on the effectiveness of coaching (Kampa-Kokesch and Anderson, 2001; Smither et al., 2003). With respect to the coaching process or, in other words, the conditions favoring effective executive coaching, numerous authors have suggested that a good working An earlier version of this paper has won the Graziadio Business School/Pepperdine University for Outstanding Practice-Based Paper on Management Consulting at the Academy of Management 2010 Conference.
Journal of Management Development Vol. 30 No. 9, 2011 pp. 847-864 q Emerald Group Publishing Limited 0262-1711 DOI 10.1108/02621711111164330
JMD 30,9
848
relationship constitutes an essential condition for successful executive coaching (Kilburg, 2001; Kampa-Kokesch and Anderson, 2001; Lowman, 2005; Kampa and White, 2002). Although the impact of the working alliance on treatment outcomes has been widely documented in the psychotherapy literature (Castonguay et al., 2006; Horvath, 2005; Martin et al., 2000), to our knowledge, only a very small number of studies have investigated the concept of working alliance in a coaching context (Baron and Morin, 2009; Berry, 2005; Dingman, 2004). Furthermore, none of these empirical studies have compared the working alliance ratings of the coach and coachee. What happens when these two individuals have a different perception of the working alliance between them? This question is very pertinent, given that in a psychotherapeutic context, similar client-therapist alliance ratings in the middle and late phases of treatment are positively linked with treatment outcomes (Horvath and Bedi, 2002). The primary purpose of this study was to investigate the effect of working alliance rating discrepancies on the development of coachees’ self-efficacy. This study endeavored to contribute to the literature in two ways. First, it aimed to increase our knowledge of the working alliance concept in the context of executive coaching. Although, authors have suggested that this variable plays a key role in coaching effectiveness, empirical research is lacking on the topic. Second, and most importantly, this study intended to delve deeper into the complexities of the coaching process. Given the increased use of executive coaching by organizations, an understanding of the conditions under which coaching is most effective is highly relevant (Paradise and Mosley, 2009). Conceptual framework Executive coaching Many definitions have been proposed for the concept of executive coaching (Hall et al., 1999; Stober and Parry, 2005; Kilburg, 2000). In this study, we relied on the definition proposed by Douglas and Morley (2000, p. 40) for whom coaching is: [T]he process of equipping people with the tools, knowledge, and opportunities they need to develop themselves and become more effective (Peterson, 1996). Executive coaching involves the teaching of skills in the context of a personal relationship with the learner, and providing feedback on the executive’s interpersonal relations and skills (Sperry, 1993). An ongoing series of activities tailored to the individual’s current issues or relevant problem is designed by the coach to assist the executive in maintaining a consistent, confident focus as he or she tunes strengths and manages shortcomings (Tobias, 1996).
Among the various reasons cited in the popular literature to explain the growing interest in coaching, the following two have particular bearing on this study: (1) The numerous and frequent changes experienced within organizations (e.g. mergers and acquisitions, changes in management philosophies, new forms of work organization) have created a need to develop management skills, especially interpersonal skills (Zeus and Skiffington, 2001). (2) Traditional training methods, such as the classroom seminar do not appear to meet these organizational needs (Whetten and Cameron, 2007; Baron and Morin, 2010).
Moreover, Fatien and Amado (2009, p. 4) suggested that: [. . .] the collective setting (associated with traditional training methods) sometimes does not facilitate self-expression, or does not allow for intimate self-disclosure. And in a society that requires more and more subjective involvement, one may need to discuss personal issues face-to-face.
Professional and personal development, as these authors suggest, is seldom realized in one-shot or one-size-fits-all interventions. Executive coaching provides an opportunity to create a genuine personal relationship between the coach and coachee through a consistent focus on the attainment of significant individual developmental goals, and it is this relationship that appears to be key in supporting managers and leaders in their development. To date, from an empirical point of view, few quantitative empirical studies have investigated executive coaching (Evers et al., 2006; Luthans and Peterson, 2003; Olivero et al., 1997; Smither et al., 2003; Thach, 2002). By focusing on the effectiveness of executive coaching, these studies have helped confirm that this type of intervention seems effective. Yet, we still know little about why it works, or more specifically, under which conditions executive coaching is most effective. In response, authors have recommended looking at the working alliance between the coach and coachee ( Joo, 2005; Latham and Heslin, 2003). These authors argued that the effectiveness of coaching is likely to depend on the mutual agreement of the goals, the paths chosen to attain them, and the level of interpersonal comfort between the coach and coachee. Other authors have further advanced the notion that a positive working alliance between the coach and coachee is an essential condition of coaching success (Kampa and White, 2002; Lowman, 2005). The following section presents the concept of the working alliance in more detail. Working alliance The concept of working alliance has its roots in the psychotherapy literature. Broadly speaking, working alliance refers to the “quality and strength of the collaborative relationship between client and therapist in therapy” (Horvath and Bedi, 2002, p. 41). Various conceptualizations have been proposed to define the therapist-client relationship (Bordin, 1979; Greenson, 1965; Luborsky, 1976). For the purposes of this study, we relied on the broadened conceptualization of working alliance advanced by Bordin (1979), which includes all change-inducing relationships (Horvath and Greenberg, 1989). This conceptualization highlights the interdependence of the therapist and the client in the development of the alliance. Furthermore, Bordin (1979) suggests that the strength of the alliance rests on the existing agreement between the client and the therapist concerning the following three aspects: the objectives of the therapy, the tasks required to reach those objectives, and the bond that develops between the client and the therapist. A wide range of empirical evidence supports the relevance of working alliance in predicting therapy outcomes (Eames and Roth, 2000; Horvath and Greenberg, 1989; Martin et al., 2000; Mallinckrodt, 1992; Horvath and Symonds, 1991). Moreover, results from empirical studies have consistently shown that the strength of the working alliance is a highly significant predictor of a therapy’s success. It is estimated that the therapeutic alliance accounts for somewhere between 7 and 17 percent of the variance in therapy outcomes, and effect sizes for this relationship range from 0.22 to 0.26 (Martin et al., 2000; Horvath and Symonds, 1991). Castonguay et al. (2006) strongly argued that any study examining the process of psychotherapy should include the concept of the working alliance.
Executive coaching
849
JMD 30,9
850
Few empirical studies have examined the concept of working alliance in executive coaching. One of them, a retrospective study by McGovern et al. (2001), reported that 84 percent of coachees identified the quality of the relationship with their coach as critical to the success of coaching. However, due to the post-facto design and descriptive nature of the study, no statistical correlation could be established between the working relationship and the success of the executive coaching. In a second study, Dingman (2004) polled, via the internet, 92 coachees who had completed a coaching process. Results revealed a significant positive correlation between the quality of the coaching relationship and the coachee’s self-efficacy. A third study by Berry (2005) compared face-to-face coaching with distance coaching by examining two variables: the coach-coachee relationship and the extent of change in the coachee’s development goals. A sample of 102 professional coaches responded to an online survey. Findings indicated a significant positive correlation between the relationship and change, as evaluated by the coaches but only in the distance coaching condition. Coachees were not surveyed in this study. Finally, results from Baron and Morin (2009) showed that the coach-coachee relationship plays a mediating role between the amount of coaching received and the development of coachees’ self-efficacy. This result suggests that it is through its effect on the coach-coachee relationship that the amount of coaching received influences the development of the coachee. This, in turn, suggests that the coach-coachee relationship constitutes a prerequisite for coaching effectiveness. In short, as is the case in psychotherapy, the working alliance appears to have a significant role in the context of executive coaching. However, none of the published studies have examined the impact of a discrepancy between the coachee’s rating and the coach’s rating of the working alliance. Could a discrepancy between ratings have an impact on executive coaching outcomes? The next section discusses the working alliance discrepancy. Working alliance discrepancy The psychotherapy literature on working alliance indicates that the client’s views of the moderate correlation between client and psychotherapist ratings of the therapeutic alliance (Cecero et al., 2001; Fenton et al., 2001). To explain the discrepancy in ratings, Horvath and Bedi (2002, p. 51) advanced that: [. . .] while the alliance is understood to involve collaboration and mutuality, it is not a symmetrical relationship. Therapists’ responsibilities are different from those of clients, and therapists’ phenomenological experience of the relationship is contextualized by their theoretical perspectives and clinical experience. The client’s felt experience in therapy is not only the result of the dialectical experience in the therapy room, but is also construed in the light of past relational history.
For their parts, Bedi et al. (2005) suggested that clients and therapists can diverge in their perceptions of what elements are important in the development of the therapeutic alliance. Findings from empirical studies have indicated that the client’s view of the working alliance is a better predictor of the success of a therapy than the therapist’s view (Horvath and Bedi, 2002). Other research has further shown that similarity or low discrepancy between client and therapist alliance ratings in the middle and late phases of treatment is a consistent predictor of positive outcomes (Hersoug et al., 2002; Kivlighan and Shaughnessy, 1995).
In light of all the above information, it seems reasonable to expect that the impacts of a discrepancy in alliance ratings noted in psychotherapeutic contexts would also be observed in the executive coaching process. If so, divergent assessments of the alliance could present a problem, in that a coach’s inaccurate assessment may lead them to neglect to work on critical relational issues of which they are unaware. Moreover, a coach’s over- or under-estimate might mean that the coach is not in tune with his coachee, or that he or she is not able to recognize the client’s perspective about their relationship, the objectives they are pursuing, the tasks required to reach those objectives, or the bond that has developed between them. A useful framework for examining the working alliance discrepancy in the context of executive coaching is the self-other agreement paradigm that issues from the leadership literature. Though the evaluation of the working alliance does not constitute in itself an evaluation of the coach, the latter may feel a greater responsibility in facilitating the developmental exercise than the coachee. In line, empirical results indicate that clients view the psychotherapist as primarily responsible for alliance formation (Bedi et al., 2005; Bachelor, 1995), a perception that might be shared by the therapist since establishing a good relationship with the client is a key component of any training or certification in psychotherapy, or in executive coaching. Self-other agreement represents the degree to which individuals see themselves as others see them (Atwater et al., 1998; Whittington et al., 2009). Typically, “difference scores are used to represent the congruence between two constructs, which is then treated as a concept in its own right” (Edwards, 2001, p. 265). Difference scores can be treated as a continuous variable, or categorized into one of three agreement groups: over-estimators, accurate and under-estimators of their leadership behaviors in comparison with ratings from their followers (Atwater et al., 1995; Atwater and Yammarino, 1992). Empirical evidence has shown that self-other agreement can be used to predict performance as well as work related perceptions, such as organizational commitment, job satisfaction, and trust (Alimo-Metcalfe, 1998; Atwater et al., 1998, 2005; Atwater and Yammarino, 1992; Bass and Yammarino, 1991; Day et al., 2002; Furnham and Stringfield, 1994; Sosik and Megerian, 1999; Van Velsor et al., 1993; Whittington et al., 2009). In short, overestimation leads to diminished outcomes, accurate estimation leads to enhanced performance, and underestimation is associated with mixed outcomes (Yammarino and Atwater, 1997). These authors explain these findings by proposing that when there is a consensus regarding the expectations of behavior and performance of both the leader and the followers, a solid foundation of trust and commitment develops between them (Whittington et al., 2009). Self-efficacy: a proxy to performance In situations where training aims to develop management skills, the measurement of skills transfer is often a considerable challenge. Consequently, many researchers opt for the measurement of self-efficacy as the main outcome of training, and some coaching studies have begun to do the same (Baron and Morin, 2010; Evers et al., 2006). Self-efficacy is defined as the belief that a person has of being capable of accomplishing a given task (Bandura, 1997). The relationship between self-efficacy and various aspects of organizational life have been observed in numerous studies. For example, in the industrial and organizational psychology, more than 800 articles on self-efficacy have been published in scientific journals in the last 25 years (Judge et al., 2007). These studies
Executive coaching
851
JMD 30,9
852
have notably examined group efficacy (Prussia and Kinicki, 1996), adaptation stress (Schaubroek and Merritt, 1997), creativity and productivity (Tierney and Farmer, 2002), management efficacy, performance and idea generation (Gist, 1989; Luthans and Peterson, 2002; Wood and Bandura, 1989), and adaptation to organizational changes (Judge et al., 1999). The connection between self-efficacy and the performance of complex interpersonal tasks such as negotiation has also been demonstrated many times (Gist and Stevens, 1998; Gist et al., 1991). Furthermore, the results of a meta-analysis of 114 studies published between 1976 and 1998 conducted by Stajkovic and Luthans (1998) showed a significant correlation between self-efficacy and work performance which, according to the authors, translates into a 28-percent improvement in work performance. In line with the above psychotherapy and leadership literature, one can argue that, relative to coachees’ estimates, coaches who overestimate or underestimate the working alliance will not foster as good coaching outcomes as coaches who accurately estimate the working alliance. By extension, coachees who work with over- or under-estimators will develop to a lesser extent than coaches who work with accurate estimators. As such, we tested the following hypothesis in this study: H1. Coachees who work with a coach who is an accurate estimator – in relation to coachees’ ratings – will develop more than coachees who work with a coach who is an under- or an over-estimator. Method Field setting This study was conducted in a large North American manufacturing company that offered its junior and mid-level managers an eight-month leadership development program that addressed various topics, such as leadership, interpersonal communication, power and delegation, and employee development and mobilization. In that program, executive coaching consisted of face-to-face, 75-minute sessions between a certified internal coach and a manager participating in the leadership development program. During the first coaching session, managers were asked to establish three main goals they wanted to work on. These goals had to be related to the skills addressed in the leadership development program. Following a structured process, the coaches’ main responsibility was to guide and support coachees in the attainment of their established goals. Although, the development program suggested one coaching session every two weeks, the specific scheduling was left to the discretion of the coaches and coachees. Participants received between three and eleven coaching sessions during eight months, representing a mean of 5.77 sessions. Qualitative data indicates that lack of time and schedule conflicts were the two key reasons reported by coachees and coaches for not attending one or several coaching sessions. While some dyads have met once almost every two weeks, others, for reasons cited above, have met on a less regular basis. Participants The participants in this study were divided into two groups: coachees and coaches. The coachees were managers who had voluntarily signed up for a leadership development program (n ¼ 127). Of these, 118 managers completed our first questionnaire, and 80 of these managers responded to the questionnaire administered at the end of the program. Survey non-response was mostly attributable to participant absences at the time
questionnaires were distributed, and in a small number of cases, to managers who simply refused to answer. Of this group of 80 participants, seven respondents were excluded from the analysis because they had participated in the program to a very limited extent. Our final sample was thus composed of 73 coachees (63 men, ten women) for a response rate of 57.5 percent. The average age of the coachees was 38 years, 63 percent had a university-level education and their average number of years as a manager was 4.7. The coaches group consisted of 64 executives who had participated in a coaching certification program. Prior to the start of the management skills development program, these senior managers had received two days of coaching training, given by an outside consultant. They then completed their certification by participating in four 2-hour individual meetings with a “master coach” and four 4-hour action learning workshops. Among these participants, 24 (21 men, three women) returned the questionnaire that was sent to them at the end of the program, for a response rate of 37.5 percent. In total, 30 coach-coachee dyads were formed, whereby some coaches were paired with two coachees for the duration of the program. Pairings were arranged to ensure that no coach had a pre-existing organizational authority over the managers he or she coached. The average age of the coaches was 41 years, 79 percent had a university-level education and their average number of years as a manager was 9.3. Data collection The data collection procedure was as follows: prior to the coaching sessions, we collected an initial measure of the coachees’ self-efficacy as well as some socio-demographic data on both coaches and coachees. Eight months later, at the end of the coaching, we collected a second measure of the coachees’ self-efficacy as well as a measure of the working alliance from both the coaches and the coachees. At both times, paper surveys were used. Measures Self-efficacy. In this study, we had the opportunity to collect data for one outcome of coaching, namely self-efficacy with respect to management soft skills. This variable was assessed following the recommendations of Bandura (1997) and Lee & Bobko (1994). These last authors mention that when measuring self-efficacy strength, researchers typically ask individuals for the degree of confidence to perform at specific levels on a specific task (rated on a near-continuous scale) at each specific performance level. Specifically, we used an eight-item, 11-point Likert scale developed specifically for this study, where 0 indicated “Not at all confident” and 10 represented “Completely confident.” All items were created to reflect the content of the leadership development program (e.g. “Today, as a manager, I feel confident in my ability to help my employees learn lessons from the difficulties and setbacks they may encounter.”). All items were examined by two subject matter experts, namely an academic specializing in management skills and the senior consultant who designed the training program. The a coefficients were 0.89 (pre-coaching) and 0.88 (post-coaching). Working alliance. This variable was measured using the Working Alliance Inventory – short version (WAI-S) (Corbie`re et al., 2006; Tracey and Kokotovic, 1989), a 12-item, seven-point Likert scale. In this study, the wording of the original version was slightly adapted to fit the coaching context (e.g. “coach” instead of “therapist”
Executive coaching
853
JMD 30,9
854
and “development needs” instead of “problems”). The WAI-S is widely used in psychotherapy research (Martin et al., 2000). Validation studies have shown that the WAI-S has good construct validity and high reliability (Corbie`re et al., 2006; Tracey and Kokotovic, 1989). Our adapted version of the WAI-S measured three components of the coach-coachee working alliance: (1) goals (e.g. “We are working toward goals that we have agreed on”); (2) tasks (e.g. “My coach and I agreed on the steps to follow to improve my situation”); and (3) bonding (e.g. “My coach and I have developed mutual trust”). Both coaches and coachees completed the WAI-S. a-coefficients were 0.90 (coaches) and 0.93 (coachees). Working alliance discrepancy. To measure this variable, we followed the procedure first developed by Atwater and Yammarino (1992) and reproduced by other studies (Sosik and Megerian, 1999; Ostroff et al., 2004). In short, coaches were categorized into one of the three agreement groups, relative to the ratings of coachees. The rating difference for each coach-coachee dyad was computed and then each coach’s difference score was compared to the mean difference score. Specifically, as in previous studies cited above, coaches whose difference scores were one-half of a standard deviation or more above the mean difference were categorized as over-estimators. Coaches whose difference scores were one-half of a standard deviation or more below the mean difference were categorized as under-estimators. Coaches whose difference scores were within one-half of a standard deviation of the mean difference were categorized as accurate estimators (Atwater and Yammarino, 1992, p. 152). Frequencies of the categorizations were as follows: 11 coaches were categorized as accurate estimators, ten as overestimators, and nine as underestimators. Results Preliminary analyses Before proceeding with the testing of our hypothesis, we first tested for significant differences between the 30 coachees for whom we were able to obtain data from their respective coaches and the 43 coachees for whom we had no data from their coaches (as mentioned above, only 24 coaches filled out all questionnaires). Findings showed no significant differences in regard to the following socio-demographic characteristics: age, gender, education, or number of years as a manager. Results also indicated no significant difference between these two groups for pre-coaching self-efficacy (t71 ¼ 1.10, n.s.) and post-coaching self-efficacy (t71 ¼ 2 0.49, n.s.). Descriptive analyses Table I presents both the descriptive statistics and partial intercorrelations of the variables under study. Partial correlations were made, controlling for pre-coaching self-efficacy, because we were interested in examining the effect of working alliance discrepancy on the development of self-efficacy. Post-coaching self-efficacy, thus served as the dependant variable (DV). It is interesting to note that the means of the working alliance ratings as assessed by coachees and coaches are quite similar, and relatively strong. We can also observe that the correlation between these two variables is marginally significant
(rp ¼ 0.35, p , 0.10) and a little stronger than the low to moderate correlation observed in previous studies (Cecero et al., 2001; Fenton et al., 2001). Table II presents the means for working alliance ratings and post-coaching self-efficacy for the three categorizations under study, namely the under-estimators, accurate estimators and over-estimators.
Executive coaching
Testing our hypothesis To test our hypothesis, a one-way analysis of covariance (ANCOVA) was conducted with post-coaching self-efficacy as the DV and pre-coaching self-efficacy and coachee’s working alliance assessment as the two covariates. Since the correlation between coachees’ working alliance assessment and our DV is strong (rp ¼ 0.51, p , 0.01), using the former variable as a covariate controlled for the effect it might have on another correlation, namely the correlation between working alliance discrepancy and the DV. After all, according to our results, if coachees rate their alliance as high, they are most likely to present a high score on their self-efficacy post-coaching, and their coaches are more likely to be categorized as under-estimators. The independent variable, namely the working alliance discrepancy, was composed of the following three groups: under-estimators, accurate estimators, and over-estimators. Table III presents the results of the ANCOVA. Results from the above table show that no significant effects were observed for pre-coaching self-efficacy (F(1,25) ¼ 3.25, p ¼ n.s., partial h2 ¼ 0.12) or for coachee working alliance assessment (F(1,25) ¼ 0.42, p ¼ n.s., partial h2 ¼ 0.02. Second, findings indicate a significant group effect on post-coaching self-efficacy after controlling for the two covariates (F(2,25) ¼ 9.57, p , 0.001). Results also demonstrate a very strong relationship between the working alliance discrepancy and self-efficacy, as assessed by a partial h2, with the working alliance discrepancy accounting for 43 percent of the variance of the dependent variable, holding pre-coaching self-efficacy and coachee working alliance assessment constant.
855
Variables 1. 2. 3. 4.
a
Working alliance – coachee Working alliance – coach Working alliance discrepancy Post-coaching self-efficacy
0.93 0.90 – 0.88
Mean 5.90 5.91 0.004 7.96
SD
2
3
4
0.78 0.70 0.78 0.75
0.35 * * *
0.56 * * 0.58 * *
0.52 * * 0.30 2 0.72 * * –
– .
–
Notes: *p , 0.05, * *p , 0.01, * * * , 0.10, n ¼ 30; control variable for correlations, pre-coaching self-efficacy; mean ¼ 6.96; SD ¼ 0.96
Group
n
Mean coachees’ working alliance ratings
Under-estimators Accurate estimators Over-estimators
9 11 10
6.33 6.03 5.37
Note: aAdjusted means
SD
Mean coaches’ working alliance ratings
0.77 0.60 0.35
5.43 5.97 6.25
SD
Mean postcoaching selfefficacya
SD
0.72 0.67 0.42
8.61 8.05 7.28
0.57 0.51 0.44
Table I. Means, standard deviations and partial correlations for variables under study
Table II. Means for working alliance and post-coaching self-efficacy
JMD 30,9
856
Follow-up tests were conducted to evaluate pairwise differences among the adjusted means of the three groups. The Holm’s sequential Bonferroni procedure was used to control for Type I errors across the three pairwise comparisons (Field, 2005; Thompson, 2006). Significant differences were found in the adjusted means between groups. Specifically, contrast analysis revealed that coachees in the over-estimators group had a significantly different post-coaching self-efficacy than coachees in the under-estimators group (contrast estimates ¼ 1.34, p , 0.001) and coachees in the accurate estimators group (contrast estimates ¼ 0.77, p , 0.001). There was also a significant difference between the accurate estimators group and the under-estimators group (contrast estimates ¼ 20.53, p , 0.05). In short, these results revealed that greater the coach-favouring discrepancy in views about the working alliance, the less his or her coachee developed. Our hypothesis, which stated that coachees who work with a coach who is an accurate estimator – in comparison with coachees’ ratings – will develop more than coachees who work with a coach who is an under- or over-estimator, is not supported. Discussion The objective of this study was to explore the effect of working alliance rating discrepancies on one key coaching outcome, namely self-efficacy. Our results indicate that coachees having worked with coaches who overestimate the working alliance experienced less growth in self-efficacy than coachees having worked with coaches who accurately estimated the working alliance and that coachees having worked with coaches who accurately estimated the working alliance experienced less growth in self-efficacy than coachees having worked with coaches who underestimated the working alliance. Thus, in this study, coaches’ underestimation of the working alliance is the best predictor of post-coaching self-efficacy in coachees. This result differs from findings in the psychotherapy literature, which have shown that similarity or low client-therapist rating discrepancies in working alliance is the best predictor of positive therapy outcomes (Hersoug et al., 2002; Kivlighan and Shaughnessy, 1995). One possible explanation for our findings comes from de Haan (2008, p. 104), who advances that: [. . .] coaches all have the tendency to want to eliminate doubts and anxieties. [. . .] The more we coach, the more we ourselves build up long-term defenses against our tensions and existential doubts without realizing it. This is perhaps the main reason why inexperienced therapists often appear to perform better than experienced ones (Dumont, 1991). They set to work with more enthusiasm, involvement and vulnerability. Source of variation
Table III. ANCOVA analysis results
Corrected model Intercept Pre-coaching self-efficacy Working alliance – coachee Working alliance discrepancy (three groups) Error Total Corrected total
Sum of squares
df
Mean2
F-statistics
Prob.
10.245 5.680 0.794 0.102 4.673 6.103 1,918.391 16.348
4 1 1 1 2 25 30 29
2.561 5.688 0.794 0.102 2.336 0.244
10.492 23.299 3.253 0.417 9.570
0.001 0.001 0.08 0.52 0.001
In consequence, this author encourages coaches to coach with an “ongoing and deliberately maintained doubt as their only certainty” (p. 106). According to this argument, coaches who overestimate the alliance with their coachee may feel overconfident about the coaching they are providing, which might lead them to be less sensitive to signs of what the coachee is experiencing, and not take the initiative to verify the coachee’s comfort level with the way coaching is proceeding. On the other hand, coaches who underestimate the alliance with their coachee may be more humble and have more doubts about their capacity to support the development of others. This stance may lead them to pay closer attention to what the client is experiencing and, consequently, to offer a coaching that is more person-centered than problem-centered. Since the “only thing the coach can actually influence to exert albeit an indirect influence on the outcome of coaching is the relationship between coach and coachee” (de Haan, 2008, p. 53), a coach who puts greater emphasis on the coaching relationship might provide better support to the development of others and, in so doing, facilitate the enhancement of others’ self-efficacy. Another explanation for our findings rests on a coach’s inability to perceive what is called an alliance rupture or a breakdown in the collaborative process in the psychotherapy literature (Safran and Muran, 2006). This inability might be as detrimental in the context of executive coaching as it is in the psychotherapy context (Safran and Muran, 1996, 2000). In line, results from empirical studies have suggested that, when faced with therapeutic impasses, therapists’ rigid adherence to prescribed techniques failed to repair such ruptures and even exacerbated them (Castonguay et al., 1996). These results suggest that in a coaching context, a coach who feels that the working alliance or the coachee are not developing as well as they should be might become more concerned with procedures and results. This in turn would negatively impact the coachee. A coach absolutely needs to be sensitive to the coach-coachee interaction during the session, in the here and now (Rogers, 1961). Results for this study have important practical implications for coaching. First, they suggest that a coach should regularly evaluate the working alliance with his or her coachee to make sure that he or she adequately perceives feelings from the client in regard to the coaching process. To do so, one might use a formal questionnaire (e.g. the WAI-S) or simply proceed with an open discussion. If this (regular) exercise reveals a gap in working alliance perceptions, addressing that gap should take precedence over all other goals for the coach (Castonguay et al., 2006). To maximize success, coaches can also take into account advice given to therapists about the working alliance (Safran et al., 2001, 1990). This advice is as follows: First, therapists should be aware that patients often have negative feelings about the way therapy is going or the therapeutic relationship, but fearing the negative reactions of their therapist, they are reluctant to address them. Therapists should thus take the initiative in exploring what is transpiring in the relationship when signs of alliance rupture appear, for instance overt expression of negative sentiments, hostility, disagreement about the goals or tasks, and compliance and avoidance maneuvers, to name a few (for an extended review of alliance rupture markers, Safran et al., 1990). Second, it is important for clients to have the opportunity to express negative feelings about the therapeutic process, should they emerge. Third, when this takes place, therapists should adopt an open, non-defensive stance and accept responsibility for their contribution to the interaction, while empathizing with the client’s experience.
Executive coaching
857
JMD 30,9
858
Some research evidence suggests that resolution of working alliance impasses can be potential change events associated with good therapy outcomes. For this reason, coaches must be sensitized to the importance of addressing these impasses, even though it may be an uncomfortable or threatening experience for them – “one that activates concerns around competency as a [coach] ” (Safran et al., 1990, p. 164). This clarification of what each party is experiencing could also allow the coachee to gain an awareness of the role he or she plays in the difficulties encountered in the coaching relationship, which in turn could help the coachee to adopt a different stance from that point forward. In summary, a coach should exercise caution about his or her perceptions of what is going on in the coaching room, and not take for granted the satisfaction of his or her client. Limitations There are several limitations associated with the study. First and foremost, a larger sample would have provided more statistical power and allowed us to use more sophisticated analyses than difference scores and categories to represent agreement. A discrepancy in working alliance ratings can be considered as a difference score, or algebraic scores, a type of analysis that has been criticized (Edwards, 1994b, 1995, 2001, 2002; Irving and Meyer, 1999). Among its limitations, authors note low reliability, especially when the two components of the difference score are strongly correlated, as it is often the case. In line, we observe a non significant moderate effect between the two components of our difference score, namely working alliance assessed by the coach and working alliance assessed by the coachee (rp ¼ 0.35, n.s.), which could have lighten the reliability problem. These authors also suggest that the integration of two components in one difference score does not allow the estimation of their differentiate effects on the dependent variable, and due to statistical constraints, lower significantly the variance associated with the dependent variable (26 percent according to Edwards (2001). To address such limitations, Edwards (1994a) and Edwards and Parry (1993) suggested using polynomial regression to obtain results that illustrate more deeply the complexity of the congruence effects. Indeed, the response surface methodology associated with this type of regression use three components in its analysis (the two assessments and their difference score) instead of the two components of the algeabric score, then allowing the estimation of the differentiate effects of the two assessments on the dependent variable. In replication studies, Ostroff et al. (2004) and Atwater et al. (1998), instead of using categories of difference score (over-, under-estimators, accurate), have used polynomial regression to explore consequences of inter-raters congruence on managerial efficacy. Their results point toward the same conclusions than their past studies that used difference scores. However, the explained variance was higher. Unfortunately, our small sample did not produce enough statistical power for the application of polynomial regression. However, given the number of participants involved in coaching programs offered in-house by organisations, which is seldom superior to 100, it becomes difficult for researchers to study such developmental exercise with large sample, especially with the constraints of a pre-post design and the pairings of coaches and coachees. In parallel, few studies about coaching compared more than the number of dyads we have studied (Luthans and Peterson, 2003; Evers et al., 2006; Jones et al., 2006; Olivero et al., 1997). Also, the few studies that had a large sample did not paired coachees and coaches as we did (Smither et al., 2003; Thach, 2002). The size sample limitation in coaching contexts represents an important challenge for
researchers aiming to analyze the complexity of the coaching process with multivariate statistics. We encourage researchers in coaching interested in studying dyads to continue their quest toward larger samples, which could permit the application of polynomial regression. Such statistical analysis could reproduce or nuance the results we obtained. At last, it is important to underline that our results probably under-estimate the impact of the coach-coachee relationship on the coachees’ self-efficacy since polynomial regression allows to enhance the explained variance while eliminating the methodological difficulties associated with algeabric scores. Furthermore, there are some limitations as to the generalization of this study’s findings. First, the context of this study was rather unique, in that it was conducted in a field setting that used recently trained internal coaches, who may differ significantly in competencies from external coaches. In general, external coaches have extensive coaching training, either in psychology or in coaching per se, as well as an expertise developed from multiple situations and organizational contexts they have encountered. For a description of pros and cons associated with the utilization of internal vs external coaches, see Wasylyshyn (2003) and de Haan (2008). Despite these limitations, the present study makes several noteworthy contributions that shed light on the coaching process. Furthermore, it confirmed the theoretical and practical importance of the working alliance factor in the field of coaching. Given organisations’ increasingly prominent use of executive coaching, understanding the conditions under which coaching works best is highly relevant (Paradise and Mosley, 2009). References Alimo-Metcalfe, B. (1998), “360 degree feedback and leadership development”, International Journal of Selection and Assessment, Vol. 6 No. 1, pp. 35-44. Atwater, L.E. and Yammarino, F.J. (1992), “Does self-other agreement on leadership perceptions moderate the validity of leadership and performance predictions?”, Personnel Psychology, Vol. 45 No. 1, pp. 141-64. Atwater, L.E., Roush, P. and Fischthal, A. (1995), “The influence of upward feedback on self-and follower ratings of leadership”, Personnel Psychology, Vol. 48 No. 1, pp. 35-59. Atwater, L.E., Ostroff, C., Yammarino, F.J. and Fleenor, J.W. (1998), “Self-other agreement: does it really matter?”, Personnel Psychology, Vol. 51 No. 3, pp. 577-98. Atwater, L.E., Waldman, D., Ostroff, C., Robie, C. and Johnson, K.M. (2005), “Self-other agreement: comparing its relationship with performance in the US and Europe”, International Journal of Selection and Assessment, Vol. 13 No. 1, pp. 25-40. Bachelor, A. (1995), “Clients’ perception of the therapeutic alliance: a qualitative analysis”, Journal of Counseling Psychology, Vol. 42 No. 3, pp. 323-37. Bandura, A. (1997), Self-efficacy: The Exercise of Control, W.H. Freeman, New York, NY. Baron, L. and Morin, L. (2009), “The coach-coachee relationship in executive coaching: a field study”, Human Resource Development Quarterly, Vol. 20 No. 1, pp. 85-106. Baron, L. and Morin, L. (2010), “The impact of executive coaching on self-efficacy related to management soft-skills”, Leadership & Organization Development Journal, Vol. 31 No. 1, pp. 18-38. Bass, B.M. and Yammarino, F.J. (1991), “Congruence of self and others ratings of naval officers for understanding successful performance”, Applied Psychology – An International Review, Vol. 40 No. 4, pp. 437-54.
Executive coaching
859
JMD 30,9
Bedi, R.P., Davis, M.D. and Williams, M. (2005), “Critical incidents in the formation of the therapeutic alliance from the client’s perspective”, Psychotherapy: Theory, Research, Practice, Training, Vol. 42 No. 3, pp. 311-23. Berry, R.M. (2005), “A comparison of face-to-face and distance coaching practices: the role of the working alliance in problem resolution”, Department of Counselling an Psychological Services, Doctoral thesis, Georgia State University, Atlanta, GA.
860
Bono, J.E., Purvanova, R.K., Towler, A.J. and Peterson, D.B. (2009), “A survey of executive coaching practice”, Personnel Psychology, Vol. 62 No. 2, pp. 361-404. Bordin, E.S. (1979), “The generalizability of the psychoanalytic concept of the working alliance”, Psychotherapy: Theory, Research, and Practice, Vol. 16 No. 3, pp. 252-60. Castonguay, L.G., Constantino, M.J. and Holtforth, M.G. (2006), “The working alliance: where are we and where should we go?”, Psychotherapy: Theory, Research, Practice, Training, Vol. 43 No. 3, pp. 271-9. Castonguay, L.G., Goldfried, M.R., Wiser, S., Raue, P.J. and Hayes, A.M. (1996), “Predicting the effect of cognitive therapy for depression: a study of unique and common factors”, Journal of Consulting and Clinical Psychology, Vol. 64 No. 3, pp. 497-504. Cecero, J.J., Fenton, L.R., Frankforter, T.L., Nich, C. and Carrol, K.M. (2001), “Focus on therapeutic alliance: the psychometric properties of six measures across three treatments”, Psychotherapy, Vol. 38 No. 1, pp. 1-11. Corbie`re, M., Bisson, J., Lauzon, S. and Ricard, N. (2006), “Factorial validation of a french short-form of the working alliance inventory”, International Journal of Methods in Psychiatric Research, Vol. 15 No. 1, pp. 36-45. Day, D.V., Schleicher, D.J., Unckless, A.L. and Hiller, N.J. (2002), “Self-monitoring personality at work: a meta-analysis”, Journal of Applied Psychology, Vol. 87 No. 2, pp. 390-401. de Haan, E. (2008), Relational Coaching: Journeys Towards Mastering One-to-One Learning, Wiley, West Sussex. Dingman, M.E. (2004), “The effects of executive coaching on job-related attitudes. Virginia beach”, Doctorate thesis, Regent University, Virginia. Douglas, C. and Morley, W. (2000), Executive Coaching: An Annotated Bibliography, Center for Creative Leadership, Greensboro, NC. Dumont, F. (1991), “Expertise in psychotherapy: inherent liabilities of becoming experienced”, Psychotherapy, Vol. 28 No. 3, pp. 422-8. Eames, V. and Roth, A. (2000), “Patient attachment orientation and the early working alliance: a study of patient and therapist reports of alliance quality and ruptures”, Journal of Psychotherapy Research, Vol. 10 No. 4, pp. 421-34. Edwards, J.R. (1994a), “Regression analysis as an alternative to difference scores”, Journal of Management, Vol. 20 No. 3, pp. 683-9. Edwards, J.R. (1994b), “The study of congruence in organizational behavior research: critique and proposed alternative”, Organizational Behavior and Human Decision Processes, Vol. 58 No. 1, pp. 683-9. Edwards, J.R. (1995), “Alternatives to difference scores as dependent variables in the study of congruence in organizational research”, Organizational Behavior and Human Decision Processes, Vol. 64 No. 3, pp. 307-24. Edwards, J.R. (2001), “Ten difference score myths”, Organizational Research Methods, Vol. 4 No. 3, pp. 265-87.
Edwards, J.R. (2002), “Alternative to difference scores: polynomial regression analysis and response surface methodology”, in Drasgow, F. and Schmitt, N. (Eds), Measuring and Analysing Behavior in Organizations, Jossey-Bass, San Francisco, CA, pp. 350-99.
Executive coaching
Edwards, J.R. and Parry, M.E. (1993), “On the use of polynomial regression equations as an alternative to difference scores in organizational research”, Academy of Management Journal, Vol. 36 No. 6, pp. 1577-613. Evers, W.J.G., Brouwers, A. and Tomic, W. (2006), “A quasi-experimental study on management coaching effectiveness”, Consulting Psychology Journal: Practice and Research, Vol. 58 No. 3, pp. 174-82. Fatien, P. and Amado, G. (2009), Value of Ambiguity – The Case of Executive Coaching, European Group for Organizational Studies (EGOS), Barcelona. Fenton, L.R., Cecero, J.J., Nich, C., Frankforter, T.L. and Carrol, K.M. (2001), “Perspective is everything: the predictive validity of six working alliance instruments”, Journal of Psychotherapy Practice and Research, Vol. 10 No. 4, pp. 262-8. Field, A. (2005), Discovering Statistics Using SPSS, Sage, London. Furnham, A. and Stringfield, P. (1994), “Congruence of self and subordinate ratings of managerial practices as a correlate of supervisor evaluation”, Journal of Occupational & Organizational Psychology, Vol. 67 No. 1, pp. 57-67. Gist, M.E. (1989), “The influence of training method on self-efficacy and idea generation among managers”, Personnel Psychology, Vol. 42 No. 4, pp. 787-805. Gist, M.E. and Stevens, C.K. (1998), “Effects of practice conditions and supplemental training method on cognitive learning and interpersonal skill generalization”, Organizational Behavior and Human Decision Processes, Vol. 75 No. 2, pp. 142-69. Gist, M.E., Stevens, C.K. and Bavetta, A.G. (1991), “Effects of self-efficacy and post-training intervention on the acquisition and maintenance of complex interpersonal skills”, Personnel Psychology, Vol. 44 No. 4, pp. 837-61. Greenson, R.R. (1965), “The working alliance and the transference neuroses”, Psychoanalysis Quarterly, Vol. 34 No. 2, pp. 155-81. Hall, D.T., Otazo, K.L. and Hollenbeck, G.P. (1999), “Behind closed doors: what really happens in executive coaching”, Organizational Dynamics, Vol. 27 No. 3, pp. 39-52. Hersoug, A.G., Monsen, J.T., Havik, O.E. and Hoglend, P. (2002), “Quality of early working alliance in psychotherapy: diagnoses, relationship and intrapsychic variables as predictors”, Psychotherapy and Psychosomatics, Vol. 71 No. 1, pp. 18-27. Horvath, A.O. (2005), “The therapeutic relationship: research and theory. An introduction to the special issue”, Psychotherapy Research, Vol. 15 Nos 1/2, pp. 3-7. Horvath, A.O. and Bedi, R.P. (2002), “The alliance”, in Norcross, J.C. (Ed.), Psychotherapy Relationships that Work: Therapists Contributions and Responsiveness to Patients, Oxford University Press, New York, NY, pp. 37-69. Horvath, A.O. and Greenberg, L.S. (1989), “Development and validation of the working alliance inventory”, Journal of Counseling Psychology, Vol. 36 No. 2, pp. 223-33. Horvath, A.O. and Symonds, B.D. (1991), “Relation between working alliance and outcome in psychotherapy: a meta-analysis”, Journal of Counseling Psychology, Vol. 38 No. 2, pp. 139-49. Hughes, P.D. and Campbell, A. (2009), Learning and Development Outlook 2009: Learning in Tough Times, Conference Board of Canada, Ottawa, ON.
861
JMD 30,9
862
Irving, P. and Meyer, J. (1999), “On using residual and difference scores in the measurement of congruence The case of met expectations research”, Personnel Psychology, Vol. 52 No. 1, pp. 85-95. Jones, R.A., Rafferty, A.E. and Griffin, M.A. (2006), “The executive coaching trend: towards more flexible executives”, Leadership & Organization Development Journal, Vol. 27 No. 7, pp. 584-6. Joo, B.K. (2005), “Executive coaching: a conceptual framework from an integrative review of practice and research”, Human Resource Development Review, Vol. 4 No. 4, pp. 462-88. Judge, T.A., Thoresen, C.J., Pucik, V. and Welbourne, T.M. (1999), “Managerial coping with organizational change: a dispositional perspective”, Journal of Applied Psychology, Vol. 84 No. 1, p. 107. Judge, T.A., Jackson, C.L., Shaw, J.C., Scott, B.A. and Rich, B.L. (2007), “Self-efficacy and work-related performance: the integral role of individual differences”, Journal of Applied Psychology, Vol. 92 No. 1, pp. 107-27. Kampa, S. and White, R.P. (2002), “The effectiveness of executive coaching: what we know and what we still need to know”, in Lowman, R.L. (Ed.), The California School of Organizational Studies. A Comprehensive Guide to Theory, Skills, and Techniques: Handbook of Organizational Consulting Psychology, Jossey-Bass, San Francisco, CA, pp. 139-58. Kampa-Kokesch, S. and Anderson, M.Z. (2001), “Executive coaching: a comprehensive review of the literature”, Consulting Psychology Journal: Practice and Research, Vol. 53 No. 4, pp. 205-28. Kilburg, R.R. (2000), Executive Coaching: Developing Managerial Wisdom in a World of Chaos, American Psychological Association, Washington, DC. Kilburg, R.R. (2001), “Facilitating intervention adherence in executive coaching: a model and methods”, Consulting Psychology Journal: Practice & Research, Vol. 53 No. 4, pp. 251-67. Kivlighan, D.M.J. and Shaughnessy, P. (1995), “An analysis of the development of the working alliance using hierarchical linear modeling”, Journal of Counseling Psychology, Vol. 42 No. 3, pp. 338-49. Latham, G.P. and Heslin, P.A. (2003), “Training the trainee as well as the trainer: lessons to be learned from clinical psychology”, Canadian Psychology, Vol. 44 No. 3, pp. 218-31. Lee, C. and Bobko, P. (1994), “Self-efficacy beliefs: comparison of five measures”, Journal of Applied Psychology, Vol. 79 No. 3, pp. 364-9. Lowman, R.L. (2005), “Executive coaching: the road to Dodoville needs paving with more than good assumptions”, Consulting Psychology Journal: Practice and Research, Vol. 57 No. 1, pp. 90-6. Luborsky, L. (1976), “Heling alliances in psychotherapy”, in Cleghorn, J.L. (Ed.), Succesful Psychotherapy, Brunner/Mazel, New York, NY. Luthans, F. and Peterson, S.J. (2002), “Employee engagement and manager self-efficacy”, Journal of Management Development, Vol. 21 No. 5, pp. 376-87. Luthans, F. and Peterson, S.J. (2003), “360-degree feedback with systematic coaching: empirical analysis suggests a winning combination”, Human Resource Management, Vol. 42 No. 3, p. 243. McGovern, J., Lindemann, M., Vergara, M., Murphy, S., Barker, L. and Warrenfeltz, R. (2001), “Maximizing the impact of executive coaching: behavioral change, organizational outcomes, and return on investment”, The Manchester Review, Vol. 6 No. 1, pp. 1-9. Mallinckrodt, B. (1992), “Client’s representations of childhood emotional bonds with parents social support, and formation of the working alliance”, Journal of Counseling Psychology, Vol. 38 No. 4, pp. 401-9.
Martin, D.J., Gaske, J.P. and Davis, M.K. (2000), “Relation of the therapeutic alliance with outcome and other variables: a meta-analytic review”, Journal of Consulting and Clinical Psychology, Vol. 68 No. 3, pp. 438-50. O’Leonard, K. (2009), The Corporate Learning Factbook: Statistics, Benchmarks, and Analysis of the US Corporate Training Market, Bersin & Associates, Oakland, CA. Olivero, G., Bane, K.D. and Kopelman, R.E. (1997), “Executive coaching as a transfer of training tool: effects on productivity in a public agency”, Public Personnel Management, Vol. 26 No. 4, pp. 461-9. Ostroff, C., Atwater, L.E. and Feinberg, B.J. (2004), “Understanding self-other agreement: a look at rater and rate characteristics, context, and outcomes”, Personnel Psychology, Vol. 57 No. 2, pp. 333-75. Paradise, A. and Mosley, J. (2009), “Learning in a down economy”, TþD, Vol. 63 No. 4, pp. 44-9. Peterson, D.B. (1996), “Executive coaching at work: the art of one-on-one change”, Consulting Psychology Journal: Practice and Research, Vol. 48 No. 2, pp. 78-86. Prussia, G.E. and Kinicki, A.J. (1996), “A motivational investigation of group effectiveness using social-cognitive theory”, Journal of Applied Psychology, Vol. 81 No. 2, pp. 187-98. Rogers, C. (1961), On Becoming a Person, Houghton Mifflin, Boston, MA. Safran, J.D. and Muran, J.C. (1996), “The resolution of ruptures in the therapeutic alliance”, Journal of Consulting and Clinical Psychology, Vol. 64 No. 3, pp. 458-77. Safran, J.D. and Muran, J.C. (2000), Negotiating the Therapeutic Alliance: A Relational Treatment Guide, Guilford Press, New York, NY. Safran, J.D. and Muran, J.C. (2006), “Has the concept of the therapeutic alliance outlived its usefulness?”, Psychotherapy: Theory, Research, Practice, Training, Vol. 43 No. 3, pp. 286-91. Safran, J.D., Crocker, P., McMain, S. and Murray, P. (1990), “Therapeutic alliance rupture as a therapy event for empirical investigation”, Psychotherapy, Vol. 27 No. 2, pp. 154-65. Safran, J.D., Muran, J.C., Samstag, L.W. and Stevens, C.K. (2001), “Reparigin alliance ruptures”, Psychotherapy, Vol. 38 No. 4, pp. 406-12. Schaubroek, J. and Merritt, D.E. (1997), “Divergent effects of job control on coping with work stressors: the key role of self-efficacy”, Academy of Management Journal, Vol. 40 No. 3, pp. 738-54. Smither, J.W., London, M., Flautt, R., Vargas, Y. and Kucine, I. (2003), “Can working with an executive coach improve multisource feedback ratings over time? A quasi-experimental field study”, Personnel Psychology, Vol. 56 No. 1, pp. 23-44. Sosik, J.J. and Megerian, L.E. (1999), “Understanding leader emotional intelligence and performance: the role of self-other agreement on transformational leadership perceptions”, Group & Organization Management, Vol. 24 No. 3, pp. 367-90. Sperry, L. (1993), “Working with executives; consulting, counseling, and coaching”, Individual Psychology, Vol. 49 No. 2, pp. 257-66. Stajkovic, A.D. and Luthans, F. (1998), “Self-efficacy and work-related performance: a meta-analysis”, Psychological Bulletin, Vol. 124 No. 2, pp. 240-61. Stober, D.R. and Parry, C. (2005), “Current challenges and future directions in coaching research”, in Grant, A.M., Cavanagh, M.J. and Kemp, T. (Eds), Evidence-Based Coaching: Contributions from the Behavioral Sciences, Vol. 1, Australian Academic Press, Bowen Hills, pp. 13-19. Thach, E.C. (2002), “The impact of executive coaching and 360 feedback on leadership effectiveness”, Leadership & Organization Development Journal, Vol. 23 Nos 3/4, p. 205.
Executive coaching
863
JMD 30,9
864
Thompson, B. (2006), Foundations of Behavioral Statistics: An Insight-Based Approach, The Guilford Press, New York, NY. Tierney, P. and Farmer, S.M. (2002), “Creative self-efficacy: its potential antecedents and relationship to creative performance”, Academy of Management Journal, Vol. 45 No. 4, pp. 1137-48. Tobias, L.L. (1996), “Coaching executives”, Consulting Psychology, Vol. 48 No. 2, pp. 87-95. Tracey, T.J. and Kokotovic, A.M. (1989), “Factor structure of the working alliance inventory”, Psychological Assessment, Vol. 1 No. 3, pp. 207-10. Van Velsor, E., Taylor, S. and Leslie, J.B. (1993), “An examination of the relationships among self-perception accuracy, self-awareness, gender, and leader effectiveness”, Human Resource Management, Vol. 32 Nos 2/3, pp. 249-63. Wasylyshyn, K.M. (2003), “Executive coaching: an outcome study”, Consulting Psychology Journal: Practice and Research, Vol. 55 No. 2, pp. 94-106. Whetten, D.A. and Cameron, K.S. (2007), Developing Management Skills, 7th ed., Pearson Prentice-Hall, Upper Saddle River, NJ. Whittington, J.L., Coker, R.H., Goodwin, V.L., Ickes, W. and Murray, B. (2009), “Transactional leadership revisited: self-other agreement and its consequences”, Journal of Applied Social Psychology, Vol. 39 No. 8, pp. 1860-86. Wood, R. and Bandura, A. (1989), “Social cognitive theory of organizational management”, Academy of Management Review, Vol. 14 No. 3, pp. 361-84. Yammarino, F.J. and Atwater, L.E. (1997), “Do managers see themselves as others see them? Implications of self-other rating agreement for human resources management”, Organizational Dynamics, Vol. 25 No. 4, pp. 35-44. Zeus, P. and Skiffington, S. (2001), The Complete Guide to Coaching at Work, McGraw-Hill, Roseville, CA. Corresponding author Louis Baron can be contacted at:
[email protected]
To purchase reprints of this article please e-mail:
[email protected] Or visit our web site for further details: www.emeraldinsight.com/reprints
