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The relationship of organizational culture to balanced scorecard effectiveness.
Article Type:
Survey
Subject:
Educational services industry
Corporate culture
Business performance management
Authors:
Deem, Jackie W.
Barnes, Barry
Segal, Sabrina
Preziosi, Robert
Pub Date:
09/22/2010
Publication:
Name: SAM Advanced Management Journal Publisher: Society for the Advancement of Management Audience: Trade Format: Magazine/Journal Subject: Business; Business, general Copyright: COPYRIGHT 2010 Society for the Advancement of Management ISSN: 0036-0805
Issue:
Date: Autumn, 2010 Source Volume: 75 Source Issue: 4
Topic:
Event Code: 200 Management dynamics Computer Subject: Company business management
Organization:
Company Name: Kaplan University
Persons:
Named Person: Norton, David P.
Geographic:
Geographic Scope: United States

Accession Number:
250999200
Full Text:
The balanced scorecard, developed by Kaplan and Norton in 1992, gained enormous popularity as a way to "translate a company's strategy into specific measurable objectives." In practice, however, relatively few of those adopting the BSC seemed to achieve measurable benefits. Why the shortfall? Was an organization's culture a deciding factor, as Kaplan and Norton posited? A literature search turns up significant empirical research supporting this link, which the authors further tested with a field-type study. The target population was county government employees in one of the 10-most populated counties in the U.S. that had implemented a BSC. The statistical analysis of survey results confirmed the positive link between BSC effectiveness and organizational culture, particularly four distinct aspects: involvement, consistency, adaptability, and mission trait.

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Since its development, the Balanced Scorecard (BSC) has gained widespread popularity. The Bain & Company Management Tools and Trends 2009 reports that 53% of the respondents were using the BSC as part of their strategic decision-making process. Even though the tool has been widely implemented, many, if not most of the user companies believe that long-term results will not be realized (Niebecker, Eager, and Kubitza, 2008). In fact, fewer than 20% of companies utilizing the BSC have realized measurable performance improvement (Williams, 2004). Buytendijk (2007) proposes that the perception that implementation of a BSC, in and of itself, will lead to organizational alignment is a "fairy tale."

Bititci, Mendibil, Nudurupati, Turner, and Garengo (2004) posit that implementing and using such performance measurement systems is greatly affected by organizational culture and management styles. Indeed, Kaplan and Norton (2004) observed that companies with successful BSC implementations "had a culture in which people were deeply aware of and internalized the mission, vision, and core values needed to execute the company's strategy."

In spite of the apparent relationship between organizational culture and BSC effectiveness, there has been little research on the subject. With the widespread use of the BSC and, at the same time, a high level of BSC project failure, future research in this area is warranted.

This article presents results of a study that examines the relationship between organizational culture and Balanced Scorecard effectiveness.

The Balanced Scorecard

Background. The BSC was developed by Robert S. Kaplan and David P. Norton and published in 1992. It was the result of a year-long study that arose out of a general notion that as knowledge became a basis for competition, conventional financial measures were becoming obsolete (Kaplan and Norton 1992).

The term balanced reflects the balanced consideration given to long- and short-term objectives, financial and nonfinancial measures, leading and lagging indicators, and external and internal performance perspectives (Kaplan and Norton, 1996a). The basis for the BSC was the causal linkage of performance measures, both financial and nonfinancial, from four different perspectives: innovation and learning; internal business; customer; and last, but not least, the financial (Kaplan and Norton, 1992). The system involves four processes: 1) Clarifying and translating the vision; 2) Communicating and linking; 3) Business planning and setting targets; and 4) Strategic feedback and learning. As a performance measurement system, the BSC combined a multitude of performance measures, related to different strategic objectives, into a single report. At the same time, the BSC helped top management avoid "sub-optimization" (Kaplan and Norton, 1992), by creating a picture of how changes implemented to produce improvements in one area can adversely affect another area.

BSC Research. Most of the research to date regarding the BSC concentrates on the relationship to firm performance. Kaplan and Norton (1996b, 2001) discuss their research, now spanning 17 years, throughout their publications. The research cited takes the form of case studies and generally provides anecdotal evidence supporting the proposition that a properly designed and implemented BSC can result in overall performance improvement for the organization. However, they provide no empirical data to support their hypotheses.

Empirical research regarding the relationship of the BSC to firm performance has shown mixed results (Davis and Albright, 2004). Davis and Albright posit two possible reasons for the lack of consistent findings: 1) The results may indicate a lack of linkage between the BSC measures chosen and the targeted financial objectives; and 2) The use of cross-sectional analysis, in the studies cited previously, allow the comparison of performance and performance measures only at one point in time.

Kaplan and Norton (1992) recognized that the BSC would not be effective for all organizations. They posited that "Even an excellent set of balanced scorecard measures does not guarantee a winning strategy. The balanced scorecard can only translate a company's strategy into specific measurable objectives" (Kaplan and Norton, 1992).

In fact, Williams (2004) reports that fewer than 20% of the companies with BSC projects have realized overall performance improvement. She suggests that this is primarily because companies choose too many performance measurement indices or continue to rely on historical financial data. Other factors affecting the success of performance measurement systems, such as the BSC, include organizational culture and management styles (Bititci, et al., 2004).

Organizational Culture

Background. As many as 164 definitions of organizational culture have been proposed in the literature (Detert, Schroeder, and Mauriel, 2000), but Schein's definition (1990) is frequently quoted:

(a) A pattern of basic assumptions, (b) invented, discovered, or developed by a given group, (c) as it learns to cope with its problems of external adaptation and internal integration, (d) that has worked well enough to be considered valid and, therefore (e) is to be taught to new members as the (f) correct way to perceive, think, and feel in relation to those problems.

The study of organizational culture as a concept is fairly recent. Most of the literature points to the late 1970s and the work of Pettigrew as the origin of such research (Detert, et al., 2000).

In the early 1980s, the popular business press began to reflect an awareness that something out there, beyond a set of behaviors, would, if repeated, would lead to business success. Ouchi's (1981) Theory Z addressed the issue comparing Japanese companies to American companies. A company's culture reflects its values, according to Ouchi. He asserted that culture and not technology was the primary difference between Japanese and American companies.

Peters and Waterman's In Search of Excellence, published in 1982, accelerated research in the area of organizational culture, perhaps because it linked an organization's performance with its culture (Lewis, 1998). While praised by business practitioners, the research presented was criticized by academic scholars as little more than anecdotal evidence (Janz, 1987), lacking sufficient rigor to be generalizable. Tom Peters (2001) ultimately confessed that much of the supporting data had been fabricated, but contended that the conclusions were correct.

Denison (1984) was one of the first to propose measuring corporate culture based on survey data. Up to that point, most of the research used qualitative, longitudinal, ethnographic studies (Cooke and Rousseau, 1988). These methodologies required a considerable investment in time, and generalizability could not be verified statistically. According to Denison, survey research allowed the same methodology to be applied to a large number of organizations in the identical manner. This facilitates generalization, but, on the downside, could lead to false conclusions. Since the acceptance of survey research as a viable methodology by the academic community, a robust stream of research has ensued.

Much of the empirical research in the area has addressed how to measure culture (Marcoulides and Heck, 1993), what culture types are most effective (Bhaskaran and Sukumaran, 2007; Cameron and Quinn, 1999; Denison, 1997; Denison and Mishra, 1995; Kotter and Heskett, 1992; Mavondo and Farrell, 2003), and how to change organizational culture to more effective types (Cooke and Rousseau, 1988; Korte and Chermack, 2007; Rashid, Sambasivan, and Rahman, 2004; Schwartz and Davis, 1981).

Denison's (1997) culture and effectiveness model is most relevant to this survey. The model is based on four hypotheses related to the dimensions or traits of organizational culture, which Denison synthesizes into a framework. The first hypothesis, involvement, suggests that when members are encouraged to participate, a sense of ownership and responsibility develops, leading to commitment to the organization. Consistency, the second hypothesis, posits that when the organization's culture, comprised of shared beliefs, values, and symbols, becomes internalized, consensus and coordination are more effectively achieved. The third hypothesis, adaptability is based on the need for the organization to recognize changes in the external and internal environment and then make the appropriate responses to accommodate those changes. Finally, the mission hypothesis states that in the presence of a clearly communicated, broadly shared mission, the organization finds purpose and meaning as well as direction. These, in turn, help to define the appropriate course of action for the organization and its members. According to Denison's (1997) hypotheses, all of the cultural traits are positively related to effectiveness.

As noted, Denison (1997) integrates these hypotheses into a framework comparing two continuums: one contrasting change and flexibility with stability and direction on one axis and the other contrasting external orientation with internal integration. Denison has since developed an organizational culture survey instrument (OCSI) to measure the four culture traits within an organization.

Each trait is further broken down into three indices as shown in Figure 1 (Fey and Denison, 2003).

Since the original publication of this research, Denison and his associates have collected over 35,000 individual survey responses from over 160 organizations. The results of this research continue to support his hypotheses.

Linking the Balance Scorecard and Organizational Culture

Background. A considerable body of literature links performance management systems to organizational culture. This is especially true for the Balanced Scorecard. Further, the body of literature regarding the relationship of organizational culture to the BSC is growing as the BSC matures.

Rigby and Bilodeau (2007) acknowledge that corporate culture directly affects the success of management tools used to aide companies in process improvement and decision making. Kaplan and Norton (2004) report that companies that successfully implemented the BSC had a culture in which "people were deeply aware of and internalized the mission, vision, and core values needed to execute the company's strategy." Research by Bititci, et al. (2004, 2006) and Assiri and Eid (2006) support the direct relationship of organizational culture to successful implementation of the BSC.

Methodology

Introduction. Based on the literature just presented, it is apparent that the BSC has become a widely-used management tool. Kaplan and Norton (2001) list some 37 examples of anecdotal evidence to support the idea that the BSC can be useful in communicating corporate strategy throughout the organization and facilitating the implementation of that strategy. Empirical evidence further supports the position. However, there is evidence that many, if not most, BSC implementation projects are not successful.

The literature further points to organizational culture as being a key mediating factor in BSC effectiveness as measured by performance improvement (Kaplan and Norton, 2004; Rigby and Bilodeau, 2007). Behaviors alone cannot account for BSC success or failure. If merely measuring performance resulted in performance improvement, would not all companies be successful?

The literature suggests that the BSC leads to performance improvement in the presence of the appropriate organizational culture (Assiri and Eid, 2006; Bititci, et al., 2004). In BSC terminology, organizational learning and growth leads to internal process improvement, customer satisfaction, and, ultimately, performance improvement. This is illustrated in Figure 2.

[FIGURE 2 OMITTED]

Accordingly, the research question that guided this study is: What is the relationship, if any, between organizational culture and BSC effectiveness?

Population. For the purpose of this study, the target population was county and municipal government organizations. In particular, this investigation studied county and municipal government employees working in departments in one of the 10 most populated counties in the U.S. that have implemented a BSC. This was a field type study.

This population was chosen for two primary reasons. First, the county government has a well publicized, ongoing BSC program. The program is broken down by departments, with over 60 different departments and agencies at different stages of implementation. The organization has about 30,000 employees. Second, while new research is being performed in the public arena, this area still has not been studied regarding the subject at hand.

Sample. Respondents were administrative, professional, supervisory, and management personnel in the various departments of the county government under study. The list of e-mail addresses for the 1,815 staff members with access to the county's BSC administration software was provided by the county and used for the study.

The staff members were notified via an internal e-mail from the county representative that the study was taking place and requesting their participation. Notice of the survey was then distributed via e-mail to the participants. Participants were asked to respond via an online form hosted by Zoomerang.com. A second e-mail was sent by the county representative one week later, followed by a reminder from Zoomerang.com. A final Zoomerang.com reminder was sent one week after that, with the survey closed out the following week.

Dependent variable. The dependent variable in this study was BSC effectiveness, which was measured by self-assessment. It is appropriate to use such a measure for this variable since it has been found that subjective measures of performance correlate with objective measures (Fey and Denison, 2003; Lopez, Peon, and Ordas, 2004).

Independent variable. Organizational culture as measured by the Denison and Neale (2000) organizational culture survey instrument (OCSI) was the independent variable for this study. The OCSI breaks down organizational culture into four traits, as noted in Figure 1: involvement, consistency, adaptability and mission. This permits further analysis of the relationship of each of the four traits to BSC effectiveness.

Survey instrument. The survey instrument was a 70-question, online form developed for this study. It used a 5 point Likert scale. Questions 1-8 collected demographic data; questions 9 and 10 measured BSC effectiveness based on a self-assessment; and questions 11-70 measured organizational culture vis-a-vis the Denison and Neale (2000) OCSI.

Hypotheses. Based on the research question previously stated, the hypotheses tested in this study are as follows:

H11: There is a positive relationship between organizational culture and BSC effectiveness.

H12: BSC effectiveness is positively related to involvement.

H13: BSC effectiveness is positively related to consistency.

H14: BSC effectiveness is positively related to adaptability.

H15: BSC effectiveness is positively related to mission.

Data analysis and strategy. The primary data analysis techniques employed by this study were descriptive statistics, analysis of variance (ANOVA), and correlation analysis. Descriptive statistics were used to analyze demographic information collected and to gauge the consistency of the self-assessment and culture measures within the departments. These statistics include means and standard deviation. It was not possible to test the sample data with population data since such population demographic data was not made available by the organization. However, a comparison of the distribution of responses by department utilizing a Kruskal-Wallis analysis of variance test of the population and sample was performed.

Normality was tested using Kolmogorov-Smirnov (K-S) single sample tests and Shapiro-Wilk (S-W) tests of normality. Cronbach's Alpha coefficients were computed for all of the scale data and compared with those reported by Denison, et al. (2007) to test the reliability of the data. Factor analysis utilizing data reduction techniques including both Varimax and Oblique rotations were used to verify that the data supported the relationships proposed by the Denison culture and effectiveness model. Finally, the data was subjected to a one-way analysis of variance test to determine if there were significant relationships between the demographics and the survey responses.

The five hypotheses were tested using Pearson's correlation to evaluate the relationships between the effectiveness measures and the various cultural trait scores. The hypotheses were tested at an [alpha] level of .05.

These data analysis techniques are consistent with other studies regarding culture and performance, in particular Ewell (2004).

Results

Of the original 1,815 invitations to participate, 46 were undeliverable, leaving 1,769 valid invitations. A total of 537 surveys were completed for a response rate of 30.4%. Based on prior research, the response rate of 30.45% for this survey was excellent (Porter and Whitcomb, 2003; Deutskens, de Ruyter, Wetzels, and Oosterveld, 2004). In the end, 150 responses were eliminated due to missing data, conflicts between the self-assessment questions, or minimum responses per department requirements. This resulted in a final sample of 387 responses from 33 departments, for a usable response rate of 21.9%--still within the acceptable ranges.

Comparison with population. Comparable demographic information for the population was not made available by the organization. However, a Kruskal-Wallis analysis of variance test of the population and sample, mentioned previously, concluded that the sample was representative of the population.

Data transformations. The responses to questions 11-70 were averaged to produce the respective indexes. The traits were developed averaging the corresponding indexes. Finally, the overall score was calculated based on an average of the traits. The data were further summarized by department.

Questions 25, 34, 39, 44, 49, 53, 60, and 68 are negative questions. For study purposes, the scores must be reversed (Denison, et al., 2007). Accordingly, for those questions all responses of 1 were re-coded to 5, responses of 2 were recoded to 4, responses of 4 were re-coded to 2, and responses of 5 were re-coded to 1.

Normality. Kolmogorov-Smirnov (K-S) single sample tests and Shapiro-Wilk (S-W) tests of normality were conducted on the responses to questions 9 and 11-70, as well as the data developed for the indexes, traits, and overall scores. These tests were conducted on the individual responses as well as the by-department, aggregate scores.

In general, the ungrouped data was not normally distributed. When grouped by department, however, the data was found to be normally distributed, except for the data for questions 12 and 50. Question 12 produced conflicting results, with the S-W not supporting normality. Both tests suggest rejecting normality for the question 50 data.

Only the responses for question 9 and the calculated data for the traits and overall measurements were used for this study. Additionally, the data were analyzed by department. Therefore, the data used to test the hypotheses of this study were considered normally distributed.

Reliability. Cronbach's alpha coefficients were computed for all of the scale data. This was compared with the findings reported by Denison, et al. (2007). The coefficients for this study ranged from .665 to .940, compared with the Denison, et al. (2007) range of .70-.92. Nunnally (1978) suggests that alpha coefficients of .7 or higher are acceptable for research purposes. However, alphas below .70 can be found in the literature (Harber, Ashkanasy, and Callan, 1997; Mallak, Lyth, Olson, Ulshafer, and Sardone, 2003). Based on the literature, the alpha coefficients from this study are acceptable.

Hypothesis testing. Five hypotheses were presented regarding the relationship between organizational culture and BSC effectiveness. The data were first subjected to ANOVA testing to identify any significant relationships between the demographic data and the survey responses. It was determined that such relationships existed based on department, job title, and years in the department. Accordingly, the five hypotheses were tested based on composite department scores, utilizing the Pearson correlation method with an [alpha] level of .05.

As previously noted, department average responses to question 9, the self-assessment of BSC effectiveness, were used as the dependent variable in all tests, and the appropriate index or trait factors were used as the independent variables. The complete correlation matrix follows.

Accordingly, the following describes the results of those tests:

Regarding Hypothesis HI, Table 1 indicates a correlation of .657 with [+ or -] < .01. Given that the sig. (.000) is less than the alpha (.05), there is support for the hypothesis that a relationship exists between organizational culture and BSC effectiveness.

Regarding Hypothesis H2, the test results produced a correlation coefficient of .602 with [+ or -] < .01. Given that the sig. (.000) is less than the alpha (.05), there is support for the hypothesis that BSC effectiveness is positively related to involvement.

Regarding Hypothesis H3, there was a correlation coefficient of .561 and, again, [+ or -] < .01. Given that the sig. (.000) is less than the alpha (.05), there is support for H3 that BSC effectiveness is positively related to consistency.

Regarding Hypothesis H4, the analysis produced a correlation coefficient of .615 with [+ or -] < .01. Given that the sig. (.000) is less than the alpha (.05), there is support for H4 that BSC effectiveness is positively related to adaptability.

Finally, Hypothesis H5 suggests that BSC effectiveness is positively related to the mission trait. This is based on a correlation coefficient of .648 with [+ or -] < .01. Given that the sig. (.000) is less than the alpha (.05), there is support for H5.

Discussion

Based on the results of this study, a positive relationship exists between the effectiveness of BSC projects and organizational culture. Additionally, the study results support the hypotheses regarding the positive relationship between the four dimensions of organizational culture as posited by Denison (1997), and BSC effectiveness.

Implications for management. This study has advanced the literature by identifying the link between organizational culture and BSC effectiveness. These findings provide valuable information to managers regarding the potential for successful implementation of the BSC in their organizations. The authors have posed the question: If merely measuring performance resulted in performance improvement, would not all companies be successful? Indeed, there has to be more to it. This study suggests that organizational culture is a key mediator in the process and further supports the position that organizational culture plays a significant role in determining the success or failure of BSC implementations.

It follows, then, that organizations fostering involvement, consistency, adaptability, and mission, as measured by the OCSI, will be more likely to achieve measurable results vis-a-vis BSC implementation. Organizations with less than favorable scores may choose to affect organizational change prior to the BSC implementation. At the very least, the organization must adjust its expectations regarding the results to be attained and the speed at which they are realized. In the end, the organization may decide to forgo BSC implementation all together. In so doing, valuable resources may be redirected at efforts that produce greater benefit to the organization.

Limitations and Recommendations for Future Research

Several limiting factors in this study might be mitigated in future studies, thereby increasing the generalizability of the findings.

First, the study was conducted in a single, municipal county government organization. The study methodology should be extended to different organizations, in both public and private sectors, to evaluate if there is a significant difference in the results.

A self-assessment for BSC effectiveness was used as the dependent variable in the study. Future research should include objective measures based on BSC results as the basis for establishing BSC effectiveness. This is complicated by the paucity of literature addressing the issue of what constitutes a successful BSC implementation. Indexes could be developed based on the percentage of objectives achieved as well as the degree to which they were achieved (that is, met the objective, slightly surpassed the objective, or greatly surpassed the objective). By developing such indexes and constructing objective measures, concerns for unbiased assessment on the part of survey respondents would be eliminated.

As a final thought, it may be possible that an organization's culture can change as a direct result of the BSC process, without any specific intervention aimed at such changes. Future research should include longitudinal studies to track organizational culture and BSC effectiveness over the life of the BSC project to assess if such changes occur.

Summary

This paper presented conclusions derived from an empirical study to the effect that a relationship exists between organizational culture and BSC effectiveness. Each of the four organizational traits--involvement, consistency, adaptability, and mission--as measured by the Denison and Neale (2000) OCSI are significantly related to BSC effectiveness. Accordingly, the study affirms a relationship between organizational culture and BSC effectiveness.

It is hoped that the recommendations regarding future research into this subject will lead to further investigations. Such investigations should further elucidate the relationship between organizational culture and BSC effectiveness as well as the interrelationship among organizational culture and BSC effectiveness.

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Jackie W. Deem, Kaplan University

Barry Barnes, H. Wayne Huizenga SBE

Sabrina Segal, H. Wayne Huizenga SBE

Robert Preziosi, H. Wayne Huizenga SBE

Dr. Deem has over 30 years of management experience with companies including Eastern Air Lines and General Motors in North America, Europe, and Australia. He chairs the Marketing Department in Kaplan's School of Business. Dr. Barnes teaches graduate courses in leadership, strategic decision-making, and organizational behavior. The recipient of teaching and research awards, his articles on the relationship between leadership, organizational change, and strategy have appeared in a number of journals. Dr. Segal, professor of marketing and statistics, has traveled widely--teaching business in Brazil and training managers in Shanghai. She has published articles on the business scene in Russia and other topics, is editor of Marketing Scene, and describes herself as "an entrepreneur at heart." Dr. Preziosi, chair of the Management Department at Nova Southeastern's Huizenga School, has designed the curriculum for graduate degrees in human resources management and leadership. A former corporate vice president, he now serves on the editorial boards of four journals and as management editor of the Journal of Applied Research. His research interests and publications focus on practical areas of leadership and adult learning.
Table 1. Correlation Matrix

               Correlations

                                         Q9     Involvement

Q9             Pearson Correlation      1.000       .602 **
               Sig. (2-tailed)                        0.000
               N                           33            33
Involvement    Pearson Correlation    .602 **         1.000
               Sig. (2-tailed)          0.000
               N                           33            33
Consistency    Pearson Correlation    .561 **         0.837
               Sig. (2-tailed)          0.001         0.000
               N                           33            33
Adaptability   Pearson Correlation    .615 **       .849 **
               Sig. (2-tailed)          0.000         0.000
               N                           33            33
Mission        Pearson Correlation      0.648       .809 **
               Sig. (2-tailed)          0.000         0.000
               N                           33            33
Overall        Pearson Correlation    .657 **       .941 **
               Sig. (2-tailed)          0.000         0.000
               N                           33            33

                                      Consistency   Adaptability

Q9             Pearson Correlation        .561 **        .615 **
               Sig. (2-tailed)              0.001          0.000
               N                               33             33
Involvement    Pearson Correlation        .837 **        .849 **
               Sig. (2-tailed)              0.000          0.000
               N                               33             33
Consistency    Pearson Correlation          1.000        .774 **
               Sig. (2-tailed)                             0.000
               N                               33             33
Adaptability   Pearson Correlation        .774 **          1.000
               Sig. (2-tailed)              0.000
               N                               33             33
Mission        Pearson Correlation        .837 **        .787 **
               Sig. (2-tailed)              0.000          0.000
               N                               33             33
Overall        Pearson Correlation        .918 **          0.924
               Sig. (2-tailed)              0.000          0.000
               N                               33             33

                                      Mission   Overall

Q9             Pearson Correlation      0.648     0.657
               Sig. (2-tailed)          0.000     0.000
               N                           33        33
Involvement    Pearson Correlation    .809 **     0.941
               Sig. (2-tailed)          0.000     0.000
               N                           33        33
Consistency    Pearson Correlation    .837 **     0.918
               Sig. (2-tailed)          0.000     0.000
               N                           33        33
Adaptability   Pearson Correlation    .787 **     0.924
               Sig. (2-tailed)          0.000     0.000
               N                           33        33
Mission        Pearson Correlation      1.000     0.929
               Sig. (2-tailed)                    0.000
               N                           33        33
Overall        Pearson Correlation    .929 **     1.000
               Sig. (2-tailed)          0.000
               N                           33        33

**. Correlation is significant at the 0.01 level (2-tailed).

Figure 1. OCSI Traits and Indices

  Involvement       Consistency      Adaptability      Mission

  Empowerment      Coordination &   Organizational    Strategic
                    Integration        Learning       Direction
                                                      and Intent

Team Orientation     Agreement      Customer Focus     Goals &
                                                      Objectives

   Capability       Core Values     Creating Change     Vision
  Development
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