Knowledge is seen as a precious and efficient source for organizations and individuals. Besides, it is seen as a tool of survival in dynamic and competitive environments increasingly. This situation shows the necessity of gaining and using knowledge for organizational activities. (Shalikar et al., 2011; Sharifirad, 2010).

Knowledge management and organizational learning are definitely not seen as new subjects; their original concepts root back to twenty years ago. Since the 1990s, the concern for researching knowledge management has gradually increased and theories were developed about knowledge management. Organizational learning applications are even older than this date (Liao et al., 2008; Senge, 1990; Wiig, 1994).  

Knowledge management and organizational learning applications show organizational performance improve-ment level (Caveleri et al., 2005; Davenport and Prusak, 1998).

However, there are a lot of obstacles for efficient and fruitful knowledge management and organizational learning. Liao (2002) states that knowledge management may inhibit an organization’s skills for learning and problem solving. Generally routine problem solving applications are accepted as time and endeavor saving, even as omitting risks (Liao et al., 2008). Static knowledge sources and old previous experiences cause stereotyped ways and approaches in dealing with problems to the root. From the aspect of behavior management, such foresights can cause the organization to take higher risks in a highly risky competition environment. Knowledge inertia does not only have a negative impact in achieving a knowledge, but also can reveal the secret knowledge of the organization (Liao, 2002). 

Knowledge inertia theory was suggested first by Liao in 2002 but was not tested experimentally. However, it is seen that knowledge inertia was tested in the studies of Liao et al. in 2008. From these studies, relation between knowledge inertia, organizational learning and organizational performance is studied by means of structural equation model approach.

Knowledge inertia

Physics explains principles of inertia as the fact that stable or monotonic action of an object continues, unless it is moved clearly by a force. In the event of encountering any obstacles, there are physical restraints in the movement of the objects and they will move in the expected orbits (Liao et al., 2008).  People can follow the moving objects and reach them by estimating the direction they are going. This fact shows that there is static mode in human mind and perception that is called laziness or knowledge inertia (Shalikar and Nikou, 2011; Sharifirad, 2010). As we consider the fact that human life is mostly spent in organizations, it is inevitable that a life with inertia will affect the performance of organizations negatively and cause conflicts between individual and organization (Schein, 1990).

Inertia is related to problems that are experienced in knowledge and skill transfers and communication. If habits can be changed and skills transferred, then organizations can improve and learn (Collinson and Wilson, 2006). On the other hand, individuals and organizations can solve high level problems with their previous knowledge and experience and can generalize them into new conditions. However, utilizing previous experiences for solving  new  problems  reveals  the  fact  that  similar phenomena leave these static positions  until a new force changes them. Because inertia in knowledge is rooted from using routine or casual methods in solving problems, following old knowledge and experiences may strengthen or weaken the problem solving skills of the organization (Shalikar et al., 2011).

When the term inertia is used for human behaviors, individuals use their knowledge and experience from the past. This is called knowledge inertia (Liao et al., 2008). Everything is caused by non-revised and non-updated previous experiences and knowledge. This situation is referred to predictable behavior and problem solving strategy of an organization. Knowledge inertia is caused by lack of innovative thinking and behavior; it affects fruitful learning and knowledge achievement negatively (Fang et al., 2010).  According to Liao et al. (2008), knowledge inertia provides the empirical evidence to support, that is it comprises two dimensions: experience and learning inertia. Experience inertia is defined as individuals solving problems with previous experience and knowledge. Learning inertia is when individuals learn knowledge from the same source.

Organizational learning

In the course of knowledge society, importance of learning has been newly understood. In our day, knowledge does not bear a meaning by itself. What is important is learning. Because knowledge emerges as a result of learning and only by means of learning can the knowledge be achieved and become useable, in that case, learning can be described as progress of achieving knowledge (Lingam and Lingam, 2013; Marquardt, 1996). In this progress both individuals and organizations strive to achieve the required knowledge. As the world changes quickly, level of uncertainty will increase evenly. Thus, previous experiences may not be sufficiently reliable most of the time. Predicting changes, reacting to them and achieving performance constantly require learning (Davenport and Prusak, 2001).

Being an important element of organizational change capacity, the knowledge that is achieved as a result of learning (Getha-Taylor, 2008) is highly important and valuable source in terms of adaptation of organizations to the changes in environmental factors (Dodgson, 1993). In this context, organizational learning has an essential value for continuing organizational existence and achieving sustainable competition supremacy by dealing with changes (Klimecki and Lassleben, 1999).

The term organizational learning has become the focus of interest of the scientists, organizations, public institutes that work on the field of management and organizations. Thus, many studies have been made over organizational learning and every scientist has described organizational learning from different points of view. According to some of these descriptions, organizational learning is “the progress where the organizations achieve timely and accurate knowledge and think better and thus, organizational behaviors change or existing behaviors improve (Garvin, 1993)”. “It is a progress of improving organizational performance and adopting this improvement, where organizations build, complete and organize knowledge and routines (Dodgson, 1993)”. “It represents a progress that starts at individual level and reaches team/group learning and from there to organizational learning as a whole (Probst and Büchel, 1997).

Organizations learn through learning individuals. Individuals are representatives of organization activities, thus, they are also representatives of organizational learning (Argyris, 1990; Shrivastava, 1983). Organizational learning happens through them (Crossan et al., 1999). However, the sum of learning of all individuals in an organization does not provide organizational learning or organizational knowledge (Cohen and Levinthal, 1990). In addition, organizational learning cannot happen without individual learning. From this point of view it can be said that organizational learning happens in three possibilities. In the first possibility, the individuals learn; in second possibility, individuals learn while the organization learns; in last possibility, a collective learning happens (Örtenblad, 2001).

However Adams et al. (1998) describe inertia as an element that prevents organization’s learning capacity towards achieving a new product. Besides, knowledge inertia may prevent individuals’ learning skills, and in return, this can affect organizational learning (cit. Liao et al., 2008).

Organizational performance

The term performance that takes place in the center of organizational and individual learning theory is the skill of achieving purposes by utilizing organization sources efficiently and productively (Boyne, 2003; Rainey, 1997). On the other hand, organizational performance is a quantitative and qualitative expression of “where has the organization reached or what has it achieved on the way to its purpose” (?im?ek and Nursoy, 2002).

Performance can be evaluated in individual or organizational basis and the main element building this term is measurement. Determining and measuring the criteria that are impressive in delivering a performance provides revealing individual and organizational performance (Turunç and Akkoç, 2014). However, measuring organizational performance is difficult since it has a complex and multidimensional structure and forming a systematic structure for every situation has not been possible so far (Dess and Robinson, 1984; Ford and Schellenberg, 1982). Thus, either objective scales obtained from organizational records or subjective scales obtained from members or shareholders of the organization based on perception have been used in organization level performance researches (Seashore and Yuchtman, 1967; Campbell, 1977).

In addition, determining performance is possible by measuring and evaluating the relation between organization input and output. Organizations also evaluate their outputs or results in accordance with performance different dimensions (Benligiray, 1999). In education system, the first thing that comes to mind in terms of performance evaluation or measurement is evaluation and measurement of students and managers. However, except these, measuring physical and technical equip-ment and families’ performance holds an important place in the system. Developing a performance management system except these is quite difficult since this relies on school’s strategic and work plan (Ensari, 2005).

The core of any evaluation process is to identify, correct and improve weak and strong side of teaching activities and to lead improving organizational performance. Sufficient, accurate and acceptable measurement instruments must be developed to measure teaching performance. Measurement of efficiency can be performed by school principals. In addition, students’ success grades, colleague reviews, self-review of the teacher and systematic observations can be considered. Developing new strategies and purposes of lessons, utilizing new teaching methods require identifying basic values of the evaluation. An evaluation cannot be performed based only on one situation. An evaluation must be performed multidimensionally by considering a combination of various evaluation strategies (Nwagwu, 1998).

One of the most important factors that can impact these endeavors towards increasing or improving organizational performance is organization’s organizational strife in learning progress. Organizations that have adopted learning organization approach constantly try to perform improving and innovative approaches. Schools as learning organization can apply a new educational technology or teaching method. Schools performing organizational develop general strategies that contain new learning subjects and that are related to ways of teaching these subjects in their daylong applications (Çelik, 1997). Learning progress in fact starts with feedbacks or responses from organization employees and causes the organization and organizational performance to improve (Mausolff, 2004; Deng and Tsacle, 2006). As agenerally accepted opinion in organizational literature, final output of the organizational learning must be improved in organizational performance (Holton and Kaiser, 2000).

According to Buckler (1998), who tried to explain the relation between organizational learning and performance within a frame of simple model, organizational learning will bring behavioral change in conjunction with achievement of new knowledge, approach and skills and this can end in improvement in product and services and progresses. Final outcome of all these progresses is a step by step improvement in performance; which means a constant improvement where the assessments are done better in time or coming to a position where one can do better jobs. On the contrary, when the fact that an important part of human life is spent in organizations is considered, it is inevitable that a life with inertia may affect performance, learning level and productivity of individuals and organizations negatively and cause conflicts between individual and organization. Hannan and Freeman (1984) stated that inertia is common in organizations where teamwork is insufficient and a resistance against constant learning is dominant.

In line with literature, the following hypotheses have been developed related to knowledge inertia, organizational learning and organizational performance and the relation between these three parameter which are described above.

Hypotheses

H1. Knowledge inertia affects learning negatively and significantly.

H2. Knowledge inertia explains organizational learning significantly.

H3. Knowledge inertia affects organizational performance negatively and significantly.

H4. Organizational learning affects organizational performance positively and significantly.

H5. Knowledge inertia and organizational learning explains organizational performance in a high grade and significantly.

H6. Organizational learning has a partial mediator impact between knowledge inertia and organizational performance.

Research model

This research was performed by means of relational screening model. This is a model that aims to determine the existence and grade between two or between more than two variables (Karasar, 2012). In terms of this, the study focuses on the interaction between teachers’ knowledge inertia, organizational learning and organi-zational performance levels and their level of explanation of each other.

Sample

Sample of the research consists of 405 teachers who work in randomly selected primary schools in Diyarbakir city’s central districts: Baglar, Kayapinar, Sur and Yenisehir. For structural equality model, data must meet the multiple normality assumption.

In order to meet this assumption, minimum sample size must be between 100 and 150 (Hair et al., 1998).  Since contributor number of the research is 405, this number is suitable for the purpose and statistical analysis of the research. Demographical features of the attendees are as follows: 61.7% of the attendees are (f=250) “females”; 28.3%, (f=155) “males”. 28,4% of the attendees (f=115) are in “30 and younger” age groups, 45.9% (f=186), “31-40” age groups and 25.7% (f=104), “41 and older” age groups.  In terms of work duration, 45.7% (f=185) has “10 or less years”; 35.3%  (f=143), “11-20 years”; 13.3% (f=54), “21-30 years and 5.7% (f=23), “31 or more years”.

Analyzing of Data

Data obtained from research were first entered into SPSS (Statistical Package for the Social Sciences) package software and demographical features of sample group were analyzed by means of this software. For confirmatory factor analysis and designed model AMOS (Analysis of Moment Structures) was utilized. In estimating model parameters in confirmatory factor analysis RMSEA (The Root Mean Square Error of Approximation); SRMR (Standardized Root Mean Square), GFI(Goodness of Fit Index), CFI (Comparative Fit Index), AGFI (Adjusted Goodness of Fit Index), NFI (Normed Fit Index), X2/sd = CMIN/DF (chi square/degree of freedom), and significance level (p) fit indexes were considered. RMSEA value was  0-0,08; SRMR value was 0-0.10; GFI value was .90-1.00; CFI value was .90-1.00; AGFI value was .85-1.00; NFI value was .90-1.00; X2/sd (CMIN/DF) value was  0-3; p value was  0.01-0.05. These show good fit indexes (Bayram, 2010; Byrne, 2001; Joreskog and Sorbom, 1993; Kline, 2005; Schermelleh-Engel and Moosbrugger, 2003; Reisinger and Mavondo, 2006; ?im?ek, 2007). In this research, lower limit for factor load of items in confirmative factor analysis is taken as .30. If there are less items in a scale that is prepared in social sciences field, factor load value lower limit can be decreased to .30 (Büyüköztürk, 2012). Additionally in assessment of normality for confirmative factor analysis and structural equality model, critical ration was grounded on fewer than 10. According to Kline (2005) critical ratio is in some sort the normalized estimation of multivariable kurtosis i.e. “z” value. Critical ratio being higher than 10 shows that there is a problem in kurtosis value of the distribution.

Data Collection tools and confirmatory factor analysis

Knowledge inertia scale

It was developed by Liao et al. (2008). The scale that was adapted by the researcher to Turkish language consists of 14 items which has the features of assessment of Learning Inertia (7 items) and Experience Inertia (7 items). Scale’s Cronbach Alpha coefficient whose validity and reliability studies were performed was .755 in terms of Learning Inertia and .602 in terms of Experience Inertia. Knowledge Inertia Scale is a Likert type scale graded from 1 to 5; accordingly, I strongly disagree: 1 point; I disagree: 2 points; I am neutral: 3 points; I agree: 4 points; I strongly agree: 5 points.

As a result of the analysis performed on data obtained from this study, Cronbach Alpha coefficient in terms of learning inertia was found to be .82, while it was .73 in terms of experience inertia (Table 1). Additionally confirmative factor analysis diagram of the scale is shown in Figure 1.

As a result of confirmative factor analysis, as the assessment of the normality is considered, critical rate from the aspect of multivariate (Mardia) values was 24.659.  Since the scale’s critical rate in terms of experience inertia  was  1  item bigger than 10, this was not included to the analysis in the next step. In this case, as a result of the analysis that was performed by considering MI (Modification Indices) in confirmative factor analysis of “Knowledge Inertia Scale” that consists of 13 items, the fit values were found to be RMSEA=.052; SRMR=.053; X2/sd (CMIN/DF)=2.09; GFI=.955; CFI=.961; AGFI=.932 and NFI=.928. This result shows that fit values of the model are acceptable and at desired level.

Organizational learning scale

For measuring the level of organizational learning, a scale developed by Calantone et al. (2002) was used. The scale that was adapted by the researcher to Turkish language consists of 17 items which has total 4 dimensions called commitment to learning (4 items), shared vision (4 items), open mindedness (4 items) and intra-organizational knowledge sharing (5 items). Contributors expressed their level of acceptance with ad Likert type scale graded from 1 to 5:  I strongly disagree: 1 point; I disagree: 2 points; I am neutral: 3 points; I agree: 4 points; I strongly agree: 5 points.

As a result of the analysis performed on data obtained from this study, Cronbach Alpha coefficient in terms of commitment to learning was found to be .78, while it was .84 in terms of shared vision, 78 in terms of open mindedness and .79 in intra-organizational knowledge sharing (Table 1). Additionally confirmative factor analysis diagram of the scale is shown in Figure 2.

As a result of confirmative factor analysis, as the assessment of the normality is considered, critical rate (c.r.) from the aspect of multivariate (Mardia) values was 44.451.  Since there was no items whose critical rate is bigger than 10, all the items were included for the next step. In this case, as a result of the analysis that was performed by considering MI (Modification Indices) in confirmative factor analysis of “Organizational Learning Scale” that consists of 17 items, the fit values were found to be RMSEA=.073; SRMR=.051; X2/sd (CMIN/DF)=3.14; GFI=.914; CFI=.918; AGFI=.917 and NFI=.928 This result shows that fit values of the model are acceptable and at desired level.

Organizational Performance Scale

For measuring the level of organizational performance, a scale developed by Bayraktaro?lu and Y?lmaz (2012) was used. The scale that was developed to measure organizational performance of private sector organizations consists of 16 items with 4 dimensions called learning and improvement (4 items), customer (4 items), financial (4 items) and internal processes (4 items). Contributors expressed their level of acceptance with Likert type scale graded from 1 to 5. 

This scale was rearranged in line with the purpose of this study and the literature as total of 16 items consisting of 4 dimensions called learning and improvement (4 items), student (4 items), productivity (4 items) and internal processes (4 items).

As a result of the analysis performed on data obtained from this study, Cronbach Alpha coefficient in terms of learning and improvement was found to be .88, while it was .88 in terms of student, .91 in productivity and .90 in internal processes (Table 1). Additionally confirmative factor analysis diagram of the scale is shown in Figure 3.

As a result of confirmative factor analysis, as the assessment of the normality is considered, critical rate (c.r.) from the aspect of multivariate (Mardia) values was 59.272.  Since there was no items whose critical rate is bigger than 10, all the items were included for the next step. In  this  case,  as  a  result  of  the  analysis  that  was performed by considering MI (Modification Indices) in confirmative factor analysis of “Organizational Performance Scale” that consists of 17 items, the fit values were found to be RMSEA=.078; SRMR=.033; X2/sd (CMIN/DF)=3.46; GFI=.919; CFI=.958; AGFI=.911 and NFI=.943 This result shows that fit values of the model are acceptable and at desired level.

Additionally, for testing the reliability of the scales used in this study, in other words, in order to understand the internal consistency; when  we look at the total reliability coefficients of the scales alongside the reliability coefficients about sub dimensions of each scale given above; as reliability coefficient of Knowledge Inertia was found as Alpha= .77, as reliability coefficient of Organizational Learning Scale was found as Alpha= .88 and as reliability coefficient of Organizational Performance Scale was found as Alpha= .99. Cronbach Alpha reliability coefficient is a scale for internal consistency between test grads of a scale. A value of 0.70 and above is accepted sufficient for test reliability (Büyüköztürk, 2012). Cronbach Alpha coefficients for internal consistency of the scales are calculated in accordance with sub dimensions and the results are given in Table 1.

Correlation analysis

Arithmetic mean and standard deviation values related to dependent and independent variables of this study and correlation coefficients between these variables are given in Table 2.

(3) Relationship between organizational learning and organizational performance: Commitment to learning has a positive relation with organizational performance dimensions such as shared vision, open mindedness and intra-organizational knowledge sharing; learning and improvement, student, productivity and internal pro-cesses. This situation shows that organizational learning at a high level increases organizational performance.

Correlation analysis only reveals the relation level between structures. Structural equality model analyses must be performed in order to reveal the direct and indirect impacts between structures, and even to reveal the mediator variables

Structural equation model

In this part of the study, a model showing the influence rate of knowledge inertia, organizational learning and organizational performance to each other and the explanation rate of each other is used. While this model was developed, testing of the studies hypotheses was considered. Structural equation model that was developed for this purpose can be seen in Figure 4. 

Model’s fit indexes analyzed by considering the MI values (Modification Indices) were found as follows: RMSEA=.060; SRMR=.069; CMIN\DF=2,475; GFI=.922; CFI=.964; AGFI=.911; NFI=.905; Chi squared=2395,329; df=968 and p=.000. This result shows that the fit values of the model are acceptable and at desirable rate (Bayram, 2010; Joreskog and Sorbom, 1993; Kline, 2005; Schermelleh-Engel and Moosbrugger, 2003; ?im?ek, 2007).

All the parameters in estimation results of the model were statistically significant. This means, values belonging to ways that were drawn from knowledge inertia to organizational learning, from knowledge inertia to organizational performance and from organizational learning to organizational performance that existed in the model were statistically significant (Table 3).

Organizational performance scale has four latent variables and 16 observed variables. While learning and improvement latent variable has .84 relation coefficient, student latent variable has .94 coefficient, productivity latent variable has .94 and internal processes latent variable has .90 correlation coefficient. While factor loads of observed variables in learning and improvement latent variable change between .73 and .83, factor loads of observed variables in student latent variable change between .76 and .84, productivity latent variable changes between .77 and .87 and internal processes latent variable changes between .79 and .88.

As the results of the study were evaluated, the following conclusion was reached.

As the standardized regression (Beta) coefficients obtained from the research are reviewed (Figure 4), it is seen that knowledge inertia has a positive impact (β= 0.54; p<0,05) on organizational learning. In line with this result, the hypothesis “Knowledge inertia affects organizational learning negatively and significantly” was partially declined. Even though knowledge inertia has affected the organizational learning positively, this impact seems significant (p<0.05). However when knowledge inertia level of explanation for organizational learning is reviewed, it is seen that knowledge explains the organizational learning in a rate of 29%. In other words, the   change   that   occurs   in   teachers’   organizational learning perception depends on knowledge inertia levels in a rate of 29%. This result confirms the hypothesis “Knowledge inertia explains learning significantly”.

When the standardized regression (Beta) coefficients are reviewed in terms of the hypothesis of the study, it is understood that knowledge inertia has a negative impact on organizational performance (β= -0.29; p<0,05).  This result confirms the hypothesis “Knowledge inertia affects the organizational performance negatively and signifi-cantly”. However as it is seen in the model in Figure 4, the hypothesis with the lowest influence level is H3.  This situation showed that knowledge inertia affects the organizational performance less compared to organiza-tional learning.

As another standardized regression (Beta) coefficient that exists between the results of the study is reviewed, it is seen that organizational learning has a positive affect on organizational performance (β= 0.83; p<0,05). This result confirms the hypothesis “Organizational learning affects organizational performance positively and significantly.

Another finding that comes into prominence in the model suggested above is that fact that the latent variables of knowledge inertia and organizational learning explain the organizational performance significantly in a rate of 51%. This means, that the change that occurs in teachers’ perception for organizational performance depends on their knowledge inertia level and perception of organizational learning in a rate of 51%. This finding shows that knowledge inertia and organizational learning are significant predictors (explanatory) of organizational performance. This result confirms the hypothesis “Knowledge inertia and organizational learning together explain the  organizational performance in a high rate and significantly”.

Other than direct impacts, indirect impacts can also be tested by means of structural equation models that are structured through AMOS software (Arbuckle, 2007). As a review in terms of this is made, predictive power of knowledge inertia and organizational learning that is the mediator variable on organizational performance variable can be seen clearly. Total, direct and indirect impacts between the variables of this study are shown in Table 4.

As the standardized value belonging to the total impacts is reviewed, it is seen that total predictive power of knowledge inertia for organizational learning was 0.54, for organizational performance was 0.16 and total predictive power of organizational learning for organiza-tional performance was 0.83.

As the standardized values belonging to direct impacts are reviewed, direct predictive power of knowledge inertia for organizational learning is found to be 0.54, for organizational performance -.29, direct predictive power of organizational learning for organizational performance is found to be 0.83. As it is seen in the table, the sole difference is the predictive power of knowledge inertia for organizational performance.

As the standardized values belonging to indirect impacts are reviewed, direct predictive power of knowledge inertia for organizational performance is found to be 0.45. This situation shows that knowledge inertia has both direct and indirect impact on organizational learning; in other words, organizational learning has a mediator impact on knowledge inertia’s impact on organizational performance. This result confirms the hypothesis “Organizational learning has a mediator function between knowledge inertia and organizational performance”. 

Within the context of this study, relationship between knowledge inertia, organizational learning and organiza-tional performance and their explanation rate of each other was tested. For reaching this purpose, by examining the literature and in light of theoretical information, six hypotheses were developed. In this part of the study, orders of the hypotheses were considered and the results were compared to other study results and discussed.

Concerning the first hypothesis of the study, it was found that knowledge inertia levels of teachers affect their organizational learning positively and significantly. As it was emphasized in theoretical frame of the study, a life based on knowledge inertia decreases individuals’ and organizations’ performance, learning level and produc-tivity. Hence, the knowledge inertia affects organizational learning positively contrary to the expectation that it affects organizational learning negatively. It was seen that the factor causing this kind of impact is caused by teachers’ perception for experience inertia. Not only it was seen that teachers’ perception for experience inertia was higher than their perception for learning inertia, but also experience inertia has a positive relation with organizational learning, while learning inertia has a negative relation with organizational learning as it was seen in correlation analyses. Hence, it is understood that teachers with high experience inertia see themselves more sufficient in performing organizational learning. On the other hand, concerning the second hypothesis of the study, it was determined that teachers’ knowledge inertia level explains their organizational learning significantly. These results comply with other study results. In their studies, Liao et al. (2008) reached the conclusion that learning inertia affects the organizational learning negatively and not only organization employees’ level of learning inertia decreases the organizations commitment to learning, shared vision and open mindedness at an important rate, but also organization employees’ high experience inertia increases the organization’s performance in subjects of commitment to learning, shared vision and open mindedness. Sharifirad (2010) and Shalikar et al. (2011) found that knowledge inertia has a negative impact on organizational learning; however as the impact learning inertia and experience inertia that are the sub-dimensions of knowledge on organizational learning is reviewed one by one, they determined that experience inertia has a positive impact on organizational learning. Thus, both in this study and other related studies, it is seen that the hypothesis about knowledge inertia’s impact on organizational learning is confirmed.

Concerning the third hypothesis of the study, it was found that teachers’ knowledge inertia level affects their organizational learning negatively and significantly. In other words, highness of knowledge inertia affects organizational performance negatively. In the literature, inertia is seen as a resistance to organizational performance or at least as a resistance against a basic trend/change (Miller, 1993) Besides, Hannan and Freeman (1984) argue that programs with inertia and habitats increase the reliability of an organization, while limiting its performance. As the results of studies performed related to the subject are reviewed, Greve (1998) shows that organizational inertia decreases organizational performance. In another study of Greve (1999) which he performed on a radio station employees in USA showed that organizational inertia and organizational performance have a negative relation. Miller (1993, 1994) showed in his studies that inertia causes undesired results in teacher’s performance of success and this shows parallelism with results of this study.

Concerning the fourth hypothesis of the study, it was found that teachers’ level of organizational learning affects their organizational performance positively and significantly. There is a strong relation between organizational learning and organizational performance. Because, organization’s performance increases in parallel with organization change rate that causes organizational performance to proceed (Dunphy and Griffths, 1998; Robinson et al., 1997; Ho, 2011). In other studies performed on this subject, it was found that organizational learning and organizational performance has a positive and strong relationship or that the organizational learning has positive impact on organizational performance (Kassim and Shoid, 2013, Akhtar et al., 2011, Dimovski, 1994; Simonin, 1997; Lam, 1998; Sloan et al., 2002; Figuieiredo, 2003; Dimovski and Škerlavaj, 2005; Škerlavaj et al., 2007).

Concerning the fifth hypothesis of the study, it was concluded that knowledge inertia and organizational learning together explain organizational performance in a rate of 51%. That means, the change that occurs in teachers’ organizational performances depends on their knowledge inertia and organizational learning grade. This finding shows that knowledge inertia and organizational learning are important predictors of organizational performance. Thus, hypothesis above that aims to impact teachers’ level of knowledge inertia and organizational learning on organizational performance supports this hypothesis.

In the study, a conclusion was reached that alongside the direct impact of teachers’ knowledge inertia levels on their organizational performances, their organizational learning level with an mediator role has an indirect impact on their organizational performances. This means not only the organizational learning has a direct impact on organizational performance, but also knowledge inertia has a partial mediator role in organizational performance. This finding shows similarities with the finding of Jyothibabu et al. (2010) that learning as a team or learning as a group has a mediator role in increasing organizational performance.

In conclusion, it is understood that as teachers’ learning inertia levels have a negative impact on their organizational learning and organizational performance, their experience inertia level has a positive impact. Based on these results, it can be said that teachers tend to increase their organizational learning and organizational performance by utilizing their professional experience. Especially, one of the most basic learning ways is to learn from past experiences. Showing effort to solve some problems by benefiting from professional and life experiences is acceptable to a certain point.  However, it is an important learning obstacle to be mistaken that we learn solely based on experience, because not every experience shows itself in life in a short term. We learn something from our behaviors that we obtained in a short term. However, decisions that yield results in long term and their impact on the system integrity show that learning solely based on experience is insufficient (Senge, 1990).  This is because learning not only covers the process of following environmental changes but also manipulating internal relationships (Schein, 2004). In this context, especially those who work in organizations where learning is in the foreground must be encouraged to learn and improve; and also cultural and structural environments that provide constant learning should be built. Systems that allow the school’s education performance to increase should be developed and improved. Management should provide a good working environment within the system; education quality should be increased by planning and directing organization structure and efficient communication.

The author has not declared any conflict of interests.