Abstract: The aim of this study was to examine the relationships among organizational factors, knowledge management processes and organizational innovation. In addition, the role of knowledge management processes as mediator in the development of organizational innovation also was investigated. In this study, four research questions and 25 hypotheses were examined. The population of this study was heads of supervisory departments of the public banks’ branches in all of the Iran provinces. A questionnaire containing 42 questions with a likert-type scale from 1 (strongly disagree) to 5 (strongly agree) was used as the main instrument in gathering data and a total of 229 respondents were involved in the survey. As an analytical method, Structural Equation Modeling was selected using AMOS 16.0 version. The findings of this study identified the mediating role of knowledge management processes in the relationship between organizational factors and organizational innovation. Results of the Structural Equation Modeling analysis also revealed that “IT support” of organizational factors has the highest contribution toward the prediction of organizational innovation and so, the incentives and leadership of organizational factors were the second and third predictor variables of organizational innovation, respectively. From an academic point of view, the results of this study especially its intermediate linkage helps scholars understand the processes further, which might be helpful in discovering additional mediator at different levels of analysis.
INTRODUCTION
There are some barriers to effective Knowledge Management (KM) in the public sector. The most important of them are structural and cultural barriers. Rigid organizational structure and hierarchy, lack of formal information-sharing mechanism, accountability to higher government organizations, leadership capabilities, resources, reward and recognition and trust and knowledge sharing environment are major factors that inhibit KM in this sector (Chawla and Joshi, 2010; Cong et al., 2007). Meanwhile in Cong and Pandya (2003) point of view, People, KM processes and technology are the three key elements that need to be considered for public sector KM framework. According to Monavvarian and Kasaei (2007), Cong et al. (2007) and Chawla and Joshi (2010), KM in the public sector is a new subject and there is generally, relatively little information on it and even less in developing countries. Wiig (2002) focused on KM in government and explored the important roles that KM could play, especially in the following four major areas:
| • | Improving decision-making in the public sector |
| • | Assisting members of the public to be involved in decision making |
| • | Building a society with intellectual capital capabilities to be competitive |
| • | Developing a KM work force |
Wiig (2002) emphasized the importance of KM within and in support of public administration, arguing that this would enable society to prosper, be more viable as people and organizations learn to work more efficiently. In general, such an approach would result in an improvement in the quality of life for the people.
Since innovation has recently been considered as an important factor for organizations especially banks to maintain their competitive edge and to develop, it is important for organizations to identify the key factors for promoting an organizations’ product or service and process innovation. These factors include the leadership paradigm (Anantatmula, 2008), organizational culture (King, 2008), organizational structure (Rhodes et al., 2008), organizational human resource (Syed-Ikhsan and Rowland, 2004) and information technology (Sher and Lee, 2004). Therefore, organizational factors, KM processes and organizational innovation are selected as the major variables of this research.
In the related to the impact of organizational factors on KM processes, although the literature review indicates that there are various views about the key organizational factors of KM processes; many researchers have focused on five factors (i.e., organizational leadership, culture, structure, human resources and IT) as the most effective factors. Implicitly, based on the findings of scholars and practitioners, collaboration, trust and incentives are the three essential components of organizational culture (DeTienne et al., 2004) , so centralization and formalization are two most studied dimensions of organizational structure (Rapert and Wren, 1998) and the training is an important enabler of organizational human recourse to KM implementation (Wong, 2005). Therefore, the key organizational factors selected for this study, based on the former literature analysis are: Leadership, collaboration, trust, incentives, centralization, formalization, training and IT support.
The main premise assumption of this study is that organizational innovation will be developed under the appropriate organizational factors that are mediated by KM processes. Therefore, major variables include organizational factors, KM processes and organizational innovation. The operational definition of each construct in this study is in Table 1.
There are different findings about the impact of organizational factors on KM processes in various environments (Ngoc, 2005; Rhodes et al., 2008; Syed-Ikhsan and Rowland, 2004). The findings show that there are no same levels of impact of organizational factors on KM processes. On the other hand, several studies have investigated the impact of KM processes on organizational innovation. The results indicate that KM systems have a distinctive contribution to the development of a sustainable competitive advantage through innovation (Du Plessis, 2007) Therefore, they can be measured and examined in an intended environment.
HYPOTHESES AND HYPOTHESIZED (MEDIATION) MODEL
This study attempts to test the relationships among organizational factors, KM processes and organizational innovation.
| Table 1: | Operational definition of each construct in this study |
In addition, in this research about the role KM processes as mediator in the development of organizational innovation are investigated. Consequently, this study tries to answer the following research questions:
| • | (a) Is there a significant relationship between organizational factors and KM processes? |
| • | (b) Is there a significant relationship between organizational factors and organizational innovation? |
| • | (c) Is there a significant relationship between KM processes and organizational innovation? |
| • | (d) Do KM processes mediate the relationship between organizational factors and organizational innovation? |
The hypotheses of this study come from the theoretical statements made in the literature on KM. These hypotheses are presented through the following variables in Table 2.
Based on the supportive evidence from literature and the above-mentioned hypotheses, the conceptual framework of the study is presented in Fig. 1.
METHODOLOGY
Sample and data collection: The population of this study was heads of supervisory departments of the public banks’ branches in all of the Iran provinces. Iran has 31 provinces and 12 public banks and they have approximately 420 supervisory departments. Therefore, the unit of analysis was each head of supervisory departments of the Iranian public banks’ branches. A questionnaire containing 42 questions with a likert-type scale from 1 (strongly disagree) to 5 (strongly agree) was used as the main instrument in gathering data. For the first step, the researchers obtained consents from the top management of the participating banks through the contacts with central organizations. Then, the questionnaires were sent to all of the population members. A total of, 237 (56%) questionnaires were returned and 229 of them were acceptable for analysis.
| Fig. 1: | Conceptual framework of the study based on the research hypotheses |
Measures: A guiding principle in developing the questionnaires is to use measurement scales that have been validated by previous research. Generally speaking, it is better to use variables and measures from previous research when available, rather than developing original ones. Existing variables have already been empirically tested and it is possible to determine their empirical validity and stability of variables in different samples and their effect on the dependent variables, i.e., their relative importance. In order to test the content validity of this instrument, five domain experts were invited to discuss and revised it. In addition, a pilot study was performed to test the research methodology and confirmation of instrument reliability and validity; a reliability analysis was used to explain internal consistency and a Confirmatory Factor Analysis (CFA) was carried out to determine the degree of model fit. In addition, as an analytical method, Structural Equation Modeling (SEM) was selected using Amos 16.0 version.
Testing for mediation: In this study, the mediating role of KM processes (KMP) on the relationship between Organizational Factors (OFs) and organizational innovation (INO) was investigated. According to Hair et al. (2010) a researcher can determine if mediation exists and whether it is full or partial, in several ways. One of the ways is the decision tree adopted from Mathieu and Taylor (2006) that is shown in Fig. 2. Mediation requires significant correlations among all three constructs (e.g., X, M and Y in Fig. 2).
| Fig. 2: | Decision tree for evidence supporting different intervening effects (Adopted from Mathieu and Taylor, 2006) |
| Table 2: | The research hypotheses made in the literature on KM |
A mediating construct facilitates the relationship between the other two constructs involved. If the mediating construct completely explains the relationship between the two original constructs (e.g., X and Y), then this is termed as full mediation. But if it is found that there is still some of the relationship between X and Y that is not explained away by the mediator, then this is denoted as partial mediation.
RESULTS
Confirmatory Factors Analysis (CFA) and Structural model: Confirmatory Factors Analysis (CFA) is used as a statistical method to determine the relationships between the observed variables and the constructs, which were also called latent variables (Byrne, 2010). In this study separate CFA were conducted for all of the latent variables including OFs, KMP and INO. The overall fit of a measurement model is determined by confirmatory factors analysis Ho (Ho, 2006). The measurement model focuses on the linear functions between latent variables and their indicators in the model.
The researcher then examines the relationship between exogenous and endogenous variables by structural modeling (Byrne, 2010). The structural model (Fig. 3) reveals a path analysis process with latent constructs to investigate the mediation, direct and indirect structural relationship between variables. In this study, the structural model assesses the relationship between: Eight predictor variables (Organizational Factors) such as Leadership (LED), Collaboration (COL), Trust (TRU), Incentives (INC), Centralization (CEN), Formalization (FOR), Training (TRA) and IT support (ITS) and KM processes (KMP) as mediator variable and organizational innovation (INO) as dependent variable.
In addition, the model fit of path analysis was evaluated by examining the Root Mean square Residual (RMR), Goodness of Fit Index (GFI), Incremental Fit Index (IFI), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI) and Root Mean Square Error of Approximation (RMSEA) (Byrne, 2010; Hair et al., 2010; Ho, 2006).
The hypothesized research model was tested using Maximum Likelihood (M.L.) estimation. The standard regression weights of the mediation, direct and indirect model are presented in Table 3.
Hypotheses testing: In order to access the research objectives and answer the research questions, this study tests 25 research hypotheses. Each research question was related to one or a set of hypotheses and the researcher has used the structural model (Fig. 3), the Standard Regression Weights in the Models (Table 3) and the regression weights related to mediation model in testing the study’s hypotheses. The research questions with related hypotheses were examined through p-value at levels (<0.1, <0.05 and <0.001).
Research Question (a): Is there a significant relationship between organizational factors and KM processes?
| Fig. 3: | Estimated path coefficients of the hypothesized (Mediation) model |
| Table 3: | Standard regression weights in the models |
| DV: Dependent variable, IV: Independent variable, β: Estimate of standardized regression weight, LED: Leadership, COL: Collaboration, TRU: Trust, INC: Incentives, CEN: Centralization, FOR: Formalization, TRA: Training, ITS: IT support, KMP: KM processes, INO: Organizational innovation, OFs: Organizational factors | |
| Table 4: | The Results of Hypotheses Testing Related to Question (a) |
| β: Estimate of standardized regression weight, C.R.: Critical ratio for regression weight, Sig.: Significant (*at p≤0.10, **at p≤0.05, ***at p≤0.01) | |
The hypotheses related to this question are Ha1, Ha2, Ha3, Ha4, Ha5, Ha5, Ha7 and Ha8.The extracted concepts of hypotheses related to Question (a) are shown in the following (Table 4):
As shown in Table 4, this study identifies the relationship between individual dimensions of organizational factors and KM processes. Specifically, it has been found that variables leadership, collaboration, centralization, training and IT support were significantly positively related to KM processes. So, variables trust, incentives and formalization, however, were not significantly related to KM processes.
Research question (b): Is there a significant relationship between organizational factors and organizational innovation?
| Table 5: | The Results of Hypotheses Testing Related to Question (b) |
| β: Estimate of standardized regression weight, C.R.: Critical ratio for regression weight, Sig.: Significant (*at p≤0.10, **at p≤0.05, ***at p≤0.01) | |
The hypotheses related to this question are Hb1, Hb2, Hb3, Hb4, Hb5, Hb6, Hb7 and Hb8. The extracted concepts of hypotheses related to Question (b) are shown in the following Table 5.
As shown in Table 5, this study identified the relationship between some of the individual dimensions of organizational factors and organizational innovation. Specifically, it has been found that variables leadership, incentives, formalization and IT support are significantly related to organizational innovation and variables collaboration, trust, centralization and training, however, are not significantly related to organizational innovation.
Research question (c): Is there a significant relationship between KM processes and organizational innovation? The hypothesis related to this question is:
| Hc: | There is a significant positive relationship between KM processes and organizational innovation |
KM processes have a positive significant relationship with organizational innovation (β = 0.61, C.R. = 8.37, p-value = 0.00) and so the research hypothesis (Hc) is supported.
Research question (d): Do KM processes mediate the relationship between organizational factors and organizational innovation?
| Table 6: | Summary of the mediation effects of “KMP” on the relationship between “OFs’ factors” and “INO” (Hd1- Hd8) |
| Sig.: Significant (*at p≤0.10, **at p≤0.05, ***at p≤0.01) | |
| Fig. 4: | Mediating effect of KMP on the relationship between LED and INO |
The hypotheses related to this question are Hd1, Hd2, Hd3, Hd4, Hd5, Hd6, Hd7 and Hd8 as in the following:
| Hd1: | KM Processes mediate the relationship between Leadership and organizational innovation |
Based on Standard Regression Weights in the Models (Table 3) and “Decision tree for evidence supporting different intervening effects” (Fig. 2) the mediating effect of “KMP” on the relationship between “LED” and “INO” (Fig. 4) was tested as follows:
| • | (a) In direct model, LED has significant relationship with INO (β = 0.19, C.R. = 2.247, p-value = 0.02) |
| • | (b) In indirect model, LED has significant relationship with KMP (β = 0.14, C.R. = 2.036, p-value = 0.04) and KMP has significant relationship with INO (β = 0.61, C.R. = 8.393, p-value = 0.00) |
| • | (c) In mediation model, LED has significant relationship with INO (β = 0.13, C.R. = 1.778, p-value = 0.08) |
Therefore, based on above results, there is an evidence for the presence of partial mediation. This means, KMP partially mediates the relationship between LED and INO.
The other hypotheses such as Hd2, Hd3, Hd4, Hd5, Hd6, Hd7 and Hd8 are tested same above. The extracted concepts of the mediation effects of KMP on the relationship between Ofs’ factors and INO have been shown in Table 6.
As shown in Table 6, the findings of the structural model analysis supported the mediating role of KM processes in the relationship between organizational factors and organizational innovation. The results of the SEM analysis revealed that KM processes partially mediate the relationship between variables leadership and IT support of organizational factors with organizational innovation. The results of the tested model also show that: (a) Variables collaboration, centralization and training of the organizational factors had indirect significant relationships with organizational innovation through KM processes, (b) Variables incentives and formalization of the organizational factors had direct significant relationships with organizational innovation; and finally, (c) Variable trust of the organizational factors did not have any significant effect on organizational innovation.
CONCLUSION
The aim of this study was to examine the relationships among organizational factors, knowledge management processes and organizational innovation. In addition, the role KM processes as mediator in the development of organizational innovation were investigated. Result of the SEM analysis revealed that, (a) Variables leadership, collaboration, centralization, training and IT support of the OFs have significant relationships with KMP.
| Table 7: | Direct, indirect and total effects of latent variables on INO |
| β: Estimate of standardized regression weight, LED: Leadership, COL: Collaboration, TRU: Trust, INC: Incentives, CEN: Centralization, FOR: Formalization, TRA: Training, ITS: IT support, KMP: KM processes, INO: Organizational innovation, OFs: Organizational factors | |
(b) Variables leadership, incentives, formalization and IT support of the OFs have significant relationships with INO. (c) There is a significant positive relationship between KMP and INO. (d) KMP partially mediates the relationship between variables leadership and IT support of the OFs with INO.
Implicitly, the results showed that for this hypothesized model, 61% of the variance in the KMP is explained by the joint influences of the Ofs predictors and so, 49% of the variance in the INO is explained for by the joint influences of the predictors of OFs and KMP. The finding of the overall structural model showed that the IT support based on Direct, Indirect and Total Effects of Latent Variables on INO (Table 7) had the highest contribution toward the prediction of organizational innovation (β = 0.49). The incentives and leadership were the second and third predictor variables of organizational innovation, respectively (β = 0.21, β = 0.19). Therefore, this study verified that, OFs positively affect the innovation of public bank branches in Iran.
Implications: From an academic point of view, the results of this study especially its intermediate linkage helps scholars understand the processes further, which might be helpful in discovering additional mediator at different levels of analysis. The findings of this study also suggest that the variables of OFs such as (leadership, collaboration, centralization, training and IT support) increase KMP that have direct influence on INO. The results of this research have important implications primarily for scholars and managers.
From a practical point of view, the results of this study have some implications for public banks as follows:
| • | The findings of this study indicated that IT support has a strongly significant relationship with KM processes and organizational innovation (β = 0.43, β = 0.35, respectively). In addition, IT support based on Direct, Indirect and Total Effects of Latent Variables on INO (Table 7) has the highest contribution toward the prediction of organizational innovation (β = 0.37). These show that IT support plays key role in knowledge management issue in public banks in Iran |
| • | This study highlighted the importance of the relationship between Incentives variable with KM processes and organizational innovation (β = 0.19, β = 0.07, respectively). Pertaining to incentives, (Syed-Ikhsan and Rowland, 2004) believed that it is unrealistic to assume that all employees are willing to easily offer knowledge without considering what may be gained or lost as a result of this action. Therefore, employees need a strong motivator in order to share knowledge. Hence, managers of public banks should be used a favorable incentives system as management tools that hopefully contribute to a bank’s productivity by influencing individual or group behavior |
| • | The result from the mediation model findings indicated that leadership variable was significantly positively related to KM processes and organizational innovation (β = 0.13, β = 0.15, respectively). Meanwhile, based on (Anantatmula, 2008) view promoting innovation using the KM process requires collaborative culture and participation in decision-making. Leadership promotes innovation by creating a vision and providing strategic direction |