This article attempts to investigate the ‘Road Map’ of critical successful factors (CSFs) of knowledge management in Iranian insurance companies. In this study, we aim to identify the CSFs of knowledge management (KM) used in Iranian insurance companies and rank them to allocate limited available resources, such as time, budget and human resources, in an attempt to implement improvement programs. The Rembrandt method, being the optimised form of the analytical hierarchy process (AHP), was used to determine which critical successful factors were suitable for the implementation of knowledge management in organizations. In each organization, there are many vital issues’some more important than others’that must be considered. No organization can implement all improvement programs of knowledge management (KMIPs). In this research, we attempt to use the most important factors of each issue and, then, rank them for the sake of KM. Administrative, organizational, IT infrastructure, process perspective and human resource issues were the most important ones dealt with in this study. The road map provided in this article will help Iranian insurance managers better prioritise and allocate their limited resources to CSFs.
Keywords: Knowledge management, Rembrandt method, Critical successful factors (CSFs), Knowledge management improvement programs (KMIPs), Insurance companies
Nowadays, many organizations attempt to implement knowledge management programs because they realise that without knowledge management, they have to spend additional human resources and time to perform their work efficiently and effectively. Hence, knowledge management has a key role in organizations (Choi et al. 2008; Grant 1996; Spender 1996; Conner & Prahalad 1996)
When organizations implemented KM correctly, they survive the competitive markets. (Jafari et al. 2011; Akhavan & Pezeshkan 2014; Ramezani et al. 2013) After the introduction of knowledge management, many studies have focused on the usage of knowledge management in a variety of subjects and industries(Laleci et al. 2010; Li et al. 2011; Tinguaro Rodr??guez et al. 2010; Vandaie 2008; Chang & Wang 2009; Wei et al. 2011; Xu & Bernard 2011; Porumb & Analoui 2008)
The role of knowledgeable and experienced members of an organization in the success of the management is indispensable. A value chain involving acquisition, storage, distribution and application of knowledge, helps organizations have good and effective KM(Disterer 2002; Meyerson et al. 1996; Prencipe & Tell 2001; Sydow et al. 2004; Laudon & Laudon 1993; Nonaka 1995). Knowledge of customer services, production and the history of organizational successes or failures are organizational resources that will provide organizations with a long-term and sustained competitive advantage. By integrating well-selected knowledge and a proper strategy, one can gain a competitive advantage for his organization(Chang & Wang 2009). However, some critical successful factors must be considered while evolving our knowledge strategy. Many attempts following the introduction and implementation of KM in organizations lead to failure. There are many factors to be considered for the successful implementation of KM in organizations. After the identification of the key factors, knowledge management improvement projects (KMIPs) need to be designed and implemented for the successful implementation of KM in organizations.
KMIPs cannot succeed unless organizations identify the key CSFs. There are many studies on the methods of identifications of CSFs of KM such as Multiple Attributes Decision Making (MADM) methods to determine the most important CSFs. The Rembrandt method is an MADM method that is used in this study.
All the organizations focus, in particular, on the few most vital CSFs because of the availability of limited resources to implement KMIPs in their organizations. In this paper, the CSFs of knowledge management are identified and prioritised using the Rembrandt method.
First, the CSFs of knowledge management were compiled. Then, a questionnaire regarding these CSFs was designed based on the Rembrandt method. The questionnaires were distributed among the top managers of Iranian insurance companies. Finally, the responses to these questionnaires were collected and analysed using the Rembrandt software to determine which of the extracted CSFs are more important that require the companies’ limited resources allocated to them.
This paper consists of six sections. Following the introduction where the main motivation for this study is discussed, the second part focuses on the review of literature pertaining to KM. The Rembrandt method is presented in the third section. Section four is devoted to methodology, and empirical findings are presented in section five. Finally, the conclusion is presented in section six.
In every organization, many resources play key roles. Knowledge is one such resource, which is increasingly being regarded by some organizations as an important asset in creating the company’s competitive advantage(Chang et al. 2009). Hence, knowledge management is a powerful tool to record knowledge of companies. There are many definitions about KM; For example Gandhi (2004) asserts that knowledge is in four sections viz. data, information, science and wisdom. This tool helps companies to avoid their performance based solely on trial-and-error method. Many organizations seek to implement knowledge management, but they face a variety of problems in implementing KMIPs. In due course, they realise that critical successful factors of KM play a key role in the elimination of problems associated with KM implementation programs. Eventually, this leads to debates regarding the critical successful management in companies (Jennex et al. 2009; Clauson et al. 2011). Critical successful factors of knowledge management mean that without considering these factors, companies face many problems in implementing KM in their companies. Hence, they need to understand the priority of each relevant CSF of a KMIP. There are many tools for prioritising CSFs. One of them is multi-attribute decision making methods. These methods are used in numerous models and industries such as SCM (Shaw et al. 2013; Aouadni et al. 2013), manufacturing (Nagar & Raj 2012) and so on. These factors can be categorised into two types: internal factors and external factors. Internal factors can be controlled by the companies and make them as the core competency of companies. However, companies cannot affect external factors and can only reduce the negative effect of them. Hence, many critical successful factors are identified such as culture, information technology (IT) and leadership. Also, the staffs play a key role in the implementation of KM in companies (Agarwal & Poo 2008).
Some researchers have focused on finding and prioritising CSFs of KM. These studies have shown that, although there is debate among researchers about CSFs, most of them are similar. (Davenport et al. (1998) found eight CSFs: KM strategy, KM technology, KM structure, KM culture, clear target of KM, employee behaviour changes based on KM, channels of KM and supporting managers from KM. Liu (2011) showed the influence of CSFs of the KM of enterprise resource planning (ERP) on management performance in high-tech industries in Taiwan, viz. support from senior managers, corporate vision, re-engineering and project management, appropriate consultants and software suppliers, suitable employees and training/education. He illustrated that these factors had positive influence and significant correlation on manager’s performance. Chang & Wang (2009) used the fuzzy multi criteria decision-making approach to measure the possibility of successful knowledge management. These criteria were employee traits, strategy, superintendent traits, audit and assessment, organizational culture, operation procedure and information technology. They depicted among these factors, direct implementation and trust relationship among all staffs, specific team to take charge of knowledge management, participation and support from senior managers, motivation to share knowledge and auditing index and system for knowledge management were most important CSFs of KM.
Lindner & Wald (2011) categorised CSFs into the following sub-criteria: a) culture and leadership; b) organization, processes, ICT system dimensions and controlling of KM activities; c) processes PK; d) institutionalisation multi PM-PMO; e) organization PK; f) maturity PM methodology; g) mistake tolerance; h) information network; i) management commitment; j) project culture; k) ICT support; l) systems communication; and m) system storage as the success factors of knowledge management in temporary organizations. They employed partial least square (PLS) to find out the influence of these factors. They showed that IT support and culture factors had strong influence on knowledge management success. Chang et al. (2009) illustrated the CSFs of KM in Taiwan’s government. They depicted the KM process and the KM performance dimensions. The first category was divided into organizational mission and value, IT application, documentation KM, process management and structure. The next dimension included knowledge capture and transformation, business performance and knowledge sharing and value addition as sub-criteria. They revealed that mission had high priority in that research. Huang & Lai (2012) showed the CSFs of KM using structure equation modelling. They categorised these CSFs into environments, individual characteristics, KM characteristics, organizational characteristics, IT infrastructure, culture factors and KM implementation. They concluded that environments had a significant effect on organizational characteristics. Moreover, environments and IT infrastructure affected KM characteristics, and both KM characteristics and organizational characteristics influenced KM implementation. Mehregan et al. (2012) prioritised top management support, communication, document management, KM user satisfaction, knowledge quality, KMS quality, KM business alignment and culture using grey relational analysis. They ranked five companies based on these CSFs of KM to show strength and weaknesses of their KM initiatives. Salimi et al. (2012) discussed the key factors of KM in Iranian companies. They asserted that KM factors can be categorised into organizational culture, information technology, human resource, organization structure and senior management. Conley & Zheng (2009) defined top management and leadership support, organizational culture, strategy, organizational structure, process, technology infrastructure, training and education, measurement, incentive and the KM team as the CSFs of KM. They believed that these factors had significant effect on KM of the companies. Wu & Lee (2007) used fuzzy DEMATEL method for segmenting CSFs of KM. He illustrated that implementation of KM needed culture and people, top management support, incentives, communication, and so on. Furthermore, culture and people exert an effect on other factors when implementing KM. As previously mentioned, many organizations prefer to implement KM to achieve competitive advantage. The insurance industry of Iran is not exceptional to this principle. Hence, in order to implement KM in this industry, CSFs of KM must be identified and prioritised for better allocation of the available limited resources. The current research attempts to consider all materials previously identified by authors as CSFs and customise these CSFs for Iranian insurance companies. The weights of these CSFs were calculated. Prioritising these CSFs of KM can help insurance companies create a “road map” of KM, which can help them properly allocate limited resources, such as budget, time and human resources.
3.The Rembrandt Method
Following the introduction of AHP by Saaty (1994), there was a considerable amount of controversy regarding this model. Because of the variations in the results of studies conducted on AHP, DMs believe that this model must be used in cases with fewer alternatives. Lootsma (1992) introduced a new model which overcame the number of weaknesses in AHP. To analyze estimated weights, the new model, called ‘Rembrandt’, uses a logarithmic method instead of the 9-scale analytical hierarchical process and a geometric method instead of arithmetical average.
Most researchers find the geometric methods to be more reliable than the other methods for calculations. Rembrandt has a software package to implement this technique(Lootsma 1997; Lootsma 1992)
In this study, our first step was to consider a group of ‘g’ DMs (where, g ‘ 1) which relates to evaluating m criteria (where, m ‘ 1). Assuming the criteria Ci, (where i = 1, ‘., m,) with the subjective value (Vi), and supposing that Vi is the same for all DMs in the group, the m ‘ vector of Vi values from the DMs’ verbal subjective judgments are estimated by Rembrandt. Each DM was asked to judge pairs of criteria, Ci and Cj, and record his/her graded comparative score in the decision matrix, Dmxn. The requirement is the pair wise comparisons of (m-1) and m(m-1)/2 for a set of m criteria, i.e, the DM records his preference for one attribute over another on a scale of weak, definite, strong, or very strong. Then, a general procedure proposed by Lootsma (1997) is used to handle incomplete pair wise comparisons. Considering the ratio information, the subjective criteria weights are normalized, so that ??iVi=1 is obtained. In order to limit the range of verbal responses, the DM’s pairwise comparison judgments are captured. Using the scale in Table 1, each verbal response is then converted into an integer-valued gradation index, ??jld.
Please Insert Table 1 Here
The gradation index, ??jld is converted into a value of geometric scale, ??. Thus, rjld, the numeric estimate of the preference ratio (Vj/Vl), which is given by the DMd, is defined as follows (Eq. 1):
Considering that there is no unique scale for human judgment, a plausible value of for the group is , implying a geometric scale with a progression factor of (Lootsma 1993). In the second step, V is approximated by the normalized vector v of group weights which minimizes: (2)
Let’s assume that a complete set of pairwise comparisons is offered by all DMs. Now & . Then, the vector of v is determined by minimizing Eq. (3) as a function of as follows:
The set dependence of normal questions is calculated using Eq. 4 as follows:
Now, let and for any . Eq. (4) can be written as follows (Eq. 5):
No unique solution to this set of normal equations can be found. For a particular solution, the sum of the variables equals zero and reduces Eq. (5) to the following unnormalized solution ( Eq.6):
where Eq. (8) implies that the criteria weights of are calculated by a sequence of geometric means. To determine the normalized solution vector v, the result of in (Eq. 8) is multiplied by the degree of freedom. In addition, since , the normalized criteria weights will be dependent on the scale parameter , without changing the rank ordering of .
In this study, in order to identify the CSFs of KM, the top managers of all insurance companies in Iran were not only interviewed but also asked to fill out the questionnaires designed for this research. The structure of this research is based on survey questionnaires. After the identification of the CSFs, the questionnaire for ranking these CSFs was designed based on CSFs of KM and Rembrandt method. The mathematical method was used to analyse the data.
‘ What are the CSFs of KM in insurance companies’? What are the weights of these CSFs’? Which of the CSFs have a higher priority?
4.3.Target of questionnaire survey
The sample population was chosen from 19 Iranian insurance companies, most of which are active in 31 provinces. The Kokran formula was used to find the sample population, resulting in the selection of 323 insurance company experts as the sample. The respondents were top managers of these companies. After distributing 323 questionnaires among experts, 318 effective questionnaires were collected.
4.4.Questionnaire design and measurement
Questionnaire of ranking CSFs consists of the following: 1) administrative issues; 2) organizational issues; 3) IT infrastructure; 4) process perspective; and 5) human resource issues. These main categories have 28 indicators. The measurement of these CSFs is done by ranking them by designing the road map of implementation of KM in Iranian insurance companies.
4.5.Data analysis method
The questionnaire of this study is designed based on pair-wise comparison of main categories and indicators of CSFs of KM. Rembrandt software was used for analysing the data.
4.6.Reliability and validity tests
Following the identification of the CSFs, questionnaires were designed based on these CSFs and the Rembrandt method, and subsequently sent to the said sample population. The questionnaire of this research is based on interview, and the questionnaires were sent to top managers of insurance companies and experts of KM to identify the CSFs of KM. The researchers ascertained the validity of this questionnaire with experts and top managers. The completed questionnaires were then collected and analysed using the Rembrandt software, which also measured the reliability of the collected data. The software does not analyse data that are found unreliable. Figure 1 describes the methodology of this research.
Please Insert Figure 1
5. Data Analysis
The CSFs were identified based on the results of the interviews and the data collected via the questionnaires sent to the sample members.
Table 2 illustrates the CSFs of KM in insurance companies
Please Insert Table 2
The CSFs were categorised into administrative, organizational, IT infrastructure, process perspective and human resources indicators.
The sub-criteria of the administrative indicator are KM thinking, stakeholder’s approach, hierarchy of organization, practice of communication, manager’s perception of KM, support of top managers, managers’ participation, strategy acceptance in organization, scale of goal achievement and scale of manager’s learning.
The organizational indicator is divided into privatisation, number of meetings held on KM, informal groups, member’s relationship and number of partners.
IT infrastructure involves using appropriate search engines, expert systems, reliability and ERP.
Value chain identification, process of storing and disseminating information, number of KM process identification, protection of intellectual property and management of process form the sub-indicators of the process indicator.
Human resources as the fifth indicator is composed of the incentive system, communication, type of available skills in the organization and staff’s knowledge of KM.
After the identification of the CSFs, another questionnaire was designed based on the identified CSFs and the Rembrandt method and was distributed among the experts. Then, the data collected were analysed using the Rembrandt software. The results were as follows:
Among the five identified key indicators of CSF of KM, the organizational indicator acquires the highest priority. The second priority goes to the administrative indicator, which means that managers must support improvement programs to implement KMIPs in insurance companies. The next priority is IT infrastructure, which refers to the availability of a hardware infrastructure for the implementation of KMIPs in insurance companies.
Human resources, as the subsequent key indicator, are the subordinates of managers who help the organization establish KM.
Process perspective has the lowest priority, indicating that the conditions of processes in insurance companies are suitable, and there is no need to focus on them.
Please Insert Table 3
The sub-indicators of the most important CSFs of KMs are as follows:
Member’s relationship is the highest priority indicator in this perspective. The next sub-indicator with a high priority is informal groups. Number of meetings held on KM is the third important factor in this indicator which is followed by the number of partners. Privatisation is the last factor in organization issues.
Please Insert Table 4
Strategy acceptance in organization is the sub-indicator of highest importance in administrative issues.
Stakeholder’s approach, as the most effective approach in an organization, is the second important sub-indicator.
The third sub-indicator is the manager’s participation and support of the top managers comes fourth. Top managers of an organization should support all KM programs and encourage staff to implement KM in their organizations.
The fifth sub-indicator is scale of goal achievement. Practice of communication is the sixth sub-indicator, which helps managers share their knowledge with other managers and staff.
The seventh sub-indicator is KM thinking.
Manager’s perception of KM is the eighth sub-indicator.
Scale of manager’s learning is the ninth sub-indicator. Hierarchy of organization, being the last sub-indicator, has the lowest effect on implementing KM in insurance companies.
Please insert Table 5
IT infrastructure is the third important indicator to be explored in this research. Using appropriate search engines is the first important sub-indicator of this criterion. ERP is the second important sub-indicator, which helps managers gain a better understanding of their organization and KM programs in their companies. Reliability is the next important sub-indicator. The final sub-indicator is the expert system that helps organizations, especially managers, make right decisions easily.
Please insert Table 6
Human resource is the fourth indicator, and its first sub-indicator is incentive system. Staff knowledge of KM is the second highest priority sub-indicator. Communication is the third important factor, which helps organizations with program documentation. The final sub-indicator is the type of available skills in the organization, which will have influence on the success of any KMIPs and will help organizations confront probable threats.
Please insert Table 7
The last indicator is process perspective, the first sub-indicator of which is processes of storage and dissemination of information. The second sub-indicator is protection of intellectual property, which urges managers to protect the knowledge produced inside the organization against unlawful applications.
The third sub-indicator is the number of KM processes identification, which shows how to identify, map and implement the KMIPs.
The fourth sub-indicator is management of the process through which the knowledge is created, collected, processed and stored. Such a process not only helps managers and staff of insurance companies create, map and store knowledge but also encourages them to acquire new knowledge.
Value chain identification is the last sub-indicator, which should be developed and disseminated throughout the organization.
Please insert Table 8
KM is one of the most important tools in creating excellence in an organization. This tool helps organizations avoid operating on a trial-error basis. There are many barriers to implementing KM in organizations. To implement KM better, companies need to know their weaknesses and strengths. The result will help them better and more efficiently allocate and manage their available limited resources.
This research attempts to show that no Iranian insurance company is able to consider all CSF indicators in KM in a given time. In other words, these organizations should first identify and then prioritise these CSFs, which are categorised into five main indicators. These indicators include: administrative, organizational and human resources, IT infrastructure and process perspective. The said indicators and their 28 sub-indicators were prioritised based on the Rembrandt method. In this research, initially, CSFs of KM in insurance companies are identified in 5 major categories and classified as 28 sub-indicators. Using the Rembrandt method, the weights of these indicators and sub-indicators are calculated and prioritised to design the road map of KM. Rembrandt is a precise model for prioritising KM indicators and sub-indicators in organizations. The reason for this lies in the application of logarithm scales and geometric methods for data analysis and its higher degree of reliability in comparison to other MADM methods. Using this method in this work resulted in an increase in the trust of insurance companies.
The results show that the indicator with the maximum priority is organizational dimension, and the least important indicator in insurance companies is process perspective. Table 9 shows the priority of all sub-indicators based on dimensions and sub-criteria weights.
Please Insert Table 9
The first indicator of CSFs of KM is Member’s relationship. The relationship among the staff will help better implement a KM improvement project in an organization and ensure better program documentation of KM projects by the staff. The next CSF is Staffs’ knowledge about KM. Should the staffs have enough knowledge of KM and its benefits, such improvement programs would rarely fail. The third indicator is Using appropriate search engine. Such engines help insurance companies find the appropriate data and knowledge they need. Without these tools, organizations tend to spend more time to find the necessary data. The fourth CSF is processes of storage and dissemination of information. These organizations have to design processes to store, document and disseminate information to minimise the risk of loss of knowledge in the organization. ERP is the fifth important CSF of KM in this research which helps managers gain a better understanding of their organization and KM programs in their companies.
The five least important factors are:
1. Practice of communication: Which helps managers share their knowledge with other managers and staff.
2. KM thinking: Without this sub-indicator, managers would not only be unable to support the staff and the organization, but they may also down play the need to deploy necessary facilities to implement KM in their organizations.
3. Manager’s perception of KM: The successful implementation of KM will depend on the perception of the managers of this improvement program
4. Scale of manager’s learning: Managers should not only invest in teaching KM programs to the staff, but they must also design scales to evaluate the efficiency and effectiveness of such KM learning programs
5. Hierarchy of organization: This means that the hierarchy of insurance companies is suitable for the implementation of KM.
These latter CSFs show insurance companies enjoy suitable condition in these factors and they must not waste their resources on those.
This “road map”, which used two powerful managerial implications, such as literature of CSFs for KM and Rembrandt method, helps Iranian insurance companies allocate their limited resources, such as time, budget and human resources, to the main indicators and sub-indicators, which have a higher priority. Moreover, it assists these organizations to identify their weaknesses and strengths to implement KMIPs.
Figure 2 shows the road map of this research
Please Insert Figure 2
6.2. Limitations of this study and future prospects
Some limitations of this study are acknowledged here. First, respondents, in general, do not prefer to answer the questionnaire. Second, completing the pair-wise questions was too hard for respondents and a lot time was spent to encourage them to answer the questions.
In future research attempts, this model can be applied to various aspects of other industries. Moreover, industries can assess the effects of these indicators and dimensions using the DEMATEL method. If the number of alternatives and options are very high or if the researchers wanted to eliminate low priority of alternatives, they can use Electre or Promethee methods, alternatively.
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