African Journal of Business Management Vol. 6(2), pp. 627-645,18 January, 2012 Available online at http://www.academicjournals.org/AJBM DOI: 10.5897/AJBM11.2148 ISSN 1993-8233 ©2012 Academic Journals

Full Length Research Paper

Using DEMATEL – Analytic network process (ANP) hybrid algorithm approach for selecting improvement

projects of Iranian excellence model in healthcare sector

Ali Taghizadeh Herat1*, Rassol Noorossana2, Sahar parsa1 and Elahe Shariatmadari Serkani1

1Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

2Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.

Accepted 10 November, 2011

Quality is the most vital factor for growth and survival of organizations and healthcare organizations, are not exceptional from this rule. There have been several models presented for deployment and assessment of quality management which much more attention is paid to organization excellence models due to their being total and complete. The European foundation for quality management (EFQM) excellence model can be used for continuous improvement of activities and performance of organizations from both private and public sector by establishing a total quality management (TQM) philosophy. Iran national productivity and excellence award in collaboration with Azad University – Science and Research campus and ministry of health, treatment and medical training, designed a model for healthcare organizations and this model was used in 23 hospitals. While using the model, hospitals noticed a large number of areas for improvement, and in order to grow they had to cover them by implementing improvement projects. (However) it was (impossible) to implement the entire project simultaneously and they needed to prioritize and chose the most effective ones. In this article based on experienced gained in hospitals, we could draw the causal relations between nine areas of healthcare organization excellence model using decision making trial and evaluation laboratory (DEMATEL) mathematical model and determine their effects on each other. Then based on these causal relations, we ranked the improvement projects using the Analytic Network Process (ANP) model. Project number nine “leadership development and succession planning” got the highest score, and it is the most appropriate choice.

Key words: European foundation for quality management (EFQM), decision making trial and evaluation

laboratory (DEMATEL), analytic network process (ANP), Health Sector. INTRODUCTION

Nowadays, many Iranian organizations have realized the need for regular and systematic self-assessment which improvement projects are based on. It has been realized that on-time detection and management of change are competitive advantages. Improvement projects help the organization achieve higher level of excellence. Self-assessment process clearly identifies the strength and improvement potentials of the organization (Najmi and *Corresponding author. E-mail: a.taghizadeh@srbiau.ac.ir.

Hoseini, 2009). Today, many countries around the world encourage organizations and companies to follow the models of excellence such as European foundation for quality management (EFQM), Deming and Baldrige. They award prizes, such as human resource (HR) excellence awards of HR management association of America, standard of investment in human resources and developer standard in Singapore, through institutions and professional associations of human resource develop-ment and management to companies and organizations that have accomplished significant achievements in the field of human-resources (Ghelich lee, 2007). The EFQM

628 Afr. J. Bus. Manage. model is a generic model for quality management, which is used in all types of organizations as a multidimensional framework. One of the most positive aspects of EFQM is the use of self-assessment (Tutuncu and Kucukusta, 2009). In order to achieve excellence, companies need to be aware of the impact of criteria on each other and also the analysis of relations between enablers and results. Since the EFQM excellence model does not show the relationships clearly, companies are not able to accu-rately analyze the effects of the projects on the criteria after implementing self-assessment and identifying areas that have to be improved. Understanding the relationships between the criteria makes it possible for companies to analyze the projects‟ effects on model criteria and to apply appropriate tools for improvement while planning and setting goals for the future direction of organization excellence. Accordingly, in 2002, following the model of the EFQM Excellence Award (EEA), Iran launched Iran National Productivity and Excellence Award (INPE). Also due to the needs of various sectors for an exclusive and customized model, the plan for recreation of the EFQM excellence model in accordance with the healthcare sector was proposed in 2010.

Mashhad University of medical sciences which, in the form of MUMS

1 Evaluation and Excellence Award

(MEEA), uses the EFQM excellence model in order to assess performance of its affiliate branches, in 2011, used the re-conceptualized model for the health sector at 23 of hospitals controlled by this university. While using the model, Hospitals noticed a large number of areas for improvement, and in order to grow they had to cover them by implementing improvement projects. However, it was impossible to implement the entire project simultaneously and they needed to prioritize and chose the most effective ones.

In this article based on experienced gained in hospitals, we could draw the causal relations between nine areas of healthcare organization excellence model using decision making trial and evaluation laboratory (DEMATEL) mathematical model and determine their effects on each other. The opinions of 15 experts are collected by means of a matrix based questionnaire and the analysis is performed based on the responses.

Then based on these causal relations, we ranked the improvement projects using the Analytic Network Process (ANP) model.

Subsequently, there will be a literature review and criteria of Healthcare organization excellence model, process of deploying the excellence model, description of DEMATEL method and analytic network process (ANP), and a review on the background of study. Then, the research methodology is discussed, and deployment of this methodology in 23 treatment centers (hospitals) in Mashhad is described. At the end, there is a conclusion on the whole discussion.

1 Mashhad University of Medical Sciences

LITERATURE REVIEW

EFQM excellence

The European foundation for quality management (EFQM) based in Brussels was founded in 1988 by 14 leading corporations. The aim is to induce and secure a systematic and incremental increase in quality in European organizations in order to strengthen their position in the global market (Herget and Hierl, 2007). There are some researchers (Westlund, 2001; Bou-Llusar et al., 2005; Calvo-Mora et al., 2005; Vijende and Gonzalez, 2007; Martinez-Lorente et al., 2009) that have pointed out that the EFQM excellence model constitutes an appropriate framework to guide the systematic implementation of total quality management (TQM) .After reviewing the literature, it turned out that many resear-chers like (Dahlgaard-park, 2008; Bergquist et al., 2005) have considered the excellence model as a systematic mechanism to improve organizational performance.

The EFQM excellence model is a non-prescriptive framework that establishes nine criteria, which any organization can use to assess the progress towards excellence. These nine criteria are divided between enablers and results (Calvo-Mora et al., 2006). The model includes five “enabler” criteria: leadership; stra-tegy; people; partnership and resources; and processes, products and services. It also comprises four “results” criteria: customer results, people results, society results, and key results (EFQM, 2010). The enablers represent the way the organization operates, and the results concentrate on achievements relating to organizational stakeholders (Bou-Llusar et al., 2009). According to EFQM (2010) organizations that aim at achieving excellence focus on improvement in some concepts of TQM theory such as achieving balanced Results, adding value for customers, leading with vision, inspiration and integrity, managing by processes, succeeding through people, nurturing creativity and innovation, building partnerships and taking responsibility for a sustainable future. The specific purpose of the EFQM excellence model is to provide a systems perspective for understanding performance management. With their acceptance nationally and internationally as the model for performance excellence, the criteria represent a common language for communicating and sharing best practices among organizations (Wongrassamee et al., 2003). The original EFQM excellence framework is presented in Figure 1.

The process of using the organizational excellence model in the health sector

Based on the method defined by EFQM, the organizational excellence model is used through an eight-stage process, as shown in Figure 2.

Stage 1: The first stage of this process is establishing

Herat et al. 629

Figure 1. EFQM excellence framework.

Stage 1:

Developing and

retaining commitment

Stage 2:

Developing

and deploying

communication

strategy for stages 3-8

Stage 3:

Planning

self-assessment

Stage 4:

selecting and training

people directly

involved in this

process

Stage 5:

performing self-assessment

Stage 6:

Studying results and priorities

Stage 7:

Defining and

implementing

improvement projects

Stage 8 : monitoring progress and revising self-assessment process

Figure 2. Stages for using organizational excellence model.

and maintenance of organizational leaders‟ commitment to organizational excellence. In this stage, using educational plans and culture building, leaders become familiar with the concepts and models of organizational excellence and the necessity of self-assessment and improvement planning based on the excellence model. Stage 2: The aim of this stage is establishing organiza-tional excellence relationships. The speeches and messages of the leaders, using panels and newsletters, and creating websites are among tools, which are used to implement excellence relationship‟s strategy. Stage 3: In the self-assessment planning stage, the manager of organizational excellence is appointed and organizing excellence is performed (appointing excellence teams). Besides, the technique used for self- assessment is specified and a schedule for implementing self-assessment is prepared. Stage 4: Implementing self-assessment begins with selecting individuals and appointing them to excellence teams as well as familiarizing them with the model and self-assessment based on the excellence model.

Stage 5: In the self-assessment stage, using techniques selected for self-assessment, excellence team members perform different stages of self-assessment. Self-assessment will have three major results for the organi-zation; strong points, improvable areas, and score. The obtained improvable areas are input of the sixth stage. Stage 6: In this stage, organization leaders discuss the improvements which have priority for the organization and prioritize them and eventually, select some of them. Stage 7: For the selected improvable areas, improvement projects are defined; trustees are selected; resources are allocated to them, and their implementation begins. Stage 8: In the last stage, progress of improvement projects is periodically monitored and by revising the process of self-assessment in the previous stages, a new self-assessment is performed at the organization. In fact, using the excellence model is a continuous improvement cycle which lasts forever. Using the excellence model in the healthcare sector at 23 hospitals was also based on this process.

630 Afr. J. Bus. Manage. DEMATEL method

DEMATEL method was introduced by BMI Institute, Swiss, between 1972 and 1976, in a project in Geneva Research Center to examine and solve complicated pro-blems (Moghadam and Alavijeh, 2009). The DEMATEL designs a system structure by using knowledge of experts (Shih et al., 2010). According to opinions of some researchers (Tamura and Akazawa, 2005; Makuyi and Samani, 2005), it is preferred to use DEMATEL method for the following reasons: 1. This method extracts mutual impressible and effective relations of elements by using graph theory so that it score rate of each relation by a number. 2. This method uses a feedback of relations; namely, each element can affect other elements in the same, upper, and lower levels and be affected by them. 3. The importance and weight of each element in this model are determined not only by upstream and downstream factors, but also by all available factors or total model. In recent years, DEMATEL technique has been widely applied to evaluate interrelationships between criteria. Tseng (2009) employed DEMATEL technique to assess relationships between the criteria of service quality exception (Tseng, 2009a) and also evaluate the interrelationships of service quality evaluation criteria and propose a cause and effect model for improving service quality in hotels (Tseng, 2009b). Tsai and Chou (2009) employed DEMATEL approach to construct interrelations between four criteria that SMEs require to evaluate a quality management system (Tsai and Chou, 2009). Wu (2008) also used DEMATEL to evaluate interrelationship between influential factors in assessing knowledge management strategies in Taiwan organizations (Wu, 2008). The steps in DEMATEL are as follows (Lee et al., 2011):

Step 1: construct scales of evaluations Using pair-wise comparisons of dimensions, the degrees of perceptions from the interviewees regarding the level of impacts of particular dimensions are examined. The measurement criteria of 0, 1, 2, 3, and 4 are used to illus-trate no influence, low influence, medium influence, high influence, and extremely high influence, respectively. Step 2: Construct the direct-influence matrix Z

The direct-influence matrix is constructed based on the degrees of relative impacts derived from the pair

comparisons. An nn direct-influence matrix Z with the directly observed relations is obtained where zij denotes the degree of impacts of the i factor on the j factor.

𝑍 =

𝑧11 𝑧12 ⋯ 𝑧1𝑛

𝑧21 𝑧22 … 𝑧2𝑛

⋮ ⋮ ⋱ ⋮𝑧𝑛1 𝑧𝑛2 ⋯ 𝑧𝑛𝑛

(1)

Step 3: Composes the normalized direct-relation matrix X Composes the normalized direct-relation matrix, which can be derived from Equations 2 and 3, where the matrix diagonal is coded 0 and the sum of each row and column does not exceed 1. X = s . Z (2)

s = min 1

max𝑖

𝑧𝑖𝑗 𝑛𝑗=1

, 1

max𝑗

𝑧𝑖𝑗 𝑛𝑖=1

, 𝑖, 𝑗

= 1,2, … , 𝑛 (3) Step 4: Derive the total-influence matrix T.

The total-influence matrix T is an nn matrix and is defined as follows: T=X+X

2+X

3+...+X

m=X(I-X)

-1 (4)

where I represents the identity matrix.

Step 5: Obtains the prominence and relation by summing each row and column in T to yield D and R

D=[di]n1 = 𝑡𝑖𝑗𝑛𝑗=1 n 1 (5)

R= [rj]1n = 𝑡𝑖𝑗

𝑛𝑖=1

1 n (6)

Where superscript denotes transpose. Here, di is the sum of each row in T and the rows show

the degrees of direct and indirect impacts over the other criteria, and rj is the sum of each column in T where columns indicates the degrees of influences from other criteria. Numeric algorithm variable di, therefore, represents the factors that influence others, rj represents factors that are influenced by others, di + rj represents the strength of relationships between factors, di - rj represents the strength of influences among factors. In other words, di + rj and di - rj represent the so called prominences and relations, respectively.

Step 6: Set a threshold value and obtain the network relationship map (NRM) (Yang and Tzeng, 2011)

In order to explain the structural relation between the

Herat et al. 631

Figure 3. Structural difference between a hierarchy and a network.(a) a hierarchy (b) a network.

criteria and keep the complexity of the system to a manageable level at the same time, decision maker must set a threshold value p to filter out some negligible effects in matrix T. Only some criteria, whose effect in the matrix T is greater than the threshold value, should be chosen and shown in a NRM for influence (Tzeng et al., 2007). After the threshold value is decided, the final influence result of criteria can be shown in a NRM.

Analytic network process (ANP) method

The ANP, a new theory extending from the AHP, is proposed by Saaty (1996). AHP model contains hierarchical relationship between overall goal, criteria, sub-criteria and alternatives. However the problems do not always show hierarchical structure. In such a case, ANP structures the problem as network instead of hierarchical modeling. However in ANP, criteria in the lower level may provide feedback to the criteria in the higher level, and the interdependence among the criteria in the same level is permitted. Another difference between AHP and ANP in the calculation process is that a new concept “super-matrix” is introduced in ANP. The application steps of ANP which is composed of four major steps are as follows (Saaty, 1999): Step 1: Forming the network structure

The problem should be stated clearly and decomposed into a rational system like a network. The structure can be obtained by the opinion of decision-makers through brainstorming or other appropriate methods. Firstly, criteria, sub criteria and alternatives are defined. Then, the clusters of elements are determined. Network is formed based on the relationship between clusters and

within elements in each cluster. An example of the format of a network is shown in Figure 3(b). Step 2: Forming pair-wise comparison matrices and obtaining the priority vector

Pair-wise comparisons are performed on the elements within the clusters as they influence each cluster and on those that it influences, with respect to that criterion. The pair-wise comparisons are made with respect to a criterion or sub-criterion of the control hierarchy. Thus, importance weight of factors is determined. In pair-wise comparison, decision makers compare two elements. Then, they determine the contribution of factors to the result (Saaty, 2001). In ANP, like AHP, it is formed pair-wise comparison matrices with use 1 to 9 scale of relative importance proposed by Saaty. 1 to 9 scale of relative importance is given in Table 1.

A reciprocal value is assigned to the inverse

comparison; that is 𝑎𝑖𝑗 =1

𝑎𝑗𝑖, where aij (aji) denotes the

importance of the ith (jth) element. Like AHP, The values of pair-wise comparisons are allocated in the comparison matrix and local priority vector is obtained from eigenvector, which is calculated from this equation:

A×w=λmax×w (6) where A is the matrix of the pair-wise comparison, w is the eigenvector, and λmax is the largest eigenvalue of A. Consistency of pair-wise matrix is checked by consistency index (CI). For accepted consistency, CI must be smaller than 0.10 [1].

CI= λmax −𝑛

𝑛−1𝐶𝑅 =

𝐶𝐼

𝑅𝐼 (7)

632 Afr. J. Bus. Manage.

Table 1. Scale of relative importance.

Intensity of importance Definition

1 Equal importance

3 Moderate importance

5 Essential or strong importance

7 Very strong importance

9 Extreme importance

2, 4, 6, 8 Intermediate value between adjacent scale values

In Equation 7, CI, RI and CR represent consistency indicator, random indicator and consistency ratio, respectively.

Step 3: Super-matrix formation

For evaluating the weights of elements, the AHP uses the principal eigenvector of the comparison matrix, while the ANP employs the limiting process method of the powers of the super-matrix. The super-matrix concept is similar to the Markov chain process (Saaty, 2005). To obtain global priorities in a system with interdependent influences, the local priority vectors are entered in the appropriate co-lumns of a matrix. As a result, a super-matrix is actually a partitioned matrix, where each sub-matrix represents a relationship between two nodes (components or clusters) in a system.

Step 4: Selection of best alternatives

It can determine importance weights of alternatives, factors and sub factors from limited super-matrix. The highest importance weight shows the best alternative.

Research background

Table 2 shows some researches in relationships among EFQM excellence model criteria field.

METHODOLOGY

The research methodology is consisted of three main phases which the process is presented in Figure 4.

Phase 1: Defining problem and theoretical framework of research.

Step 1: Review on fundamental of organization excellence model and healthcare excellence model. Step 2: Review on process of using the organization excellence model (which was defined by EFQM and were deployed exactly the same in Iran‟s health and treatment centers).

Phase 2: Modeling and deployment of DEMATEL method

In this phase, the interrelations within the excellence model will be understood by deployment of DEMATEL method.

Phase 3: Deployment of ANP for ranking the projects In final phase ANP method will be used on network made by DEMATEL for prioritizing 10 improvement projects.

IMPLEMENTATION AND DATA ANALYSIS Here, based on steps of DEMATEL method, data analysis was performed. Besides, in order to form the effect matrix and determining the coefficients of effectiveness of criteria on each other, focal group with executives of the plan for using the excellence model in the health sector at 23 hospitals was formed. Following the steps in DEMATEL, we obtained the results as shown in Tables 3, 4, 5 and 6.

This case study the threshold value used in step 6 is to compute the average of the elements in matrix T, which is 0.407. Based on Table 5, there are six criteria which have the influence on key results but the contribution of people is the smallest. Thus, people are not a necessity. In contrast, strategy is the one more essential criterion to strengthen key results. The effectiveness of organizational strategies is revealed in key results and lessons learned from analyzing key results and revising them leads to reconsideration of the strategies by the organization.

The findings based on Table 6 indicated that, key results is the most important criterion with the value of 8.23, while society results is the least important criterion with the value of 5.52. Also, based on this table, in contrast to the importance, leadership, strategy, and partnership and resources are net causes, whereas people, processes, products and services, and results criteria (customer results, people results, society results, and key results) are net receivers based on (d - r) values. The cause and effect diagram is shown in Figure 5.

In Figure 5, the mutual relationship between people and people results is observed. Human resources planning, personnel training and development, personnel participation, organizational relationships, and rewarding and encouraging the personnel are among people criterion issues, which lead to improvement of human resources management performance and increase of personnel motivation and satisfaction. Undoubtedly, feedback from personnel satisfaction and motivation and revising and improving the human resources procedures and the effects of people results and people on each other leads to creation of a cycle of continuous improvement between enablers and human resources results.

After specifying the causal relations using DEMATEL method, ANP algorithm will be applied to this network in order to prioritize 10 improvement projects. The main objective which is to select the best improvement project placed on the topmost level of the model. Second level consists of the main criteria that affect the selection of the best improvement project. There are 10 improvement projects, which are evaluated at the lowest level (Figure 6 and Table 7).

In this model, the relationship between clusters and criteria are identified even they are not hierarchical. The links between

Herat et al. 633

Table 2. Research background.

Year Authors Methodology and results

EFQM and DEMATEL (using DEMATEL for understanding interrelations between criteria of EFQM excellence model)

2010 Ehsan Sadeh and Veeri Chettiar Arumugam

Iranian small and medium-sized enterprises (SMEs) need to utilize management systems, especially quality systems in their operations and they are proposed to apply a suitable performance assessment and improvement model such as the EFQM. The aim of this paper is to determine interrelationships among excellence criteria which are presupposed by the original EFQM framework in Iranian industrial SMEs. The results indicate Leaderships is the most effective criteria having the largest influence on other excellence concepts. Also the finding revealed people is an important impressive criterion having a large effect value on other concepts. Further results show key results criterion is significantly affected by other excellence criteria.

EFQM (Using “SEM”,”PLS” and other technics use for understanding interrelations between criteria of EFQM excellence model)

2009 Martinez-Lorente et al

The regression technique was used to test the direct and indirect interrelationships in 71 organizations by apply a questionnaire. The results revealed the direct and indirect relationships among the criteria which are forgotten by original EFQM excellence model.

2007 Chinda and Mohamed

The structural equation modeling (SEM) was used to test causal relationships between key elements (five enablers and goals) of safety culture. The results demonstrated Leadership has positive effects on people, Partnership and resources, and strategy. Also people influence partnership and resources and processes, products and services. Further partnership and resources impact on strategy. Beside it was showed that strategy has impact on processes. Finally, results revealed the effect of processes on goals.

2007 Sila

The SEM was used to test relationships among result factors in a TQM system. The results showed people results have a direct, positive effect on customer results and Society results. Also society results have a direct, positive effect on customer results and key performance results. Further customer results have a direct, positive effect on key performance results.

2007 Vijande and Gonzalez

The SEM technique is applied to test the impact of the enabler criteria on the results in the EFQM model. Confirmatory factor analysis was used to test the measurement scales and hypothesized relationship between enablers and results. The results demonstrated there are causal relationships between enablers and results.

634 Afr. J. Bus. Manage. Table 2. Contd.

2005 Calvo-Mora et al.

Partial Least Squares (PLS) was applied as a multivariate analysis technique to test the relationships in EFQM excellence model adapted to the university sphere. The leadership and commitment of the management have a positive influence on people management, strategy and partnerships and resources. Strategy has a positive influence on people management, partnerships and resources and process management. People management has a positive influence on process management. Partnership and resources have a positive influence on process management. Process management has a positive influence on people results and the centre results. People results have a positive influence on the centre results and the student results. Student results have a positive influence on the centre results. The centre results have a positive influence on social results.

2000 Eskildsen and Dahlgaard

They some linkages between the five enabler criteria and people results by using SEM technique. This study indicated that leadership significantly drives people, strategy, partnership and resources, which affect processes. Moreover, there is a direct influence of strategy on people and partnerships and resources. Also people and processes influence people results. But customer results have only effect on Key results and Society results have merely effect on customer results.

EFQM and ANP 2011 Abbas Toloie Eshlaghy and Mehrdad Peydaie

This article introduces a conceptual and mathematical model to evaluate human resource excellence in Iranian governmental organizations .In this process on study of concept and different models of excellence; they provided a new definition of excellence. Then the researchers used analytic network process (ANP), and coefficients weights for each criterion of organizations. This study provided a pattern which evaluates the performance of the human resources excellence and has been introduced as national award of human resources excellence. Profiting from quantitative models as well as measurable factors, this pattern is applied in designing human resources dashboards and decision making support systems.

DEMATEL and ANP 2011 Chun-AnChen et al.

In this study, DEMATEL and Maximum Mean De-Entropy (MMDE) are adopted to analyze the factors of tourism as they relate to branding Taiwan. The results show that the ‘festival’ is the most important fact for Taiwan nation brand in perspective of tourism.

2010 Wen-Hsien Tsai et al.

A sourcing decision about whether to keep IT functions in-house or contract with a third-party service provider is nevertheless entirely strategic and contingent upon organizational goals and contextual and project-specific factors. This article proposes a Multi-Criteria Decision Making (MCDM) approach to achieve effective problem-solving by combining DEMATEL, ANP, and zero-one goal programming. The final research results reveal that an organization can – simultaneously – not only take advantage of its internal or external resources to set priorities for task arrangements within the portfolio of sourcing decisions, but also optimize operating strategy and management despite limited resources after consulting with the expert panel.

Herat et al. 635

Table 2. Contd.

2011

Jiann Liang Yang and Gwo-Hshiung Tzeng

In this paper, in which the DEMATEL method is used to visualize the structure of complicated causal relationships between criteria of a system and obtain the influence level of these criteria. And, then adopt these influence level values as the base of normalization supermatrix for calculating ANP weights to obtain the relative importance. Additionally, an empirical study is illustrated to demonstrate that the proposed method is more suitable and reasonable. By the concept of ideal point, some important conclusions drawn from a practical application can be referred by practitioners.

2011 Wen-Shiung Lee a

Existing methodologies of equity investment, such as fundamental analysis, technical analysis, and institutional investor analysis, explore important factors of stock price behaviors This paper provides the first analysis on the interactive relationships among the factors in incorporating the methods of DEMATEL and ANP. The empirical results show that factors from the existing analytical methodologies have significant interactive and self-feedback dynamics. Among the key factors, profitability is the most important one affecting investment decision, followed by growth and trading volume. In addition, due to the complexity of the ANP, this study proposes a new methodology to simplify the process, and empirical evidences indicate that the approach is effective and efficient.

2008 Wei-Wen Wu

This paper proposes an effective solution based on a combined ANP and DEMATEL approach to help companies that need to evaluate and select knowledge management strategies. Additionally, an empirical study is presented to illustrate the application of the proposed method. The results of this study show that the most desired purpose was „„activating information‟‟, and „„Personalization strategy‟‟ was preferred.

Health care and MCDM

2011 Frank F. C. Pan

This research focused on identifying the patients‟ perceived values toward hospitals. To capture with more confidence the misty inner of the patients‟ value perception, this study adopted the fuzzy logic, a method that had been develop to reflect the fuzzy nature of human mind. Being the first in adopting a fuzzy logic in this context, this research find quality of care and physician competence were the top two value aspects perceived by patients. This was consistent with previous studies, yet some new insights were further revealed. This study used a closeness index to distinguish the best hospital that was otherwise assessed by other methods as similar to the rivalries. Results also indicated that the hospital with superior operation performance was the one received better levels of patients‟ perceived value. The research brought several managerial implications, particularly in the needs of identifying and correcting marketing myopia.

636 Afr. J. Bus. Manage.

Table 2. Contd.

2010 Chung-Hsiung Fang et al.

This study conducts AHP method to develop a managerial competency framework for middle managers in the medical industry. The data collection is from nursing supervisors and top-level executives in medical institutions. Participants are required to make a comparison in importance between two competencies and then comparison results are processed and analyzed. Factors at the first level for selecting middle managers in the medical industry are sorted by importance as follows: personality, plan, manage, professional ability and interpersonal ability, indicating that experts believe that personality and plan are very important to middle managers in the medical industry, most of which are responsible for administrative management. We establish a core competency model for reserve middle-level managers in the medical industry. Reserve cadres can take training courses for administrative management arranged by the Nursing Department and the hospital, in which they can establish their career plans and improve their abilities and the human resource department can also find and train excellent talents.

2008 Astrid Oddershede Herreraa et al.

This paper has presented a practical assessment of an Information and Communication Technology (ICT) network system for health care related services through the scientific MCDM method, the Analytic Hierarchical Process, offering a decision making process based on end user‟s perceptions. The resultant prioritization indicates that efforts should be aimed at improving the QoS of the ICT system in keeping easy access to the network, ubiquity, continuity, and security. It is indispensable to count on better information about the needs, expectations of the users and the services operations, to integrate the economic, welfare, and clinical information. The results of this pilot study may be considered as a starting point for analyzing the performance issues in ICT Health Service Network.

2011 Mehtap Dursun et al.

This paper employs a fuzzy multi-criteria group decision making approach, which is based on the principles of fusion of fuzzy information, 2-tuple linguistic representation model, and technique for order preference by similarity to ideal solution (TOPSIS), to evaluate health-care waste (HCW) treatment alternatives for Istanbul The evaluation of four HCW treatment alternatives for Istanbul using the fuzzy multi-criteria decision making technique yields "Steam sterilization" as the most suitable alternative, which is followed by "Microwave". "Steam sterilization" is the preferred alternative treatment method for Istanbul since it minimizes the impact on the environment and demonstrates a commitment to public health. "Incineration" ranks after "Microwave" due to its high costs, and adverse environmental and health impacts. Although "Landfill" is an economic alternative compared with other alternatives, it should only be used in a limited extent because of its significant drawbacks related to environment and public health. Future research will focus on taking financial limitations of Istanbul Metropolitan Municipality explicitly into consideration.

Herat et al. 637

Defining problem

and Theoretical framework

of research

Review on Process of using organizational excellence

model

Research Definition:Problem: Prioritizing and selection of Improvement projectsObjective: Using DEMATEL – ANP hybrid algorithm approach for selecting improvement projects of organizational excellence model in healthcare sector

Understanding

interrelations in health

care excellence

model using DEMATEL

Modeling (Forming effect matrix and data gathering from contributors of

deployment of excellence in hospitals using focus group)

Deployment of DEMATEL for determining the causal relations between

criteria of excellence model in healthcare sector

Experiences of using health

care excellence model in 23 hospitals of

Iran

Prioritizing improvement projects using ANP

Modeling ( Developing ANP model and Forming Pair-wise Comparison matrix in collaborations with contributors of deployment of health care excellence model in hospitals)

Deployment of ANP for prioritizing 10 improvement projects introduced in criteria of organizational excellence model in healthcare sector

Review on fundamental of excellence

model in healthcare sector

Figure 4. DEMATEL-ANP algorithm.

Table 3. The direct-influence matrix Z.

Criterion Leadership Strategy people Partnership

and resources

Processes, products

and services

Customer results

People results

Society results

Key results

Leadership 0 4 3 3 3 1 2 3 4

Strategy 3 0 4 4 4 2 2 2 4

People 2 2 0 2 4 2 4 1 2

Partnership and resources

1 3 2 0 4 3 2 3 4

Processes, products and services

1 2 3 3 0 4 2 2 3

Customer results 2 2 2 1 3 0 2 2 4

People results 2 1 4 1 1 4 0 2 1

Society results 2 2 1 2 2 1 1 0 2

Key results 3 3 3 3 3 2 2 1 0

elements affect each other. A relationship exists among clusters and the elements within the clusters. These clusters and elements are then introduced to the software, and the evaluation is held by pair wise comparisons. The number of comparisons is related to the connected nodes in each cluster. Priorities obtained from the pair- wise comparison matrix (Table 8), as the shown in Figure 7.

First, the un-weighted super-matrix is constructed after weighting

that matrix with the component matrix, and finally, we obtain the limit super-matrix, represented as follows: The un-weighted, weighted and limit super-matrix for this model is shown in Tables 9, 10 and 11, respectively. Limit super matrix shown in Table 11 is obtained from the weighted super matrix by raising it to powers until it converges and shows the importance weights of sub factors, factors and alternatives. All columns in this limiting super matrix are

638 Afr. J. Bus. Manage.

Table 4. The normalized direct-relation matrix X.

Criterion Leadership Strategy people Partnership

and resources

Processes, products

and services

Customer results

People results

Society results

Key results

Leadership 0 0.16 0.12 0.12 0.12 0.04 0.08 0.12 0.16

Strategy 0.12 0 0.16 0.16 0.16 0.08 0.08 0.08 0.16

People 0.08 0.08 0 0.08 0.16 0.08 0.16 0.04 0.08

Partnership and resources

0.04 0.12 0.08 0 0.16 0.12 0.08 0.12 0.16

Processes, products and services

0.04 0.08 0.12 0.12 0 0.16 0.08 0.08 0.12

Customer results 0.08 0.08 0.08 0.04 0.12 0 0.08 0.08 0.16

People results 0.08 0.04 0.16 0.04 0.04 0.16 0 0.08 0.04

Society results 0.08 0.08 0.04 0.08 0.08 0.04 0.04 0 0.08

Key results 0.12 0.12 0.12 0.12 0.12 0.08 0.08 0.04 0

Table 5. The total-influence matrix T.

Criterion Leadership Strategy people Partnership

and resources

Processes, products and

services

Customer results

People results

Society results

Key results

Leadership 0.321 0.51632 0.5398 0.4932 0.5795 0.4211 0.4178 0.418 0.6032

Strategy 0.4496 0.40517 0.6049 0.5522 0.65 0.4883 0.448 0.409 0.6403

People 0.33368 0.37629 0.3593 0.3822 0.5214 0.3976 0.4262 0.296 0.4504

Partnership and resources

0.34032 0.45604 0.4775 0.357 0.5802 0.469 0.3945 0.398 0.575

Processes, products and services

0.31329 0.39196 0.4741 0.4281 0.4037 0.471 0.3705 0.339 0.505

Customer results

0.32654 0.36706 0.4136 0.339 0.4735 0.2997 0.3434 0.315 0.502

People results 0.29215 0.29192 0.4325 0.2905 0.3603 0.4002 0.2397 0.285 0.3542

Society results 0.26331 0.29834 0.2955 0.3028 0.3536 0.2652 0.2415 0.186 0.3514

Key results 0.39097 0.44215 0.4942 0.448 0.529 0.4162 0.3832 0.319 0.4154

Table 6. The sum of influences given and received on criteria.

Criterion D R D + R D - R

Leadership 4.31008 3.03085 7.3409 1.2792

Strategy 4.64799 3.54526 8.1932 1.1027

People 3.54309 4.09145 7.6345 -0.548

Partnership and resources 4.04743 3.59302 7.6404 0.4544

Processes, products and services 3.6968 4.45133 8.1481 -0.755

Customer results 3.38001 3.62831 7.0083 -0.248

People results 2.94635 3.26491 6.2113 -0.319

Society results 2.55799 2.96558 5.5236 -0.408

Key results 3.83788 4.39691 8.2348 -0.559

Herat et al. 639

Leadership

Key results

Society Results

People Results

Customer Results

Strategy

people

processes, products

and services

Partnerships & Resources

Figure 5. Network relationship map based on the threshold value p = 0.407.

Leadership

key results

Society Results

People Results

Customer results

Strategy

People

processes, products

and services

Partnerships & Resources

Selection of improvement projects

2 3 4 5 61 7 8 9 10

Level 1.Goal

Level 2.Criteria

Level 3.Alternatives

Figure 6. The network structure of the proposed model.

640 Afr. J. Bus. Manage. Table 7. Name of alternatives (projects).

S/No. Name of alternative

1 Design and implementation of employee performance management system

2 Design and implementation of macro-level performance management system

3 Design and implementation of mechanisms for periodic monitoring of aberrations to improve its budgeting and planning

4 Design and implementation of systems and equipment maintenance and calibration of measuring instruments

5 Designing and implementing a patient relationship management System

6 Designing and implementing a process management system (identification, formulation, implementation, measuring, improve)

7 Designing and Implementing a promotion and marketing system to increase bed occupancy rate

8 Formulation, implementation and evaluation of current strategies

9 Leadership development and succession planning

10 Staff surveys and improvement planning in human resources

Table 8. Pair wise comparison matrix improvement projects respect to the leadership.

Leadership 1 2 3 4 5 6 7 8 9 10

1 1/5 2 4 1 2 5 1/5 1/5 1/2

2 5 7 3 3 7 1 1/3 5

3 3 1 1/2 5 1/5 1/7 1/2

4 1/5 1/5 1/2 1/6 1/7 1/4

5 1 3 1/7 1/6 1

6 5 1/4 1/5 1

7 1/7 1/7 1/4

8 1/3 5

9 5

10

Figure 7. Leadership‟s priorities relative to alternatives.

Herat et al. 641

Table 9. Un-weighted super-matrix.

Design~ Designing~ Formula~ Leaders~ Staff ~ Leaders~ Partner~ People~ Process~ Strategy~ Customer~ Key~ People~ Society~

Design~ 0 0 0 0 0 0 0 0 0 0 0.06145 0.10655 0.1991 0.04104 0.02515 0.04317 0.07515 0.13639 0.04142

Design~ 0 0 0 0 0 0 0 0 0 0 0.17819 0.18338 0.09396 0.21853 0.11483 0.08772 0.16692 0.07383 0.10002

Design~ 0 0 0 0 0 0 0 0 0 0 0.04293 0.06759 0.03767 0.07935 0.02464 0.03146 0.07493 0.02764 0.02471

Design~ 0 0 0 0 0 0 0 0 0 0 0.01837 0.05341 0.01748 0.02126 0.05169 0.02708 0.01529 0.01799 0.01785

Designing~ 0 0 0 0 0 0 0 0 0 0 0.05289 0.02379 0.02447 0.04287 0.15351 0.20239 0.11438 0.03226 0.13108

Designing~ 0 0 0 0 0 0 0 0 0 0 0.06072 0.06449 0.06637 0.09001 0.10855 0.10405 0.03618 0.05663 0.07125

Designing~ 0 0 0 0 0 0 0 0 0 0 0.02041 0.03089 0.01957 0.03136 0.09617 0.07683 0.05747 0.02119 0.09359

formula~ 0 0 0 0 0 0 0 0 0 0 0.20167 0.2116 0.11822 0.21853 0.19888 0.19839 0.18183 0.18079 0.20397

Leaders~ 0 0 0 0 0 0 0 0 0 0 0.30084 0.1718 0.15009 0.20637 0.19911 0.18524 0.194 0.25285 0.25085

Staff ~ 0 0 0 0 0 0 0 0 0 0 0.06253 0.0865 0.27308 0.05068 0.02748 0.04368 0.08387 0.20043 0.06525

Leaders~ 0 0 0 0 0 0 0 0 0 0 0 0 0 0.53895 0 0 0 0 0

Partner~ 0 0 0 0 0 0 0 0 0 0 0.09821 0 0 0.09304 0.24998 0 0.09821 0 0

People~ 0 0 0 0 0 0 0 0 0 0 0.29464 0.32748 0 0.184 0.75002 0 0.29464 1 0

Process~ 0 0 0 0 0 0 0 0 0 0 0.25075 0.4126 1 0.184 0 1 0.25076 0 0

Strategy~ 0 0 0 0 0 0 0 0 0 0 0.3564 0.25992 0 0 0 0 0.35639 0 0

Customer~ 0 0 0 0 0 0 0 0 0 0 0.364 0.5 0 0.364 0.5 0 0.5 0 0

Key~ 0 0 0 0 0 0 0 0 0 0 0.37453 0.5 0.66667 0.37453 0.5 1 0.5 0 0

People~ 0 0 0 0 0 0 0 0 0 0 0.21884 0 0.33333 0.21884 0 0 0 0 0

Society~ 0 0 0 0 0 0 0 0 0 0 0.04263 0 0 0.04263 0 0 0 0 0

identical.

FINDINGS

Finally, we obtained a score of projects, which are represented by raw values, from the limit super-matrix table. To get normal values, raw values are summed up and every row in raw column is divided by the sum. To obtain ideal values, every value in raw values column is divided by the greatest value of the column. The final ranking of the projects is presented in Figure 8.

It can be clearly seen that project number nine “leadership development and succession planning” has the best score and can be said that it is the most suitable project and followed by projects 8, 2, 5, 10, 1, 6, 7, 3, 4.

The findings based on Table 6 indicated that,

key results is the most important criterion while society results is the least important criterion. Key results criterion is a criterion in which the outcome of all the efforts of the organization (hospital) is presented. At hospitals, this criterion includes important financial issues (total revenue, financial resources absorbed through organizational or individual aids, the income from foreign heath tourism, operational revenue from diagnosis and treatment units such as laboratory, photography, endoscopy, drugstore, operation rooms, etc) and nonfinancial indexes (net mortality rate, infection rate, bed circulation, combination of accepted patients, number of surgeries, waiting time for emergency hospital services, etc). In other words, this criterion is the most important issue that the organization deals with. Furthermore, leadership has highest d - r and it is the most direct

effectiveness to others. When enablers are the cause of the results, stimulant leadership is enabling and in fact is the first cause.

In the organizational excellence model, leaders determine the organizational vision and prepare suitable inputs for strategic criterion and create required management systems for implementing strategies in the fields of people, partnership and resources, processes, products and services and also monitor organizational performance in the fields of customer results, people results, and society results. Another important criterion which has the greatest effect on the model is the strategy criterion. After receiving the vision from the leaders, the strategy criterion develops the strategy and this means that it determines strategies of other fields as operational strategies. Strategy criterion is responsible for fulfilling

642 Afr. J. Bus. Manage.

Table 10. Weighted super-matrix.

Design~ Designing~ Formula~ Leaders~ Staff ~ Leaders~ Partner~ People~ Process~ Strategy~ Customer~ Key~ People~ Society~

Design~ 0 0 0 0 0 0 0 0 0 0 0.02049 0.03552 0.06637 0.01368 0.00838 0.01328 0.02312 0.07794 0.04142

Design~ 0 0 0 0 0 0 0 0 0 0 0.0594 0.06113 0.03132 0.07284 0.03828 0.02699 0.05136 0.04219 0.10002

Design~ 0 0 0 0 0 0 0 0 0 0 0.01431 0.02253 0.01256 0.02645 0.00821 0.00968 0.02305 0.01579 0.02471

Design~ 0 0 0 0 0 0 0 0 0 0 0.00612 0.0178 0.00583 0.00709 0.01723 0.00833 0.0047 0.01028 0.01785

Designing~ 0 0 0 0 0 0 0 0 0 0 0.01763 0.00793 0.00816 0.01429 0.05117 0.06227 0.03519 0.01843 0.13108

Designing~ 0 0 0 0 0 0 0 0 0 0 0.02024 0.0215 0.02212 0.03 0.03618 0.03202 0.01113 0.03236 0.07125

Designing~ 0 0 0 0 0 0 0 0 0 0 0.0068 0.0103 0.00652 0.01045 0.03206 0.02364 0.01768 0.01211 0.09359

formula~ 0 0 0 0 0 0 0 0 0 0 0.06722 0.07054 0.03941 0.07284 0.06629 0.06104 0.05595 0.1033 0.20397

Leaders~ 0 0 0 0 0 0 0 0 0 0 0.10028 0.05727 0.05003 0.06879 0.06637 0.057 0.05969 0.14449 0.25085

Staff ~ 0 0 0 0 0 0 0 0 0 0 0.02084 0.02883 0.09103 0.01689 0.00916 0.01344 0.02581 0.11453 0.06525

Leaders~ 0 0 0 0 0 0 0 0 0 0 0 0 0 0.17965 0 0 0 0 0

Partner~ 0 0 0 0 0 0 0 0 0 0 0.03274 0 0 0.03101 0.08333 0 0.02267 0 0

People~ 0 0 0 0 0 0 0 0 0 0 0.09821 0.10916 0 0.06134 0.25001 0 0.068 0.42858 0

Process~ 0 0 0 0 0 0 0 0 0 0 0.08359 0.13753 0.33333 0.06134 0 0.23077 0.05787 0 0

Strategy~ 0 0 0 0 0 0 0 0 0 0 0.1188 0.08664 0 0 0 0 0.08225 0 0

Customer~ 0 0 0 0 0 0 0 0 0 0 0.12134 0.16667 0 0.12134 0.16667 0 0.23077 0 0

Key~ 0 0 0 0 0 0 0 0 0 0 0.12484 0.16667 0.22222 0.12484 0.16667 0.46153 0.23077 0 0

People~ 0 0 0 0 0 0 0 0 0 0 0.07294 0 0.11111 0.07294 0 0 0 0 0

Society~ 0 0 0 0 0 0 0 0 0 0 0.01421 0 0 0.01421 0 0 0 0 0

Table 11. Limit super-matrix.

Design~ Designing~ Formula~ Leaders~ Staff ~ Leaders~ Partner~ People~ Process~ Strategy~ Customer~ Key~ People~ Society~

Design~ 0 0 0 0 0 0 0 0 0 0 0.02601 0.02601 0.02601 0.02601 0.02601 0.02601 0.02601 0.02601 0

Design~ 0 0 0 0 0 0 0 0 0 0 0.04311 0.04311 0.04311 0.04311 0.04311 0.04311 0.04311 0.04311 0

Design~ 0 0 0 0 0 0 0 0 0 0 0.0163 0.0163 0.0163 0.0163 0.0163 0.0163 0.0163 0.0163 0

Design~ 0 0 0 0 0 0 0 0 0 0 0.00857 0.00857 0.00857 0.00857 0.00857 0.00857 0.00857 0.00857 0

Designing~ 0 0 0 0 0 0 0 0 0 0 0.03684 0.03684 0.03684 0.03684 0.03684 0.03684 0.03684 0.03684 0

Designing~ 0 0 0 0 0 0 0 0 0 0 0.02321 0.02321 0.02321 0.02321 0.02321 0.02321 0.02321 0.02321 0

Designing~ 0 0 0 0 0 0 0 0 0 0 0.01901 0.01901 0.01901 0.01901 0.01901 0.01901 0.01901 0.01901 0

formula~ 0 0 0 0 0 0 0 0 0 0 0.0597 0.0597 0.0597 0.0597 0.0597 0.0597 0.0597 0.0597 0

Leaders~ 0 0 0 0 0 0 0 0 0 0 0.06276 0.06276 0.06276 0.06276 0.06276 0.06276 0.06276 0.06276 0

Staff ~ 0 0 0 0 0 0 0 0 0 0 0.03148 0.03148 0.03148 0.03148 0.03148 0.03148 0.03148 0.03148 0

Leaders~ 0 0 0 0 0 0 0 0 0 0 0.00932 0.00932 0.00932 0.00932 0.00932 0.00932 0.00932 0.00932 0

Partner~ 0 0 0 0 0 0 0 0 0 0 0.02509 0.02509 0.02509 0.02509 0.02509 0.02509 0.02509 0.02509 0

People~ 0 0 0 0 0 0 0 0 0 0 0.09024 0.09024 0.09024 0.09024 0.09024 0.09024 0.09024 0.09024 0

Herat et al. 643

Table 11. Contd.

Process~ 0 0 0 0 0 0 0 0 0 0 0.11916 0.11916 0.11916 0.11916 0.11916 0.11916 0.11916 0.11916 0

Strategy~ 0 0 0 0 0 0 0 0 0 0 0.0349 0.0349 0.0349 0.0349 0.0349 0.0349 0.0349 0.0349 0

Customer~ 0 0 0 0 0 0 0 0 0 0 0.12795 0.12795 0.12795 0.12795 0.12795 0.12795 0.12795 0.12795 0

Key~ 0 0 0 0 0 0 0 0 0 0 0.24572 0.24572 0.24572 0.24572 0.24572 0.24572 0.24572 0.24572 0

People~ 0 0 0 0 0 0 0 0 0 0 0.01969 0.01969 0.01969 0.01969 0.01969 0.01969 0.01969 0.01969 0

Society~ 0 0 0 0 0 0 0 0 0 0 0.00093 0.00093 0.00093 0.00093 0.00093 0.00093 0.00093 0.00093 0

Figure 8. The results of the proposed model.

644 Afr. J. Bus. Manage. the vision and gaining excellent key results. This criterion plays an important role in directing all criteria especially gaining key results.

Overall, the findings of this study increase the insight of managers about the effects of excellence component in order to lead their efforts to successful implementation. In summary, should pay much attention to causes rather than receivers. At the end, it should be mentioned that the findings should be interpreted with caution due to the sample includes hospitals which are the subsets of health sector in Iran. Studies in other countries should be conducted to ensure the reliability of the results obtained. Despite this limitation, however, the study does shed light on a very important issue, the study of the cause and affect relationships between criteria of the EFQM model. CONCLUSION

In conclusion, EFQM organization excellence model is the most important approach for organizational diagnosis, and it is a practical tool that can be used as a guideline to identify areas for improvement. In this article based on experienced gained in hospitals, we could draw the causal relations between nine areas of healthcare orga-nization excellence model using DEMATEL mathematical model and determine their effects on each other. Then based on these causal relations, we ranked the improve-ment projects using ANP model. According to Table 6, leadership has highest d - r and it is the most direct effectiveness to others and also key results are net receiver based on (d - r) values. Sadeh et al. (2010) showed the similar results. Finally, project number seven “leadership development and succession planning” got the highest score and it is the most appropriate choice and followed by projects 8, 2, 5, 10, 1, 6, 7, 3, 4.

There were some limitations in this research project. For example, Iranian excellence model in healthcare sector has been implemented in 23 hospitals and there-fore the number of improvement projects was limited. If the model were implemented in more hospitals, the results were probably more accurate. Another limitation, were the direct-influence matrix (Table 3) and pair wise comparison matrix improvement projects respect to the criteria built based on the thoughts, comments, and suggestions of 15 experts. If these matrixes were built using more experts, the results were probably more accurate.

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