ascarya wp the persistence of low pls financing in ib
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THE PERSISTENCE OF LOW PROFIT‐AND‐LOSS SHARING FINANCING
IN ISLAMIC BANKING: THE CASE OF INDONESIA
A s c a r y a
Center for Central Banking and Education Studies, Bank Indonesia Jl. MH Thamrin No.2, Sjafruddin Prawiranegara Tower, 20th fl., Jakarta 10350, Indonesia
Email: ascarya@bi.go.id; Phone: +6221.381.7345; Fax: +6221.350.1912
ABSTRACT
Low profit‐and‐loss sharing (PLS) financing in Islamic banking has become a classic problem which has not been given proportional attention by practitioners as well as academicians. This study analyzes the problems of persistence low PLS financing in Indonesia’s Islamic banking and proposes alternative solutions using Analytic Network Process (ANP) method. The root causes of low PLS financing can be grouped into three aspects, namely 1) Internal problems, which include upper management, human resources and technical aspects; 2) System conditions, which include conventional bank domination, unsupportive environment and competition; and 3) Externalities which include society, the authorities and customers. The results show that the primary problems come from: 1) Authority (External); 2) Top Management (Internal); 3) Customer (External); 4) Unsupportive Environment (System); and 5) Conventional Domination (System). In more detail, the primary problems are: 1) Lack of Knowledge of the Customer; 2) Lack of Commitment of the Authority; 3) Value in the Environment; 4) Business Oriented of the Top Management; and 5) Conventional Competition on Products. The primary solutions are: 1) Customer Education; 2) Top Management Commitment; 3) Protocol and Grand Strategy; 4) Law and Regulation; and 5) Government Commitment. Meanwhile, policies and strategies that should be prioritized are: 1) Product Development; 2) Fair Treatment; 3) Service Improvement; 4) Market Mapping; and 5) Professionalism. Furthermore, the levels of agreements among respondents (Kendall’s W) are generally low, with Islamic bankers show higher rater agreement than that of Experts. However, the priority of choices shows greater agreement among respondents, especially among Islamic bankers. JEL Classification: C14, G21, G28 Keywords: ANP, Islamic Banking, Profit‐and‐Loss Sharing
Working Paper, Center for Central Banking Education and Studies, Bank Indonesia, 2011.
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1. INTRODUCTION
1.1 Background
Historically, Islamic banking is banking which is free from interest or riba, so that it is also called interest‐free banking. Conceptually, Islamic banking is not only free from riba, but also free from maysir (excessive speculation or gambling) and gharar (unclear transaction). Furthermore, the way Islamic banking operates, instead of using interest system, it applies trade financing and investment financing. Islamic banks are expected to engage in these activities only on a profit‐and‐loss sharing (PLS) basis. This is where Islamic banks’ main income is coming from and this is also from where the investment account holders are expected to derive their profits from.
Gafoor (2004) mentions that several writers have attempted to show, with varying degrees of success, that Islamic Banking based on the concept of profit and loss sharing (PLS) is theoretically superior to conventional banking from different angles. See, for example, Khan and Mirakhor (1987). However from the practical point of view things do not seem that rosy. In the over half‐a‐decade of full‐scale experience in implementing the PLS scheme the problems have begun to show up. Consequently, the rapid development of Islamic banking all over the world has been depended on alternative modes of financing other than PLS financing; especially trade financing using murabahah mode of finance and its derivatives.
With no exception, Islamic banking in Indonesia has also been developed rapidly (but also with low PLS financing) since the government and Bank Indonesia (the central bank of Indonesia) committed to expand Islamic banking more seriously through supporting policies, especially ever since the amendment of Banking Regulation no. 10 of 1998.
In 2000, there were two Islamic banks and three Islamic branches with only 65 offices and 0.17% share of total assets. While, at the end of 2010 there were 11 Islamic banks and 23 Islamic Business Units (of conventional banks) with the total of 1477 offices and 1277 counters of office channeling in conventional banks. Share of total assets has reached 3.24% or Rp.97.52 trillion with 48% annual growth (see figure 1.1).
Figure 1.1 Growth of Islamic Banking in Indonesia
2 3 48
1521
27
37
50
66
98
1 2 3 612
1621
28
37
52
76
1 2 3 611
1520
28
38
47
68
52% 49%
94% 95%
36%28%
37% 36% 33%
48%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Assets Deposits Financing Assets Growth
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The growth of Islamic banking in Indonesia can also be shown from deposits collected and financing extended. In 2000, deposits was Rp.1.03 trillion and financing extended was Rp.1.27 trillion, with 123.3% FDR (financing to deposit ratio). At the end of 2010, deposits grew 45.47% a year and reached Rp.76.04 trillions, while financing extended grew 45.42% a year and reached Rp.66.18 trillions, with 89.67% FDR. This FDR figure was a great achievement compared to Islamic banks in other countries, and it was far beyond LDR (loan to deposit ratio) of conventional banks in Indonesia, which reached only 75.21%.
Nevertheless, at the end of 2010, the portfolio of financing comprised of 21.4% musharakah, 12.7% mudharabah, 55.0% murabahah, and 10.9% other modes of financing (see figure 1.2). This portfolio showed the domination of non profit‐and‐loss (PLS) financing (65.9%), particularly murabahah. Meanwhile, the share of PLS financing (mudharabah and musharakah) was only 34.1%, even though PLS financing is not only the essence of Islamic financing but also more appropriate modes of financing to stimulate the real sector, to stabilize financial system and to curb inflation, since it can improve direct interaction and risk sharing between investor and entrepreneur. Nevertheless, the figure of PLS financing in Indonesia has always been far better than those of neighboring countries, like Malaysia and Pakistan.
Figure 1.2 Financing Portfolio of Islamic Banks
Figure 1.2 shows the persistence of low PLS financing and high trade financing in Indonesia’s Islamic banking, with some increasing PLS financing trend up to year 2009 and slight decreasing trend afterward. Mudharabah PLS mode of finance has been declining since year 2006, while musharakah PLS mode of finance has been increasing since the same year. Moreover, murabahah non‐PLS mode of finance has also been slightly declining overtime. New modes of finance have decreasing trend since year 2002, and have been increasing again in application since year 2008, and have reached 10.9 percent at the end of 2010.
The never‐ending issue of low PLS financing in Islamic banking has always been an important subject to be discussed, even though new studies on this issue have been very limited. It seems that current conduct of Islamic banking with minimum application of PLS financing has been generally accepted by the majority of stakeholders. The implication of the domination of non‐PLS financing brings the public to perceive that Islamic banking is almost
15.2 14.4 18.0 20.5 19.9 20.0 16.2 14.1 12.7
1.8 5.511.1 12.5 11.4 15.8 19.4 22.2 21.4
70.9 71.566.5 62.3 61.7 59.2 58.9 55.9 55.0
12.0 8.6 4.5 4.7 7.0 5.0 5.5 7.8 10.9
2002 2003 2004 2005 2006 2007 2008 2009 2010
Mudharabah Musharakah Murabahah Others
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no different from conventional banking. This perception could form a reputation risk to Islamic banking that could create cynicism in public that Islamic banking is just only a re‐branding, while the mind‐set of the bankers are still conventional. The problem of implementing PLS financing becomes even more acute in countries with dual banking system, such as Egypt, Bangladesh, Pakistan, Malaysia, as well as Indonesia.
The low implementation of PLS financing clearly is not the expected ideal. Islamic banking industry, the government, as well as the central bank, must strive to improve the system and infrastructure and to find appropriate solutions to promote PLS financing. Even though the problems of implementing PLS financing in Islamic banking tend to be complex and multi dimensional, they have to be identified, so that alternative gradual and systemic solutions can be proposed, so that the development of Islamic banking can be redirected towards its natural character.
1.2 Objectives
The objectives of this study is to identify factors causing the low implementation of PLS financing in Indonesia’s Islamic banking and to find alternative solutions, as well as to determine gradual and systemic policies and strategies to stimulate and improve the implementation of PLS financing in Indonesia’s Islamic banking, so that related stakeholders such as Islamic banking industry, investor, entrepreneur, Bank Indonesia, and the government can take appropriate policy actions to deal with the current problems and attain the expected goals of strong and sound Islamic banking.
1.3 Methodology
This study will apply Analytic Network Process (ANP) method with three steps. First, focus group discussion (FGD) and in‐depth interview will be conducted with various stakeholders, such as scholars, experts, practitioners, customers, and regulators of Islamic banking, to fully understand the real problems and to identify factors affecting low implementation of PLS financing. Second, the results of the first steps will be used to develop an appropriate ANP network and its questionnaires to obtain proper data from experts and practitioners of Islamic banking. Third, ANP analysis will be applied to set priority on alternative solutions as well as policies and strategies to formulate optimal policy recommendations.
2. LITERATUR REVIEW
The raison d’être of Islamic economics, finance and banking is derived from the Islamic injunction against riba (interest), maysir (excessive risk or gambling) and gharar (unclear transaction). In banking operation, Islam prohibits interest on deposits taking and loans or financing extension regardless of their nature or purpose. As replacements, Islamic bank provides various deposit products and financing products which are based on various modes of finance. Among those various modes of finance, conceptually, profit‐and‐loss sharing (PLS) is the prime mode of finance, represented by mudharabah and musharakah modes of finance, which are also termed as equity‐based finance or PLS modes of finance.
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2.1 Profit‐and‐Loss Sharing
The most important modes of finance agreed by Muslim scholars are PLS modes of finance, namely, mudharabah (trustee profit sharing) and musharakah (joint venture profit sharing), that embed the principle of al‐ghunm bi’l‐ghurm or al‐kharãj bi’l‐damãn, meaning that there is no return without involvement in risk (Al‐Omar and Abdel‐Haq, 1996), or for every real economic benefit there must be real economic cost (Khan, 1995). According to Shiddiqi in Karim (2002), the issues of PLS and partnership have been discussed by Muhammad bin Hasan Al Syaibani (132‐189 AH/750‐804 AD).
Ahmad (20xx) mentions that according to theoretical models developed by Muslim economists, Islamic banking based on the principle of PLS modes of finance claims to be superior to interest‐based commercial banking in terms of equity, efficiency, stability and growth. In comparison with other financial systems, Islamic banking will be more just because the contract of PLS modes of finance is based on the principles of justice and equity. It will be more efficient as it will help attain a more rational and balanced allocation of financial resources among the competing projects because the main consideration in the allocation of funds under Islamic banking would be the profitability of relevant projects and not the safe return of the principal amount as in the case of conventional banking.
Mudharabah is a mode of financing based on trustee partnership for a specific venture in which the bank provides capital finance and the customer‐entrepreneur provides managerial and professional skills to operate the business project. Profits are shared in the pre‐agreed ratio, while losses are entirely absorbed by the bank if the client is not negligent or in violation of the terms. Mudharabah can cover one deal, several deals, or a specified period of time up to a specified ceiling.
Figure 2.1 Mudharabah Mode of Finance
The Practical steps of Mudharabah are as follows:
1. Establishing a Mudharabah project. The bank provides the capital as a capital owner or Shahibul Maal, while the customer as Mudharib (entrepreneur) provides his effort and expertise for the investment of capital in exchange for a share in profit agreed upon.
THE PROJECT
BANK
SHAHIBUL MAAL
CUSTOMER
MUDHARIB
CAPITAL 100% SKILL 100%
PROFITS
Mudharabah
Contract
CAPITAL
Share of Profits Y
Capital 100%
Share of Profits X
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2. The results of Mudharabah. The two parties calculate the earnings and divide profits at the end of Mudharabah. This can also be done periodically in accordance with the agreement and legal compliance.
3. Payment of Mudharabah capital. The bank: Recovers the Mudharabah capital it contributed before dividing the profits between the two parties because profit is protection to capital. In case of agreement to distribute profits periodically before the final settlement it must be on account until the security of capital is assured.
4. Distribution of wealth resulting from Mudharabah.
In case of loss, the capital owner (the bank) bears the loss.
Profits are divided between the two parties in accordance with the agreement between them with observance to the principle "profit is protection to capital".
Mudharabah mode of financing is considered to be an important mode by the Islamic banks in their relationship with the depositors who tender their moneys to the bank as capital owner. This money is invested by the bank as Mudharib on the basis of profit sharing according to specific pre‐agreed rates. The Islamic banks use this product to finance capable professionals such as physicians, engineers, traders or craftsmen. The bank provides required finance as a capital owner in exchange for a share in the profit to be agreed upon. It is worth noting that this mode carries high risk for the bank because the bank delivers capital to the Mudharib who undertakes the work and management and the Mudharib is held responsible for loss only in case of negligence. The Islamic banks take necessary precautions to minimize risk and to ensure better execution of Mudharabah transaction.
Musharakah is a mode of financing based on joint venture partnership in which both the bank and its customer‐client contribute to entrepreneurship and capital. Profits are shared in the pre‐agreed ratio, while losses are shared in proportion to their capital contributions. This mode of finance is represented in the contribution of partners to equal or unequal ratios of capital to establish a new project or to participate in an established one, whereby each participant owns a share in the capital permanently and deserves his share of the profit. The partnership originally is intended to continue up to the dissolution of the company. It is possible that for one reason or another, one of the partners sells its share in the capital to withdraw from the project. The Islamic banks use the mode of partnership in many projects. They finance their customers with part of the capital in exchange of a share of the output as they may agree upon. Mostly they leave the responsibility of management to the customer partner and retain the right of supervision and follow up.
The practical steps of Musharakah are as follows:
1. Partnership in Capital. The bank tenders part of the capital required in its capacity as a partner and authorizes the customer / partner to manage the project, while the partner (customer) tenders part of the capital required for the project and becomes the trustee for bank's funds.
2. Results of the project. The work in the project is for the growth of capital. The project may achieve positive or negative results.
3. Distribution of wealth accrued from the project. In case of loss, each partner bears part of the loss proportionate to its share in capital. Profit is divided between the two parties (the bank and the partner) in accordance with the agreement.
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Figure 2.2 Musharakah Mode of Finance
Musharakah mode of financing or partnership is considered to be an appropriate mode for collective investment in modern economic life. The Islamic banks use partnership by contributing capital to new or established projects. They also bear part of the cost of a project in the ratios of their shares in capital. The Islamic banks by using partnership as a mode of investment make sufficient liquidity available to the customer for a long period. The Islamic banks are usually active partners and participate in determining the methods of production and the objectives of the establishment. They also supervise and follow up the performance of the establishment. The Islamic banks share profit or loss with the customer (partner) without burdening the customer with debt or any financial liabilities which the customer has to pay under all circumstances.
PLS modes of finance have been proven theoretically superior to other modes of finance in generating macro‐economic benefits. Some empirical studies have also been done to prove this superiority for the case of Indonesia.
Ryandono (2006) compares interest system and PLS system. He concludes that interest (riba) system has negative relationship with the economy and causes money turn over becomes ineffective and inefficient at macro and micro levels that subsequently will cause instability in the economy. Interest (riba) system can also impede investment and economic growth. Thus, it is difficult to synchronize monetary sector and real sector, since the two sides have different interests and objectives in the economy which is difficult to settle. In contrast, PLS system has positive relationship with the economy and causes money turnover becomes effective and efficient at macro and micro levels that subsequently will cause stability in the economy. PLS system can also stimulate investment and economic growth. Thus, it will synchronize monetary sector and real sector, since the two sides have similar interests and objectives in the economy.
Ascarya, et al. (2008b) tries to compare demand for money and monetary stability under dual monetary system. The results show that demand for money in Islamic system is more stable in response to the shock of other variables than that of demand for money in conventional system. Conventional demand for money shows the behavior for transaction and investment, while Islamic demand for money shows the behavior for transaction only. Moreover, PLS system outperforms interest system in terms of efficiency, fairness, and
THE PROJECT
BANK
PARTNER
CUSTOMER
PARTNER
CAPITAL&SKILL CAPITAL&SKILL
PROFITS
Musharakah
Contract
CAPITAL
Share of Profits Y
Share of Capital X
Share of Profits X
Share of Capital Y
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stability. Therefore, PLS return can be used as an alternative to interest rate as a monetary policy instrument.
Ascarya (2009) tries to investigate the determinants of Inflation under dual monetary system in Indonesia. The result shows that the main sources of inflation (78.1%) in conventional economic/financial system are interest rate (54.7%) and fiat money (23.4%). When these two main pillars of conventional economic/financial system are replaced by PLS and gold standard, they only affect inflation by 2.9% and 0.5%, respectively. This means that the implementation of PLS system to replace interest system will reduce 51.8 percent share of inflation in Indonesia.
Furthermore, Ascarya and Yumanita (2009) tries to compare the financial stability under conventional and Islamic financial systems. The results show that although its share is still small, Islamic banking has given positive impact to Indonesian financial system as a whole in terms of financial stability. The study finds that Islamic FSI (Financial Stability Index) is more stable than Conventional FSI. Moreover, Islamic FSI influences the stability of Conventional FSI to the better, while Conventional FSI does not influence Islamic FSI.
2.2 Previous Studies
Although PLS financing has been proven theoretically and empirically superior to other modes of financing to macro‐economic conditions, from practical point of views things do not seem that promising.
The earliest study by Khan (1995) has mentioned aversion to risk from Islamic bankers, as well as moral hazard due to asymmetric information from customers as the main causes why PLS financing is not popular. Other scholars, such as Dar and Presley (2000), Chapra (2000), Algoud and Lewis (2001), Muljawan (2001), Al Jarhi (2002), Iqbal and Llewellyn (2002) and Parinduri (2003), agree with these main problems with the addition of adverse selection due to asymmetric information from Islamic bankers. In addition, Sarker (1999) divides the lack of PLS financing problem of Islamic banking into several macro and micro operations. Macro operation include: a) there is no uniform opinions on the Shariah jurisprudence; b) lack of skilled and expert human resources in Islamic banking and Shariah; c) fierce competition in financial sector; and d) lack of uniform operational procedures. While, micro operations include: a) increase cost of information; b) not ready to handle higher risk; c) lack of Shariah manual; d) lack of methodology to analyze and measure investment risk Islamicly; d) unsupportive tax regulation; and e) lack of Shariah management manual.
Meanwhile, the main study of the lack of PLS financing in Indonesia’s Islamic banking has done by Ascarya and Yumanita (2005 and 2006). The problem was grouped into four aspects, namely Islamic bank internalities, customers, regulations, and the Government. The clusters were grouped into problems, alternative solutions, and development strategies. Internal problems include: 1) Lack of understanding of Islamic banking fundamentals; 2) Emphasis on business or profit orientation (business‐oriented); 3) Lack of quality and quantity of human resources; 4) Islamic banks are still averse to efforts; and 5) Islamic banks are still averse to risks. Customer problems include: 1) Lack of understanding of Islamic banking fundamentals; and 2) Customers are still averse to risks. Regulation problems include: 1) Lack of incentives to stimulate PLS financing; and 2) Lack of supportive
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regulations. Meanwhile, government problem is lack of government commitment and support.
Some of these earlier lacks of PLS financing problems have been resolved in Indonesia, such as fatwas (legal Shariah opinion) on PLS financing, equal tax treatment Act, Islamic Banking Act, and Sukuk Act. However, fundamental problems still remain, such as asymmetric information (moral hazard, adverse selection, and increased costs) and lack of human resource. Moreover, dynamic development of Islamic banking also generates new problems (or previously unseen problems).
After the study by Ascarya and Yumanita (2005 and 2006), there are only a few new studies on the lack of PLS financing, lately. Gafoor (2004) states that there are four main areas where the Islamic banks find it difficult to finance under the PLS scheme: a) participating in long‐term low‐yield projects, b) financing the small businessman, c) granting non‐participating loans to running businesses, and d) financing government borrowing. IFSB (2005) concludes that the lack of PLS financing is caused by credit risk, equity investment risk, market risk, liquidity risk, rate of return risk, and operational risk. Iqbal and Greuning (2007) study finds that inherent risks, low appetite for risk, monitoring cost, lack of transparency, depositors’ risk aversion, as well as asymmetric information are the causes of low PLS financing. Moreover, Febianto and Kasri (2007) find that lack of risk management is the main cause of the lack of PLS financing.
The study of Ascarya and Yumanita (2005) has been revisited by Ascarya (2009) to see the newest development on lack of PLS financing in Indonesia’s Islamic banking. Comparison of the results can be seen in table 2.1.
Table 2.1 Summary of 2005 and 2009 Results
ASPECTS 2005 STUDY 2009 STUDY
1st 2nd 1st 2nd
Internal Problems
Lack of Quality & Quantity of Human Resource
Averse to Risk Technical: No Management tools; Higher Risk
Top Management: Lack of Commitment; Business Oriented
Internal Solutions
Human Resource Improvement
Technical: IT & SOP Top Management: Commitment
External Problems
Regulation: Lack of Supportive Regulations
Government: Lack of Support
Authority: Lack of Commitment; Lack of Support
Society: Lack of Trust; Lack of Perception
External Solutions
Supportive Regulations
Incentive Authority: Commitment
Society: Communication; Da’wah
Policies Directed Market Driven
Directed Market Driven
Professionalism
Strategies ‐‐ ‐‐ Service
Improvement Socialization & Communication Program
Table 2.1 shows that the problems have shifted and expanded, the priority solutions have also changed, while the priority policies and strategies have also expanded. Nevertheless, the main problem of lack of PLS financing remains.
The newest study and analysis on PLS financing has done by Tarsidin (2010), which views that the determinants of the lack of PLS financing are; a) asymmetric information problems, such as private information, adverse selection, moral hazard type I (disincentive), and moral
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hazard type II (falsification); b) profit function and utility function of capital owner and entrepreneur, c) willingness to pay; d) reservation utility; e) incentive compatibility; and f) participation. Other determinants include risk aversion, financial constraint, length of contract, performance standard, and signal. Based on these constraints he develops optimal scheme (first best and second best) of PLS financing (mudharabah and musharakah), which can be applied by Islamic financial institutions, in static and dynamic environments.
PLS financing or equity financing does not exclusively belong to Islamic finance, but also has long been used and discussed in conventional finance. Stiglitz (1974) states that profit‐and‐loss sharing has been widely adopted in farming sector using sharecropping scheme, where labor will equalize his/her share of output with marginal productivity of labor multiplied by marginal disutility of work. Laffont and Matoussi (1995) develop theory of sharecropping based on moral hazard and financial constraints, as well as risk aversion. Both Stiglitz (1974) as well as Laffont and Matoussi (1995) conclude that sharecropping is a tradeoff between incentive and risk‐sharing.
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3. METHODOLOGY
3.1 Analytic Network Process
3.1.1 Overview
Saaty (1999) defined analytic network process (ANP) as a general theory of relative measurement used to derive composite priority ratio from individual ratio scale reflecting relative measurement of interconnected elements within control criteria. While, Azis (2003) described ANP as a mathematic theory that allows one to deal systematically with dependence and feedback and that can capture and combine tangible and intangible factors by using ratio scale.
ANP is a new approach in decision making process that provides general framework in treating decisions without making any assumption about independency of elements in higher level from elements in lower level and about independency of elements within the same level. Moreover, ANP uses network without having to determine level as in hierarchy used in Analytic Hierarchy Process (AHP), which is a starting point of ANP. The main concept of ANP is influence, while the main concept of AHP is preference. AHP with its dependency assumptions on clusters and elements are a special cases of ANP.
In AHP network, there are levels of goal, criteria, sub criteria, and alternative, where each level has its own elements. Meanwhile, in ANP network, level in AHP is called cluster that can consist of criteria and alternative which now is called node (see figure 3.1)
With the feedback, alternatives can depend on criteria, like in a hierarchy, but it can also depend on other criteria. Furthermore, those criteria themselves can depend on alternatives and other criteria (see figure 3.1). Meanwhile, feedback improves priority which derived from judgment and makes prediction more accurate. Therefore, the result of ANP is expected to be more stable. From feedback network in figure 3.1, it can be seen that the parent node or element and nodes to be compared can be in different clusters. For example, there is a direct link from parent node cluster C4 to the other clusters (C2 and C3), which called outer dependence. Meanwhile, there is parent node and nodes to be compared lie within the same cluster, so that this cluster will be connected with itself and create loop link. This is called inner dependence.
In a network, element of the cluster can be a person (e.g. an individual in Bank of Indonesia) and element in another cluster can be also a person (e.g. an individual in the parliament). Element in one cluster can influence other elements in the same cluster (inner dependence) and can also influence elements in other clusters (outer dependence) with respect to each criteria.
The intended output of ANP is to determine the overall influence from all elements. Therefore, all criteria must be configured and set their priority in a framework of control hierarchy or network. After that, do the comparison and synthesis to obtain the order of priority from these criteria. Then, we derive the influence from element in feedback system with respect to each criterion. Finally, the results of these influences are weighted according to the important level of the criteria, and summed them up to get overall influence from each element.
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Figure 3.1 Comparisons of Hierarchy and Network
Seven AHP pillars can be used as starting point of ANP1. ANP is a combination of two parts. First part consists of control hierarchy or network from criteria and sub criteria that control interaction. The second part is network of influences among elements and clusters.
AHP and ANP utilize ratio scale. Priorities in ratio scales are fundamental number which makes basic arithmetic operation possible, such as addition and subtraction within the same scale, multiplication and division of different scale, and combination of both operations by weighting and adding different scales to obtain unidimensional scale.
It should be noted that ratio scales are also absolute scales. Both of them are derived from pairwise comparisons using judgments or derive from pairwise dominance ratios using actual measurements. When using judgments, in AHP one asks “which one is more preferred or more important?” while in ANP one asks “which one has greater influence?” The second question obviously requires factual observation and knowledge to produce valid answer. This makes the second question more objective than the first one.
3.1.2 Axiom of ANP
Every theory is based on axioms. The simpler and the fewer the axioms, the more general and applicable the theory is. AHP has four (ANP has three) relatively simple axioms which carefully restrict the scope of a problem.
1. Reciprocal. This axiom requires that if PC (EA,EB) is a paired comparison of elements A and B with respect to their parent, element C, representing how many times more the element A possesses a property than does element B, then PC (EB,EA) = 1/ PC (EA,EB). For instance, if A is 4 times larger than B, then B is one forth as large as A.
2. Homogeneity. This axiom states that the elements being compared should not differ by too much, else there will tend to be larger errors in judgment. The verbal scale of ANP ranges from one to nine, or about an order of magnitude (see Table 3.1). Saaty and Vargas (2005) state that According to mathematician and cognitive neuropsychologist Stanislas Dehaene (1997): “introspection suggests that we can mentally represent the meaning of numbers 1 through 9 with actual acuity. Indeed,
1 For more details, see Thomas L. Saaty “The Seven Pillars of the Analytic Hierarchy Process” (2003).
•••••
•••
••••
• Goal
Criteria
Subcriteria
A loop indicates that each element depends only on it self
Component, Cluster (Level)
Element
C3•••
•• C1••
••• C2•
C4••••
Linear Hierarchy Feedback Network
Feedback
Source: Saaty and Vargas (2006)
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these symbols seem equivalent to us. They all seem equally easy to work with, and we feel that we can add or compare any two digits in a small and fixed amount of time like a computer”.
Table 3.1 Comparison of Verbal and Numeric Scales
Verbal Scale Numeric Scale Much More Greater Influence 9
8
Much Greater Influence 7
6
Greater Influence 5
4
Slightly Greater Influence 3
2
Equal Influence 1
3. Hierarchy Structure (not applicable to ANP). This axiom states that judgments about, or the priorities of, the elements in a hierarchy do not depend on lower level elements. This axiom requires the application of hierarchy structure.
4. This axiom states that individuals who have reasons for their beliefs should make sure that their ideas are adequately represented for the outcome to match these expectations.
From the experience, the first two axioms are completely consonant with real world applications, while the third axiom requires careful applications, as it is not uncommon for it to be violated, because (in choice applications, for example) the preference for alternatives is almost always dependent on higher level elements (i.e., the objectives), while the importance of the objectives might be dependent on lower level elements (i.e., the alternatives). When such dependent exists, the third axiom of AHP does not apply. There is feedback from lower level factors to higher level factors in the hierarchy. Supermatrix calculation in ANP accommodates such situation, so that the structure of hierarchy is just a special case of ANP.
Meanwhile, the forth axiom might sound a bit vague. But, it is important since the generality of AHP/ANP makes it possible to apply it in a variety of ways, and the application of this axiom will prevent the application of AHP/ANP in inappropriate ways.
The simpler the theory the more preferable it is in practice. Most practitioners of AHP/ANP feel that AHP/ANP’s axioms are simpler and more realistic than other decision theories. In addition, AHP/ANP is applicable to areas besides choice decisions (such as forecasting and resource allocation) and the ratio scale measures produced by AHP/ANP makes it more powerful than other theories that rely on ordinal or interval measures.
3.1.3 Basic Principles of ANP
There are three related basic principles of AHP/ANP, namely decomposition, comparative judgments, and hierarchic composition or synthesis of priorities (Saaty, 1994).
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1. Decomposition. The principle of decomposition is applied to structure a complex problem into a hierarchy or network of clusters, sub clusters, sub‐sub clusters, and so on. In other words, decomposition tries to model the problem into AHP/ANP framework.
2. Comparative Judgments. The principle of comparative judgments is applied to construct pairwise comparisons of all combinations of elements in a cluster with respect to the parent of the cluster. These pairwise comparisons are used to derive ‘local’ priorities of the elements in a cluster with respect to their parent.
3. Hierarchic Composition or Synthesis. The principle of hierarchic composition or synthesis is applied to multiply the local priorities of the elements in a cluster by the ‘global’ priority of the parent element, producing global priorities throughout the hierarchy or network and then adding the global priorities for the lowest level elements (usually the alternatives).
3.1.4 The Primary Functions of ANP
In line with its basic principles, there are three primary functions of AHP/ANP, namely, structuring complexity, measurement on a ratio scale, and synthesis.
1. Structuring Complexity. AHP/ANP chooses a simple way to deal with complexity. Simple enough so that lay people with no formal training could understand and participate. Saaty found one thing common in numerous examples of the ways humans had dealt with complexity over the ages – that was the hierarchical structuring of complexity into homogeneous clusters of factors previously thought by L.L. Whyte (1969) and Herbert Simon (1972). Structuring complexity includes developing ANP network of the problem. Saaty (undated) states that “One structures a hierarchy from a goal downwards to criteria, sub‐criteria and goals, involving actors and stakeholders and terminating in alternatives at the bottom. The ideas to go gradually from the general to the particular. In a network, elements are put in clusters or components with their connections indicating influence.”
2. Measurement on a Ratio or Absolute Scale. Earlier decision making methodologies relied on lower levels of measurement, while AHP/ANP employs ratio scales measurement that believed to be the most accurately measure the factors that comprised the hierarchy. There are five levels of measurements (scales) ranging from the lowest to the highest, namely Nominal, Ordinal, Interval, Ratio, and Absolute. Each level has all of the meaning of the levels below plus additional meaning. Ratio measure is necessary to represent proportion. To keep the methodology simple, Saaty proposed using judgments of the ratios of each pair of factors in the hierarchy or network to derive (rather than assign) ratio scale measures. Saaty (undated) states that “Comparisons are more scientific in deriving scales because they use a unit and estimate multiples of that unit rather than simply assigning numbers by guessing.”
Any hierarchically structured methodology must use ratio scale priorities for elements above the lowest level of the hierarchy. This is necessary since the priorities (or weights) of the elements at any level of the hierarchy are determined by multiplying the priorities of the elements in that level by the priorities of the parent element. Since the product of two interval level measures is mathematically meaningless, ratio scales are required for this multiplication. The ratio scale, being a higher level of
15
measurement, is particularly important if the priorities are to be used not only in choice application, but for other types of application such as resource allocation. The measurement includes pairwise comparisons on the elements and relative weight estimation of all dependence and feedback relationships in the ANP network.
Furthermore, the ratio of two numbers from the same ratio scale is an absolute number, which is dimensionless. Saaty (undated) states that “If the objects are homogeneous and if we have knowledge and experience, paired comparisons actually derive measurements that are likely to be close and that indicate magnitude on an absolute scale.” For example, the ratio of two readings from a ratio scale such as dividing 6 kg of bananas by 3 kg of bananas yields the number 2, which is a number that belongs to an absolute scale that says that the 6 kg bananas is twice heavier than the 3 kg bananas. Numbers from the same ratio scale, being invariant under the identity transformation, can be added and multiplied.
3. Synthesis. Synthesis is the opposite of analysis. While analysis means separating a material or abstract entity into its constituent elements, synthesis means putting together or combining parts into a whole. Because complex, crucial decision situations, or forecasts, or resource allocations often involve too many dimensions for humans to synthesize intuitively, we need a way to synthesize over many dimensions. Although AHP/ANP facilitates analysis, an even more important function is the ability of AHP/ANP to help measure and synthesize multitude of factors in a hierarchy or network. There is no other methodology that facilitates synthesis as does AHP/ANP. Synthesis involves: a) construction of original (unweighted) supermatrix; b) construction of weighted supermatrix; and c) calculation of the global priority weights (by construction of limiting supermatrix).
3.1.5 Consistency in ANP
The comparison mode in AHP/ANP allows for inconsistent transitivity relationships of preference. The axiom of transitivity must hold. For example:
If 21 aa and 32 aa , then 31 aa ; ≻ means preferred to
If 21 4aa and 31 8aa , then 32 84 aa
Under a single criterion rubric, we might not ordinarily expect to have intransitive relations. But, for multi‐criteria problems, it is often impossible not to have intransitivities, as the decision maker cannot simplify the complexities of the problem to achieve true transitivity.
For example, professor A is about to change jobs. He knows that if two offers are far apart on salary, the salary will be the determining factor in his choice. Otherwise, factors such as prestige of the university will come to play. He eventually receives three offers, described in part as follows:
University Salary Prestige
X $65.000 Low
Y $50.000 High
Z $58.000 Medium
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On reflection, A concludes that YX , ZY , and XZ . The intransitivity makes the professor difficult to make the best decision.
Since it is difficult to achieve consistency, AHP/ANP introduces the notion of deviation from consistency so that the decision maker can proceed accordingly. It is recommended that inconsistency should not be greater than ten percents.
Moreover, one should not compare more than 7 (seven) elements (Saaty and Vargas, 2005), since when comparing more than 7 elements, each additional element introduces such a small relative inconsistency that it becomes very difficult to tell which element is most responsible for the inconsistency.
3.1.6 Procedure to Obtain Ratio Scale2
Let A1, A2, A3, ..., An be n elements in a matrix within a hierarchy. The pairwise comparisons on pairs of elements (Ai, Aj) that we have to make are represented by an n‐by‐n matrix A = (aij), where i,j = 1, 2, 3,....., n. Define a set of numerical weights w1, w2, w3, ..., wn that reflects the recorded comparisons, so that we can write:
A1 A2 An
nnn
n
n
n wwww
wwwwww
wwwwww
A
A
A
A
/........./
...............
...............
/......//
/......//
.
.
1
22212
12111
2
1
(3.1)
Since every row is a constant multiple of the first row, A has a unit rank. By multiplying A with the vector of weights w,
Aw = nw (3.2)
To recover the scale from the matrix ratios, the following system ought to be solved:
(A‐nI)w = 0 (3.3)
Clearly, a nontrivial solution can be obtained if and only if det(A‐nI) vanishes, i.e., the characteristic equation of A. Hence, n is an eigenvalue and w is an eigenvector, of A. Given that A has a unit rank, all its eigenvalues except one are zero. Thus, the trace of A is equal to n.
If each entry in A is denoted by aij, then aij = 1/aji (reciprocal property) holds, and so does ajk = aik/aij (consistency property). By definition, aii = ajj = 1 (when comparing two same elements). Therefore, if we are to rank n number of elements, i.e., A is of the size n‐by‐n, the required number of inputs (from the paired comparison) is less than n2; it is equal to only the number of entries of the sub‐diagonal part of A (see Saaty, 1994). Hence, if there are three elements in a particular level of a hierarchy, only three pairwise comparisons are required.
In general, however, the precise value of wi /wj is hardly known simply because the pairwise
comparisons we made is only an estimate, suggesting that there are some perturbations.
2 Azis (2003), pp. 3‐4.
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While the reciprocal property still holds, the consistency property does not. By taking the largest eigenvalue denoted by λmax,
AP wP = λmax . wP (3.4)
where Ap
is the actual, or the given, matrix (perturbed from matrix A). Although (3.2) and (3.4) are not identical, if wp is obtained by solving (3), the matrix whose entries are wi /wj
is
still a consistent matrix; it is a consistent estimate of A, although Ap
itself does not need to be consistent. Note that Ap will be consistent if and only if λmax = n. As long as the precise value of wi /wj cannot be given, which is common in a real case due to the bias in the comparisons, λmax is always greater than or equal to n (hence, a measure of consistency can be derived based on the deviation of λmax
from n).
When more than two elements are compared, the notion of consistency can be associated
with transitivity condition: if 21 AA , and 32 AA , then 31 AA . It should be clear that in
solving for w, the transitivity assumption is not strictly required; the inputted comparisons do not have to reflect a full consistency. Yet, as shown above, the resulting matrix and the corresponding vector remain consistent. It is this consistent vector w that reflects the priority ranking of the elements in each level. Hence, in a standard hierarchy with three levels (goals, criteria, and alternative policies), the elements in each level are pairwise compared with respect to elements in the level above it, and the resulting vector for the bottom level reflects the priority ranking of the alternative policies.
3.1.7 Supermatrix in ANP3
While both AHP and ANP use the above procedure to derive the ratio scales, the presence of feedback influences in ANP requires a large matrix known as supermatrix containing a set of sub‐matrices. This supermatrix should capture the influence of elements on other elements in the network.
Denoting a cluster by Ch, h = 1, …, N, and assuming that it has nh elements eh1, eh2, eh3
, …,
ehmh, Equation 3.5 shows the supermatrix of the hierarchy.
(3.5)
When the bottom level affects the top level of the hierarchy, a form of network known as holarchy is formed, the supermatrix of which will look like the one displayed in Figure 3.3.
3 Azis (2003), pp. 4‐7.
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Notice that the entry in the last row and column of the supermatrix in equation 3.5 is the identity matrix I corresponding to a loop at the bottom level of the hierarchy. This is a necessary aspect of a hierarchy viewed within the context of the supermatrix. On the other hand, the entry in the first row and last column of a holarchy in equation 3.6 is nonzero, indicating that the top level depends on the bottom level.
(3.6)
In general, when feedback influences are present as in Figure 3.1 (right), the supermatrix is formed by laying out all the clusters and all the elements in each cluster both vertically on the left and horizontally at the top as in equation 3.7.
(3.7)
Typical entry of the above supermatrix is:
(3.8)
where i and j denote the affected and affecting cluster respectively, and n is the element of the respected cluster.
The entries of sub‐matrices in Wij are the ratio scales derived from paired comparisons
performed on the elements within the clusters themselves according to their influence on each element in another cluster (outer dependence) or elements in their own cluster (inner
eN1 eN2
e21
C1 C2 CN e11 e1 e21 e2 eN1 eN
W11 W12 W1NC1 e11
W21 W22 W2N
WN1 WN2 WNN
W = C2
CN
19
dependence)4.
The resulting unweighted supermatrix is then transformed into a matrix each of whose columns sums to unity to generate a stochastic supermatrix. The derived weights are used to weight the elements of the corresponding column blocks (cluster) of the supermatrix, resulting in a weighted supermatrix which is also stochastic. The stochastic nature is required for the reasons described below.
It has been shown that such a limit exists given the stochastic nature of the weighted supermatrix (Saaty, 2001). There are 3 cases to consider in deriving Wk: (1) λmax
= 1 is a
simple root and there are no other roots of unity in which case given the nonnegative matrix W is primitive, we have lim
k→∞ Wk = weT
, implying that it is sufficient to raise the primitive
stochastic matrix W to large powers to yield the limit outcome; (2) there are other roots of unity that cause cycling, in which case Cesaro sum is applied5 ; and (3) λmax
= 1 is a multiple
root, in which case the Sylvester’s formula with λmax = 1 is applied6.
Hence, the powers of the supermatrix do not converge unless it is stochastic, because then its largest eigenvalue is one. When a convergence is failed to achieve (a cyclic case) the average of the successive matrices of the entire cycle gives the final priorities (Cesaro sum), in which the limit cycles in blocks and the different limits are summed and averaged and again normalized to one for each cluster7.
In practice, however, one simply needs to raise the stochastic supermatrix to large powers to read off the final priorities in which all the columns of the matrix are identical and each gives the relative priorities of the elements from which the priorities of the elements in each cluster are normalized to one. At any rate, raising the stochastic supermatrix to large powers gives what is known as limiting supermatrix.
Hence, there are 3 supermatrices: (1) the original unweighted supermatrix of column eigenvectors obtained from pairwise comparison matrices of elements; (2) the weighted supermatrix in which each block of column eigenvectors belonging to a cluster is weighted by the priority of influence of that cluster, rendering the weighted supermatrix column stochastic; and (3) the limiting supermatrix obtained by raising the weighted supermatrix to large powers.
3.2 Step of Research
Based on ANP discussion, the main steps of ANP modeling are: 1) Decomposition, which is the development of ANP network of the problem; 2) Measurement, which is pairwise comparisons on the elements and relative weight estimation of all dependence and feedback relationships in the ANP network; and 3) Synthesis, which includes construction
4 If the clusters influence and be influenced by other clusters, paired comparisons on the clusters are to be made as well. 5 Cesaro’ summability basically stipulates that if a sequence converges then the sequence of arithmetic means formed from that sequence also converges to the same limit as the sequence (see Saaty, 2001). 6 James Joseph Sylvester (1814 – 1897), who was an English poet and great creators of terms in mathematics, developed a mathematical formula that allows limit priorities to be obtained from a reducible stochastic matrix W with λmax
= 1 being a multiple root.
7 In other words, one has to compute the limit priorities of the stochastic supermatrix according to whether it is irreducible (primitive or imprimitive [cyclic]) or it is reducible with one being a simple or a multiple root and whether the system is cyclic or not.
20
and calculation of original unweighted supermatrix, weighted supermatrix, and limiting supermatrix (the global priority weights).
This study comprises of several extended steps of main ANP modeling, which can be grouped into three phases. Phase 1 is model construction or decomposition to identify, analyze and structure the complexity of the problems into an appropriate ANP network, which includes: a) Literature reviews, questionnaires and in‐depth interviews with experts and practitioners (Islamic bankers) to comprehend the problem fully; b) Construction of ANP network; and c) Validation of ANP network. Phase 2 is model quantification or pair‐wise comparison, includes: a) Design pair‐wise questionnaires in accordance with ANP network; b) Test the pair‐wise questionnaires to respondents (experts and/or Islamic bankers); and c) Survey to respondents to fill out pair‐wise questionnaires. Phase 3 is synthesis and results analysis, which includes: a) Data processing and synthesis using ANP software SUPERDECISIONS, as well as results analyses to calculate geometric mean and rater agreement; b) Validation of the results; and c) Interpretations of the results.
Figure 3.2 Steps of Research
3.2.1 Model Construction
To construct ANP model in phase 1, based on theoretical and empirical literature reviews of the problem, open questionnaires are sent via email to 20 practitioners (Islamic bankers) from various Islamic banks and 15 Islamic banking experts from various institutions, universities and consulting firms. Follow‐up is conducted through in‐depth interviews to garner more detailed information to be able to comprehend the real problems. Based on this comprehensive understanding, ANP network is developed and refined further by validation from experts and/or Islamic bankers. ANP network is then inputted to the computer using SUPERDECISIONS software.
Literature Review
Indepth Interview
Questionnaire
ANP Model Construction
ANP Model Validation
Pair‐wise Questionnaire Design
Pair‐wise Questionnaire Testing
Pair‐wise Survey
Data Synthesis & Analysis
Results Validation
Results Interpretation
PHASE 1 Model
Construction
RESEARCHER EXPERTSiBANKERS
PHASE 2 Model
Quantification
PHASE 3 Results Analysis
21
Figure 3.3 ANP Model Development
3.2.2 Model Quantification
To quantify and measure the ANP model or network in phase 2, pair‐wise questionnaires are drawn based on final ANP network designed in phase 1, which has been automatically formed in SUPERDECISIONS software. To make sure that the questionnaires are worked effectively within allowable inconsistency, questionnaire testing is conducted to respondents. In this step, modification to questionnaires might be needed to improve its effectiveness to gather appropriate data. Subsequently, pair‐wise surveys to experts and Islamic bankers are conducted using final pair‐wise questionnaires. Pair‐wise data collected are then inputted to the ANP Network in SUPERDECISIONS software to be processed to produce outputs in the form of priorities and supermatrices. Each respondent will be inputted into one individual ANP network.
Figure 3.4 Input‐Output Process of ANP
3.2.3 Synthesis and Analysis
In phase 3, Results or synthesis of ANP network in SUPERDECISIONS software for each respondent can be generated. The data are then exported to excel worksheet to be manipulated to produce the desired outputs. To produce scientific ‘consensus’ results, geometric means of all respondents’ responses are calculated, re‐inputted to ANP network in SUPERDECISIONS software, and re‐synthesized. To make sure that all results are correct, validation is done for each step of procedure. Kendall’s coefficient of concordance can be calculated to assess the agreement among respondents. Finally, interpretation of detailed (individual) and overall (geometric mean) results is completed to be able to draw conclusions and to propose policy recommendations.
ANP Model PRIORITY OF CHOICES
INPUT (Pairwise Comparisons)
EXPERTS’ OPINIONS
PROCESS(SuperDecisions)
OUTPUT (Supermatrices)
LiteratureReviews (THEORY)
Literature Reviews
(EMPIRICAL)
InDepth Interviews
ANP Network
Questionnaires
EXPERTS iBANKERS
22
Figure 3.5 Detailed Input‐Output Process of ANP
a. Geometric Mean
The Geometric Mean, which is a theorem in mathematics, is the unique way to combine group judgments. Instead of obtaining pairwise questionnaires from FGD consensus of all respondents, pairwise questionnaires of each respondent can be combined to obtain geometric mean consensus.
Geometric mean is a type of mean or average in mathematics, which indicates the central tendency or typical value of a set of numbers. To calculate geometric mean, the numbers are multiplied and then the nth root of the resulting product is taken (n is the count of numbers in the set). The geometric mean of a data set {a1, a2, …, an} is given by:
∏ / … (3.9)
The geometric mean of a data set is less than or equal to the data set’s arithmetic mean (the two means are equal if and only if all members of the data set are equal). This allows the definition of the arithmetic‐geometric mean, a mixture of the two which always lies in between.
b. Rater Agreement
Kendall’s coefficient of concordance or Kendall’s W is a non‐parametric statistic, which measures and assesses the level of agreement among raters or respondents. Kendall’s W is a normalization of the statistic of the Friedman test, which ranges from 0 (no agreement) to 1 (complete agreement). If the value of W is 1, it means that all the survey respondents have been unanimous, and each respondent has assigned the same order to the list of concerns. If the value of W is 0, it means that there is no overall trend of agreement among the respondents, and their responses may be regarded as essentially random. Intermediate values of 0 < W < 1 indicate a greater or lesser degree of unanimity among various respondents.
To calculate Kendall’s W, suppose that object i is given the rank ri,j by judge number j, where there are in total n objects and m judges. Then the total rank given to object i is:
∑ , (3.10)
and the mean value of these total ranks is:
1 (3.11)
ANP SuperDecisions
Pairwise Questionnaires (7iB + 7Ex)
Individual ANP Pairwise (7iB + 7Ex)
Geo. Mean ANP Pairwise (iB, Ex, Tot)
IndividualOUTPUTS (7iB + 7Ex)
Geo. MeanOUTPUTS (iB, Ex, Tot)
RESULTS‐ Detailed ‐ Overall
Rater Agreement
Geo
metric
Mean
23
The sum of squared deviations, S, is defined as:
∑ (3.12)
and then Kendall's W is defined as8:
S (3.13)
When the value of test statistic W is 1, it can be concluded that all the judges or survey respondents have been unanimous, and each judge or respondent has assigned the same order to the list of objects or concerns. When the value of test statistic W is 0, it can be concluded that there is no overall trend of agreement among the respondents, and their responses may be regarded as essentially random. Intermediate values of test statistic 0 < W < 0 indicate a greater or lesser degree of unanimity among the various judges or respondents.
4. RESULTS AND ANALYSIS
The discussion of this chapter will follow the steps of ANP, which are decomposition, pair‐wise comparison, synthesis, and analysis.
4.1 Decomposition
4.1.1 Problem Identification
According to several experts’ opinions9, as well as questionnaire and in‐depth interviews with local experts and practitioners, contemporary factors causing low PLS financing can still be viewed from internally and externally. Internal aspects include upper management, human resources, and technical, while external aspects include society, the authorities, and customers. The subsequent clusters are grouped into problems, solutions, policies and strategies with the details as follows.
a. Internal Problems
Internal problems (IP) are lack of PLS financing problems coming from internal organization. IP could be grouped into three, namely: 1) Upper Management (including Board of Commissioners and Board of Directors); 2) Human Resources; and 3) Technical. Elements of each group are as follows.
1. Upper Management (Board of Commissioners and Board of Directors), include: a) Lack of understanding in Islamic economy, finance and banking fundamentals; b) Emphasis on business or profit orientation (business‐oriented); c) Risk averse and risk transfer behavior still leads to the inability to accept the possibility of loss; and d) Lack of commitment to improve the portfolio of PLS financing.
8 Legendre, P (2005) Species Associations: The Kendall Coefficient of Concordance Revisited. Journal of Agricultural, Biological and Environmental Statistics, 10(2), 226–245. 9 Chapra (2000), Iqbal and Llewellyn (2002), Dar and Presley (2000), Sarker (1999), Algaoud and Lewis (2001), Mulyawan (2001), Al‐Jarhi (2002) and Parinduri (2003).
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2. Human Resources, include: a) Lack of knowledgeable and skilled human resources with expertise in Islamic banking and Shariah Law; b) Emphasis on business targets or profit (target‐oriented); c) Risk averse and risk transfer behavior still lead to inability to accept the possibility of loss; and d) Aversion to diversification efforts because it is more complicated to deal with PLS financing than to deal with other modes of financing.
3. Technical Aspects, include: a) Less applicable than other modes of financing for working capital, small businesses or long‐term projects; b) Higher risk than other modes of financing, while Islamic banks are still unable to manage higher risk; c) More complicated to structure and deal with PLS financing than to structure and deal with other modes of financing; and d) Islamic banks have insufficient management tools to manage higher risk or to analyze and measure investment risk adhering to Islamic principles.
b. System Problems
System problems (SP) are lack of PLS financing problems coming from existing conditions of the system. SP could be grouped into three, namely: 1) Conventional Domination; 2) Unsupportive Environment; and 3) Conventional Competition. Elements of each group are as follows.
1. Conventional Domination reflects the condition of general system in Indonesia which still dominates by conventional system. This includes: a) Mindset and ideology of all stakeholders and general population, which are still mostly conventional capitalistic; b) Existing Social system; c) Existing Political system which is largely democratic system; and d) Existing Economic system which is dominated by capitalistic system.
2. Unsupportive Environment reflects the condition of general environment in Indonesia which is influenced by monarchy, Dutch occupation and Islam. This includes: a) Value system; b) Culture which is dominated by a mix of local culture and pop culture; c) Infrastructures; and d) Rules and regulations.
3. Conventional Competition reflects the condition of financial market which is dominated by conventional banking and finance. This includes: a) Financial institutions; b) Financial instruments; c) Financial products; and d) Financial services.
c. External Problems
External problems (EP) are lack of PLS financing problems coming from outside organization. EP could be grouped into three, namely: 1) Society; 2) Authority; and 3) Customer. Elements of each group are as follows.
1. Society, include: a) Multi‐ethnic and multi‐religious affiliations have sensitized society to issues of ethnicity and religiosity (unity through diversity is more important); b) Lack/loss of trust in society has introduced agency problem and asymmetric information that lead to moral hazard and adverse selection; c) Inaccurate perceptions of Islam and riba have made society ignorant to Islamic finance and banking; and d) Lack of understanding and knowledge regarding the fundamentals of the Islamic economy, finance and banking;
2. Authority, include: a) Lack of understanding in Islamic economy, finance and banking fundamentals; b) Lack of political commitment, political will, and political courage to support the development of Islamic finance and banking; c) Lack of supporting
25
infrastructure (hard and soft) in the development of Islamic finance and banking; and d) Lack of incentives and efforts to promote PLS‐based finance.
3. Customer, include: a) Lack of understanding and knowledge concerning the fundamentals of the Islamic economy, finance, and banking; b) Customers (depositors/borrowers) are naturally risk averse because they are not accustomed to the possibility of loss and are accustomed to an interest rate system; c) Low demand for PLS financing due to its limited applicability and unpopularity; and d) The majority of Islamic banks’ customers are floating (not loyal) customers.
d. Internal Solutions
Internal solutions (IS) are alternative solutions to internal problems of lack of PLS financing. IS could also be grouped into three, namely: 1) Upper Management (including Board of Commissioners and Board of Directors); 2) Human Resources; and 3) Technical. Elements of each group are as follows.
1. Upper Management, include: a) Appropriate ‘Fit and Proper Test’ for BOC or BOD candidates; b) Management commitment to apply PLS financing as the main mode of financing; and c) Reward and Punishment mechanism to promote PLS financing.
2. Human Resources, include: a) Introduce a thorough human resource selection process; b) Ameliorate human resources knowledge and skills in Islamic banking and Shariah Law; and c) Incentive system for Islamic bank officers extending PLS‐based financing.
3. Technical Aspects, include: a) Simplification of standards and procedures in the application of PLS based financing; b) Development of innovative and attractive yet simple PLS‐based products; and c) Development of Information Technology and Standard Operating Procedures in the extension of PLS financing.
e. System Solutions
System solutions (SS) are alternative solutions to system problems of lack of PLS financing. SS could also be grouped into three, namely: 1) Conventional Domination; 2) Unsupportive Environment; and 3) Conventional Competition. Elements of each group are as follows.
1. Solutions to conventional domination include: a) Union and cooperation; b) Protocol and grand strategy; and c) Economic strengthening.
2. Solutions to unsupportive environment include: a) Laws and regulations; b) Appropriate infrastructures; and c) alternative Islamic system.
3. Solutions to conventional competition include: a) Increase share of Islamic banking; b) Improve standards to be comparable to their conventional counterparts; and c) Diversification of Islamic financial products and services.
f. External Solutions
External solutions (ES) are alternative solutions to external problems of lack of PLS financing. ES could also be grouped into three, namely: 1) Society; 2) Authority; and 3) Customer. Elements of each group are as follows.
1. Society, include: a) Extensive and intensive socialization of IEFB and PLS financing; b) Effective da’wah (outreach to the people) for IEFB and PLS financing; c) Systematic and comprehensive education system from elementary school up to higher education;
26
2. Government/Authority, include: a) Political commitment, political will and political courage to support the development of IEFB and PLS financing; b) Government support of hard and soft infrastructure in the development of IEFB; and c) Supportive regulations to foster IEFB and PLS‐based financing.
3. Customer, include: a) Education offered to customers and potential customers regarding PLS financing; b) A systematic and concerted national promotion program to nurture PLS financing; and c) An incentive system for customers to choose PLS‐based financing.
g. Policies
Policies are some recommended general policies which can be taken to solve the problems of lack of PLS financing. These recommended policies could include: 1) Directed market‐driven policy; 2) Fair Treatment; 3) Gradual and Sustainable; 4) Shariah Compliant; and 5) Professionalism.
h. Development Strategies
Development strategies are programs that can immediately be implemented to solve the problems of lack of PLS financing for certain periods. These could include: 1) New Image Program; 2) New Mapping of Market Segmentation; 3) Product Development Program; 4) Service Improvement Program; and 5) Socialization and Communication Program.
4.1.2 Conceptual Framework
Based on the previous problem identification, the conceptual framework of this study can be read in figure 4.1 in appendix 1.
[Insert Figure 4.1]
4.1.3 ANP Network Design
Therefore, the ANP network of the above framework will be as can be seen in figure 4.2 in the appendix.
[Insert Figure 4.2]
4.2 Pair‐wise Comparison
The most knowledgeable respondents (seven Islamic bankers and seven experts) are chosen to be the respondents of phase 2 to fill out pair‐wise questionnaires. To simplify the original rather complicated pair‐wise questionnaires and to maintain consistency, modified pair‐wise questionnaires are used as shown in figure 4.3 in appendix 1. Meanwhile, the respondents are equipped with a show card describing the scale and the ANP network.
[Insert Figure 4.3]
The modified pair‐wise questionnaire will significantly reduce the time required for in‐depth interviews with respondents and will provide consistent results. For example, the time taken to complete the entire pair‐wise questionnaire of more than 1,200 questions was less than two hours.
27
4.3 Synthesis and Analysis
The detailed synthesis results of individual respondents (Islamic bankers and Experts) can be seen in Appendix 2, while overall and summary synthesis results (geometric means of 7 Islamic bankers, 7 Experts and 7 Islamic bankers + 7 Experts) will be discussed in this section.
4.3.1 Overall Results
The complete results of the synthesis from geometric mean can be read in tables 4.1 – 4.3 in appendix 1. These results reflect statistically generated ‘consensuses’ of Islamic bankers, Experts, and all respondents (7 Experts and 7 Islamic bankers).
[Insert Table 4.1 – Table 4.3]
Experts view that External and System are two most important aspects, but with very low rater agreement (We = 0.036). Meanwhile, Islamic bankers view that Internal is the most important aspect, with high rater agreement (Wi = 0.39). The overall results, which resemble Islamic bankers’ view, shows that the most important issues of low implementation of PLS financing lies within Internal aspect of Islamic banking, followed by Existing System and External Environment aspects (see figure 4.4), with low rater agreement (Wt = 0.162).
Figure 4.4 Priorities of Aspects
Experts and Islamic bankers agree that the most crucial Internal Problem is within Top Management (See figure 4.5 top‐left). However, they do not agree on the next most crucial Internal Problems with low rater agreement. Experts view that it is within Human Resources (with low rater agreement, We = 0.143), while Islamic bankers view that it is within Technical (with very low rater agreement, Wi = 0.02). Overall, the next most crucial Internal Problems are Technical and then Human Resource (with very low rater agreement, Wt = 0.061).
Furthermore, Islamic bankers believe that the problems of Top Management are ‘Lack of Understanding’ and ‘Business Oriented’ (with Wi = 0.149), while Experts believe that they are ‘Business Oriented’ and ‘Lack of Commitment’ (with We = 0.178). Overall, ‘Business Oriented’ stands out as the most crucial problem of Top Management, with Wt = 0.149 (see figure 4.5 top‐right). Islamic bankers do not agree on the most crucial problems of Technical (with very low rater agreement, Wi = 0.004), which turns out to be ‘Less Applicable’ and ‘No
0 0.1 0.2 0.3 0.4 0.5 0.6
iBankers
Experts
Total ASPECTWi = 0.39We = 0.036Wt = 0.162
InternalSystem
External
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEAN
ASPECTWi = 0.39
Internal
System
External
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEAN
ASPECTWe = 0.036
Internal
System
External
28
Management Tools’, while Experts do agree on the most crucial problems of Technical (with high rater agreement, We = 0.516), which are ‘Complicated’ and ‘Higher Risk’, and these results are confirmed in overall, with rater agreement, Wt = 0.121 (see figure 4.5 bottom‐left). The problems of Human Resource viewed by Islamic banker are ‘Target Oriented’ and ‘Lack of Knowledge and Skill’ (with Wi = 0.065), while viewed by Experts are ‘Risk Averse’ and ‘Effort Averse’ (with We = 0.153). Overall, ‘Target Oriented’ and ‘Risk Averse’ stand out as the most crucial problem of Human Resource, with Wt = 0.014 (see figure 4.5 bottom‐right). The more detailed results of individual Islamic bankers and individual Experts can be seen in Appendix 2.
Figure 4.5 Priorities of Internal Problems
Experts and Islamic bankers do not agree on most crucial System Problem. Islamic bankers believe it is within Conventional Domination, with very low rater agreement, Wi = 0.061, while Experts believe it is within Unsupportive Environment, with very low rater agreement, We = 0.082 (See figure 4.6 top‐left). Overall, the most crucial System Problems are within Unsupportive Environment and Conventional Dominant (with very low rater agreement, Wt = 0.066).
Furthermore, Islamic bankers and Experts agree that the most crucial problems of Unsupportive Environment are ‘Value System’ and ‘Existing Culture’, with low rater agreement, Wt = 0.121. Islamic bankers have very low rater agreement, Wi = 0.055, while Experts have low rater agreement, We = 0.22 (see figure 4.6 top‐right). Islamic bankers view that the most crucial problems of Conventional Domination are ‘Existing Economic System’ and ‘Mindset’ (with Wi = 0.21), while Experts’ views are just the opposite (with We = 0.118), so that in overall the most crucial problems of Conventional Domination are ‘Existing Economic System’ and ‘Mindset’ with equal priority, but with very low rater agreement, Wt = 0.156 (see figure 4.6 bottom‐left). Meanwhile, Islamic Bankers and Experts agree that the most crucial problem of Conventional Competition is ‘Product’ and then ‘Service’ and ‘Instrument’. In this case, Islamic bankers have very high rater agreement Wi = 0.724, while Experts have very low rater agreement We = 0.073, so that overall rater agreement are moderate at Wt = 0.313 (see figure 4.6 bottom‐right). The more detailed results of individual Islamic bankers and individual Experts can be seen in Appendix 2.
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Top MgtTechnicalH Resource
INTERNALPROBLEMSWi = 0.02We = 0.143Wt = 0.061
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
L UnderstandingL CommitmentBusiness OrientedAverse Risk
TOP MGTWi = 0.149We = 0.178Wt= 0.06
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
No Mgt ToolsLess ApplicableHigher RiskComplicated
TECHNICALWi = 0.004We = 0.516Wt = 0.121
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
Target OrientedRisk AverseL.Know&SkillEffort Averse
HUMANRESOURCEWi = 0.065We = 0.153Wt = 0.014
29
Figure 4.6 Priorities of System Problems
Experts and Islamic bankers agree on two most crucial External Problems, which are within Authority and Customer, with moderate rater agreement, Wt = 0.321. Islamic bankers believe that Authority is the most crucial problem with high rater agreement, Wi = 0.571, while Experts believe that Customer is the most crucial problem, with low rater agreement We = 0.143 (see figure 4.7 top‐left).
Furthermore, Islamic bankers’ view on the problems of Society are ‘Lack of Knowledge’ and ‘Lack of Perception’ with high rater agreement, Wi = 0.52, while Experts’ view are ‘’Lack of Trust’ and ‘Lack of Knowledge’ with moderate rater agreement, We = 0.31, so that overall problems of Society are ‘Lack of Knowledge’ and ‘Lack of Perception’ with moderate rater agreement Wt = 0.289 (see figure 4.7 top‐right). Islamic bankers’ view on the problems of Customer are ‘Lack of Knowledge’ and ‘Averse to Risk’ with high rater agreement, Wi = 0.663, while Experts’ view are ‘’Lack of Knowledge’ and ‘Floating Majority’ with moderate rater agreement, We = 0.318, so that overall problems of Customer are ‘Lack of Knowledge’ and ‘Floating Majority’ with high rater agreement Wt = 0.464 (see figure 4.7 bottom‐left). Meanwhile, the problems of Authority agreed by Islamic bankers and Experts are ‘Lack of Commitment’ and ‘Lack of Support’ with low rater agreement, Wt = 0.088 (see figure 4.7 bottom‐right). Islamic bankers have very low rater agreement, Wi = 0.069, while Experts have low rater agreement, We = 0.167. The more detailed results of individual Islamic bankers and individual Experts can be seen in Appendix 2.
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Unsupportive Env.Conv.DominantConv.Competition
SYSTEMPROBLEMSWi = 0.061We = 0.082Wt = 0.066
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
ValueRuleInfraStructureCulture
UNSUPPORTIVEENVIRONMENT
Wi = 0.055We = 0.22Wt = 0.121
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
ThoughtSocialPoliticsEconomy
CONV.DOMINANTWi = 0.21We = 0.118Wt = 0.156
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
ServiceProductInstrumentInstitution
CONV. COMPETITIONWi = 0.724We = 0.073Wt = 0.313
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
SocietyCustomerAuthority
EXTERNALPROBLEMSWi = 0.571We = 0.143Wt = 0.321
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
L.of TrustL PerceptionL KnowledgeDiversity
SOCIETYWi = 0.52We = 0.31Wt = 0.289
30
Figure 4.7 Priorities of External Problems
Experts and Islamic bankers agree that the most urgent Internal Solution is within Top Management (See figure 4.8 top‐left). However, they do not agree on the next most urgent Internal Solutions with low rater agreement. Experts view that it is within Human Resources (with low rater agreement, We = 0.143), while Islamic bankers view that it is within Technical (with very low rater agreement, Wi = 0.02). Overall, the next most urgent Internal Solutions are Technical and then Human Resource (with very low rater agreement, Wt = 0.061).
Furthermore, the most urgent solution of Top Management agreed by Islamic bankers and Experts is ‘Commitment’ with moderate rater agreement, Wt = 0.216, while Islamic bankers’ rater agreement is Wi = 0.107 and Experts’ rater agreement is We = 0.388 (see figure 4.8 top‐right). Islamic bankers’ view on the most urgent Technical solution is ‘IT&SOP’ with low rater agreement, Wi = 0.143, while Experts’ view are ‘Simplification’ and ‘IT&SOP’ with low rater agreement, We = 0.097, so that overall views on the most urgent Technical solutions are ‘IT&SOP’ and ‘Simplification’ with very low rater agreement, Wt = 0.017 see figure 4.8 bottom‐left). Islamic bankers’ view on the most urgent solution of Human Resource is ‘Human Resource Improvement’ with low rater agreement, Wi = 0.184, while Experts’ view is ‘Human Resource Incentive’ with very low rater agreement, We = 0.015, so that overall view on the most urgent solution of Human Resource is ‘Human Resource Improvement’ and ‘Human Resource Incentive’ with very low rater agreement, Wt = 0.073 (see figure 4.8 bottom‐right). The more detailed results of individual Islamic bankers and individual Experts can be seen in Appendix 2.
Figure 4.8 Priorities of Internal Solutions
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
Low Demand
L.Knowledge
Floating Majority
Averse to Risk
CUSTOMERWi = 0.663We = 0.318Wt = 0.464
0 0.1 0.2 0.3 0.4
iBankers
Experts
Total
L.UnderstandingL.SupportL.IncentiveL.Commitment
AUTHORITYWi = 0.069We = 0.167Wt = 0.088
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
S.Top MgtS.TechnicalS.H Resource
INTERNALSOLUTIONS
Wi = 0.02We = 0.143Wt = 0.061
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Reward&Punish
I.Commitment
Fit&Proper
S. TOP MGT.Wi = 0.107We = 0.388Wt = 0.216
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Simplification
IT & SOP
Innovation
S. TECHNICALWi = 0.143We = 0.097Wt = 0.017
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Selection
HR.Incentive
HR.Improvement
S. HUMANRESOURCEWi = 0.184We = 0.015Wt = 0.073
31
Experts and Islamic bankers do not agree on most urgent System Solution. Islamic bankers believe it is within Conventional Domination, with very low rater agreement, Wi = 0.061, while Experts believe it is within Unsupportive Environment, with very low rater agreement, We = 0.082 (See figure 4.9 top‐left). Overall, the most crucial System Problems are tie within Unsupportive Environment and Conventional Dominant (with very low rater agreement, Wt = 0.066).
Furthermore, the most urgent solution of Unsupportive Environment agreed by Islamic bankers and Experts is ‘Supportive Law and Regulation’ with low rater agreement, Wt = 0.116 (See figure 4.9 top‐right). Islamic bankers and Experts score low rater agreement of Wi = 0.097 and We = 0.143, respectively. The two most urgent solutions of Conventional Domination agreed by Islamic bankers and Experts are ‘Grand Strategy’ and “Union/Cooperation’ with high rater agreement, Wt = 0.537 (see figure 4.9 bottom‐left). Islamic bankers and Experts score high rater agreement of Wi = 0.45 and We = 0.679, respectively. Meanwhile, two most urgent solution of Conventional Competition agreed by Islamic bankers and Experts is ‘Improved Standard’ and ‘Diversification’ with low rater agreement, Wt = 0.17 (See figure 4.9 bottom‐right). Islamic bankers and Experts score moderate and low rater agreements of Wi = 0.291 and We = 0.082, respectively. The more detailed results of individual Islamic bankers and individual Experts can be seen in Appendix 2.
Figure 4.9 Priorities of System Solutions
Experts and Islamic bankers agree on two most urgent External Solutions, which are within Authority and Customer, with moderate rater agreement, Wt = 0.321. Islamic bankers believe that Authority is the most crucial problem with high rater agreement, Wi = 0.571, while Experts believe that Customer is the most crucial problem, with low rater agreement We = 0.143 (see figure 4.10 top‐left).
Furthermore, the most urgent solution of Society agreed by Islamic bankers and Experts is ‘Communication’ with low rater agreement, Wt = 0.143 (See figure 4.10 top‐right). Islamic bankers and Experts score moderate and very low rater agreements of Wi = 0.388 and We = 0.02, respectively. The most urgent solution of Customer agreed by Islamic bankers and Experts is ‘Customer Education’ with moderate rater agreement, Wt = 0.356 (See figure 4.10
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
S.Unsupportive Env.S.Conv.DominantS.Conv.Competition
SYSTEMSOLUTIONSWi = 0.061We = 0.082Wt = 0.066
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Law/Regn
Infrastructure
Alt.Islamic System
S. UNS.ENVIRONMENT
Wi = 0.097We = 0.143Wt = 0.116
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Union/Coop
G.Strategy
Econ.Strengthening
S. CONV.DOMINANTWi = 0.45We = 0.679Wt = 0.537
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Incr.Share
Improve Std.
Diversification
S. CONV.COMPETITIONWi = 0.291We = 0.082Wt = 0.17
32
bottom‐left). Islamic bankers and Experts score moderate and high rater agreements of Wi = 0.321 and We = 0.551, respectively. Meanwhile two most urgent solution of Authority agreed by Islamic bankers and Experts are ‘Regulation’ and ‘Commitment’ with low rater agreement, Wt = 0.096 (See figure 4.10 bottom‐right). These results in line with Experts’ view (also with low rater agreement We = 0.02), while Islamic bankers’ view are the opposite, i.e. ‘Commitment’ first, and then Regulation’ (with moderate rater agreement, Wi = 0.25). The more detailed results of individual Islamic bankers and individual Experts can be seen in Appendix 2.
Figure 4.10 Priorities of External Solutions
Experts and Islamic bankers agree on two most important Policies to be taken, which are ‘Fair Treatment’ and ‘Professionalism’, although with low rater agreement, Wt = 0.099. Islamic bankers have moderate rater agreement, Wi = 0.177, while Experts have very low rater agreement We = 0.081 (see figure 4.11 left). Furthermore Experts and Islamic bankers agree on one most important Strategies to be adopted, which is ‘Product Development’ (see figure 4.11 right). The next two most important Strategies according to Islamic bankers are ‘Market Mapping’ and ‘Service Improvement’ (with high rater agreement, Wi = 0.441), while according to Experts are ‘New Image’ and ‘Service Improvement’ (with We = 0.134). Overall, the next two most important Strategies are ‘Service Improvement’ and ‘Market Mapping’ (with Wt = 0.194). The more detailed results of individual Islamic bankers and individual Experts can be seen in Appendix 2.
Figure 4.11 Priorities of Policies and Strategies
4.3.2 Summary Results
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
S.SocietyS.CustomerS.Authority
EXTERNALSOLUTIONSWi = 0.571We = 0.143Wt = 0.321
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
S. Education
Da'wah
Communication
S. SOCIETYWi = 0.388We = 0.02Wt = 0.143
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Promotion
Incentive
C.Education
S. CUSTOMERWi = 0.321We = 0.551Wt = 0.356
0 0.1 0.2 0.3 0.4 0.5
iBankers
Experts
Total
Support
Regulation
E.Commitment
S. AUTHORITYWi = 0.25We = 0.02Wt = 0.096
0 0.1 0.2 0.3
iBankers
Experts
Total
Shariah Compliance
Professionalism
Gradual&Sustain
Fair Treatment
Directed Mkt Driven
POLICIESWi = 0.177We = 0.081Wt = 0.099
0 0.1 0.2 0.3
iBankers
Experts
Total
Sos.Comm.Program
Service Improve
Product Dev
New Image
Mkt Mapping
STRATEGIESWi = 0.441We = 0.134Wt = 0.194
33
Table 4.4 in the appendix 1 shows the summary results of Kendall’s coefficient of concordance, which represent level of agreement (rater agreement) among respondents divided into three groups, namely, Islamic bankers, Experts and Total (Islamic bankers and Experts).
[Insert Table 4.4]
The results show that the levels of agreement among respondents are generally low. Islamic bankers show slightly higher level of agreement than Experts. Moreover, the priority of choices shows greater agreement among respondents, especially among Islamic bankers. Furthermore, Islamic bankers agree the most in External Problems (0.571), External Solutions (0.571), as well as in Strategies (0.441). In more detail, Islamic bankers agree the most in Conventional Competition of System Problems (0.724) and Customer of External Problems (0.663). Meanwhile, Experts agree the most in Conventional Domination of System Solutions (0.679) and Customer of External Solutions (0.551). Finally, all respondents agree the most in Conventional Domination of System Solutions (0.537) and Customer of External Problems (0.464).
Figure 4.12 Priorities of Aspects
Overall geometric mean results of all respondents show that priority aspects to be handled are 1) Internal aspects; 2) System aspects; and 3) External aspects (see figure 4.12).
Figure 4.13 Priority Problems of Low PLS Financing
Summary results show that the most crucial and primary problems of low implementation
of PLS financing are (see figure 4.13): 1) Authority (External); 2) Top Management (Internal);
0.000 0.002 0.004 0.006 0.008 0.010 0.012
ASPEC
T
ASPECTW=0.162
External
System
Internal
0.000
0.010
0.020
0.030
0.040
0.050
34
3) Customer (External); 4) Unsupportive Environment (System); and 5) Conventional
Domination (System). It seems that root causes of the problems lie in people who involve in
the implementation of PLS financing, including authority of Islamic banking, Islamic bank’s
top management as well as customer of Islamic banking.
Furthermore, the most crucial and primary internal problems of low implementation of PLS
financing are (see figure 4.14 left‐blue): a) too much emphasis on business or profit oriented
(top management); b) too complicated to structure and deal with PLS financing (technical);
c) lack of commitment to PLS financing (top management); d) risk averse and risk transfer
behavior (top management); and e) lack of IEF understanding (top management). It is
obvious that the root cause of the internal problems prevalent in top management.
The most crucial and primary system problems of low implementation of PLS financing are
(see figure 4.14 center‐red): a) existing value system (unsupportive environment); b)
product (conventional competition); c) existing economic system (conventional
domination); d) mind set (conventional domination); and e) existing culture (unsupportive
environment). All elements of the existing system contribute to the system problems.
The most crucial and primary external problems of low implementation of PLS financing are
(see figure 4.14 right‐green): a) lack of knowledge (customer); b) lack of commitment
(authority); c) lack of support (authority); d) floating majority (customer); and e) lack of
understanding (authority). Elements of authority and customers mostly contribute to the
external problems.
When all problems (internal, system, and external) are combined, the most crucial problems of low implementation of PLS are: a) lack of knowledge (customer ‐ external); b) lack of commitment (authority ‐ external); c) existing value system (unsupportive environment ‐ system); d) too much emphasis on business or profit oriented (top management ‐ internal); and e) lack of support (authority ‐ external).
0.000
0.001
0.001
0.002
0.002
0.003
Effort Averse
L.Know&Skill
Risk Averse
Target Orien
ted
Complicated
Higher Risk
Less Applicable
No M
gt Tools
Averse Risk
Business Orien
ted
L Commitmen
tL Understanding
Institution
Instrumen
tProduct
Service
Economy
Politics
Social
Thought
Culture
InfraStructure
Rule
Value
L.Commitmen
tL.Incentive
L.Support
L.Understanding
Averse to Risk
Floating Majority
L.Knowledge
Low Dem
and
Diversity
L Knowledge
L Perception
L.of Trust
35
Figure 4.14 Detailed Priority Problems of Low PLS Financing
The most urgent internal solutions of low implementation of PLS financing are (see figure 4.15 left‐blue): a) management commitment to apply PLS financing as the main mode of financing (top management); b) development of Information Technology and Standard Operating Procedures in the extension of PLS financing (technical); c) Ameliorate human resources knowledge and skills in Islamic banking and Shariah Law; (human resource); d) Appropriate ‘Fit and Proper Test’ for BOC or BOD candidates; (top management); and e) Reward and Punishment mechanism to promote PLS financing (top management). It is obvious that the most urgent internal solutions should be started from top management.
The most urgent system solutions of low implementation of PLS financing are (see figure 4.15 center‐red): a) Protocol and grand strategy (conventional domination); b) Laws and regulations (unsupportive environment); c) Improve standards to be comparable to their conventional counterparts (conventional competition); d) Union and cooperation; and e) alternative Islamic system (unsupportive environment).
The most urgent external solutions of low implementation of PLS financing are (see figure 4.15 right‐green): a) Education offered to customers and potential customers regarding PLS financing (customer); b) Supportive regulations to foster IEFB and PLS‐based financing (authority); c) political commitment, political will and political courage to support the development of IEFB and PLS financing (authority); d) a systematic and concerted national promotion program to nurture PLS financing (customer); and e) government support of hard and soft infrastructure in the development of IEFB and PLS financing (authority). The most urgent external solutions should address the authority.
Figure 4.15 Detailed Priority Solutions of Low PLS Financing
When all alternative solutions (internal, system, and external) are combined, the most urgent solutions to the problems of low implementation of PLS are: a) Education offered to customers and potential customers regarding PLS financing (customer ‐ external); b) management commitment to apply PLS financing as the main mode of financing (top management ‐ internal); c) Protocol and grand strategy (conventional domination ‐ system); d) supportive regulations to foster IEFB and PLS‐based financing (authority ‐ external); and
0.0000
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
HR.Improvemen
t
HR.Incentive
Selection
Innovation
IT & SOP
Simplification
Fit&
Proper
I.Commitmen
t
Rew
ard&Punish
Diversification
Improve Std.
Incr.Share
Econ.Stren
gthen
ing
G.Strategy
Union/Coop
Alt.Islam
ic System
Infrastructure
Law/Regn
E.Commitmen
t
Regulation
Support
C.Education
Incentive
Promotion
Communication
Da'wah
S. Education
36
e) political commitment, political will and political courage to support the development of IEFB and PLS financing (authority – external).
Finally, policies and grand strategies that should be implemented to stimulate PLS financing are (see figure 4.16): a) Product development (grand strategies); b) Fair treatment (policies); c) Service improvement (grand strategies); d) Market mapping (grand strategies); and e) Professionalism (policies). A combination of grand strategy and effective policies are expected to be able to stimulate PLS financing.
Figure 4.16 Priorities of Policies and Strategies to Stimulate PLS Financing
4.4 Analysis
The problem of low implementation of PLS financing in Islamic banking has been existed since the early development of Islamic banking. This problem has not been given sufficient attention by scholars and practitioners, as well as by the authority. Consequently, customer and the society at large do not aware of this problem, which can be a disadvantage to macro‐economic soundness.
Problems which have been persisted since previous study in Ascarya and Yumanita (2005 and 2006) are: a) lack of understanding or knowledge of the customer; and b) lack of support from the government or authority. These are external factors which cannot be controlled by Islamic bank. In general, the root causes have not been changed so much, which have been still persisted in people who are involve in Islamic banking, namely, the Islamic banker, the authority and the customer. However, the issues have been slightly changed in priority (see table 4.4).
Alternative solutions which have still been priorities are: a) education or socialization to customer and society at large; and b) supportive regulations from the authority, although there have been some improvements on these issues. Some new supportive Acts have been stipulated, such as Islamic Bank Act no.21/2008 in 2008, Sovereign Sukuk Act no.19/2008 in 2008, and Tax Act no.42/2009 in 2009. It seems that more genuine commitments from the authority and the management of Islamic bank are desperately needed to improve the implementation of PLS financing.
0.000
0.005
0.010
0.015
0.020
0.025
0.030
0.035
37
Furthermore, strategy which has not been effectively implemented and which has still been a priority is product development. So far, there has not been significant improvement in new products innovations based on PLS mode of finance. One emerging product based on PLS mode of finance is home financing using musharakah mutanaqisah contract, which has some resemblance with mortgage financing. Further strategies and policies are needed to improve PLS financing.
Table 4.4 Comparison of Summary Results
ASPECTS PREVIOUS STUDY (2009) CURRENT STUDY
Problems
1. No Management Tools (Technical ‐ Internal)
2. Lack of Commitment (Authority ‐ External)
3. Lack of Trust (Society – External) 4. Lack Commitment (Top Management – Internal)
5. Lack of Knowledge & Skill (Human Resource – Internal)
1. Lack of knowledge (Customer ‐ External) 2. Lack of commitment (Authority ‐ External) 3. Value system (Unsupportive Environment ‐ System)
4. Business or profit oriented (Top Management ‐ Internal)
5. Lack of support (Authority ‐ External)
Solutions
1. IT & SOP (Technical – Internal) 2. Commitment (Authority – External) 3. HR. Incentive (Human Resource – Internal)
4. Internal Commitment (Top Management – Internal)
5. Education (Customer – External)
1. Education on PLS financing (Customer ‐ External)2. Management commitment to apply PLS financing (Top Management ‐ Internal)
3. Protocol and grand strategy (Conventional Domination ‐ System)
4. Supportive regulations (Authority ‐ External) 5. Political commitment, political will and political courage (Authority – External)
Policies/ Strategies
1. Service Improvement (Strategies) 2. Socialization & Communication Programs (Strategies)
3. Professionalism (Policies) 4. Directed Market Driven (Policies) 5. Shariah Compliance (Policies)
1. Product development (Strategies) 2. Fair treatment (Policies) 3. Service improvement (Strategies) 4. Market mapping (Strategies) 5. Professionalism (Policies)
Therefore, the problem of low implementation of PLS financing in Indonesia’s Islamic banking has not been resolved, yet, although some partial solutions have been emerged, both internally and externally. Main problems have always been in the people who involved in Islamic banking. On the supply side, Islamic bankers should commit to implement PLS financing through product development and service improvement, as well as professionalism. On the demand side, education and socialization to customer and society at large should be improved. On the authority side, the government should provide real political commitment, political will and political courage to honestly develop Islamic banking and PLS financing.
5. CONCLUSION AND RECOMMENDATION
5.1 Conclusion
38
The low implementation of PLS financing in Islamic banking has been a persistent global phenomenon since the early development of Islamic banking in early 1970s, and Indonesia is no exception. However, the implementation of PLS financing in Indonesia has been better than those of other neighboring countries like Malaysia and Pakistan, or those of other Middle East and North Africa countries, except Sudan.
The data shows that the implementation of PLS financing in Indonesia is among the highest compared to that of Islamic banks in other countries. At the end of October 2010, the share of PLS financing (mudharabah and musharakah) in Indonesia’s Islamic banking reached 35.5%. Nevertheless, PLS financing has never been placed as the main and dominant mode of finance.
The problem of low implementation of PLS financing in Islamic banking has not been given sufficient attention by people who directly or indirectly involve in it, such as Islamic bankers, scholars, the authority, as well as the customer and the society at large. Therefore, this problem has persistently existed and stakeholders have unconsciously accepted as a given condition.
The most crucial problems of low implementation of PLS are: a) lack of knowledge (customer ‐ external); b) lack of commitment (authority ‐ external); c) existing value system (unsupportive environment ‐ system); d) too much emphasis on business or profit oriented (top management ‐ internal); and e) lack of support (authority ‐ external).
The most urgent solutions to the problems of low implementation of PLS are: a) Education offered to customers and potential customers regarding PLS financing (customer ‐ external); b) management commitment to apply PLS financing as the main mode of financing (top management ‐ internal); c) Protocol and grand strategy (conventional domination ‐ system); d) supportive regulations to foster IEFB and PLS‐based financing (authority ‐ external); and e) political commitment, political will and political courage to support the development of IEFB and PLS financing (authority – external).
Policies and grand strategies that should be implemented to stimulate PLS financing are: a) Product development (grand strategies); b) Fair treatment (policies); c) Service improvement (grand strategies); d) Market mapping (grand strategies); and e) Professionalism (policies).
The levels of agreements among respondents, reflected by Kendall’s coefficient of concordance W, are generally low, with Islamic bankers show higher rater agreement than that of Experts. However, the priority of choices shows greater agreement among respondents, especially among Islamic bankers.
5.2 Recommendation
PLS financing should become the main and dominant mode of finance in Islamic banking, since it provides greater macro‐economic benefits to the economy and society as a whole in terms of reducing inflation, stabilizing the economy, catalyzing real sector growth, reducing unemployment, promoting justice and equality, as well as improving the welfare of society in general. Therefore, the authority (the Government and Bank Indonesia) should take this problem seriously in order to optimize the benefits of PLS‐based finance in the nationwide financial system. This implies that PLS‐based finance should not only be the principle mode
39
of financing in Islamic banking, but also in the entire Islamic financial system and Islamic monetary system.
The bottom line strategies to stimulate and improve the implementation of PLS‐based finance are to create supply, to create demand and to gain support. Supply can be created by the innovation of competitive PLS‐based Islamic financial products and services. Demand can be created by effective education, socialization, communication, and marketing of Islamic finance and banking. Moreover, supports could be obtained from real government commitment and support in all areas/sectors, the implementation of PLS‐based sovereign sukuks, and the implementation of PLS‐based monetary instruments.
REFERENCES
Algaoud, LM and MK Lewis. (2001). Perbankan syariah. [translation], Jakarta: Serambi.
Al‐Jarhi, MA. (2002). ‘Islamic finance: an efficient and equitable option’. mimeo, Jeddah: Islamic Research and Training Institute.
Ascarya. (2009). ‘The determinants of inflation under dual monetary system in Indonesia’. Working Paper. Jakarta: Bank Indonesia.
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42
APPENDIX 1
Lack of PLS Financing
I n t e r n a l E x t e r n a l
Customer
S y s t e m
Authority
B.O.C./B.O.D.
Human Resource
Technical
Lack of Understanding Business Oriented
Target Oriented Lack of Knowledge & Skill
Averse to Risk
Averse to Effort
Less Applicable Higher Risk
Lack of Knowledge
Low Demand
Lack of Understanding
Lack of Support
More Complicated
Lack of Incentive Averse to Risk
Averse to Risk
Lack of Commitment
Lack of Commitment
Commitment
Selection
Simplification
Commitment
Communication
Support
Education
P o l i c i e s
Regulation Incentive
Lack of Management Tools
Directed Mkt Driven
Fair TreatmentShariah Compliance
Society
Diversity Lack/Lost of Trust Lack of Perception
I n t e r n a l E x t e r n a l S y s t e m
S o l u t i o n s
Floating Majority
Union & Cooperation
Protocol & Grand Strategy
Law & Regulation
Gradual & SustainableProfessionalism
B.O.C./B.O.D. Society
Fit & Proper
Reward & Punishment
Human Resource
Improvement
Technical
InnovationIT & SOP
Authority
Customer
Promotion
Da’wah Education
Incentive
Conv. Dominant
Economic Strengthening
Unsupportive Envrnmnt
InfrastructureAlternative Islamic System
Conv. Competition
Increase ShareImprove Standard
Diversification
Lack of Knowledge
Conv. Dominant
Unsupportive Envrnmnt
Conv. Competition
Politics
Infrastructure
Institution
Service
Thought & Ideology
Economy
Rule
Product
Instrument
Social
ValueCulture
S t r a t e g i e s
New Image Program
Service ImprovementProgram
New Market Mapping
Product DevelopmentProgram
Socialization & Communication Program
43
Figure 4.1 Conceptual Framework
Figure 4.2 ANP Network
Figure 4.3 Samples of Simplified Pair‐wise Questionnaires
44
Table 4.1 Overall iBANKERS Geometric Mean Results
Name Normalized By Cluster
Limiting Name Normalized By Cluster
Limiting Name Normalized By Cluster
Limiting
ASPECT
Internal 0.52283 0.014865 System 0.29038 0.008256 External 0.1868 0.005311
INTERNAL PROBLEMS SYSTEM PROBLEMS EXTERNAL PROBLEMS
H Resource 0.28146 0.032333 Conv.Competition 0.28356 0.032064 Authority 0.4376 0.049132
Technical 0.31976 0.036733 Conv.Dominant 0.4064 0.045954 Customer 0.39181 0.043991
Top Mgt 0.39879 0.045812 Unsupportive Env. 0.31004 0.035058 Society 0.17058 0.019152
TOP MANAGEMENT PROBLEMS CONV.COMPETITION PROBLEMS SOCIETY PROBLEMS
Averse Risk 0.19268 0.001069 Institution 0.0881 0.000342 Diversity 0.11902 0.000276
Business Oriented 0.28803 0.001598 Instrument 0.25554 0.000992 L Knowledge 0.37732 0.000875
L Commitment 0.19737 0.001095 Product 0.40443 0.00157 L Perception 0.32773 0.00076
L Understanding 0.32192 0.001786 Service 0.25193 0.000978 L.of Trust 0.17594 0.000408
HUMAN RESOURCE PROBLEMS CONV.DOMINANT PROBLEMS AUTHORITY PROBLEMS
Effort Averse 0.22503 0.000881 Economy 0.33879 0.001885 L.Commitment 0.3446 0.00205
L.Know&Skill 0.27816 0.001089 Politics 0.19033 0.001059 L.Incentive 0.19818 0.001179
Risk Averse 0.19336 0.000757 Social 0.17416 0.000969 L.Support 0.24054 0.001431
Target Oriented 0.30345 0.001188 Thought 0.29673 0.001651 L.Understanding 0.21668 0.001289
TECHNICAL PROBLEMS UNSUPPORTIVE ENV. PROBLEMS CUSTOMER PROBLEMS
Complicated 0.23994 0.001067 Culture 0.25512 0.001083 Averse to Risk 0.22452 0.001196
Higher Risk 0.22689 0.001009 InfraStructure 0.19694 0.000836 Floating Majority 0.21419 0.001141
Less Applicable 0.27614 0.001228 Rule 0.22968 0.000975 L.Knowledge 0.45485 0.002423
No Mgt Tools 0.25703 0.001143 Value 0.31826 0.001351 Low Demand 0.10644 0.000567
INTERNAL SOLUTION SYSTEM SOLUTIONS EXTERNAL SOLUTIONS
S.H Resource 0.27121 0.031156 S.Conv.Competition 0.28396 0.032109 S.Authority 0.42954 0.048227
S.Technical 0.32393 0.037212 S.Conv.Dominant 0.41525 0.046955 S.Customer 0.39409 0.044247
S.Top Mgt 0.40486 0.04651 S.Unsupportive Env. 0.3008 0.034013 S.Society 0.17636 0.019801
TOP MANAGEMENT SOLUTIONS CONV.COMPETITION SOLUTIONS SOCIETY SOLUTIONS
Fit&Proper 0.30984 0.001745 Diversification 0.30898 0.001201 Communication 0.51877 0.001244
I.Commitment 0.44158 0.002487 Improve Std. 0.47312 0.001839 Da'wah 0.24562 0.000589
Reward&Punish 0.24858 0.0014 Incr.Share 0.21791 0.000847 S. Education 0.23561 0.000565
HUMAN RESOURCE SOLUTIONS CONV.DOMINANT SOLUTIONS AUTHORITY SOLUTIONS
HR.Improvement 0.46117 0.00174 Econ.Strengthening 0.1956 0.001112 E.Commitment 0.41308 0.002412
HR.Incentive 0.2987 0.001127 G.Strategy 0.55954 0.003181 Regulation 0.39082 0.002282
Selection 0.24013 0.000906 Union/Coop 0.24485 0.001392 Support 0.1961 0.001145
TECHNICAL SOLUTIONS UNSUPPORTIVE ENV. SOLUTIONS CUSTOMER SOLUTIONS
Innovation 0.27763 0.001251 Alt.Islamic System 0.2974 0.001225 C.Education 0.44588 0.002389
IT & SOP 0.46982 0.002117 Infrastructure 0.26973 0.001111 Incentive 0.18813 0.001008
Simplification 0.25255 0.001138 Law/Regn 0.43287 0.001783 Promotion 0.36599 0.001961
POLICIES STRATEGIES
Directed Mkt Drvn 0.22178 0.023144 Mkt Mapping 0.24371 0.025433
Fair Treatment 0.23599 0.024627 New Image 0.11094 0.011577
Gradual&Sustain 0.16219 0.016926 Product Dev 0.30511 0.031841
Professionalism 0.23442 0.024463 Service Improve 0.23662 0.024693
Shariah Complance 0.14563 0.015197 Sos.Comm.Prog. 0.10362 0.010814
45
Table 4.2 Overall EXPERTS Geometric Mean Results
Name Normalized By Cluster
Limiting Name Normalized By Cluster
Limiting Name Normalized By Cluster
Limiting
ASPECT
Internal 0.29692 0.008442 System 0.34999 0.009951 External 0.35309 0.010039
INTERNAL PROBLEMS SYSTEM PROBLEMS EXTERNAL PROBLEMS
H Resource 0.3197 0.036167 Conv.Competition 0.31636 0.035919 Authority 0.39373 0.044713
Technical 0.29739 0.033643 Conv.Dominant 0.28307 0.032139 Customer 0.40565 0.046067
Top Mgt 0.38291 0.043318 Unsupportive Env. 0.40057 0.04548 Society 0.20062 0.022783
TOP MANAGEMENT PROBLEMS CONV.COMPETITION PROBLEMS SOCIETY PROBLEMS
Averse Risk 0.26864 0.001409 Institution 0.16142 0.000702 Diversity 0.12545 0.000346
Business Oriented 0.29438 0.001544 Instrument 0.25592 0.001113 L Knowledge 0.25925 0.000715
L Commitment 0.27645 0.00145 Product 0.31892 0.001387 L Perception 0.25018 0.00069
L Understanding 0.16053 0.000842 Service 0.26374 0.001147 L.of Trust 0.36512 0.001007
HUMAN RESOURCE PROBLEMS CONV.DOMINANT PROBLEMS AUTHORITY PROBLEMS
Effort Averse 0.24817 0.001087 Economy 0.28854 0.001123 L.Commitment 0.30089 0.001629
L.Know&Skill 0.17785 0.000779 Politics 0.20349 0.000792 L.Incentive 0.15811 0.000856
Risk Averse 0.32717 0.001433 Social 0.18063 0.000703 L.Support 0.28814 0.00156
Target Oriented 0.2468 0.001081 Thought 0.32734 0.001274 L.Understanding 0.25286 0.001369
TECHNICAL PROBLEMS UNSUPPORTIVE ENV. PROBLEMS CUSTOMER PROBLEMS
Complicated 0.38856 0.001583 Culture 0.28763 0.001584 Averse to Risk 0.24727 0.001379
Higher Risk 0.2813 0.001146 InfraStructure 0.17323 0.000954 Floating Majority 0.29855 0.001665
Less Applicable 0.10825 0.000441 Rule 0.16906 0.000931 L.Knowledge 0.33369 0.001861
No Mgt Tools 0.22189 0.000904 Value 0.37007 0.002038 Low Demand 0.12049 0.000672
INTERNAL SOLUTION SYSTEM SOLUTIONS EXTERNAL SOLUTIONS
S.H Resource 0.32097 0.036311 S.Conv.Competition 0.31265 0.035498 S.Authority 0.39304 0.044635
S.Technical 0.29624 0.033513 S.Conv.Dominant 0.2878 0.032677 S.Customer 0.41262 0.046858
S.Top Mgt 0.38279 0.043304 S.Unsupportive Env. 0.39955 0.045364 S.Society 0.19434 0.02207
TOP MANAGEMENT SOLUTIONS CONV.COMPETITION SOLUTIONS SOCIETY SOLUTIONS
Fit&Proper 0.22178 0.001163 Diversification 0.31317 0.001346 Communication 0.39469 0.001055
I.Commitment 0.52136 0.002734 Improve Std. 0.42299 0.001818 Da'wah 0.32286 0.000863
Reward&Punish 0.25686 0.001347 Incr.Share 0.26384 0.001134 S. Education 0.28245 0.000755
HUMAN RESOURCE SOLUTIONS CONV.DOMINANT SOLUTIONS AUTHORITY SOLUTIONS
HR.Improvement 0.32932 0.001448 Econ.Strengthening 0.14004 0.000554 E.Commitment 0.3337 0.001804
HR.Incentive 0.37548 0.001651 G.Strategy 0.49671 0.001965 Regulation 0.38975 0.002107
Selection 0.2952 0.001298 Union/Coop 0.36325 0.001437 Support 0.27654 0.001495
TECHNICAL SOLUTIONS UNSUPPORTIVE ENV. SOLUTIONS CUSTOMER SOLUTIONS
Innovation 0.27667 0.001123 Alt.Islamic System 0.30007 0.001648 C.Education 0.52159 0.002959
IT & SOP 0.32299 0.001311 Infrastructure 0.24854 0.001365 Incentive 0.2593 0.001471
Simplification 0.40034 0.001625 Law/Regn 0.45138 0.002479 Promotion 0.21911 0.001243
POLICIES STRATEGIES
Directed Mkt Drivn 0.16283 0.016993 Mkt Mapping 0.19482 0.020331
Fair Treatment 0.28759 0.030012 New Image 0.22554 0.023537
Gradual&Sustain 0.17426 0.018185 Product Dev 0.25386 0.026492
Professionalism 0.19327 0.020169 Service Improve 0.20195 0.021075
Shariah Complance 0.18206 0.018999 Sos.Comm.Progm 0.12383 0.012923
46
Table 4.3 Overall iBANKERS + EXPERTS Geometric Mean Results
Name Normalized By Cluster
Limiting Name Normalized By Cluster
Limiting Name Normalized By Cluster
Limiting
ASPECT
Internal 0.40588 0.01154 System 0.3304 0.009394 External 0.26372 0.007498
INTERNAL PROBLEMS SYSTEM PROBLEMS EXTERNAL PROBLEMS
H Resource 0.30043 0.03424 Conv.Competition 0.30005 0.034021 Authority 0.41574 0.046925
Technical 0.30842 0.035151 Conv.Dominant 0.34396 0.039 Customer 0.39889 0.045023
Top Mgt 0.39115 0.04458 Unsupportive Env. 0.356 0.040365 Society 0.18537 0.020923
TOP MANAGEMENT PROBLEMS CONV.COMPETITION PROBLEMS SOCIETY PROBLEMS
Averse Risk 0.23268 0.001256 Institution 0.12017 0.000495 Diversity 0.1251 0.000317
Business Oriented 0.29659 0.001601 Instrument 0.25783 0.001062 L Knowledge 0.32123 0.000814
L Commitment 0.23935 0.001292 Product 0.36222 0.001492 L Perception 0.294 0.000745
L Understanding 0.23138 0.001249 Service 0.25977 0.00107 L.of Trust 0.25967 0.000658
HUMAN RESOURCE PROBLEMS CONV.DOMINANT PROBLEMS AUTHORITY PROBLEMS
Effort Averse 0.24071 0.000998 Economy 0.313 0.001478 L.Commitment 0.32313 0.001836
L.Know&Skill 0.23251 0.000964 Politics 0.19737 0.000932 L.Incentive 0.17793 0.001011
Risk Averse 0.25519 0.001058 Social 0.17726 0.000837 L.Support 0.26417 0.001501
Target Oriented 0.27159 0.001126 Thought 0.31237 0.001475 L.Understanding 0.23478 0.001334
TECHNICAL PROBLEMS UNSUPPORTIVE ENV. PROBLEMS CUSTOMER PROBLEMS
Complicated 0.31525 0.001342 Culture 0.27256 0.001332 Averse to Risk 0.23129 0.001261
Higher Risk 0.25957 0.001105 InfraStructure 0.18539 0.000906 Floating Majority 0.25367 0.001383
Less Applicable 0.17876 0.000761 Rule 0.19767 0.000966 L.Knowledge 0.40114 0.002187
No Mgt Tools 0.24642 0.001049 Value 0.34438 0.001683 Low Demand 0.1139 0.000621
INTERNAL SOLUTION SYSTEM SOLUTIONS EXTERNAL SOLUTIONS
S.H Resource 0.29575 0.033707 S.Conv.Competition 0.29993 0.034008 S.Authority 0.41348 0.046669
S.Technical 0.31005 0.035337 S.Conv.Dominant 0.35055 0.039748 S.Customer 0.40462 0.045669
S.Top Mgt 0.3942 0.044927 S.Unsupportive Env. 0.34951 0.03963 S.Society 0.18191 0.020532
TOP MANAGEMENT SOLUTIONS CONV.COMPETITION SOLUTIONS SOCIETY SOLUTIONS
Fit&Proper 0.26397 0.001436 Diversification 0.31156 0.001283 Communication 0.45597 0.001134
I.Commitment 0.48235 0.002624 Improve Std. 0.44779 0.001844 Da'wah 0.28388 0.000706
Reward&Punish 0.25368 0.00138 Incr.Share 0.24065 0.000991 S. Education 0.26015 0.000647
HUMAN RESOURCE SOLUTIONS CONV.DOMINANT SOLUTIONS AUTHORITY SOLUTIONS
HR.Improvement 0.39319 0.001605 Econ.Strengthening 0.16705 0.000804 E.Commitment 0.37392 0.002113
HR.Incentive 0.33782 0.001379 G.Strategy 0.53169 0.002559 Regulation 0.39179 0.002214
Selection 0.26899 0.001098 Union/Coop 0.30127 0.00145 Support 0.23429 0.001324
TECHNICAL SOLUTIONS UNSUPPORTIVE ENV. SOLUTIONS CUSTOMER SOLUTIONS
Innovation 0.28214 0.001207 Alt.Islamic System 0.29825 0.001431 C.Education 0.48897 0.002704
IT & SOP 0.39551 0.001692 Infrastructure 0.25969 0.001246 Incentive 0.22387 0.001238
Simplification 0.32235 0.001379 Law/Regn 0.44206 0.002121 Promotion 0.28716 0.001588
POLICIES STRATEGIES
Directed Mkt Drivn 0.19133 0.019967 Mkt Mapping 0.22065 0.023027
Fair Treatment 0.26165 0.027305 New Image 0.15908 0.016601
Gradual&Sustain 0.16897 0.017633 Product Dev 0.28297 0.02953
Professionalism 0.21406 0.022339 Service Improve 0.22318 0.023291
Shariah Complance 0.16399 0.017114 Sos.Comm.Progm 0.11412 0.011909
47
Table 4.4 Kendall’s Coefficient of Concordance (W)
Respondent Wi Respondent We Respondent Wt
ASPECT
Islamic Bankers 0.390 Experts 0.036 Total 0.162
INTERNAL PROBLEMS SYSTEM PROBLEMS EXTERNAL PROBLEMS
Islamic Bankers 0.020 Islamic Bankers 0.061 Islamic Bankers 0.571
Experts 0.143 Experts 0.082 Experts 0.143
Total 0.061 Total 0.066 Total 0.321
TOP MANAGEMENT PROBLEMS CONV.COMPETITION PROBLEMS SOCIETY PROBLEMS
Islamic Bankers 0.149 Islamic Bankers 0.724 Islamic Bankers 0.520
Experts 0.178 Experts 0.073 Experts 0.310
Total 0.060 Total 0.313 Total 0.289
HUMAN RESOURCE PROBLEMS CONV.DOMINANT PROBLEMS AUTHORITY PROBLEMS
Islamic Bankers 0.065 Islamic Bankers 0.210 Islamic Bankers 0.069
Experts 0.153 Experts 0.118 Experts 0.167
Total 0.014 Total 0.156 Total 0.088
TECHNICAL PROBLEMS UNSUPPORTIVE ENV. PROBLEMS CUSTOMER PROBLEMS
Islamic Bankers 0.004 Islamic Bankers 0.055 Islamic Bankers 0.663
Experts 0.516 Experts 0.220 Experts 0.318
Total 0.121 Total 0.121 Total 0.464
INTERNAL SOLUTION SYSTEM SOLUTIONS EXTERNAL SOLUTIONS
Islamic Bankers 0.020 Islamic Bankers 0.061 Islamic Bankers 0.571
Experts 0.143 Experts 0.082 Experts 0.143
Total 0.061 Total 0.066 Total 0.321
TOP MANAGEMENT SOLUTIONS CONV.COMPETITION SOLUTIONS SOCIETY SOLUTIONS
Islamic Bankers 0.107 Islamic Bankers 0.291 Islamic Bankers 0.388
Experts 0.388 Experts 0.082 Experts 0.020
Total 0.216 Total 0.170 Total 0.143
HUMAN RESOURCE SOLUTIONS CONV.DOMINANT SOLUTIONS AUTHORITY SOLUTIONS
Islamic Bankers 0.184 Islamic Bankers 0.450 Islamic Bankers 0.250
Experts 0.015 Experts 0.679 Experts 0.020
Total 0.073 Total 0.537 Total 0.096
TECHNICAL SOLUTIONS UNSUPPORTIVE ENV. SOLUTIONS CUSTOMER SOLUTIONS
Islamic Bankers 0.143 Islamic Bankers 0.097 Islamic Bankers 0.321
Experts 0.097 Experts 0.143 Experts 0.551
Total 0.017 Total 0.116 Total 0.356
POLICIES STRATEGIES
Islamic Bankers 0.177 Islamic Bankers 0.441
Experts 0.081 Experts 0.134
Total 0.099 Total 0.194
48
APPENDIX 2
PRIORITIES of Internal Problems:
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEAN
INTERNAL PROBLEMSWi = 0.02
Top Mgt
Technical
H Resource
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEAN
INTERNAL PROBLEMSWe = 0.143
Top Mgt
Technical
H Resource
0 0.1 0.2 0.3 0.4 0.5
P1
P2
P3
P4
P5
P6
P7
G MEANTOP
MANAGEMENTWi = 0.149
L Understanding
L Commitment
Business Oriented
Averse Risk0 0.1 0.2 0.3 0.4 0.5 0.6
E1
E2
E3
E4
E5
E6
E7
G MEANTOP
MANAGEMENTWe = 0.178
L Understanding
L Commitment
Business Oriented
Averse Risk
0 0.1 0.2 0.3 0.4 0.5
P1
P2
P3
P4
P5
P6
P7
G MEAN
TECHNICALWi = 0.004
No Mgt Tools
Less Applicable
Higher Risk
Complicated
0 0.1 0.2 0.3 0.4 0.5 0.6
E1
E2
E3
E4
E5
E6
E7
G MEAN
TECHNICALWe = 0.516
No Mgt Tools
Less Applicable
Higher Risk
Complicated
0 0.1 0.2 0.3 0.4 0.5 0.6
P1
P2
P3
P4
P5
P6
P7
G MEANHUMANRESOURCE Wi = 0.065
Target Oriented
Risk Averse
L.Know&Skill
Effort Averse0 0.1 0.2 0.3 0.4 0.5 0.6
E1
E2
E3
E4
E5
E6
E7
G MEANHUMANRESOURCEWe = 0.153
Target Oriented
Risk Averse
L.Know&Skill
Effort Averse
49
PRIORITIES of Internal Solutions:
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEAN
INTERNAL SOLUTIONSWi = 0.02
S.Top Mgt
S.Technical
S.H Resource
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEAN
INTERNALSOLUTIONSWe = 0.143
S.Top Mgt
S.Technical
S.H Resource
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEANS. TOP
MANAGEMENTW = 0.107
Reward&Punish
I.Commitment
Fit&Proper
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEANS. TOP
MANAGEMENTW = 0.388
Reward&Punish
I.Commitment
Fit&Proper
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEAN
S. TECHNICAL Wi = 0.143
Simplification
IT & SOP
Innovation
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEAN
S. TECHNICALWe = 0.097
Simplification
IT & SOP
Innovation
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEANS. HUMANRESOURCEWi = 0.184
Selection
HR.Incentive
HR.Improvement
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEAN
S. HUMANRESOURCEWe = 0.015
Selection
HR.Incentive
HR.Improvement
50
PRIORITIES of System Problems:
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEANSYSTEM
PROBLEMSWi = 0.061
Unsupportive Env.
Conv.Dominant
Conv.Competition
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEAN
SYSTEMPROBLEMSWe = 0.082
Unsupportive Env.
Conv.Dominant
Conv.Competition
0 0.1 0.2 0.3 0.4 0.5
P1
P2
P3
P4
P5
P6
P7
G MEANUNSUPPORTIVEENVIRONMENT
Wi = 0.055
Value
Rule
InfraStructure
Culture
0 0.1 0.2 0.3 0.4 0.5 0.6
E1
E2
E3
E4
E5
E6
E7
G MEANUNSUPPORTIVEENVIRONMENT
We = 0.22
Value
Rule
InfraStructure
Culture
0 0.1 0.2 0.3 0.4 0.5
P1
P2
P3
P4
P5
P6
P7
G MEANCONV.
DOMINANTWi = 0.21
Thought
Social
Politics
Economy
0 0.1 0.2 0.3 0.4 0.5 0.6
E1
E2
E3
E4
E5
E6
E7
G MEANCONV.
DOMINANTWe = 0.118
Thought
Social
Politics
Economy
0 0.1 0.2 0.3 0.4 0.5
P1
P2
P3
P4
P5
P6
P7
G MEANCONV.
COMPETITIONWi = 0.724
Service
Product
Instrument
Institution
0 0.1 0.2 0.3 0.4 0.5 0.6
E1
E2
E3
E4
E5
E6
E7
G MEANCONV.
COMPETITIONWe = 0.073
Service
Product
Instrument
Institution
51
PRIORITIES of System Solutions:
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEAN
SYSTEM SOLUTIONSWi = 0.061
S.Unsupportive Env.
S.Conv.Dominant
S.Conv.Competition
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEANSYSTEM
SOLUTIONSWe = 0.082
S.Unsupportive Env.
S.Conv.Dominant
S.Conv.Competition
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEANS. UNS.
ENVIRONMENTWi = 0.097
Law/Regn
Infrastructure
Alt.Islamic System
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEANS. UNS.
ENVIRONMENTWe = 0.143
Law/Regn
Infrastructure
Alt.Islamic System
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEANS. CONV
DOMINANTWi = 0.45
Union/Coop
G.Strategy
Econ.Strengthening0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEANS. CONV
DOMINANTWe = 0.679
Union/Coop
G.Strategy
Econ.Strengthening
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEANS. CONV
COMPETITIONWi = 0.291
Incr.Share
Improve Std.
Diversification
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEANS. CONV
COMPETITIONWe = 0.082
Incr.Share
Improve Std.
Diversification
52
PRIORITIES of External Problems:
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEAN
EXTERNAL PROBLEMSWi = 0.571
Society
Customer
Authority
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEAN
EXTERNALPROBLEMSWe = 0.143
Society
Customer
Authority
0 0.1 0.2 0.3 0.4 0.5
P1
P2
P3
P4
P5
P6
P7
G MEAN
SOCIETYWi = 0.52
L.of Trust
L Perception
L Knowledge
Diversity
0 0.1 0.2 0.3 0.4 0.5 0.6
E1
E2
E3
E4
E5
E6
E7
G MEANSOCIETYWe = 0.31
L.of Trust
L Perception
L Knowledge
Diversity
0 0.1 0.2 0.3 0.4 0.5
P1
P2
P3
P4
P5
P6
P7
G MEANCUSTOMERWi = 0.663
Low Demand
L.Knowledge
Floating Majority
Averse to Risk
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEANCUSTOMERWe = 0.318
Low Demand
L.Knowledge
Floating Majority
Averse to Risk
0 0.1 0.2 0.3 0.4 0.5
P1
P2
P3
P4
P5
P6
P7
G MEAN
AUTHORITY Wi = 0.069
L.Understanding
L.Support
L.Incentive
L.Commitment
0 0.1 0.2 0.3 0.4 0.5 0.6
E1
E2
E3
E4
E5
E6
E7
G MEANAUTHORITYWe = 0.167
L.Understanding
L.Support
L.Incentive
L.Commitment
53
PRIORITIES of External Solutions:
0 0.2 0.4 0.6 0.8
P1
P2
P3
P4
P5
P6
P7
G MEAN
EXTERNAL SOLUTIONSWi = 0.571
S.Society
S.Customer
S.Authority
0 0.2 0.4 0.6 0.8
E1
E2
E3
E4
E5
E6
E7
G MEAN
EXTERNALSOLUTIONSWe = 0.143
S.Society
S.Customer
S.Authority
0 0.1 0.2 0.3 0.4 0.5 0.6
P1
P2
P3
P4
P5
P6
P7
G MEAN
S. SOCIETYWi = 0.388
S. Education
Da'wah
Communication
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEAN
S. SOCIETYWe = 0.02
S. Education
Da'wah
Communication
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEAN
S. CUSTOMERWi = 0.321
Promotion
Incentive
C.Education
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEANS. CUSTOMERWe = 0.551
Promotion
Incentive
C.Education
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
P1
P2
P3
P4
P5
P6
P7
G MEAN
S. AUTHORITYWi = 0.25
Support
Regulation
E.Commitment
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
E1
E2
E3
E4
E5
E6
E7
G MEANS. AUTHORITYWe = 0.02
Support
Regulation
E.Commitment
54
PRIORITIES of Policies and Strategies:
0 0.1 0.2 0.3 0.4
P1
P2
P3
P4
P5
P6
P7
G MEANPOLICIESWi = 0.177
Shariah Compliance
Professionalism
Gradual&Sustain
Fair Treatment
Directed Mkt Driven
0 0.1 0.2 0.3 0.4
E1
E2
E3
E4
E5
E6
E7
G MEANPOLICIESWe = 0.081
Shariah Compliance
Professionalism
Gradual&Sustain
Fair Treatment
Directed Mkt Driven
0 0.1 0.2 0.3 0.4
P1
P2
P3
P4
P5
P6
P7
G MEANSTRATEGIESWi = 0.441
Sos.Comm.Program
Service Improve
Product Dev
New Image
Mkt Mapping
0 0.1 0.2 0.3 0.4
E1
E2
E3
E4
E5
E6
E7
G MEANSTRATEGIESWe = 0.134
Sos.Comm.Program
Service Improve
Product Dev
New Image
Mkt Mapping
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