In this research, we provide a game theoretical approach of new projects financed under musharakah contracts using two types of contracts. The first type is effort based. It compensates the agent for the effort provided regardless of market conditions. The other type of contract is output based where the agent compensation is based solely on output realized. Our intuition is, on one hand, that an agent acceptance of an effort based contract signals a higher ability and therefore merits a higher compensation. On the other hand, an agent opting for an output based signals a reliance on market condition and therefore a lower effort ability meriting lower compensation. We found evidence that an effort based contract offer better compensation to the agent in the form of lower sharing ratio to the financier. This result has two important Islamic implications. First it emphasizes the sentiment of altruism which the financier shows by taking a smaller sharing ratio. Second it emphasizes the sentiment of positive reciprocity which the agent exhibits by providing high effort. Another finding is that an effort based contract offers more span of negotiation than an output based contract. This is an important Islamic concept as the agent has fewer restrictions in terms of negotiations. This paper tackle two problems of information assymetries. Namely it tackles adverse selection and moral hazards.

We develop a formal game-theoretic analysis of the economic (value-adding abilities) and behavioural factors (empathy, emotional excitement, passion) affecting a development bank's choice of private-equity partner when investing into emerging market entrepreneurship. Triple-sided moral hazard (TSMH) problems occur in the form of effort-shirking, since the bank, the PE-manager, and the entrepreneur all contribute to value-creation. The bank's investment choices are crucially affected by a) the relative abilities and the potential level of empathy, excitement and passion that may be generated between a PE-manager and an entrepreneur, and b) the personal emotional attachment that the bank develops towards a PE. The severity of TSMH increases inefficiencies in decision-making. Finally, we consider, in addition to political risk mitigation, an additional impact that the bank may have on PE/E value-creation: the bank may have a coaching/mentoring role. Our analysis has implications for academics and practitioners alike.

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Joint liability aspires to improve micro-loan performance through the support of, and pressure from, the group borrowers. This paper examines how the group composition, in terms of the mixture of kinship (Family) ties and social (Friends and Neighbours) ties among the borrowers, affects the default rates. Using binary logistics regression and three machine learning models, responses from 507 group micro-loan borrowers from four major Moroccan cities were analysed. The results show that the stronger the family and kinship ties are within a loan group, the higher is the default rate. On the contrary, the stronger the social ties are among the group, the lower is the default rate.Other key findings include that the diversion of fund usage from investment to consumption is not found to significantly cause default. Also, loan default can be a consequence of borrowers' strategic choice rather than financial distress.As compared to the female members, male borrowers are found to be causing higher default rates. Interestingly, the gender-related default rates are lower when more of the male borrowers are only socially related. Finally, group size is found to be positively associated with default. Our findings can help microfinance institutions refine their lending policies and guidance on groups' composition and size to reduce default rates.

In this research the authors tried to solve the adverse selection problem in the Mudaraba contracts with respect to the projects privately known prospects. The authors introduced a model of two contracts characterized by an adverse selection index for each contract. They have managed to find that a case of market breakdown can occur because the efficient agent might mimic the inefficient agent. The authors, then, managed to develop a ‘Mimicking Likelihood Index’ whereby one can infer whether a type of an agent has a tendency to mimic the other type. In the same context, the authors developed a “Relative Adverse Selection” index to measure which type of agents has more tendencies to select a specific type of contracts. These findings should help Islamic financial institutions in their agent selection process and hedge its risky Mudaraba contracts

Purpose: There are variety of factors that influence a customer’s selection of a bank in general. However, there is a large gap in the literature that covers a customer decision to choose between an Islamic bank and a conventional one. To this end, we try to fill this gap by using a case study in Morocco to analyse factors contributing to a consumer’s bank selection. Methodology: The analysis presented in the paper is using a case in Morocco and applying an artificial intelligence method using KANO analysis. We apply it in three stages. First, customers preferences are identified and classified according to their impact on customer’s satisfaction. Second, a Satisfaction Increasing Index (SII) is formulated. Third a Dissatisfaction Decreasing Index (DII) is formulated. Findings: The analysis shows that Islamic banking attributes (Provision of profit-loss sharing financing , Operating on Islamic law and principles, Staff knowledge of Islamic banking, Provision of interest-free loans) are required by customers in selecting an Islamic bank as opposed to a conventional bank. However, these requirements do not necessarily contribute to increasing customers’ satisfaction. Significance: To the best of our knowledge, this is perhaps the first paper which uses a Kano analysis in the context of consumers selection of an Islamic or Conventional bank Research Limitations/Implications: This Paper has the main limitation of being conducted only in Morocco. It will be interesting to see how the results would change if the country context is changed. Practical and Social Implications: The findings using these techniques, should help financial institution, whether it be Islamic or conventional banks to tailor their offerings to match consumers requirements.

With advances in information technology, big data, mobile communications, and robotics, digital technologies are increasingly being used in factories around the world. This digital transformation is named industry 4.0. Today, industrial companies are looking at how to adopt this era and implement these technologies 4.0 while improving their performance and generating more profits. The objective of this paper is to help companies to better choose the appropriate digital technologies according to their activities using a multi-experts-multi-criteria decision-making approach under hesitant fuzzy information. The proposed model is a generic model based on Multi-Agent Systems allowing to have an idea of the parameters necessary to apply the adopted approach. The adopted approach allows a better representation of uncertainty and subjectivity of experts’ judgments. It would be of great interest, especially, when exact quantitative data are not available. A real case company example is exposed (automotive company) towards putting into practice the proposed approach.