Effect of incentive policy on performance and international competitiveness of fruits, vegetables, and olive oil in Morocco: the case of greenhouse tomatoes, Clementine mandarins, and Maroc-Late oranges

This article presents a brief review of agriculture situation in Morocco and deals with evaluating the effects of Morocco's incentive policy on performance and international competitiveness of four agricultural produce. These products are: green house tomatoes, two citrus fruits: the large orange variety Maroc- Late and the small fruit Clementine, and olive oil. Data of the respective agricultural chains of the four products were collected in two major producing areas of the products, and were used to calculate the Nominal Protection Coefficients (NPC) and the Effective Protection Coefficients (EPC) to evaluate the effects of the local incentive policy, and to calculate the Domestic Resource Cost (DRC) ratios as indicators of international competitiveness of the products. The four NPC ratios, which all were less than one, indicate that the four products are relatively taxed. In addition, the EPC's show that along with the direct taxes on these products, indirect taxes on their inputs are further penalizing these products. All the DRC ratios for the four products were also less than one, indicating a comparative advantage and an efficient allocation of domestic resources. Green house tomatoes had the smallest DRC, 0.36. Those of the two citrus products were a little higher; 0.41 for the Clementine and 0.50 for Maroc- Late. Olive oil had the highest, 0.93, DRC. The low yield per hectare is the main contributor to this relatively modest performance. However, there is a considerable potential for this product if its productivity is improved and the processing industry along with the marketing channels are modernized. Reforms therefore need to be implemented to correct the distortions introduced by the current incentive system which is biased against the export oriented products and is favorable to import substitute products. Such reforms will have to ensure better allocations of domestic resources according to the comparative advantage of the country and to deal with the challenges facing the agricultural sector within the trade agreements signed by Morocco with its trade partners.International Relations/Trade, Marketing,

A Distance-Based Decision in the Credal Level

Belief function theory provides a flexible way to combine information provided by different sources. This combination is usually followed by a decision making which can be handled by a range of decision rules. Some rules help to choose the most likely hypothesis. Others allow that a decision is made on a set of hypotheses. In [6], we proposed a decision rule based on a distance measure. First, in this paper, we aim to demonstrate that our proposed decision rule is a particular case of the rule proposed in [4]. Second, we give experiments showing that our rule is able to decide on a set of hypotheses. Some experiments are handled on a set of mass functions generated randomly, others on real databases

Solitonska teorija smetnje za Kawahara-ovu jednadžbu

The Kawahara equation is studied along with its perturbation terms. The adiabatic dynamics of the soliton amplitude and the velocity of the soliton is obtained by the aid of soliton perturbation theory.Proučavamo Kawahara-ovu jednadžbu s članovima smetnje. Izveli smo adijabatsku dinamiku solitonske amplitude i brzinu solitona primjenom solitonske teorije smetnje

Golden Ball Algorithm for solving Flow Shop Scheduling Problem

The Flow Shop Scheduling Problem (FSSP) is notoriously NP-hard combinatorial optimization problem. The goal is to find a schedule that minimizes the makespan. This paper proposes an adaptation of a new approach called Golden Ball Algorithm (GBA). The proposed algorithm has been never tested with FSSP; it’s based on soccer concept to obtain the optimal solution. Numerical results are presented for 22 instances of OR- Library. The computational results indicate that this approach is practical for small OR-Library instances

Corruption In Morocco-A Sectorial Analysis

Corruption, a pervasive socio-economic problem, has a significant impact on Morocco, reflecting a global challenge that undermines trust in public institutions and hinders development. This phenomenon, often defined as the abuse of public power for private gain, results in widespread citizen distrust of their government and public institutions. Recognizing the critical need to address this issue, Morocco has implemented various strategies and reforms at the institutional and civil society levels to combat corruption. Our study aims to provide a sectoral analysis of corruption in Morocco, assessing the prevalence of corrupt practices and the effectiveness of anti-corruption measures put in place. Using a descriptive methodology, our research relies on secondary data from various databases, including Transparency International's Corruption Perceptions Index (CPI) from 2004 to 2023. This index provides a longitudinal perspective on how perceptions of corruption have evolved in Morocco over the years and serves as a key indicator of the effectiveness of anti-corruption efforts. Our findings indicate that despite these efforts, corruption remains entrenched in several sectors, suggesting that the strategies adopted have not yet succeeded in significantly changing the corruption landscape. This analysis underscores the complexity of fighting corruption in Morocco and highlights the need for continued efforts and innovative strategies to effectively address this endemic problem

Strategic Availability and Cost Effective UAV-based Flying Access Networks: S-Modular Game Analysis

Telecommunication service providers deploy UAVs to provide flying network access in remote rural areas, disaster-affected areas or massive-attended events (sport venues, festivals, etc.) where full set-up to provide temporary wireless coverage would be very expensive. Of course, a UAV is battery-powered which means limited energy budget for both mobility aspect and communication aspect. An efficient solution is to allow UAVs switching their radio modules to sleep mode in order to extend battery lifetime. This results in temporary unavailability of communication feature. Within such a situation, the ultimate deal for a UAV operator is to provide a cost effective service with acceptable availability. This would allow to meet some target Quality of Service while having a good market share granting satisfactory benefits. We construct a duopoly model to capture the adversarial behavior of service providers in terms of their pricing policies and their respective availability probabilities. Optimal periodic beaconing (small messages advertising existence of a UAV) is a vital issue that needs to be addressed, given the UAVs limited battery capacity and their recharging constraints. A full analysis of the game outcome, both in terms of equilibrium pricing and equilibrium availability, is derived. We show that the availability-pricing game exhibits some nice features as it is sub-modular with respect to the availability policy, whereas it is super-modular with respect to the service fee. Furthermore, we implement a learning scheme using best-response dynamics that allows operators to learn their joint pricing-availability strategies in a fast, accurate and distributed fashion.Comment: 10 pages, 14 figure

Hybrid Algorithm for Solving the Quadratic Assignment Problem

The Quadratic Assignment Problem (QAP) is a combinatorial optimization problem; it belongs to the class of NP-hard problems. This problem is applied in various fields such as hospital layout, scheduling parallel production lines and analyzing chemical reactions for organic compounds. In this paper we propose an application of Golden Ball algorithm mixed with Simulated Annealing (GBSA) to solve QAP. This algorithm is based on different concepts of football. The simulated annealing search can be blocked in a local optimum due to the unacceptable movements; our proposed strategy guides the simulated annealing search to escape from the local optima and to explore in an efficient way the search space. To validate the proposed approach, numerous simulations were conducted on 64 instances of QAPLIB to compare GBSA with existing algorithms in the literature of QAP. The obtained numerical results show that the GBSA produces optimal solutions in reasonable time; it has the better computational time. This work demonstrates that our proposed adaptation is effective in solving the quadratic assignment problem