This paper proposes a model of performance indicators for Moroccan Textile industry subcontractors. First, the study reports, through a PMQ questionnaire, the KPIs used and deemed relevant by a sample of 82 companies. Second, the weight and hierarchy of various indicators are developed using Analytical Hierarchy Process (AHP) to release a formula for calculating the overall performance. The study shows that outsourcers and Moroccan manufacturers consider compliance with the schedule and the competence and versatility of the production system as a priority. The formula for calculating the overall performance also includes other dimensions such as quality and human resource development. This should facilitate the selection of the contractor and make it more objective.

This research aims to develop a Performance Measurement model for Moroccan automotive suppliers. The study is done in two steps: First, it derives Key Performance Indicators (KPI) from the Performance Measurement Questionnaire (PMQ) and matches their weights by the Analytical Hierarchy Process (AHP). Then, the latter two are applied to build an overall performance formula for these companies. The findings of this work show that the Moroccan automotive suppliers consider the efficiency of the production system and the development of the Human skills as the foremost priority. Also, the global performance formula integrated others dimensions such as safety at work and favorable social climate. This finding should integrate strategies and policies for the decision makers in the Moroccan automotive sector.

<p>Qualities required to provide managers of what make them effective in their actions and behavior within the organizational structure generate, perpetually, the interest of researchers and professionals. Notwithstanding the prevailing conceptions, with reference to the subject of our research, make no consensus between the different stakeholders involved, among others, the college business students. This article is seeking clarification of the business students’ perception about the qualities required to be a good manager. Methodologically, our research was based on a quantitative questionnaire distributed to 500 college business students in Kingdom of Morocco to highlight their appreciation of the qualities needed to be a good manager. Factor analysis was used to analyze the data. Categorization, in the light of the business students’ perception, was made to aggregate, in blocks, the qualities required to be acknowledged as a good manager. As results, five factors underlying the business students’ perception were found. However these factors, when confronted to the literature, explicit certain divergences that could be explained by the students cognitive process problems.</p>

The main purpose of this paper is to present a fusion approach to bridge the period of Global Positioning System (GPS) outages using two proprioceptive sensors that are the Inertial Navigation System (INS) and the odometer in order to assure a continuous localization for land vehicle in urban areas where GPS signal blockage is very often. Odometer and GPS measures are exploited to correct inertial sensor errors. In fact, during GPS availability, INS is integrated with GPS to provide accurate localization solution; whereas during GPS outages, the odometer measurements are used to correct the INS error thereby improving the positioning accuracy and assuring the continuity of navigation solution. The problem of estimation of vehicle localization is realized by Kalman Filter (KF) that merges sensor measurements. The paper thus introduces results from simulation and real data.

Wastewater flow forecasts are key components in the short- and long-term management of sewer systems. Forecasting flows in sewer networks constitutes a considerable uncertainty for operators due to the nonlinear relationship between causal variables and wastewater flows. This work aimed to fill the gaps in the wastewater flow forecasting research by proposing a novel wastewater flow forecasting model (WWFFM) based on the nonlinear autoregressive with exogenous inputs neural network, real-time, and forecasted water consumption with an application to the sewer system of Casablanca in Morocco. Furthermore, this research compared the two approaches of the forecasting model. The first approach consists of forecasting wastewater flows on the basis of real-time water consumption and infiltration flows, and the second approach considers the same input in addition to water distribution flow forecasts. The results indicate that both approaches show accurate and similar performances in predicting wastewater flows, while the forecasting horizon does not exceed the watershed lag time. For prediction horizons that exceed the lag time value, the WWFFM with water distribution forecasts provided more reliable forecasts for long-time horizons. The proposed WWFFM could benefit operators by providing valuable input data for predictive models to enhance sewer system efficiency.