E-learning websites evaluation and selection is extremely important for the establishment of ef-fective E-learning. The E-learning website selection has crucial importance for the educational sector. The selection of E-learning website problem is generally considered as a Multi-Criteria Decision Making (MCDM) problem which mainly consists of both qualitative and quantitative criteria. The development of an E-learning website mainly depends on the success of the E-learning website selection along with various alternatives. So, for the effective evaluation and se-lection of E-learning websites, a set of selection criteria should be obtained. This paper consists of two steps, the first step is the identification of E-learning website selection criteria, second step provides the linguistic variables against the selection criteria and then fuzzy set theory (FST) is adopted for the calculation of the priority weights of each selection criteria. To show the rela-tive importance of each selection criteria, they ranked according to their global weights.

Consumer’s values, Cultural values, Emotional Values and Word of mouth expressiveness, are good predictors for their buying decision satisfaction. In current study sample of 500 was taken to assess the consumer’s buying decision satisfaction in relation to the importance of their values associated with those decisions. This study also reveals how gender influences buying decision satisfaction. Consumer values have a positive and significant impact on buying decision satisfac-tion. While evaluation on the basis of gender and females have more emotional and word of mouth linkages than males, on the contrary to this, males are more concerned with cultural val-ues, and are less expressive and have a tendency to suppress their emotions while making buy-ing decisions.

Organizing function is the significant component of management guaranteeing the success of construction works. Many studies have been emphasizing on the topic of critical success factors (CSFs) within construction works, yet the results have rarely emphasized examining organizing behaviors within public construction work management; these less researched topics were the aims of this study. To fulfil this research aim, a regression analysis design was employed. Data were collected using questionnaires conducted from 139 professionals involved in public construction works management in Vietnam. The structural equation modelling (SEM) technique with partial least-squares estimation (PLS) was utilized to analyze the data. The results revealed 6 behavioral dimensions (i.e., structure organizing (OR1), authorization organizing (OR2), coordination organizing (OR4), human resource organizing (OR3), job organizing (OR5), responsibility organizing (OR6) to assess organizing function in terms of public construction work management. The study also reveals that structure organizing (OR1), authorization organizing (OR2), coordination organizing (OR4) have significant effects on management effectiveness (ME). In addition, coordination organizing (OR4) acts as the mediator of Human resource organizing (OR3), job organizing (OR5); while responsibility organizing (OR6) indicates an indirect influence through the mediator of OR5. The success of this approach is expected to reinforce the contribution of organizing function and suggest a useful tool for supporting the professionals in enhancing public construction work management.

Monitoring productivity of economic sections of a country would be an important step towards a reliable planning. Developmental decisions based on weaknesses and strengths will guarantee effectiveness, since it will lead to an effective allocation of resources. Among performance measurement approaches, the Data envelopment analysis (DEA), is a model that measures and reports excesses and deficits via analyzing input and output aspects. Aid of this exact and dis-criminating measurement, a proper DEA model applied in this study, can be an efficient instru-ment in fields which need scrutinizing analyses. Industrial productivity analysis of a country is one of such fields. This study applies an instrument developed based on the DEA approach for measuring the industrial productivity of the country. The results obtained, may pave the path for policy-making for economic growth in such a way that enables an effective resources allocation. The applied instrument is a weighted additive model, for which a sufficient number of yearly pe-riods are considered as decision making units (DMUs). The weights included in the model are driven by executing an analytical hierarchy process. After running the model the results demon-strate excesses and deficits in each DMU which can illuminate not only the past performance but also help to plan for the future policies.

This study contributes to the hybrid flow shop due to a lack of consideration of characteristics existing in real-world problems. Prior studies are neglecting identical machines, explicit and sequence-dependent setup times, and machine blocking. We propose a hybrid genetic algorithm to solve the problem. Furthermore, we also propose a mixed-integer linear programming formulation. We note a predominance of the mathematical model for small instances, with five jobs and three machines because of how fast there is convergence. The objective function adopted is to minimize the makespan, and relative deviation is used as a performance criterion. Our proposal incorporates two metaheuristics in this process: a genetic algorithm to generate sequences (the flow shop subproblem) and a GRASP to allocate the jobs in the machines (the parallel machines subproblem). The extensive computational experience carried out shows that the proposed hybrid genetic algorithm is a promising procedure to solve large-sized instances.

Mobile advertising is a perfect tool to build a relationship based on proximity between brand and consumer. It is tactile, interactive, and personalized. As few studies have focused on this con-cept, particularly in the Algerian context, we aim in this research to show the role of mobile ad-vertising on consumer attitudes. After a literature review, an empirical study is conducted among150 students in Tlemcen city. Results, using regression analysis, show that attitude to-wards mobile advertising had no influence on the attitude towards brand and purchase intention.

This study aims to identify and evaluate the critical success factors (CSFs) for international development projects (IDPs) from the perspective of key IDP stakeholders in Afghanistan. The study adopts a quantitative cross-sectional survey research design. Thirty-one success factors were identified and shortlisted through literature reviews and validated by experts and IDP management practitioners. The study's target population is the IPD senior management, IDP team members, and the general public. Amongst 500 questionnaires distributed, a total of 217 were returned and considered for analysis. The result of Exploratory Factor Analysis (EFA) revealed five key CSFs, namely: project cycle management, effective recruitment, continuous learning and adapting, project management method, and clear project goals and objectives. Besides, one-way ANOVA results revealed no statistically significant differences in the ranking of CSFs by the three groups of respondents. However, the post hoc test result indicated that the CSF 'continuous learning and adapting' was relatively rated lower by the general public. The findings of the study would assist the international community, their implementing partners, and IDP management practitioners in better management and successful implementation of IDPs in developing countries. It will also contribute to the CSFs theories and IDPM body of knowledge. The research is the first of its kind to examine the CSFs for IDPs in Afghanistan.

Job precedence can often be seen in various manufacturing process scenarios. For instance, in the context of flow shop scheduling, certain jobs must be processed before a specific job may be executed. Formally, this scenario is known as precedence constraint, which influences the optimal job sequence. Because of this practical significance, in this study, a two-machine flow shop scheduling problem in which transportation times, breakdown time, and weighted jobs are considered. In addition to that, an ordered precedence constraint is considered that ensures a successor job cannot start on any machine before its predecessor job has been done on all machines. This is the first study that deals with flow shop scheduling problems with transportation times, breakdown time, job weights, and precedence constraints altogether, to the best of the author’s knowledge. To solve this problem, a simple and efficient solution methodology is developed that assures optimal or near-optimal solutions effectively. The developed algorithm is tested on various test instances and results are reported, which will be useful for future comparative studies.

Airport Collaborative Decision Making (ACDM) flight scheduling plans rely on accurate predictions of both optimal and reliable aircraft turnaround times, which is one of the most difficult things to complete. In order to account for the effects of randomness and fuzziness on the turnaround process duration, this paper deals with transforming the probability distribution of well-fitted sub-processes into a cumulative density function, which is equivalent to the fuzzy membership function (FMF), and then using goodness-of-fit to determine the fuzzy membership grade of each turnaround sub-process. The turnaround time is calculated using the fuzzy critical path method (FCPM), which is a combination of the Critical Path Method (CPM) and fuzzy set theory. In order to verify this estimate, we created the FMF using historical data and compared it to turnaround times based on FCPM. A linear regression model is used to examine the relationship between arrival delays and the FCPM-based turnaround process. We also use historical data to generate fuzzy sets of different arrival delays using Frankfurt airport data from the summer of 2017 and conclude that delays are positively correlated with the FCPM-based turnaround process.

Scheduling plays an important role in service and manufacturing environments for the delivery of reliable products on time. The scheduling literature reveals that the vast majority of the investigated scheduling problems are for the deterministic case where all parameters of jobs are known in advance and are fixed. However, in some real-world environments, the assumption of fixed parameters of jobs is not valid since job parameters are uncertain. An uncertain parameter can be modelled as having a probability distribution, or it can be modelled as a fuzzy number, or it can be modelled as a random variable within some interval with lower and upper bounds, distribution free. If the uncertain parameter, e.g., processing time, is modelled as a random variable within some lower or upper bounds, it is called interval or bounded processing time. The objective of this paper is to survey the investigated scheduling problems with interval or bounded processing/setup times. The scheduling literature is reviewed, the addressed problems are analyzed, and classified based on shop environments (single machine, parallel machine, flowshop, job shop), performance measures, the approach taken in the papers to solve the considered problem, and interval/bounded processing times or setup times. Some future research opportunities with interval/bounded processing/setup times are presented.