Although e-learning management-related research has been pursued in many parts of the world, there is dearth of research that integrates this concept with the increasing trend of smartphone usage for educational purposes. Furthermore, research in the area shows a general lack of contextualizing the concept in the Middle Eastern context. Therefore, the aim of this study is twofold: (i) to explore the everyday use and role of smartphones among university students in Kuwait; and (ii) to identify if there are any socio-demographic differences in smartphone usage among university students. A questionnaire was completed by 376 students in order to achieve the study objectives. The results showed that students frequently used their smartphones at home and that they sometimes used these phones in recreation places and on transportation, at university, and when walking. Also, they always used their smartphones to complete fourteen non-learning activities, such as making phone calls, using it as a watch and as an alarm clock, and ten learning activities, such as checking their exam schedules, checking class timetables, and checking their grades. Moreover, social networking, learning, privacy, and safety were important reasons offered by students for owning/using smartphones. Furthermore, the study found that at least one of eight socio-demographic variables (i.e., gender, marital status, major/subject, nationality, smartphone brand, using it for the first time, age range, and level of study) has an effect on at least one pattern of smartphone usage. Several recommendations were made based on these findings that may improve the effectiveness of smartphone usage among university students in Kuwait.

The performance of a product is generally characterized by more than one response variable. Hence the management often faces the problem of simultaneous optimization of many response variables. This study was undertaken to simultaneously optimize the surface hardness and case depth of carbonitrided bushes. Even though lots of literature has been published on various methodologies for tackling the multi-response optimization problem, the simultaneous optimization of heat treated properties of carbonitrided bushes are not reported yet. In this research the effect of four factors and two interactions on surface hardness and case depth of carbontirded bushes were studied using design of experiments. Based on the experimental results, the expected values of the heat treated properties of the bushes were estimated for all possible combination of factors. Then the best combination which, simultaneously optimized the response variables, was arrived at using desirability function. The study showed that the optimum combination obtained through desirability function approach not only minimized the variation around the targets of surface hardness and case depth but also was superior to the ones obtained by optimizing the response variables separately. Moreover this study provides a useful and effective approach to design the production process to manufacture bushes with customer specified surface hardness and case depth targets.

Strategic warehouse location-allocation problem is a multi-staged decision-making problem having both numerical and qualitative criteria. In order to survive in the global business scenario by improving supply chain performance, companies must examine the cross-functional drivers in the optimization of logistic systems. A meticulous observation makes evident that strategy warehouse location selection has become challenging as the number of alternatives and conflicting criteria increases. The issue becomes particularly problematic when the conventional concept has been applied in dealing with the imprecise nature of the linguistic assessment. The qualitative decisions for selection process are often complicated by the fact that often it is imprecise for the decision makers. Such problem must be overcome with defined efforts. Fuzzy multi-criteria decision making methods have been used in this research as aids in making location-allocation decisions. The anticipated methods in this research consist of two steps at its core. In the first step, the criteria of the existing problem are inspected and identified and then the weights of the sector and subsector are determined that have come to light by using Fuzzy AHP. In the second step, eligible alternatives are ranked by using TOPSIS and Fuzzy TOPSIS comparatively. A demonstration of the application of these methodologies in a real life problem is presented.

The design of supply chain networks has attracted more attention in recent years according to business and environmental factors.in this paper a multi objective supply chain network design model aims to minimize network costs while satisfying the desired service level, is presented. A fuzzy goal programming (FGP) solution approach based on fuzzy membership function concept is developed to minimize costs and amount of investment while obtain maximum service level. Numerical experiments are conducted to test the efficiency of proposed solution method.

The paper reflects the importance of social networks in the organization of social communication processes in public administration. The essence of communication in public administration and its paradigm is determined. The main differences between public administration and object-oriented public administration are shown. The paper also describes the importance of social networks in the conduct of communication processes compared to other communication channels. Research on the use of social networks in public administration is conducted based on the results of research of the Ukrainian Government and users of the Ukrainian social networks. The main trends in the use of social networks in public administration in Ukraine are described. According to the results of the study, the possible directions of social networks development in public administration in the context of preserving democratic values were proposed.

Cutting force and chip reduction coefficient is the important index of machinability as it determines the power consumption and amount of energy invested in machining actions. It is primarily influenced by process parameters like cutting speed, feed and depth of cut. This paper presents the application of Taguchi’s parameter design to optimize the parameters for individual responses. For multi-response optimization, Taguchi’s quality loss function approach is proposed. In the present investigation, optimal values of cutting speed, feed and depth of cut are determined to minimize cutting force and chip reduction coefficient during orthogonal turning. The effectiveness of the proposed methodology is illustrated through an experimental investigation in turning mild steel workpiece using high speed steel tool.

The development of the internet infrastructure has generated a new phenomenon and lead to some changes in business strategies as it allowed two-way communications among consumers and companies. At present, social media play a key role in communicating information to people around the world and clearly play a vital role in increasing interaction and awareness in an important way. At present, awareness of diseases has disappeared with new methods. Social networking sites like Twitter, Snapchat and Facebook may change the roles the meanings of information delivery and play a superior in that scope. This research investigates the main factors of the power of social media activities (customization, and e-WOM) towards in-creasing Saudi’s awareness on using m-healthcare apps. The results indicate that customization had a positive and direct influence on increasing Saudi’s awareness towards using m-healthcare apps (Brand Awareness). e-WOM had a positive and direct influence on increasing Saudi’s awareness toward using m-healthcare apps (brand awareness), confirming that the power of social media activities was an imperative contributor to brand equity (brand awareness).

Technology transfer, from research and technology organizations (RTOs) toward local industries, is considered as one of important and significant strategies for countries & apos; industrial development. In addition to recover the enormous costs of research and development for RTOs, successful technology transfer from RTOs toward local firms forms technological foundations and develops the ability to enhance the competitiveness of firms. Better understanding of factors influencing process of technology transfer helps RTOs and local firms prioritize and manage their resources in an effective and efficient way to maximize the success of technology transfer. This paper aims to identify important effective factors in technology transfer from Iranian RTOs and provides a comprehensive model, which indicate the interactions of these factors. In this regard, first, research background is reviewed and Cummings and Teng’s model (2003) [Cummings, J. L., & Teng, B.-S. (2003). Transferring R & D knowledge: The key factors affecting knowledge transfer success. Journal of Engineering and Technology Management, 20(1-2), 39-68.] was selected as the basic model in this study and it was modified through suggesting new factors identified from literature of inter-organizational knowledge and technology transfer and finally a Delphi method was applied for validation of modified model. Then, research conducted used Interpretive Structural Modeling (ISM) to evaluate the relationship between the factors of final proposed model. Results indicate that there were twelve factors influencing on technology transfer process from Iranian RTOs to local firms and also the intensity of absorption capability in transferee could influence on the intensity of desorption capability in transferor.

The use of saturated two-level designs is very popular, especially in industrial applications where the cost of experiments is too high. Standard classical approaches are not appropriate to analyze data from saturated designs, since we could only get the estimates of the main factor effects and we would not have degrees of freedom to estimate the variance of the error. In this paper, we propose the use of empirical Bayesian procedures to get inferences for data obtained from saturated designs. The proposed methodology is illustrated assuming a simulated data set.

Flow-shop problems, as a typical manufacturing challenge, have become an interesting area of research. The primary concern is that the solution space is huge and, therefore, the set of feasible solutions cannot be enumerated one by one. In this paper, we present an efficient solution strategy based on a genetic algorithm (GA) to minimize the makespan, total waiting time and total tardiness in a flow shop consisting of n jobs and m machines. The primary objective is to minimize the job waiting time before performing the related operations. This is a major concern for some industries such as food and chemical for planning and production scheduling. In these industries, there is a probability of the decay and deterioration of the products prior to accomplishment of operations in workstation, due to the increase in the waiting time. We develop a model for a flowshop scheduling problem, which uses the planner-specified weights for handling a multi-objective optimization problem. These weights represent the priority of planning objectives given by managers. The results of the proposed GA and classic GA are analyzed by the analysis of variance (ANOVA) method and the results are discussed.