The use of social media becomes a common habit in today's community and routinely used to interact with the community member. Also, many companies used social media to create a social media community concerning the products and services provided to strengthen the company's brand. This study surveys as many as 231 respondents and data analysis uses the PLS method utilizing smart PLS software. The result reveals that the use of information technology that is getting faster with high-speed data accessibility enhances the intensity of interaction between the community member with the path coefficient value of 0.605. Furthermore, the use of information technology with high-speed data accessibility also increase the satisfaction of movie trailer viewers with the path coefficient value of 0.392 since it can provide excitement and entertainment. Besides, the increased use of information technology provides higher satisfaction to the audience. The results also show that the presence of a social media community could provide satisfaction for movie trailer viewers with a coefficient of 0.332. The availability of films in the community provides excellent interactive communication between users. This research has focused only on the use of information technology in the respondents who watch movie trailers and is limited to a region of East Java province, Indonesia. Further research is required to be performed, which focuses on different types of social media and context and needs to analyze the comment of the film viewer in order to provide a better benefit on the latest films and for the entertainment company.

Suitable selection of various machining parameters for wire electrical discharge machining (WEDM) process heavily relies on the operator’s experience and manufacturer’s technologies because of their numerous and diverse operating ranges. Artificial neural networks have been introduced as an effective tool to predict values of responses and input parameters of different machining processes through forward and reverse modeling approaches respectively. This paper mainly focuses on predicting values of some machining responses, like machining rate, surface roughness, dimensional deviation and wire wear ratio using feed forward back propagation artificial neural network based on six WEDM process parameters, such as pulse on time, pulse off time, peak current, spark gap voltage, wire feed and wire tension. The corresponding reverse model is also developed to recommend the optimal settings of WEDM process parameters for achieving the desired responses according to the requirements of the end users. These modeling approaches are quite efficient to predict the values of machining responses as well as process parameter settings with reduced time and effort which otherwise have to be determined experimentally based on trial and error method. The predicted results are found to be in well congruence with the previously obtained experimental observations.

Several studies in the past have reviewed numerous factors that become the consideration of the customers in performing transactions through online sites. In this study, the researcher investigates whether consumer review, web design and online advertisement variables are important for customers in performing transaction through e-commerce. The results of the study contribute for the providers of the online shopping sites in defining the future strategies. At the same time, the results of the study are also expected to provide contributions for the future studies that focus on the e-commerce from the perspective of consumer review, web design and online advertisement. Furthermore, in analyzing the respondents’ characteristics the researcher runs the SPSS Software and for analyzing the data the researcher runs the PLS 3.0. Then, the survey technique in the form of questionnaire distribution implemented toward the respondents who used to perform transactions through online shopping sites. The research finds that consumer review, web design and online advertisement influence on online purchase intention.

Reliability is one of the most important characteristics of the electrical and mechanical systems with applications in the space communication industries, internet networks, telecommunication systems, power generation systems, and productive facilities. What adds to the importance of reliability in these systems are system complications, nature of competitive markets, and increasing production costs due to failures. This paper investigates availability optimization of a system using both repairable and non-repairable components, simultaneously. The availability-redundancy allocation problems involve the determination of component availability (i.e., life time and repair time of the components) and the redundancy levels that produce maximum system availability. These problems are often subject to some constraints on their components such as cost, weight, and volume. To maximize the availability and to minimize the total cost of the system, a new Mixed Integer Nonlinear Programming (MINLP) model is presented. To solve the proposed model, an improved version of the genetic algorithm is designed as an efficient meta-heuristic algorithm. Finally, in order to verify the efficiency of the proposed algorithm, a numerical example of a system is presented that consists of both repairable and non-repairable components.

The study sought to find out the effect of Technological Readiness Index (TRI) on the adoption of the inDubai application by potential tourists to Dubai. The finding showed a distinct relationship between TRI dimensions and the intention to make use of the inDubai mobile application. The findings of the study further proved that the TRI model as developed by Parasuraman can indeed prove the intention of individuals to adopt a new technology. The study showed that if the first two dimensions (Optimism and Innovation) are present, then a traveler will most likely see the perceived benefits of using the product or technology which in turn will lead to a positive intention to adopt such a technology. The findings also showed that if the last two dimensions (Insecurity and Discomfort) are present then such individuals exhibiting these behaviors are less likely to want to adopt this new technology. This implies that applications like the inDubai application and other similar applications need to address issues that lead to insecurity and discomfort among users if they are to attract a lot of adopters.

The purpose of the present study is to investigate the inter-relationship among the indices that influence on knowledge sharing systems in lessons learned systems. To do this, while reviewing the literature, the researchers first identified the indices affecting KSS; then, they collected the related data through the use of a researcher-devised questionnaire. The results of surveying the indices of knowledge sharing system based on DEMATEL system analysis indicated that there were systemic relationships with the predominant characteristic of impressibility among the indices of the system. Investigating the internal relationship among the indices of knowledge sharing in learned lessons systems showed that in order to create a positive as well as optimum effect on knowledge sharing processes, the first priority should be updating and reinforcing “communication channels”; also, “reward systems and processes” should be reinforced as the second priority in line with the strengthening of the purposeful process of knowledge sharing system.

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.