Nowadays, companies offer product bundles with special discounts in order to sell more products. However, it is important to note that customers show different levels of loyalties to companies, and each segment of the market has unique features, which influences the customers’ buying patterns. The primary purpose of this paper is to propose a novel model for product bundling in e-commerce websites by using market segmentation variables and customer loyalty analysis. RFM model is employed to calculate customer loyalty. Subsequently, the customers are grouped based on their loyalty levels. Each group is then divided into different segments based on market segmentation variables. The product bundles are determined for each market segment via clustering algorithms. Apriori algorithm is also used to determine the association rules for each product bundle. Classification models are applied in order to determine which product bundle should be recommended to each customer. The results demonstrate that the silhouette coefficient, support, confidence, and accuracy values are higher when both customer loyalty level and market segmentation variables are used in product bundling. Accordingly, the proposed model increases the chance of success in direct marketing and recommending product bundles to customers.

Mokran coasts have good potentials for development and investment, in terms of access to the high seas, geopolitical situation, especially, benefit from certain natural circumstances and history, but for various reasons, this area has no growth, commensurate with the potential. This study is conducted to evaluate investment opportunities in the region, to identify the necessary infrastructures and the promotion of entrepreneurial activities. The method identifies 22 investment opportunities through a comparative study and using best-worst multi-criteria decision method (BWM), and experts’ opinion, the possibility of implementing them are ranked in Mokran. Then, the necessary public infrastructure requirements are ranked in eleven groups with TOPSIS. The results show that, private port sites, loading, warehouses, commercial centers and special areas of fisheries, provide good opportunities for investors, and infrastructure, security, transport, sustainable energy, and the single window government services are the priorities for planning in the public sector.

Inspired by the industries such as food and beverage, metal and steel, as well as petroleum and petrochemical ones, the current study addresses a joint order acceptance and scheduling, lot streaming in a flexible flow shop and batch delivery problem. For maximizing a profit objective function with trading off between the revenue of the accepted orders and the costs incurred, a novel mixed integer linear programming is proposed. This paper develops a hybrid metaheuristic algorithm based on the Genetic Algorithm. In the developed algorithm, (1) a heuristic, (2) a local search, and (3) a restart phase is proposed. To set the appropriate parameters of the algorithms, Taguchi experimental design was applied. The obtained results reveal the appropriate performance of the hybrid genetic algorithm.

Medical tourism industry is an international phenomenon, which most of medical tourists for some reasons such as high costs of treatment, long waiting queues, lack of insurance and lack of access to health care in the origin country, travel long distances to benefit from health care services of destination country. Given the competitive nature of this industry, most countries are designing practical and legal services and planning for their development. For this purpose, this study has been conducted to develop a strategic planning framework for development of medical tourism industry in Yazd province of Iran; because in recent years Yazd has recognized as the health pole by patients in developing countries. In sum, emphasizing on servicing, enhancing and developing specialized treatment centers, has attracted patients from center, south and east of the country as well as Middle East and Central Asia countries. The dominant approach in this study is developmental – practical and also the research method is descriptive, analytical and survey. In order to analyzing the data, the SWOT model and best-worst techniques have been used. In the following, after identifying strategic position of Yazd province in terms of medical tourism industry, the related strategies were formulated and practical results were presented.

In this study, a 3D finite element model of an intact mandible was used for the simulation of the movement of the lower jaw and analysis of the effects of TemporoMandibular Joint (TMJ) prosthesis replacement on the jaw movement. Seven bundles of muscle fibers were inserted in their appropriate positions following anatomical data. Digastric, geniohyoid and lateral pterygoid muscles were considered for opening the mouth while medial pterygoid, superficial masseter, deep masseter and temporalis muscles were used for closing the mouth. Then, the TMJ was replaced by two different types of TMJ prostheses in the same way as in a surgery operation. One of the prostheses was designed based on anatomical shape of the ramus and condyle of the mandible while the other one was taken similar to the commercial TMJ prostheses. Eventually, all three models underwent an opening jaw simulation and produced an identical range of motion while were mismatched in other parameters. The results show that since the anatomical TMJ prosthesis resembles the shape and structure of an intact mandible; therefore, it is more capable of simulating the motion of mandible compared to the commercial TMJ prosthesis. Furthermore, better contact between the anatomical TMJ prosthesis and the mandible leads to lower stress distribution in comparison with the commercial TMJ implant. Finally, as the amount of muscle forces and strain in anatomical TMJ prosthesis replacement are less than the commercial one, the patient needs to make less effort to move the mandible and open the mouth.

Tourism infrastructure development in different regions of the world does not follow a symmetrically equal pattern. Because of the importance of infrastructure in the tourism development, the present research is an attempt to examine the hard elements of tourism infrastructure in different provinces of Iran, using the indicators proposed by Pearce and Wu (2015) [Pearce, P. L. & Wu, M. Y. (2015). Soft infrastructure at tourism sites: identifying key issues for Asian tourism from case studies. Tourism Recreation Research, 40 (1), 120-132.]. To accomplish this, the data registered in the statistical yearbook of the Statistical Center of Iran were investigated. The method of research was analytical survey. To analyze and rank the data collected from the yearbook, VIKOR and TOPSIS methods were employed. The results of the analysis show that Tehran Province was under the best conditions of the Iranian tourism infrastructure, whereas Ilam Province was under the worst condition. The results about the condition of hard tourism infrastructure in the provinces of Iran, next to their tourism potentials, can provide necessary data for the future planning of the industry.

In this paper, a mathematical model for multi-product inventory management in a three-tier supply chain consisting of multi-supplier, a manufacturer, and several retailers is presented. The model determines different factors such as the optimum ordering of the raw materials and the optimal level of the production items with the optimal order of the products by retailers at each level of the chain, with the objective of minimizing inventory management costs in the supply chain. An algorithm is presented to determine the solution of the problem and the implementation of the proposed method is demonstrated using some numerical example.

Job selection and scheduling are among the most important decisions for production planning in today’s manufacturing systems. However, the studies that take into account both problems together are scarce. Given that such problems are strongly NP-hard, this paper presents an approach based on two heuristic algorithms for simultaneous job selection and scheduling. The objective is to select a subset of jobs and schedule them in such a way that the total net profit is maximized. The cost components considered include jobs & apos; processing costs and weighted earliness/tardiness penalties. Two heuristic algorithms; namely scatter search (SS) and simulated annealing (SA), were employed to solve the problem for single machine environments. The algorithms were applied to several examples of different sizes with sequence-dependent setup times. Computational results were compared in terms of quality of solutions and convergence speed. Both algorithms were found to be efficient in solving the problem. While SS could provide solutions with slightly higher quality for large size problems, SA could achieve solutions in a more reasonable computational time.

By advances in information technology and considering the fast pace of innovation in targeted technologies, blended learning with the aim of satisfying the needs of blended learning is composed of online learning and face-to-face learning. The aim of the present paper is to study the impact of blended learning on the relevant factors through a mixed method. The study is considered fundamental in terms of research methodology. The present paper is carried out on students of West Tehran Payame Noor University, Iran through a questionnaire. According to the results, it is concluded from the perspective of students that although blended learning is formed of several factors such as face-to-face learning and virtual learning, this type of learning has significant impact on its constituent elements as well as on relevant factors related to this type of learning. Finally, the effectiveness of blended learning, virtual and face-to-face learning in accordance on their factors were determined and assessed which ultimately led to conclusions and recommendations to advance research objectives.

The purpose of this paper is to measure the effects of intellectual capital components; namely, human capital, structural capital and relational capital on company performance in Iranian auto industry. The study uses a questionnaire consists of 100 questions to cover intellectual capital and company performance in Likert scale and it is distributed among 180 experts in one of Iranian auto industry. Cronbach alphas for intellectual capital components, i.e. human capital, relational capital and structural capital are 0.82, 0.80 and 0.80, respectively. In addition, Cronbach alpha for company performance is 0.82. Using structural equation modeling, the study has determined a positive and meaningful relationship between intellectual capital and company performance. The study has also determined a positive and meaningful relationship between human capital and structural capital. Among components of performance, efficiency maintained the highest effect while innovation represents the minimum effect.