The Framework for the Rational Analysis of Mobile Education (FRAME) model explains mobile learning features as a process in terms of mobile technologies, human learning capacities, and social interaction. It describes various issues of information overload, knowledge navigation, and cooperation in learning. The framework gives insight for development of future mobile devices as well as learning materials, and an appropriate design of learning and teaching strategies for the purpose of mobile education. The proposed study of this paper implements the FRAME model in Iranian banking industry. The study has been implemented among a sample of 160 regular employees who worked for Bank Maskan in province of Alborz, Iran. To validate the questionnaire, we use content validity ratio (CVR) and verify the questionnaire using Cronbach alphas. Using t-student test, the study has determined that the firm was ready to adopt mobile learning in terms of device, social and learner aspects. In our survey, learner aspect was number one priority followed by device and social aspects.

The present study reviews different studies on inventory control of deteriorating items in chain supply published over the period 1963- 2013. The study investigates supply chain of the items in terms of various perspectives. Finally, the summary of the studies is shown in two tables for one-echelon and multi-echelon supply chain including the main information and assumptions of each paper. In the mentioned tables, the papers were classified in terms of the type of demand rate, deterioration rate, solution procedure and findings. It can be said that no analysis on the results was done in the present study and it can be only used as a good reference in the study field for other researchers.

Exchange rates always affect the prices of the imports and export of products and services in which countries are trading with other parts of the world. Therefore, exchange rate calculation is one of the essential issues for making appropriate policies. This research investigates the determinants of trade, i.e. import, export, industrial growth, consumption level and oil prices fluctuation, which bring changes in exchange rate and their influence eventually on balance of payments. Data of defined variables was collected on yearly basis for China and USA for thirty one years. By applying cointegration, it is estimated that there existed a long run relationship in both countries. USA and China had significant and correct signs on the short run dynamic and some of the factors did not. Exchange rate did not granger cause balance of payment and balance of payment did not granger cause exchange rate. In conclusion, we found that determinants of balance of trade could affect the exchange rates, also, these rates had considerable effect (positive or negative) on balance of payments. In this twofold study, we found relationship of exchange rate with selected determinants of trade, and also examined their bilateral effect, and then made contrast of both countries.

This paper analyzes a supply chain, which consists of a manufacturer, a retailer and several suppliers in which the retailer orders jobs to the manufacturer and the suppliers provide the requiring parts. The manufacturer schedules and processes the orders and dispatches them to the retailer either individually or collectively in batches. The manufacturer incurs a penalty cost for each tardy job and a transportation cost for every delivered batch and therefore, searches for a schedule that yields minimum number of tardy jobs and batches. Moreover, the manufacturer tries to optimize its supplying cost through locating the suppliers that offer appropriate release times and costs for manufacturing parts. Since the release times of parts directly affect scheduling of orders, in this research, we develop an integrated mathematical model for the manufacturer that incorporates suppliers & apos; selection issue into the scheduling and batching decisions. Furthermore, we present a heuristic algorithm (greedy algorithm) and also a local search to quickly determine the optimal or near-optimal solutions. The computational analysis shows the importance of the integrated model and also the superiority and effectiveness of the heuristic algorithms.

Population growth and rapid urbanization growth in recent decades have not only led to unbalanced physical expansion of cities, but also contributed to growth and development of cities. The city of Sari in Iran, like many other cities is not immune from these changes. The city population has increased by 16 times over the last fifty years. Therefore, the increasing population growth has created uncontrolled physical expansion in the city. In order to prevent these inefficiencies of urban problems, the present study was accomplished to determine the factors influencing the process of expanding the city of Sari and to find out some solutions to fix and prevent this process. The method used in this study, descriptive–analytical method, to data analysis and Heldern and Shannon entropy model were used. The results show that: 82% of the physical growth of the city during the period 1977-2005 was related to the population growth and the remaining 18 percent, was associated with the horizontal growth. The city sprawl, the metropolitan area of the city had denser structure and the surrounding areas had a more dispersed structure. Also the effects of synthetic and natural factors restricting the city of Sari physical development made the city exorbitance horizontal and linearly developed. According to the findings that could help prevent the horizontal development of the city, it could be said that we could make the city vertically developed rather than horizontal expansion, improvement and renovation of old texture of implementation and more use of the land, filling the empty spaces.

This research aims to study factors influencing the adoption of internet shopping by Iranian consumers by integrating task technology fit (TTF) model and the unified theory of acceptance and usage of technology (UTAUT). The statistical population includes consumers in capital city of Iran, Tehran, who have had at least one experience of internet shopping. The data were collected through questionnaire. A total of 400 questionnaires were distributed and 392 usable questionnaires were returned. SPSS statistical software was used for data analysis .The results show that except for effort expectation, there was a significant and positive relationship between other variables (task technology fit, performance expectation, social impact and facilitating conditions) and internet shopping. In addition, the findings also indicated a significant effect of task features and technology features on task technology fit.

Hsu and Hsu (2013a) established a closed-form solution for an EOQ model with imperfect quality items, inspection errors, shortage backordering, and sales returns, where the customers who return the defective items will receive full price refunds; i.e., the returned items are not replaced with good items. In this note, we extend Hsu and Hsu & apos; s (2013a) work to consider the case that returned items are replaced with good items. A closed-form solution is developed for the optimal order size and the maximum shortage level. Numerical examples are provided to show the differences in the optimal solutions when returned items are replaced, and when they are not.

There is a tremendous growth of the use of the component based software engineering (CBSE) approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s) has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS) components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA)’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP) which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

Herbal Products industry has experienced significant growth in product demand. Therefore, this study aims to identify the factors effecting the actual buying of Herbal Product. This study also examines the moderation effect of perceived risk on the relationship between product safety and intention. Mall intercept survey was used to collect data from six various states in Malaysia. The data is analyzed using Partial Least Squares (PLS) path modeling. The path coefficient results supported the direct influence of intention on actual buying. Similarly, the findings reveal that perceived risk moderate the relationship between product safety and buying intention.

This paper presents a mathematical model to solve a multi-objective decision making supplier selection problem. The proposed problem considers three objective functions: the first objective function minimizes the cost of purchasing the products while the second objective function minimizes the due dates and finally the third objective function maximizes the customer satisfaction. The resulted problem is formulated as mixed integer programming and, therefore, we use invasive weed optimization technique to solve the resulted problem. The performance of the proposed model is compared with NSGA II based on different criteria such as mean ideal distance and quality matrix. The preliminary results indicate that the proposed model performs relatively well compared with alternative method.