Inventory control of deteriorating items constitutes a large part of the world’s economy and covers various goods including any commodity, which loses its worth over time because of deterioration and/or obsolescence. Vendor managed inventory (VMI), which is a win-win strategy for both suppliers and buyers gains better results than traditional supply chain. In this research, we study an economic order quantity (EOQ) with shortage in form of partial backorder under VMI policy. The model is concerned with multi-item subject to multi-constraint including storage space, time period and budget constraints. Two metaheuristic algorithms, namely Simulated Annealing and Tabu Search, are used to find a near optimal solution for the proposed fuzzy nonlinear integer-programming problem with the objective of minimizing the total cost of the supply chain. Furthermore, the sensitivity analysis of the metaheuristic parameters is performed and five numerical examples containing different numbers of items are conducted in order to evaluate the performance of the algorithms.

A molecular mechanism of the [3+2] cycloaddition has been explored using various DFT theoretical levels. It was found that the reaction proceeds via transition states with different synchronicity, but no intervention of the theoretical possible zwitterionic intermediates. Additionally, regioselectivity of the cycloaddition process has been analysed using vibrational analysis of localised TSs

This paper empirically tried to analyze the effects of education on the gender wage gap in Indonesia and to examine whether globalization could alter such a relationship. We modified a decomposition method for the panel dataset that corresponds to the National Socio-Economic Survey from 1996 to 2016. Overall, we found that schooling could significantly influence the salary discrepancy. We also proved that globalization did matter in explaining the relationship between the educational attainment and the salary gap. Here, it could widen the difference in the remuneration. Based on the results, strengthening the gender-responsive budget at the national government level might be one of the solutions. Basically, it actually started with a new awareness of the budget that was not genderneutral. Thus, the positioning of women in education and decision-making process is very crucial for the future of development.
This paper has been retracted due to conflict of interest

In this study, we incorporate trade credit policy into a joint marketing and pricing problem in which demand rate depends on the length of the credit period provided by the retailer for her customers, marketing expenditure, and selling price. The trade credit policy adopted here is a delayed payment policy in partial form in which the customers must pay a percent of the total purchasing cost at the time of placing an order and can pay the remaining amount later. Shortages are allowed and partially backordered. The main objective of this study is to determine the optimal credit period, marketing expenditure, selling price, and variables of inventory control simultaneously in order to maximize retailer’s total profit. For solving the proposed problem, first an approximation method is applied to simplify the profit function and transform the problem into a constrained Signomial Geometric Programming (SGP) problem, then a global optimization approach is used for solving the model. Finally, a numerical example and sensitivity analysis of the important parameters are conducted to show the effectiveness of proposed approach.

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big Data External and Internal, Innovative Usage, Indexing, and Sources Accuracy. In addition, Artificial intelligence positively affects business performance, including Data Accuracy, Data Transparency, Data Speed, and Creative Thinking and Learning. Moreover, business intelligence has a direct and positive impact on business performance, including Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. In addition, the findings indicate that e-learning which represents system quality, information quality, and self-efficacy has a positive relationship on enhancing business performance. Interestingly, the present findings are inconsistent with those of previous studies showing the variables of interest which have no effect on e-learning and business performance. Taken together, the findings of this study suggest that firms should begin to apply processes related with applying e-learning and developing business performance. The novelty of the present study lies in highlighting the key dimensions of big data, artificial intelligence, and business intelligence when it comes to enhancing e-learning and business performance at Jordanian telecommunications industry.

Risk monitoring and control is often poorly implemented in construction projects because of a failure to monitor and manage identified risks. Construction companies experience significant losses due to project managers' lack of project risk monitoring and control in construction projects. Most studies have concentrated on risk identification, risk assessment, and risk analysis processes while neglecting crucial risk management processes of risk control, risk monitoring, and risk response. The lack of research on these three crucial processes highlights a gap in the literature concerning how these processes can increase the delivery of successful projects. The purpose of this study was to examine whether the utilization of project risk monitoring and control practices was related to project success in construction projects in the United States. An electronic survey instrument was used to collect data from a sample of 50 construction project managers in the Dallas-Fort Worth area in the state of Texas, in the United States. Spearman rho correlation analysis was used to examine the relationship between project risk monitoring and control practices and project success. The results of this study indicated that all project risk monitoring and control practices, including risk reassessment, risk audits, contingency reserves analysis, and risk status meetings, were significantly and positively related to project success in construction projects. One of the recommendations presented in this study was that future research should conduct the same study in developing countries to see if the study’s findings remain the same and generalizable. The study concluded that construction organizations should regularly consider the importance and usage of project risk monitoring and control practices and apply them to improve the success rate of a project.

Detecting how a cutout affects the critical buckling load in circular cylindrical shell is a serious issue for the design of the shells used in marine structures, aerospace and automobile applications. In this paper, buckling behavior of aluminum cylindrical shell with rectangular cutout, subjected to axial pressure was studied by means of finite element simulations. The effects of geometric parameters (R, t, a, b and L) on the first buckling mode capacity of the shell were studied. The effects of these factors and their interaction effects were investigated by combined numerical and statistical analysis. The results show that R/b, t and Rt/b were the main effective factors of critical buckling load. Based on the statistical analysis, a model for prediction of the critical buckling load was obtained with an accuracy equal to 95% (R2, R2 (pred) and R2 (adj)). This equation could be used to predict the critical buckling load of an isotropic circular shell with a rectangular cutout.

In a Pay What You Want (PWYW) setting companies empower their customers to fix the prices buyers voluntarily pay for a delivered product or service. The seller agrees to any price (includ-ing zero) customers are paying. For about ten years researchers empirically investigate customer reactions to and economic outcomes of this pricing method. The present paper distinguishes PWYW from other voluntary payment mechanisms and reviews 72 English- or German-speaking PWYW publications, which appeared between January 2006 and September 2016 and contain 97 independent empirical data sets. Prior PWYW research is structured with the help of a conceptual framework which incorporates payment procedure design, buyer, seller, focal sales object and market context characteristics as factors potentially influencing customer perceptions of the PWYW scheme and their behavioral reactions to PWYW offers. The review discusses both consistent key findings as well as contradictory results and derives recommendations for future empirical PWYW research efforts.

This paper presents a multiobjective ant colony algorithm for the Multi-Depot Vehicle Routing Problem with Backhauls (MDVRPB) where three objectives of traveled distance, traveling times and total consumption of energy are minimized. An ant colony algorithm is proposed to solve the MDVRPB. The solution scheme allows one to find a set of ordered solutions in Pareto fronts by considering the concept of dominance. The effectiveness of the proposed approach is examined by considering a set of instances adapted from the literature. The computational results show high quality results within short computing times.

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.