Vendor management inventory, as one of the inventory management methods, reduces the cost of inventory in the chain, quick response to customers, increased service level, customer satisfaction, and improves collaboration between the members of supply chain. In this study, a single-product bi-level supply chain model with one manufacturer and several retailers under a vendor management inventory system to select retailers under competitive conditions is investigated. In this study, the retailer selection problem formulated as a Stackelberg game model with consideration of manufacturing as a leader and retailers as followers to help the manufacturer and optimally select his retailers to form a VMI system. The manufacturer delivers the products to the selected retailer at the same time. Also, demand for the product in the retailers market is the decreasing function of price. Due to the prevailing policy and the agreement between the manufacturer and the retailer, the manufacturer is also responsible for managing the retailer's inventory. Therefore, the manufacturer will bear all the costs of maintaining the inventory, whether with himself or the retailer. In return, to accept the responsibility of inventory management by the manufacturer, the retailer pays the manufacturer a fee per unit as inventory costs. The objective of the model is to maximize manufacturing profits at the first level and maximize profits of any retailer at the second level. Model decisions are finding the optimal quantities of wholesale price decisions, product's replenishment cycle time, backorder, retailer selection, and determining whether or not to set up a production line for the manufacturer and retail price quantities for the retailer. In order to validate the proposed model, sensitivity analysis was performed on some parameters. As demonstrated by our numerical studies, the optimal retailer selection can increase the manufacturer's profit by 91% and the selected retailer's profits significantly compared to the non-selection strategy.

Data mining techniques have been used widely in the area of customer relationship management (CRM). In this study, we have applied data mining techniques to address a problem in the business-to-business (B2B) setting. In order to continue its business in a manufacturer-retailer-consumer chain, a manufacturer should improve its relationship with retailers. In this regard, segmentation is a useful tool for identifying groups of similar retailers in order to improve retailer loyalty by developing and implementing segment-specific marketing strategies. Therefore, this study proposes a methodology for retailer segmentation based on the value-based segmentation and the analytical hierarchy process (AHP). The proposed methodology is implemented by using the data of a firm in the hygienic industry in Iran. As a result, having found six groups of retailers and labelled them according to their performance, we provide some possible measures that can be taken in order to improve the relationship between the firm and its retailers.

This paper examines the simultaneous decisions regarding advertising, pricing, and service to supply chain coordination involving one manufacturer and one retailer. Demand is impacted by these decisions, with service playing a crucial role in enhancing customer loyalty and boosting sales. The study employs three well-known game theory approaches—Nash, Stackelberg-retailer, and Cooperative games—to analyze their effects on the supply chain. Optimal strategies for both the manufacturer and the retailer are identified within each approach, and the strategies' results are compared. Results show that the retailer manufacturer, and the entire system achieves higher profits through the Stackelberg-retailer game compared to the Nash game, while the Cooperative game results in the highest overall profits. Finally, the Nash bargaining model is outlined and analyzed to assess opportunities for sharing profits.

Purpose: Managers are one of the important elements of an organization, for this reason, in order to draw the future of the organization, it is necessary for the planners to specify the conditions of their selection and appointment. Therefore, the current research has been done with the aim of identifying and analyzing the components of selecting future principals.Method: In this research, comparative and benchmarking method is used as a prospective approach. This approach is based on the belief that today's advanced organizations/countries can be considered as a model for the future of another organization/countries in their respective subjects. For this, first, the fields of comparison and benchmarking were determined using Brody's four-step comparison method; then the countries of Canada, Finland, Australia, South Africa, and Japan were selected according to the qualitative balance value in the international advanced TEAMS test, human development index, life quality index(health, instruction, and welfare), education quality index, and other scientific-scholarly indexes; finally, by extracting the criteria for the selection and appointment of principals through content analysis and comparison with Iran, the proposed framework for Iran has been presented.Findings: A total of 61 components for the selection of secondary school principals were identified from among the studies conducted in the selected countries in this article. By extracting the commonalities and differences of each of the components among the countries, it was found that the highest index of manager selection and appointment belongs to Japan and the lowest one is related to Finland.Conclusion: There are similarities between the components of selection of principals of secondary schools in Iran and selected countries. In Iran, special attention should be paid to important components such as adherence to religious principles, appropriate personality traits, creativity and innovation, motivation to develop capabilities, professional growth, power of supervision and accountability, social image, leader skills, and purposefulness and foresight.

This work considers cooperative advertising in a manufacturer–retailer supply chain. While the manufacturer is the Stackelberg leader, the retailer is the follower. Using Sethi model it models the dynamic effect of the manufacturer and retailer’s advertising efforts on sale. It uses optimal control technique and stochastic differential game theory to obtain the players’ advertising strategies and the long-run value of the awareness share. Further, it models the relationship between the payoffs of both players and the awareness share. The work shows that with the provision of subsidy the retail advertising effort increases while the manufacturer’s advertising effort reduces. It further shows that the total channel payoff is higher for subsidised retail advertising. However, the subsidy can only be possible if the rate of growth of the manufacturer’s payoff is twice higher than that of the retailer.

The aim of this study was a strain-improvement program for Trichoderma reesei PTCC 5142 by using a combination of UV light and NTG (N-methyl-N'-nitro-N-nitrosoguanidine) for enhanced cellulase production. Following mutagenesis after several rounds, mutant A6: 2 was selected from a total of 6500 colonies. Results obtained after 4 days were: Enzyme activity 1.26 U/ml and 0.82 U/ml for exoglucanase and endoglucanase, respectively. The comparative results showed increased production exoglucanase and endoglucanase by mutant A6: 2 than Trichoderma reesei PTCC 5142 to amount 130% for exoglucanase and 156% for endoglucanase.

Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.

This paper investigates cooperative advertising with local advertising options in a channel with three players including a manufacturer and two retailers. The current study applied the cooperative advertising literature to a case with two options for local advertising investment. To this end, this paper compared two cases of the presence and absence of cooperative advertising, which has almost been neglected in the cooperative advertising literature. The objective of this study is to determine the equilibrium strategy of the retailers' advertising options, players' advertising expenditures, and manufacturers' participation rates on retailers' investment. The aforementioned problem was analyzed as a three-stage game using backward induction. In the fi, rst and second stages, advertising investments of players were analytically determined. In the third stage, the Nash equilibrium pair of advertising options was found through numerical studies. The problem was solved by illustrative examples in two cases of the presence and absence of the cooperative advertising contract. Finally, the conditions for which offering the contract was win-win for all players were identified. Sensitivity analysis was carried out to explain the efficacy of the model.