International Journal of Supply and Operations Management
Volume:8 Issue: 4, Autumn 2021

Comprehensive economic development is possible only with the balance of interests of business entities and the state, which should be reflected in financial policy. In this case, the transformation of the fiscal system should take into account the stage of economic development of the country. An information array consisting of 36 countries and 10 socio-economic indicators was adopted as the basis for the development of benchmarks for assessing the effectiveness of public resources for the implementation of social policies in the region. The basic features which characterize the state of social orientation of the state policy of the countries in correlation of the spheres of social expenditures and the national system of taxation as social arguments are outlined. Comparative intercluster characteristics are identified and essential differential and baseline characteristics are distinguished. In order to determine the rationality and effectiveness of the current tax system and its impact in the field of social guarantees of the state as well as to increase the degree of social protection of the most needy population, a methodological approach was proposed, using a multidimensional statistical procedure, cluster ranking, which allows the grouping of objects on several grounds simultaneously to define main characteristics of the studied world economies for simulation of “bench marking” – system of financial support of state social expenditures, built on the principle of "human-center" taxation.

Production planning in manufacturing-to-order (MTO) environments has been treated by several researchers as a project scheduling problem, in which customers’ orders are assumed to be different projects that rely on several shared resources. Processing several orders at the same time extends this problem to the resource-constrained multi-project scheduling problem (RCMPSP), while only single projects are considered in the relevant literature. A primary issue for this problem is procurement scheduling, which is handled using integrated project scheduling and material ordering (PSMO) models; however, existing PSMO models do not consider inflation-related costs caused by the ordering times for procurement items. In this paper, MTO production planning is modeled as a resource-constrained multi-project scheduling problem integrated with procurement scheduling under inflation. The proposed model reduced the delay by 72.7% on average and also reduced the delay penalties by 54% on average, compared to the current status of the case study.

This research expands the evolving information body about supply chain management (SC) activities by re-evaluating the links that supply chain integration (SCI) has with financial and operational performance by subjecting under-tier competitive strategy. Quantitative data was gathered from 120 Ghanaian firms and analyzed using descriptive statistics, factor analysis, and regular regression models. The study found that a reasonable level of SCI has already been achieved by firms with average performance but the degree of integration varies greatly when it comes to supplier integration. The study results support the contingency theory and reinforce the latest findings of empirical research that SCI positively affects firm performance. The study further found that internal integration is much more accessible than the integration of consumers and suppliers, and the integration of suppliers is less practiced among Ghanaian firms. The results confirmed that there is a moderate role played by competitive strategy on the relationship between SCI and operational performance.

An effective marketing strategy is essential to get a competitive price to the farmer and the best quality product to the customer. Marketing efficiency (ME) reflects the distribution of price between producer and customer in the fruit supply chain. Farmers mostly use traditional marketing because of fear of the perishability and seasonal nature of the mango, leading to significant price fluctuation. The major scope of this paper is to identify, study and model various factors, and their effect on ME and farmers' profit. After reviewing the available literature and taking experts opinion, eighteen factors were found which directly or indirectly affect ME. Interpretive Structural Modeling (ISM) is an ideal method to determine the key factors that influence ME. The developed ISM model is helpful for farmers to make appropriate decisions in the mango marketing system. After analyzing various factors, the following three factors are primarily responsible for improving ME and farmers' profit. These are lack of government control and assistance in the marketing system, lack of industrial and business approach in farming, and lack of education or low education levels of farmers.

A review of natural disasters that have occurred over recent decades indicates the high costs and casualties caused by them for governments and societies arousing concerns in this field. In this regard, making proper decisions and taking appropriate and real-time measures in each phase of the crisis management cycle can re-duce possible damages during disasters and decrease the vulnerability of society. Hence, the present study aims to propose a fuzzy goal programming (FGP) model in the primary and secondary stages of disasters. The primary stage is aimed at providing disaster-affected areas with relief services and commodities while the purpose of the secondary stage is to provide disaster centers with aid and transfer the injured to relief centers. The proposed mathematical model has been validated using the FGP approach and the NSGAII metaheuristic algorithm and adjusting the parameters of the Taguchi method. The results reveal that the proposed model can improve the programming and flexibility of relief measures in disaster-affected areas in both primary and secondary stages. It is also found that the use of the metaheuristic algorithm facilitates the evaluation and decision-making procedures in big disasters and verifies the efficiency of the algorithm in large dimensions.

In the recent era, Transportation considers the most powerful component of the business logistics system. Likewise, there is an interdependent relationship between the transportation and logistics systems. This paper aims to make a comparative study of logistics transportation problems based on intelligence algorithms. The researchers surveyed the previous studies conducted in the Artificial Intelligent field to solve complex problems. In this research study, the authors focused on techniques that are mostly applied in transportation and logistics systems, especially, Artificial Neural Network, Genetic Algorithm, and Fuzzy Logic models. Also, a proposed model and algorithm was done to obtain customers’ and organizations’ satisfaction. Artificial Neural Network uses as a decision tool that combines the system stat sets and the operation state-dependent sets. As well, the genetic algorithm combines the best parameters as a method to finds the best evaluation solutions. And fuzzy logic uses a fuzzy set to help decision-makers in making the best decisions in multiple fields. Finally, authors recommended to work in two new areas which are FGA, NFGA Algorithms to solve complex and multimodal problems that faces transportation logistics sector.

Supply chain system containing two-level i.e. single-manufacturer and single-retailer is considered, assuming the time varying deterioration rate. The units deteriorate in the warehouse. The system allows the offering of two-level credit. Demand function is the increasing function of retailer’s credit offered to the consumers. Under the agreed contract, manufacturers offer trade credit in the form of delay payment to the retailers such that profit will be shared jointly. Modelling of mathematical computation is done with a view to maximize total joint profit in the supply chain. Next, numerical examples are discussed, followed by sensitivity analysis to validate the outcomes of solution procedure.