نشریه مدیریت صنعتی
سال چهاردهم شماره 44 (بهار 1401)

Local content policies in resource-rich countries are a common and consensual approach. However, in reliable scientific sources, the method of formulating and implementing a coherent and effective model for local content policies, by specifying the desired extent and method of intervention of national oil and gas companies, has not been presented. The purpose of this study is to identify the tools and strategies of the National Iranian Gas Company (NIGC) to strengthen the capability of domestic suppliers and prioritize the effectiveness of selected and localized strategies.

For this purpose, first, by reviewing the literature on industrial policy and the experiences of local content policies in oil-rich countries, the tools and strategies were identified. Then, by conducting semi-structured interviews, the cases were adjusted to the company's mission and regulations. Relying on the obtained opinions of experts via adopting the Fuzzy Delphi method, the counted cases were localized. In the end, they were prioritized in terms of importance by employing the Best-Worst multi-criteria decision-making method.

In this study, tools and strategies were coded in eight main axes and 49 tools and strategies. The main areas of importance were reducing the challenges of a macroeconomic and political environment with a weight of 25.9 percent, supporting research and development of technology and innovation with a weight of 13.6 percent, demand and market management with a weight of 12.8 percent, supporting investment in the supply chain Gas industry with a weight of 12.2 percent, coordination and management of external factors with a weight of 11.5 percent, supporting human resource development with a weight of 10.5 percent, creating or strengthening institutions with a weight of 8.1 percent, and finally compensating for information deficiencies 5.5 percent. In this study, the tools and strategies which could be used to reduce macroeconomic and political environmental challenges, with a significant difference, had the highest weight. Regarding the sharp fluctuations in the exchange rate, high financing costs in the country, and restrictions imposed by the country's sanctions seemed reasonable.

Supporting domestic suppliers is a multi-disciplinary issue and requires a coherent and balanced package of tools and solutions. Focusing on one aspect of the issue will not lead to sustainable and reliable results. Solutions such as purchase guarantee, demand management, and reverse engineering have a long history in Iran. In the long run, without additional tools and solutions, such tools lead to backwardness in global technology and reduce the quality and productivity of the domestic gas industry. These strategies, along with supporting the strengthening of technological capabilities, and the strengthening of human resources and other aspects mentioned above, can bring competitive advantage, and pave the way for entering the global value chain for domestic producers. On the other hand, focusing on the technical, engineering, and ingbuild-capacity aspects of this sector will not be effective without considering other aspects necessary for technology development, such as funding, and commercialization requirements.

Today, extensive political, economic, social, and environmental challenges have made designing the gas supply chain network one of the biggest concerns of governments, local states, and global companies. Due to the development of global regulations about environmental concerns, important issues such as sustainability and resilience are needed to be considered in building up supply chain networks. The purpose of this study is to present a mathematical model of a three-echelon gasoline supply chain network, as well as to consider sustainability and resilience approaches.

This is a fundamental and applied study. The mathematical model developed in this research is a two-stage scenario-based multi-objective stochastic one that considers the risks of chain disruption in the form of stochastic scenarios. The disruption considered in this study included supply disruption due to disruption of refinery production capacity, reduction of gasoline imports due to political pressures, disruption of storage facilities, and a demand surge in some customer zones. In order to find robust solutions against scenarios, the Aghezzaf robust optimization method was used, and to find efficient solutions. The Torabi-Hosseini approach was applied to the multi-objective model.

Some of the most important findings of the present study were the quantification of sustainability measures, including the cost of network establishment, environmental effects of CO2 emissions due to the gasoline production and transmission in the network, and the social effects of the network development on the job opportunities, while improving the economic conditions of local areas. The development of a quantitative approach to optimizing various dimensions of the network resilience, including design quality besides the proactive-reactive capabilities against these disturbances were the other finding of this study. Proactive capabilities encompass the establishment of backup storage facilities in critical nodes of the chain and devising backup links for transporting gasoline from backup refineries to the disrupted facilities. In addition, fortification of critical facilities to be operable in the face of disruptions was another proactive option considered in the proposed mathematical model. Reactive capabilities included planning the recovery of disrupted storage tanks and gasoline pipelines.

The proposed model, that quantitatively optimizes all three aspects of sustainability, i.e., economic, social, and environmental, in the gasoline supply chain network, strengthens the network resilience against disruption. Besides, the applicability and efficiency of the proposed approach were shown through a real case study of the gasoline supply chain network design problem in the Khorasan Razavi province of Iran. The obtained results showed that the cost reduction in the whole network along with sustainability and resilience achievements were made in comparison with the current condition of the gasoline supply chain in Khorasan Razavi.

This study introduces Metaphorical Operational Research (MOR) as a new insight into decision making and answers to some criticisms of classical Operational Research (OR). It also shows the ability of MOR to describe pairs trading problems.

The basic assumption of the study is that classic OR is still in the crisis phase before the paradigm shift and no competing paradigm has ever been able to overcome it and provide a complete response to the criticisms. Therefore, in order to respond to some of the criticisms, this study tried to introduce MOR as a new subject in the field of OR. The main focus of this paper was to introduce the problem representation process (as a classic OR critical point) using MOR as a novel approach to problem structuring. Also, in order to show the ability of MOR, this study used pairs trading problems as a case study and binary stars as a source domain. This study used MOR to redefine the pairs trading problems in the form of binary stars and theorize in this field.

The findings of this study show that there are six principles as the main theories of this research in pairs trading problems by looking at it through the window of binary stars. These principles include the principle of the common center of gravity, the principle of historical records, the principle of divergence convergence, the principle of external conditions neutrality, the property of being a pair, and the existence of different classes of pairs.

Two general conclusions can be drawn from the study. First, it is possible to communicate between binary stars and paired shares through MOR. Second, MOR can solve some problems that classical OR cannot address.

The problem of selecting the suppliers along with their Economic Order Quantity (EOQ) has always been an important issue in the Newsvendor model. Multiple qualitative and quantitative criteria are needed to be regarded for making a better supplier selection while performing trade-offs among them. An approach that can take all criteria into account in the selection of suppliers has not been developed yet in the Newsvendor model. Multiple criteria decision-making (MCDM) can be leveraged to make trade-offs among multiple criteria.

This study sought to develop a solution to the Newsvendor problem, accounting for the most significant criteria in supplier selection and product reliability so that the total cost of the chain would be minimized in a multi-product and multi-period model with multiple suppliers. This approach adopted the Bayesian Best Worst Method (BWM), which is one of the MCDM methods, to rank the criteria and also implemented the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritize the suppliers. Then, the suppliers' weights were used as the proposed model inputs. The results obtained from Bayesian BWM validated the effectiveness of the presented approach. The objective function was set in a way that a retailer's profit and weight value of products considering the ranking of suppliers were maximized. The goal was to find optimal order quantity allocating to suppliers. To convert the multi-objective model to a single-objective, the Lp-metric method was used.

To evaluate the derived model, a case study with real data in the electronic supply chain was investigated. The developed model for the Newsvendor problem could find the best suppliers by considering a combination of qualitative and quantitative criteria in selecting them. In this research, the real-world case study was considered in the electronics industry, which allowed the researchers to make a better evaluation of the model.

The obtained results indicated that the retailer uses a combination of suppliers in each period for optimal order allocation to profit-maximizing considering product's reliability and the weight value of products.

Iran's oil reservoirs are operated in cooperation with international oil companies under a contract titled Iran Petroleum Contract (IPC). During the life of the concluded contracts, Iran and oil companies seek to maximize the economic value as well as the value of the cash flow. In this paper, IPC was modeled and the sensitivity of parameters was illustrated.

Contract financial flow was mathematically modeled considerin the physical characteristics of the oil well. This model was simulated using Matlab to evaluate the effect of different values of two parameters of production rate and wages in IPC contracts on the field production process.

Results show that contractors were inclined to lower production rates if the fee per barrel is not set in the proper range (3$-7$). Furthermore, for very low oil prices (under 30$) contractor is at the risk of investment and for higher prices contractor’s share saturates.

All the parameters of the problem including contractual, reservoir, field parameters, oil price, investment costs, and operating costs play a role in the profitability of the project, and knowing contract parameters sensitivity can give Iran a clear view of negotiating the contract.

Increasing sales profits and inventory control leads to productivity in the retailing industry. To minimize inventory costs and reach an optimal order quantity, it is essential to develop a mathematical model for inventory control that is suited to industries. It is a common practice in the retailing industry to consider the shelf space for storing perishable products without taking the warehouse space into account. This study intends to address the issue and touch upon selling high-profit products and signing total minimum commitment contracts with suppliers in order to optimize total costs in the order time.

Reviewing the literature comprehensively, the authors could identify the effective parameters of the model through desk research. On the basis of the defects found, a model was proposed for inventory control considering the new limitations. The particle swarm optimization algorithm was used in MATLAB in order to reach an optimal response in the problem-solving process and a time series analysis was performed by Minitab for demand forecasting.

The proposed model can have applied implications for the industry. The results from the numerical analyses of the model revealed that an effective change in product face and a total minimum commitment contract with suppliers reduce the costs during the planning period. However, using both of them doesn’t always deliver favorable results. When a total minimum commitment contract is signed with the supplier and a change is made in the product face, it is necessary to reconsider the extent of commitment.

This study addressed the utility obtained from the effects of product face changes on the number of demands and number of orders together with total minimum commitment. The quantity of orders was considered according to the shelf space limitations in order to lower the costs. Results showed that the methods adopted to boost sales and lower costs can be profitable for retailers.