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Showing 3 results for Hashemi
DEA common set of weights based on a multi objective Fractional Programming
Seyed Hossein Razavi Hajiagha, Shide Sadat Hashemi, Hannan Amoozad Mahdiraji,
Volume 25, Issue 3 (IJIEPR 2014)
Abstract
Data envelopment analysis operates as a tool for appraising the relative efficiency of a set of homogenous decision making units. This methodology is applied widely in different contexts. Regarding to its logic, DEA allows each DMU to take its optimal weight in comparison with other DMUs while a similar condition is considered for other units. This feature is a bilabial characteristic which optimizes the performance of units in one hand. This flexibility on the other hand threats the comparability of different units because different weighting schemes are used for different DMUs. This paper proposes a unified model for determination of a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights that rank the DMUs and increase the model's discrimination power. Comparison of the proposed method with some of the previously presented models has shown its advantages as a DMUs ranking model.
Coordination of Pricing and Inventory Decisions in a Fresh-product Supply Chain Considering the Competition between New and Old Products
Tahere Hashemi, Ebrahim Teimoury, Farnaz Barzinpour,
Volume 31, Issue 3 (IJIEPR 2020)
Abstract
Retailers selling fresh products often encounter unsold inventory remains at the end of each period. The leftover product has a lower perceived quality than the new product. Therefore, retailers try to influence consumers’ preferences through price differentiation that leads to an internal competition based on product age and prices. This paper addresses the pricing and inventory control problem for fresh products to capture the influence of this competition on the supply chain members’ decisions and profits. A new coordination model based on a return policy with the revenue and cost-sharing contract is developed to improve the profits of independent supply chain members. The supply chain consists of one supplier and one retailer, where consumers are sensitive to the product’s retail price and freshness degree. Firstly, the retailer’s optimal decisions are derived in a decentralized decision-making structure. Then a centralized approach is used to optimize the supply chain decisions from the whole supply chain viewpoint. Eventually, a new coordination contract is designed to convince the members to participate in the coordination model. Numerical examples are carried out to compare the performance of different decision-making approaches. Our findings indicate that the proposed contract can coordinate the supply chain effectively. Furthermore, the coordinated decision-making model is more profitable and beneficial for the whole supply chain compared to the decentralized one. The results also demonstrate that when consumers are more sensitive to freshness, the simultaneous sale of multiple-aged products at different prices is more profitable.

Challenges and Drivers of the Internet of Things in the Supply Chain: A Systematic Review
Zahrasadat Hasheminasab, Esmaeil Mazroui Nasrabadi, Zahra Sadeqi-Arani,
Volume 35, Issue 3 (IJIEPR- In Progress 2024)
Abstract
In today’s world, supply chains must adopt new and intelligent technologies to achieve objectives such as enhancing productivity and performance, competitiveness, and overcoming challenges. The Internet of Things (IoT), as an emerging and transformative technology, is considered one of the most significant technology areas today and has garnered considerable attention across various industries. However, the implementation of IoT at the supply chain (SC) level faces numerous challenges and obstacles, and its acceptance at this level requires specific drivers. To date, no specific classification has been provided for drivers at the SC level, and existing classifications for challenges also need to be reviewed and updated. Given the importance of IoT in SC management, a systematic review at this level is necessary. This article provides a systematic literature review to identify and classify the challenges and drivers of IoT at the SC level. The study reviewed articles published from 2004 to 2023, ultimately identifying and categorizing 92 challenges into 16 categories: financial, standards and government regulations, privacy and security, energy consumption, health issues, hardware and software issues, culture in the SC, lack of knowledge and awareness, poor IT management, coordination in the SC, perception, the Challenge of uncertainty, lack of Plan and Strategy, incompatibility with existing technology, supply Problems, and user acceptance and trust in technology. Additionally, the study identified 4 antecedent drivers (pressures, understanding the benefits, government regulations, government incentives) and 10 consequent drivers (production benefits, improving competitive advantage, inventory management, cost management, improving transparency, efficiency of information flow, development of responsiveness and agility, sustainable development, facilitation of management, and development of cooperation and coordination). Finally, a model for implementing IoT technology in the SC is presented. This model synthesizes the findings from the literature review and offers a practical roadmap for organizations seeking to leverage IoT in their supply chains. By addressing the identified challenges and utilizing the drivers, organizations can effectively integrate IoT technology, thereby enhancing the efficiency, transparency, and overall performance of their SC operations. 

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