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Article
Publication date: 20 February 2020

Niloufar Ghafari Someh, Mir Saman Pishvaee, Seyed Jafar Sadjadi and Roya Soltani

Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory…

219

Abstract

Purpose

Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory performance cannot be obtained easily. The purpose of this paper is to illustrate the use of interval network data envelopment analysis (INDEA) based on sustainable development indicators under uncertainty.

Design/methodology/approach

In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU) and an INDEA model is used for calculating the efficiency of each medical diagnostic laboratory under imprecise inputs and outputs. The proposed model helps provide managers with effective performance scores for deficiencies and business improvements. The proposed model with realistic efficiency scores can help administrators manage their deficiencies and ultimately improve their business.

Findings

The results indicate that uncertainty can lead to changes in performance scores, rankings and performance classifications. Therefore, the use of DEA models under certainty can be potentially misleading.

Originality/value

The contribution of this study provides useful insights into the use of INDEA as a modeling tool to aid managerial decision-making in assessing efficiency of medical diagnostic laboratories based on sustainable development indicators under uncertainty.

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Article
Publication date: 4 October 2019

Seyed Jafar Sadjadi, Zahra Ziaei and Mir Saman Pishvaee

This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability…

847

Abstract

Purpose

This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability of vaccines, wastages in storage, limited capacity and different priorities for demands.

Design/methodology/approach

This study presents a mixed-integer linear programming (MILP) model and using a robust counterpart approach for coping with uncertainties of model.

Findings

The presented robust model in comparison with the deterministic model has a better performance and is more reliable for network design of vaccine supply chain.

Originality/value

This study considers uncertainty in the network design of vaccine supply chain for the first time in the vaccine context It presents an MILP model where strategic decisions for each echelon and tactical decisions among different echelons of supply chain are determined. Further, it models the difference between high- and low-priority demands for vaccine.

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Article
Publication date: 6 September 2021

Bahareh Shafipour-Omrani, Alireza Rashidi Komijan, Seyed Jafar Sadjadi, Kaveh Khalili-Damghani and Vahidreza Ghezavati

One of the main advantages of the proposed model is that it is flexible to generate n-day pairings simultaneously. It means that, despite previous researches, one-day to n-day…

227

Abstract

Purpose

One of the main advantages of the proposed model is that it is flexible to generate n-day pairings simultaneously. It means that, despite previous researches, one-day to n-day pairings can be generated in a single model. The flexibility in generating parings causes that the proposed model leads to better solutions compared to existing models. Another advantage of the model is minimizing the risk of COVID-19 by limitation of daily flights as well as elapsed time minimization. As airports are among high risk places in COVID-19 pandemic, minimization of infection risk is considered in this model for the first time. Genetic algorithm is used as the solution approach, and its efficiency is compared to GAMS in small and medium-size problems.

Design/methodology/approach

One of the most complex issues in airlines is crew scheduling problem which is divided into two subproblems: crew pairing problem (CPP) and crew rostering problem (CRP). Generating crew pairings is a tremendous and exhausting task as millions of pairings may be generated for an airline. Moreover, crew cost has the largest share in total cost of airlines after fuel cost. As a result, crew scheduling with the aim of cost minimization is one of the most important issues in airlines. In this paper, a new bi-objective mixed integer programming model is proposed to generate pairings in such a way that deadhead cost, crew cost and the risk of COVID-19 are minimized.

Findings

The proposed model is applied for domestic flights of Iran Air airline. The results of the study indicate that genetic algorithm solutions have only 0.414 and 0.380 gap on average to optimum values of the first and the second objective functions, respectively. Due to the flexibility of the proposed model, it improves solutions resulted from existing models with fixed-duty pairings. Crew cost is decreased by 12.82, 24.72, 4.05 and 14.86% compared to one-duty to four-duty models. In detail, crew salary is improved by 12.85, 24.64, 4.07 and 14.91% and deadhead cost is decreased by 11.87, 26.98, 3.27, and 13.35% compared to one-duty to four-duty models, respectively.

Originality/value

The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.

Details

Kybernetes, vol. 51 no. 12
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 20 July 2012

Mostafa Jafari, Roozbeh Hesamamiri, Jafar Sadjadi and Atieh Bourouni

The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet‐based kind of knowledge market by considering both…

987

Abstract

Purpose

The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet‐based kind of knowledge market by considering both social and economic interactions.

Design/methodology/approach

A system dynamics (SD) model is formulated in this study to investigate the dynamic characteristics of complex interactions in a fee‐based online question & answer (Q&A) knowledge market. The proposed model considers the dynamic, non‐linear, asymmetric, and reciprocal relationships between its components, and allows the study of the evolution of the market under assumed conditions.

Findings

Some illustrative results show that: this market is very sensitive to the prices that the customers choose; low‐priced questions are as important as high‐priced ones; gradually increasing experts' proportion of a question's price reduces customer satisfaction and experts' reputation; and training programs for experts result in higher customer satisfaction and researchers' reputation. Furthermore, three types of customers are identified and discussed.

Practical implications

This model can be used to change, manage, and control this market and also helps to design new similar markets. In addition, the proposed model helps to observe the behavior of a market under one or more policies before applying to the real world.

Social implications

Since GA was shut down in 2006, the implications of this research serve as a strategic tool (strategic evaluation software) for understanding and examining the effects of policies for many existing similar Q&A business models. Furthermore, the SD approach can provide new insights into the field of online Q&A knowledge markets and overcome traditional econometric treatment of data for understanding the dynamic behavior of these markets.

Originality/value

Understanding the complex social and economic behavior of Q&A markets is one of the most important concerns for academics and practitioners in the areas of online markets' management. The paper shows how SD can provide attractive insights into the field of online fee‐based knowledge markets based on a qualitative and quantitative modeling. However, the background literature lacks a holistic view of these kinds of markets.

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