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Article
Publication date: 5 May 2015

Yong Zha, Jun Wang, Zhao Linlin and Liang Liang

The purpose of this paper is to consider the following problem: the authors consider a new constructed unit system to indicate the characteristics of the inputs and outputs

Abstract

Purpose

The purpose of this paper is to consider the following problem: the authors consider a new constructed unit system to indicate the characteristics of the inputs and outputs of different decision-making units (DMUs) and propose several modified models to calculate their efficiencies based on overall value judgment and weight restriction in the production process.

Design/methodology/approach

This paper applies principal component analysis (PCA) to analyze the original value judgment information, and the key indices in the production process are extracted. The modified data envelopment analysis (DEA) models are proposed and DEA efficiencies and their projections are calculated.

Findings

By incorporate PCA and DEA, the authors propose new virtual DMUs composed of unique optimal multipliers of each DMU. Crucial indexes are extracted and the weights of inputs and output are ranked through using PCA by taking the preference and value judgments of all DMUs into consideration. Weight constraints from the ranking are utilized to improve the traditional CCR-DEA model. The empirical results validate the feasibility of the approach.

Practical implications

The method can be used in many organizations which have excessive amounts of inputs and outputs variables, such as banks, chain stores, car factory, etc.

Originality/value

This paper presents an integrated methodology of using PCA and DEA for considering the preferences of the inputs and outputs and value judgment of all DMUs and ranks the importance of the indicators from the overall perspectives.

Details

Kybernetes, vol. 44 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 22 March 2021

Mirpouya Mirmozaffari, Elham Shadkam, Seyyed Mohammad Khalili, Kamyar Kabirifar, Reza Yazdani and Tayyebeh Asgari Gashteroodkhani

Cement as one of the major components of construction activities, releases a tremendous amount of carbon dioxide (CO2) into the atmosphere, resulting in adverse…

Abstract

Purpose

Cement as one of the major components of construction activities, releases a tremendous amount of carbon dioxide (CO2) into the atmosphere, resulting in adverse environmental impacts and high energy consumption. Increasing demand for CO2 consumption has urged construction companies and decision-makers to consider ecological efficiency affected by CO2 consumption. Therefore, this paper aims to develop a method capable of analyzing and assessing the eco-efficiency determining factor in Iran’s 22 local cement companies over 2015–2019.

Design/methodology/approach

This research uses two well-known artificial intelligence approaches, namely, optimization data envelopment analysis (DEA) and machine learning algorithms at the first and second steps, respectively, to fulfill the research aim. Meanwhile, to find the superior model, the CCR model, BBC model and additive DEA models to measure the efficiency of decision processes are used. A proportional decreasing or increasing of inputs/outputs is the main concern in measuring efficiency which neglect slacks, and hence, is a critical limitation of radial models. Thus, the additive model by considering desirable and undesirable outputs, as a well-known DEA non-proportional and non-radial model, is used to solve the problem. Additive models measure efficiency via slack variables. Considering both input-oriented and output-oriented is one of the main advantages of the additive model.

Findings

After applying the proposed model, the Malmquist productivity index is computed to evaluate the productivity of companies over 2015–2019. Although DEA is an appreciated method for evaluating, it fails to extract unknown information. Thus, machine learning algorithms play an important role in this step. Association rules are used to extract hidden rules and to introduce the three strongest rules. Finally, three data mining classification algorithms in three different tools have been applied to introduce the superior algorithm and tool. A new converting two-stage to single-stage model is proposed to obtain the eco-efficiency of the whole system. This model is proposed to fix the efficiency of a two-stage process and prevent the dependency on various weights. Converting undesirable outputs and desirable inputs to final desirable inputs in a single-stage model to minimize inputs, as well as turning desirable outputs to final desirable outputs in the single-stage model to maximize outputs to have a positive effect on the efficiency of the whole process.

Originality/value

The performance of the proposed approach provides us with a chance to recognize pattern recognition of the whole, combining DEA and data mining techniques during the selected period (five years from 2015 to 2019). Meanwhile, the cement industry is one of the foremost manufacturers of naturally harmful material using an undesirable by-product; specific stress is given to that pollution control investment or undesirable output while evaluating energy use efficiency. The significant concentration of the study is to respond to five preliminary questions.

Article
Publication date: 1 May 1990

Sushil

A systems perspective of waste management allows an integratedapproach not only to the five basic functional elements of wastemanagement itself (generation, reduction…

3273

Abstract

A systems perspective of waste management allows an integrated approach not only to the five basic functional elements of waste management itself (generation, reduction, collection, recycling, disposal), but to the problems arising at the interfaces with the management of energy, nature conservation, environmental protection, economic factors like unemployment and productivity, etc. This monograph separately describes present practices and the problems to be solved in each of the functional areas of waste management and at the important interfaces. Strategies for more efficient control are then proposed from a systems perspective. Systematic and objective means of solving problems become possible leading to optimal management and a positive contribution to economic development, not least through resource conservation. India is the particular context within which waste generation and management are discussed. In considering waste disposal techniques, special attention is given to sewage and radioactive wastes.

Details

Industrial Management & Data Systems, vol. 90 no. 5
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 23 November 2018

Sara Yousefi, Reza Farzipoor Saen and Seyed Shahrooz Seyedi Hosseininia

To manage cash flow in supply chains, the purpose of this paper is to propose inverse data envelopment analysis (DEA) model.

Abstract

Purpose

To manage cash flow in supply chains, the purpose of this paper is to propose inverse data envelopment analysis (DEA) model.

Design/methodology/approach

This paper develops an inverse range directional measure (RDM) model to deal with positive and negative values. The proposed model is developed to estimate input and output variations such that not only efficiency score of decision making unit (DMU) remains unchanged, but also efficiency score of other DMUs do not change.

Findings

Given that auto making industry deals with huge variety and volumes of parts, cash flow management is so important. In this paper, inverse RDM models are developed to manage cash flow in supply chains. For the first time, the authors propose inverse DEA models to deal with negative data. By applying the inverse DEA models, managers distinguish efficient DMUs from inefficient ones and devise appropriate strategies to increase efficiency score. Given results of inverse integrated RDM model, other combinations of cash flow strategies are proposed. The suggested strategies can be taken into account as novel strategies in cash flow management. Interesting point is that such strategies do not lead to changes in efficiency scores.

Originality/value

In this paper, inverse input and output-oriented RDM model is developed in presence of negative data. These models are applied in resource allocation and investment analysis problems. Also, inverse integrated RDM model is developed.

Article
Publication date: 11 July 2022

Sunil Kumar Jauhar, Hossein Zolfagharinia and Saman Hassanzadeh Amin

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors…

Abstract

Purpose

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

Design/methodology/approach

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

Findings

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

Research limitations/implications

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

Practical implications

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

Originality/value

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 4 March 2022

Wang Jianhong

The purpose of this paper is to extend the authors’ previous contributions on aircraft flutter model parameters identification. Because closed-loop condition is more…

Abstract

Purpose

The purpose of this paper is to extend the authors’ previous contributions on aircraft flutter model parameters identification. Because closed-loop condition is more widely used in today’s practice, a closed-loop stochastic model of the aircraft flutter test is constructed to model the aircraft flutter process, whose inputoutput signals are all corrupted by the observed noises. Through using a rational transfer function, the equivalent property between the aircraft flutter model parameters and polynomial coefficients is established, and then the problem of aircraft flutter model parameters identification is turned to one closed-loop identification problem. An iterative identification algorithm is proposed to identify the unknown polynomial coefficients, being benefit for the latter flutter model parameter identification. Furthermore, as the closed-loop output corresponds to the flutter amplitude, so from the point of the minimization with respect to the variance of the closed-loop output, the optimal input signal and optimal feedback controller are all derived to achieve the zero flutter, respectively, for example, the optimal input spectrum and the detailed form for optimal feedback controller.

Design/methodology/approach

First, model parameter identification for aircraft flutter is reviewed as one problem of parameter identification and this aircraft flutter model corresponds to one closed-loop stochastic model, whose input signal and output are corrupted by external noises. Second, for aircraft flutter closed-loop statistical model with statistical noise, an iterative identification algorithm is proposed to identify the unknown model parameters. Third, from the point of minimizing with respect to the variance of the closed-loop output, the optimal input signal and optimal feedback controller are all derived to achieve the zero flutter, respectively, for example, the optimal input spectrum and the detailed form for optimal feedback controller.

Findings

This aircraft flutter model corresponds to one closed-loop stochastic model, whose input signal and output are corrupted by external noises. Then, identification algorithm and optimal input signal design are studied for aircraft flutter model parameter identification with statistical noise, respectively. It means the optimal input signal and optimal feedback controller are useful for the aircraft flutter model parameter identification within the constructed new closed-loop stochastic model.

Originality/value

To the best of the authors’ knowledge, this problem of the model parameter identification for aircraft flutter is proposed by their previous work, and they proposed many identification strategies to identify these model parameters. This paper proposes a new closed-loop stochastic model to construct the aircraft flutter test, and some related topics are considered about this closed-loop identification for aircraft flutter model parameter identification in the framework of closed-loop condition.

Details

Aircraft Engineering and Aerospace Technology, vol. 94 no. 7
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 1 December 2001

Graham J. Treloar, Peter E.D. Love and Olusegun O. Faniran

Embodied energy is the total amount of energy required to produce a product, and is significant because it occurs immediately and can be equal over the life cycle of a…

1673

Abstract

Embodied energy is the total amount of energy required to produce a product, and is significant because it occurs immediately and can be equal over the life cycle of a building to the transient requirements for operational energy. Methods for embodied energy analysis include process analysis, inputoutput analysis and hybrid analysis. Proposes to improve the reliability of estimating embodied energy based on inputoutput models by using an algorithm to extract systematically the most important energy paths for the “other construction” sector from an Australian inputoutput model. Demonstrates the application of these energy paths to the embodied energy analysis of an individual commercial building, highlighting improvements in reliability due to the modification of energy paths with process analysis data. Compares materials and elements for the building, and estimates likely ranges of error.

Details

Logistics Information Management, vol. 14 no. 5/6
Type: Research Article
ISSN: 0957-6053

Keywords

Article
Publication date: 2 May 2008

B. Sharma and O.P. Gandhi

Most of the mechanical systems consist of common tribo components such as gear, bearing, seal, pump, etc. During operation, the failure of such a component may lead to…

Abstract

Purpose

Most of the mechanical systems consist of common tribo components such as gear, bearing, seal, pump, etc. During operation, the failure of such a component may lead to failure of the system or any other components depending on the system structure or its connections. The transformation of functional quantities or parameters within and various components make these vulnerable to failures and breakdowns. The main purpose of this paper is to evaluate the reliability of a tribo‐pair during operation based on the operational parameters which takes into account the deviation in functional objective and considers the component structure explicitly.

Design/methodology/approach

Failure representation using digraph models have mainly been limited to chemical systems and processes but have been applied to a limited extent to mechanical systems. Researchers have considered the operating parameters such as pressure, temperature; feed rate, flow, etc. as the input/output operational parameter for failure cause identification of tribo mechanical system. However, these are not true in case of components like gear, bearing, etc. Therefore, this methodology has been refined in this paper, and is extended to a tribo‐pair by considering its functions along with operating parameters for reliability assessment. The tribo‐pair considered for the development of model is a gear pair, which is a common and important example of mechanical components.

Findings

Understanding of the failure modes helps the designer in identifying the root cause of failure and the operational parameters whose increase/decrease affects the functional objective. Consideration of the input and output parameters and their interrelations are used to develop inputoutput model of a gear pair called gear pair model. This requires consideration of the input and output parameters, which are based on the gear pair functionality. These parameters have been identified. Four input parameters; five output parameters and one condition monitoring parameter are considered to model the gear pair. In addition to input and output parameters condition monitoring parameters are also considered to develop the gear pair model.

Originality/value

Reliability assessment of a tribo‐pair during operation will help the practicing engineers to take corrective action and minimize the occurrence of undesired failure symptom during operation. The decrease in possibility of undesired failure symptom will enhance the reliability of mechanical system.

Details

Industrial Lubrication and Tribology, vol. 60 no. 3
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 6 May 2020

Fu-Chiang Yang

The purpose of this study is to address three managerial issues in a retail network under a centralised regime, including resource allocation, expansion and downsizing. In…

Abstract

Purpose

The purpose of this study is to address three managerial issues in a retail network under a centralised regime, including resource allocation, expansion and downsizing. In particular, this study investigates how to optimise resource allocation across retailers and how to decide the optimal size of a retail network for an empirical case, where 27 retailers belong to an automobile parts supplier in Taiwan.

Design/methodology/approach

The centralised data envelopment analysis (DEA) approach is used to optimise resource allocation among retailers and to seek the possibility of either an expansion and/or downsizing for a retail network.

Findings

The case company knows the best way to (re)allocate its available resources and (re)arrange the outcome goals for its own retailers. The 27 retailers are assigned specific targets for input and output adjustments to become Pareto or technically efficient units. Besides, an experiment is designed to measure how changing the number of retailers affects the group efficiency of the retail network. To keep the current aggregated output level of the retail network, the centralised supplier needs at least 24 retailers. However, the retail network with 37 retailers can achieve maximal group efficiency.

Originality/value

Centralised resource allocation is an inherent feature of most supplier-retailer relationships, where the supplier is usually a central planner with the power to allocate available resources among its own retailers. To the best of our knowledge, this is the first study to assess retail performance under a centralised regime.

Details

International Journal of Retail & Distribution Management, vol. 48 no. 7
Type: Research Article
ISSN: 0959-0552

Keywords

Article
Publication date: 25 November 2019

Reza Farzipoor Saen and Seyed Shahrooz Seyedi Hosseini Nia

The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems.

Abstract

Purpose

The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems.

Design/methodology/approach

The authors estimate inputs’ variations based on outputs so that the efficiencies of decision-making unit under evaluation (DMUo) and other decision-making units (DMUs) are constant.

Findings

The new INDEA model is developed to allocate resources such that inputs are not increased while efficiency scores of all DMUs remain constant. Furthermore, the authors obtain new combinations of inputs and outputs, together with a growth in efficiency score of DMUo such that efficiency scores of other DMUs are not changed. A case study is provided.

Originality/value

This paper proposes INDEA model to estimate inputs (outputs) without changing efficiency scores of DMUs.

Details

Benchmarking: An International Journal, vol. 27 no. 2
Type: Research Article
ISSN: 1463-5771

Keywords

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