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11 – 20 of over 67000The main aim of this paper is to develop a supply chain efficiency framework to improve overall business performance in the competitive era. This paper offers a critical…
Abstract
Purpose
The main aim of this paper is to develop a supply chain efficiency framework to improve overall business performance in the competitive era. This paper offers a critical literature review on supply chain efficiency that aims to reveal the basic research that has been carried out, the problem areas and requirements for the efficiency in the new era of the supply chain.
Design/methodology/approach
The methodology followed during this research involves beginning with a wide base of articles lying at the supply chain intersection, performance measurement topics, and then screening the list to concentrate on supply chain efficiency.
Findings
Findings show that supply chain efficiency in the modern era remains an open research field. This research contributes to the supply chain literature by clarifying the supply chain efficiency definition, defining key measurements and variables for supply chain efficiency and developing a supply chain efficiency framework to improve overall performance.
Practical implications
This study will be very useful to the scholars working in this field. The proposed framework would help researchers and academicians to understand every dimension and variable of supply chain efficiency, allowing practitioners to measure efficiency levels and identify improvement measures. This framework would also act as a comprehensive guide for future studies and business practices.
Originality/value
As there are several state-of-the-art review papers on various supply chain areas, there is a lack of literature available on supply chain efficiency studies that can provide a comprehensive framework for researchers on related literature. Thus, the present study seeks to bridge this gap in the supply chain literature. Also, this study will provide a strong basis for researchers and academicians to apply the supply chain efficiency measurement system to the dynamic supply chain.
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This paper aims to assess the efficiency levels of World Cup teams via the slack-based data envelopment analysis (DEA) approach, which contributes to filling an important gap for…
Abstract
Purpose
This paper aims to assess the efficiency levels of World Cup teams via the slack-based data envelopment analysis (DEA) approach, which contributes to filling an important gap for performance measurement in football.
Design/methodology/approach
This study focuses on a comparative analysis of the past two World Cups. The authors initially estimate the efficiency of the World Cup teams via the slack-based DEA approach, which is a novel approach for sports performance measurement. The authors also present the conventional DEA results to compare results. The authors also include improvement ratios, which provide significant details for inefficient countries to enhance their efficiency. Besides, the authors include effectiveness ratings to present a complete performance overview of the World Cup teams.
Findings
According to the analysis results of the slack-based DEA approach, titleholder Germany and France are found as efficient teams in the 2014 and 2018 World Cup, respectively. Besides, Belgium and Russia recorded the highest efficiency improvement in the 2018 World Cup. The novel approach for sports performance measurement, the slack-based DEA approach, significantly overlaps with the actual performance of teams.
Originality/value
This study presents novelty in football performance by adopting the slack-based DEA with an undesirable output model for the performance measurement of the World Cup teams. This empirical analysis would be a pioneer study measuring the performance of football teams via the slack-based DEA approach.
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Wai Peng Wong and Kuan Yew Wong
This paper aims to illustrate the use of data envelopment analysis (DEA) in measuring internal supply chain performance.
Abstract
Purpose
This paper aims to illustrate the use of data envelopment analysis (DEA) in measuring internal supply chain performance.
Design/methodology/approach
Two DEA models were developed – the technical efficiency model and the cost efficiency model. The models are further enhanced with scenario analysis to derive more meaningful business insights for managers in making resources planning decisions.
Findings
The information obtained from the DEA models helps managers to identify the inefficient operations and take the right remedial actions for continuous improvement. More importantly, the opportunity cost (forgone profit) calculated serves as a good reference to managers to make efficient decisions on resource allocations.
Research limitations/implications
Results are based on the deterministic data set. Future enhancement of the study would be to look into the possibility of modeling DEA in a stochastic supply chain environment (non‐deterministic) due to the fact that supply chain operates in a dynamic environment.
Practical implications
The proposed DEA‐based approach provides useful managerial implications in the measurement of supply chain efficiency. The study proves the usefulness of DEA as a decision‐making tool in supply chain.
Originality/value
This paper provides useful insights into the use of DEA as a modeling tool to aid managerial decision making in measuring supply chain efficiency.
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M. Oberholzer and G. van derWesthuizen
When bank managers are asked to comment on the bank’s performance over the past year, most would quote either their bank’s return on equity or return on assets. If these measures…
Abstract
When bank managers are asked to comment on the bank’s performance over the past year, most would quote either their bank’s return on equity or return on assets. If these measures were higher than those of their peers, the bank is referred to as a high‐performance bank. The ratios involved are financial ratios and the main problem with this approach is its reliance on comparable ratios. To find suitable comparable standards (norms) is quite difficult, and when the standard (norm) is not appropriate, the comparison may mislead the analyst. A measurement tool that can compensate for the weaknesses in financial ratios is therefore needed. One such tool that can be used to measure bank performance is Data Envelopment Analysis (DEA). The objective of this article is to draw a comparison between the results of financial ratios (as a conventional performance measurement) and the results obtained by means of DEA with regard to the performance evaluation of the ten regional offices of one of South Africa’s larger banks.
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This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The…
Abstract
This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO2 emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.
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Xiancun Hu and Chunlu Liu
The purpose of this paper is to develop a simultaneous measurement of overall performance and its two dimensions of efficiency and effectiveness in the case of Chinese…
Abstract
Purpose
The purpose of this paper is to develop a simultaneous measurement of overall performance and its two dimensions of efficiency and effectiveness in the case of Chinese construction industry.
Design/methodology/approach
A relational two-stage data envelopment analysis (DEA) method, which builds a relationship between component stages and can effectively identify inefficient stages, is developed and applied in order to measure overall performance, efficiency and effectiveness.
Findings
The construction industry of the Eastern region in China demonstrated the best results for overall performance, efficiency and effectiveness. The gaps between regions were primarily reflected in differences of pure technical efficiency. Performance indicators in the whole construction industry improved steadily and but could be improved more effectively. The coefficients of variation became smaller and more well-balanced across the whole industry.
Practical implications
Improving overall performance should focus on promoting construction efficiency at the project level and increasing management effectiveness at the company level. Sustainable development policies, which may include large investment and preferential policies, can narrow performance differences among the regions’ construction industries, and ultimately promote overall performance for the whole industry.
Originality/value
The relational two-stage DEA model is further developed in a variable returns-to-scale condition. The developed approach is generic and can provide a pathway for simultaneously measuring performance, efficiency and effectiveness and to recognise competitive advantages for promoting sustainable development.
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Universities are expected to operate with high efficiency, with ever-growing expectations from a rising number of stakeholders in society. From a theoretical perspective economic…
Abstract
Universities are expected to operate with high efficiency, with ever-growing expectations from a rising number of stakeholders in society. From a theoretical perspective economic science does provide frameworks and methods in order to tackle this, with the cornerstone of defining efficiency as a simple relation of a quantity of inputs toward a quantity of outputs. For the practice of university management and policy this does not answer the crucial questions of which inputs and which outputs to measure, and how to ensure the quality aspect of such management approaches. Higher education research can contribute to answering these questions. This chapter outlines a sector-specific framework for efficiency analysis and management, including suggestions regarding how to implement efficiency-improving measures in university settings.
In this chapter, the concepts of technical efficiency, efficiency, effectiveness, and productivity are illustrated. It is discussed that when firms are not homogeneous, the…
Abstract
In this chapter, the concepts of technical efficiency, efficiency, effectiveness, and productivity are illustrated. It is discussed that when firms are not homogeneous, the situation is the same as when each factor has a different unit of measurement from one firm to another, and therefore, no meaningful discrimination can be expressed, unless a set of known weights are introduced to standardize data. A linear programming data envelopment analysis model is used when a set of known weights are given to calculate the technical efficiency and efficiency of a set of homogeneous DMUs with multiple input factors and output factors. A numerical example is also provided.
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The purpose of this paper is to investigate the feasibility of using artificial neural networks (ANNs) in conjunction with data envelopment analysis (DEA) for the performance…
Abstract
Purpose
The purpose of this paper is to investigate the feasibility of using artificial neural networks (ANNs) in conjunction with data envelopment analysis (DEA) for the performance measurement of major mobile phone providers, and for subsequent predictions related to best performance benchmarking and decision making.
Design/methodology/approach
DEA and ANN are combined, providing an integrated modeling approach via a two-stage process. DEA is used for front end measurement, while ANN provides learning and prediction capabilities. DEA analysis of industry characteristics is based on the measurement of each decision-making unit's (DMU) performance. Back propagation neural networks (BPNN) can then predict each DMU's efficiency score, based on the results of the DEA models. Additional BPNN models provide best performance predictions.
Findings
The DEA module successfully evaluates the competitive status of firms in the mobile phone industry in terms of efficiency. Efficiency trends over the observation period reveal the dynamic nature of competition in this industry. The predictive power of the BPNN module has been demonstrated as well. The proposed system is an effective benchmarking and decision support tool, via its capability to simulate performance scenarios, thereby facilitating insightful, prudent decision making.
Originality/value
This paper proposes the use of two different but complementary methods, DEA and ANN, in a combined performance modeling approach, and examines mobile phone providers. This methodology can improve users’ performance benchmarking and decision-making processes. Additionally, adaptive prediction capability is provided through approximating efficient frontiers, in addition to performance measurement.
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Muhammad Asif, Muhammad Shahzad, Muhammad Usman Awan and Huseyin Akdogan
The growing emphasis on “managerialism” in police and the pressure to employ scientific methods of performance measurement warrants the need for a structured framework. The scope…
Abstract
Purpose
The growing emphasis on “managerialism” in police and the pressure to employ scientific methods of performance measurement warrants the need for a structured framework. The scope of police duties is large as it relates to several preventive and corrective action related to public safety and crime management. A challenge in measuring police performance is to take into consideration a range of variables that can potentially influence performance. The purpose of this paper is to provide a structured framework for measuring different facets of police efficiency, which is especially useful in managerial decision making.
Design/methodology/approach
This paper uses data envelopment analysis and discusses efficiency measurement in terms of the technical, managerial and scale efficiency, resources utilization patterns, returns-to-scale analysis and measurement of super-efficiency. The application of framework is based on the data of the police stations of Lahore, a large metropolitan city in Pakistan.
Findings
The paper shows the application of different measures of efficiency in making decisions pertaining resources allocation, prioritizing areas for improvement and identifying benchmarks for performance improvement. Different measures of efficiency are presented in the form of a structured framework.
Practical implications
Managers can use this framework to glean rich insights into different types of efficiency and sources of inefficiency. Further, a discussion of variables provided in this paper can be especially useful in determining trade-offs during the selection of inputs and outputs.
Originality/value
The key contribution of this paper is in providing a multifaceted efficiency measurement framework, that is capable of providing rich insights into the sources of inefficiency and helps scientific decision making. To the best of our knowledge, such a multifaceted approach has not been provided in previous publications.
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