Benchmarking the performance indicators of Indian Railway container business using data envelopment analysis

Analysis of the Efficiency of Transport Infrastructure Connectivity and Trade

Analyzing the efficiency of transport infrastructure connectivity and trade in the Regional Comprehensive Economic Partnership (RCEP) is very important for regional integration for international trade in the RCEP. This study aims to significantly measure the efficiency of the connectivity of infrastructure in the RCEP for improving the performance of infrastructure connection and suggest the way to improve the connection of infrastructure. Therefore, the input and output variables of infrastructure connectivity have been inserted to achieve this objective. The inputs are: the number of ports, rail range, and road networks, the number of land borders, the number of maritime borders, number of cross border points, railway linkage with other countries, number of ports connected with railways, and the number of ports connected with road base on the “intermodal and multimodal concept”. On the other hand, the output factors most related to trade and economics are GDP, transport, import, and export volume. The paper applied DEA (Data Envelopment Analysis) model by using DEAP software to analyze the data. The result reveals that the efficiency of infrastructures connectivity and international trade in 10 countries were efficient and 5 countries were inefficient. The research study presents ways of development to improve the connectivity by investing in the basic infrastructures, such as increasing the logistics connection points and driving forward for international trade in the RCEP.

A DEA-ANN-based analytical framework to assess and predict the efficiency of Canadian universities in a service supply chain context

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.

Developing and training artificial neural networks using bootstrap data envelopment analysis for best performance modeling of sawmills in Ontario

Purpose

The measurement capabilities of the data envelopment analysis (DEA) models are used to train the artificial neural network (ANN) models for the best performance modeling of the sawmills in Ontario. The bootstrap DEA models measure robust technical efficiency scores and have benchmarking abilities, whereas the ANN models use abstract learning from a limited set of information and provide the predictive power.

Design/methodology/approach

The complementary modeling approaches of the DEA and the ANN provide an adaptive decision support tool for each sawmill.

Findings

The trained ANN models demonstrate promising results in predicting the relative efficiency scores and the optimal combination of the inputs and the outputs for three categories (large, medium and small) of sawmills in Ontario. The average absolute error in predicting the relative efficiency scores varies from 0.01 to 0.04, and the predicted optimal combination of the inputs (roundwood and employees) and the output (lumber) demonstrate that a large percentage of the sawmills shows less than 10% error in the prediction results.

Originality/value

The purpose of this study is to develop an integrated DEA-ANN model that can help in the continuous improvement and performance evaluations of the forest industry working under uncertain business environment.

Performance evaluation of privatized ports by entropy based TOPSIS and ARAS approach

Purpose

Ports are the key elements of maritime transportation, which is crucial for world trade. Approximately 180 port facilities are located in Turkey. After 2007, 5 of the ports, which are formerly owned by Turkish Republic Railways Administration (TRRA), are privatized. The aim of the study is to evaluate the performance of these privatized ports by multi-criteria decision-making (MCDM) approach.

Design/methodology/approach

The application process is performed by a MCDM model. This model includes both criteria (dry bulk, liquid bulk, general cargo, container, RO-RO capacity, total port area, total berth, total berths length and depth) and alternatives (Mersin, Samsun, Bandirma, Iskenderun and Derince Ports). It determines the weights of the criteria by entropy and ranks the alternatives by ARAS and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods.

Findings

The results of entropy, ARAS and TOPSIS methods are compared. According to these results, “container” is the most important criteria while Mersin port has the best performance.

Originality/value

In the literature, most of the studies about this subject were analyzed by data envelopment analysis (DEA) and there are no studies had been taken into consideration ports that are owned by TRRA, in Turkey. Moreover, few of these studies used integrated MCDM models, and this is the first study that integrates entropy, ARAS and TOPSIS methods in this field.

Quality assessment of city bus service based on subjective and objective service quality dimensions

Purpose

The purpose of this paper is to estimate and compare the service quality of the city bus service measured by two different approaches which are subjective service quality dimensions and objective service quality dimensions.

Design/methodology/approach

The objective service quality dimensions have been estimated based on the benchmarking technique provided by the Ministry of Urban Development, India. For the analysis of subjective service quality dimensions, a questionnaire survey has been conducted to measure the users’ satisfaction and dissatisfaction about the service. The questionnaire consists of users’ socioeconomic characteristics and 23 questions related to city bus service quality dimensions. Questionnaire data have been analyzed by factor analysis, regression analysis and path analysis to find out the indicators representing subjective service quality dimensions. Finally, the overall service quality of the bus service has been determined based on both the measures.

Findings

The study indicates that the overall service quality of the bus service is different for subjective and objective analyses. While the objective measures show that the service quality is very good, the subjective measures indicate that the service is not doing well.

Research limitations/implications

The analysis of the subjective dimensions is complicated. Analysis of the subjective dimensions needed more expertise and resources than the objective analysis.

Originality/value

In this study, the estimated service quality of the bus service is more reliable than the other methods as it comprises of both operators’ perspective and passengers’ expectations from the service.

A six sigma based approach to evaluate the on time performance of Indian railways

Purpose

The purpose of this paper is to propose an approach to evaluate “on time” performance for a class of Indian railways (IR). This approach is build-up on the theme of six sigma level computation for continues data. The arrival data obtained from a class of IR called “Rajdhani Express” exhibited a unique characteristic: neither did the data followed a distribution nor could it be transformed to fit into a distribution. In this work, the authors present an approach to evaluate on time performance of IR, given such “unruly” data.

Design/methodology/approach

An attempt is made to develop a lucid approach, given an unruly data. Initially, the authors plot a histogram using Scott’s method. Later, the authors use Taguchi’s quality loss function to assign weights to each of the bins in histogram. Weights to each of the bins are assigned based on the predefined rules. Finally, sigma level is computed by using weighted defect per million opportunities (DPMO) approach. In this paper, the authors discuss the proposed algorithm, an illustrative example with an emphasis on a class of IR.

Findings

Given the unique characteristic (unruly data) of arrival data of IR, the proposed methodology helps in quantifying it is on time performance. This method extends the conventional DPMO approach of computing the sigma level. The proposed method is validated using various data sets of different distributions. Further, this approach can be generalized and applied to data set of any distribution. Since distribution of the data is not the pre-requisite, the proposed approach can be applied to compare (and benchmark) data sets of different distributions. This methodology, thus, paves path to develop newer approaches in quantifying and benchmarking the sigma levels.

Research limitations/implications

In this manuscript, the authors present a case of Rajdhani Express trains, a class of IR. A practicing manager can use this approach to compare the performance of various classes of railways and benchmark their performance. Such an approach, with suitable modifications (if any) can be applied to evaluate performance in various service industries.

Originality/value

Usually, if the data are unruly, the sigma level is computed by usingad-hocmethods that may provide compromising solutions and/or inaccurate results. The developed methodology proposes a unique approach to quantify sigma level, given such an unruly nature of the data. This approach thus fills the long needed gap in addressing such situations. This approach can be applied in various similar situations. A case of IR is presented.

Productivity changes in Indian steel plants: DEA approach

Purpose

The purpose of this paper is to evaluate the technical efficiency and productivity changes in the integrated steel plants in India over a period of five years.

Design/methodology/approach

Since this evaluation of integrated steel plants needs consideration of multiple input and output factors, data envelopment analysis (DEA) has been employed including bootstrapping (to account for statistical noise) to evaluate the relative efficiency of the steel manufacturing units. The efficiency and Malmquist productivity indices of a sample of ten integrated steel plants producing around 55 percent of the industry’s output were determined for the period 2008-2013. The results of these changes were further categorized according to the management control, route followed to produce crude steel, size and age of these steel plants, for gaining insights.

Findings

The study finds that private sector steel plants with larger capacity and which have adopted the latest and most modern technologies are more efficient and productive over the study period.

Practical implications

Public sector steel plants should therefore be provided with more autonomy and delegation of power and should be agiler in responding to market requirements as well as increasing their installed capacities to be competitive in technical efficiency and productivity as well as profitability in the long term to ensure sustainable achievements.

Originality/value

Productivity changes over time, both with respect to technological and efficiency changes, for the Indian integrated steel plants producing comparable products using DEA.

Improving the quality of Sweden’s rail freight rolling stock

Purpose

The purpose of this paper is to provide a theoretical conceptualization of how data envelopment analysis (DEA) can be applied to rail freight rolling stock in order to develop a tariff for track access charges which is functionally dependent upon the derived relative benchmark values of performance.

Design/methodology/approach

It is posited that track access charges should be differentiated to reflect differences in the performance of rolling stock and that this can be achieved purely on the basis of technical and other characteristics. The performance benchmarking of rolling stock is proposed as the basis for formulating and justifying a performance-based tariff structure. Using DEA, relative index measures of rolling stock performance can be derived, benchmark performance can be identified and a tariff structure can be developed.

Findings

A workable approach to implementing the concept, utilizing existing in-house databases, is found to be feasible and a template for tariff setting is established.

Research limitations/implications

In the absence of access to in-house technical data on rolling stock, which is commercially sensitive, no empirical application of the concept is possible.

Originality/value

There are many ways to improve the efficiency of a railway system. Many are inherently long term and involve significant investment. Using Sweden as an example, this paper proposes the more immediate, simpler and cheaper approach of incentivising the use of better rolling stock through appropriate track access charging. Such an approach should reduce the number of problems arising on the rail network and the costs imposed on other rail users, the infrastructure providers and society. Ultimately, the implementation of this approach would support the objective of increasing long-term robustness and reducing disruptions to railways.

Best performance modeling using complementary DEA-ANN approach

Purpose

– The purpose of this paper is to design an innovative performance modeling system by jointly using data envelopment analysis (DEA) and artificial neural network (ANN). The hybrid DEA-ANN model integrates performance measurement and prediction frameworks and serves as an adaptive decision support tool in pursuit of best performance benchmarking and stepwise improvement.

Design/methodology/approach

– Advantages of combining DEA and ANN methods into an optimal performance prediction model are explored. DEA is used as a preprocessor to measure relative performance of decision-making units (DMUs) and to generate test inputs for subsequent ANN prediction modules. For this sequential process, Charnes, Cooper, and Rhodes and Banker, Chames and Cooper DEA models and back propagation neural network (BPNN) are used. The proposed methodology is empirically supported using longitudinal data of Japanese electronics manufacturing firms.

Findings

– The combined modeling approach proves effective through sequential processes by streamlining DEA analysis and BPNN predictions. The DEA model captures notable characteristics and efficiency trends of the Japanese electronics manufacturing industry and extends its utility as a preprocessor to neural network prediction modules. BPNN, in conjunction with DEA, demonstrates promising estimation capability in predicting efficiency scores and best performance benchmarks for DMUs under evaluation.

Research limitations/implications

– Integration of adaptive prediction capacity into the measurement model is a practical necessity in the benchmarking arena. The proposed framework has the potential to recalibrate benchmarks for firms through longitudinal data analysis.

Originality/value

– This research paper proposes an innovative approach of performance measurement and prediction in line with superiority-driven best performance modeling. Adaptive prediction capabilities embedded in the proposed model enhances managerial flexibilities in setting performance goals and monitoring progress during pursuit of improvement initiatives. This paper fills the research void through methodological breakthrough and the resulting model can serve as an adaptive decision support system.

Impact of leader member exchange, human resource management practices and psychological empowerment on extra role performances

Purpose

– The purpose of this paper is to seek to examine the mediating role of organizational commitment (OC) in the relationship that extra role performance (EXR) shares with leader member exchange (LMX), psychological empowerment (PE) and human resource management practices (HRMP) in a large, public-sector service organization in India.

Design/methodology/approach

– Structural equation modeling and confirmatory factor analysis was conducted to evaluate the hypothesized model. Reliability and validity of measures were also examined.

Findings

– Statistical analysis indicated that each of the following - LMX, PE and HRMP had a positive impact on OC, and OC influenced EXR. Further LMX influence EXR through OC while HRMP and PE partially influence EXR.

Practical implications

– In an Indian context, this study offers a deeper understanding of the factors influencing OC, and how OC affects EXR. This understanding will help practitioners formulate effective human resource policies and restructure their training programs to increase commitment levels and enhance performance of their employees.

Originality/value

– This paper considers a sample in a large, public-sector service organization in India which has not been attempted earlier; previous studies have focussed more on Western contexts. Further, findings of this research corroborate the findings of previous studies that established a positive relation between OC and EXR, and found that LMX, PE and HRMP positively influenced OC.

Performance evaluation of Indian Railway zones using DEMATEL and VIKOR methods

Purpose

– The purpose of this paper is to propose the application of a decision-making tool for performance evaluation of Indian Railway zones. It basically seeks to analyze the effects of various evaluation criteria on the performance of Indian Railways using a combined multi-criteria decision-making approach which employs decision-making trial and evaluation laboratory (DEMATEL) and “VIse Kriterijumska Optimizacija kompromisno Resenje” (VIKOR) methods.

Design/methodology/approach

– The performance of 16 Indian Railway zones is first evaluated using DEMATEL method which addresses the inter-relationships between different criteria with the aid of a relationship structure. The VIKOR method which is a compromise ranking approach is then adopted to rank those candidate railway zones. Pareto analysis is also carried out to identify the benchmark railway zones for the under/poor performers so as to improve their operational excellence.

Findings

– A numerical example from Indian Railways is illustrated and solved for better understanding of the integrated decision-making tool in which the relevant information for the considered railway zones with respect to different evaluation criteria are collected from various websites and Indian Railways annual statistical report. Western and North-Eastern zones, respectively, take the first and the last positions in the derived ranking list. The relevance of selecting different performance indices/evaluation criteria is also discussed.

Practical implications

– The application of this integrated methodology would serve as a systematic approach for measurement of the aggregate operational performance of Indian Railway zones so as to gain valuable academic and practical insights. It is also expected to provide an insightful guidance to the railway administrators in taking valuable strategic decisions in promoting the service of Indian Railways.

Originality/value

– The integrated DEMATEL-VIKOR method is conceptually simple and easily comprehensible which can consider numerous attributes simultaneously. This paper enables the readers to gain some valuable inputs from a managerial perspective for Indian Railways to formulate strategies for its zones to foster better performance.