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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
A. Cansu Gök-Kısa ◽  
Pelin Çeli̇k ◽  
İskender Peker
Keyword(s):  
Maritime Transportation ◽  
Bulk Liquid ◽  
Data Envelopment ◽  
Application Process ◽  
Turkish Republic ◽  
Content Type ◽  
Port Area ◽  
Port Facilities ◽  
Order Preference ◽  
General Cargo

PurposePorts 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/approachThe 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.FindingsThe 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/valueIn 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.

Development of a three-tier assessment model: a case study

2018 ◽  
Vol 25 (7) ◽  
pp. 2216-2229 ◽  
Author(s):  
Henry C. Lau ◽  
Andrew Ip ◽  
CKM Lee ◽  
GTS Ho
Keyword(s):  
Operations Management ◽  
Management Practices ◽  
Assessment Model ◽  
Application Process ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Proposed Model ◽  
Order Preference ◽  
Industrial Settings

PurposeThe purpose of this paper is to propose a three-tier assessment model (TAM), aiming to identify and evaluate the competitiveness level of companies. The existing problem is that companies find it difficult to choose a proper model which can be deployed to benchmark with competitors in terms of their competiveness level in the marketplace. Most of the available models are not appropriate or easy to use. The proposed assessment model is able to provide an insight for better planning and preparation so as to gain a better chance of success comparing with their competitors. Most importantly, the proposal model adopts a pragmatic approach and can be implemented without going through tedious mathematical calculations and analysis.Design/methodology/approachTAM embraces three different approaches deployed in various stages of the application process. The first stage is to identify the relevant criteria using hierarchical holographic modeling and the second stage is to assess the associated weightings of these criteria used to rate the potential competitiveness of related companies. The technique used in stage two is known as fuzzy analytic hierarchy process (FAHP) which is a combination of two well-established methods including fuzzy logic and analytical hierarchical programming. In stage three, a technique known as technique for order preference by similarity to the ideal solution (TOPSIS) is adopted to benchmark the level of competitiveness covering several companies in the same industry.FindingsIn this paper, a case study is conducted in order to validate the feasibility and practicality of the proposed model. Results indicate that TAM can be easily applied in various industrial settings by practitioners in the field for supporting operations management practices.Research limitations/implicationsSignificant amount of work is needed to ensure that the proposed model can be practically deployed in real industrial settings.Practical implicationsThis proposed model is able to capitalize on the benefits of the HMM, FAHP and TOPSIS methods and offset their deficiencies. Most importantly, it can be applied to various industries without complex modification.Originality/valueThis paper suggests a hybrid model to assess competitiveness level embracing three different techniques with the unique feature which is able to provide an insight for better planning and preparation in order to excel competitors. Companies may be able to follow the procedures and steps suggested in the paper to implement the model which is proven to be pragmatic and can be applied in real situations.

Selecting Six Sigma projects: MCDM or DEA?

2016 ◽  
Vol 11 (1) ◽  
pp. 309-325 ◽  
Author(s):  
Ali Yousefi ◽  
Abdollah Hadi-Vencheh
Keyword(s):  
Decision Making ◽  
Six Sigma ◽  
Point Of View ◽  
Decision Quality ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Risk Of Failure ◽  
Order Preference ◽  
Hierarchy Process

Purpose – Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks. Design/methodology/approach – In this paper, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, the analytic hierarchy process (AHP) is used to rank the results. Then, a real example is resolved by two important techniques in decision-making process, that is the AHP and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), as well as data envelopment analysis (DEA). The results from the above three methods are compared. Findings – The results of this paper show that by using fewer criteria, the results from AHP and TOPSIS are very similar. Also, the results from these techniques vary from DEA’s ones in many aspects. So regarding the different results and the importance of criteria in selecting the Six Sigma projects, multi-criteria decision-making (MCDM) techniques are more reliable in comparison with DEA, because decision-maker’s point of view is more effective in MCDM techniques. Originality/value – The paper, using a real case study, provides important new tools to enhance decision quality in Six Sigma project selection.

A benchmarking study of Indian seaports

2019 ◽  
Vol 13 (1) ◽  
pp. 88-102
Author(s):  
Sajeev Abraham George ◽  
Anurag C. Tumma
Keyword(s):  
Financial Performance ◽  
Future Research ◽  
Data Envelopment ◽  
Operational Parameters ◽  
Two Stage ◽  
Content Type ◽  
The Public ◽  
Port Authorities ◽  
Financial Performance Measures ◽  
The Government

Purpose The purpose of this paper is to benchmark the operational and financial performances of the major Indian seaports to help derive useful insights to improve their performance. Design/methodology/approach A two-stage data envelopment analysis (DEA) methodology has been used with the help of data collected on the 13 major seaports of India. The first stage of the DEA captured the operational efficiencies, while the second stage the financial performance. Findings A window analysis over a period of three years revealed that no port was able to score an overall average efficiency of 100 per cent. The study identified the better performing units among their peers in both the stages. The contrasting results of the study with the traditional operational and financial performance measures used by the ports helped to derive useful insights. Research limitations/implications The data used in the study were majorly limited to the available sources in the public domain. Also, the study was limited to the major seaports which are under the Government of India and no comparisons were carried out with other local or international ports. Practical implications There is a need to prioritize investments and improvement efforts where they are most needed, instead of following a generalized approach. Once the benchmark ports are identified, the port authorities and other relevant stakeholders should work in detail on the factors causing inefficiencies, for possible improvements in performance. Originality/value This paper carried out a two-stage DEA that helped to derive useful insights on operational efficiency and financial performance of the India seaports. A combination of the financial and operational parameters, along with a comparison of the DEA results with the traditional measures, provided a different perspective on the Indian seaport performance. Considering the scarcity of research papers reported in the literature on DEA-based benchmarking studies of seaports in the Indian context, it has the potential to attract future research in this field.

DEA window analysis and Malmquist index to assess efficiency and productivity in the Spanish electricity sector

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jaime Sánchez-Ortiz ◽  
Teresa Garcia-Valderrama ◽  
Vanesa Rodríguez-Cornejo ◽  
Francisca Cabrera-Monroy
Keyword(s):  
Malmquist Index ◽  
Electricity Sector ◽  
Theory Of Constraints ◽  
Economic Regulation ◽  
Data Envelopment ◽  
Electricity Distribution ◽  
Content Type ◽  
External Constraints ◽  
Efficiency And Productivity ◽  
Dea Window Analysis

Purpose The purpose of this paper is to demonstrate that overcapacity and tariff deficit (external constraints) negatively affect the efficiency of distribution firms in the Spanish electricity sector. To do this, the paper is based on the theory of constraints and theory of economic regulation. Design/methodology/approach Data envelopment analysis (DEA) window methodology is carried out on the constant scales (I-C) with a sample consisting of five main distribution firms during the period from 2006 to 2015. In turn, an analysis of the Malmquist index is carried out to assess whether it has had a displacement with respect to the efficiency frontier. Findings The results show that the overcapacity and the tariff deficit negatively affect the efficiency of the distribution firms of the Spanish electricity sector. In addition, there is an existence of external constraints that affect the activities of regulated organisations and the importance of adequate legislation in regulated sectors. Originality/value This study defines a model that shows how the efficiency problems associated with electricity distribution companies such as productive overcapacity or tariff deficit can be measured based on the theory of constraints and theory of economic regulation.

Productivity dispersion in the Italian knowledge-intensive business services (KIBS) industry: a multilevel analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Domenico Campisi ◽  
Paolo Mancuso ◽  
Stefano Luigi Mastrodonato ◽  
Donato Morea
Keyword(s):  
Multilevel Models ◽  
Geographic Location ◽  
Productivity Index ◽  
Data Envelopment ◽  
Business Services ◽  
Content Type ◽  
Knowledge Intensive Business Services ◽  
Multifactor Productivity ◽  
Knowledge Intensive ◽  
Business Sectors

PurposeThis paper aims to provide an analysis of the productivity evolution of a sample of 18,459 knowledge-intensive business services (KIBS) firms operating in Italy over the period 2012–2018. The interaction between productivity heterogeneity firm localization and firm sector of business are also analyzed.Design/methodology/approachThe empirical setting is based on data envelopment analysis (DEA) to measure the multifactor productivity index (MPI) and on the multilevel models to investigate if the source of productivity heterogeneity among the Italian KIBS are due to the geographic location and/or to the specific business sectors in which firms operate. Data have been gathered from the AIDA database, which contains financial data of all Italian firms.FindingsThe empirical results show that MPI heterogeneity in the Italian KIBS firms' is sensitive to the regional context in which firms operate to the specific KIBS sector and above all at the interactions arising between region and sector.Originality/valueThe paper contributes to identify the source of productivity dispersion in the Italian KIBS.

A comparative study of formal coaching and mentoring programmes in higher education

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jenni Jones ◽  
Helen A. Smith
Keyword(s):  
Higher Education ◽  
Undergraduate Students ◽  
Business School ◽  
Best Practice ◽  
Application Process ◽  
Content Type ◽  
Record Keeping ◽  
Practice Recommendations ◽  
Matching Process ◽  
Two Phases

PurposeThe purpose of this paper is to evaluate two coaching and mentoring programmes focused on the ever-increasingly important aim of enhancing the chances of professional level employment for undergraduate students, at two UK universities. In addition, to offer recommendations to enhance coaching and mentoring success within higher education (HE).Design/methodology/approachTwo similar programmes are compared; the first study is a coaching programme delivered in two phases involving over 1,500 students within the business school. The second study is a mentoring programme involving over 250 students over a ten-year period within the business school at a different institution.FindingsThe two programmes have been compared against the key success criteria from the literature, endorsed by coaching and mentoring experts. The results highlight the importance of integrating with other initiatives, senior management commitment, budget, an application process, clear matching process, trained coaches and mentors, induction for both parties, supportive material, ongoing supervision and robust evaluation and record keeping.Research limitations/implicationsThe research focuses on two similar institutions, with comparable student demographics. It would have been useful to dig deeper into the effect of the diverse characteristics of coach/mentor and coachee/mentee on the effectiveness of their relationships. In addition, to test the assumptions and recommendations beyond these two institutions, and to validate the reach and application of these best practice recommendations further afield.Practical implicationsThe results identify a number of best practice recommendations to guide HE institutions when offering coaching and mentoring interventions to support career progression of their students.Originality/valueThere are limited comparison studies between universities with undergraduate career-related coaching and mentoring programmes and limited research offering best practice recommendations for coaching and mentoring programmes in HE. The top ten factors offered here to take away will add value to those thinking of running similar programmes within HE.

Does capacity utilisation influence financial performance? A study of Indian public bus transport companies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shivam Kushwaha ◽  
Shankar Prawesh ◽  
Anand Venkatesh
Keyword(s):  
Financial Performance ◽  
Public Transport ◽  
Ordinary Least Squares ◽  
Positive Influence ◽  
Data Envelopment ◽  
Truncated Regression ◽  
Capacity Utilisation ◽  
Content Type ◽  
Unit Increase ◽  
Unused Capacity

PurposeThe objective of the paper is to get a better understanding of capacity utilisation (CU) in Indian public bus companies. More specifically, this paper would be measuring CU and identifying the drivers of the same. Finally, the influence of CU on the financial performance of Indian bus companies is examined.Design/methodology/approachThe study adopted data envelopment analysis (DEA) to measure the CU in Indian public bus companies. Truncated regression was used to identify the drivers of CU. Subsequently, the ordinary least squares (OLS) regression was used to analyse the influence of CU on Indian bus companies' financial performance. The period of study was from 2013 to 17.FindingsThe significant drivers of CU were fleet age, passenger lead and fleet utilisation. Additionally, it was found that CU had a significant positive influence on the financial performance of Indian public bus companies and a unit increase in unused capacity has led to an increase of 7% in the operating ratio of the bus companies.Practical implicationsGetting insights into CU, apart from technical efficiency, is of immense use to both public transport researchers and practitioners. Managers of public bus companies should be mindful of CU as it has a significant bearing on their financial performance.Originality/valueThis is the first study in public transport, which establishes the linkage between CU and financial performance. Besides, a modified measure of cost-efficiency has also been conceptualised in this study.

Fuzzy preference programming formulation in data envelopment analysis for university department evaluation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dyanne Brendalyn Mirasol-Cavero ◽  
Lanndon Ocampo
Keyword(s):  
Data Envelopment Analysis ◽  
Real Life ◽  
The Philippines ◽  
Data Envelopment ◽  
Data Accessibility ◽  
Content Type ◽  
Proposed Model ◽  
University Department ◽  
Fuzzy Dea ◽  
Fuzzy Preference

Purpose University department efficiency evaluation is a performance assessment on how departments use their resources to attain their goals. The most widely used tool in measuring the efficiency of academic departments in data envelopment analysis (DEA) deals with crisp data, which may be, often, imprecise, vague, missing or predicted. Current literature offers various approaches to addressing these uncertainties by introducing fuzzy set theory within the basic DEA framework. However, current fuzzy DEA approaches fail to handle missing data, particularly in output values, which are prevalent in real-life evaluation. Thus, this study aims to augment these limitations by offering a fuzzy DEA variation. Design/methodology/approach This paper proposes a more flexible approach by introducing the fuzzy preference programming – DEA (FPP-DEA), where the outputs are expressed as fuzzy numbers and the inputs are conveyed in their actual crisp values. A case study in one of the top higher education institutions in the Philippines was conducted to elucidate the proposed FPP-DEA with fuzzy outputs. Findings Due to its high discriminating power, the proposed model is more constricted in reporting the efficiency scores such that there are lesser reported efficient departments. Although the proposed model can still calculate efficiency no matter how much missing and unavailable, and uncertain data, more comprehensive data accessibility would return an accurate and precise efficiency score. Originality/value This study offers a fuzzy DEA formulation via FPP, which can handle missing, unavailable and imprecise data for output values.

Efficiency evaluation of Indian oil and gas sector: data envelopment analysis

2019 ◽  
Vol 14 (2) ◽  
pp. 362-378 ◽  
Author(s):  
Vikas Vikas ◽  
Rohit Bansal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Capital Investment ◽  
Oil And Gas ◽  
Stock Exchange ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
Indian Economy ◽  
Oil And Gas Sector

Purpose Data envelopment analysis (DEA), a non-parametric technique is used to assess the efficiency of decision-making units which are producing identical set of outputs using identical set of inputs. The purpose of this paper is to find the technical efficiency (TE), pure technical efficiency and scale efficiency (SE) levels of Indian oil and gas sector companies and to provide benchmark targets to the inefficient companies in order to achieve efficiency level. Design/methodology/approach In the present study, a group of 22 oil and gas companies which are listed on the National Stock Exchange for which the data were available for the period 2013–2017 has been considered. DEA has been performed to compare the efficiency levels of all companies. To measure efficiency, three input variables, namely, combined materials consumed and manufacturing expenses, employee benefit expenses and capital investment and two output variables – operating revenues and profit after tax (PAT) have been considered. On the basis of performance for the financial year ending 2017, benchmark targets based on DEA–CCR (Charnes, Cooper and Rhodes) model have been provided to the inefficient companies that should be focused upon by them to attain the efficiency level. The performance of the companies for the past five years has been examined to check the fluctuations in the various efficiency scores of the companies considered in the study over the years. Findings From the results obtained, it is observed that 59 percent, i.e. 13 out of 22 companies are technically efficient. By considering DEA BCC (Banker, Charnes and Cooper) model, 16 companies are observed to be pure technically efficient. In terms of SE, there are 14 such companies. The inefficient units need to improve in terms of input and output variables and for this motive, specified targets are assigned to them. Some of these companies need to upgrade significantly and the managers must take the concern earnestly. The study has also thrown light on the performance of the companies over last five years which shows Oil India Ltd, Gujarat State Petronet Ltd, Petronet LNG Ltd, IGL Ltd, Mahanagar Gas, Chennai Petroleum Corporation Ltd and BPCL Ltd as consistently efficient companies. Research limitations/implications The present study has made an attempt to evaluate the efficiency of Indian oil and gas sector. The results of the study have significant inferences for the policy makers and managers of the companies operating in the sector. The results of the study provide benchmark target level to the companies of Oil and Gas sector which can help the managers of the relatively less efficient companies to focus on the ways to improve efficiency. The improvement in efficiency of a company would not only benefit the shareholders, but also the investors and other stakeholders of the company. Originality/value In the context of Indian economy, very limited number of studies have focused to measure the efficiency of oil and gas sector in the context of Indian economy. The present study aims to provide the latest insight to the efficiency of the companies especially operating in the Indian oil and gas sector. Further, as per our knowledge, this study is distinctive in terms of analyzing the efficiency of Indian oil and gas sector for a period of five years. The longitudinal study of the sector efficiency provides a bird eye view of the average efficiency level and changes in the efficiency levels of the companies over the years.

Benchmarking the efficiencies of Indonesia’s municipal water utilities using Stackelberg data envelopment analysis

2015 ◽  
Vol 22 (4) ◽  
pp. 588-609 ◽  
Author(s):  
Andreas Wibowo ◽  
Hans Wilhelm Alfen
Keyword(s):  
Data Envelopment Analysis ◽  
The Body ◽  
Water Utilities ◽  
Data Envelopment ◽  
Two Stage ◽  
Restrictive Assumption ◽  
Content Type ◽  
Second Stage ◽  
Municipal Water ◽  
The Impact

Purpose – The purpose of this paper is to present a yardstick efficiency comparison of 269 Indonesian municipal water utilities (MWUs) and measures the impact of exogenous environmental variables on efficiency scores. Design/methodology/approach – Two-stage Stackelberg leader-follower data envelopment analysis (DEA) and artificial neural networks (ANN) were employed. Findings – Given that serviceability was treated as the leader and profitability as the follower, the first and second stage DEA scores were 55 and 32 percent (0 percent = totally inefficient, 100 percent = perfectly efficient), respectively. This indicates sizeable opportunities for improvement, with 39 percent of the total sample facing serious problems in both first- and second-stage efficiencies. When profitability instead leads serviceability, this results in more decreased efficiency. The size of the population served was the most important exogenous environmental variable affecting DEA efficiency scores in both the first and second stages. Research limitations/implications – The present study was limited by the overly restrictive assumption that all MWUs operate at a constant-return-to-scale. Practical implications – These research findings will enable better management of the MWUs in question, allowing their current level of performance to be objectively compared with that of their peers, both in terms of scale and area of operation. These findings will also help the government prioritize assistance measures for MWUs that are suffering from acute performance gaps, and to devise a strategic national plan to revitalize Indonesia’s water sector. Originality/value – This paper enriches the body of knowledge by filling in knowledge gaps relating to benchmarking in Indonesia’s water industry, as well as in the application of ensemble two-stage DEA and ANN, which are still rare in the literature.

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