An application of data envelopment analysis for Korean banks with negative data

Measuring Profitable Efficiency, Technical Efficiency, Technological Innovation of Waste Management Companies Using Negative Super-SBM–Malmquist Model

In recent decades, waste generation has increased gradually because of the development of the quantity and size of businesses, together with the high growth rate of the population. However, in 2019, like other industries, the waste management industry was affected by the COVID-19 pandemic, particularly in relation to aspects concentrated on strategy. Subsequently, appropriate waste management in all aspects of the community, specifically for waste management enterprises, was demanded. This research aims to assess the profitable efficiency, position, technical, and technological innovation and compare the global major waste management corporations by integrating the negative super-slacks-based measure model and the negative Malmquist model in data envelopment analysis. Various inputs and outputs are initially selected from nine waste management companies’ financial statements from 2017 to 2020, including negative values, to attain their performance. The empirical results indicated that waste management companies’ managers could make better investment or strategy decisions for superior performance. At the same time, collaborators from other sectors could find their potential partners in the waste management industry. In general, considering the efficiency, Veolia Environment (DMU3) and Heritage-Crystal Clean Company (DMU8) were the most efficient companies. Meanwhile, Covanta Holding (DMU2) and Republic Services Corporation (DMU5) required additional development to improve their performance. Besides, because of the disparity in technical and technological innovation, most decision-making units could not achieve consistent improvement in terms of technical, technological change, and total production.

Assess the Impact of the COVID-19 Pandemic and Propose Solutions for Sustainable Development for Textile Enterprises: An Integrated Data Envelopment Analysis-Binary Logistic Model Approach

The COVID-19 pandemic impacted many socio-economic areas of countries around the world. It has made the production and business situations of enterprises face substantial difficulties. In this study, the authors used data envelopment analysis (DEA) models to assess the impact of the COVID-19 pandemic on Vietnam’s textile and garment enterprises. The authors have used the binary logistic model to determine the factors affecting employees’ decision to change jobs in the textile industry. The research results showed that the COVID-19 pandemic greatly affected the business performance of the textile and garment enterprises in Vietnam. Moreover, the results helped identify the factors affecting employee turnover and proposed solutions to help businesses stabilize their personnel situation and develop sustainable businesses in the post-COVID-19 era.

Application of Mathematical Models to Assess the Impact of the COVID-19 Pandemic on Logistics Businesses and Recovery Solutions for Sustainable Development

The logistics industry can be considered as the economic lifeline of each country because of its role in connecting production and business activities of enterprises and promoting socio-economic development between regions and countries. However, the COVID-19 pandemic, which began at the end of 2019, has seriously affected the global supply chain, causing heavy impacts on the logistics service sector. In this study, the authors used the Malmquist productivity index to assess the impact of the pandemic on logistics businesses in Vietnam. Moreover, the authors used a super-slack-based model to find strategic alliance partners for enterprises. The authors also used the Grey forecasting model to forecast the business situation for enterprises during the period 2021–2024, in order to provide the leaders of these enterprises with a complete picture of their partners as a solid basis for making decisions to implement alliances that will help logistics enterprises in Vietnam to develop sustainably. The results have found that the alliance between LO7 and LO10 is the most optimal, as this alliance can exploit freight in the opposite direction and reduce logistics costs, creating better competitiveness for businesses.

Triangular Single Valued Neutrosophic Data Envelopment Analysis: Application to Hospital Performance Measurement

The foremost broadly utilized strategy for the valuation of the overall performance of a set of identical decision-making units (DMUs) that use analogous sources to yield related outputs is data envelopment analysis (DEA). However, the witnessed values of the symmetry or asymmetry of different types of information in real-world applications are sometimes inaccurate, ambiguous, inadequate, and inconsistent, so overlooking these conditions may lead to erroneous decision-making. Neutrosophic set theory can handle these occasions of data and makes an imitation of the decision-making procedure with the aid of thinking about all perspectives of the decision. In this paper, we introduce a model of DEA in the context of neutrosophic sets and sketch an innovative process to solve it. Furthermore, we deal with the problem of healthcare system evaluation with inconsistent, indeterminate, and incomplete information using the new model. The triangular single-valued neutrosophic numbers are also employed to deal with the mentioned data, and the proposed method is utilized in the assessment of 13 hospitals of Tehran University of Medical Sciences of Iran. The results exhibit the usefulness of the suggested approach and point out that the model has practical outcomes for decision-makers.

Perspectives of University-Industry Technology Transfer in African Emerging Economies: Evaluating the Nigerian Scenario via a Data Envelopment Approach

All of Africa’s emerging economies are faced with developmental challenges, which can be partly ameliorated using effective University–Industry technology transfer. While technology transfer remains at the infant stage, sparsely documented, and with no complex ongoing processes in many African societies, Universities in Africa are making efforts in University–Industry collaborations aimed at bringing significant improvements to the continent in a bid to drive national innovation and regional economic development. In this paper, we attempt to evaluate the progress made so far by Nigerian Universities in technological innovation transfer, in order to suggest ways for possible future progress. To do this, crucial technology transfer resource factors (inputs), namely, the number of linkage projects funded by the “African Research Council” (ARC), consortium membership of the University’s technology transfer office, and the number of doctoral staff at the University’s technology transfer office, were checked against a set of performance measures (number of executed licenses, amount of licensing royalty income, number of spin-offs created, and the number of spin-offs created with university equity), using data envelopment analysis and multiple regression, respectively. Results suggest that Universities that possess better resource factors reported higher outputs on most of the performance indicators applied. In addition, it was observed that Universities with greater ability to effectively transfer knowledge had higher technology commercialization performance and financial sustainability. The implication of these results is that Universities in Africa need to develop in line with the technology transfer resource (input) factors suggested within this study, as this is the way to go for better performance.

Public sector R&D and relative efficiency measurement of global comparators working on similar research streams

Purpose

Deriving a measure of efficiency of public-funded organizations (primarily not-for-profit organizations) and ranking these efficiency measures have been major subjects of debate and discussion. The purpose of this paper is to evaluate the relative performances of public-funded research and development (R&D) organizations functioning across multiple countries working on similar research streams. The authors use multiple measures of inputs and outputs for this purpose.

Design/methodology/approach

The authors use the data envelopment analysis (DEA) as the primary methodology of analysis The keywords highlighting the major research areas in the field of non-metrology, conducted by National Physical Laboratory (NPL), India, were utilized to select the global comparators working on similar research streams. These global comparators were three R&D organizations located in the USA and one each located in Germany and Japan. The relative efficiencies of the organizations were assessed with the following output variables – external cash flow, and the numbers of technologies transferred, publications and patents; and the following input variables – amount of grants received from the parent body, and the number of scientific personnel working in these public R&D organizations. The authors follow the output-oriented measure of efficiency at constant return to scale and variable return to scale, along with scale efficiencies.

Findings

The performance of NPL, India under multiple dimensions has been evaluated relative to its global comparators – the National Institute for Materials Science, Japan; the National Renewable Energy Laboratory, USA; Fritz Haber Institute of the Max Planck Society, Germany; the National Centre for Atmospheric Research, USA; and the Oak Ridge National Laboratory, USA. The study indicates suggested measures and a set of targets to achieve the best possible performance for NPL and other R&D organizations. In most cases of efficient local but not so efficient global efficiency scores indicate that, on an average, the actual scale of production has diverged from the most productive scale size.

Research limitations/implications

The approach highlights the utilization of the DEA methodology for relative R&D performance assessment of global comparators. The discriminatory analysis has brought into sharp focus the dichotomy between local efficiency and global efficiency scores of these units and issues of scale size and regional disparities. The outcome of this approach is dependent upon correct selection of input and output variables and data availability.

Practical implications

The study results have profound implications for the management of public R&D institutions across nations working on similar-focused research streams, but functioning within different societal, economic, and political contexts.

Originality/value

The present work, being perhaps one of the few multinational studies of relative performance assessment of pubic-funded R&D organizations working on similar research streams, signifies the relevance of such an approach in the field of R&D/innovation management. This has opened up new avenues for further research in this area.