Dynamic Efficiency Evaluation Research Articles

Evaluation of innovation efficiency of high-tech enterprise based on DEA and Malmquist index under the background of sustainable development

Purpose This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country. Design/methodology/approach By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020. Findings The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance. Research limitations/implications Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized. Originality/value Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

Dynamic efficiency evaluation of electric power and environmental treatment efficiency in China

Dynamic efficiency evaluation of electric power and environmental treatment efficiency in China

The dynamic efficiency evaluation of major liner shipping companies: the long-term impact of strategical investment

The dynamic efficiency evaluation of major liner shipping companies: the long-term impact of strategical investment

ECONOMIC EFFICIENCY ASSESSMENT OF INVESTMENTS IN AGRICULTURAL PRODUCTION

The purpose of this study is to assess the economic benefits of agricultural production and provide guidance to manufacturers and investors interested in agriculture. This paper applies dynamic efficiency evaluation methods i.e. net present value, profitability index, and internal rate of return, together with the sensitivity analysis that is useful in cases of market turbulences. The presented investment is purchasing 10 hectares of arable land and cultivating two alternative crops: corn and soybeans. Research results and projections imply that both scenarios are acceptable and economically profitable with the preference for the cultivation of corn giving better economic efficiency. This study can provoke further investment evaluations with dynamic capital budgeting methods in other crops or implementation of mechanization in agricultural production.

Cooperative Efficiency Evaluation System for Intelligent Transportation Facilities Based on the Variable Weight Matter Element Extension

In order to effectively evaluate the cooperative efficiency of intelligent transportation facilities, a structural model of four cooperative development elements, including functional cooperative, operational cooperative, information cooperative, and operation cooperative, is constructed with the guidance of system coordination and a cooperative efficiency evaluation system is established based on it. Then, a dynamic efficiency evaluation model based on variable weight and matter-element extension method was constructed to describe the cooperative efficiency of intelligent transportation facilities and analyze the cooperative efficiency of key road sections in the Jinan area as an example. The results show that of the ten sections, two are in poor performance status, three are in good performance status, and five are in excellent performance status. The four indexes of vertical cooperative construction, functional scheduling level, information element completeness, and multi-departmental information integration level have the most significant impact on facility cooperative efficiency and are the most sensitive; the three indexes of plan executability, functional ease of upgrading, and space–time alignment rate have the most negligible impact on facility cooperative efficiency and are the least sensitive.

The Dynamic Efficiency Evaluation of Major Liner Shipping Companies: The Long-Term Impact of Strategical Investment

The Dynamic Efficiency Evaluation of Major Liner Shipping Companies: The Long-Term Impact of Strategical Investment

An efficiency analysis of container terminals in Southern Vietnam using DEA dynamic efficiency evaluation

Southern Vietnam is a key economic region for the country, producing 45% of Vietnam’s GDP, despite only accounting for 9% of the country’s total landmass and 21% of its population. Specifically, the Southern Region dominates seaport-based container transportation, contributing 55% of Vietnam’s total vessel calls and 74% of its total container cargo volume, with the North and Central regions trailing far behind. However, despite the sector’s importance, the efficiency of container terminals in Southern Vietnam has not been evaluated by the literature in recent years. This study fills this research gap by using data envelopment analysis (DEA) to evaluate the efficiency of major container terminals in Southern Vietnam. The results of the DEA Malmquist analysis show that most container terminals demonstrated productivity growth between 2017 and 2019, and that this mainly derived from advancements in catch-up operational efficiency and in technological innovation. Moreover, the DEA slack-based measure and DEA undesirable output analyses demonstrate that three container terminals (Cai Mep International Terminal, Tan Cang Cat Lai, and Tan Cang–Cai Mep International Terminal) achieved the maximum efficiency level when both applying and not applying the undesirable output variable. However, other container terminals displayed severe operational inefficiency, with these terminals’ efficiency values decreasing by between 9% and 40% when considering undesirable outputs. The ineffective terminals can therefore be categorized as consuming excessive inputs and lacking in the production of desirable outputs or creating large amounts of undesirable outputs. Therefore, using these results, port authorities and policymakers should be better placed to develop appropriate strategies for managing container terminals in Southern Vietnam.

Dynamic efficiency evaluation of Italian judicial system using DEA based Malmquist productivity indexes

The aim of this study is the empirical analysis of the Italian judicial system, measuring its efficiency and productivity. For this purpose, in details, the Data Envelopment Analysis (DEA) and Malmquist indexes were used, since they are recognized by the current literature as successful techniques to evaluate the performance of decision making units, namely the courts of law in our field of application.The statistical data on the administration of justice in Italy, as reported in Dossier n. 11 May 2013, Senate Research Services, Research Office on Institutional Issues, Justice and Culture, XVII legislature, shows that the efficiency crisis of justice in Italy began in the 1970s of the last century, aggravating during the ‘80s, and reaching its most critical moment during the 1990s. Several studies emphasize the relevance of the effects of inefficiency upon the judicial system on the credit and financial markets.The present analysis, using data that covers a wide time span and is disaggregated at district level, has set the goal of measuring the efficiency of the individual Italian judicial offices while assessing the progress of productivity in its components, by the means of technological progress and scale efficiency. The efficiency analysis that was carried out transcends the aspect of judicial taxation, considering how the passage of time has impacted on judicial efficiency.Considering the judges and judicial administration employed, in the new, pending and finished cases during the years ranging from 2011 to 2016, the results highlighted a distinct heterogeneity among courts, depending on their geographical location. The five-year period that was considered, included the years in which the judicial geographical distribution reform entered into force, so to better comprehend how this complex reform influenced the recovery of efficiency of the judicial offices. Furthermore, by breaking down the index into change in efficiency and change in technology, this work offers a further glimpse into judiciary organization. The application of combined DEA method and Malmquist indexes for evaluating court efficiency in a large time frame showed very interesting and useful results, relevant for judicial administration.

Dynamic efficiency evaluation of state‐level business incubators in China by using a slacks‐based measure approach

AbstractIt is important to evaluate the efficiency of business incubators for their performance improvement. Because few enterprises can successfully graduate from the incubation process in one incubation period, the incubating enterprises will be carried over to the successive periods. In this context, the number of incubating enterprises can be regarded as a carry‐over variable linking different incubation periods, which can also be treated as an undesirable output in the current period. This paper proposes a dynamic slacks‐based measure model to evaluate the efficiency of China's state‐level business incubators during 2010–2012. The empirical results show that neglecting new entrants and the typical carry‐over variable may underestimate the incubation system's efficiency. Moreover, the operational efficiency of China's state‐level business incubators is relatively low, which is largely caused by the lower pure technical efficiency. There exist great disparities between pure technical efficiency and scale efficiency for all considered incubators in China. Some important insights and policy suggestions are presented.

Analyzing Internal Efficiency Dynamics Of Turkish Banks: Activity Based Multi-Objective Dynamic DEA Model And Its Application

Efficiency measurement is an important analysis for institutions in order to investigate their performance comparatively. On the other hand, evaluating efficiency of institutions carrying out more than one activity using common resources is important management problems. Since both efficiency and priorities may change in time, the problem set is getting more complex.Sub-activities of total system (Decision Making Sub-Units/DMSU) of institutions may act in different ways since they have different priorities or goals. In addition, factors effecting efficiencies of these DMSUs may differ. Each DMSUs' countermeasures can vary in order to reach the efficient frontier. Therefore, total system efficiency results may not represent the DMSUs' efficiencies.In line with these inferences, the aim of this study is to analyze efficiency differences between DMUs and DMSUs in terms of their behaviors, efficiencies and countermeasures in a dynamic manner. A hybrid non-parametric dynamic efficiency evaluation model, "Multi-Activity Window Data Envelopment Analysis (MA-WDEA)", is developed first[1]. Then, internal dynamics of DMUs and DMSUs are analyzed via dynamic returns to scale(RTS) analysis and Tobit regression models. Both analysis are established on efficiency results of the MA-WDEA model.The proposed process is applied to measure the performance of Turkish banking system. The results first show that MA-WDEA is a suitable tool to measure efficiency trends of DMUs/DMSUs. There exist important differences among Turkish banks with respect to their operating and non-operating activities’ efficiencies. The results of the dynamic RTS and regression models also show that behavioral attitudes of DMUs and DMSUs are significantly different.[1] The developed hybrid model is first presented in 3rd International Conference on Governance, Management and Entrepreneurship in Crotia by Kaya and Cinar, (2015).

New insights into dynamic efficiency: the effects of firm factors

Purpose – This paper aims to investigate the determinants of dynamic efficiency in the Spanish hotel industry. The study also aims to introduce a large number of variables potentially related to efficiency and performance measurement. In particular, it seeks to explore the association between efficiency scores and firm-specific factors (variables related to market conditions, business factors, audit variables, organisational forms and subsidiary variables). Design/methodology/approach – In this study, the data envelopment analysis (DEA) double-frontier approach is used according to firm size in conjunction with non-parametric tests (Mann–Whitney U and Kruskal–Wallis tests), a dynamic Tobit regression model and a bootstrapping procedure. The tests are performed using 1,805 hotels from the years 2002 to 2011. This allows the authors to overcome several of the major limitations of previous papers, namely, the low number of observations, the static or cross-sectional analysis referring to a single period and the use of conventional DEA models, among others. Findings – The results show significant differences in dynamic efficiency among Spanish hotel companies. In addition, the evidence suggests the levels of efficiency are related to the hotel's location, the hotel's size, internationalisation, the first source of the hotel's activity, audit service and management variables. Research limitations/implications – One limitation of the study is related to the input and output variables specified in the DEA model. The selection of inputs and outputs was based on data availability and the previous literature on hotel efficiency, but the results might change if the hotel sample and the selected input and output variables were changed. Another limitation is the availability of data on ownership structure and subsidiary variables for very small businesses. Originality/value – The paper contributes to the tourism literature by offering new insights into hotel performance: dynamic efficiency evaluation and its main determinants. The paper presents strategic market implications for hoteliers, government decision-makers and destination management organisations.

Is DEA useful in the regulation of water utilities? A dynamic efficiency evaluation (a dynamic efficiency evaluation of water utilities)

The discussion about public utilities efficiency and its management has become increasingly important in the last decades. We focus on the distribution of water, which is one of the most important natural resources (Marshall, 1879). This research shows the relationship between efficiency and institutional factors such as management system. For this purpose, we have data about some Spanish water utilities under different provision systems, during the period 1985 to 2000. Using Data Envelopment Analysis (DEA), we estimate potential cost savings in this context. We will extend the results obtained by Thanassoulis (2000a, b), in attempt to guide the regulation of this sector.