Two-stage network DEA with shared resources: Illustrating the drawbacks and measuring the overall efficiency

Wen-lai

et al. 2023

Land

Improving the water and land resource system efficiency can effectively alleviate the severe situation of water and land resources in China. Through the two-stage network DEA model, spatial autocorrelation analysis, multiple linear regression, and geographic weighted regression analysis, this paper revealed the change characteristics, distribution types, spatial correlation relationship, and main driving factors of China’s water and land resources system efficiency. The results show that the water and land resources system efficiency fluctuates widely in different regions. Water and land resources systems in nearly half of the provinces belong to the high development, low economic benefit transformation type, mainly distributed in southwestern and northwestern China. The economic benefit transformation is becoming the weak link of water and land resources system. The overall efficiency of water and land resource system has significant spatial positive correlation, and this correlation has an increasing trend. Low-Low Clusters occupy more provinces. The urbanization level, population density, proportion of output value of secondary and tertiary industries, and effective irrigation all have a positive impact on the overall efficiency of water and land resources system. The impact of the proportion of construction land is bidirectional and the per land pesticide application has negative impact in general.

Section: Discussionmentioning

confidence: 99%

Evaluation for Water and Land Resources System Efficiency and Influencing Factors in China: A Two-Stage Network DEA Model

Wen-lai

et al. 2023

Land

“…Song (2020) used a DEA process to identify the key factors affecting the innovation and development of an enterprise in China. Khoveyni and Eslami (2022) contributed to network DEA by proposing an input–output-oriented linear model to measure the overall efficiency of two-stage DMUs with shared resources. To demonstrate the applicability of the proposed model, an empirical example of twenty manufacturing supply chains is provided.…”

Section: Literature Reviewmentioning

confidence: 99%

Improving performance evaluation based on the balanced scorecard with data envelopment analysis and game theory approaches: a case study

Abedian,

Shirouyehzad,

Davoodi

2024

JM2

Purpose This paper aims to propose an integrated use of balanced scorecard (BSC), data envelopment analysis (DEA) and game theory approach as an enhanced performance measurement technique to determine and rank the importance of manufacturing indicators of a steel company as a real case study. Design/methodology/approach An efficiency change ratio is defined to examine the characteristic function of each coalition which is super-additive. Then, the Shapley value index is used as the solution of the cooperative game to determine the importance of the BSC indicators of the company and rank order them. Findings The results reveal that “profitability rate” is the most important BSC indicator, whereas “customer satisfaction” is the least significant one. The ranking order of the importance of all BSC indicators makes it possible for the senior managers of the organization to realize the importance of each index separately and to improve the profitability and the number of customers by presenting programs according to the budget and time constraints. Originality/value The main contribution of this paper lies in the adoption of a game theory approach to performance measurement in the industrial sector that determines and ranks the importance of manufacturing indicators.

“…It can measure the efficiency of decision-making departments under data distribution uncertainty and is often used to evaluate industrial efficiency and corporate production efficiency [44][45][46][47][48][49][50]. DEA can evaluate the efficiency of multiple decision-making units with multiple inputs and outputs [51,52]. This paper drew on an input-oriented DEA model to analyze the efficiency of the prefabricated building industry in China.…”

Section: Validity and Reliability Of The Datamentioning

confidence: 99%

The Efficiency of the Chinese Prefabricated Building Industry and Its Influencing Factors: An Empirical Study

2022

China is a world leader in capital construction. In the construction field, the shift toward prefabricated construction has become an important path for industrial transformation. This paper refers to the development of the prefabricated building industry in China, and uses input and output perspectives to examine its efficiency. It builds a data envelopment analysis model to evaluate the efficiency of the prefabricated building industry in China at both the micro and macro levels, and uses the Tobit model to empirically analyze the factors that influence this industry’s efficiency. It finds that the country’s prefabricated building industry has a moderate micro-level efficiency. This means that it is necessary to further rationalize industrial planning; strengthen technological innovation; and improve standardization, mechanization, and automation levels. At the macro level, China’s prefabricated buildings have a low industrial efficiency and remain at the initial stage of industrial development. A series of problems, such as small industrial scale and unsound policies, are restricting the industry’s rapid and efficient development. We propose several countermeasures and suggestions for the (micro- and macro-level) sustainable development of the prefabricated building industry in China, and anticipate that this will have implications for this industry’s worldwide development.