Evaluating the influence of E-marketing on hotel performance by DEA and grey entropy

Shuai, Jia-Jane; Wu, Wei‐Wen

doi:10.1016/j.eswa.2011.01.086

Cited by 94 publications

(62 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For example, Shuai and Wu [50] integrated DEA and grey to evaluate the impact of internet marketing on hotel performance. Liu et al [51] measured the goal cost of the petroleum enterprise by DEA and grey.…”

Section: Proposed Data Envelopment Analysis Methodsmentioning

confidence: 99%

An Integrated Approach to Evaluating and Selecting Green Logistics Providers for Sustainable Development

Wang

Luo

et al. 2017

Sustainability

View full text Add to dashboard Cite

Balancing economic development with environmental protection has become a critical concern worldwide. However, along with the highly competitively global marketplace, economic factors are known to directly affect an enterprise's development and its future business. Therefore, selecting the right partner for sustainable collaboration that will lead to improved business performance and reduce carbon dioxide (CO 2 ) emissions is a significant problem for many enterprises. In addition, investigating the economic impact of companies that are charged to protect the environment is becoming increasingly problematic. Thus, the purpose of this paper is to evaluate the comparative efficiencies of 16 Green Logistics Providers (GLPs) in the USA from 2012 to 2015, and the projected four-year period of 2016-2019, by means of an integrated approach that combines the grey forecasting model GM (1,1) and Data Envelopment Analysis (DEA). The results show that there are two GLPs, Knight Transportation and the Union Pacific Corporation, that possess a higher efficiency level and are achieving positive technical change. However, this study also determined that Hyster-Yale Materials Handling and CSX Corporation did not reach an acceptable efficiency score; therefore, they should improve technical efficiency to mitigate environmental concerns. This completely integrative methodology has the potential to provide the best decision-making strategies for finding suitable collaborative partners who are able to meet the sustainability requirements in most economic and environmental areas.

show abstract

Section: Proposed Data Envelopment Analysis Methodsmentioning

confidence: 99%

An Integrated Approach to Evaluating and Selecting Green Logistics Providers for Sustainable Development

Wang

Luo

et al. 2017

Sustainability

View full text Add to dashboard Cite

show abstract

“…Based on Soleimani-Damaneh and Zarepisheh's research, some other literature [25][26][27][28][29][30][31][32] can be found where the DEA method is also combined with Shannon's entropy. However, as there are a great many different DEA models, then the selection of DEA models would have a great effect on the results of the entropy DEA model.…”

Section: Dea With Shannon's Entropymentioning

confidence: 99%

“…Besides, Yang et al [29] proposed a statistical approach to detect the influential observations in DEA in which the entropy was used to detect the change in the distribution after the DMU is removed. There are also some other researches and applications of entropy in the DEA method [30][31][32], but as far as we know, there has been no research that combines Shannon's entropy with the common weights DEA.…”

Section: Introductionmentioning

confidence: 99%

Determining Common Weights in Data Envelopment Analysis with Shannon’s Entropy

2014

Entropy

View full text Add to dashboard Cite

Data Envelopment Analysis (DEA) is a non-parametric method for evaluating the efficiency of Decision Making Units (DMUs) with multiple inputs and outputs. In the traditional DEA models, the DMU is allowed to use its most favorable multiplier weights to maximize its efficiency. There is usually more than one efficient DMU which cannot be further discriminated. Evaluating DMUs with different multiplier weights would also be somewhat irrational in practice. The common weights DEA model is an effective method for solving these problems. In this paper, we propose a methodology combining the common weights DEA with Shannon's entropy. In our methodology, we propose a modified weight restricted DEA model for calculating non-zero optimal weights. Then these non-zero optimal weights would be aggregated to be the common weights using Shannon's entropy. Compared with the traditional models, our proposed method is more powerful in discriminating DMUs, especially when the inputs and outputs are numerous. Our proposed method also keeps in accordance with the basic DEA method considering the evaluation of the most efficient and inefficient DMUs. Numerical examples are provided to examine the validity and effectiveness of our proposed methodology.

show abstract

“…DEA is a nonparametric approach in operation research and economics for production frontiers estimation. It is utilized to empirically assess productive efficiency of decision making units and also acts as a classical and common tool to measure performance [44][45][46][47]. This paper first applies the factor analysis method to calculate the factor scores of FDI renewable energy technology spillover, and adopts DEA method to obtain energy industry performance in China.…”

Section: Mathematical Modelmentioning

confidence: 99%

Impacts of FDI Renewable Energy Technology Spillover on China’s Energy Industry Performance

Liu

Yang

et al. 2016

Sustainability

View full text Add to dashboard Cite

Environmental friendly renewable energy plays an indispensable role in energy industry development. Foreign direct investment (FDI) in advanced renewable energy technology spillover is promising to improve technological capability and promote China's energy industry performance growth. In this paper, the impacts of FDI renewable energy technology spillover on China's energy industry performance are analyzed based on theoretical and empirical studies. Firstly, three hypotheses are proposed to illustrate the relationships between FDI renewable energy technology spillover and three energy industry performances including economic, environmental, and innovative performances. To verify the hypotheses, techniques including factor analysis and data envelopment analysis (DEA) are employed to quantify the FDI renewable energy technology spillover and the energy industry performance of China, respectively. Furthermore, a panel data regression model is proposed to measure the impacts of FDI renewable energy technology spillover on China's energy industry performance. Finally, energy industries of 30 different provinces in China based on the yearbook data from 2005 to 2011 are comparatively analyzed for evaluating the impacts through the empirical research. The results demonstrate that FDI renewable energy technology spillover has positive impacts on China's energy industry performance. It can also be found that the technology spillover effects are more obvious in economic and technological developed regions. Finally, four suggestions are provided to enhance energy industry performance and promote renewable energy technology spillover in China.

show abstract

Evaluating the influence of E-marketing on hotel performance by DEA and grey entropy

Cited by 94 publications

References 40 publications

An Integrated Approach to Evaluating and Selecting Green Logistics Providers for Sustainable Development

An Integrated Approach to Evaluating and Selecting Green Logistics Providers for Sustainable Development

Determining Common Weights in Data Envelopment Analysis with Shannon’s Entropy

Impacts of FDI Renewable Energy Technology Spillover on China’s Energy Industry Performance

Contact Info

Product

Resources

About