An allocation Malmquist index with an application in the China securities industry

Zhu, Nan; Liu, Yi; Emrouznejad, Ali; Huang, Qiang

doi:10.1007/s12351-016-0249-6

Cited by 10 publications

(10 citation statements)

References 13 publications

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“…Presently, the DEA method is very popular in banking and financial sector performance measurement. A plethora of studies (e.g., Chang, Jang, Li, & Kim, 2017;Yu, Huang, and Shao, 2019;Sathye, 2003, Ray, 2007Ray and Das, 2010;Hada, Zhu, & Tamang, 2017;Wanke, Barros and Emrouznejad, 2016;Miller and Noulas, 1996;Zhu, Liu, Emrouznejad and Huang, 2017) applied the DEA models in banking and financial sectors of different regions of the world.…”

Section: Bbc Modelmentioning

confidence: 99%

Efficiency and productivity analysis of Pakistan's banking industry: ADEAapproach

et al. 2020

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The objective of this study is to investigate operational efficiency, productivity, and associated differences between the operational efficiency and productivity of Pakistan's private, public, and foreign banks over the period 2006-2017. To measure the operational efficiency scores and productivity growth change, we used data envelopment analysis (DEA) and Malmquist productivity index (MPI) simultaneously. Kruskal-Wallis test was used to check the significant differences between the mean technical efficiencies of different commercial banking industries of Pakistan. Empirical results revealed that mean technical and pure technical efficiency scores of foreign banks are better than domestic banks; however, the mean scale efficiency score of domestic banking is relatively better than foreign banks. Further public sector banks performed well than the private banking industry during the period 2006-2017. Kruskal-Wallis test demonstrated a significant difference between the mean technical efficiency scores of three different banking sectors (public, private, and foreign) of the Pakistan commercial banking industry. Moreover, the MPI results indicated that there is (1.9%) decline in mean total factor productivity change for all commercial banks during the sample period. Further, total factor productivity change of foreign commercial banks shows growth, while a decaying trend is observed for domestic commercial banks.

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Section: Bbc Modelmentioning

confidence: 99%

Efficiency and productivity analysis of Pakistan's banking industry: ADEAapproach

et al. 2020

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“…At present, the DEA models and development with applications in banking and finance areas can be seen. See, for examples, Emrouznejad and Anouze (2010), Hada and Tamang (2014), Wanke et al (2016Wanke et al ( , 2017, and Zhu et al (2017).…”

Section: Data Envelopment Analysismentioning

confidence: 99%

A Comparative Analysis of Operational Efficiency between Chinese and Indian Commercial Banks

Zhu¹,

Zhang²

2018

CEREM

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Aim:The objective of this paper is to make comparative analysis on operational efficiency between Chinese and Indian commercial banks (CBs). Design / Research methods: Following the previous scholars’ study, two models with different sets of input and output variables have been used to show how efficiency scores vary with change in inputs and outputs. The efficiency scores are measured by using data envelopment analysis (DEA) approach. Conclusions / findings: The mean technical efficiency score of Chinese CBs is always relatively higher than the corresponding score of Indian CBs in 2012-2013, respectively. In terms of technical efficiency and pure technical efficiency, the performance of foreign banks in China is always relatively lower than that of foreign banks in India. Originality / value of the article: While many similar studies have evaluated the performance of banking industries in different countries, very few studies have evaluated the performance of banking sectors between Chinese and Indian economies. The paper would be of interest for OR scholars and practitioners in financial industry. Implications of the research (if applicable): The next step of this study could collect more samples and use Malmquist index method to conduct further study on efficiency, efficiency changing and productivity, in order to conduct further competitive power analysis on both of banking industries of China and India.

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“…As we have mentioned earlier, we aim to introduce and decompose a revenue Luenberger indicator (RLI) based on the WADF. So, by analogy with the cost Malmquist index in Zhu et al [6] we define:…”

Section: Revenue Luenberger Indicatormentioning

confidence: 99%

“…So, if information on market prices is known, it seems necessary to define Malmquist-type indexes or/and Luenberger-type indicators when decision-makers are assumed to be revenue maximizers or cost minimizers. In this respect, Maniadakis and Thanassoulis [5] , Zhu et al [6] have defined and decomposed a cost Malmquist index, and Juo et al [7] have introduced a Luenberger indicator than can be applied in these situations.…”

Section: Introductionmentioning

confidence: 99%

The measurement of revenue inefficiency over time: An additive perspective

Jradi

Bouzdine‐Chameeva

Aparicio

2019

Omega

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An allocation Malmquist index with an application in the China securities industry

Cited by 10 publications

References 13 publications

Efficiency and productivity analysis of Pakistan's banking industry: ADEAapproach

Efficiency and productivity analysis of Pakistan's banking industry: ADEAapproach

A Comparative Analysis of Operational Efficiency between Chinese and Indian Commercial Banks

The measurement of revenue inefficiency over time: An additive perspective

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