scholarly journals Differential evaluation of county eco-efficiency in Jiangsu Province from the perspective of multi-dimensional development orientation

2021 ◽  
Vol 41 (23) ◽  
Author(s):  
蓝以信,张庆,李婵 LAN Yixin
1998 ◽  
Vol 47 (4) ◽  
pp. 571-574
Author(s):  
Lal Bahadur Singh ◽  
Parmanand Prasad Singh ◽  
Meera Kumari

Author(s):  
Tran Minh Hieu ◽  
Nguyen Duong Ngoc Mai Chi

This study applied SERVQUAL scale of Parasuraman et al to measure factors affecting customer satisfaction on service quality at Vietnam Technological and Commercial Joint Stock Bank - An Giang Branch (Techcombank An Giang). The study was conducted to survey 207 customers who have been using the service at Techcombank An Giang. The survey results were analyzed by the Cronbach's Alpha reliability test method, then used Exploratory factor analysis (EFA) to verify and evaluate the scale of service quality. The results of the regression analysis show that customer's satisfaction about service quality at Techcombank An Giang includes four factors: The factor with the highest level is the Empathy with Beta = 0.253, the second of factor is the Responsibility with Beta = 0.248, ranked third in the influence level is the Tangible with Beta = 0.235, and the lowest impact level is the Reliability with Beta = 0.144. The research also uses statistical methods to describe and test the differences of demographic factors with customer's satisfactionon service quality.The analysis results show that there is no difference between customer's satisfaction on service quality and factors such as gender, age, income, number of transaction banks, regular transaction banks, and time to use the service at Techcombank An Giang. Through the research results, the author would like to propose some ideas to improve the quality of services, thereby attracting new customers and importantly, keeping traditional customers because the development orientation of Techcombank is to take care of old customers to cross sell other products of the bank. The Stud results offer a basis for the branch to identify the factors influencing customer satisfaction on their service quality, thereby having an appropriate strategy to improve customer satisfaction.


2019 ◽  
Vol 12 (1) ◽  
pp. 175 ◽  
Author(s):  
Zijing Liang ◽  
Yung-ho Chiu ◽  
Xinchun Li ◽  
Quan Guo ◽  
Yue Yun

Under the low-carbon background, with the aid of the Malmquist–Luenberger SBM (Slack-based Measure) model of unexpected output, the green total factor productivity (GTFP) of the logistics industry in Jiangsu Province, China, was measured and decomposed in this study based on the reality and experience of logistics industry development in 13 cities in three regions of Jiangsu Province in the years 2006–2018 by taking resource consumption into the input system and discharged pollutants into the output system. It is concluded that the environmental regulation (ER) has a significant positive effect on the growth of the GTFP of the logistics industry, and technological progress has become an important endogenous force that promotes the GTFP of the logistics industry in Jiangsu Province. On this basis, a dynamic GMM (Generalized method of moment) model and a Tobit model were constructed to further study the possible temporal and spatial effects of ER on the GTFP of the logistics industry. The research results reveal that the ER can exert both promoting and inhibitory effects on the GTFP of the logistics industry, and there is a temporal turning point for the effects. Besides, the effects notably differ spatially and temporally. Finally, some policies and advice for the green sustainable development of the logistics industry were proposed. For example, the government and enterprises should pay attention to the green and efficient development of the logistics industry and dynamically adjust the ER methods. They should consider the greening of both forward logistics links and reverse logistics system in the supply chain.


Chemosphere ◽  
2020 ◽  
Vol 246 ◽  
pp. 125563 ◽  
Author(s):  
Ting Zhang ◽  
Penghui Liu ◽  
Xue Sun ◽  
Can Zhang ◽  
Meng Wang ◽  
...  

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