scholarly journals A Study of Different Types of Air Pollutants on the Efficiency of China’s Hotel Industry

2019 ◽  
Vol 16 (22) ◽  
pp. 4319 ◽  
Author(s):  
Xiaoying Guo ◽  
Wei Wei ◽  
Yang Li ◽  
Lei-Ya Wang
Keyword(s):  
Regression Model ◽  
Air Pollutants ◽  
Hotel Industry ◽  
Operational Efficiency ◽  
Operational Performance ◽  
Truncated Regression ◽  
Empirical Results ◽  
Sensory Experiences ◽  
Different Types

This study focuses on visible and invisible air pollutants and their impacts on China’s hotel industry. Overall, visible air pollutants may block the sights and sceneries and worsen the quality of visitors’ sensory experiences, and invisible air pollutants are unlikely to result in the same perceptions and sensations. Hence, different types of air pollutants may have various impacts on the hotel industry’s operational performance. We employed a bootstrapped truncated regression model to investigate whether different types of air pollutants had distinctive impacts on the hotel industry. The dataset consisted of 31 provinces of China for the period 2012–2015. Empirical results indicate that visible air pollutants significantly decrease the operational efficiency of China’s hotel industry, while invisible air pollutants insignificantly affect the hotel industry.

scholarly journals Factors Influencing the Frequency of Consumers’ Purchases of Locally-Produced Rice in Indonesia: A Poisson Regression Analysis

Agriculture ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 117 ◽  
Author(s):  
Apri Wahyudi ◽  
John K. M. Kuwornu ◽  
Endro Gunawan ◽  
Avishek Datta ◽  
Loc T. Nguyen
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Marketing Strategy ◽  
Poisson Regression ◽  
Poisson Regression Model ◽  
Poisson Regression Analysis ◽  
Empirical Results ◽  
Factors Influencing ◽  
Using Data

This study assessed the factors influencing the frequency of purchases of locally-produced rice using data collected from a sample of 400 consumers in Jakarta Province in Indonesia. The empirical results of a Poisson regression model revealed that socio-economic characteristics of the consumers (i.e., gender, age, occupation, education, and income), characteristics of the product (i.e., label and color), and the product’s price and promotion significantly influenced consumers’ frequency of purchasing locally-produced rice. The implication is that increasing the quality of locally-produced rice, applying an appropriate marketing strategy such as offering a relatively lower-priced product compared to the price of imported rice, and product promotion are necessary for increasing the frequency of consumers’ purchases of locally-produced rice.

Estimation of operational efficiency and its determinants using DEA

2013 ◽  
Vol 7 (4) ◽  
pp. 409-429 ◽  
Author(s):  
Sudhir Kumar Singh ◽  
Vijay Kumar Bajpai
Keyword(s):  
Sensitivity Analysis ◽  
Power Plant ◽  
Regression Model ◽  
Power Plants ◽  
Research Work ◽  
Regression Result ◽  
Truncated Regression ◽  
Specific Knowledge ◽  
Content Type

Purpose – The purpose of this study is to benchmark the performance of state-owned coal-fired power plants (CFPPs) and test whether plant-specific knowledge in terms of quality of coal, size, age and make of plant contribute to an improvement in plant efficiency. Design/methodology/approach – The methodology that is utilized in the study follows a nonparametric approach of data envelopment analysis (DEA) with sensitivity analysis and Tobit regression model. The input-oriented DEA models are applied to evaluate the overall, pure technical and scale efficiencies of the CFPPs. Further, slack analysis is conducted to identify modes to improve the efficiency of the inefficient plants. Sensitivity analysis based on peer count and the removal of variables is carried out to identify the benchmark power plant. Through Tobit and bootstrap-truncated regression model, the paper investigates whether a plant's specific knowledge influences its efficiency. Findings – The DEA analysis demonstrates that nine plants are technically purely efficient.The slack analysis reveals that reducing the consumption of oil is the most effective way to improve the efficiency of inefficient plants. Mattur plant is the benchmark for most of the inefficient plants. Regression result suggests that quality of coal and size of plant significantly affect the inefficiency of the sample plants. Bharat Heavy Electrical Limited MAKE plant achieved higher efficiency in comparison to mixed MAKE. Originality/value – This study is one of the few published studies that benchmark the performance of state-owned CFPPs. This research carried out taking some new uncontrollable parameters of power plant utilities of India. Research work also identifies the possible causes of inefficiency and provides measures to improve the efficiency of the inefficient power plant.

Drivers of financial and operational efficiency of MFIs: empirical evidences from Eastern Europe and Central Asia

2020 ◽  
Vol 27 (9) ◽  
pp. 2679-2697
Author(s):  
Asif Khan ◽  
Saba Shireen
Keyword(s):  
Eastern Europe ◽  
Central Asia ◽  
Best Practice ◽  
Operational Efficiency ◽  
Microfinance Institutions ◽  
Truncated Regression ◽  
Content Type ◽  
Bootstrap Procedure ◽  
Empirical Results ◽  
Second Stage

PurposeThe study attempts to examine the bias-adjusted financial and operational efficiency estimates of microfinance institutions (MFIs) operating in the Eastern Europe and Central Asia (ECA) region during the financial year 2017–2018. In addition, the study also identifies the responsible factors determining the financial and operational performances of MFIs operating in the ECA region.Design/methodology/approachThe study employs two-stage bootstrap data envelopment analysis (DEA). In the first stage, the authors incorporate the bootstrap procedure in the DEA framework as suggested by Simar and Wilson (2000) to estimate the bias-corrected efficiency scores of 67 sample MFIs. In order to identify the drivers of efficiency level, the study deploys the bootstrap truncated regression model following the Simar and Wilson (2007) guidelines in the second stage of analysis.FindingsThe authors note from the empirical results that MFIs operating in the ECA region are relatively more financially efficient (0.588) than socially efficient (0.496). However, none of the MFIs were found to be operating at best-practice frontier while considering the bias-adjusted efficiency estimates. Further, the results of second stage of analysis confirm that corporate governance, that is, board size has positive and statistically significant impact on MFIs’ performances. In addition, the bad credit quality deteriorates both financial revenue and operational efficiency. Moreover, the MFIs’ size, profit status and debt-to-equity ratio were also found to be statistically significant to determine the operational and financial efficiency of MFIs in the ECA region.Practical implicationsThe study provides the robust efficiency estimates and factors responsible to determine the financial and operational efficiency of MFIs operating in the ECA region. Further, the empirical results of the study provide the inputs and further direction to the policymakers, regulators, practitioners and managers in framing the policy and optimal operating strategies for ECA MFIs industry.Originality/valueThe study extends the DEA analysis by incorporating the bootstrap procedure in DEA model to estimate the bias-adjusted efficiency scores which are more reliable and robust. In addition, bootstrap truncated regression has been applied to identify the drivers of efficiency. Moreover, in the literature there is no single study which has deployed the double bootstrap DEA framework to examine the financial and operational efficiency estimates and its drivers.

scholarly journals Comparison of a Multiple Regression Model and a two-Regime Model of a Vertical Refraction/ Porovnanie Viacnásobného Regresného Modelu A Dvojrežimového Modelu Vertikálnej Refrakcie

2015 ◽  
Vol 61 (1) ◽  
pp. 32-41
Author(s):  
Štefan Sokol ◽  
Mroslav Lipták ◽  
Marek Bajtala
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Meteorological Parameters ◽  
Multiple Regression Model ◽  
Physical Principle ◽  
Threshold Function ◽  
Explanatory Variables ◽  
Different Types ◽  
The Impact

Abstract Accuracy of the trigonometric measurement of elevations is affected by the systematic influence of a vertical refraction, which is caused by changes of meteorological parameters. Submitted paper deals with a modelling of the impact of the vertical refraction using selected meteorological parameters. At first, a concise derivation of a physical principle of the vertical refraction is given. Then, a multiple regression model and its extension into a form of two-regime model are given. Division into two regimes provides a threshold function, which expresses the dependence of the original explanatory variables. Different types of the threshold function are considered and finally a comparison of the quality of the proposed models and application of a chosen model on the results of repeated trigonometric measurements is given.

Income Diversification and Bank Efficiency in Vietnam

2017 ◽  
pp. 52-67
Author(s):  
Sang Nguyen Minh
Keyword(s):  
Regression Model ◽  
Commercial Banks ◽  
Banking System ◽  
Operational Efficiency ◽  
Commercial Banking ◽  
Tobit Regression ◽  
Income Diversification ◽  
Positive Effects ◽  
Study Results ◽  
The Impact

This study uses the DEA (Data Envelopment Analysis) method to estimate the technical efficiency index of 34 Vietnamese commercial banks in the period 2007-2015, and then it analyzes the impact of income diversification on the operational efficiency of Vietnamese commercial banks through a censored regression model - the Tobit regression model. Research results indicate that income diversification has positive effects on the operational efficiency of Vietnamese commercial banks in the research period. Based on study results, in this research some recommendations forpolicy are given to enhance the operational efficiency of Vietnam’s commercial banking system.

Physico-Chemical Analysis of Groundwater and Effect of Climatic Change in Angul-Talcher Area

2018 ◽  
Vol 6 (12) ◽  
pp. 26
Author(s):  
Aliva Bera ◽  
D.P. Satapathy
Keyword(s):  
Water Resources ◽  
Linear Regression ◽  
Regression Model ◽  
Climatic Change ◽  
Linear Regression Model ◽  
Ann Model ◽  
Quality Of Water ◽  
Physico Chemical ◽  
Simulation Based

In this paper, the linear regression model using ANN and the linear regression model using MS Excel were developed to estimate the physico-chemical concentrations in groundwater using pH, EC, TDS, TH, HCO3 as input parameters and Ca, Mg and K as output parameters. A comparison was made which indicated that ANN model had the better ability to estimate the physic-chemical concentrations in groundwater. An analytical survey along with simulation based tests for finding the climatic change and its effect on agriculture and water bodies in Angul-Talcher area is done. The various seasonal parameters such as pH, BOD, COD, TDS,TSS along with heavy elements like Pb, Cd, Zn, Cu, Fe, Mn concentration in water resources has been analyzed. For past 30 years rainfall data has been analyzed and water quality index values has been studied to find normal and abnormal quality of water resources and matlab based simulation has been done for performance analysis. All results has been analyzed and it is found that the condition is stable. 

Enumeration of Cryptosporidium oocysts from surface water concentrates by laser-scanning cytometry

2000 ◽  
Vol 41 (7) ◽  
pp. 197-202 ◽  
Author(s):  
F. Zanelli ◽  
B. Compagnon ◽  
J. C. Joret ◽  
M. R. de Roubin
Keyword(s):  
Surface Water ◽  
Water Samples ◽  
Laser Scanning ◽  
Immunomagnetic Separation ◽  
Entire Surface ◽  
Cryptosporidium Oocysts ◽  
Different Types ◽  
Laser Scanning Cytometry ◽  
Direct Microscopic Observation

The utilization of the ChemScan® RDI was tested for different types of water concentrates. Concentrates were prepared by cartridge filtration or flocculation, and analysed either without purification, or after Immunomagnetic separation (IMS) or flotation on percoll-sucrose gradients. Theenumeration of the oocysts was subsequently performed using the ChemScan® RDI Cryptosporidium application. Enumeration by direct microscopic observation of the entire surface of the membrane was carried out as a control, and recoveries were calculated as a ratio between the ChemScan® RDI result and the result obtained with direct microscopic enumeration. The Chemscan enumeration technique proved reliable, with recoveries yielding close to 100% in most cases (average 125%, range from 86 to 467%) for all the concentration/purification techniques tested. The quality of the antibodies was shown to be critical, with antibodies from some suppliers yielding recoveries a low as 10% in some cases. This difficulty could, however, be overcome by the utilization of the antibody provided by Chemunex. These data conclusively prove that laser scanning cytometry, which greatly facilitates the microscopic enumeration of Cryptosporidium oocysts from water samples and decreases the time of observation by four to six times, can be successfully applied to water concentrates prepared from a variety of concentration/purification techniques.

Study on Application of Oat Flour in Quick-Frozen Dumpling Production

2013 ◽  
Vol 634-638 ◽  
pp. 1532-1536
Author(s):  
Chang Xin Ji ◽  
Xiao Yan Jing ◽  
Yan Qi Liu
Keyword(s):  
Regression Model ◽  
Correlation Coefficient ◽  
Sensory Evaluation ◽  
Outward Appearance ◽  
Optimal Amount ◽  
Oat Flour ◽  
Model Equations

Quick-frozen oat dumplings were produced by adding some Oat flour in dumpling wrapper. The effect of oat flour ratio on the optimal amount of water of the bland flour, cracking ratio and edible quality of quick-frozen oat dumpling were researched. The optimal amount of water of per gram Xiang Man Yuan dumpling flour and oat flour are 0.43g and 0.63g individually. The cracking ratio of products increases with the increases of oat flour ratio. The effect of oat flour ratio on the sensory evaluation and the outward appearance score of quick-frozen oat dumplings is very significant in 1‰ level, their correlation coefficient are 0.990 and 0.994 respectively, and the regression model equations are as follows: Y=90.094－112.477X; Y=18.519－21.763X.

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