Journal of Statistics and Management Systems最新文献_第6页

Guest Editors 客人编辑

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2156107

R. C. Poonia, Vaibhav Bhatnagar, Kashinath Chatterjee, Vijander Singh, Md. Ashraful Babu, Pranav Dass

引用次数: 0

Applicability of K-medoids and K-means algorithms for segmenting students based on their scholastic performance k - medidoids和K-means算法在基于学习成绩分割学生中的适用性

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130566

Usha Badhera, Apoorva Verma, P. Nahar

引用次数: 4

A comparative study on SIP and LIP with reference to Indian mutual fund industry using non-regression performance evaluation ratios and single factor CAPM model 基于非回归绩效评价比率和单因素CAPM模型的印度共同基金行业的SIP和LIP比较研究

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130575

A. Goswami, Ity Patni, S. Choubey, Nishu Gupta

引用次数: 1

Understanding the customer preferences of non-scheduled operators in India 了解印度不定期航班运营商的客户偏好

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130580

Deepti Kiran, Ashish Sharma, Itisha Sharma

引用次数: 0

Impact of online shopping advertising on customer trust and loyalty during festival sales 节日促销期间网购广告对顾客信任和忠诚度的影响

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130574

L. Vijayan, R. Venkatesh

{"title":"Impact of online shopping advertising on customer trust and loyalty during festival sales","authors":"L. Vijayan, R. Venkatesh","doi":"10.1080/09720510.2022.2130574","DOIUrl":"https://doi.org/10.1080/09720510.2022.2130574","url":null,"abstract":"Abstract The viewpoint of online shopping is increasing in India because of several factors such as increased Internet knowledge, perceived efficacy, ease of use, increased number of working women, entry from the worldwide and local partakers, and the increased prominence of online companies. The purpose of this study is to find the customers trust and loyalty on online shopping during festival sales in India where various factors have been discussed. Descriptive research was used in this study using structured questionnaires to collect data from the respondents. The survey was carried out online using Goggle forms due to the ongoing pandemic. Regression analysis was used for testing of hypothesis. The results showed that there is a strong relationship between advertising and trust & loyalty during online shopping festival sales and advertising is a major boost online platforms sales during festival sales. The study in particular focuses on festival sales of online shopping in India where it’s limited to a defined period of online shopping, also increased number of respondents would give a broader outcome of the study. Online shopping festival sales has been growing at a rapid pace in India, focus of this study was on trust and loyalty as a prime factor. Though various aspects of festival sales in online shopping have been studied the effect of advertising This research was conducted at VIT University as part of my Research Program. driving these sales and its impact on customer trust and loyalty has been the first of its kind to be tested.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"377 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114511260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting student dropouts using random forest 使用随机森林预测学生退学

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130570

K.Bharatha Devi, S. Ratnoo

引用次数: 1

Air pollution prediction and hotspot detection using machine learning 利用机器学习进行空气污染预测和热点检测

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130568

Shailee Bhatia, Shelly Sachdeva, Puneet Goswami

{"title":"Air pollution prediction and hotspot detection using machine learning","authors":"Shailee Bhatia, Shelly Sachdeva, Puneet Goswami","doi":"10.1080/09720510.2022.2130568","DOIUrl":"https://doi.org/10.1080/09720510.2022.2130568","url":null,"abstract":"Abstract Air pollution is a vital issue that affects day-to-day lives. It is observed that throughout the world, there is an instant need to overcome the monster of pollution. According to statistics, most of the polluted cities in the world are in India. This poses a serious need of the hour for the Indian scientists, engineers, and authorities as a whole to fight and reduce it as much as possible. The time has come when one needs to plan their outside activities on pollution levels and air quality status. Air Quality Index (AQI) varies daily; hence it is difficult to predict future trends for the same. The current study proposed a machine learning-based model that uses sensors, past/present pollutants concentration data, and satellite data to predict air pollution in the regions in India. We emphasize the fact that other than measurable pollutants (PM10, PM2.5, NO2, etc.); meteorological data like wind, temperature, and fire are also important factors in determining pollution. The model uses Long Short-Term Memory, which is the state-of-the-art technique used for time series prediction. The model could predict the concentration of the pollutants and calculate the AQI for the areas where data was available for the near future. The Root Mean Square Error on test data is 54. The results are quite promising and future model can be made, taking this as a base model. An inexpensive prediction technique can greatly help the administration in mitigating pollution.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114199614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A robust controlling and management of load with minimum frequency and voltage deviation in network employing genetic algorithm 利用遗传算法对电网中频率和电压偏差最小的负荷进行鲁棒控制和管理

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130565

A. Saxena, Arun Sharma, Mohd Majid

引用次数: 0

Estimating the volatility of stock price index for Indian market using GARCH model 用GARCH模型估计印度股市股价指数的波动率

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130564

R. Maheshwari, V. Kapoor

引用次数: 1

Economic growth of India and the impact of direct and indirect tax : An ARDL approach 印度经济增长及直接税和间接税的影响:一种ARDL方法

Journal of Statistics and Management Systems Pub Date : 2022-10-03 DOI: 10.1080/09720510.2022.2130578

T. Durga Prasad, Astha Sharma, Manish Mittal, M. Govardhan Reddy, B. Giri Babu

{"title":"Economic growth of India and the impact of direct and indirect tax : An ARDL approach","authors":"T. Durga Prasad, Astha Sharma, Manish Mittal, M. Govardhan Reddy, B. Giri Babu","doi":"10.1080/09720510.2022.2130578","DOIUrl":"https://doi.org/10.1080/09720510.2022.2130578","url":null,"abstract":"Abstract This paper examines and portrays the impact of direct and indirect tax revenue on economic growth in India. Numerous studies were conducted earlier to study taxation from various perspectives, but very few have discussed the impact of taxation on economic growth. Various tax revenue reports from 1990 to 2021 were collected to conduct the present research. An ARDL inbound and outbound tests were applied to continue the investigation further. The study identifies tax variables that have a positive relationship with economic performance. Finally, an in-depth analysis was conducted between variables with the help of ARDL long-run trend analysis. The outcome reveals that direct and indirect tax growth rates positively impact GDP growth. It was suggested that government should focus on corporate tax policies, and more incentives for upcoming and existing entrepreneurs must be provided. The present study is limited only to tax and GDP revenue; it does not focus on economic or corporate policies. However, this research forms a base for further study in taxation, which will support designing policies for economic growth. It is known that the Indian government has introduced nation-one tax policy and implemented GST. Hence, further study can be conducted on the dynamics of GST and its impact on GDP or revenue growth rates.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131531039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0