Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.134452
Mohit Beniwal, Archana Singh, Nand Kumar
Predicting the stock market is a complex and strenuous task. Moreover, the stock market time series is nonlinear, volatile, dynamic, and chaotic. The efficient market hypothesis (EMH) and random walk hypothesis (RWH) state that it is futile to predict the stock market. Auto-regressive integrated moving average (ARIMA) and support vector regression (SVR) are popular methods in time series forecasting. This study empirically compares static and iterative models of ARIMA and SVR's ability to predict stock market indices in developed and emerging economies. Five global stock indices, two from emerging and three from developing economies, are predicted. In the long-term, in contrast to EMH and RWH, the results show that the SVR has predictable power. Further, the SVR has better predictability in emerging economies than in developed ones in long-term forecasting. The market shows efficient behaviour in daily prediction, and the naïve model is the best performer. Additionally, the ARIMA model is equivalent to the naïve model in daily and long-term prediction.
{"title":"A comparative study of static and iterative models of ARIMA and SVR to predict stock indices prices in developed and emerging economies","authors":"Mohit Beniwal, Archana Singh, Nand Kumar","doi":"10.1504/ijams.2023.134452","DOIUrl":"https://doi.org/10.1504/ijams.2023.134452","url":null,"abstract":"Predicting the stock market is a complex and strenuous task. Moreover, the stock market time series is nonlinear, volatile, dynamic, and chaotic. The efficient market hypothesis (EMH) and random walk hypothesis (RWH) state that it is futile to predict the stock market. Auto-regressive integrated moving average (ARIMA) and support vector regression (SVR) are popular methods in time series forecasting. This study empirically compares static and iterative models of ARIMA and SVR's ability to predict stock market indices in developed and emerging economies. Five global stock indices, two from emerging and three from developing economies, are predicted. In the long-term, in contrast to EMH and RWH, the results show that the SVR has predictable power. Further, the SVR has better predictability in emerging economies than in developed ones in long-term forecasting. The market shows efficient behaviour in daily prediction, and the naïve model is the best performer. Additionally, the ARIMA model is equivalent to the naïve model in daily and long-term prediction.","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135156186","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}
Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.10058475
M. Hoq Chowdhury, Jakia Parvin
{"title":"A Machine Learning Based Credit Lending Eligibility Prediction and Suitable Bank Recommendation: An Android App for Entrepreneurs","authors":"M. Hoq Chowdhury, Jakia Parvin","doi":"10.1504/ijams.2023.10058475","DOIUrl":"https://doi.org/10.1504/ijams.2023.10058475","url":null,"abstract":"","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136137278","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}
Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.133677
Habiba Abdessalem, Aida Bouzir, Saloua Benammou
{"title":"Determinants of Tunisian multimodal travel choice: a hybrid model based on multinomial logit and wavelet transform","authors":"Habiba Abdessalem, Aida Bouzir, Saloua Benammou","doi":"10.1504/ijams.2023.133677","DOIUrl":"https://doi.org/10.1504/ijams.2023.133677","url":null,"abstract":"","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135845013","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}
Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.134427
Clóvis Santos, Carina Dorneles
Data integration represents a challenge in application development. Although there are several alternatives to data integration, such as federated and distributed databases, there are still problems with the standardisation of distinct data sources, and this happens because different companies develop distinct systems with different paradigms and concepts. In this paper, we present a case study, in the agriculture and environment domain, of an essential point in the data integration domain which is to show resources to identify nearby attributes concerning the characteristics of the content foreseen in the requirements presented in the proposed schema. Information technology experts in agribusiness help map the most relevant attributes for the investigated scenario. In our experimental tests, we used a quantitative method data analysis approach to validate the results with quantitative comparisons regarding the percentages of proximity between the attribute contents in the databases. Our proposal presents an alternative to simplify data integration without intermediate application or middleware layers. The results were measured on a scale between 0% and 100% to identify candidate attributes. The results were good in identifying attributes in the databases in almost 67% of the cases.
{"title":"Global schema as local data integrator using active learning to identify candidates attributes","authors":"Clóvis Santos, Carina Dorneles","doi":"10.1504/ijams.2023.134427","DOIUrl":"https://doi.org/10.1504/ijams.2023.134427","url":null,"abstract":"Data integration represents a challenge in application development. Although there are several alternatives to data integration, such as federated and distributed databases, there are still problems with the standardisation of distinct data sources, and this happens because different companies develop distinct systems with different paradigms and concepts. In this paper, we present a case study, in the agriculture and environment domain, of an essential point in the data integration domain which is to show resources to identify nearby attributes concerning the characteristics of the content foreseen in the requirements presented in the proposed schema. Information technology experts in agribusiness help map the most relevant attributes for the investigated scenario. In our experimental tests, we used a quantitative method data analysis approach to validate the results with quantitative comparisons regarding the percentages of proximity between the attribute contents in the databases. Our proposal presents an alternative to simplify data integration without intermediate application or middleware layers. The results were measured on a scale between 0% and 100% to identify candidate attributes. The results were good in identifying attributes in the databases in almost 67% of the cases.","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135158000","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}
Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.10059248
Shantanu Saha, Vishal Soodan
{"title":"Applying an extended theory of planned behaviour to predict Indian customer's e-vehicle purchase intention","authors":"Shantanu Saha, Vishal Soodan","doi":"10.1504/ijams.2023.10059248","DOIUrl":"https://doi.org/10.1504/ijams.2023.10059248","url":null,"abstract":"","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135600402","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}
Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.10059655
Julia T. Thomas, Mahesh Kumar
{"title":"An optimal Bayesian acceptance sampling plan using decision tree method","authors":"Julia T. Thomas, Mahesh Kumar","doi":"10.1504/ijams.2023.10059655","DOIUrl":"https://doi.org/10.1504/ijams.2023.10059655","url":null,"abstract":"","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136202250","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}
Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.10059814
Carina Dorneles, Clóvis Santos
{"title":"Global schema as local data integrator using active learning to identify candidates attributes","authors":"Carina Dorneles, Clóvis Santos","doi":"10.1504/ijams.2023.10059814","DOIUrl":"https://doi.org/10.1504/ijams.2023.10059814","url":null,"abstract":"","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136372397","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}
Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.133669
Gaurav Nagpal, Udayan Chanda
This research work puts forward the inventory optimisation model for the high technology multi-generation products under the situation of limited warehouse storage space. It is assumed that the manufacturer has its own space which has a lesser opportunity cost of usage as compared to another rented space. Therefore, the manufacturer utilises the own storage space for the period of time where his own space is sufficient to keep the inventories. While the research work has been done earlier on various demand patterns under such a scenario, there is no research present under storage space constraints for the generations of innovative products whose demand follows the Norton Bass Model of Innovation Diffusion. This paper lays down such a model for inventory optimisation, but also puts forward a few theorems on the dynamics of inventory decisions, and also performs numerical illustrations of the proposed model.
{"title":"P-Model of inventory optimisation for high technology multi-generation products under limited warehouse storage space","authors":"Gaurav Nagpal, Udayan Chanda","doi":"10.1504/ijams.2023.133669","DOIUrl":"https://doi.org/10.1504/ijams.2023.133669","url":null,"abstract":"This research work puts forward the inventory optimisation model for the high technology multi-generation products under the situation of limited warehouse storage space. It is assumed that the manufacturer has its own space which has a lesser opportunity cost of usage as compared to another rented space. Therefore, the manufacturer utilises the own storage space for the period of time where his own space is sufficient to keep the inventories. While the research work has been done earlier on various demand patterns under such a scenario, there is no research present under storage space constraints for the generations of innovative products whose demand follows the Norton Bass Model of Innovation Diffusion. This paper lays down such a model for inventory optimisation, but also puts forward a few theorems on the dynamics of inventory decisions, and also performs numerical illustrations of the proposed model.","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844963","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}
Pub Date : 2023-01-01DOI: 10.1504/ijams.2023.133670
Vishal Soodan, Shantanu Saha
{"title":"Applying an extended theory of planned behaviour to predict Indian customer's e-vehicle purchase intention","authors":"Vishal Soodan, Shantanu Saha","doi":"10.1504/ijams.2023.133670","DOIUrl":"https://doi.org/10.1504/ijams.2023.133670","url":null,"abstract":"","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135845003","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}
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