Ahmed Imran Kabir | United International University (original) (raw)
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Papers by Ahmed Imran Kabir
IAR Consortium, 2021
This paper attempts to find out the factors that contribute to the success in retail sector of Ba... more This paper attempts to find out the factors that contribute to the success in retail sector of Bangladesh when using big data analytics in their business operations. Recently, there is a driving success in the retail sector in Bangladesh for adopting big data analytics in their operations. So it was necessary for identifying what is/are contributing to this increasing success. To carry out the investigation, 9 constructs were developed including 1 dependent and 8 independent. The 8 independent variables "Cost saving", "Increased revenue", "Speedy data management", "Future demand", "Micro targeting customers", "Better inventory management", "Better pricing management" and "Product development" were expected to be driving the success in retail sector when using big data analytics (Dependent variable). For this, a survey was carried on the mid/higher level employees of organizations with a close ended questionnaire including questions related to the variables. To analyze the survey data a statistical software (SPSS) was used to run reliability tests, multiple regression, and find out the correlations between the independent variables. 8 hypotheses were developed for individual independent variables and were accepted or rejected based on their beta standardized coefficient score. In conclusion it was seen that, four hypotheses were accepted. The independent variables "cost saving", "increased revenue", "speedy data management", "future demand" were the only contributing factors that drove success in the retail sector for using big data analytics.
Informatica Economica, 2021
Nowadays, Covid-19 is a serious issue, which is outspread all over the world. As, this is a conta... more Nowadays, Covid-19 is a serious issue, which is outspread all over the world. As, this is a contagious illness, so people maintaining social distance to prevent it. Government of every country announced lockdown to the respective countries to stop its rapid spread. For this reason, most of the sectors especially the education sector is going through a crisis. Students cannot go to their institution because of this pandemic. Therefore, Government of every country decided to start online class in this pandemic situation. It is very much tough to continue study through online rather than intuitional class. Not only students but also the teachers also faced many problems to do the online class properly because this is a new process for both of them. In online class, teachers have to identify that the students are present or not. If the students turn on their webcam, then the teachers can take their attendance easily. In this research, researchers tried to develop a prototype using R programming language and machine learning tools that can detect and recognize students' face easily that might help teachers to take attendance without any hassle. Researchers took help of Artificial Intelligence as well as used Machine Learning tools to complete this research. People using artificial intelligence because people do mistake but machine cannot do mistake so the in here the error rate is low. Machine learning is also important because it is time consuming, this machine have to trained up so that it is act as human and solve all the problems easily. That is why various types of programming language are needed to train up the machine. In here, Researchers mainly used OpenCV that is a built-in package of R programming language, which is used for real time face detection and so on.
IAR Journal of Business Management, 2021
This paper attempts to find out the factors that contribute to the success in retail sector of Ba... more This paper attempts to find out the factors that contribute to the success in retail sector of Bangladesh when using big data analytics in their business operations. Recently, there is a driving success in the retail sector in Bangladesh for adopting big data analytics in their operations. So it was necessary for identifying what is/are contributing to this increasing success. To carry out the investigation, 9 constructs were developed including 1 dependent and 8 independent. The 8 independent variables "Cost saving", "Increased revenue", "Speedy data management", "Future demand", "Micro targeting customers", "Better inventory management", "Better pricing management" and "Product development" were expected to be driving the success in retail sector when using big data analytics (Dependent variable). For this, a survey was carried on the mid/higher level employees of organizations with a close ended questionnaire including questions related to the variables. To analyze the survey data a statistical software (SPSS) was used to run reliability tests, multiple regression, and find out the correlations between the independent variables. 8 hypotheses were developed for individual independent variables and were accepted or rejected based on their beta standardized coefficient score. In conclusion it was seen that, four hypotheses were accepted. The independent variables "cost saving", "increased revenue", "speedy data management", "future demand" were the only contributing factors that drove success in the retail sector for using big data analytics.
IAR Consortium, 2021
This paper attempts to find out the factors that contribute to the success in retail sector of Ba... more This paper attempts to find out the factors that contribute to the success in retail sector of Bangladesh when using big data analytics in their business operations. Recently, there is a driving success in the retail sector in Bangladesh for adopting big data analytics in their operations. So it was necessary for identifying what is/are contributing to this increasing success. To carry out the investigation, 9 constructs were developed including 1 dependent and 8 independent. The 8 independent variables "Cost saving", "Increased revenue", "Speedy data management", "Future demand", "Micro targeting customers", "Better inventory management", "Better pricing management" and "Product development" were expected to be driving the success in retail sector when using big data analytics (Dependent variable). For this, a survey was carried on the mid/higher level employees of organizations with a close ended questionnaire including questions related to the variables. To analyze the survey data a statistical software (SPSS) was used to run reliability tests, multiple regression, and find out the correlations between the independent variables. 8 hypotheses were developed for individual independent variables and were accepted or rejected based on their beta standardized coefficient score. In conclusion it was seen that, four hypotheses were accepted. The independent variables "cost saving", "increased revenue", "speedy data management", "future demand" were the only contributing factors that drove success in the retail sector for using big data analytics.
Informatica Economica, 2021
Nowadays, Covid-19 is a serious issue, which is outspread all over the world. As, this is a conta... more Nowadays, Covid-19 is a serious issue, which is outspread all over the world. As, this is a contagious illness, so people maintaining social distance to prevent it. Government of every country announced lockdown to the respective countries to stop its rapid spread. For this reason, most of the sectors especially the education sector is going through a crisis. Students cannot go to their institution because of this pandemic. Therefore, Government of every country decided to start online class in this pandemic situation. It is very much tough to continue study through online rather than intuitional class. Not only students but also the teachers also faced many problems to do the online class properly because this is a new process for both of them. In online class, teachers have to identify that the students are present or not. If the students turn on their webcam, then the teachers can take their attendance easily. In this research, researchers tried to develop a prototype using R programming language and machine learning tools that can detect and recognize students' face easily that might help teachers to take attendance without any hassle. Researchers took help of Artificial Intelligence as well as used Machine Learning tools to complete this research. People using artificial intelligence because people do mistake but machine cannot do mistake so the in here the error rate is low. Machine learning is also important because it is time consuming, this machine have to trained up so that it is act as human and solve all the problems easily. That is why various types of programming language are needed to train up the machine. In here, Researchers mainly used OpenCV that is a built-in package of R programming language, which is used for real time face detection and so on.
IAR Journal of Business Management, 2021
This paper attempts to find out the factors that contribute to the success in retail sector of Ba... more This paper attempts to find out the factors that contribute to the success in retail sector of Bangladesh when using big data analytics in their business operations. Recently, there is a driving success in the retail sector in Bangladesh for adopting big data analytics in their operations. So it was necessary for identifying what is/are contributing to this increasing success. To carry out the investigation, 9 constructs were developed including 1 dependent and 8 independent. The 8 independent variables "Cost saving", "Increased revenue", "Speedy data management", "Future demand", "Micro targeting customers", "Better inventory management", "Better pricing management" and "Product development" were expected to be driving the success in retail sector when using big data analytics (Dependent variable). For this, a survey was carried on the mid/higher level employees of organizations with a close ended questionnaire including questions related to the variables. To analyze the survey data a statistical software (SPSS) was used to run reliability tests, multiple regression, and find out the correlations between the independent variables. 8 hypotheses were developed for individual independent variables and were accepted or rejected based on their beta standardized coefficient score. In conclusion it was seen that, four hypotheses were accepted. The independent variables "cost saving", "increased revenue", "speedy data management", "future demand" were the only contributing factors that drove success in the retail sector for using big data analytics.