-------------------------------------------------------------------------***------------------------------------------------------------------------ Abstract - In carrying out successful E-Commerce , the most important things are innovation and understanding what customer wants. Now-a-days the ease of using ecommerce encourages the customers to buy using ecommerce. It runs on the basis of innovation having the ability to enthral the customers with the products, but with such a large raft of products leave the customers confused of what to buy and what not to. According to business , a company may create three segments like High ( Group who buys often , spends more and visited the platform recently ) , Medium ( Group which spends less than high group and is not that much frequent to visit the platform) and Low (Group which is on the verge of churning out ). This is where Machine Learning provides a crucial solution , several algorithms are applied for revealing the hidden patterns in data for better decision making. In this paper we proposed a Customer segmentation concept in which the customer bases of an establishment is divided into segments based on the customers’ characteristics and attributes. This idea can be used by the B2C companies to outperform the competition by developing uniquely appealing products and services and make it reach to potential customers. This approach is implemented using “k-means”, an unsupervised clustering machine learning algorithm.
The article presents the results of the empirical analysis of the system of training future heads of educational institutions under the master's educational program, which showed that quality management of future leaders depends on setting standards, updating educational programs, highly qualified staff, quality organization of the educational process and effective management.The study empirically confirms and theoretically proves that it is very important for a higher education institution to really see the levers that it can manage -internal resources, as well as to understand the factors that are outside the sphere of influence -external threats.
:- In the recent times there is growing need for measuring and managing of Human Resource processes. This can be the result of strategic business value Human Resource function is been given in the organizations. This led to introduction of HR Analytics to prove HR process efficiency & Efficacy.The use of HR analytics has proven successful inimproving company performance by reducing workforce costs, improving the quality ofrecruitment, improving talent management and employee engagement, and generallyimproving productivity. It had become as important decision-making tool supporting the HR processing with supporting data. This paper is a qualitative study with MNC Pharma organization. This study explores the extent of the usage of HR Analytics for predictive decision making in the organization and discusses about how HR digitalization paved way for HR analytics. This paper also discusses different HR Analytics widely used and how they are useful for decision making. Different definitions of HR Analytics are also mentioned as part literature review.
A suspension system is one of the important elements of an automobile which directly influences its safety, comfort, and lifespan. It is used to enhance the efficiency of the vehicle by providing the smooth motion of the vehicle on road. Its function also includes giving support to the moving and vibrating parts of the braking system and overall vehicle. In the present work, Macpherson strut suspension system is designed using SOLIDWORKS software. In a further study, its modal analysis in ANSYS is performed to detect the range of deformation which is caused due to the vibrations. The Macpherson strut suspension system is preferred over the other suspension due to its overall simplicity of the design, reduced wear due to fewer joints, better handling and steering.
The current study is about to investigate the role of supervisors research expertisein improvingacademic satisfaction and research skills of scholars. The main objective of the study is to find out that how supervisors research attitude effects the academic satisfaction of supervisees and play role in enhancing their research skills and command. For this purpose, study is conducted at M.Phil and PHD research scholars. Population of study is students enrolled in universities across the Pakistan. Especially the provincial and federal capital of Pakistan. 471 scholars participated in study as a sample. Data is collected through the questionnaire-based survey technique. This study adopts the partial least square (PLS) software to measure structural equation modeling (SEM) in term structural model and measurement model. The results of current study show strong relationship and effect of supervisors research support to scholars develop positive social and academic satisfaction among students. Research skills among students promote due to the expertise and proper guidance of supervisors to their supervisees.
