This paper aimed to study the effect between attitude, brand awareness, consumer experiences and price on young female purchase intention towards local cosmetic products in Malaysia. The main factor of consumer behaviour that used in this study was to analyse customer female purchase intention were attitude, brand awareness, consumer experience, and price. We used a survey questionnaire to collect 226 valid responses from a female student of Bachelor of Entrepreneurship (Retailing) with Honours in UMK. These collected data were analysed using Statistical Package for Social Science (SPSS) version 24 and the result gathered through the Pearson Correlation Coefficient and Multiple Regression. The findings revealed that attitude, brand awareness, consumer experiences, and price emerged with a significant influence on female intention toward local cosmetics among young female consumers. The implication from this study is for the female consumer who is wearing a cosmetic product, an industry or organization who involve in produce local cosmetic product and retailer who sale a local cosmetic product. Finally, the result shows that attitude influences young female purchase intention the most compared to brand awareness, consumer experiences, and price.
Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. WOA is known of having slow convergence and at the same time, the computation of the algorithm will also be increased exponentially with multiple objectives and huge request from n users. The current constraints surely limit for solving and optimizing the quality of Demand Side Management (DSM) case, such as the energy consumption of indoor comfort index parameters which consist of thermal comfort, air quality, humidity and vision comfort. To address these issues, this proposed work will firstly justify and validate the constraints related to the appliances scheduling problem, and later proposes a new model of the Cluster based Multi-Objective WOA with multiple restart strategy. In order to achieve the objectives, different initialization strategy and cluster-based approaches will be used for tuning the main parameter of WOA under different MapReduce application which helps to control exploration and exploitation, and the proposed model will be tested on a set of well-known test functions and finally, will be applied on a real case project i.e. appliances scheduling problem. It is anticipating that the approach can expedite the convergence of meta-heuristic technique with quality solution.
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