A Multi-attribute Online Advertising Budget Allocation Under Uncertain Preferences - Gupta Aggarwal, Anu; ., Aakash (Ingeniería Solidaria, 2018)
Introduction: The present research was conducted at the University of Delhi in 2017.Method: Websites were ranked on the basis of feedback from unbiased experts. Later, we proposed an integrated approach by combining ordered weighted averaging (owa) operator with fuzzy analytic hierarchy process (fahp) for budget allocation.Results: A numerical example related to a company, which deals with consumer goods and wants to advertise on few e-commerce websites is discussed at the end of the paper. Budget distribution is decided by solving multi-objective maximum-dispersion-minimum-variance (mdmv) owa and fahp method.Conclusions: The proposed methodology aids managerial decisions made by handling multiple attributes simultaneously through industry experts’ opinion, and using a simple proportional rule for allocating budget.Originality:  The conventional methods based on reach maximization, exposure or profit cannot meet the budget allocation needs of the modern advertising planning. Firstly, they do not take into consideration multiple attributes of media. Secondly, they do not incorporate the expert opinion and their preferences. To address these problems, we propose a multi-attribute method based on the advertising budget allocation method to divide the budget into individual websites. The attributes under consideration are: system quality, content quality, usage, trust, customer support, online customer feedback, and personalization.Limitations: In this study, we used a mdmv-owa operator in fuzzy environment but in future occasions, it may be extended to intuitionistic fuzzy domain.
Keywords: electronic commerce; fuzzy analytic hierarchy proces; maximum dispersion; minimum variance