Constructing an investment selection model for a Chinese movie ticketing App based on ANP-TOPSIS

Abstract

Chinese firms are actively investing in movie ticketing Apps, but there is no unified model for how to evaluate such investments, which can hinder investment decision-making into such ticketing Apps. Currently, there is limited research on the criteria for investors to select the best Chinese movie ticketing Apps. To fill this gap, the present study proposes a three-stage evaluation model for investments in these specific Apps. First, it constructs a new hierarchy for movie ticketing App networks via the Modified Delphi Method (MDM), which consists of 5 criteria and 20 sub-criteria. Second, we apply the Analytic Network Process (ANP) to calculate the weight of the criteria and sub-criteria, finding that information is the most important, followed by system, trust, service, and word-of-mouth (WOM) in that order. Finally, three movie ticketing Apps are utilized as alternatives, and the best alternative is selected by Techniques for Order Preference Similarity Ideal Solution (TOPSIS) to verify the model’s feasibility. The results herein offer theoretical and practical insights for the development and promotion of movie ticketing Apps and provide a reference for investors to formulate relevant financing strategies.