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Between app efficiency and user wellbeing: a cluster analysis on consumer types and continuance usage of food delivery app

Trinh Thu Thi, Mai Xuan Tai

Annals of Computer Science and Information Systems

2022

Vol. 34

69--74

The introduction of food delivery apps, facilitated by the global pandemic, has created a significant disruption in the hospitality industry. However, how consumers use mobile applications in the context of daily choices and food consumption has not been fully explored. Using data collected through an online questionnaire comprising 165 food delivery app subscribers, k-mean cluster analysis was performed to classify users based on their internal motivations. The results reveal three distinct groups: Health-conscious Eaters, Food Enthusiasts, and Lifetime Diners. Practically, the present exploratory study assists FDA providers to better identify customers, so potentially optimizing marketing initiatives, and maximizing profitability.

Fuzzy model for the information and decision making support system for the CFM branch company

Walaszek-Babiszewska A., Chudzicki M.

Applied Computer Science

2006

Vol. 2, no 1

110--121

The aim of this work is to present the ways of improvement the management process in the CFM company, by developing and implementing the Management Information System (MIS). In the first chapter the characteristic of Car Fleet Management company is presented. The second chapter describes how MIS could support management of that type of company, as well as general and functional requirements of the computer application. Third chapter presents an example of methodology of solving selected decision-making problem using a fuzzy rule-based model.