A data-driven quantitative assessment model for taxi industry: the scope of business ecosystem’s health

Autor: Miner Zhong, Yong Zhang, Yunjian Jiang
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: European Transport Research Review, Vol 9, Iss 2, Pp 1-14 (2017)
ISSN: 1866-8887
1867-0717
DOI: 10.1007/s12544-017-0241-0
Popis: Introduction The taxi industry has boomed over the years, both in street-hail and dispatch market. However, few studies focus on comprehensive perspectives, which make decisions such as implementing regulative or incentive policies difficult. As an economic community working in the value-oriented process, the taxi industry requires a holistic performance evaluation to determine how to adapt strategies to survive and grow. Methods This paper proposed the concept “Taxi Industry Health degree” based on the theory of Business Ecosystem and the evaluation of its health. A four-layer criteria set is developed from aspects of robustness, productivity and sustainability, and weights are determined through Analytic Hierarchy Process. Results A synthetic evaluating model combining Fuzzy Comprehensive Evaluation and Artificial Neural Network is used to maintain the goal of multi-criteria decision-making. With the GPS and Taximeter dataset of taxicabs in the whole taxi industry in Wuxi, the model is applied to empirical studies. Conclusions This paper provides sensibility analysis on not only the company’s order volatility, revenue growth and utilization of resources, but also influence on citizen’s welfare, energy consumption and environmental pollution, which enables practical regulations and policies within taxi industry.
Databáze: OpenAIRE