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Forecasting the medium-term performance of restructured tourism firms with an adaptive integrated predictor
Tourism Management  (IF10.967),  Pub Date : 2021-09-17, DOI: 10.1016/j.tourman.2021.104436
Hui Li, Ling-Yang He, Jing-Jing Yang

This paper investigates the forecasting of the medium-term performance of restructured tourism firms using a new adaptive integrated predictor. The predictor incorporates internal characteristics of firms (economic factors and management practice), restructuring characteristics (strategy types and payment means), and timing (e.g. calendar month) of the restructuring. The results show that, the firms that perform better after restructuring are those that: a) have experience of operating under liability, b) are able to acquire large amounts of undistributed profit and liquid assets, and c) are able to increase their turnover. Tourism firms that generate large proportion of profit with their equity value and rapid growth in their operational income will suffer losses due to restructuring. Forecasting the medium-term performance of restructured tourism firms needs to take account of time heterogeneity derived from the periodicity (seasonality) inherent to the tourism industry. The adaptive integrated predictor presented in this paper performs better than a series of benchmark models, because it is able to allow for both the high-risk nature and periodicity of the tourism industry.