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on Tourism Economics |
| By: | Chia-Lin Chang; Hui-Kuang Hsu; Michael McAleer (University of Canterbury) |
| Abstract: | This paper uses monthly data from April 2005 to August 2013 for Taiwan to propose a novel tourism indicator, namely the Tourism Conditions Index (TCI). TCI accounts for the spillover weights based on the Granger causality test and estimates of the multivariate BEKK model for four TCI indicators to predict specific tourism and economic environmental indicators for Taiwan. The foundation of the TCI is the Financial Conditions Index (FCI), which is derived from the Monetary Conditions Index (MCI). The empirical findings show that TCI weighted by spillovers reveal greater significance in forecasting the Composite Index (CI), an economic environmental indicator, than the Tourism Industry Index (TII), which is an existing indicator for the tourism industry that is listed on the Taiwan Stock Exchange (TWSE). Moreover, previous values of the alternative TCI and TII are shown to contain useful information in predicting both tourism and economic environmental factors. Overall, the new Tourism Conditions Index is straightforward to use and also provides useful insights in predicting tourism arrivals and the current economic environment. |
| Keywords: | Monetary Conditions Index (MCI), Financial Conditions Index (FCI), Tourism Conditions Index (TCI), BEKK, Spillovers, Granger causality |
| JEL: | B41 E44 E47 G32 |
| Date: | 2014–01–10 |
| URL: | http://d.repec.org/n?u=RePEc:cbt:econwp:14/03&r=tur |
| By: | Najda-Janoszka, Marta |
| Abstract: | According to the open innovation model an effective strategy for increasing innovation and competitiveness of the region should be based on active and multilevel cooperation among operators of the local tourism business environment. It is commonly assumed that an exceptionally important role in creating a favorable environment for the cooperative practices in the region is performed by local authorities. Yet, a modest number of research findings presented in the literature indicate a rather high level of inertia of local authorities in creating appropriate conditions for tourism business development, thus putting in question the effectiveness of performed intermediary function in the process of knowledge transfer among tourist enterprises. Given the paucity of empirical evidence on effectiveness of innovation policy interventions at the regional level, this article presents the empirical findings regarding cooperation in innovation between tourist enterprises and local institutional agents. |
| Keywords: | tourism, innovation, cooperation, institutional environment, local government |
| JEL: | H70 L83 O31 |
| Date: | 2013–09–15 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:52991&r=tur |
| By: | Sumit Kunnumkal; Kalyan Talluri |
| Abstract: | The choice network revenue management (RM) model incorporates customer purchase behavior as customers purchasing products with certain probabilities that are a function of the offered assortment of products, and is the appropriate model for airline and hotel network revenue management, dynamic sales of bundles, and dynamic assortment optimization. The underlying stochastic dynamic program is intractable and even its certainty-equivalence approximation, in the form of a linear program called Choice Deterministic Linear Program (CDLP) is difficult to solve in most cases. The separation problem for CDLP is NP-complete for MNL with just two segments when their consideration sets overlap; the affine approximation of the dynamic program is NP-complete for even a single-segment MNL. This is in contrast to the independentclass (perfect-segmentation) case where even the piecewise-linear approximation has been shown to be tractable. In this paper we investigate the piecewise-linear approximation for network RM under a general discrete-choice model of demand. We show that the gap between the CDLP and the piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinear approximation is polynomially-time solvable for a fixed consideration set size, bringing it into the realm of tractability for small consideration sets; small consideration sets are a reasonable modeling tradeoff in many practical applications. Our solution relies on showing that for any discrete-choice model the separation problem for the linear program of the piecewise-linear approximation can be solved exactly by a Lagrangian relaxation. We give modeling extensions and show by numerical experiments the improvements from using piecewise-linear approximation functions. |
| Keywords: | Optimization Techniques; Programming Models; Dynamic Analysis; Air Transportation ; Sports; Gambling; Recreation; Tourism; Production Management |
| JEL: | C61 L93 L83 M11 |
| Date: | 2014–01 |
| URL: | http://d.repec.org/n?u=RePEc:upf:upfgen:1409&r=tur |