Ticket prices and revenue levels of tourist attractions in China: Spatial differentiation between prefectural units

Ticket pricing is a key issue for tourism research in China. Owing to regional differences, a unified nationwide price reduction strategy for tourist attractions would be inappropriate for China. To assist in regional ticket pricing decisions, this study uses ArcGIS spatial analysis methods to analyze the spatial differentiation of ticket prices and revenue levels between prefectural units, using 2017 data from 9450 A-grade tourist attractions. The results reveal prominent characteristics of spatial differentiation in tourist attractions’ average ticket prices, as well as in the proportion of their revenue from ticket sales, between prefectural units. Ticket prices are generally low in north China and high in south China; meanwhile, the proportion of ticket revenue is generally high in east China and low in west China. The factors influencing such spatial differentiation are tourism resources, local socio-economic conditions, and the management of tourist attractions. The findings help stakeholders to make differentiation strategy.     

国内旅游景区门票定价模型研究

本文从国内旅游景区门票价格制定影响因素实证研究结论出发，将定价影响因素与景区门票价格的相关系数予以标准化，并作为各因素决定门票价格的权重，同时从纵向对各因素进行科学的等级划分，进而构建出国内旅游景区门票的定价模型，并以南岳景区为例进行了实证，为我国旅游景区制定科学、合理的门票价格，提供了一种新的思路及其定价的实用模型。     

我国旅游景区门票多目标定价机制研究

传统产品定价研究大都从市场供需出发,以利润最大化来设置产品价格.然而景区门票价格是由市场因素和政策因素共同作用形成,景区门票定价不仅要满足景区经营方的利润最优目标,还应符合景区的生态承栽能力和社会福利目标.文章通过建立景区基于利润最优目标、生态承裁力目标和社会福利最优目标模型,证明了当追求利润最大化目标时,景区应该以产业利润最大化来制定门票价格；当景区生态承载能力低于产业利润最优的游客数量时,票价应该根据生态承栽人数来制定；当公共景区基于社会福利最优定价时,完全免费并不一定是社会福利的最优选择.在此基础上,对多目标定价机制进行比较分析,并结合杭州西湖景区案例对多目标门票定价机制进行了动态综合研究.     

A contingent valuation approach to estimating the recreational value of commercial whale watching – the case study of Faxaflói Bay,Iceland

There is currently limited knowledge concerning the economic value of commercial whale watching from the perspective of the consumer's trip experience. This study outlines the results of an in-person contingent valuation survey, which asked whale watching tourists in Faxaflói Bay, Iceland, how much they would have been willing to pay beyond the paid ticket price. Based on a sample of 163 tourists, only 30 (18.40%) reported any consumer surplus, despite the majority stating positive satisfaction with the experience. Mean consumer surplus was 768 ISK (approximately 5.60 euros). Scaled up to the number of whale watching tourists in Faxaflói Bay in 2018 of 148,442, aggregate CS was approximately 114.0 million ISK (0.83 million euros), a 6.9% mark-up on estimated annual revenue generation derived from average ticket prices. The study provides new information on the economic value of whale watching in an area which had already been part-designated as a whale sanctuary.     

An analysis of asymmetry in dynamic pricing of hospitality industry

The paper analyzes the influence of changing tourist arrival on various hotel performance measures related to prices, such as price charges per room, revenue per available room, occupancy rate, and total revenue using price dynamics of Oslo as a case. It also measured whether there is an asymmetric relation between the above performance measures in response to the increase and decrease of tourist arrival. While the presence of a significant long-run relationship between tourist arrival and revenue per available room, capacity utilization, and total revenue has been confirmed, it was found that the price per room does not have such a relationship, and it suggests that the price adjustments are made only on short-run considerations. Another interesting observation is that the magnitude of asymmetric influence is high for revenue per available room and occupancy rate when tourist arrival declines, compared to the corresponding magnitude when tourist arrival increases. These findings indicate that there lies a scope to improve the dynamic pricing model currently being followed.     

Competitive revenue management for fixing quota and price of hotel commodities under uncertainty

This article develops an artificial neural network (ANN) based forecasting model using the past profit records of hotel commodities. Based on forecasting, hotel commodities are categorised into two kinds: ones that push up the revenue, and others, which pull it down. Thereafter, long and short term goals are formulated for fixing quota and proper revenue management under uncertainty. For long term goal, analytical network process (ANP) framework is adopted to establish interrelationships among the factors using DEMATEL methodology. Risk adjusted maximum expected profit is employed for short term goal. Subsequently optimal numbers of commodities are obtained using a fuzzy goal programming approach, and favourable price of the individual commodities is determined keeping the price elasticity as one. Finally, a comparison is made between the respective revenue generated with the new quota and price from the proposed revenue maximization model, and that of the old practised price and quota. The paper demonstrates the superiority of the proposed approach. A case study of a hotel has been taken up to demonstrate the model.     

Improving revenue performance with third-degree price discrimination in the cruise industry

The leisure cruise industry has enjoyed high levels of growth for nearly five decades due in part to traveler interest in the cruise experience, but also to relatively lower pricing. Although revenue management of cruise fares is now standard practice, there are untapped opportunities to improve yields through data-driven market segmentation and third-degree price discrimination. This paper uses a finite mixture modeling approach to develop, empirically validate, and compare pricing models. By unveiling segments of travelers based on individual attributes, third-degree price discrimination can improve target marketing, the timing and appeal of price discounts, and the matching of variable demand with fixed, though differentiated, room supply. Empirical results from running thousands of simulations with pricing data from one of the world’s largest cruise lines show that the segmentation analysis using third-degree price discrimination can increase fare revenue more than four percent. The modeling approach used in this research extends the emerging literature on revenue management in the cruise industry and offers meaningful managerial implications for advanced pricing tactics and revenue management.     

A stochastic cost efficiency analysis of international tourist hotels in Taiwan

The one-stage stochastic frontier approach (SFA) is used in this study to simultaneously estimate cost efficiency scores and factors of cost inefficiency for 66 international tourist hotels in Taiwan during 1997–2006. An SFA model with three outputs and three inputs is defined. The three outputs are room revenue, food and beverage revenue, and other operation revenue while the three inputs are price of labor, price of other operation, and price of food and beverage. This model also takes into account five environmental variables, including dummy variable of the hotels located in non-metropolitan area, dummy variable of chain hotels, the number of tourist guides, the minimum distance from each hotel to Taoyuan international airport and the minimum distance from each hotel to Kaohsiung international airport. Empirical results show that international tourist hotels in Taiwan are on average operating at 91.15% cost efficiency. All nominal variables are transformed into real variables in 1997 prices by GDP deflators. Chain systems, tourist guides, and international transportation can significantly improve the cost efficiency of international tourist hotels in Taiwan.     

Importance of early snowfall for Swedish ski resorts: Evidence based on monthly data

Since the early 1970s, Sweden has experienced an almost uninterrupted surge in demand for downhill skiing. However, from the 2009/2010 season, lift ticket sales have stagnated. With the use of monthly data, this study investigates the role of snow depth and economic factors in the demand for downhill skiing in Sweden. The empirical approach is based on a seemingly unrelated regression model, allowing snow conditions, but not economic factors to differ during the season. The estimates show that an early season increase in natural snow depth by 10 cm raises the growth rate of lift ticket sales by 9 percentage points in the same period. Further, the results indicate that downhill skiing is characterised by low income and price elasticities, implying weak impacts on demand for such changes. The price increase of lift tickets exceeds that of the inflation rate. The recent decline in demand might indicate changed leisure preferences.     

How do advertising expenditures influence hotels’ performance?

Existing studies have shown a positive relationship between advertising and hotel room revenue. However, it is not clear through which channel advertising affects hotel revenue. We contribute to the literature by showing that advertising has a significant positive impact on hotel room price, but not on room occupancy. Thus, advertising affects room revenues through room price, not quantity demanded.     

Exploring effective price presentation format to reduce decision difficulty and increase decision satisfaction

Variable pricing is frequently employed by service firms that adopt revenue management practices. This strategy is effective in stimulating and increasing revenue by appealing to customers with different levels of price sensitivity. However, by providing excessive price options, a company may cause choice overload for customers. Within the framework of behavioral economics, this study explores an effective price presentation strategy to mitigate choice overload due to a large assortment size of price options in the context of hotels. The findings of the experimental design study suggest that the number of categories that distinguish and organize price options positively affects consumers' perceived decision difficulty and consequent decision satisfaction when a large assortment size of price options is provided. This research extends the understanding of the effect of variable pricing on consumers' responses and provides marketers with guidance on how to manage variable pricing and its price presentation format.     

Price and RevPAR determinants of Airbnb listings: Convergent and divergent evidence

This paper explores the performance determinants of Airbnb listings, analyzing three research questions. First, the study investigates the different effects generated by the antecedents on price and revenue; second, it ranks different groups of variables; third, it distinguishes between private rooms and entire homes or apartments. These research questions are addressed by analyzing Airbnb listings in Milan, a business city where the sharing economy is growing fast. In particular, the study will use the monthly data of all Airbnb listings in Milan recorded by AirDNA during the period from November 2014 to June 2019, which consists of 323,184 total observations. Some hedonic price models are calculated, adding the Shapley value approach. Empirical findings show some important differences between price and revenue determinants. Furthermore, listing type and size, along with location and seasonality, are by far the most important factors that explain performance differentials among Airbnb properties.     

Travel Agents and Their Survival Thomas

Abstract

The travel agency industry depends upon commissions for a majority of its revenue. When these commissions decrease or stop the industry must change the means in which revenue is made. The Internet has caused a significant reduction in airline ticket sales and therefore has caused travel agencies to change. In addition travel agencies have reduced commissions paid to airlines thus causing more changes. There were four categories of travel agencies discussed in the article along with their adaptation styles. These types include (1) the independent operator of a small travel agency with very limited resources (2) the normal agency with 2 or 3 agents which does a substantial business (3) the larger agency that is high-tech and high touch and depends on automation and the Web to some extent (innovators) (4) agencies that are Web based with very little automation otherwise and who were technologically adaptable and saw opportunity in the Web. The study examines how agencies have adapted and prospered through this transitional period.     

Dynamic pricing and revenues of Airbnb listings: Estimating heterogeneous causal effects

This paper investigates the extent to which the implementation of intertemporal price discrimination affects Airbnb listings’ revenue. We found that on average, a price surge (i.e., increasing the price as we approach the date of service consumption) has an adverse effect on revenue. However, the magnitude of such effect exhibits significant heterogeneity among listings. Through the application of generalized random forests, a causal machine learning technique, we identify exacerbating and moderating treatment modifiers and shed light on the listing dimensions that cause price surges to be particularly detrimental for hosts’ revenues.     

Let your algorithm shine: The impact of algorithmic cues on consumer perceptions of price discrimination

How can hospitality and tourism firms reduce consumers’ perceptions of unfairness regarding their price discrimination practices? We propose that pricing algorithms, as advanced revenue management tools, can play a role. We demonstrated the effects of an algorithmic cue through a tweet analysis and four experiments. We found that informing consumers that the offered price is determined by algorithms mitigated their negative responses in the disadvantaged price discrimination context. Also, such algorithmic cue effects only occur when the algorithm is less anthropomorphic (vs. highly anthropomorphic or human). The positive impact of an algorithmic cue was identified not only when customers directly experienced disadvantaged price discrimination but also when they obtained the information from different channels. The results suggest hospitality and tourism firms that have implemented pricing algorithms in their revenue management can benefit from disclosing an algorithmic cue to customers.     

How demand uncertainty and market concentration affect long-term price instability

The object of this paper was to investigate the long-term influences of demand uncertainty and market concentration on price instability in the hotel industry. We applied 1996–2008 price and room revenue data collected by Taiwan's Tourism Bureau to test the following two hypotheses: (1) demand uncertainty is negatively associated with price instability in the hotel industry; (2) the market concentration is negatively associated with hotel price instability. We constructed a two-stage price instability model and the estimate results produced the following two findings: First, the uncertainty in room demand significantly contributed to the price instability. Second, the effects of market structure on price instability were heterogeneous across different levels of price instability distribution. Notably, when the distribution of price instability moved from lower to higher quantiles, the relationship between market concentration and price instability altered from positive to negative.     

Function space revenue management: A product bundling approach to hotel function space utilization

This article extends revenue management research into non-traditional hotel operating departments pertaining to convention hotel function space. This research evaluates utilization patterns of multiple convention hotel function spaces and identifies concurrent high-, medium- and low-utilization groupings of multiple convention spaces using k-means clustering. These high- and low-utilization function space pairings allow us to identify convention spaces to target for additional revenue management oversight. A Bayesian analysis of potential lift in revenue per available foot (RPAF) attributable to product bundling concludes the research linking hot and cold function spaces compatible with value based price packaging opportunities.     

Do price promotions drive consumer spending on luxury hotel services? The moderating roles of room price and user-generated content

Price promotion, as price information, and user-generated content (UGC), as non-price information, play an important role in generating luxury hotel revenue. This study empirically investigates how price promotion influences actual consumer spending on luxury hotel services except room price, by considering the contingency role of room price and volume and valence of UGC. Combined data of daily settlements and Tripadvisor customer reviews of a regional luxury hotel chain are used for the analyses. The results indicate that, overall, price promotion negatively influences consumer spending on luxury hotel services and its negative effect is strengthened when the room is higher priced or the valence of UGC is high. Furthermore, a larger volume of intrinsic attribute-related UGC–amenity and location–with price promotion leads to more consumer spending than a larger volume of extrinsic attribute-related UGC–food and staff. The findings provide hotel managers with important insights into pricing and UGC management.     

Customer Loyalty under the Influence of Revenue Management: The Case of Taiwanese Hotel Customers

Revenue management (RM), a common practice for the hotel industry, has been found to be very effective in generating extra revenue. However, prior studies have shown that the implementation of RM may potentially be in conflict with customer loyalty, the basis for long-term profitability. With a view to alleviating the impact of RM on customer loyalty, this study investigates the relationship between customer loyalty and RM knowledge level, and examines the moderating effect of the fairness perception for pricing based on a survey and the related statistical analyses. The findings suggest that hotel operators should facilitate the RM knowledge and the fairness perception of their customers so as to result in a potential win-win situation, in which profit-seeking hotels increase their revenue through better resource utilization, and heterogeneous customers benefit from more diversified services.     

Conflict in tourism development in rural China

This paper explores the phenomenon of conflict in tourism development in rural China. Four cases were selected and analyzed as part of this exploration. The study identified eight major conflict issues: land expropriation, ticket revenue distribution, vending rights, tourism management rights, house demolition, house building, entry restrictions, and village elections. The conflict evolution process indicates that these issues are dynamic and connected rather than static and isolated. Local government was found to be the most important conflicting party for local people due to its authority and economic interests in tourism development. In addition, an often-ignored conflicting party, villagers' committees, was found to have limitations in maintaining local people's interests. The findings of this study shed light on this complicated and sensitive tourism conflict phenomenon in rural China. A couple of practical implications for local authorities and UNESCO are outlined at the end of the paper.