Differential effects of patriotism and support on post-development visit intention: the Korean DMZ Peace Park

This study investigates how resident support for the development of the demilitarized zone (DMZ) Peace Park incorporates two key components (support and patriotism) as part of the theory of planned behavior (TPB). The results of this study confirm that support is important because it is directly associated with three TPB constructs, and it acts as a mediator between patriotism and the three TPB constructs. Both support and patriotism are statistically significant but different depending on the distance to the DMZ Peace Park. Resident support in the predevelopment stage can possibly extend to behavioral support in the post-development stage.     

How do green attributes elicit pro-environmental behaviors in guests? The case of green hotels in Vietnam

This study aims to identify green-hotel attributes and determinants that contribute to guests’ intention generation for visiting a green hotel and practicing pro-environmental actions during their hotel stay. The study’s results find five dimensions (Customer benefit, Energy efficiency, Water efficiency, Recycling policy and Green characteristic) that underlie 24 green-hotel attributes. Out of the five dimensions, Customer benefit, Energy efficiency, and Green characteristic are found to positively affect pro-environmental value and attitude that in turn enhance intention to practice environmentally friendly actions and visit a green hotel, while pro-environmental value does not trigger pro-environmental attitude. Theoretical and managerial implications are discussed.     

Alone with others: The paradox of privacy in wilderness

Attitudinal studies of wilderness visitors have indicated that people seek opportunities to limit interaction with other visitors so as to achieve privacy and solitude. This conventional interpretation of wilderness recreation was evaluated by comparing measures of visitor attitudes and social behavior in the backcountry of Yosemite National Park. Results show no association between visitor attitudes toward crowding and observed social interaction or behavior to avoid such social interaction. These findings suggest that subjective responses of visitors measured by questionnaires and interviews are often of debatable validity. Greater validity can be achieved by avoiding reliance on common‐sense interpretations in theory formulation and by employing multiple measurement techniques.     

The Moderating Role of Water Park Service Quality,Environment, Image,and Food Quality on Perceived Value and Customer Loyalty: A South Korean Case Study

This study empirically examined not only the relationship between perceived value and customer loyalty, but also the moderating role of service quality, environment, image, and food quality at a water park, a segment of the tourism industry. In particular, the current study, using hierarchical regression analyses, examined the direct effects of perceived value on customer loyalties—loyalty and behavioral loyalty—as well as the moderating effect of four elements. As anticipated, this study showed that perceived value has significant and positive effect on both types of loyalty. In addition, the result of the interaction effects showed that service quality and food quality acted as moderators on the relationship between perceived value and attitudinal loyalty; however, water park image acted as a moderator on the relationship between perceived value and behavioral loyalty only. Finally, these results indicated that three elements—service quality, water park image, and food quality—have significant interaction on the relationship between perceived value and attitudinal/behavioral loyalty. These findings may provide water park operators with useful and detailed guidelines for satisfying customer loyalty levels, both attitudinally and behaviorally. More detailed findings and implications are also discussed.     

An analysis on perceived crowding level reported by domestic visitors of South Korean National Parks: a multilevel ordered logit approach

Perceived Crowding Level (PCL) is an indicator of the social carrying capacity of recreational sites such as National Parks. Using a sample of national-level visitor survey data across 21 National Parks in South Korea, this paper aims to apply a multilevel ordered logit model as a method in testing for statistical relationships between the PCL and the covariates, accounting for site- and individual-specific heterogeneity. The results hint that levels of perceived crowding in South Korean National Parks are related to factors such as the behaviour of other users and the quality of park facilities such as comfort in accommodation. The measured level of heterogeneity can provide useful information about the level (nation-wide or park-specific) of intervention policies and management strategies.     

Investigating the key drivers of traveler loyalty in the airport lounge setting

This study intended to examine the structural relationships among functional congruity factors, delight, well-being perception, brand identification, and traveler satisfaction in the formation of air traveler loyalty for airline lounges. The survey sample consisted of 394 air travelers who visited an airline lounge in airport in the U.S. during the past six months. Structural equation modeling was used to test the conceptual model. Results of the structural equation modeling indicated that functional congruity of the physical environments and facilities were significantly and positively associated with delight, which in turn, affected air travelers’ perceived well-being and satisfaction level in the lounge. It was also found that well-being perception significantly and positively affected brand identification and satisfaction, and loyalty was a positive and significant function of satisfaction. The mediation test showed that delight and well-being perception were significant mediators in the proposed theoretical framework. Practical and theoretical implications are discussed.     

Capital City Museums and Tourism Flows: an Empirical Study of the Museum of New Zealand Te Papa Tongarewa

This study uses time series analysis to explore the extent to which the opening of the Museum of New Zealand in 1998 contributed to tourism growth in the nation's capital, Wellington. With the use of a series of different measures for tourism and major events in the city, econometric regressions are undertaken to better understand the relationship between visitors to the museum and tourism growth in the city's short‐term commercial accommodation sector. The findings are consistent with the museum having a positive impact on tourist arrivals and overnight stays. These results contribute valuable empirical evidence of the positive role of museums in attracting tourists to urban centres. Copyright © 2012 John Wiley & Sons, Ltd.     

Delta Boosting Machine with Application to General Insurance

In this article, we introduce Delta Boosting (DB) as a new member of the boosting family. Similar to the popular Gradient Boosting (GB), this new member is presented as a forward stagewise additive model that attempts to reduce the loss at each iteration by sequentially fitting a simple base learner to complement the running predictions. Instead of relying on the negative gradient, as is the case for GB, DB adopts a new measure called delta as the basis. Delta is defined as the loss minimizer at an observation level. We also show that DB is the optimal boosting member for a wide range of loss functions. The optimality is a consequence of DB solving for the split and adjustment simultaneously to maximize loss reduction at each iteration. In addition, we introduce an asymptotic version of DB that works well for all twice-differentiable strictly convex loss functions. This asymptotic behavior does not depend on the number of observations, but rather on a high number of iterations that can be augmented through common regularization techniques. We show that the basis in the asymptotic extension differs from the basis in GB only by a multiple of the second derivative of the log-likelihood. The multiple is considered to be a correction factor, one that corrects the bias toward the observations with high second derivatives in GB. When negative log-likelihood is used as the loss function, this correction can be interpreted as a credibility adjustment for the process variance. Simulation studies and real data application we conducted suggest that DB is a significant improvement over GB. The performance of the asymptotic version is less dramatic, but the improvement is still compelling. Like GB, DB provides a high transparency to users, and we can review the marginal influence of variables through relative importance charts and the partial dependence plots. We can also assess the overall model performance through evaluating the losses, lifts, and double lifts on the holdout sample.     

Statistically based quarterly earnings expectation models for nonseasonal firms

We present empirical evidence on the relative predictive power of statistically based quarterly earnings expectation models for firms that are characterized as nonseasonal in nature. We are particularly interested in nonseasonal firms for two reasons. First, it appears that a sizable and growing percentage of firms exhibit quarterly earnings patterns that are clearly nonseasonal in nature. We present new evidence that is consistent with this trend. Specifically, 36% of our sample firms (n = 296) are nonseasonal compared to 12% reported in Lorek and Bathke (J Acc Res 22:369–379, 1984) (n = 29); 17% in Brown and Han (J Acc Res 38:149–164, 2000) (n = 155); and 28.2% in Bathke et al. (J Business Inquiry 5:39–49, 2006) (n = 167). Second, we also find that 43.6% of the nonseasonal firms in our sample have no analyst coverage. Therefore, interest in the predictive ability of statistically based models for such firms is greatly enhanced. Our predictive findings indicate that the random walk model provides significantly more accurate pooled, one-step ahead quarterly earnings predictions across 40 quarters in the 1994–2003 holdout period than the first-order autoregressive model popularized in the literature. We attribute the superior performance of the random walk model to at least three contributing factors: (1) its parsimonious nature; (2) the reduced levels of autocorrelation observed in our quarterly earnings data relative to previous work; and (3) a significantly greater frequency of loss quarters evidenced by nonseasonal versus seasonal firms.