Dividend behavior of lodging firms: Heckman's two-step approach

This study examines lodging firms’ dividend behavior with a framework that clearly distinguishes between the two steps of dividend decisions: whether or not to pay and how much to pay. This study also investigates how firm characteristics influence the payment and amount decisions of dividends. Heckman's two-step approach is used for data analyses because it can differentiate between the two stages of dividend decisions, precluding potential sample selection bias. Results imply that the way in which firm characteristics affect the two steps of dividend decisions are indeed different. The payment of dividends is determined by many firm financial characteristics, the previous year's dividend amount, and some external year-specific events. The variation in the amount of dividends, by contrast, is not explained by such firm characteristics. Only the previous year's dividend amount and some year-specific events have a significant impact on the decision of dividend amount. Results also present some interesting findings, which may contribute to a better understanding of lodging firms’ unique dividend behavior.     

Prediction accuracy for reservation-based forecasting methods applied in Revenue Management

With a few notable exceptions, airlines and hospitality forecasting research has been focused so far on point predictions of customers’ bookings. However, Revenue Management decisions are subject to a much greater risk when based exclusively on point predictions. To overcome this drawback, we propose a stochastic framework that allows the construction of prediction intervals for reservation-based (pickup) forecasting methods, which are widely used in the industry. Moreover, we introduce an extension of the multiplicative pickup technique based on Generalized Linear Models. We test the proposed framework with real reservation data from a medium-sized hotel on Lake Maggiore (Italy) and we obtain more efficient prediction intervals relative to classical time series methods. Our approach can be useful to hotel revenue managers that wish to make more informed decisions, planning alternative pricing and room allocation strategies for a range of possible demand scenarios.     

An exploratory analysis of hotel selection factors: A comprehensive survey of Tehran hotels

The selection of residence location in different countries is of high priority and significance for tourists. The selection of the most appropriate hotel entails a rather complicated decision-making process. A comprehensive hotel selection model can empower the hotel managers, the tourists, and the tourism industry to make decisions based on more effective indicators of high quality services for a higher rate of satisfaction. The purpose of this research is to deeply explore the broad literature and to identify the most significant hotel selection indicators and factors in Tehran hotels and to present a comprehensive model through an exploratory factor analysis of the extracted indicators so as to provide the managers and tourists with a firm ground for making better decisions regarding the indicators of hotel selection. Promenade and comfort, security and protection, network services, pleasure, staff and their services, news and recreational information, cleanliness and room comfort, expenditure, room facilities and car parking were identified as the main hotel selection factors of Tehran hotels. Afterwards, another factor analysis has been done in order to extract the next hidden set of factors within the aforementioned factors which return two main factors of “Hotel Comfort Factors” and “Hotel Compensatory Factors”. Following the creation of the final model and based on the intrinsic vagueness of decision making in the process of selection, a set of fuzzy membership functions for the extracted factors has been provided. The intention has been to provide the expert system and decision support system developers and users with a set of practical indicators in order to help them design and implement realistic systems based on the deeply studied indicators and factors of hotel selection. Such supportive systems can be directly presented to the tourists requesting a mechanism for selecting the most appropriate hotel but lacking enough information about the important indicators and factors and also to the managers of hotels who are trying to make strategic decisions regarding the most optimized investments on the indicators of selecting a hotel. Considering the priorities of tourists, hotel managers, entrepreneurs and investors in the hotel industry require deep investigations and studies for which this paper provides a firm basis.     

Hotel pricing at tourist destinations – A comparison across emerging and developed markets

The application of price hedonic theory in the hotel pricing domain has relatively ignored the destination and country-level differences. We compare hotel rents across tourist and non-tourist destinations for an emerging (India) and a developed (USA) market. Utilizing multiple regression on a combined dataset of 21,904 data points spread over 2458 unique hotels, we show that the nature of destination and market moderates the association between hotel attributes and rents. Further, the results show that hotels at tourist destinations enjoy a rent premium across markets. However, this rent premium is positively associated with star rating, only in emerging markets, and is stable in developed markets. We contribute to price hedonic theory by proposing destination and market variables as moderators. Globalization and industry concentration make location decisions recurring and flexible. The study aims to help hotel managers by providing a contextual framework for making these strategic investment decisions.     

Different from or similar to neighbors? An investigation of hotels' strategic distances

This paper examines how conformity and differentiation impacts hotel performance. It evaluates strategic outcomes of hotel entrepreneurs' choice of geographic location, capacity, and quality. Using instrumental variable (IV) estimation, we find that the distribution of similar competitors affects hotel performance and performance risk. Specifically, results show that choosing a similar capacity (conformity) to competitors may lead to higher and more stable performance. The results also reveal that locating geographically close to competitors or choosing a similar quality of product to competitors (both conformity strategies) can increase hotel performance but also increases performance risk. Additionally, when mixing conformity and differentiation strategies in terms of location, capacity, and quality selection, a higher dispersion of differentiation (i.e., highly differentiated in one product dimension while conforming to others in all remaining product dimensions) increases both performance and performance risk. Findings of this study can aid entrepreneurs in improving their strategic decisions and product positioning.     

Senior Travelers and Airport Shopping: Deepening Repurchase Decision-making Theory

Despite the importance of the seniors market, little is known about international senior tourists' post-purchasing behaviors in the airport-shopping industry. The aims of this study were to attain a better comprehension of these customers' repurchase decision formation by employing a Theory of Repurchase Decision-making (TRD) and identify differences in the proposed theoretical framework between senior and non-senior travelers. A field survey was conducted to collect data at international airports. Results of a structural model showed that the TRD has an excellent ability to predict seniors' repurchase intentions; some variables in the model were found to have a significant mediating impact. Additionally, satisfaction was determined to play a prominent role in these decisions. Finally, findings from the test for metric invariance revealed that the proposed theoretical framework significantly differed across senior and non-senior tourist groups, verifying the moderating impact of age. Implications for both researchers and practitioners are discussed.     

Modelling Site Location Decisions in Tourism

Site location analysis and retail location strategy can be considered critical factors and integral elements of an effective organizational business plan in the tourism industry. This paper focuses on two different approaches that can be applied to site location analysis and selection in tourism: spreadsheet models and the analytic hierarchy process (AHP). Rule Based Expert Systems are also discussed. The LOCAT model (a spreadsheet-based algebraic approach) attempts to measure the total attractiveness index of a particular site location on the basis of calculating the impact of components (degrree of accessibility, total catchment population, level of tourist product uniqueness, and probability of tourist patronization). A practical example testing the degree of applicability of the model is also introduced. The Analytic Hierarchy Process provides a general structure capable of representing a wide range of decision problems. It is especially effective when dealing within complex multivariate decisions and with variables which are difficult to quantify.     

Ethical travel decisions travel agents and human rights

This paper explores the ethics of selling tourism products for destinations that have known major human rights issues. The study uses the moral intensity framework to analyze the ethical decisionmaking of New Zealand travel agents. Qualitative interviews reveal support for all aspects of the framework. In particular, agents’ judgements are strongly influenced by their perceptions of how their decisions impact upon their clients. In contrast, uncertainty surrounds the probability and magnitude of consequences of their decisions for destination communities. Strong social, cultural, legal, and economic links between the agent and the more proximate stakeholders mean that ethical decisions commonly favor these stakeholders.     

A fuzzy multi-criteria decision model for international tourist hotels location selection

The main purpose of this paper is to present a fuzzy multi-criteria decision making (FMCDM) model for international tourist hotel location selection. In this article we created 21 criteria for selecting the international tourist hotel location acquired from literatures review and practical investigations. And the methods of fuzzy set theory, linguistic value, hierarchical structure analysis, and fuzzy analytic hierarchy process are used to consolidate decision-makers’ assessments about criteria weightings. Finally, an empirical study for identifying the international tourist hotel location selection in Taiwan is conducted to demonstrate the computational process and effectiveness of FMCDM proposed by this paper.     

Understanding travel tracking mobile application usage: An integration of self determination theory and UTAUT2

By integrating the Self-Determination Theory (Deci & Ryan 1985) and a modified version of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework (Venkatesh et al., 2012), this study aimed to investigate factors affecting travelers' intention to share their travel-related information on travel tracking mobile applications (TTMA). The proposed model was tested via structural equation modeling by using data collected from 305 mobile app users. The results revealed that effort expectancy, hedonic motivation, social benefits, self-image had a positive impact; and location privacy concern had a negative impact on users' intention to post travel-related information on TTMAs. The findings of the current study contribute to the literature in the context of technology acceptance in general, and TTMA acceptance in the travel and tourism industries in particular. The study results also provide practical implications, especially for entrepreneurs and tourism-related technology companies.     

The COVID-19 pandemic: The mitigating role of government and hotel support of hotel employees in Egypt

We investigated the effect of government support of hotels on hotels' employee support (namely, health support, staff retention, and staff training) and consequently on employee job satisfaction and organizational commitment, through the moderating role of perceived overall organizational justice and ethical climate, during the COVID-19 pandemic. Using a quantitative approach and a framework that drew on the stakeholder and organizational support theories, we collected data from 669 employees in Egyptian hotels through a web-based survey. The results support the proposed framework and show a positive effect of government support through the strengthened perception of perceived overall organizational justice. Surprisingly, findings indicated that the association between job satisfaction and organizational commitment is significantly and negatively influenced by hotel ethical climate. Furthermore, job satisfaction partially mediates the association between hotels’ support of employees and organizational commitment. The study holds important implications for both theory and practice.     

The Impact of Supplier Development on Financial Performance in the Restaurant Industry

ABSTRACT

Many firms have come to recognize the crucial role that cooperative relationships with suppliers play in determining high financial performance. Of main concern in many firms are supplier development activities and behaviors (SDABs) of buying firms, which are an attempt to meet current and future business needs such as high financial performance by improving supplier performance. The purpose of this study is to evaluate how buying firms' SDABs affect supplier performance (in delivery as well as product and service quality) and its impact on financial performance of the buying firms. The authors critically revisit extant knowledge on the subject, develop a conceptual framework integrating buyer and supplier relationship marketing/management practices, and test the framework in the independent restaurant industry context. Using structural equation modeling and data collected from 236 restaurant owners and/or presidents in the United States, the results of this research support the usefulness of the framework, showing that buying firms' SDABs directly affect supplier performance, which leads to high financial performance of the buying firms.     

Understanding the FLE-based organizational knowledge creation process in hospitality firms

This study explores how front-line employees' (FLE) knowledge is stepwise transformed into a hotel's organizational knowledge. It combines insights from organizational knowledge creation theory with empirical evidence from three Chinese five-star hotels. Qualitative data were collected through semi-structured interviews and reading archives, and analyzed using thematic analysis. We develop a novel framework comprising three types of FLEs' knowledge activities–knowledge demonstration (KD), knowledge justification (KJ), and knowledge re-contextualization (KRC)–which can routinely trigger the hotel's bottom-up organizational knowledge creation process. We also explain how FLEs' KD/KJ/KRC activities facilitate the hotel's organizational knowledge creation practices by examining changes in the new knowledge's scope of application and the participant structure of knowledge-related interactions induced by these activities. This study contributes to knowledge management research in hospitality by proposing a new perspective that encompasses FLEs' knowledge activities and the concomitant knowledge transformation that occurs in hotels.     

IDENTIFYING LEISURE TRAVEL MARKET SEGMENTS BASED ON PREFERENCE FOR NOVELTY

The motivation and knowledge of travelers affects their choice of destination and selection of activities while on vacation. Understanding motivation is important for all stakeholders in the tourism industry. The search for novelty is one motivating factor when planning leisure trips and vacation activities. A foreign destination offers a form of novelty to the traveler because it can provide experiences that are not of the everyday variety. The chosen location may have specific geographical features, a different cultural background, special shopping opportunities, a different language, new foods, and unique leisure activities that can provide a novel experience. The purpose of this study is to identify segments of potential U.S. leisure travelers based on their level of novelty seeking and to investigate the relationship between travelers' levels of novelty seeking and their knowledge of a destination and preferred travel style.     

Developing energy conservation and carbon reduction indicators for the hotel industry in Taiwan

This study develops and weights energy conservation and carbon reduction (ECCR) indicators for the hotel industry in Taiwan to create an instrument to help address climate change. Eighteen semi-structured interviews were conducted with senior hotel managers, environmental specialists, and government officials to identify the preliminary ECCR framework. An expert panel then was invited to review the structure of ECCR criteria and the compiled criteria in a structure for item modification. An analytic network process questionnaire survey was employed to determine the relative weights of the criteria. The data analysis reveals seven categories in the ECCR framework: communication and participation, top management commitment, energy, water, waste, building, and purchasing. A total of 32 indicators were identified and prioritized in terms of their relative importance to ECCR contributions. The results of this study suggest that the success of ECCR implementation depends primarily on management support and staff engagement. Hotel operators can improve their environmental management by initiating ECCR practices based on the proposed ECCR indicators.     

Green purchase and sustainable consumption: A comparative study between European and non-European tourists

This research aims to investigate tourists' sustainable consumption values and choice behaviour regarding green products in Europe by integrating the Theory of planned behaviour (TPB) and consumption values (TCV). This study also compares the decisions of European and non-European tourists to purchase green products and services while travelling in some selected European cities. A total number of 720 useable questionnaires were collected from residents of two tourist groups in Europe. PLS-SEM, MGA, and other newly developed advanced analysis methods were applied to test the model and hypotheses. Findings reveal that environmental attitudes, environmental knowledge, subjective norms, perceived behavioural control, conditional value, and emotional value have a significant positive relationship with green purchase intentions for European and non-European tourist groups. To our knowledge, this is the first empirical study that broadly provides a theoretical framework for green purchase choice and sustainable consumption intention in Europe. The theoretical and practical contributions to tourists' purchasing green products are discussed.     

Forecasting business failure: The use of nearest-neighbour support vectors and correcting imbalanced samples - Evidence from the Chinese hotel industry

Previous studies on firm failure prediction (FFP) have chiefly addressed predictions based on balanced datasets without considering that the real-world target population consists of imbalanced data. The current study investigates tourism FFP based on the imbalanced data of Chinese listed companies in the hotel industry. The imbalanced dataset was collected and represented in terms of significant financial ratios, and a new up-sampling approach and forecasting method were proposed to correct imbalanced samples. To balance the imbalanced dataset, the up-sampling method generates new minority samples according to random percentage distances from each minority sample to its nearest neighbour (NN). The NNs of unlabelled samples are retrieved from the balanced dataset to produce a knowledge base of nearest-neighbour support vectors, from which base support vector machines (SVMs) are generated and assembled. Empirical results indicate that the proposed sampling approach helped models produce more accurate performance on minority samples, with accuracy rates in excess of 90 per cent. This method of using nearest-neighbour support vectors and correcting imbalanced samples is useful in controlling risk in tourism management.     

Forecasting Chinese cruise tourism demand with big data: An optimized machine learning approach

After more than ten years of exponential development, the growth rate of cruise tourist in China is slowing down. There is increasingly financial risk of investing in homeports, cruise ships and promotional activities. Therefore, forecasting Chinese cruise tourism demand is a prerequisite for investment decision-making and planning. In order to enhance forecasting performance, a least squares support vector regression model with gravitational search algorithm (LSSVR-GSA) is proposed for forecasting cruise tourism demand with big data, which are search query data (SQD) from Baidu and economic indexes. In the proposed model, hyper-parameters of the LSSVR model are optimized with GSA. By comparing these models with various settings, we find that LSSVR-GSA with selected mobile keywords and economic indexes can achieve the highest forecasting performance. The results indicate the proposed framework of the methodology is effective and big data can be helpful predictors for forecasting Chinese cruise tourism demand.     

Why do you use Yelp? Analysis of factors influencing customers’ website adoption and dining behavior

The number of review websites has increased within the past years since more people rely on online reviews to help their decision-making process. Previous studies have either focused on the attributes of the content posted on review websites (i.e., reviews) or customers’ behavior concerning their selection of review website on which to post reviews. This study, however, extends the Technology Acceptance Model (TAM) to investigate the factors that influence individuals’ restaurant review website adoption behaviors to read reviews and make dining decisions. In addition, this study will look at the differences in individuals’ perceptions of various restaurant review websites (i.e., Yelp vs. others). The findings revealed the role of influential factors on individuals’ review website adoption and dining decisions as well as the differences in proposed structural relationships among various restaurant review websites.     

Exploring Everyday Self-Regulation in Nearby Nature: Determinants,Patterns, and a Framework of Nearby Outdoor Recreation Behavior

The understanding of determinants and underlying mechanisms of everyday nearby outdoor recreation behavior (NORB) remains insufficient for use in urban planning. We explored the nearby recreational decisions of walkers, cyclists, and joggers in problem-focused interviews (N = 18). The identified influences include various demands of work and private life, strains, and action circumstances. Loads and strains showed several compensatory associations with NORB. These findings were synthesized into a NORB framework that offers empirically grounded hypotheses for future research. The proposed framework may help to integrate findings from different research fields while providing a more comprehensive understanding of NORB.