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1 – 10 of over 19000Yang Yang, Graziano Abrate and Chunrong Ai
This chapter provides an overview of the status of applied econometric research in hospitality and tourism management and outlines the econometric toolsets available for…
Abstract
This chapter provides an overview of the status of applied econometric research in hospitality and tourism management and outlines the econometric toolsets available for quantitative researchers using empirical data from the field. Basic econometric models, cross-sectional models, time-series models, and panel data models are reviewed first, followed by an evaluation of relevant applications. Next, econometric modeling topics that are germane to hospitality and tourism research are discussed, including endogeneity, multi-equation modeling, causal inference modeling, and spatial econometrics. Furthermore, major feasibility issues for applied researchers are examined based on the literature. Lastly, recommendations are offered to promote applied econometric research in hospitality and tourism management.
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Doris Chenguang Wu, Haiyan Song and Shujie Shen
The purpose of this paper is to review recent studies published from 2007 to 2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging…
Abstract
Purpose
The purpose of this paper is to review recent studies published from 2007 to 2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field.
Design/methodology/approach
Articles on tourism and hotel demand modeling and forecasting published mostly in both science citation index and social sciences citation index journals were identified and analyzed.
Findings
This review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, whereas disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area.
Research limitations/implications
The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting.
Practical implications
This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices.
Originality/value
The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.
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Houtian Ge, Jing Yi, Stephan J. Goetz, Rebecca Cleary and Miguel I. Gómez
Using recent US regional data associated with food system operations, this study aims at building optimization and econometric models to incorporate varying influential factors on…
Abstract
Purpose
Using recent US regional data associated with food system operations, this study aims at building optimization and econometric models to incorporate varying influential factors on food hub location decisions and generate effective facility location solutions.
Design/methodology/approach
Mathematical optimization and econometric models have been commonly used to identify hub location decisions, and each is associated with specific strengths to handle uncertainty. This paper develops an optimization model and a hurdle model of the US fresh produce sector to compare the hub location solutions between these two modeling approaches.
Findings
Econometric modeling and mathematical optimization are complementary approaches. While there is a divergence between the results of the optimization model and the econometric model, the optimization solution is largely confirmed by the econometric solution. A combination of the results of the two models might lead to improved decision-making.
Practical implications
This study suggests a future direction in which model development can move forward, for example, to explore and expose how to make the existing modeling techniques easier to use and more accessible to decision-makers.
Social implications
The models and results provide information that is currently limited and is useful to help inform sustainable decisions of various stakeholders interested in the development of regional food systems, regional infrastructure investment and operational strategies for food hubs.
Originality/value
This study sheds light on how the application of complementary modeling approaches improves the effectiveness of facility location solutions. This study offers new perspectives on elaborating key features to encompass facility location issues by applying interdisciplinary approaches.
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Colin Harris, Andrew Myers, Christienne Briol and Sam Carlen
A discipline is bound by some combination of a shared subject matter, shared theory, and shared technique. Yet modern economics is seemingly without limit to its domain. As a…
Abstract
A discipline is bound by some combination of a shared subject matter, shared theory, and shared technique. Yet modern economics is seemingly without limit to its domain. As a discipline without a shared subject matter, what is the binding force of economics today? The authors combine topic modeling and text analysis to analyze different approaches to inquiry within the discipline of economics. The authors find that the importance of theory has declined as economics has increasingly become defined by its empirical techniques. The authors question whether this trajectory is stable in the long run as the binding force of the discipline.
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After briefly reviewing the past history of Bayesian econometrics and Alan Greenspan's (2004) recent description of his use of Bayesian methods in managing policy-making risk…
Abstract
After briefly reviewing the past history of Bayesian econometrics and Alan Greenspan's (2004) recent description of his use of Bayesian methods in managing policy-making risk, some of the issues and needs that he mentions are discussed and linked to past and present Bayesian econometric research. Then a review of some recent Bayesian econometric research and needs is presented. Finally, some thoughts are presented that relate to the future of Bayesian econometrics.
This article seeks to (1) identify forecasting techniques used to estimate taxable sales in California counties; (2) analyze which of these produces the most accurate estimate;…
Abstract
This article seeks to (1) identify forecasting techniques used to estimate taxable sales in California counties; (2) analyze which of these produces the most accurate estimate; (3) document what prevented officials from using the most accurate forecasting technique in California counties; and (4) determine what forecasting approach would work best for individual counties. This research generally confirms previous research findings that judgmental approaches are the most commonly used method of revenue forecasting in smaller localities. In terms of accuracy, econometric models outperform other quantitative methods, particularly compared to trend line fitting and extrapolation-by-average approaches. The “not now but later” perception in the use of econometric models can be ascribed to California county forecasters’ discomfort and lack of preparation for using this sophisticated technique. Once the critical prerequisites for the use of econometric models are provided -- such as statewide training, timely inter-governmental data sharing, easy access to economic data, and user-friendly forecasting formats with automated procedures -- econometric models can serve the needs of California counties.
Asli Ogunc and Randall C. Campbell
Advances in Econometrics is a series of research volumes first published in 1982 by JAI Press. The authors present an update to the history of the Advances in Econometrics series…
Abstract
Advances in Econometrics is a series of research volumes first published in 1982 by JAI Press. The authors present an update to the history of the Advances in Econometrics series. The initial history, published in 2012 for the 30th Anniversary Volume, describes key events in the history of the series and provides information about key authors and contributors to Advances in Econometrics. The authors update the original history and discuss significant changes that have occurred since 2012. These changes include the addition of five new Senior Co-Editors, seven new AIE Fellows, an expansion of the AIE conferences throughout the United States and abroad, and the increase in the number of citations for the series from 7,473 in 2012 to over 25,000 by 2022.
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Giles D’Souza and Arthur Allaway
The marriage of new scanner‐type data sources and new computing and analysis methods is allowing a new approach to the development and use of models for decision support and…
Abstract
The marriage of new scanner‐type data sources and new computing and analysis methods is allowing a new approach to the development and use of models for decision support and product line management. Data‐driven modeling describes a process of model‐building wherein models are created that fit the dynamics of the data rather than assuming a priori relationships among brands and their marketing mix elements. Based on a combination of time‐series and econometric modeling methods, these models can significantly improve a modeler’s ability to capture marketplace structure and dynamics. Although more complex than their predecessors, the capabilities of these new data‐driven decision support models make them potentially very powerful tools, improving intuition and managerial understanding while suggesting improved decision alternatives. Develops such a model using detailed multiproduct retail data and demonstrates its capabilities.
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