Search results

This research aims to determine the ideal fare for various aircraft itineraries by modeling prices using a neural network method. Dynamic pricing has been studied from the airline’s point of view, with a focus on demand forecasting and price differentiation. Early demand forecasting on a specific route can assist an airline in strategically planning flights and determining optimal pricing strategies.

A feedforward neural network was employed in the current study. Two hidden layers, consisting of 18 and 12 neurons, were incorporated to enhance the network’s capabilities. The activation function employed for these layers was tanh. Additionally, it was considered that the output layer’s functions were linear. The neural network inputs considered in this study were flight path, month of flight, flight date (week/day), flight time, aircraft type (Boeing, Airbus, other), and flight class (economy, business). The neural network output, on the other hand, was the ticket price. The dataset comprises 16,585 records, specifically flight data for Iranian airlines for 2022.

The findings indicate that the model achieved a high level of accuracy in approximating the actual data. Additionally, it demonstrated the ability to predict the optimal ticket price for various flight routes with minimal error.

Based on the significant alignment observed between the actual data and the tested data utilizing the algorithmic model, airlines can proactively anticipate ticket prices across all routes, optimizing the revenue generated by each flight. The neural network algorithm utilized in this study offers a valuable opportunity for companies to enhance their decision-making processes. By leveraging the algorithm’s features, companies can analyze past data effectively and predict future prices. This enables them to make informed and timely decisions based on reliable information.

The present study represents a pioneering research endeavor that investigates using a neural network algorithm to predict the most suitable pricing for various flight routes. This study aims to provide valuable insights into dynamic pricing for marketing researchers and practitioners.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

Following the increasing trend of artificial intelligence (AI) research in hospitality literature, this critical reflection paper aims to identify AI-assisted mindfulness as a critical yet under-investigated issue and to contribute feasible directions for future research.

The authors first conceptualize a framework explaining the effects of mindfulness design in AI interventions on improving human mindfulness. The authors then identify opportunities for interventions in AI-assisted mindfulness for the tourism, hospitality and events industries. Finally, the authors propose potential themes for AI-assisted mindfulness research.

This study contributes three major conceptual works. First, we conceptualize a framework of AI-assisted mindfulness, showcasing that the scope of AI-assisted mindfulness spans from AI interventions to state mindfulness and then to trait mindfulness. Second, the authors offer two approaches to strategic thinking, one from mindfulness (i.e. mindfulness-focused niche markets and activities) and one from AI applications (i.e. AI-facilitated devices and platforms), to identify opportunities for AI-assisted mindfulness interventions. Third, for both management- and marketing-oriented AI-assisted mindfulness research, the authors propose 18 themes.

This critical reflection paper offers directions for future knowledge creation in AI-assisted mindfulness in the tourism, hospitality and events industries.

To the best of the authors’ knowledge, this critical reflection paper serves as the first in hospitality and tourism literature to systematically propose the research issue of AI-assisted mindfulness, offering directions and themes for future research.

This study aims to investigate low-carbon footprint travel choices, considering both destination attributes and climate change perceptions, and examine the impacts of nudging (a communication tool to alter individuals’ choices in a predictable way) on tourists’ preferences for carbon mitigation in destinations.

A discrete choice experiment questionnaire was administered to a sample of 958 Hong Kong respondents. Hybrid choice modeling was used to examine the respondents’ preferences for destination attributes and to explain preference heterogeneity using tourists’ climate change perceptions. The respondents’ willingness to pay for the destination attributes was also calculated to measure the monetary value of the attributes.

Destination type, carbon emissions and travel cost had significant effects on tourists’ choices of destination. Nudging increased tourists’ preference for low-carbon footprint choices. Tourists with higher climate change perceptions were more likely than others to select low-carbon destinations with carbon offset projects.

The findings of this study provide an impetus for destination management organizations to support local carbon offset projects, implement policies that mitigate carbon emissions and develop sustainable tourism to fulfill tourists’ demand for low-carbon footprint travel choices. Based on the findings, policymakers could promote sustainable tourism by publishing relevant climate change information on social media.

This study addressed a gap in the literature on tourist travel choice by considering carbon emission-related attributes and climate change perceptions and by confirming the role of nudging in increasing the choice of low-carbon destinations.

Vietnam has repositioned itself from a war-torn country to a popular tourist destination. Although research on Vietnam tourism has grown in number, a macro analysis of national tourism governance and policies has largely been missing.

This synthesis paper offers a systemic analysis of Vietnam’s tourism accommodating intensified government intervention and dramatic market changes in recent decades. The authors offer a chronological analysis of tourism development along with the major political and economic turns of the country.

The patterns of tourism development reflect a compromise between centralization and decentralization of the governance system and a trade-off between economic and social objectives of development. Balancing these opposites, the internal strength of the domestic market and the resilience of communities and businesses become key assets for growth in circumstances where the socialist market economy continues to inform the current and future development of the industry.

Although the case of Vietnam is unique, the adaptive mechanism of the tourism industry highlighted in this paper offers a useful lesson for other developing countries. The research addresses tourism in the political economy in developing countries, which is valuable for researchers, policy analysts as well as practitioners in tourism.

The practical contribution of the study is derived from authors’ academic and industrial backgrounds. Findings from the study serve as a useful reference for those who embark on the study of tourism governance and policy-making in developing countries and problems associated with the economic transitional process. Those problems of the disparity between centralization and decentralization of the political system might not be only significant in Vietnam, but also prevail in developing countries. Thus, this study offers a point of departure for future empirical and comparative research on the kindship of tourism and political economy in a full scale.

The transitional economy as viewed through the tourism industry is prominently presented in the “evolutionary” approach to the transitional economy, which exhibits several unique features: the transition from a centrally planned (command) economy to a market economy and the manifestations of a socialist orientation in the modern economic management system (Vuong et al., 2019). While data from this study is mainly illustrative of the first point, the transition from a planned economy to a market economy, the second characteristic, the manifestation of a social orientation has only slightly been addressed and will need further elaboration in a future study. While Vietnam’s tourism positions itself in a socialist market-oriented economy might set a unique case, the study highlights the politics of tourism is shaped by the politico-economic system. The authors conclude that the adaptation of Vietnam tourism to a socialist market-orientated economy is better perceived as a social evolution achievement rather than a feature of capitalism.

The latest study on tourism governance (Bui et al., 2022) has outlined the evolution of the tourism administrative system and markets in the country; however, linkages of tourism to the broader political economic system have yet to be addressed. Addressing this gap, the authors carry out analysis of policies and governance from the insider’s viewpoint, when team members have been involved in numerous tourism planning and development projects, both on international and national scales. The practical experience along with thorough review of literature and statistical data contributes to shaping a fresh understanding of tourism in a transitional economy.

这篇综述对越南旅游业进行了系统分析, 包括近几十年来不断增强的政府干预以及巨大的市场变化。作者根据时间顺序分析了旅游业的发展以及该国的主要政治及经济的转变。此外, 政策文件的内容分析及旅游市场分析进一步说明了政治经济体系对旅游治理及政策的影响。

越南已将自己从一个饱受战争的国家重新定位成备受欢迎的旅游目的地。尽管对越南旅游业的研究不断增多, 但对国家旅游治理和政策的宏观分析却被之前的探究所忽略。此研究通过展示越南转型经济中的旅游治理模式连接了两个学科, 并且丰富了政治经济学和旅游学的文献。

旅游政策和市场分析反应了治理体系集权与分权之间的折中以及经济和社会发展目标之间的权衡。国内市场的内在优势以及社区及企业的韧性可以成为成长的关键资产来平衡这些对立面, 同时社会主义市场经济将继续影响产业的当前及未来的发展。因此我们的结论是, 越南旅游业适应社会主义市场经济应该被视为社会进化的成就, 而不是资本主义的特征。

考虑到一篇文章所能解决的问题有限, 作者无法就转型经济与中国进行比较研究。我们的研究为未来亚洲旅游与政治经济之间联系的实证和比较研究提供了一个出发点。

研究结果为发展中国家旅游治理和政策制定研究提供了有益的参考。

研究结果对于发展中国家旅游治理及政策制定研究具有重要参考意义。这项研究的成果对于发展中国家的旅游政策分析师, 特别是亚洲的研究人员来说很有价值。

当前的研究弥补了政治经济学中的一个研究不足, 即马克思主义学说及其与旅游业的对话。知识转移是本研究的一个亮点, 它源自对国家政治经济议程中的旅游治理的批判性分析。

Vietnam ha pasado de ser un país devastado por la guerra a convertirse en un popular destino turístico. Aunque la investigación sobre el turismo en Vietnam ha crecido en número, ha faltado en gran medida un macroanálisis de la gobernanza y las políticas turísticas nacionales. Nuestra investigación ha enriquecido la literatura tanto de la economía política como del turismo tendiendo un puente entre ambas disciplinas al presentar las pautas de la gobernanza del turismo en la economía de transición de Vietnam.

Este documento de síntesis ofrece un análisis sistemático del turismo de Vietnam que abarca la intensificación de la intervención gubernamental y los drásticos cambios del mercado en las últimas décadas. Los autores ofrecen un análisis cronológico del desarrollo del turismo junto con los principales giros políticos y económicos del país. Además, el análisis del contenido de los documentos políticos y el análisis del mercado turístico ilustran mejor las repercusiones de los sistemas político-económicos en la gobernanza y las políticas turísticas.

Las políticas turísticas y el análisis del mercado revelan un compromiso entre la centralización y la descentralización del sistema de gobernanza y un compromiso entre los objetivos económicos y sociales del desarrollo. Al equilibrar estos opuestos, la fuerza interna del mercado nacional y la resistencia de las comunidades y las empresas se convierten en activos clave para el crecimiento en unas circunstancias en las que la economía de mercado socialista sigue informando el desarrollo actual y futuro de la industria. Concluimos que la adaptación del turismo vietnamita a una economía socialista orientada al mercado se percibe mejor como un logro de la evolución social que como una característica del capitalismo.

Dentro del limitado abanico de cuestiones que podrían abordarse en un solo artículo, los autores no pueden establecer un estudio comparativo con China, en lo que respecta a la economía de transición. Nuestro estudio ofrece un punto de partida para futuras investigaciones empíricas y comparativas sobre la conexión entre turismo y economía política en Asia.

Las conclusiones del estudio sirven de referencia útil para quienes se embarcan en el estudio de la gobernanza y la formulación de políticas turísticas en los países en desarrollo.

Los resultados de la investigación son valiosos para los investigadores del sudeste asiático en particular y para los analistas de la política turística del mundo en desarrollo en general.

La presente investigación contribuye a un área poco investigada de la economía política, a saber, la doctrina marxista y su diálogo con el turismo. La transferencia de conocimientos es un aspecto destacado de esta investigación, que se ha derivado de un análisis crítico de la gobernanza del turismo en la agenda económica política nacional.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

The purpose of this study is to determine if blockchain-supported carbon offset information provision and shipping options with different cost and environmental footprint implications impact consumer perceptions toward retailers and logistics service providers. Blockchain and carbon neutrality, each can be expensive to adopt and complex to manage, thus getting the “truth” on decarbonization may require additional costs for consumers.

Experimental modeling is used to address these critical and emergent issues that influence practices across a set of supply chain actors. Three hypotheses relating to the relationship between blockchain-supported carbon offset information and consumer perceptions and intentions associated with the product and supply chain actors are investigated.

The results show that consumer confidence increases when supply chain carbon offset information has greater reliability, transparency and traceability as supported by blockchain technology. The authors also find that consumers who are provided visibility into various shipping options and the product's journey carbon emissions and offset – from a blockchain-supported system – they are more willing to pay a premium for both the product and shipping options. Blockchain-supported decarbonization information disclosure in the supply chain can lead to organizational legitimacy and financial gains in return.

Understanding consumer action and sustainable consumption is critical for organizations seeking carbon neutrality. Currently, the literature on this understanding from a consumer information provision is not well understood, especially with respect to blockchain-supported information transparency, visibility and reliability. Much of the blockchain literature focuses on the upstream. This study focuses more on consumer-level and downstream supply chain blockchain implications for organizations. The study provides a practical roadmap for considering levels of blockchain information activity and consumer interaction.

The huge Muslim population has increased the demand for halal tourism products and destination factors in this niche tourism segment. Despite the growing body of research conducted regarding ChatGPT’s revolutionary impact on the tourism industry, the use of such an artificial intelligence (AI) tool in halal tourism needs more attention. This study aims to provide a comprehensive an overview of using ChatGPT in the tourism industry, specifically in halal tourism, and offer an agenda for further essential research questions exploration.

Through the intensive examination of the tourism literature dealing with AI and halal tourism, this review identifies the implications related to the use of ChatGPT for Muslim travelers and future trends in halal tourism.

This paper identified the possible utilization of ChatGPT in assisting Muslim travelers across various stages of their journey, encompassing pre-trip, staying and post-trip phases. Subsequently, this paper identified the opportunities and challenges associated with implementing ChatGPT in the context of halal tourism. Finally, the paper delves into potential avenues for future research.

The findings serve as crucial implications, contributing to the theory of halal tourism development and the applications of ChatGPT in halal tourism.

This paper provides essential foundational knowledge for upcoming research on halal tourism theory, ChatGPT and the development of halal tourism sector.