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This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.

Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.

The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.

This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.

This study produced a reliable, accurate forecasting model considering risk and competitor behavior.

This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.

This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.

This study aims to create actionable guidelines for pricing decision-making by employing game a theory matrix to forecast the correlation between the average daily rate and the latest ambiance of hotels.

Utilizing a vector error correction model, the research employs game theory to assess the influence of the average daily rate on the hotel's newest atmosphere during both peak season (April–September) and valley season (October–March).

Findings indicate that during the peak season, when the average daily rate rises in resorts and falls in suburban areas, the hotel’s newest atmosphere is at its best in both types of accommodations. During the off-peak season, the hotel’s newest atmosphere is achieved when both resorts and suburban accommodations increase their average daily rates.

There are two study constraints. One is the assumption that hotel guests in both parties prefer not to change hotels, but in fact they would. Two is a limited sample of two resort and suburban markets.

This suggests that the hotel’s newest atmosphere can draw both leisure and business travelers to suburban areas during the low season and more leisure travelers to resorts during the high season.

The study’s findings have implications for revenue related to the hotel’s newest atmosphere and cleanliness for both suburban and resort hotels, particularly when promoting tourism collaboratively.

The study provides valuable insights for hotel managers in analyzing pricing strategies using matrices.

This paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per available room (RevPAR).

The authors conducted review sentiment analyses in three moments (−1, −7 and −14 days) before arrival time using a data set of budget hotel performance and online reviews. The aim was to identify the effect of review sentiment in the budget hotel market on the three performance metrics.

Daily sentiment positively affects ADR and negatively affects OR and RevPAR, but only up to a certain threshold, after which the trend reverses. Prices increase with the level of sentiment, and high prices lead to low OR and RevPAR only when the sentiment scores are low. When they are high, they are associated with low rates, which lead to high OR and RevPAR.

Daily review sentiment can be viewed as a valuable “barometer” indicating a hotel’s daily operational effectiveness. Daily sentiment can thus allow hotel managers to adjust their dynamic pricing strategies more accurately.

This study identifies daily sentiment as an alternative predictor of hotel performance. In addition to the roles of valence and volume in the decision-making process, the authors found that daily review sentiment can be an “in-the-moment” factor with a high impact, encouraging consumers to complete their transactions. This study suggests that aggregated measures such as the total number of reviews and overall ratings of the hotel should not be the sole consideration in reputation management.

The COVID-19 pandemic has posed many challenges in almost all sectors around the globe. Because of the pandemic, government entities responsible for managing health-care resources face challenges in managing and distributing their limited and valuable health resources. In addition, severe outbreaks may occur in a small or large geographical area. Therefore, county-level preparation is crucial for officials and organizations who manage such disease outbreaks. However, most COVID-19-related research projects have focused on either state- or country-level. Only a few studies have considered county-level preparations, such as identifying high-risk counties of a particular state to fight against the COVID-19 pandemic. Therefore, the purpose of this research is to prioritize counties in a state based on their COVID-19-related risks to manage the COVID outbreak effectively.

In this research, the authors use a systematic hybrid approach that uses a clustering technique to group counties that share similar COVID conditions and use a multi-criteria decision-making approach – the analytic hierarchy process – to rank clusters with respect to the severity of the pandemic. The clustering was performed using two methods, k-means and fuzzy c-means, but only one of them was used at a time during the experiment.

The results of this study indicate that the proposed approach can effectively identify and rank the most vulnerable counties in a particular state. Hence, state health resources managing entities can identify counties in desperate need of more attention before they allocate their resources and better prepare those counties before another surge.

To the best of the authors’ knowledge, this study is the first to use both an unsupervised learning approach and the analytic hierarchy process to identify and rank state counties in accordance with the severity of COVID-19.

The purpose of this study is to investigate the impact of the COVID-19 pandemic on the beliefs and attitudes toward the use of information and communication technology (ICT). The study examines the challenges of implementing ICT-based training and provides insights for promoting the acceptance of online training in volunteer sports communities.

The study uses an action design research methodology that combines the implementation of ICT-based training, interviews, and a survey of 523 participants to examine the influence of online training on beliefs and attitudes.

The study shows that before the COVID-19 pandemic, soccer referees had negative beliefs about the use of ICT for learning. However, the experience of being forced to use ICT for training during the pandemic led to a positive shift in their beliefs about ICT.

The study offers four lessons learned for promoting the use of ICT-based training in voluntary sports. Future research should investigate the influence of blended learning approaches on affective, cognitive, and skill-based learning outcomes.

The study has practical implications for those responsible for implementing ICT-based training in voluntary sport. The findings suggest that design features such as usefulness, ease of use and enjoyment should be emphasized to increase the acceptance of online training.

The study contributes to the literature by providing insights into the challenges of implementing ICT-based training in voluntary sport contexts. The findings suggest that the experience of being forced to use ICT can promote the acceptance of online training in volunteer sports communities.

The purpose of this paper is to identify the areas and logic of integration of different stakeholders using different methods and to analyse their applicability and challenges in practical projects. The main aim is to describe how these different methods impact value creation.

Action design research was carried out in a large hospital construction project where the first author acted as an “involved researcher” and the second author acted as an “outside researcher”. Two workshops were organised to evaluate the direct and indirect challenges and benefits of the applied four methods and to explain how different methods enable value creation.

All the studied methods provide good results in terms of usability and commitment to the aims of the project, thus delivering the direct benefits expected. Process, people and tools logic works well in this case project when applying the methods properly. Significant evidence was provided on secondary deliverables of the methods, and all analysed methods had a significant impact in the area of leading people, clarifying what “focus on people” means and how it is enabled.

Focus on people can be achieved through different operative methods if applied in the right way. It is necessary to select the most suitable methods based on all the direct and indirect deliverables.

This case project offered a platform to analyse integration methods in a real-life project using the collaborative contract method. The authors were able to participate in the analysis by taking action from the very beginning of the project in terms of training, learning, continuous development and coaching of these methods and evaluating the applicability.

This study aims to investigate the relationship between business group affiliation and CO2 emissions in Chile, providing insights into the pollution externalities associated with business group structures and their implications for environmental performance.

A hand-matched sample of industrial facilities and subsidiaries of listed firms in Chile was utilized to analyze the CO2 emissions of business group-affiliated firms compared to stand-alone firms. Fixed-effect regression analysis and propensity score matching were employed to examine the differences in emissions levels.

The results suggest that firms affiliated with business groups have higher CO2 emissions in comparison to similar stand-alone firms. This suggests that business group structures may weaken the pressures for emission reduction and maintenance of public legitimacy among affiliated firms.

The findings of this study are subject to certain limitations, such as the use of a specific dataset from Chile and the inability to explore certain factors due to data constraints. For instance, we were unable to examine the separation between control and cash-flow rights as well as the influence of manager characteristics on pollution levels. Future research should address these limitations and expand the analysis to other emerging market countries to further investigate the impact of lax or ineffective environmental regulations on pollution outcomes.

The research findings have practical implications for investors and policymakers. Investors interested in environmentally sustainable investments should consider the higher pollution levels associated with business group-affiliated firms. Policymakers can use these findings to design more effective regulations and incentives to encourage emission reduction efforts within business group structures.

The study’s results emphasize the need for a comprehensive understanding of the environmental implications of business group affiliation. By recognizing the potential for higher emissions in business group structures, stakeholders can advocate for sustainable practices, encourage transparency and promote responsible environmental management within corporate entities.

This study contributes to the literature on corporate governance, climate risks and pollution externalities by providing an empirical evidence on the relationship between business group affiliation and CO2 emissions. It highlights the importance of considering the influence of corporate structures on environmental performance, particularly in the context of emerging market economies.

Este estudio tiene como objetivo investigar la relación entre la afiliación a grupos empresariales y las emisiones de CO2 en Chile, proporcionando información sobre las externalidades de contaminación asociadas con las estructuras de grupos empresariales y sus implicaciones para el desempeño ambiental de las empresas.

Se utilizó una muestra recolectada de manera manual de instalaciones industriales y subsidiarias de empresas listadas en Chile para analizar las emisiones de CO2 de empresas afiliadas a grupos empresariales en comparación con empresas independientes. Se emplearon análisis de regresión de efectos fijos y modelos de emparejamiento por puntaje de propensión para examinar las diferencias en los niveles de emisiones.

Los resultados sugieren que las empresas afiliadas a grupos empresariales tienen mayores emisiones de CO2 en comparación con empresas independientes similares. Esto sugiere que las estructuras de grupos empresariales pueden debilitar las presiones para la reducción de emisiones y el mantenimiento de la legitimidad pública entre las empresas afiliadas.

Este estudio contribuye a la literatura sobre gobierno corporativo, riesgos climáticos y externalidades de contaminación al proporcionar evidencia empírica sobre la relación entre la afiliación a grupos empresariales y las emisiones de CO2. Destaca la importancia de considerar la influencia de las estructuras corporativas en el rendimiento ambiental, especialmente en el contexto de las economías de mercados emergentes.

Los hallazgos de este estudio están sujetos a ciertas limitaciones, como el uso de un conjunto de datos específico de Chile y la incapacidad para explorar ciertos factores debido a restricciones de datos. Por ejemplo, no pudimos examinar la influencia de las características de los ejecutivos de las empresas en los niveles de contaminación. Investigaciones futuras deberían abordar estas limitaciones y ampliar el análisis a otros países de mercados emergentes para investigar más a fondo el impacto de regulaciones ambientales laxas o ineficaces en los resultados de contaminación.

Los hallazgos de la investigación tienen implicaciones prácticas para inversores y responsables políticos. Los inversores interesados en inversiones ambientalmente sostenibles deben tener en cuenta los niveles más altos de contaminación asociados con empresas afiliadas a grupos empresariales. Los responsables políticos pueden utilizar estos hallazgos para diseñar regulaciones más efectivas e incentivos para fomentar los esfuerzos de reducción de emisiones dentro de las estructuras de grupos empresariales.

Los resultados del estudio enfatizan la necesidad de comprender de manera integral las implicaciones ambientales de la afiliación a grupos empresariales. Al reconocer el potencial de mayores emisiones en las estructuras de grupos empresariales, los interesados pueden abogar por prácticas sostenibles, fomentar la transparencia y promover una gestión ambiental responsable dentro de las entidades corporativas.

This study examines how bilateral international trade among mandatory International Financial Reporting Standards (IFRS) adopter countries moderates the relation between IFRS adoption and firms’ financial reporting quality.

The authors use data from 2007 to 2015 and focus on publicly listed firms from non-European Union countries that adopted IFRS on a mandatory basis.

The authors find that the interaction between mandatory IFRS adoption and a country’s bilateral trade with other countries using IFRS is negatively and significantly related to accruals-based earnings management, which is an inverse measure of financial reporting quality. This result is driven by firms in less developed countries. The improvement in accounting quality is for firms located in countries that both fully and partially adopt IFRS. The authors also find a significant and negative coefficient for the relation between real earnings management and the interaction between mandatory IFRS adoption and a country’s bilateral trade with other IFRS countries in the post-global financial crisis period.

Overall, the authors’ results are consistent with the notion that the mandatory adoption of IFRS creates a positive externality where firms improve their accounting quality because increased financial statement comparability means that foreign customers and suppliers can monitor the quality of earnings more easily.

This article takes into account object identification, enhanced visual feature optimization, cost effectiveness and speed selection in response to terrain conditions. Neither supervised machine learning nor manual engineering are used in this work. Instead, the OTV educates itself without instruction from humans or labeling. Beyond its link to stopping distance and lateral mobility, choosing the right speed is crucial. One of the biggest problems with autonomous operations is accurate perception. Obstacle avoidance is typically the focus of perceptive technology. The vehicle's shock is nonetheless controlled by the terrain's roughness at high speeds. The precision needed to recognize difficult terrain is far higher than the accuracy needed to avoid obstacles.

Robots that can drive unattended in an unfamiliar environment should be used for the Orbital Transfer Vehicle (OTV) for the clearance of space debris. In recent years, OTV research has attracted more attention and revealed several insights for robot systems in various applications. Improvements to advanced assistance systems like lane departure warning and intelligent speed adaptation systems are eagerly sought after by the industry, particularly space enterprises. OTV serves as a research basis for advancements in machine learning, computer vision, sensor data fusion, path planning, decision making and intelligent autonomous behavior from a computer science perspective. In the framework of autonomous OTV, this study offers a few perceptual technologies for autonomous driving in this study.

One of the most important steps in the functioning of autonomous OTVs and aid systems is the recognition of barriers, such as other satellites. Using sensors to perceive its surroundings, an autonomous car decides how to operate on its own. Driver-assistance systems like adaptive cruise control and stop-and-go must be able to distinguish between stationary and moving objects surrounding the OTV.

One of the most important steps in the functioning of autonomous OTVs and aid systems is the recognition of barriers, such as other satellites. Using sensors to perceive its surroundings, an autonomous car decides how to operate on its own. Driver-assistance systems like adaptive cruise control and stop-and-go must be able to distinguish between stationary and moving objects surrounding the OTV.

This study is carried out to evaluate how well legal knowledge can be demonstrated by a built environment professional via the scenario-based approach to the learning of law modules.

A Delphi analysis of the advice provided by an MSC quantity surveying student, on a scenario-based legal problem arising due to a property contract, is carried out. The tendered legal advice was submitted as part of the assessment requirements for an MSc law module, following the university criteria, after the teaching of a law module. The student report, which attained an A-grade, and the assessment criteria used for marking/grading by the university were subsequently sent to 18 practicing lawyers, who were selected to constitute an expert panel, to independently judge the extent of legal knowledge demonstrated in the student report.

The Delphi analysis outcome showed that the expert panel holds a similar consensus view to the university on the level of legal knowledge demonstrated and by extension the effectiveness of the law module in imparting legal knowledge to a non-lawyer. The study outcome shows how well legal knowledge can be acquired and applied by a non-lawyer, within the context of the built environment, via scenario-based teaching of a law module.

This study serves as a preliminary step necessary to arouse further research toward empirically profiling the current outlook of a wider range of graduating students receiving scenario-based legal education in the built environment.