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The growing share of proactive actors in the electricity markets calls for more attention on prosumers and more support for their decision-making under decentralized electricity markets. In view of the changing paradigm, it is crucial to…
Tourism is an exciting thing to be visited by people in the world. Search for attractive and popular places can be done through social media. Data from social media or websites can be used as a reference to find current travel trends and…
Demand estimation plays an important role in dynamic pricing where the optimal price can be obtained via maximizing the revenue based on the demand curve. In online hotel booking platform, the demand or occupancy of rooms varies across…
An understanding of the economic landscape in a world of ever increasing data necessitates representations of data that can inform policy, deepen understanding and guide future research. Topological Data Analysis offers a set of tools which…
The hospitality industry is one of the data-rich industries that receives huge Volumes of data streaming at high Velocity with considerably Variety, Veracity, and Variability. These properties make the data analysis in the hospitality…
Aircraft manufacturing relies on pre-order bookings. The configuration of the to be assembled aircraft is fixed by the design assisted market surveys. The sensitivity of the supply chain to the market conditions, makes, the relationship…
This study explores the enhancement of customer satisfaction in the airline industry, a critical factor for retaining customers and building brand reputation, which are vital for revenue growth. Utilizing a combination of machine learning…
3D corporate tourism in the marine sciences is a solution-based approach to innovation in science, engineering and design. Corporate international scientists, engineers and designers work with local experts in Malaysian marine and coastal…
China's rapid economic growth resulted in serious air pollution, which caused substantial losses to economic development and residents' health. In particular, the road transport sector has been blamed to be one of the major emitters. During…
This paper deals with the market-bidding problem of a cluster of price-responsive consumers of electricity. We develop an inverse optimization scheme that, recast as a bilevel programming problem, uses price-consumption data to estimate the…
Prediction markets are used in real life to predict outcomes of interest such as presidential elections. This paper presents a mathematical theory of artificial prediction markets for supervised learning of conditional probability…
Recommendation based on user preferences is a common task for e-commerce websites. New recommendation algorithms are often evaluated by offline comparison to baseline algorithms such as recommending random or the most popular items. Here,…
Estimating conditional average dose responses (CADR) is an important but challenging problem. Estimators must correctly model the potentially complex relationships between covariates, interventions, doses, and outcomes. In recent years, the…
The main goal of the paper is to extract the aggregate demand and aggregate supply shocks in Greece, Ireland, Italy and Portugal, as well as to examine the correlation among the two types of shocks. The decomposition of the shocks was…
A robust model for time series forecasting is highly important in many domains, including but not limited to financial forecast, air temperature and electricity consumption. To improve forecasting performance, traditional approaches usually…
We propose a uniform approach for the design and analysis of prior-free competitive auctions and online auctions. Our philosophy is to view the benchmark function as a variable parameter of the model and study a broad class of functions…
Accurate forecasting of daily attendance is vital for managing transportation, crowd flows, and services at large-scale international events such as Expo 2025 Osaka, Kansai, Japan. However, existing approaches often rely on multi-source…
In this paper, we forecast euro area inflation and its main components using an econometric model which exploits a massive number of time series on survey expectations for the European Commission's Business and Consumer Survey. To make…
Mobile crowdsourcing has become easier thanks to the widespread of smartphones capable of seamlessly collecting and pushing the desired data to cloud services. However, the success of mobile crowdsourcing relies on balancing the supply and…
We develop a time series model to forecast weekly peak power demand for three main states of Australia for a yearly time-scale, and show the crucial role of environmental factors in improving the forecasts. More precisely, we construct a…