New Developments in Tourism and Hotel Demand Modeling and Forecasting

Abstract Purpose The purpose of the study is to review recent studies published from 2007-2015 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 in both science citation index (SCI) and social science citation index (SSCI) journals were identified and analyzed. Findings This review found 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, while 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.

D6.6 – Summary, Analysis, Road-mapping and Production of Training materials

This deliverable summarizes, validates and explains the purpose and concept behind the RAGE knowledge and innovation management platform as a self-sustainable Ecosystem, supporting innovation processes in the Applied Gaming (AG) industry. The Ecosystem portal will be developed with particular consideration of the demand and requirements of small and medium sized game developing companies, education providers and related stakeholders like AG researchers and AG end-users. The innovation potential of the new platform underlies the following factors: a huge, mostly entire collection of community specific knowledge (e.g., content like media objects, software components and best practices), a structured approach of knowledge access, search and browse, collaboration tools as well as social network analysis tools to foster efficient knowledge creation and transformation processes into marketable technology assets. The deliverable provides an overview of the current status and the remaining work to come, preceding the final version in month 48 of the RAGE project.

Numerical Analysis on a Dual-Loop Waste Heat Recovery System Coupled with an ORC for Vehicle Applications

The internal combustion (IC) engines exploits only about 30% of the chemical energy ejected through combustion, whereas the remaining part is rejected by means of cooling system and exhausted gas. Nowadays, a major global concern is finding sustainable solutions for better fuel economy which in turn results in a decrease of carbon dioxide (CO2) emissions. The Waste Heat Recovery (WHR) is one of the most promising techniques to increase the overall efficiency of a vehicle system, allowing the recovery of the heat rejected by the exhaust and cooling systems. In this context, Organic Rankine Cycles (ORCs) are widely recognized as a potential technology to exploit the heat rejected by engines to produce electricity. The aim of the present paper is to investigate a WHR system, designed to collect both coolant and exhausted gas heats, coupled with an ORC cycle for vehicle applications. In particular, a coolant heat exchanger (CLT) allows the heat exchange between the water coolant and the ORC working fluid, whereas the exhausted gas heat is recovered by using a secondary circuit with diathermic oil. By using an in-house numerical model, a wide range of working conditions and ORC design parameters are investigated. In particular, the analyses are focused on the regenerator location inside the ORC circuits. Five organic fluids, working in both subcritical and supercritical conditions, have been selected in order to detect the most suitable configuration in terms of energy and exergy efficiencies.

A state-of-the-art review and feasibility analysis of high altitude wind power in Northern Ireland

In many countries wind energy has become an indispensable part of the electricity generation mix. The opportunity for ground based wind turbine systems are becoming more and more constrained due to limitations on turbine hub heights, blade lengths and location restrictions linked to environmental and permitting issues including special areas of conservation and social acceptance due to the visual and noise impacts. In the last decade there have been numerous proposals to harness high altitude winds, such as tethered kites, airfoils and dirigible based rotors. These technologies are designed to operate above the neutral atmospheric boundary layer of 1,300 m, which are subject to more powerful and persistent winds thus generating much higher electricity capacities. This paper presents an in-depth review of the state-of-the-art of high altitude wind power, evaluates the technical and economic viability of deploying high altitude wind power as a resource in Northern Ireland and identifies the optimal locations through considering wind data and geographical constraints. The key findings show that the total viable area over Northern Ireland for high altitude wind harnessing devices is 5109.6 km2, with an average wind power density of 1,998 W/m2 over a 20-year span, at a fixed altitude of 3,000 m. An initial budget for a 2MW pumping kite device indicated a total cost £1,751,402 thus proving to be economically viable with other conventional wind-harnessing devices.

Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation

Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in modern power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. In this analysis a direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimisation in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Market of Republic of Ireland and Northern Ireland.

Statistical Analysis of Wind Power Generation in Europe

Studies have shown that large geographical spreading can reduce the wind power variability and smooth production. It is frequently assumed that storage and interconnection can manage wind power variability and are totally flexible. However, constraints do exist. In the future more and more electricity will be provided by renewable energy sources and more electricity interconnectors will be built between European Union (EU) countries, as outlines in many of the Projects of Common Interests. It is essential to understand the correlation of wind generation throughout Europe considering power system constraints. In this study the spatial and temporal correlation of wind power production across several countries is examined in order to understand how “the wind ‘travels’ across Europe”. Three years of historical hourly wind power generation from ten EU countries is analysed to investigate the geographic diversity and time scales influence on correlation of wind power variations. Results are then compared with two other studies and show similar general characteristics of correlation between EU country pairs to identify opportunities for storage optimisation, power system operations, and trading.

An analysis of wind curtailment and constraint at a nodal level

Many countries have set challenging wind power targets to achieve by 2020. This paper implements a realistic analysis of curtailment and constraint of wind energy at a nodal level using a unit commitment and economic dispatch model of the Irish Single Electricity Market in 2020. The key findings show that significant reduction in curtailment can be achieved when the system non-synchronous penetration limit increases from 65% to 75%. For the period analyzed, this results in a decreased total generation cost and a reduction in the dispatch-down of wind. However, some nodes experience significant dispatch-down of wind, which can be in the order of 40%. This work illustrates the importance of implementing analysis at a nodal level for the purpose of power system planning.

Qualitative Comparative Analysis as a Tool for Concept Clarification, Typology Building, and Contextualized Comparisons in Gender and Feminist Research

Qualitative Comparative Analysis (QCA) is a method for the systematic analysis of cases. A holistic view of cases and an approach to causality emphasizing complexity are some of its core features. Over the last decades, QCA has found application in many fields of the social sciences. In spite of this, its use in feminist research has been slower, and only recently QCA has been applied to topics related to social care, the political representation of women, and reproductive politics. In spite of the comparative turn in feminist studies, researchers still privilege qualitative methods, in particular case studies, and are often skeptical of quantitative techniques (Spierings 2012). These studies show that the meaning and measurement of many gender concepts differ across countries and that the factors leading to feminist success and failure are context specific. However, case study analyses struggle to systematically account for the ways in which these forces operate in different locations.

Analysis of the Bovespa Futures and Spot Indexes With High Frequency Data. Chinese Business Review

Data from the World Federation of Exchanges show that Brazil’s Sao Paulo stock exchange is one of the largest worldwide in terms of market value. Thus, the objective of this study is to obtain univariate and bivariate forecasting models based on intraday data from the futures and spot markets of the BOVESPA index. The interest is to verify if there exist arbitrage opportunities in Brazilian financial market. To this end, three econometric forecasting models were built: ARFIMA, vector autoregressive (VAR), and vector error correction (VEC). Furthermore, it presents the results of a Granger causality test for the aforementioned series. This type of study shows that it is important to identify arbitrage opportunities in financial markets and, in particular, in the application of these models on data of this nature. In terms of the forecasts made with these models, VEC showed better results. The causality test shows that futures BOVESPA index Granger causes spot BOVESPA index. This result may indicate arbitrage opportunities in Brazil.

Development of functionalised multiwalled carbon nanotube/polyaniline composites for electrical applications

Combining intrinsically conducting polymers with carbon nanotubes (CNT) helps in creating composites with superior electrical and thermal characteristics. These composites are capable of replacing metals and semiconductors as they possess unique combination of electrical conductivity, flexibility, stretchability, softness and bio-compatibility. Their potential for use in various organic devices such as super capacitors, printable conductors, optoelectronic devices, sensors, actuators, electrochemical devices, electromagnetic interference shielding, field effect transistors, LEDs, thermoelectrics etc. makes them excellent substitutes for present day semiconductors.However, many of these potential applications have not been fully exploited because of various open–ended challenges. Composites meant for use in organic devices require highly stable conductivity for the longevity of the devices. CNT when incorporated at specific proportions, and with special methods contributes quite positively to this end.The increasing demand for energy and depleting fossil fuel reserves has broadened the scope for research into alternative energy sources. A unique and efficient method for harnessing energy is thermoelectric energy conversion method. Here, heat is converted directly into electricity using a class of materials known as thermoelectric materials. Though polymers have low electrical conductivity and thermo power, their low thermal conductivity favours use as a thermoelectric material. The thermally disconnected, but electrically connected carrier pathways in CNT/Polymer composites can satisfy the so-called “phonon-glass/electron-crystal” property required for thermoelectric materials. Strain sensing is commonly used for monitoring in engineering, medicine, space or ocean research. Polymeric composites are ideal candidates for the manufacture of strain sensors. Conducting elastomeric composites containing CNT are widely used for this application. These CNT/Polymer composites offer resistance change over a large strain range due to the low Young‟s modulus and higher elasticity. They are also capable of covering surfaces with arbitrary curvatures.Due to the high operating frequency and bandwidth of electronic equipments electromagnetic interference (EMI) has attained the tag of an „environmental pollutant‟, affecting other electronic devices as well as living organisms. Among the EMI shielding materials, polymer composites based on carbon nanotubes show great promise. High strength and stiffness, extremely high aspect ratio, and good electrical conductivity of CNT make it a filler of choice for shielding applications. A method for better dispersion, orientation and connectivity of the CNT in polymer matrix is required to enhance conductivity and EMI shielding. This thesis presents a detailed study on the synthesis of functionalised multiwalled carbon nanotube/polyaniline composites and their application in electronic devices. The major areas focused include DC conductivity retention at high temperature, thermoelectric, strain sensing and electromagnetic interference shielding properties, thermogravimetric, dynamic mechanical and tensile analysis in addition to structural and morphological studies.

Responding to Fluctuating Demand for Healthcare Services

The level of demand for healthcare services can fluctuate quite strongly. Indeed, some parts of the healthcare service are renowned for having peaks of demand which challenge capacity. Dealing with fluctuations in demand is a common problem in many service industries. This article examines some of the strategies available for influencing the level of demand, including the use of price, communications and demand analysis. The article also outlines a wide variety of ways in which patients can be encouraged to be more tolerant of waiting to receive service from healthcare professionals. In particular, eight principles of waiting are discussed and illustrated in the context of healthcare services.

Job-demand for Learning, Job-related Learning and Need for Achievement

Individual learning is important, as it is both a precursor and an outcome of learning in organisations. Job-related learning is driven by external factors (e.g., the demands of the job) and internal factors (i.e., the personality of the individual). The study examined whether need for achievement moderates the relationship between job-demand for learning and job-related learning. Data were obtained from 153 full-time, white-collar employees from a range of industries. Hierarchical regression analysis using the product term revealed that need for achievement moderates the relationship between job-demand for learning and job-related learning. Specifically, although job-demand for learning is correlated positively to job-related learning for both the high and the low need for achievement groups, this correlation is stronger amongst the high group. The findings are discussed in terms of their implications for future research and practice.

Production planning, pricing and market coordination for news vendor problem with price dependent demand

Thesis (Ph.D.)--University of Washington, 2016-08

Job-demand for Learning and Job-related Learning: the Mediating Effect of Job Performance Improvement Initiatives

This study examined whether job-performance-improvementinitiatives mediate the relationship between individuals’ job-demand for learning and job-related learning. Data were obtained from 115 full-time employees in a diverse range of occupations. A partial least squares analysis revealed that job-performance-improvement-initiatives mediate partially the effects of job-demand for learning on job-related learning. Several implications for future research and policy are drawn from the findings.