Hasil untuk "Recreation leadership. Administration of recreation services"

Tuğba Arıcı, Nuray Eker

Generation Z, born into the digital age, differs from previous generations in their perspectives on future generations, communication styles, and online consumption habits. They view technology as an essential part of daily life. Digital environments that transfer, preserve, and make cultural heritage values accessible encourage young people to engage with these values, enabling them to pass them on to future generations and reach a broader audience. Tourism is another factor that supports the sustainability of cultural heritage. Generation Z, whose consumer habits are shaped by digital technologies, has become a key segment in the tourism market. It is believed that transforming intangible cultural heritage elements into digital media could increase Generation Z's curiosity about and interest in cultural heritage tourism. As a result, intangible cultural heritage (ICH) values can be handed down to future generations, and conservation plans can be developed. This research conceptually explores the potential impact of Generation Z's interaction with digital intangible components on their intention to participate in cultural heritage tourism. The study's focus on Generation Z's digital engagement with intangible cultural heritage within the context of cultural heritage tourism makes it unique. Accordingly, it is recommended that the Theory of Planned Behavior model be used to examine how interactions with digital intangible cultural heritage influence Generation Z's intentions to engage in cultural heritage tourism. This study could serve as a foundation for further empirical research.

Dominika Wandrychowska, Dawid Koźlenia

Background and purpose Evaluation of body composition features have a place in sports practice. This study aimed to investigate the effect of body composition indices on change of direction speed  performance through linear speed ability. Material and methods The 20 m linear speed and agility t-test was performed, and body morphology was evaluated by the bioimpedance method. The body mass index, fat, fat mass index, and skeletal mass index were calculated. Results The gender moderation effect was confirmed, and mediation analysis was conducted separately for gender to investigate the mediation role of linear speed on the association between body composition indices and agility. The models included body mass index (Indirect Effect: b is 0.06; p is 0.030), fat mass index (Indirect Effect: b is 0.11; p is 0.040) and body fat percentage (b is 0.06; p is 0.037) for males and (Indirect Effect: b is 0.05; p is 0.046) for females were statistically significant. Conclusions These results suggested that subjects with higher values of indices based on body fat amount had worse change of direction speed  throughout weaker linear speed. Therefore, control of body fat level seems to be crucial in speed abilities shaping.

Christian Banse, Björn Fanta, Juncal Alonso et al.

The conspicuous lack of cloud-specific security certifications, in addition to the existing market fragmentation, hinder transparency and accountability in the provision and usage of European cloud services. Both issues ultimately reflect on the level of customers' trustworthiness and adoption of cloud services. The upcoming demand for continuous certification has not yet been definitively addressed and it remains unclear how the level 'high' of the European Cybersecurity Certification Scheme for Cloud Services (EUCS) shall be technologically achieved. The introduction of AI in cloud services is raising the complexity of certification even further. This paper presents the EMERALD Certification-as-a-Service (CaaS) concept for continuous certification of harmonized cybersecurity schemes, like the EUCS. EMERALD CaaS aims to provide agile and lean re-certification to consumers that adhere to a defined level of security and trust in a uniform way across heterogeneous environments consisting of combinations of different resources (Cloud, Edge, IoT). Initial findings suggest that EMERALD will significantly contribute to continuous certification, boosting providers and users of cloud services to maintain regulatory compliance towards the latest and upcoming security schemes.

Andres Navarro, Carlos de Quinto, José Alberto Hernández

This paper introduces a novel architectural framework that integrates Large Language Models (LLMs) with email interfaces to automate administrative tasks, specifically targeting accessibility barriers in enterprise environments. The system connects email communication channels with Optical Character Recognition (OCR) and intelligent automation, enabling non-technical administrative staff to delegate complex form-filling and document processing tasks using familiar email interfaces. By treating the email body as a natural language prompt and attachments as contextual information, the workflow bridges the gap between advanced AI capabilities and practical usability. Empirical evaluation shows that the system can complete complex administrative forms in under 8 seconds of automated processing, with human supervision reducing total staff time by a factor of three to four compared to manual workflows. The top-performing LLM accurately filled 16 out of 29 form fields and reduced the total cost per processed form by 64% relative to manual completion. These findings demonstrate that email-based LLM integration is a viable and cost-effective approach for democratizing advanced automation in organizational settings, supporting widespread adoption without requiring specialized technical knowledge or major workflow changes. This aligns with broader trends in leveraging LLMs to enhance accessibility and automate complex tasks for non-technical users, making technology more inclusive and efficient.

Ana Isabel Polo-Peña , María Lina Fernández-Ruano , Dolores María Frías-Jamilena

This study examines the effectiveness of a strategy designed to enhance destination perceived value (PV) by raising tourists’ awareness and understanding of sustainability. The approach uses information and communications technologies—specifically, gamification—to design an environmental interpretation (EI) program for tourists. While the literature has tended to approach gamification from a systemic perspective, this study addresses a significant gap by adding the experiential dimension. The research (a) designs an EI program based on a holistic gamified approach that takes game objectives, features, the context of the application, and the participant experience into consideration; (b) measures the tourist’s perspective on the design to test whether it successfully generated a motivating and enjoyable (gameful) experience that could positively impact their behaviours; and (c) determines whether a gameful EI experience positively influences destination PV. The results show that the proposed strategy contributes to enhancing destination PV. The gamification of EI experiences is thus found to be a valid strategy for enhancing destination sustainability, tourist behaviours, and, ultimately, destination competitiveness.

Heba Said , Noha Ahmed Kamel

E-leaders should encourage academics to manage their multi-dimensional work requirements and even to go beyond these requirements to innovate in their tasks and achieve sustainable development in educational institutions. This study aims to examine the relationship between e-leadership, innovative work behavior and proactive work behavior in the presence of work engagement as a mediator. Researchers implemented a quantitative methodology. This study used data from an online survey of 398 academics in Egyptian tourism higher education institutions. The results of structural equation modeling presented strong support for the proposed model. E-leadership has been proven to affect innovative and proactive work behavior among academic staff positively. Work engagement has shown an effective and significant mediating role between the examined variables. Further, the academic department was proven to moderate the relation between e-leadership and innovative work behavior, while age had no moderation effect in this relation. The study draws researchers’ attention to the role of e-leadership in helping academics to cope with the dynamic nature of research and education.

Oana-Diana Crîșmariu, Mihail-Ovidiu Tănase, Iulian Tenie et al.

The pandemic situation that began in 2019 directly affected all industries. The most affected industries are: airlines, cruises, HORECA, entertainment, etc. The restaurant industry, which is part of the HORECA industry, was severely affected throughout the world. The industry faced many restrictions in 2020 and 2021. Among most common, we can mention: temporary suspension of the activity, limited operating hours and available seats, access restrictions (like EU Green Certificate, for indoor activities), etc. As a response to legal regulations in order to avoid the spread of the virus, but also to prevent a further economic downturn, each industry had to take various measures. This article contains a theoretical overview of the evolution of the restaurant industry during the pandemic, from March 2020 to the present day. An analysis, based on qualitative research, of representative restaurants, in their category, for Romania shows how different actions were taken to adapt to the new normal. Furthermore, the research presents an important view of the future of the industry. The purpose of this paper is to analyze the changes produced and the adaptability of the restaurant industry to the current and ever-changing situation. The results revealed many interesting measures that similar companies and hope for better times.

Tarik Moufakir, Mohamed Faten Zhani, Abdelouahed Gherbi et al.

With the emergence of network softwarization trend, traditional networking services offered by Internet providers are expected to evolve by fully leveraging new recent technologies like network function virtualization and software defined networking. In this paper, we investigate offering Service Function Chains as a Service (SFCaaS) in NFV Environments. We first describe the potential business model to offer such a service. We then conduct a detailed study of the costs of virtual machine instances offered by Amazon EC2 with respect to the location, instance size, and performance in order to guide service chain provisioning and resource allocation. Afterwards, we address the resource allocation problem for service chain functions from the SFC provider's perspective while leveraging the performed cost study. We hence formulate the problem as an Integer Linear Program (ILP) aiming at reducing the SFC provider's operational costs of virtual machine instances and links as well as the synchronization costs among the instances. We also propose a new heuristic algorithm to solve the mapping problem with the same aforementioned goals taking into account the conducted study of the costs of Amazon EC2 instances. We show through extensive simulations that the proposed heuristic significantly reduce operational costs compared to a Baseline algorithm inspired by the existing literature.

Agustín Del Castillo García, Sergio Manuel Fernández Miguélez

The globalization process and the recent economic crises have increased the development of models to identify the factors related to business bankruptcy. As a consequence, previous research has provided bankruptcy prediction models both of a global nature for certain industries or regions of the world, and models focused on certain economic activities. The tourism industry is not immune to this concern and in the previous literature there are certain bankruptcy prediction models, generally focused on hotels or restaurants. However, there are no experiences of global models for tourism companies, although in the bankruptcy prediction literature there is numerous evidence of the advantages offered by global models compared to those focused on single business activity. This study develops a global bankruptcy prediction model capable of predicting with high precision any of the activities carried out in the tourism industry. To this end, a sample of 406 Spanish companies that have developed their activity in three sectors of the tourism industry (hotels, restaurants, and travel agencies) in the period 2017-2019 has been used. This sample includes bankrupt and non-bankrupt corporations and has allowed the comparison between a global model and various focused models applying artificial neural network techniques. The results have confirmed the superiority of the global model and provide different sample selection and cost minimization solutions for bankruptcy prediction modeling in the tourism industry.

Henrietta Lyons, Eduardo Velloso, Tim Miller

A paper presented at the Workshop on Contestability in Algorithmic Systems at CSCW 2019. Challenging algorithmic decisions is important to decision subjects, yet numerous factors can limit a person's ability to contest such decisions. We propose that administrative law systems, which were created to ensure that governments are kept accountable for their actions and decision making in relation to individuals, can provide guidance on how to design contestation systems for algorithmic decision-making.

Jinfeng Wen, Yi Liu

Along with the wide-adoption of Serverless Computing, more and more applications are developed and deployed on cloud platforms. Major cloud providers present their serverless workflow services to orchestrate serverless functions, making it possible to perform complex applications effectively. A comprehensive instruction is necessary to help developers understand the pros and cons, and make better choices among these serverless workflow services. However, the characteristics of these serverless workflow services have not been systematically analyzed. To fill the knowledge gap, we survey four mainstream serverless workflow services, investigating their characteristics and performance. Specifically, we review their official documents and compare them in terms of seven dimensions including programming model, state management, etc. Then, we compare the performance (i.e., execution time of functions, execution time of workflows, orchestration overhead of workflows) under various experimental settings considering activity complexity and data-flow complexity of workflows, as well as function complexity of serverless functions. Finally, we discuss and verify the service effectiveness for two actual workloads. Our findings could help application developers and serverless providers to improve the development efficiency and user experience.

Anum Talpur, Mohan Gurusamy

The emergence of technologies such as 5G and mobile edge computing has enabled provisioning of different types of services with different resource and service requirements to the vehicles in a vehicular network.The growing complexity of traffic mobility patterns and dynamics in the requests for different types of services has made service placement a challenging task. A typical static placement solution is not effective as it does not consider the traffic mobility and service dynamics. In this paper, we propose a reinforcement learning-based dynamic (RL-Dynamic) service placement framework to find the optimal placement of services at the edge servers while considering the vehicle's mobility and dynamics in the requests for different types of services. We use SUMO and MATLAB to carry out simulation experiments. In our learning framework, for the decision module, we consider two alternative objective functions-minimizing delay and minimizing edge server utilization. We developed an ILP based problem formulation for the two objective functions. The experimental results show that 1) compared to static service placement, RL-based dynamic service placement achieves fair utilization of edge server resources and low service delay, and 2) compared to delay-optimized placement, server utilization optimized placement utilizes resources more effectively, achieving higher fairness with lower edge-server utilization.

Ehsan Aslani, Mohammadhossein Dehghan Pour Farashah, Somayeh Fadaei Nezhad Bahramjerdi

The purpose of this study is to estimate the physical, real, and effective tourism carrying capacity of one of the three pathways defined for walking tourists based on the Historic City of Yazd document in the UNESCO World Heritage List. In recent years, this pathway has been renovated. Mass arrival of tourists select it because of its older and larger number of historical buildings, boutique hotels and handicraft stores. In this research, a library-documentary approach, together with an analytical method, has been implemented. The data was collected from official sources and field studies as well as the data was consolidated by convening a panel of professionals. The total area of the main tourism pathway was first calculated using AutoCAD software based on urban map and, along with other information required in carrying capacity formulas, was embedded. Then, the number of allowed visitors was estimated based on existing limitations. The research findings show that the number of visitors in this area, based on official statistics, is far from its carrying capacity. Thereby, it is suggested that for high seasons, Nowruz Holidays in particular, measures should be taken to control the crowd of this area such as developing alternative tourism attractions, leading the crowding population towards other pathways, planning distribution of tours, specifying time limit for tours, increasing the time spent visiting the site in the first half of the year, enhancing qualities of urban spaces, as well as organizing tour guides and local trained people to manage tourists.

Hanchuan Xu, Xiao Wang, Yuxin Wang et al.

Various types of services, such as web APIs, IoT services, O2O services, and many others, have flooded on the Internet. Interconnections among these services have resulted in a new phenomenon called "Internet of Services" (IoS). By IoS,people don't need to request multiple services by themselves to fulfill their daily requirements, but it is an IoS platform that is responsible for constructing integrated solutions for them. Since user requirements (URs) are usually coarse-grained and transboundary, IoS platforms have to integrate services from multiple domains to fulfill the requirements. Considering there are too many available services in IoS, a big challenge is how to look for a tradeoff between the construction efficiency and the precision of final solutions. For this challenge, we introduce a framework and a platform for transboundary user requirement oriented solution design in IoS. The main idea is to make use of domain priori knowledge derived from the commonness and similarities among massive historical URs and among historical integrated service solutions(ISSs). Priori knowledge is classified into three types: requirement patterns (RPs), service patterns (SPs), and probabilistic matching matrix (PMM) between RPs and SPs. A UR is modeled in the form of an intention tree (ITree) along with a set of constraints on intention nodes, and then optimal RPs are selected to cover the I-Tree as much as possible. By taking advantage of the PMM, a set of SPs are filtered out and composed together to form the final ISS. Finally, the design of a platform supporting the above process is introduced.

Armin Moin

In this paper, we propose a novel approach for developing Sense-Compute-Control (SCC) applications for the Internet of Things and Services (IoTS) following the Model-Driven Software Engineering (MDSE) methodology. We review the recent approaches to MDSE and argue that Domain Specific Modeling (DSM) suites our needs very well. However, in line with the recent trends in cloud computing and the emer-gence of the IoTS, we believe that both DSM creation tools and DSM solutions that are created via those tools should also be provided to their respective users in a service-oriented fashion through the cloud in the IoTS. In this work, we concentrate on the latter, i.e., DSM solu-tions that are created via a DSM creation tool. We argue that it makes sense for the owners of a DSM solution in a domain to provide their DSM solution as a service, following the well known Software as a Ser-vice (SaaS) model, to the interested customers through the IoTS. Our proposed approach concentrates on such a DSM solution for developing SCC applications in the IoTS. However, the idea could be applied to DSM solutions in other domains as well.

Phuong Pham, Vivek Jain, Lukas Dauterman et al.

As cloud services are growing and generating high revenues, the cost of downtime in these services is becoming significantly expensive. To reduce loss and service downtime, a critical primary step is to execute incident triage, the process of assigning a service incident to the correct responsible team, in a timely manner. An incorrect assignment risks additional incident reroutings and increases its time to mitigate by 10x. However, automated incident triage in large cloud services faces many challenges: (1) a highly imbalanced incident distribution from a large number of teams, (2) wide variety in formats of input data or data sources, (3) scaling to meet production-grade requirements, and (4) gaining engineers' trust in using machine learning recommendations. To address these challenges, we introduce DeepTriage, an intelligent incident transfer service combining multiple machine learning techniques - gradient boosted classifiers, clustering methods, and deep neural networks - in an ensemble to recommend the responsible team to triage an incident. Experimental results on real incidents in Microsoft Azure show that our service achieves 82.9% F1 score. For highly impacted incidents, DeepTriage achieves F1 score from 76.3% - 91.3%. We have applied best practices and state-of-the-art frameworks to scale DeepTriage to handle incident routing for all cloud services. DeepTriage has been deployed in Azure since October 2017 and is used by thousands of teams daily.

Laura J. Burton, Jon Welty-Peachey

Tho V. Le, Satish V. Ukkusuri

The objective of this study is to understand how senders choose shipping services for different products, given the availability of both emerging crowd-shipping (CS) and traditional carriers in a logistics market. Using data collected from a US survey, Random Utility Maximization (RUM) and Random Regret Minimization (RRM) models have been employed to reveal factors that influence the diversity of decisions made by senders. Shipping costs, along with additional real-time services such as courier reputations, tracking info, e-notifications, and customized delivery time and location, have been found to have remarkable impacts on senders' choices. Interestingly, potential senders were willing to pay more to ship grocery items such as food, beverages, and medicines by CS services. Moreover, the real-time services have low elasticities, meaning that only a slight change in those services will lead to a change in sender-behavior. Finally, data-science techniques were used to assess the performance of the RUM and RRM models and found to have similar accuracies. The findings from this research will help logistics firms address potential market segments, prepare service configurations to fulfill senders' expectations, and develop effective business operations strategies.

Johanne Cohen, Daniel Cordeiro, Loubna Echabbi

We present an algorithm for detecting service provider alliances. To perform this, we modelize a cooperative game-theoretic model for competitor service providers. A choreography (a peer-to-peer service composition model) needs a set of services to fulfill its requirements. Users must choose, for each requirement, which service providers will be used to enact the choreography at lowest cost. Due to the lack of centralization, vendors can form alliances to control the market. We propose a novel algorithm capable of detecting alliances among service providers, based on our findings showing that this game has an empty core, but a non-empty bargaining set.

Helena Araujo Costa, Dra, Amanda Fontes de Oliveira Franco

O objetivo do trabalho foi mapear as relações de cooperação entre hostels, entendidos como empresas de hospedagem de pequeno porte, e as vantagens resultantes destas ações. A pesquisa realizou um levantamento de dados primários a partir de questionários estruturados junto a 22 gerentes e/ou proprietários de empreendimentos nos bairros de Copacabana e Ipanema, na cidade do Rio de Janeiro. A análise de dados, de caráter quantitativo, aplicou ferramental estatístico descritivo e medidas de associação. Os resultados indicaram que poucas ações de cooperação eram realizadas pelos empreendimentos. A principal ação identificada foi a indicação de outros hostels quando o do respondente estava sem vagas. As vantagens percebidas em cooperar foram pouco expressivas. Nenhuma associação entre porte, tempo de atuação, localização e tipo de gestão foi encontrada com as ações de cooperação realizadas e seus resultados. A principal dificuldade para cooperar identificada foi a falta de interesse por parte dos empreendimentos, revelando indícios de que existe um menor interesse em estabelecer ações conjuntas quando as empresas reconhecem uma situação conjuntural favorável para elas.