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Forecasting is a vital part of hospitality operations because it allows businesses to make imperative decisions, such as pricing, promotions, distribution, scheduling, and arranging facilities, based on the predicted demand and supply. This chapter covers three main concepts related to forecasting: it provides an understanding of hospitality demand and supply, it introduces several forecasting methods for practical application, and it explains yield management as a function of forecasting. In the first section, characteristics of hospitality demand and supply are described and several techniques for managing demand and supply are addressed. In the second section, several forecasting methods for practical application are explored. In the third section, yield management is covered. Additionally, examples of yield management applications from airlines, hotels, and restaurants are presented.

Software-define vehicular networks (SDVN) assure the direct programmability for controlling the vehicles with improved accuracy and flexibility. In this research, the resource allocation strategy is focused on which the seek-and-destroy algorithm is implemented in the controller in such a way that an effective allocation of the resources is done based on the multi-objective function.

The purpose of this study is focuses on the resource allocation algorithm for the SDVN with the security analysis to analyse the effect of the attacks in the network. The genuine nodes in the network are granted access to the communication in the network, for which the factors such as trust, throughput, delay and packet delivery ratio are used and the algorithm used is Seek-and-Destroy optimization. Moreover, the optimal resource allocation is done using the same optimization in such a way that the network lifetime is extended.

The security analysis is undergoing in the research using the simulation of the attackers such as selective forwarding attacks, replay attacks, Sybil attacks and wormhole attacks that reveal that the replay attacks and the Sybil attacks are dangerous attacks and in future, there is a requirement for the security model, which ensures the protection against these attacks such that the network lifetime is extended for a prolonged communication. The achievement of the proposed method in the absence of the attacks is 84.8513% for the remaining nodal energy, 95.0535% for packet delivery ratio (PDR), 279.258 ms for transmission delay and 28.9572 kbps for throughput.

The seek-and-destroy algorithm is one of the swarm intelligence-based optimization designed based on the characteristics of the scroungers and defenders, which is completely novel in the area of optimizations. The diversification and intensification of the algorithm are perfectly balanced, leading to good convergence rates.

Wireless sensor networks, due to their potentially wide application perspectives, may proliferate in future. Two major stumbling blocks are the dynamic variance of the network caused by both the capacity constraint of sensor nodes and uncertainties of wireless links, and secure routing in the special security sensitive environment. Therefore, adaptable and defendable routing mechanism is in urgent need for the deployment of sensor networks. This paper aims to propose a feedback‐based secure routing protocol (FBSR).

Feedback from the neighboring nodes serves as the dynamic information of the current network, with which sensor nodes make forwarding decisions in a secure and energy aware manner. Feedback message is included in the MAC layer acknowledgement frame to avoid network congestion, and it is authenticated with the proposed Keyed One Way Hash Chain (Keyed‐OWHC) to avoid feedback fabrication. FBSR's resilience to node compromise is enhanced by statistic efforts accomplished by the base station.

Both mathematical analysis and simulation results show that FBSR is not only reliable but also energy efficient.

The paper introduces a novel routing scheme for wireless sensor networks.

The purpose of this paper is to highlight the Western roots of the gap between practice and theory in HRM to underline the relevance of a flexible HR support. This support deserves to be nurtured by an insightful consideration of traditional Chinese thought, especially “vital nourishments” and “non-action.”

Following the methodology of deconstruction provided by French Sinologist and Philosopher François Jullien, this paper brings forward the implicit tenets of Western thought that feed HRD. The work of deconstruction relies here on an “heterotopia” (which literally means “a thought coming from elsewhere”) while making use of the founding tenets of traditional Chinese thought.

A flexible support, echoing some existing practices of coaching, mentoring and other developmental interactions, acts as an efficient and natural “non-active” development of HR especially relevant when facing stress at work.

If it is worth recalling the already existing bridges between theory and practice in HRM, it is also important to imagine new ones favorable to HRD.

The paper provides a critical reference for managers in charge of HRD.

The paper provides a critical reference for academics who wish to be more scholarly engaged in supporting executives and managers.

The paper challenges the Western ethnocentric reading of management in order to welcome another millenary way of thinking built in China. It escapes the fundamentals of managerial thought which have durably ruled over Western management studies.

Recommender systems collect information about users and businesses and how they are related. Such relation is given in terms of reviews and votes on reviews. User reviews gather opinions, rating scores and review influence. The latter component is crucial for determining which users are more relevant in a recommender system, that is, the users whose reviews are more popular than the average user’s reviews.

A model of measure of user influence is proposed based on review and social attributes of the user. User influence is also used for determining how influenced has been a business being based on popular reviews.

Results indicate there is a connection between social attributes and user influence. Such results are relevant for marketing, credibility estimation and Sybil detections, among others.

The proposed model allows search parameterization based on the social attribute weights of users, reviews and businesses. Such weights defines the relevance on each attribute, which can be adjusted according to the search needs. Popularity results are then a function of weight preferences on user, reviews and businesses data join.

The purpose of this study is to extensively explore the vehicular network paradigm, challenges faced by them and provide a reasonable solution for securing these vulnerable networks. Vehicle-to-everything (V2X) communication has brought the long-anticipated goal of safe, convenient and sustainable transportation closer to reality. The connected vehicle (CV) paradigm is critical to the intelligent transportation systems vision. It imagines a society free of a troublesome transportation system burdened by gridlock, fatal accidents and a polluted environment. The authors cannot overstate the importance of CVs in solving long-standing mobility issues and making travel safer and more convenient. It is high time to explore vehicular networks in detail to suggest solutions to the challenges encountered by these highly dynamic networks.

This paper compiles research on various V2X topics, from a comprehensive overview of V2X networks to their unique characteristics and challenges. In doing so, the authors identify multiple issues encountered by V2X communication networks due to their open communication nature and high mobility, especially from a security perspective. Thus, this paper proposes a trust-based model to secure vehicular networks. The proposed approach uses the communicating nodes’ behavior to establish trustworthy relationships. The proposed model only allows trusted nodes to communicate among themselves while isolating malicious nodes to achieve secure communication.

Despite the benefits offered by V2X networks, they have associated challenges. As the number of CVs on the roads increase, so does the attack surface. Connected cars provide numerous safety-critical applications that, if compromised, can result in fatal consequences. While cryptographic mechanisms effectively prevent external attacks, various studies propose trust-based models to complement cryptographic solutions for dealing with internal attacks. While numerous trust-based models have been proposed, there is room for improvement in malicious node detection and complexity. Optimizing the number of nodes considered in trust calculation can reduce the complexity of state-of-the-art solutions. The theoretical analysis of the proposed model exhibits an improvement in trust calculation, better malicious node detection and fewer computations.

The proposed model is the first to add another dimension to trust calculation by incorporating opinions about recommender nodes. The added dimension improves the trust calculation resulting in better performance in thwarting attacks and enhancing security while also reducing the trust calculation complexity.

Nowadays, connected vehicles are becoming quite complex systems which are made up of different devices. In such a vehicle, there are several electronic control units (ECUs) that represent basic units of computation. These ECUs communicate with each other over the Controller Area Network (CAN) bus protocol which ensures a high communication rate. Even though it is an efficient standard which provides communication for in-vehicle networks, it is prone to various cybersecurity attacks. This paper aims to present a systematic literature review (SLR) which focuses on potential attacks on CAN bus networks. Then, it surveys the solutions proposed to overcome these attacks. In addition, it investigates the validation strategies aiming to check their accuracy and correctness.

The authors have adopted the SLR methodology to summarize existing research papers that focus on the potential attacks on CAN bus networks. In addition, they compare the selected papers by classifying them according to the adopted validation strategies. They identify also gaps in the existing literature and provide a set of open challenges that can significantly improve the existing works.

The study showed that most of the examined papers adopted the simulation as a validation strategy to imitate the system behavior and evaluate a set of performance criteria. Nevertheless, a little consideration has been given to the formal verification of the proposed systems.

Unlike the existing surveys, this paper presents the first SLR that identifies local and remote security attacks that can compromise in-vehicle and inter-vehicle communications. Moreover, it compares the reviewed papers while focusing on the used validation strategies.

The aim of this paper is to evaluate the use of blockchain for identity management (IdM) in the context of the Internet of things (IoT) while focusing on privacy-preserving approaches and its applications to healthcare scenarios.

The paper describes the most relevant IdM systems focusing on privacy preserving with or without blockchain and evaluates them against ten selected features grouped into three categories: privacy, usability and IoT. Then, it is important to analyze whether blockchain should be used in all scenarios, according to the importance of each feature for different use cases.

Based on analysis of existing systems, Sovrin is the IdM system that covers more features and is based on blockchain. For each of the evaluated use cases, Sovrin and UniquID were the chosen systems.

This paper opens new lines of research for IdM systems in IoT, including challenges related to device identity definition, privacy preserving and new security mechanisms.

This paper contributes to the ongoing research in IdM systems for IoT. The adequacy of blockchain is not only analyzed considering the technology; instead the authors analyze its application to real environments considering the required features for each use case.