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The Euro-centric nature of dark tourism research is limiting the perspective and restricting the scope of contemporary theory. Hence, this paper aims to explore how dark tourism consumption differs in a society apart from the Anglo/Eurosphere. This is done by testing Stone and Sharpley’s (2008) thanatological framework in Mexico, a country whose residents are renown for having a unique perspective on death, to assess whether Mexican dark tourism consumers undergo a similar, or different, thanatological experience to that proposed in the framework.

The study adopts a qualitative approach in the form of a case study. The opinions of Mexican dark tourism consumers were gained by using the technique of semi-structured interviewing in four separate dark tourism sites within Mexico City, with coding serving as the form of analysis.

The findings show that due to the non-existence of an absent/present death paradox in Mexican society, the research participants experienced a thanatological process that contrasts with those from Western societies, which indicates that the thanatological framework is unsuitable in the context of Mexican dark tourism. At the same time, the study contests the common perception that Mexicans have a jovial familiarity with death, and demonstrates that in this case the thanatological process confirmed an acceptance of death, rather than any kind of intimacy.

The research is valuable in that it is a response to recent calls for research in geographical locations not previously considered in a dark tourism/thanatology context.

The COVID-19 pandemic has disrupted the ‘real’ world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that offers a wealth of natural experiments and produced new data about broadband, clouds, and the Internet in times of crisis. In this chapter, we characterise and evaluate the evolving impact of the global COVID-19 crisis on traffic patterns and loads and the impact of those on Internet performance from multiple perspectives. While we place a particular focus on deriving insights into how we can better respond to crises and better plan for the post-COVID-19 ‘new normal’, we analyse the impact on and the responses by different actors of the Internet ecosystem across different jurisdictions. With a focus on the USA and Europe, we examine the responses of both public and private actors, with the latter including content and cloud providers, content delivery networks, and Internet service providers (ISPs). This chapter makes two contributions: first, we derive lessons learned for a future post-COVID-19 world to inform non-networking spheres and policy-making; second, the insights gained assist the networking community in better planning for the future.

This study proposes and validates an integrated theoretical model involving the theory of planned behavior (TPB), health belief model (HBM), personal norms and information privacy to understand determinants of acceptance and resistance to the use of mobile contact tracing app (MCTA) in a pandemic situation.

This study draws on online surveys of 194 research respondents and uses partial least squares structural equation modeling (PL-SEM) to test the proposed theoretical model.

The study establishes that a positive attitude towards MCTA is the most important predictor of individuals' willingness to use MCTA and resistance to use MCTA. Furthermore, barriers to taking action positively influence resistance to the use of MCTA. Personal norms negatively influence resistance to the use of MCTA. Information privacy showed a negative and positive influence on willingness to use MCTA and use the resistance of MCTA, respectively, but neither was statistically significant. The authors found no significant influence of perceived vulnerability, severity, subjective norms and perceived behavioral control on either acceptance or use resistance of MCTA.

The study has been one of the first in the literature to propose an integrated theoretical model in the investigation of the determinants of acceptance and resistance to the use of MCTA in a single study, thereby increasing the scientific understanding of the factors that can facilitate or inhibit individuals from engaging in the use of a protection technology during a pandemic situation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0533

An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection robot cross obstacle automatically. This paper aims to propose an improved approach which is called adaptive homomorphic filter and supervised learning (AHSL) for overhead ground wire detection.

First, to decrease the influence of the varying illumination caused by the open work environment of the inspection robot, the adaptive homomorphic filter is introduced to compensation the changing illumination. Second, to represent ground wire more effectively and to extract more powerful and discriminative information for building a binary classifier, the global and local features fusion method followed by supervised learning method support vector machine is proposed.

Experiment results on two self-built testing data sets A and B which contain relative older ground wires and relative newer ground wire and on the field ground wires show that the use of the adaptive homomorphic filter and global and local feature fusion method can improve the detection accuracy of the ground wire effectively. The result of the proposed method lays a solid foundation for inspection robot grasping the ground wire by visual servo.

This method AHSL has achieved 80.8 per cent detection accuracy on data set A which contains relative older ground wires and 85.3 per cent detection accuracy on data set B which contains relative newer ground wires, and the field experiment shows that the robot can detect the ground wire accurately. The performance achieved by proposed method is the state of the art under open environment with varying illumination.

The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.

This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.

This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.

The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

Recommendation systems are a fundamental tool for hotels to adopt a differentiating competitive strategy. The main purpose of this work is to use machine learning techniques to treat imbalanced data sets, not applied until now in the tourism field. These techniques have allowed the authors to analyse the influence of imbalance data on hotel recommendation models and how this phenomenon affects client dissatisfaction.

An opinion survey was conducted among hotel customers of different categories in 120 different countries. A total of 135.102 surveys were collected over eleven quarters. A longitudinal design was conducted during this period. A binary logistic model was applied using the function generalized lineal model (GLM).

Through the analysis of a representative amount of data, the authors empirically demonstrate that the imbalance phenomenon is systematically present in hotel recommendation surveys. In addition, the authors show that the imbalance exists independently of the period in which the survey is done, which means that it is intrinsic to recommendation surveys on this topic. The authors demonstrate the improvement of recommendation systems highlighting the presence of imbalance data and consequences for marketing strategies.

The main contribution of the current work is to apply to the tourism sector the framework for imbalanced data, typically used in the machine learning, improving predictive models.

The 2013 Central European floods were not only one of the most severe natural disasters in Austria in the last decades, but also constituted a landmark in crisis communication. For the first time, social media and online newspapers were important news channels, creating a need for new crisis communication strategies. Based on 20 semi-structured interviews and an analysis of online data, we reconstruct in this chapter the online communication of different stakeholders such as the authorities, rescue organisations and journalists during this emergency situation. The study shows that the use of social media was a weak point in official crisis communication. Through detailed analyses of information flows and the requirements of different stakeholders, the study reveals new challenges and possibilities for crisis communication in the digital age.

This conceptual study examines the implications of the Internet of Behaviors (IoB) for tourism stakeholders in a hyper-connected and data-driven world.

Based on nudge theory, a literature review and empirical evidence from multidisciplinary research, this study explores the implications of the IoB for smart tourism.

This study reviews the literature, presents a conceptual framework and proposes a research agenda with areas for future research.

The research on the IoB is nascent. Therefore, it is critical to understand how data-driven nudging influences tourist behavior.

The purpose of this paper is to develop an innovative branding method based on the hermeneutical approach and interpretive theory, to respond to the need of a simple and effective tool to build corporate identity through an industrial brand identity design and, being a new business, has been considered the brand perception of their stakeholders as the main input to analyze.

The case study of a small- and medium-sized enterprise (SME), that produces nanomaterials for the business-to-business (B2B) industrial market, is used to design the new hermeneutic branding method. The methodology process has been structured in four phases that have marked the investigation and that correspond to four different levels of knowledge that, in succession, between them, constituted the so-called hermeneutic circle.

This new approach allowed us to understand the social phenomenon related to the brand: its characteristic, context and the brand itself. Though hermeneutic analysis has confirmed that business strategy is only part of a more complex system of brand management, it must also consider the competitive environment and the views of the stakeholders.

This paper contributes to research on industrial branding by adopting the hermeneutical approach in managerial practice. This paper is the first of its kind in detail modelling the design phases of a B2B brand, providing an operational tool for marketing specialists.

There is a lack of research studies in the methods for designing industrial brands. The contribution of this paper lies in proposing a new interpretative approach that, acknowledging the different expectations of the stakeholder in the supply chain, allows to draw a B2B brand that communicates the system values of the product and company.

The association of work and learning has been well established for many years. However, some of the terms used to describe the various pedagogies related to work and learning have been used interchangeably, with many lacking definitional clarity and scope. These include work-related learning (WRL), work-based learning, workplace learning (WPL) and work-integrated learning (WIL). This agglomerating approach to usage has resulted in pedagogical confusion and what some theorists call a “problematization” for the field, resulting in undermining shared understanding and potential benefit. The purpose of this conceptual paper is an attempt to unpack the meaning and application of some of the key pedagogical terms used in the applied field of work + learning theory and practice.

Conceptual modelling and qualitative descriptions of each pedagogy.

Many of the work + learning pedagogies do overlap and cohere but attempts to create umbrella terms, which apply to all theories and approaches, are misguided; definitional clarity with the different modes of practice is required for sustainable educational outcomes.

A proto-theoretical model, along with a breakdown of distinguishing features of each term as well as their source in the published literature, has been developed to improve clarity and aid the future praxis of educators.