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This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a framework to guide designers in creating ITTSs.

This chapter discusses individual differences in information experiences, with particular focus on emotional aspects. It reports findings from two studies that explored K12 and mature students’ experiences of uncertainty in the information search process. These experiences were related to the respondents’ personality traits and approaches to studying. The studies found that intrinsic motivation and openness to experience increased the likelihood of a pleasant information experience in a study context, while extrinsic motivation and insecurity often resulted in a negative one. Conscientious and systematic searchers tended to be foremost goal-oriented, whereby the affective tone of a search depended on the amount of progress towards the goal. Patterns of explorative or systematic searching were found both during a specific inquiry process and as broader conceptions of regularly occurring information experiences.

This research aims to explore the impact of augmented reality (AR), the digital technology that superimposes virtual elements in a real environment, on consumers in the context of experiential marketing. Specifically, this study proposes a research model based on the stimulus-organism-response model, which considers AR media characteristics as external stimuli, consumers’ value perceptions as the organisms, and purchase intentions as the responses. The research model was tested with 248 consumers using structural equation modelling. The results show that informativeness, ease of use, and telepresence have positive effects on consumers’ utilitarian value perception and that telepresence and interactivity have positive effects on hedonic value perception. Overall, this study contributes to the growing body of knowledge on AR and provides actionable insights for managers implementing digital transformation strategies and AR applications in marketing practices.

Unobtrusive measurement methodologies are critical to implementing intelligent tutoring systems (ITS) for teams. Such methodologies allow for continuous measurement of team states and processes while avoiding disruption of mission or training performance, and do not rely on post hoc feedback (including for the aggregation of data into measures or to develop insights from these real-time metrics). This chapter summarizes advances in unobtrusive measurement developed within Army research programs to illustrate the variety and potential that unobtrusive measurement approaches can provide for building ITS for teams. Challenges regarding the real-time aggregation of data and applications to current and future ITS for teams are also discussed.

Purpose: This paper presents a review of the current state and potential capabilities for application of robots, artificial intelligence and automated services (RAISA) in hotel companies.

Design/methodology/approach: A two-step approach was applied in this study. First, the authors make a theoretical overview of the robots, artificial intelligence and service automation (RAISA) in hotels. Second, the authors make a detailed overview of various case studies from global hotel practice.

Findings: The application of RAISA in hotel companies is examined in connection with the impact that technology has on guest experience during each of the five stages of the guest cycle: pre-arrival, arrival, stay, departure, assessment.

Research implications: Its implications can be searched with respect to future research. It deals with topics such as how different generations (guests and employees) perceive RAISA in the hotel industry and what is the attitude of guests in different categories of hotels (luxury and economy) towards the use of RAISA. It also shows what is the attitude of different types of tourists (holiday, business, health, cultural, etc.) and what kinds of robots (androids or machines) are more appropriate for different types of hotel operations.

Practical implications: The implications are related to the improvement of operations and operational management, marketing and sales, enhancement of customer experience and service innovation, training and management.

Originality/value: This book chapter complements and expands research on the role of RAISA in the hotel industry and makes some projections about the use of technologies in the future.

In many security domains, the ‘human in the system’ is often a critical line of defence in identifying, preventing and responding to any threats (Saikayasit, Stedmon, & Lawson, 2015). Traditionally, such security domains are often focussed on mainstream public safety within crowded spaces and border controls, through to identifying suspicious behaviours, hostile reconnaissance and implementing counter-terrorism initiatives. More recently, with growing insecurity around the world, organisations have looked to improve their security risk management frameworks, developing concepts which originated in the health and safety field to deal with more pressing risks such as terrorist acts, abduction and piracy (Paul, 2018). In these instances, security is usually the specific responsibility of frontline personnel with defined roles and responsibilities operating in accordance with organisational protocols (Saikayasit, Stedmon, Lawson, & Fussey, 2012; Stedmon, Saikayasit, Lawson, & Fussey, 2013). However, understanding the knowledge that frontline security workers might possess and use requires sensitive investigation in equally sensitive security domains.

This chapter considers how to investigate knowledge elicitation in these sensitive security domains and underlying ethics in research design that supports and protects the nature of investigation and end-users alike. This chapter also discusses the criteria used for ensuring trustworthiness as well as assessing the relative merits of the range of methods adopted.

Purpose: The goal of the chapter is to define customer attitudes towards robots in travel, tourism and hospitality (TTH) and to analyse their most significant characteristics.

Design/methodology/approach: The book chapter develops a conceptual framework of attitudes towards robots in travel, tourism and hospitality, based on critical analysis of relevant publications.

Findings: The chapter provides a definition and discussion of the characteristics of customer attitudes towards robots in TTH. It elaborates the structural elements of attitudes towards robots, and the links and interactions between the elements.

Research limitations: Research limitations stem from the small number of studies on customer attitudes towards robots in TTH.

Practical implications: The theoretical analysis can be used as a starting point for empirical studies of customer attitudes towards robots in travel, tourism and hospitality.

Social implication: Combined services, based on human employee-service robot collaboration, are the optimal decision for forming favourable customer attitudes towards robotisation and automation in tourism and hospitality. In that way clients’ needs of high technological convenience, interpersonal communication and socialisation are met simultaneously.

Originality/value: This research is among the few publications that study customer attitudes towards robots in travel, tourism and hospitality. The authors develop a matrix of users’ attitudes and behaviours when using robots in travel, tourism and hospitality.

“The Computing Research Association (CRA) is an association of more than 200 North American academic departments of computer science, computer engineering, and related fields; laboratories and centers in industry, government, and academia engaging in basic computing research; and affiliated professional societies” (CRA, 2010a). Each year the CRA publishes its Taulbee Survey. “The Taulbee Survey is the principal source of information on the enrollment, production, and employment of Ph.D.s in computer science and computer engineering (CS & CE) and in providing salary and demographic data for faculty in CS & CE in North America. Statistics given include gender and ethnicity breakdowns” (Computer Research Association, CRA, 2010a).