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This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

This article aims to develop a new theory that can better explain and predict how and when humans interact with commercial robots. To this end, utility maximization theory (UMT) along with four principles and propositions that may guide how human-to-commercial robot interactions are developed.

This article conceptualizes UMT by drawing from social exchange, conservation of resources, and technology-driven theories.

This article proposes UMT, which consists of four guiding principles and propositions. First, it is proposed that the human must invest sufficient resources to initiate a human-to-commercial robot interaction. Second, the human forms an expectation of utility gain maximization once a human-to-commercial robot interaction is initiated. Third, the human severs a human-to-commercial robot interaction if the human is unable to witness maximum utility gain upon the interaction. Finally, once the human severs a human-to-commercial robot interaction, the human seeks to reinvest sufficient resources in another human-to-commercial robot interaction with the same expectation of utility maximization.

This article is one of the few studies that offers a theoretical foundation for understanding the interactions between humans and commercial robots. Additionally, this article provides several managerial implications for managing effective human-to-commercial robot interactions.

The purpose of this paper is to explore the effects of human interaction versus interactions with technology in overall customer satisfaction with banking services, specifically, tellers versus Automated Teller Machines (ATMs) vs online transactions. All types of interactions are important in services, yet their level of importance is changing as the environment change.

Two studies were conducted through surveys with students who had a bank checking account; six item measures were used to examine human interaction, interaction with an ATM, interaction with an online banking service and overall satisfaction with the specific bank. Multiple regression analyses were conducted to determine the effects of the interactions on overall satisfaction.

The findings from the two studies show that while the human encounter was more important before online banking became so prevalent, the convenience of online banking has displaced the importance of human interaction. However, there were gender differences in that males, more than females, remain influenced by teller transactions.

The study utilizes student samples, which could be biased. However, students are also users of banking services so they represent a traditional target market for financial service firms.

The results are informative for managers when planning and implementing new online services in the financial industry.

This paper draws together research on interpersonal interactions and technological interactions to examine the effects on overall satisfaction. Given the proliferation of technological advances, understanding how these technologies impact customer satisfaction is vital.

The healthcare sector is experiencing a major paradigm shift toward a people-centered approach. The key issue with transitioning to a people-centered approach is a lack of understanding of the ever-increasing role of technology in blended human-technology healthcare interactions and the impacts on healthcare actors' well-being. The purpose of the paper is to identify the key mechanisms and influencing factors through which blended service realities affect engaged actors' well-being in a healthcare context.

This conceptual paper takes a human-centric perspective and a value co-creation lens and uses theory synthesis and adaptation to investigate blended human-technology service realities in healthcare services.

The authors conceptualize three blended human-technology service realities – human-dominant, balanced and technology-dominant – and identify two key mechanisms – shared control and emotional-social and cognitive complexity – and three influencing factors – meaningful human-technology experiences, agency and DART (dialogue, access, risk, transparency) – that affect the well-being outcome of engaged actors in these blended human-technology service realities.

Managerially, the framework provides a useful tool for the design and management of blended human-technology realities. The paper explains how healthcare services should pay attention to management and interventions of different services realities and their impact on engaged actors. Blended human-technology reality examples – telehealth, virtual reality (VR) and service robots in healthcare – are used to support and contextualize the study’s conceptual work. A future research agenda is provided.

This study contributes to service literature by developing a new conceptual framework that underpins the mechanisms and factors that influence the relationships between blended human-technology service realities and engaged actors' well-being.

The purpose of this paper is to study the use of blended learning in the workplace and questions whether interpersonal interaction facilitates learner engagement (specifically behavioral, cognitive and/or emotional engagement), and if so, the means by which this occurs.

A qualitative approach was taken to this exploratory study, a single-case study design was utilized, and data collection methods involved interviews with facilitators and past participants of a blended workplace learning (BWL) program.

Human interaction in the BWL program included learner–facilitator, learner–learner and learner–colleague interaction. Where human interaction was present, it was reported to be linked with more active behavioral engagement, higher cognitive engagement and stronger and more positive emotional engagement than where human interaction was absent.

The single-case study design does not allow for generalizability of findings. Reliance on self-reported data through interviews without cross-validation from other forms of measurement is a further limitation of the study.

Effective blended learning programs for workplaces are those that provide opportunities for learners to engage through human interaction with facilitators, other learners and colleagues. The findings advance current knowledge of BWL, and have implications for human resource development professionals, and designers and facilitators of blended learning programs for workplaces.

The study contributes to existing literature on blended learning in the workplace and emphasizes the importance of ensuring that human interaction is still an element of blended learning to maximize the benefits to learners and organizations.

The purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.

A trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.

Six volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.

The AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

This piece is a review of the animal selfhood literature in sociology, organized into four main parts. First, I review the sociological literature of human–animal interactions, in which sociologists claim that animals possess selves. Second, I review how sociologists have referred to the self, from which I construct five criteria of selfhood, including self as attribution, self-awareness, intersubjectivity, self-concept/reflexivity, and narration. Third, I address how animals have selves using these criteria, drawing on sociological and ethological evidence. Fourth, I critique the animal interaction sociologists’ specific claims of animal selfhood, including their epistemological failure to distinguish between human accounts of animal subjectivities and animal subjectivities, and their empirical failure to show how animals act toward themselves. Ultimately, I conclude that animal selves, particularly in an elemental Meadian sense, are potentially real, but in most cases are unobservable or unverifiable phenomena.

This paper aims to synthesize the key findings of prior research on the topic of human-wildlife interactions (HWI) in natural places for tourism.

The methodology of systematic review was used to search for, appraise and analyze the relevant research evidence. A total of 47 English-language academic journal articles, published between 2003 and 2018, with free online access to full texts in the database of Hospitality and Tourism Complete have been reviewed. Thematic analysis was adopted to synthesize the textual data.

The reviewed articles cover a wide geographical spread, diverse wildlife species and interaction types, and various research focuses including ecological impacts, human dimensions and management issues of wildlife tourism. The interactions between wildlife and human systems in the context of tourism constitute a complicated social-ecological system, in which both the humans and animals can be affected positively and negatively. Management and scientific research provide the nexus between the ecological and human dimensions of wildlife tourism. While opportunities for sustainable development abound, challenges are not to be neglected.

Due to the complexity of wildlife encounters for tourist purposes, the extant literature indicates a diverse and fragmented view from which integrated implications are difficult to obtain. This paper presents the first overarching review in English of the literature on human-wildlife interactions for tourism and provides a big picture understanding of what has been and what is needed to be done in terms of both wildlife tourism research and practices.

Service robots can offer benefits to consumers (e.g. convenience, flexibility, availability, efficiency) and service providers (e.g. cost savings), but a lack of trust hinders consumer adoption. To enhance trust, firms add human-like features to robots; yet, anthropomorphism theory is ambiguous about their appropriate implementation. This study therefore aims to investigate what is more effective for fostering trust: appearance features that are more human-like or social functioning features that are more human-like.

In an experimental field study, a humanoid service robot displayed gaze cues in the form of changing eye colour in one condition and static eye colour in the other. Thus, the robot was more human-like in its social functioning in one condition (displaying gaze cues, but not in the way that humans do) and more human-like in its appearance in the other (static eye colour, but no gaze cues). Self-reported data from 114 participants revealing their perceptions of trust, anthropomorphism, interaction comfort, enjoyment and intention to use were analysed using partial least squares path modelling.

Interaction comfort moderates the effect of gaze cues on anthropomorphism, insofar as gaze cues increase anthropomorphism when comfort is low and decrease it when comfort is high. Anthropomorphism drives trust, intention to use and enjoyment.

To extend human–robot interaction literature, the findings provide novel theoretical understanding of anthropomorphism directed towards humanoid robots.

By investigating which features influence trust, this study gives managers insights into reasons for selecting or optimizing humanoid robots for service interactions.

This study examines the difference between appearance and social functioning features as drivers of anthropomorphism and trust, which can benefit research on self-service technology adoption.