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The main objective of this paper is to analyze the relationship between employees' propensity to innovate and cultivate entrepreneurial aspirations whilst working within an organization. This paper aims to contribute to a better understanding of this interrelation, reflecting from a theoretical point of view on the factors that influence innovative propensity and entrepreneurial intention of the paid employee working in a public sector organization and studying the role played by the opportunity cost.

A questionnaire survey was used to collect data from 149 employees working for a public organization. In order to verify the hypotheses proffered, two multiple regression analyses were undertaken.

The authors provide evidence that an understanding of the capacity that some employees have towards innovation offers an added tier of information and affords meaningful results. Their findings suggest that there is a positive impact of innovative propensity on entrepreneurial intention, and that it is stronger when combined with lower opportunity cost.

The study contributes to the field of entrepreneurship being informative for researchers interested in the antecedents of entrepreneurial intention and can also be utilized to further research in the field of human resource management and retention practices within organizations.

This study contributes to the growing empirical literature on entrepreneurial intention from a perspective that has been hitherto largely overlooked: the employee's perspective.

Although humanoid robots are increasingly adopted in many business settings, the dynamic effects of anthropomorphism and the functional perceptions of service robots on consumers’ responses remain unclear. This paper aims to examine the impacts of robot anthropomorphism on consumers’ trust, receptivity and the downstream effect on satisfaction. Furthermore, it examines the mediating effects of perceived ease of use (PEOU) and perceived usefulness (PU) in the relationship between anthropomorphism and consumer responses.

After conducting two separate pilot studies to help design the research materials, this research involves three sequential studies. In studies 1A and 1B, the authors used two distinct humanoid robots (i.e. Connie and Pepper) to test the direct effects of anthropomorphism on trust and receptivity and the mediated effects via PEOU and PU. Study 2 conducted a 2 (robot appearance: machine-like vs. human-like) × 2 (task complexity: low vs. high) between-subjects experimental design to further explore the boundary effects of task complexity on trust and customer satisfaction.

This research theorizes and empirically examines the mediating effects of PEOU and PU in the relationship between anthropomorphism and consumers’ responses (i.e. trust and receptivity) to service robots. Results also demonstrate a moderating role of task complexity, whereby only when the task was complex did anthropomorphism affect consumer responses and customer satisfaction. The parallel mediations of PEOU and PU were also confirmed. However, when task complexity was low, the authors observed no differences between human- and machine-like robots.

First, this research used a scenario-based method by exposing participants to different pictures or videos of service robots and measuring individuals’ responses. Consumers may respond differently upon interacting with robots in actual service contexts. Second, future research could investigate the effects of other aspects of anthropomorphism, such as robots’ voice characteristics (gender, high/low pitch), verbal communication styles and emotional expression. Finally, future research could explore other service contexts to test the generalizability of the findings.

Findings of this study also provide useful insight for companies interested in adopting service robots. First, the authors unearthed several positive outcomes of using human-like versus machine-like robots in service settings. Despite concerns about the perceived creepiness and discomfort associated with human-like robots, managers should not worry about these service agents’ potential negative effects. Second, it shows that human-like robots’ competitive advantage over machine-like robots stands out when task complexity is high. Managers should therefore carefully consider relevant service characteristics and task requirements when deciding whether to adopt robots.

This study provides original and valuable contributions to the growing literature on service robots by addressing scholarly incongruencies regarding the impact of anthropomorphism and disentangling its positive influence on consumers’ perceptions and acceptance of service robots. This study also contributes to research on technology acceptance and service robot receptivity by empirically demonstrating the mediating role of PEOU and PU. Furthermore, this research enriches the body of knowledge on task-technology fit by providing evidence that task complexity is a crucial factor to consider in service robot design.

The changing technological landscape has brought about new forms of groups and grouping that span across computing and communication devices, space, time, institutions, cultures, realities (physical, virtual, and augmented), and intelligence (natural and artificial intelligence). This chapter utilizes a series of publication and keyword analyses to identify trends in group and technology research in the fields of communication, management, and computer-supported cooperative work (CSCW) between 2008 and 2019. The results reveal prominent research areas, and recent shifts and emergent questions in the study of groups and technology, highlighting a complex entanglement of technology with collaborative social practices. The chapter concludes with a discussion of novel key areas and trends suggested by the analyses, with the goal of contributing toward a research agenda for future study of groups and technology.

Within tertiary education, service-learning can offer deeply engaging and transformational experiences for students, broadening their consideration of a host of social justice issues of our time, including diversity and inclusion. This chapter describes how service-learning interfaces with two areas in particular, both of which have wide-ranging public health implications and are generally misrepresented in public media: poverty and mental health. Representative studies are highlighted and case examples are presented in each domain, concluding with recommendations for future research. The authors argue that service-learning courses addressing social justice issues such as poverty and mental health can lead to deep learning in students if they are sequenced to include both direct service-learning that concretizes the issue and community-based research that highlights the public policy challenges and implications of addressing that issue systemically.

The purpose of this paper is to compare relative levels of rental affordability across the English housing association sector.

A total of two methods, rent‐to‐income ratio and residual income standards (poverty‐line and budget standard), are used to maximise their strengths and complement their weaknesses in measuring rental affordability.

The rent‐to‐income ratio analysis identified that housing association rents were generally affordable. However, the residual income analyses using two different minimum acceptable standards suggested some scepticism in this regard. In particular, both analyses confirmed the affordability problem in London where nearly half of existing housing association tenants had disposable household incomes that were well below the poverty‐line as well as the largest rent‐to‐income ratio. Both analyses also confirmed that lone parents were more likely than average households to have an affordability problem.

The main limitations of this study are the small sample size of existing housing association tenants and different definitions of incomes, and subsequently different residual income measures for existing and new tenants. However, this study demonstrates that when examining the affordability of housing for the poorest households, multiple overlapping measures of affordability are likely to be more reliable than any single measure.

The paper is an empirical attempt to use a combination of two affordability measures to examine the affordability problem of social tenants in the English housing association sector. It is also unusual in the scientific literature to use different data sources to obtain household incomes for different types of housing association tenants.

The chapter provides a brief review of team diversity research from its roots in group composition and workforce demographics through recent trends toward dynamic multilevel models. The divergence from this research area's early motivations in social justice and inclusion to a primarily economic motivation is highlighted. The chapter also reviews major theories that have been used to explain diversity effects in team interactions and outcomes. The review leads to a discussion of three broad critiques of mainstream diversity research, namely a predominance of US cultural outlook, a narrow disciplinary base in organization sciences and psychology, and inadequate attention and overly simplistic perspective on communication processes. The chapter ends with implications for team diversity research and a discussion of how the suggestions can be applied to emerging dimensions of diversity.

This study aims to compares the effects of different human-like appearances (low vs. medium vs. high) of service robots (SRs) on consumer trust in service robots (CTSR), examines the mediating role of perceived warmth (WA) and perceived competence (CO) and demonstrates the moderating role of culture and service setting.

The research design includes three scenario-based experiments (Chinese hotel setting, American hotel setting, Chinese hospital setting).

Study 1 found SR’s human-like appearance can arouse perceived anthropomorphism (PA), which positively affects CTSR through parallel mediators (WA and CO). Study 2 revealed consumers from Chinese (vs. American) culture had higher CTSR. Study 3 showed consumers had higher WA and CO for SRs in the credence (vs. experience) service setting. The authors also had an exploratory analysis of the uncanny valley phenomenon.

The findings have practical implications for promoting the diffusion of SRs in the hospitality industry. Managers can increase CTSR by augmenting the anthropomorphic design of SRs; however, they must consider the differences in this effect across all service recipients (consumers from different cultures) and service settings.

The authors introduce WA and CO as mediators between PA and CTSR and set the culture and service setting as moderators.

The following is an annotated list of materials dealing with information literacy including instruction in the use of information resources, research, and computer skills related to retrieving, using, and evaluating information. This review, the twenty‐second to be published in Reference Services Review, includes items in English published in 1995. After 21 years, the title of this review of the literature has been changed from “Library Orientation and Instruction” to “Library Instruction and Information Literacy,” to indicate the growing trend of moving to information skills instruction.

This study reviews existing research and current applications of artificial intelligence (AI) in the hospitality and tourism industry. It further proposes a new evaluation framework to inform the susceptibility of AI adoptions.

This is a synthesis and evaluation study that qualitatively summarizes and presents findings on AI applications in the hospitality and tourism industry. Current AI applications are rated using a seven-dimensional framework based on Rogers' (2003) diffusion theory.

AI adoption susceptibility in the hospitality and tourism industry varies based on the type of AI. Search/booking engines, virtual agents and chatbots rank high in the adoption susceptibility.

This study bridges innovation diffusion theoretical underpinnings and AI applications. The findings support researchers, developers and managers in evaluating the adoption susceptibility of AI technologies in the hospitality and tourism industry.

This paper is among the few that focus on assessing AI adoption susceptibility in the hospitality and tourism industry. This paper develops a theory-based framework for systematically evaluating AI innovations in hospitality and tourism.