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The purpose of this paper is to examine employees’ experiences of institutional betrayal after a campus sexual assault.

University employees completed online measures evaluating various attitudes toward the university.

The majority of participants reported institutional betrayal in the university’s response to the case. Employees who reported institutional betrayal indicated significantly lower attachment to the university than employees who reported no institutional betrayal. Institutional betrayal mediated the relationship between institutional attachment and institutional forgiveness.

Universities’ failure to respond effectively and promptly to sexual violence does not go unnoticed by employees. Institutional actions after sexual assault have the power to damage employees’ attachment to the university – employees who experienced institutional betrayal were less attached, and ultimately less forgiving of the institution. Universities’ poor prevention and response efforts impact their entire campus community and compromise community members’ ongoing relationship with the school.

College students’ active resistance to sexual violence on campus is featured prominently on the pages of major news outlets. Yet, less featured in research and media is the impact of campus sexual assault on university employees, particularly after sexual assault cases are mishandled. This study offers perspective on employees’ experiences and reactions after a prominent sexual assault case.

Although prior research has indicated that posttraumatic stress symptoms may result from sex-based harassment, limited research has targeted a key posttraumatic outcome – dissociation. Dissociation has been linked to experiences of betrayal trauma and institutional betrayal; sex-based harassment is very often a significant betrayal creating a bind for the target. The purpose of this paper is to extend existing research by investigating the relationship between sex-based harassment, general dissociation, sexual dissociation and sexual communication.

This exploratory study utilized self-report measures from a sample of male and female Oregon residents using Amazon Mechanical Turk (N=582).

Results of regression analyses indicated that harassment statistically predicted higher general dissociation, higher sexual dissociation and less effective sexual communication, even after controlling for prior sexual trauma experiences. Results did not indicate any significant interactions between gender and harassment.

When considering the effects of sex-based harassment on women and men, clinicians and institutional organizations should consider the role of dissociation as a possible coping mechanism for harassment.

These correlational findings provide evidence that sex-based harassment is uniquely associated with multiple negative psychological outcomes in men and women.

This paper analyzes the age pay gap in Italy (22%), particularly as it is of interest in an aging society and as it may affect social cohesion. Instead of the traditional approach for model selection, we use a machine-learning approach (post double robust Least Absolute Shrinkage Operator [LASSO]). This approach allows us to reduce Omitted Variable Bias (OVB), given data restrictions, and to obtain a robust estimate of the conditional age pay gap. We then decompose the conditional gap and analyze the impact of four further potential sources of heterogeneity (workers', sectors', and occupations' permanent heterogeneity as well as sample selection bias). The results suggest that age discrimination in pay is only perceived but not real in Italy for both men and women.

This chapter explores the relationship between emotional design and customer experience. It begins with an introduction to the concept of emotional design, comprising behavioral, visceral, and reflective elements. Next, the nature of service experiences is examined, leading to a framework that classifies services according to their functional and experiential positions. Understanding customer goals allows this framework to be used to design customer experiences, in terms of the journey that customers take when consuming a service. The chapter then discusses the cognitive traits associated with designers and argues that they are well suited to understanding the customer journey and designing the prerequisites for the desired experience. Two different approaches to understanding and acting on customer requirements are explored – user centered and design driven.

The marketing literature uses five different experience terms that are supposed to represent different streams of research. Many papers do not provide a definition, most of the used definitions are unclear, the different experience terms have similar dimensionality and are regularly used interchangeably or have the same meaning. In addition, the existing definitions are not adequately informed from other disciplines that have engaged with experience. This paper aims to build a comprehensive conceptual framework of experience in marketing informed by related disciplines aiming to provide a more holistic definition of the term.

This research follows previously established procedures by conducting a systematic literature review of experience. From the approximately 5,000 sources identified in three disciplines, 267 sources were selected, marketing (148), philosophy (90) and psychology (29). To address definitional issues the analysis focused on enlightening four premises.

This paper posits that the term brand experience can be used in all marketing-related experiences and proposes four premises that may resolve the vagaries associated with the term’s conceptualization. The four premises address the what, who, how and when of brand experience and aim to rectify conceptual issues. Brand experience is introduced as a multi-level phenomenon.

The suggested singular term, brand experience, captures all experiences in marketing. The identified additional elements of brand experience, such as the levels of experience and the revision of emotions within brand experience as a continuum, tempered by repetition, should be considered in future research.

The multi-level conceptualization may provide a greater scope for dynamic approaches to brand experience design thus providing greater opportunities for managers to create sustainable competitive advantages and differentiation from competitors.

This paper completes a systematic literature review of brand experience across marketing, philosophy and psychology which delineates and enlightens the conceptualization of brand experience and presents brand experience in a multi-level conceptualization, opening the possibility for further theoretical, methodological and interdisciplinary promise.

Purpose: This chapter describes the design and implementation, at the computer hardware and software level, of the Greggg robot. Greggg is a scalable high performance, low cost hospitality robot constructed from off-the-shelf parts. Greggg has a robust architecture and acts as a tour guide on-campus, both indoors or outdoors. This research allows one to build a customized robot at a low cost, under U.S. $2,000, for accomplishing the desired hospitality tasks, and scale, and expand the capability of the robot as required.

Practical Implications: The practical implication of the research is the capability to build and program a robot for hospitality tasks. Greggg is a customizable robot capable of giving on-campus tours both indoors and outdoors. In its current architecture, Greggg can be trained to be a museum docent and give directions to visitors on-campus or at an airport and scaled up for other hospitality tasks using off-the-shelf components. Enhancing the robot by scaling it up and expanding it, in addition to testing it with a range of increasingly more difficult tasks using machine learning algorithms, is highly beneficial to advancing research on the use of robots in the hospitality sector. Greggg can also be used for Robot-as-a-service (Rass) applications.

Societal Implications: The economic implication of Greggg is the ease and low cost with which one, with minimal technology know-how, can construct an autonomous hospitality industry robot. This chapter details the hardware and software needed to build a low cost scalable and customizable autonomous robot for the hospitality industry without having to pay an exorbitant price.

Research/Limitations/Implications: This research allows one to build their own customized hospitality robot under U.S. $2,000. Given the cost of building the robot, it has limitations on the hospitality tasks it can perform. It can navigate on flat surfaces, has limited vision and speech processing capabilities and has a battery life not exceeding an hour. Furthermore, it does not have any robotic manipulators or tactile processing capabilities.

Purpose – To compare the histories of two opioid medications that are pharmacologically similar but subject to contrasting regulations in their use in treatment of opiate dependence in the United States – methadone and buprenorphine – in order to analyze the role of racial imagery and racial politics in the legalization and clinical promotion of their use.

Methodology/approach – Historical methods of archival analysis of published articles and unpublished governmental records were used in researching methadone. Ethnographic methods of participant observation and semistructured interviews were used in researching buprenorphine.

Findings – Contrasting uses of racial imagery played a major role in shaping the current regulatory differences between the two treatments. The association of methadone with black and Latino heroin users has contributed to its increased federal regulation, while the association of buprenorphine with white, middle class prescription opioid users enabled its use in deregulated private physicians’ offices.

Originality/value of paper – Advocates of biomedicalization of behaviors and conditions thought of as social or moral, such as addiction, argue that biomedicalization reduces the stigma of the condition and imply that, in turn, it also reduces the racial inequalities associated with the condition. This study of the biomedicalization of treatment for opioid dependence indicates that the very process of biomedicalization depended on heightened racial imagery associated with each treatment and ultimately intensified, rather than reduced, the stigma of addiction for black and Latino low-income patients.

This chapter treats the luxury hotel concept and practice and its recent trends in the tourism industry. This niche market is expanding rapidly with changing global income structures and increasing complexity of the hospitality sector. Its clientele comprises quality-seeking, prestige-striving, and high-spending customers. The chapter first explores the concept of luxury in relation to hotels. It further groups various associated assets into tangibles and intangibles to discuss their recent trends across the world. It is suggested that companies and destinations active in the luxury hotel market or contemplating entry take these trends into account to gain and/or maintain competitiveness.

The global health crisis represents an unprecedented opportunity for the development of artificial intelligence (AI) solutions. This paper aims to integrate explainable AI into the decision-making process in emergency scenarios to help mitigate the high levels of complexity and uncertainty associated with these situations. An AI solution is designed to extract insights into opioid overdose (OD) that can help government agencies to improve their medical emergency response and reduce opioid-related deaths.

This paper employs the design science research paradigm as an overarching framework. Open-access digital data and AI, two essential components within the digital transformation domain, are used to accurately predict OD survival rates.

The proposed AI solution has two primary implications for the advancement of informed emergency management. Results show that it can help not only local agencies plan their resources for timely response to OD incidents, thus improving survival rates, but also governments to identify geographical areas with lower survival rates and their primary contributing factor; hence, they can plan and allocate long-term resources to increase survival rates and help in developing effective emergency-related policies.

This paper illustrates that digital transformation, particularly open-access digital data and AI, can improve the emergency management framework (EMF). It also demonstrates that the AI models developed in this study can identify opioid OD trends and determine the significant factors improving survival rates.