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Emphasizing the role of residents as destination advocates, the purpose of this paper is to investigate the influence of residents’ familiarity with, and, favorability of attractions on destination image.

A mixed methods research strategy was employed using 15 individual in-depth interviews and a survey questionnaire with a sample of n=364. The study utilizes an attraction familiarity index to classify respondents into four groups based on high, average, and low familiarity and examines the characteristics of each in the relationship between informational familiarity, experiential familiarity, and favorability and destination image.

The study reveals resident perceptions of attractions within the tourism product assembly framework and illustrates the positive relationship between the residents’ level of familiarity with, and favorability of visitor attractions and destination image. Further, the findings also demonstrate the significant role of demographic characteristics such as gender and length of residency in the area. The study findings suggest that temporary residents can function as destination advocates.

Employees and students from a prominent northeastern university were sampled, representing local residents and temporary residents respectively. While appropriate and fairly representative of the target market for the research questions in this investigation, more work is required to replicate this study utilizing representative samples across different locations.

Evidence from the study indicates the importance of marketing to residents as they serve as destination advocates. In particular, the residents’ familiarity with and favorability of attractions is critical to positive destination image. The research offers insights into the identification of potential segments of residents that require special attention.

Limited existing research investigates the role of residents as destination advocates, especially in the context of destinations that lack a primary tourism attraction but have a well-balanced mix of attractions.

This chapter unpacks the unique characteristics of online students, research that exists pertaining to support of online students in American higher education, and reviews the subsequent chapters in this volume. The chapters in this book focus on research, theoretical foundations for supporting the success of online student. Authors present case studies in various context including a large state university system, a large and increasingly growing public master’s degree, two private institutions, and a Scottish institution. Various theoretical constructs are provided to help inform practices for supporting online students including “communities of practice” (Wenger, 2000) or “communities of inquiry” (Garrison, 2007) and the Dynamic Student Development Metatheodel (DSDM). The final chapters of this book unpack the experiences of specific populations including post-baccalaureate, students, and doctoral students, understanding that each subset of students encounters different challenges throughout their online experiences. Finally, this book closes with a focus on a very important topic for all professionals: accessibility discussing the importance of inclusion, participation, and engagement for students with disabilities no matter the modality of learning. The last chapter compares two models of support (medical and social) and offers recommended changes for implementation of best practices to enhance literacy supports in online learning environments.

The first research objective is to understand the role of digital [artificial intelligence (AI)] technologies on user engagement and conversion that has resulted in high online activities and increased online sales in current times in India. In addition, combined with changes such as social distancing and lockdown due to the COVID-19 pandemic, digital disruption has largely impacted the old ways of communication both at the individual and organizational levels, ultimately resulting in prominent social change. While interacting in the virtual world, this change is more noticeable. Therefore, the second research objective is to examine if a satisfying experience during online shopping leads to repurchase intention.

Using primary data collected from consumers in a developing economy (India), we tested the theoretical model to further extend the theoretical debate in consumer research.

This study empirically tests and further establishes that deploying AI technologies have a positive relationship with user engagement and conversion. Further, conversion leads to satisfying user experience. Finally, the relationship between satisfying user experience and repurchase intention is also found to be significant.

The uniqueness of this study is that it tests few key relationships related to user engagement during this uncertain period (COVID-19 pandemic) and examines the underlying mechanism which leads to increase in online sales.

This paper aims to outline the purpose, planning, development and delivery of the “1st Academic-Practitioner Research with Impact workshop: Customer Experience Management (CEM) and Big Data” held at Alliance Manchester Business School on 18th and 19th January 2016, at which four subsequent papers were initially developed.

The paper sets out a summary of the importance and significance of the four papers developed at the workshop and how the co-creative dialogue between managerial practitioners, presenting key problems and issues that they face, and carefully selected teams of academics was facilitated.

To develop richer and more impactful understanding of current problems challenging customer-focused managers, there is a need for more dialogue and engagement between academics and practitioners.

The paper serves as a guideline for developing future workshops that aim at strengthening the links between academia and the business world.

This paper highlights the value of academic–practitioner workshops for focusing academic research on areas of importance for practitioners to generate impact. The innovative format of the workshop and the resulting impactful papers should serve as a call and motivation for future academic–practitioner workshop development.

This study aims to analyse and understand the current state of research in the field of digital marketing in “library and information science”.

This study used a “bibliometric research design.” A lexical title search was used to obtain the required data set for executing this study, and a comprehensive “indexing and abstracting” database, Web of Science, was used as a data harvesting source. Louvain’s clustering algorithm was used for network metrics.

The findings revealed that research productivity and impact have grown considerably over time, indicating significant attention towards digital marketing research in library and information science (LIS). Moreover, the results showed that the overall author collaboration patterns were weak, hence creating room for development in the author’s collaboration patterns.

The current study could be very beneficial in providing a comprehensive and up-to-date overview of the “digital marketing” research field scholarly output in LIS, which can be used by researchers, practitioners and policymakers to guide their work and make informed decisions.

The originality of this bibliometric study lies in its comprehensive and up-to-date analysis of the current state of research in the field of “digital marketing” in LIS. This study provides a unique and in-depth understanding of the key authors, venues and papers in the field, as well as the trends and patterns in the research.

This paper aims to focus on how companies shape the architecture of a phygital customer journey through the exploitation of smart technologies.

The research adopts a qualitative method using a grounded theory approach involving leading players in digital customer solutions and service providers from different industries.

The shaping of the architecture of the phygital customer journey comes from the interplay between systems of insights and systems of engagement activated by multiple customer-provider interactions in an entanglement of physical and digital contexts.

Companies need to design a blended approach to bridge disconnected contexts, capture new opportunities and provide customer engagement along the entire journey.

This study depicts the “phygital customer journey” under systems of insights and systems of engagement: These systems operate as dynamic architectures to capture insights and engage customers.

This paper aims to address the limitations in designing educational approaches that apply critical approaches to data literacy, given the obscure nature of digital platforms, which leave youth unable to develop discourses that challenge dominant narratives about the role of data in their lives. The purpose of this study is to propose and evaluate a critical data literacy approach that empowers youth to engage with data from a sociocultural perspective using a speculative participatory research approach that affords opportunities to develop alternative discourses.

This is a multiple-case study that involves five alternative schools in Uruguay which implemented the Nayah-Irú curriculum over ten weeks leading to the development of six distinct research projects about the materialization of data in youth lives. The curriculum incorporates an alternate reality game (ARG) to engage youth in critical data literacy, based on the principles of Youth Participatory Action Research (YPAR) epistemology and Speculative Civic Literacies.

The findings of this study highlight the integration of speculative storytelling and real-life experiences in developing alternative discourses about datafication. The analysis revealed instances of discursive closure among the youth, but through the curriculum's speculative fiction elements, such as the narrative of Nayah-Irú, emotional connections were formed, leading to increased engagement, critical inquiry, and problem framing.

The study conducted on the Nayah-Irú curriculum shows its effectiveness in engaging youth and educators in critical data literacy by affording opportunities for youth to engage in the analysis of their personal data literacies in an alternative world. Bringing speculative approaches to data literacy can open new avenues for exploring data literacy with youth in ways that center their voices and help them overcome different forms of discursive closure.

This study offers new insights into critical data literacy education blending youth participatory action research epistemologies with a speculative literacies framework to support youth in developing alternative discourses regarding the role of data in their lives.

As public health professionals strive to promote vaccines for inoculation efforts, fervent anti-vaccination movements are marshaling against it. This study is motived by a need to better understand the online discussion around vaccination. The authors identified the sentiments, emotions and topics of pro- and anti-vaxxers’ tweets, investigated their change since the pandemic started and further examined the associations between these content features and audiences’ engagement.

Utilizing a snowball sampling method, data were collected from the Twitter accounts of 100 pro-vaxxers (266,680 tweets) and 100 anti-vaxxers (248,425 tweets). The authors are adopting a zero-shot machine learning algorithm with a pre-trained transformer-based model for sentiment analysis and structural topic modeling to extract the topics. And the authors use the hurdle negative binomial model to test the relationships among sentiment/emotion, topics and engagement.

In general, pro-vaxxers used more positive tones and more emotions of joy in their tweets, while anti-vaxxers utilized more negative terms. The cues of sadness predominantly encourage retweets across the pro- and anti-vaccine corpus, while tweets amplifying the emotion of surprise are more attention-grabbing and getting more likes. Topic modeling of tweets yields the top 15 topics for pro- and anti-vaxxers separately. Among the pro-vaxxers’ tweets, the topics of “Child protection” and “COVID-19 situation” are positively predicting audiences’ engagement. For anti-vaxxers, the topics of “Supporting Trump,” “Injured children,” “COVID-19 situation,” “Media propaganda” and “Community building” are more appealing to audiences.

This study utilizes social media data and a state-of-art machine learning algorithm to generate insights into the development of emotionally appealing content and effective vaccine promotion strategies while combating coronavirus disease 2019 and moving toward a global recovery.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-03-2022-0186

Intergenerational appreciative inquiry is an approach that maximizes the generativity of all generations and the generative outcomes of intergenerational collaboration. While conversations about intergenerationalism have increased in recent decades, forums and strategies for intergenerational collaboration have emerged at a much slower rate. In this chapter we explore definitions of the concepts of intergenerational and multigenerational and discuss generativity in the context of intergenerationalism. We share how we have found the appreciative inquiry summit, and other appreciative-based processes, to possess a natural capacity for enabling intergenerational inquiry that can maximize generativity. We conclude by turning to the future and discussing generational changes that are taking place in society and why we expect intergenerational appreciative inquiry will only increase in importance as we continue caring for the future together.