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This study addresses the pivotal role of digital transformation (DT) in the post-pandemic business landscape, identifying a notable gap in comprehending strategic adaptations and digital communication amidst the complexities of the digital era. It seeks to illuminate practical insights for businesses navigating through DT by intertwining its technological and organizational aspects.

Employing a conceptual approach, this paper synthesizes existing literature and theoretical frameworks related to DT, integrating its technological, strategic and organizational dimensions. It utilizes real-world instances to elucidate the digital era’s practical implications and strategic adaptations. The study also proposes a research agenda that spotlights pressing DT issues, challenges and actionable strategies for businesses.

Despite DT’s inherent complexity, the paper reveals that it is crucial for businesses navigating the contemporary digital landscape. It underscores the importance of strategic adaptations in DT, highlighting their implications on customer experiences and organizational structures amidst the evolving technological and market dynamics. Moreover, it accentuates the significance of effective digital communication strategies in enhancing user experiences and conveying value propositions adeptly.

This paper brings vital aspects of DT impacting modern organizations, offering invaluable insights for practitioners and scholars aiming to comprehend and navigate DT’s complexities. The identified research gaps underscore the necessity for further exploration, aiming to broaden DT’s theoretical and practical facets.

This study aims to investigate the potential impact and passenger perceptions of integrating multimedia books within airline services, aiming to elucidate the evolving landscape of in-flight entertainment and reading experiences.

A quantitative research methodology was used, using a structured questionnaire distributed to presenters at the International Federation of Library Associations.

Analysis revealed varying passenger interest in multimedia books, with approximately 57.7% displaying engagement, while 40.4% demonstrated limited interest or none. However, a notable majority (60.6%) preferred multimedia books over traditional print books during flights. Furthermore, 90.4% perceived a positive impact of multimedia books on flight reading experiences, leading to increased satisfaction (81.7%) and a high likelihood of recommending airlines offering such content (91.3%).

The study's limitations include a specific focus on International Federation of Library Associations and Institutions (IFLA) World Library and Information Congress (WLIC) presenters, potentially limiting broader generalisations. Further research might explore the preferences of a wider demographic range and incorporate qualitative aspects to deepen understanding. Airlines could leverage multimedia books to enhance passenger satisfaction, attract diverse audiences and foster cultural inclusivity within in-flight entertainment.

This study contributes insights into the evolving landscape of in-flight entertainment, emphasising the significant potential and positive impact of integrating multimedia books within airline services. It underscores the importance of catering to diverse passenger preferences and enhancing overall satisfaction during air travel.

Fierce competition among over-the-top (OTT) platforms has rendered branding a precondition for consumer appeal. This study proposes a new structural equation model for OTT brands, especially Netflix, where hedonic and eudaimonic entertainment motives function as facilitators of consumer brand engagement.

An online survey was conducted. Structural Equation Modeling was used to build the model and test for various direct, mediation, and moderation effects.

The results suggest a multiple mediation model in which the relationship between the two types of entertainment and intention to use Netflix is sequentially mediated by consumer attention and consumer brand engagement. Moreover, this study confirms that female consumers, compared to male consumers, exhibit higher levels of consumer brand engagement when motivated by hedonic entertainment.

This is the first study to present a novel structural model for the content consumption of OTT brands and test the role of the two types of entertainment in the intention to use Netflix.

ChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing realm. To address this gap, the current study explores ChatGPT’s application in marketing by mining social media data. Additionally, the study employs the stages-of- growth model to assess the current state of ChatGPT’s adoption in marketing organizations.

The study collected tweets related to ChatGPT and marketing using a web-scraping technique (N = 23,757). A topic model was trained on the tweet corpus using latent Dirichlet allocation to delineate ChatGPT’s major areas of applications in marketing.

The topic model produced seven latent topics that encapsulated ChatGPT’s major areas of applications in marketing including content marketing, digital marketing, search engine optimization, customer strategy, B2B marketing and prompt engineering. Further analyses reveal the popularity of and interest in these topics among marketing practitioners.

The findings contribute to the literature by offering empirical evidence of ChatGPT’s applications in marketing. They demonstrate the core use cases of ChatGPT in marketing. Further, the study applies the stages-of-growth model to situate ChatGPT’s current state of adoption in marketing organizations and anticipate its future trajectory.

The study explored how information institutions can support the resilience of parents of adolescents affected by the Russia–Ukraine war. Ukrainian parents are facing major challenges of supporting their teenagers through a difficult developmental phase while also “buffering” their war-related hardships. By supporting parents, information institutions can also support children.

Fifteen parents were interviewed about mental health challenges and resources that are helpful and/or missing from their support systems. Recordings of participant narratives were analyzed using the qualitative thematic analysis technique.

The findings indicate that both teens and parents rely on internal resilience skills, family, friends and community resources to support themselves. However, a number of additional resources could be offered by information institutions, including content for (1) teens on developing skills in communication, interpersonal relationships, problem solving and academic pursuits; (2) parents on child development and opportunities in their host countries; both groups on (3) both groups on mental health first aid and safe spaces to meet peers. The study recommendations will be of interest to information professionals working with families, especially families affected by disasters.

The study relied on a small convenience sample of participants.

Study recommendations would be of interest to information professionals who develop and provide services to families affected by natural and manmade disasters.

Study recommendations improve understanding of the (potential) role of information institutions and libraries in strengthening family and community resilience.

The study offers a rare insight into experiences of war-affect families and provides evidence-driven recommendations for information institutions to support family and community resilience.

In today’s digital world, data-driven digital artefacts pose challenges for education, as many students lack an understanding of data and feel powerless when interacting with them. This paper aims to address these challenges and introduces the data awareness framework. It focuses on understanding data-driven technologies and reflecting on the role of data in everyday life. The paper also presents an empirical study on young school students’ data awareness.

The study involves a teaching unit on data awareness framed by a pre- and post-test design using a questionnaire on students’ awareness and understanding of and reflection on data practices of data-driven digital artefacts.

The study’s findings indicate that the data awareness framework supports students in understanding data practices of data-driven digital artefacts. The findings also suggest that the framework encourages students to reflect on these data practices and think about their daily behaviour.

Students learn a model about interactions with data-driven digital artefacts and use it to analyse data-driven applications. This approach appears to enable students to understand these artefacts from everyday life and reflect on these interactions. The work contributes to research on data and artificial intelligence literacies and suggests a way to support students in developing self-determination and agency during interactions with data-driven digital artefacts.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

This paper considers the exhibition: UnDoing. This research-through-curation project examined interactions within existing spaces and situations. This established links between the selected exhibits, the gallery, the city and with the continuum of the previous exhibition.

Carefully selected architects, designers and artists were invited to contribute—those who pursued a contextual approach; whose practice explored the way buildings, places and artefacts are reused, reinterpreted and remembered.

Through the act of curation, this research uncovered a series of different approaches to constructed sites and existing buildings, from layered juxtaposition, the refusal to undo, to interventions of new elements within architectural works.

Curation offered the opportunity to consider works of architecture and of art through the same lens, for direct comparisons to be made and the influence of one upon the other to be comprehended.

The examination processes the architect employs is similar to that of the artist; the development of an understanding of place, and from this synthesis, creative interpretation. However, despite the similarities in the starting position, the elucidation developed by the artist can be vastly different to that of the architect.

The juxtaposition and new classifications created by the exhibition encouraged visitors to look at art, architecture and the city in a different way; to grasp the direct link between the different subjects; and the possibilities created.

The two driving factors for UnDoing were places of previous occupation and the city of Manchester. The qualities of surrounding constructed environment combined were combined with attitudes towards existing structures and places.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

Recent archiving and curatorial practices took advantage of the advancement in digital technologies, creating immersive and interactive experiences to emphasize the plurality of memory materials, encourage personalized sense-making and extract, manage and share the ever-growing surrounding knowledge. Audiovisual (AV) content, with its growing importance and popularity, is less explored on that end than texts and images. This paper examines the trend of datafication in AV archives and answers the critical question, “What to extract from AV materials and why?”.

This study roots in a comprehensive state-of-the-art review of digital methods and curatorial practices in AV archives. The thinking model for mapping AV archive data to purposes is based on pre-existing models for understanding multimedia content and metadata standards.

The thinking model connects AV content descriptors (data perspective) and purposes (curatorial perspective) and provides a theoretical map of how information extracted from AV archives should be fused and embedded for memory institutions. The model is constructed by looking into the three broad dimensions of audiovisual content – archival, affective and aesthetic, social and historical.

This paper contributes uniquely to the intersection of computational archives, audiovisual content and public sense-making experiences. It provides updates and insights to work towards datafied AV archives and cope with the increasing needs in the sense-making end using AV archives.