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The purpose of this study is to examine whether PV uptake is associated with key housing market determinants and linked to socio-economic profiles. An abundance of extant literature has examined the role of solar photovoltaic (PV) adoption and user costs, with an emerging corpus of literature investigating the role of the determinants of PV uptake, particularly in relation to the built environment and the spatial variation of PV dependency and dissimilarity. Despite this burgeoning literature, there remains limited insights from the UK perspective on housing market characteristics driving PV adoption and in relation spatial differences and heterogeneity that may exist.

Applying micro-based data at the Super Output Area-level geography, this study develops a series of ordinary least squares, spatial econometric models and a logistic regression analysis to examine built environment, housing tenure and deprivation attributes on PV adoption at the regional level in Northern Ireland, UK.

The findings emerging from the research reveal the presence of some spatial clustering and PV diffusion, in line with several existing studies. The findings demonstrate that an urban-rural dichotomy exists seemingly driven by social interaction and peer effects which has a profound impact on the likelihood of PV adoption. Further, the results exhibit tenure composition and “economic status” to be significant and important determinants of PV diffusion and uptake.

Housing market characteristics such as tenure composition across local market structures remain under-researched in relation to renewable energy uptake and adoption. This study examines the role of housing market attributes relative to socio-economic standing for adopting renewable energy.

The attempt to establish a common European framework for core platforms' duties and responsibilities toward other actors in the digital environment is at the core of the recent scholarly debate surrounding the Digital Markets Act (DMA) proposal. In particular, the everlasting juxtaposition between the “data power” – as emerging from recent cases (Section 2) – that dominant tech companies enjoy and the concept of consumer sovereignty (Section 3) lies at the core of the proposal's attempt to identify digital core platforms as market gatekeepers. Accordingly, this chapter critically investigates the divide between power imbalance and consumer sovereignty in light of the architecture designed by the DMA, with a specific focus on its effectiveness in identifying gatekeepers' power drivers (Section 4). After highlighting the main critical aspects of the pertinent rules, opportunities for fruitful developments are then identified through the reframing of some of the notions considered in the proposal, and namely the role of “lock-in” effects and “data accumulation” (Section 5). Lastly, this chapter suggests that the DMA advancements – while desirable – are bound to be fragmentary in the absence of a wider appraisal of the nature of data power imbalance dynamics in the modern digital markets (Section 6).

Granting ‘sanctuary’ in the United States to those fleeing poverty and violence is rooted in a deep history of hospitality and compassion. As we are witnessing a rise in xenophobia accompanied by policies of exclusion, we also see a rising number of ‘sanctuary jurisdictions’ limiting their cooperation with immigration authorities that many communities consider are using extremely harsh and punitive measures to detain and deport irregular migrants. As this chapter will demonstrate, there has been a dramatic increase through ‘immigration federalism’ of the number of these jurisdictions in cities, states and municipalities since the first practices of ‘sanctuary’ in the 1980s as result of the waves of forced migration due to the civil wars in Central America. The author also proposes that those entities granting ‘sanctuary’ to irregular migrants should also apply practices of ‘compassionate migration’ as described in the chapter to expand their protections further and include them in their communities.

This study aims to explore and extend the consumer–brand relationship literature by integrating the relatively new construct of brand coolness with a growing body of work on gratitude. Specifically, gratitude is explored alongside emotional brand attachment as an additional mechanism affecting the relationship between cool brands and the loyalty outcome of repurchase intention. Consumption context is examined as a boundary condition to the effect of gratitude.

Data was collected from an online survey of a Qualtrics panel of 356 US consumers. A moderated mediation model is used to explain the effects of brand coolness on repurchase intention via emotional brand attachment and brand gratitude in the moderating presence of consumption context.

Brand coolness significantly increases repurchase intention. Furthermore, emotional brand attachment and brand gratitude are established as parallel mediators of the relationship between brand coolness and repurchase intention, with brand gratitude exhibiting a significantly stronger mediated effect. The impact of brand coolness on brand gratitude is moderated by social visibility, with publicly consumed cool brands stimulating greater brand gratitude than their privately consumed counterparts.

Brand gratitude is shown to influence repurchase intention independent of the impact exerted by consumers’ emotional brand attachment. Cognitive appraisal theory is used to distinguish brand gratitude from other mediators studied in consumer–brand relationships. Findings establish the moderating influence of the social visibility of the brand on the relationship between brand coolness and gratitude.

Embedded in built environment discourse, this chapter examines the traditional knowledge and resilience of the Ngadjuri Nation Peoples through an Elder’s narrative of reconciliation as well as resistance in their subsisting colonial settlement. Removed from ‘Country’ in the 1840s, Ngadjuri Aboriginal community endured colonial industries of open-cut copper mining and large-scale pastoralism as irreparable destruction to their cultural landscapes. European processes in the resources sectors reshaped natural topographies, deconstructing Ngadjuri Songlines and Ancestral Dreaming stories. Burra’s colonial stone buildings of settlement, painstakingly cut and composed from materials of the surrounding ecological terrain, prompted new narratives from Ngadjuri as a way of alleviating scars. Broadly speaking, this chapter aims to show how cultural heritage of two communities is provocatively and conceptually unpacked through the vernacular buildings’ cross-cultural foundations. That is, an under-reported narrative was unwittingly bestowed on the colonial-built forms with hidden meanings that deserve further investigation. This chapter offers a counternarrative to colonial histories revealing Ngadjuri’s methods for reconnecting to Country and culture after generations of disempowerment. It explores how within the materiality of colonial structures, the Ngadjuri entwined their remediated storylines – revealing a data curation that had avoided popular discourse in the galleries, libraries, archives, and museums [GLAM] sector representation. This example implies there are bodies of knowledge in built cultural heritage hidden elsewhere on our Aboriginal Nations and the challenges it presents GLAM in their Indigenisation processes.

Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to identify key service- and digital technology-driven B2B innovation modes and proposes a research agenda for further exploration.

This conceptual paper adopts a techno-demarcation view on service innovation, encompassing three core dimensions: service offering (the service product, or the “what”), service process (the “how”) and service ecosystem (the “who/for whom”). It delineates the implications of three digital technologies – the internet-of-things (IoT), intelligent automation (IA) and digital platforms – for service innovation across these core dimensions in B2B markets.

Digital technology has immense potential ramifications for value creation by reshaping all three core dimensions of service innovation. Specifically, IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, while digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems.

This study suggests an agenda with six themes for further research, each linked to one or more of the three service innovation dimensions. They are (1) new recurring revenue models, (2) service innovation in the metaverse, (3) scaling up service innovations, (4) ecosystem innovations, (5) power dependency and lock-in effects and (6) security and responsibility in digital domains.

A recent study reported Black women are frequently labeled unprofessional due to hair presentation, 1.5 times more likely to be sent home citing “unprofessional hair,” and 80% likely to alter their natural hair texture (Dove, 2019) through chemicals or heat to fit into organizational norms. Meanwhile, conversations about hair discrimination and bias remain whispers in The Ivory Tower. Despite this study, contemporary research regarding higher education and the politics of Black women, Black hair, and hair texture is sparse. The lack of representation in higher education organizations and lack of literature suggest that Black, higher education professional women are at risk of experiencing chilly work environments that could impact belonging, career trajectory, and earning potential. Some individuals outside the African Diaspora may consider the notion of a physical characteristic, like hair, to be insignificant, let alone a salient identity for Black women. However, my experience as a higher education practitioner and scholar states differently. I assert higher education institutions continue to perpetuate and reproduce oppressive dynamics that specifically target Black women and Black hair when hair discrimination and bias are left out of the conversation to address diversity and inclusion concerns. This chapter introduces a historical context of Black hair discrimination; explores my lived experiences navigating Black hair, hair texture, and professionalism in higher education; outlines challenges for higher education institutions and prioritizes Black women alongside diversity and inclusion efforts.

In recognising the key role of business intelligence and big data analytics in influencing companies’ decision-making processes, this paper aims to codify the main phases through which companies can approach, develop and manage big data analytics.

By adopting a research strategy based on case studies, this paper depicts the main phases and challenges that companies “live” through in approaching big data analytics as a way to support their decision-making processes. The analysis of case studies has been chosen as the main research method because it offers the possibility for different data sources to describe a phenomenon and subsequently to develop and test theories.

This paper provides a possible depiction of the main phases and challenges through which the approach(es) to big data analytics can emerge and evolve over time with reference to companies’ decision-making processes.

This paper recalls the attention of researchers in defining clear patterns through which technology-based approaches should be developed. In its depiction of the main phases of the development of big data analytics in companies’ decision-making processes, this paper highlights the possible domains in which to define and renovate approaches to value. The proposed conceptual model derives from the adoption of an inductive approach. Despite its validity, it is discussed and questioned through multiple case studies. In addition, its generalisability requires further discussion and analysis in the light of alternative interpretative perspectives.

The reflections herein offer practitioners interested in company management the possibility to develop performance measurement tools that can evaluate how each phase can contribute to companies’ value creation processes.

This paper contributes to the ongoing debate about the role of digital technologies in influencing managerial and social models. This paper provides a conceptual model that is able to support both researchers and practitioners in understanding through which phases big data analytics can be approached and managed to enhance value processes.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.