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High levels of interior water vapour lead to condensation and black mould that in turn represent significant risks to residential properties and their occupants. Beliefs about window opening are good predictors of the degree to which householders will actually open windows to purge their homes of water vapour, including water vapour that they themselves generate. The present study tested if a short information-giving intervention could enhance householders’ beliefs that foster window opening as purge ventilation and, in turn, lead to greater window opening.

Data were collected from 242 UK householders with robust psychometrically sound measures embedded in an online self-report survey that also presented the intervention information.

The intervention led participants, and males in particular, to have significantly greater concerns about condensation and mould and significantly less concerns about heat loss costs arising from opening windows, and these altered beliefs in turn predicted a greater intention to open windows in the future.

By sharing simple information, surveyors and other building professionals can help householders take the simple step of opening their windows and so reduce the threats that condensation and mould present to themselves and their homes.

This is the first study to test (1) a time-based model that predicted the intervention would have a positive effect on specific window opening attitudes and that those new attitudes would in turn affect window opening intentions, and (2) if the intervention had different effects on men and women.

Despite the potential benefits of open government data (OGD) and its recent adoption by many governments, little is known about monitoring its use by the public. This paper aims to address the knowledge gap by empirically examining OGD usage in Tanzania.

A field survey design was used to gather quantitative data from 288 people in seven regions of Tanzania to facilitate an analysis of the determinants of users’ behavioural intention and use behaviour of OGD. Guided by the Unified Theory of Acceptance and Use of Technology model, the study analysed the tendencies of these determinants on the use of the OGD portal.

The results show that performance expectancy, effort expectancy, social influence and facilitating conditions affect users’ acceptance and use of the OGD portal. The results suggest that OGD initiatives should focus more on their potential applications than publication. It is important to monitor and evaluate OGD use and the conditions that allow it to continue. By linking OGD with other government initiatives, governments can build strategies, capacity and social awareness. During the development of OGD platforms for extensive reuse, new data technologies like the semantic web should be considered.

Hitherto, research has underlined the significance of OGD initiatives at large and that studies in developing countries are scarce, especially that probe the uptake of the current efforts. The present study seeks to plug this research gap by examining the use of OGD in Tanzania’s context.

In March 2020 the United Nations published an open brief for the creative community to propose interventions to the unfolding COVID-19 pandemic. However, when faced with unprecedented wicked problems such as these, the rigour of design and creative processes can tested. COVID-19 has demonstrated how important human centred design responses are in understanding the worldviews and ecosystems of users. Ad hoc design responses or design hacks have demonstrated that they have a role to play in how we create our future individual, community and societal ecosystems.

In terms of age friendly design, this pandemic makes us envision what should be, furthermore, how we could create better products and services through technology. For our ageing communities “Cocooning” and other social restriction measures have exposed technological deficiencies for the needs of older people and opens up questions of our future preparedness for a growing ageing society. Now more than ever, designers need to understand the behavioural mind-set of older people in their own ecosystem and understand existing mental models.

In this opinion piece we posit what acts of design hacking can lead us to greater understanding of users mental models and therefore better understanding of technology needs for both older and younger adults. While presenting various examples of how design hacking is conducted by citizens and participants alike, it shows that it offers designers differing perspectives, experiences and inspiration for technology.

Science policy and practice for open access (OA) books is a rapidly evolving area in the scholarly domain. However, there is much that remains unknown, including how many OA books there are and to what degree they are included in preservation coverage. The purpose of this study is to contribute towards filling this knowledge gap in order to advance both research and practice in the domain of OA books.

This study utilized open bibliometric data sources to aggregate a harmonized dataset of metadata records for OA books (data sources: the Directory of Open Access Books, OpenAIRE, OpenAlex, Scielo Books, The Lens, and WorldCat). This dataset was then cross-matched based on unique identifiers and book titles to openly available content listings of trusted preservation services (data sources: Cariniana Network, CLOCKSS, Global LOCKSS Network, and Portico). The web domains of the OA books were determined by querying the web addresses or digital object identifiers provided in the metadata of the bibliometric database entries.

In total, 396,995 unique records were identified from the OA book bibliometric sources, of which 19% were found to be included in at least one of the preservation services. The results suggest reason for concern for the long tail of OA books distributed at thousands of different web domains as these include volatile cloud storage or sometimes no longer contained the files at all.

Data quality issues, varying definitions of OA across services and inconsistent implementation of unique identifiers were discovered as key challenges. The study includes recommendations for publishers, libraries, data providers and preservation services for improving monitoring and practices for OA book preservation.

This study provides methodological and empirical findings for advancing the practices of OA book publishing, preservation and research.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The Cloud of Things (IoT) that refers to the integration of the Cloud Computing (CC) and the Internet of Things (IoT), has dramatically changed the way treatments are done in the ubiquitous computing world. This integration has become imperative because the important amount of data generated by IoT devices needs the CC as a storage and processing infrastructure. Unfortunately, security issues in CoT remain more critical since users and IoT devices continue to share computing as well as networking resources remotely. Moreover, preserving data privacy in such an environment is also a critical concern. Therefore, the CoT is continuously growing up security and privacy issues. This paper focused on security and privacy considerations by analyzing some potential challenges and risks that need to be resolved. To achieve that, the CoT architecture and existing applications have been investigated. Furthermore, a number of security as well as privacy concerns and issues as well as open challenges, are discussed in this work.

Higher education models continue to transform and advance across multiple trajectories spurred by knowledge economies and digital futures. The demand for disciplinary expertise, agile and responsive transition of graduates from university to industry, and employees who are adept and multi-skilled at working with global teams, has continued to raise the significance of international curricula and wider student experiences.

This chapter discusses the changing landscape of higher education and the disruptive influences that impinge on existing pedagogical models in the delivery of learning and teaching. It analyses the need for ‘just in time’, stackable units of learning that support learners in their lifelong learning journeys, embedded with 21st Century Learning skills. Further, the chapter will review existing models for course and curriculum development, recommend appropriate course development processes that are seamless, and meet industry and professional disciplinary agency requirements.

The introductory chapter in the volume offers a rationale for bringing together, in an edited collection, contributions from authors who emphasize the continued relevance of mentoring in academia. The focus of mentoring in the volume is on enabling academics to orient their practice towards the Sustainable Development Goals (SDGs); the introduction highlights the selection of SDGs discussed, as well as critically reflective responses to these in existing literature. The structure of the volume and of individual chapters is mapped for the benefit of readers. The volume is a hybrid text, combining academic scholarly reflection with narrative vignettes and with dialogue excerpts, to illustrate more fully SDG-oriented mentoring practices and experiences. The principles underpinning the writing methodology and the sources which have helped shape these principles are discussed here. As well as unpacking the writing methodology, the introductory chapter spotlights three core texts on mentoring which informed the volume at proposal stage and throughout the writing process. A personal note on mentoring from the volume editor is followed by a ‘pause and reflect’ section, which offers questions for the reader to consider when engaging with some or all the chapters in the volume.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.