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This paper aims to assess the interaction between environmental challenges and policy interventions in shaping housing prices. It emphasises the need to understand how policy interventions and environmental conditions can disproportionately affect housing affordability, population growth and building density, especially for vulnerable communities.

The study uses a panel quantile ARDL regression model to thoroughly investigate the asymmetric impact on a sample of 16 UK cities spanning the period 2000–2023.

The study reveals that pollution significantly impacts house prices, with cleaner areas experiencing faster price changes. Cleaner air pollution has a greater impact on property prices in cities with cleaner air. Climate policies and superior environmental technologies also influence consumer purchases. Addressing affordability has little short-term effect on house values, but building activity temporarily affects pricing. Investment in clean technology and climate action legislation may boost house prices and attract environmentally conscious individuals.

Based on these findings, policymakers seeking equitable and sustainable housing outcomes should consider these finding. It proposes evaluating city environmental features, eliminating environmental inequities, encouraging clean technology, balancing affordability and environmental concerns, monitoring and lowering pollutants and supporting sustainable building practices.

To the best of the author’s knowledge, this study is the first to analyse how environmental conditions, regulations on environmental action and demand-supply affect housing prices in 16 major UK cities. The connection between these factors is also examined in 8 cities with high and 8 cities with extremely low pollution. The research seeks to explore how environmental issues affect policy interventions to promote sustainable and equitable housing development. The asymmetric impact is examined using a panel quantile ARDL regression model. If property values are asymmetrical, the government should enforce severe environmental laws.

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.

We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.

Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.

This is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.

This chapter reviews some of the technical background relating to the designs of digital infrastructures for financial services. Such technical background could be useful to the understanding of the design choices that the central banks and pertinent regulators face when developing or promoting open digital infrastructures for financial services. First, the chapter reviews modularity and interoperability in the design of digital infrastructure. The chapter then examines three broad architectural models of open digital infrastructures: decentralized, centralized and distributed. The chapter ends with some lessons learnt from the different architectural models that have been implemented in practice.

This study aims to understand how distributed agile teams (DATs), encouraged by globalisation, and recently accelerated by the COVID-19 outbreak, adopt agile practices to achieve project goals by working virtually.

This study developed a multiple-case study involving four companies undergoing several changes, especially during the COVID-19 pandemic. The authors collected data mainly through in-depth, face-to-face interviews with seven key informants. Moreover, this study operates data triangulation by referring to secondary data sources and developing a grounded theory data analysis.

The findings highlight three main categories associated with the DAT functioning, namely, “DATs’ implementation issues”, “elements supporting DATs’ implementation” and “outcomes of DATs’ implementation”, that show DATs’ primary triggers, critical aspects and supportive actions for team functioning.

This paper produced valuable theoretical knowledge of DATs’ dynamics within a socio-technical approach that distinguishes soft and hard variables supporting DAT implementation. Moreover, the evidence provides useful suggestions for managers about creating an objective-oriented virtual work environment based on DATs’ self-organisation, digitally shared leadership and occasional on-site socialisation.

This paper provides new and interesting insights that bring to evidence the main variables related to DATs’ adoption and dynamics, showing supporting activities that enhanced their operativity. It provides a valuable descriptive framework for academics and practitioners to understand DATs’ functioning better and take action to improve their implementation.

This chapter first reviews open banking, a key data sharing initiative promoted by various central banks and regulators around the world to help nudge competition, innovation and better financial services for consumers in the digital age. The chapter then reviews various models and approaches as well as key success factors of open banking, as well as the extensions of open banking into open finance in various jurisdictions.

Integrating sustainability into university curricula brings diverse challenges and conflicts as separate units vie for ownership of courses and topics. This case study presents a six dimensions sustainability framework developed at The Ohio State University to organize curricula under an inclusive strategy.

An interdisciplinary group of faculty focused on sustainability education engaged in a three-phased process including review of sustainability definitions from diverse disciplines; analysis of key aspects of the definitions in conjunction with course descriptions and learning outcomes; and identification of commonalities across the key aspects. This yielded six foundational dimensions of sustainability which serve as a means to assess curricular contributions across University units and topics. The six dimensions framework has been used in practice in multiple contexts.

The six dimensions framework provides a way to identify and foster diverse sustainability curricula efforts. It has enabled academic units to describe their disciplinary and interdisciplinary perspectives on diverse sustainability topics and the University to advance a broad sustainability vision.

The six dimensions framework provides a novel “big tent” approach to integration of sustainability into higher education curricula. The framework provides guidance about what counts as sustainability while maintaining the breadth that widens participation.

The paper proposes a framework for the successful deployment of Industry 4.0 (I4.0) principles in the aerospace industry, based on identified success factors. The paper challenges the perception of I4.0 being aligned with de-skilling and personnel reduction and instead promotes a route to successful deployment centred on upskilling and retaining personnel for future role requirements.

The research methodology involved a literature review and industrial data collection via questionnaires to develop and validate the framework. The questionnaire was sent to a purposive sample of 50 respondents working in operations, and a response rate of 90% was achieved. Content analysis was used to identify patterns, themes, or biases, and the data were tabulated based on specific common attributes. The proposed framework consists of a series of gates and criteria that must be met before progressing to the next gate.

The proposed framework provides a feedback mechanism to review minimum standards for successful deployment, aligned with new developments in capability and technology, and ensures quality assessment at each gate. The paper highlights the potential benefits of I4.0 implementation in the aerospace industry, including reducing operational costs and improving competitiveness by eliminating variation in manufacturing processes. The identified success factors were used to define the framework, and the identified failure points were used to form mitigation actions or controls for inclusion in the framework.

The paper provides a framework for the successful deployment of I4.0 principles in the aerospace industry, based on identified success factors. The framework challenges the perception of I4.0 as being aligned with de-skilling and personnel reduction and instead promotes a route to successful deployment centred on upskilling and retaining personnel for future role requirements. The framework can be used as a guideline for organizations to deploy I4.0 principles successfully and improve competitiveness.

This chapter examines the world of risk management within fintech. It initiates by emphasizing the crucial role of technology and risk assessment in shaping the fintech landscape. It discusses various risk categories prevalent in fintech operations, elucidating the nuances of technology, operational, compliance, strategic, and reputational risks. A comparative analysis across different fintech sub-sectors unveils their distinct risk profiles. The narrative extends to proactive risk management frameworks, contrasting prominent models like the COSO ERM, FAIR Risk Quantification, and NIST Cybersecurity Frameworks. Integral defense measures are scrutinized, encompassing data encryption, access controls, vulnerability assessments, and incident response plans. This chapter underscores the significance of building operational resilience through robust technology infrastructure, regular system updates, disaster recovery planning, and business continuity measures. Ultimately, this chapter culminates in a comprehensive summary, offering pragmatic recommendations to fortify technology risk management in fintech.