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The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

Entrepreneurs are generally considered to be committed in order to strive for highly desirable goals, such as growth or commercial success. However, commitment is a multidimensional concept and may have asymmetric relationships with positive or negative entrepreneurial outcomes. This paper aims to provide a nuanced perspective to show under what conditions commitment may be detrimental for entrepreneurs and lead to overinvestment.

Using a sample of entrepreneurs from incubators in France (N = 437), this study employs a configurational perspective, fuzzy-set qualitative comparative analysis (fsQCA), to identify which commitment profiles lead entrepreneurs to overinvest different resources in their entrepreneurial projects.

The paper exposes combinations of conditions that lead to overinvestment and identifies five different commitment profiles: an “Affective profile”, a “Project committed profile”, a “Profession committed profile”, an “Instrumental profile”, and an “Affective project profile”.

The results show that affective commitment is a necessary condition for entrepreneurs to conduct overinvesting behaviors. This complements previous linear research on the interdependence between affect and commitment in fostering detrimental outcomes for nascent entrepreneurs.

This research navigates the confluence of data analytics, machine learning, and artificial intelligence to revolutionize the management of urban services in smart cities. The study thoroughly investigated with advanced tools to scrutinize key performance indicators integral to the functioning of smart cities, thereby enhancing leadership and decision-making strategies. Our work involves the implementation of various machine learning models such as Logistic Regression, Support Vector Machine, Decision Tree, Naive Bayes, and Artificial Neural Networks (ANN), to the data. Notably, the Support Vector Machine and Bernoulli Naive Bayes models exhibit robust performance with an accuracy rate of 70% precision score. In particular, the study underscores the employment of an ANN model on our existing dataset, optimized using the Adam optimizer. Although the model yields an overall accuracy of 61% and a precision score of 58%, implying correct predictions for the positive class 58% of the time, a comprehensive performance assessment using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) metrics was necessary. This evaluation results in a score of 0.475 at a threshold of 0.5, indicating that there's room for model enhancement. These models and their performance metrics serve as a key cog in our data analytics pipeline, providing decision-makers and city leaders with actionable insights that can steer urban service management decisions. Through real-time data availability and intuitive visualization dashboards, these leaders can promptly comprehend the current state of their services, pinpoint areas requiring improvement, and make informed decisions to bolster these services. This research illuminates the potential for data analytics, machine learning, and AI to significantly upgrade urban service management in smart cities, fostering sustainable and livable communities. Moreover, our findings contribute valuable knowledge to other cities aiming to adopt similar strategies, thus aiding the continued development of smart cities globally.

Performance measures are an important mediating mechanism that influences the design and delivery of care. Unfortunately, it is still commonly the case that acute care indicators are employed to assess the efficacy of integrated care. This hinders the ability to accurately assess and continuously improve integrated care efforts for priority populations, including older persons who live with complex health and social care requirements. A core set of indicators is needed from which to assess the quality and impact of integrated care on these older persons and care partners.

A modified Delphi process was employed that comprised of the following steps: (1) selection of an indicator inventory (2) defining criteria for ranking and achieving consensus, (3) recruiting participants, (4) iterative voting rounds and analysis and (5) selection of a core indicator set.

The study produced a core set of 16 indicators of integrated care that pertain to older persons who live with health and social care requirements. The set can be applied by health and social care organizations and systems to assess the quality and impact of integrated care for this population across the continuum of care.

Although the gap in the availability of relevant indicators was the impetus for the study, this also meant there was a dearth of validated indicators to draw from. There are significant gaps in commonly used data sets with respect to indicators of integrated care as it relates to older persons and care partner.

The indicator set is intended to follow the older person and care partner throughout their health journey, enabling a whole systems view of their care. The set can be used in full or in part by health and social care systems and organizations across various primary, acute, rehabilitative and community settings for program development and evaluation purposes.

The core set of indicators that emerged out of this study is a first step toward ensuring that older persons who live with complex health and social care requirements and their care partners receive quality integrated care across the continuum of care.

The findings are informed by the perspectives of older persons, care partners and healthcare professionals. Future research is needed to test, validate and potentially expand the indicator set.

This study aims to investigate the contextual challenges of emergency Web-enabled teaching from instructors’ point of view and their future preference for online education.

A total of 165 instructors from various public and private universities and university colleges in Malaysia participated in this online survey. Data were analyzed using multiple regression.

The significant challenges for future preference for online education in terms of their relative importance were supporting learners, effectiveness, disadvantages and advantages of emergency Web-enabled teaching.

This study discusses theoretical, practical and public policy implications for the future of teaching in higher education due to the COVID-19 public health emergency.

How can large international financial firms go green in authentic ways? What enhances ‘Net Zero action’? Changes in global banks, fund managers, and insurance firms are at the heart of green finance. External change pressures – combined with problematic firm predispositions – exacerbate barriers to change and promote scepticism about authentic Net Zero change. Field research reveals main elements, connections, and interactions of this question by considering financial firms as complex socio-technical systems (Mitleton-Kelly, 2003). An interdisciplinary/holistic narrative approach (De Bakker et al., 2019) is adopted to design a conceptual framework that can support a green ‘behavioural theory of the financial firm’ (green BTFF). The BTFF presents an international version (Peng, 2001) of the resource-based view (RBV) of the firm (Barney, 1991; Hart, 1995; Teece et al., 1997).

The approach of this chapter is aimed at closing knowledge gaps and realign values in financial markets and society. By raising awareness about organised hypocrisy and facades (Brunsson, 1993; Cho et al., 2015; Schoeneborn et al., 2020) in financial firms the chapter aims at overcoming the gap between ‘talking’ and ‘walking’ in the financial sector. The chapter defines testable firm-level hypotheses for ‘Green Finance’ (Poterba, 2021) as well as – by implication – tests for ‘greenwashing’.

Although virtual worlds, such as the Metaverse, can disrupt the hospitality sector, few empirical investigations have critically evaluated the scope and scale of this disruption from an industry perspective. This study aims to rectify this knowledge gap by exploring the opportunities and challenges of the Metaverse as seen by hospitality professionals.

This is a Delphi study conducted with UK-based senior hospitality industry practitioners experienced in designing and implementing digital innovations within their organisations.

The Metaverse is most likely to be adopted by hospitality organisations willing and able to take risks, such as large and/or chain-affiliated enterprises. The Metaverse will not replace traditional hospitality services but supplement and enhance them with new layers of service. The main applications are in the context of events and experiences. The Metaverse will also provide the “try before you buy” option, revealing the opportunities to design digital twins of physical businesses. Young and technology-savvy individuals are most likely to first adopt the Metaverse. The key challenges of the adoption are attributed to the technological unpreparedness of hospitality organisations; market immaturity; inflated customer expectations; a skills gap among hospitality employees; and regulatory issues. These challenges require the engagement of various stakeholders to create an operational and monitoring framework for hospitality organisations to embrace the Metaverse.

This study highlights how the Metaverse can disrupt the hospitality industry at the level of strategic planning and business operations.

To the best of the authors’ knowledge, this is one of the first empirical investigations of the potential of the Metaverse from the viewpoint of hospitality industry practitioners.