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The purpose of this study is to quantify the impact of electricity power outages on the local housing market in South Africa.

This study uses the autoregressive distributive lag (ARDL) and quantile autoregressive distributive lag (QARDL) models on annual time series data, for the period 1971–2014. The interest rate, real income and inflation were used as control variables to enable a multivariate framework.

The results from the ARDL model show that real income is the only factor influencing housing price over the long run, whereas other variables only have short-run effects. The estimates from the QARDL further reveal hidden cointegration relationship over the long run with higher quantile levels of distribution and transmission losses raising the residential price growth.

Overall, the findings of this study imply that the South African housing market is more vulnerable to property devaluation caused by power outages over the short run and yet remains resilient to loadshedding over the long run. Other macro-economic factors, such as real income and inflation, are more influential factors towards long-run developments in the residential market.

To the best of the authors’ knowledge, this is the first study to examine the empirical relationship between power outages and housing price growth.

Managing biosphere reserves (BR) have become more challenging regarding the socio-cultural conflict between communities and BR administrators. For the past two decades, community participation (CP) has become the central narrative for BR management practices in Asia. This paper aims to set out to analyse the current literature because of the paucity of systematic reviews on CP in Asian BR. Also, it proffers possible solutions to enhance biosphere performance.

In total, 31 related studies were identified from the Scopus, Web of Science databases and materials from organisations in the field of practice of territorial conservation. Three themes emerged from the review – willingness to participate, encumbrances and possible solutions.

Factors that influence community willingness to participate in a BR, encumbrances facing the community and possible policy solutions to enhance CP in a BR in Asia were the three themes that emerged from the review. The factors that influence community willingness were categorised into the level of participants in education, perceived waste of time, no confidence of the outcome, okay with current management, land owned, household size and gender factors.

This paper’s recommendations were based on empirical literature reviewed systematically but do not compromise the robustness concerning BR management practices in Asia. It was established that to enrich the findings of this research, regional studies of CP in BR should be conducted, including primary source data using the mixed methods paradigm.

As part of the practical implications, recommendations were highlighted to enhance CP in BR. Also, the paper suggested that BR administrators should have two-way communication mechanisms, cross-sectoral participation and collaboration, implement locally-based solutions through full engagement of community members in decision-making.

This is probably the first systematic review paper on BR management practices in Asia. Filling the theoretical gap via systematic review was part of the significant contribution to CP in Asian BR.

In this chapter, we theorize about online freelancers’ approaches to work flexibility. Drawing from an ongoing digital ethnography of US-based online freelancers pursuing work on digital platforms, our data question the common conceptualizations around the flexibility of online freelancing. We posit that the flexibility of where to work, not when to work, is the most important attribute of their work arrangement. Our data show (1) the online freelancers in our study prefer the stability and sustainability of full-time work over freelancing when both are offered as remote options; (2) full-time remote employment increases these workers’ freelancing control / flexibility; (3) these workers keep freelance work options open even as they transition to more permanent full-time work arrangements. We discuss how these findings relate to workplace culture shifts and what this means for contemporary working arrangements. Our insights contribute to the discourses on knowledge-based gig work and for what it means to study individuals online.

The purpose of this research is to evaluate corruption in the context of India, spanning the period between 1988 and 2021. Additionally, it aims to provide an in-depth comprehension of the factors that drive its prevalence and to propose policy directives for addressing these underlying issues.

The study instead of relying on perception-based measures, takes a distinct approach by formulating a corruption index derived from reported instances, thus ensuring a more objective assessment. Furthermore, we employ stochastic frontier analysis to tackle the issue of under-reporting within the corruption index based on reported cases. Subsequently, an auto regressive distributed lag (ARDL) methodology is applied to ascertain the principal drivers of corruption, encompassing both long and short factors.

This study reveals that corruption in India is notably influenced by economic growth and income inequality. Conversely, government effectiveness and globalization display a tendency to mitigate corruption. However, our rigorous analysis demonstrates that financial development does not wield a substantial influence in our study. Moreover, our inquiry uncovers a nonlinear relationship between economic growth and corruption. Additionally, we ascertain that the long run and short run impacts of corruption remain relatively stable across both models utilized in our study.

This study differs from previous research in the subsequent manners. Primarily, we employed an objective measure to formulate the corruption index, coupled with addressing the underreporting issues via stochastic frontier analysis. Moreover, this study pioneers the identification of a non-linear relationship between corruption and economic growth within the Indian context, a facet unexplored in previous investigations.

This study aims to develop an entrepreneurial business model capable of addressing and preventing the exploitation and inequality that traditionally have resulted from entrepreneurship, particularly in emerging economies.

The research uses systems thinking, the first law of cybernetics, and the principles of harmony to formulate a systemic solution to the problem, which it exemplifies via six purposefully selected short cases drawn from diverse industry sectors and economies.

This paper demonstrates how the conventional model of entrepreneurship, often associated with colonial exploitation and resultant inequalities, can be transformed into a triple bottom line model—harmonious entrepreneurship – that integrates the traditional economic, eco-, humane, and social approaches and creates a synergy where profit, planet, and people are in harmony. The model challenges the profit maximisation/shareholder value doctrine of business success.

Only six cases are presented here, and there is a need for further research in different political-economic contexts and industry sectors. Also, the way entrepreneurship is taught needs to change so that it addresses the sustainability challenge in general and the problem of inequality in particular.

There needs to be a change in the entrepreneurial mindset and the way entrepreneurship is taught and potential entrepreneurs are trained if entrepreneurship is to address the sustainability challenge in general and the problem of inequality in particular.

This is a novel approach to the study of entrepreneurship and its impact on inequality that shows how it can ameliorate and/or prevent inequality, particularly in emerging economies, by adopting a more holistic approach to business success and supplanting “having and needing” with “being and caring”.

How do radical technological fields become naturalized and taken for granted? This is a fundamental question given both the positive and negative hype surrounding the emergence of many new technologies. In this chapter, we study the emergence of the US nanotechnology field, focusing on uncovering the mechanisms by which leaders of the National Nanotechnology Initiative managed hype and its concomitant legitimacy challenges which threatened the commercial viability of nanotechnology. Drawing on the cultural entrepreneurship literature at the interface of strategy and organization theory, we argue that the construction of a naturalizing frame – a frame that focuses attention and practice on mundane, “rationalized” activity – is key to legitimating a novel and uncertain technological field. Leveraging the insights from our case study, we further develop a staged process model of how a naturalizing frame may be constructed, thereby paving the way for a decrease in hype and the institutionalization of new technologies.

This chapter on anti-racism struggles applies an anti-racist activist framing, both critically examining and recognising the milestones achieved through centuries of pro-justice and anti-racism struggles. It delves into the arduous journey that the global fight for racial equity has undergone and highlights the significant progress as well as setbacks experienced during this lengthy struggle. The earliest history of the fight against racial oppression and domination goes back to anti-slavery and anti-colonial movements. Scholars have analysed the emergence, development and state of global anti-racism struggles in a variety of ways. I approach this subject from a sociological perspective, highlighting the role of social structures, groups and institutions that have contributed to shaping the outcomes of anti-racist initiatives. While recognising the role of individuals and leading political activists, this chapter emphasises anti-racism as a collective social justice struggle. To do this, I explore various local and global anti-racism endeavours and examine how they may influence discussions on race, racism and racial equity and their evolving trajectories across different societies.

Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lightning prediction.

The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

The research is limited to the data collected in support of weather prediction work through the 45th Weather Squadron of the United States Air Force.

These methods are important due to the increasing reliance on sensor systems. These systems often provide incomplete and chaotic data, which must be used despite collection limitations. This work establishes a viable data imputation methodology.

Improved lightning prediction, as with any improved prediction methods for natural weather events, can save lives and resources due to timely, cautious behaviors as a result of the predictions.

Based on the authors’ knowledge, this is a novel application of these imputation methods and the forecasting methods.