Search results

Purpose: The study aims to analyse and discuss the effect of COVID-19 on businesses. The chapter discusses the various machine learning (ML) tools and techniques, which can help in better decision making by businesses in the present world.

Need for the Study: COVID-19 has increased the role of VUCA elements in the business environment, and there is a need to address the challenges faced by businesses in such environment. ML and artificial learning can help businesses in facing such challenges.

Methodology: The focus and approach of the chapter are in the context of using artificial intelligence (AI) and ML techniques for decision making during the COVID-19 pandemic in a VUCA business environment.

Findings: The key findings and their implications emphasise the importance of understanding and implementing AI and ML techniques in business strategies during times of crisis.

Practical Implications: The chapter’s content is in the context of using AI and ML techniques during the COVID-19 pandemic and in a VUCA business environment.

Although educators would likely agree that values and ethics are important in all disciplines, they have particular importance for practice-oriented fields. These applied professionals need to solve complex social problems that require the application of ethical standards and value perspectives. While the importance of value-engaged practice is known to the applied field, there is little research and conversation about how values can be integrated into teaching. This chapter synthesizes values-education approaches in various practice-based disciplines such as public administration (PA), program evaluation, social work, and public health. This chapter draws from empirical and theoretical works as well as the authors' experiences developing, participating in, and conducting values-based research on professionals and professional education.

Implementing the 17 Sustainable Development Goals (SDGs) unarguably demands huge financial investments. However, the United Nations has acknowledged the huge financial gap militating against the implementation of the SDGs worldwide, leading experts to question the possibility of complete implementation of the goals by their terminal dateline of 2030. While the bulk of the finance currently outlaid on the SDGs comes from traditional sources including foreign direct investments (FDIs), there is the need to focus more attention on developing and exploiting impact investments that are more suitable for financing development programmes and projects. In this chapter, the SDG implementation profiles of the 12 Arab West Asia countries concerning the five most targeted SDGs were evaluated and sustainable finance issues were discussed. Secondary data were retrieved from World Bank's DataBank. The data were descriptively analyzed. Based on the profiles generated, debt relief is put forward as a possible impact investment mechanism suitable for funding the SDGs. Specifically, this chapter recommends that outright cancellation of debts based on the debt-for-SGD swap could serve as some of the impact investments needed to boost the global drive for a developed, peaceful, and just world.

This book aimed to conceptualise a construction workforce management model suitable for effectively managing workers in construction organisations. To this end, this chapter presents the conceptualised model, which consists of seven workforce management practices with their respective measurement variables. Drawing from existing theories, models, and practices, the chapter concludes that a construction organisation that will attain its strategic objectives in the current fourth industrial revolution era must be willing to promote effective recruitment and selection, compensation and benefits, performance management and appraisal, employee involvement and empowerment, training and development, as well as improving workers emotional intelligence and handling external environment pressure. These practices can promote proactiveness, participation, and improved skills and can lead to effective commitment, better quality, and flexibility within the organisation.

Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.

A quick search of the headlines of major newspapers reveals a treasure trove of technology procurement gone wrong. While the private sector seems to adopt and implement new technology seamlessly and quickly to deliver for customers, the government struggles to accomplish technology purchases and integrations with the same ease. As governments in the United States are looking to retain their current workforce and attract the next generation of workers, the technological capabilities and ethos of governments will be paramount. With nearly every industry being transformed by technology and Generation T being the first generation to have an ingrained “technology first” mindset, the ability of governments to attract these workers depends, in large part, on the ability to transform their government technology culture, policies, and practices.

In this chapter, the authors examine the administrative branch and observe two key components at the root of most technology failures: poor organizational structure in the bureaucracy and the lack of an empowered Chief Information/Technology Officer. Building upon case studies from Massachusetts and California, this chapter looks at the factors related to failure or success to understand the technology procurement culture. The chapter concludes by presenting four key “best practice” principles of public policy and administration that can be implemented by almost any governmental entity to improve their acquisition and implementation of technology.

This chapter is dedicated to understanding the idea of international as a key notion to the development of globalisation and to promoting the rescaling of spaces and subjects in contemporary higher education. The author discusses the concept of scale as a performative device that activates the capacities of bodies. Instead of seeing scale as a naturalised and hierarchical structure of spatial distribution, the author understands it as an ensemble of discourses and practices that produce scalar effects. Globalisation uses scale to promote the idea that subjects would become ‘international’ by being linked to privileged spaces and bodies in the Global North. In this sense, globalisation is not merely about nodes where certain flows converge. Rather, the author understands it as the political conditions that control and constrain the space for certain flows to occur and not others. Using assemblage analysis, the author presents and analyses three scenes taken from his ethnographic records that have as a guiding line the materialisation of the international. These scenes report the experience of being a Latin American doctoral student attending a congress in the United States, a tense situation experienced at a Chilean university academic event, and the unpretentious manifestation of an elaborate idea of internationality from a personal experience of a trip to India. The results point to three elaborations of the international: an optimistic view of a shared world, a geopolitical internationality and the production of a global corporeality.

Purpose: Significant structural changes are currently occurring in the Indian labour sector. Artificial intelligence (AI) and other emerging technologies are redefining the activities and skill requirements for various jobs in the healthcare sector. These adjustments have been accelerated by the economic crisis brought on by COVID-19, along with other considerations.

Need for the Study: Skills shortages, job transitions, and the deployment of AI at the company level are the three main challenges confronting the Indian labour market. This chapter aims to discuss policy alternatives to address a rising need for health workers and provide an overview of changes to the healthcare sector’s labour market.

Methodology: A review of the available literature was conducted to determine the causes of the widening skill gap despite a vibrant and prodigious young population. The background of the sustainable labour market is examined in this chapter, with a focus on workforce migration and mobility.

Findings: This chapter gives a comparative review of recent policy papers and evidence, as well as estimates of the health workforce and present Indian datasets. Furthermore, it highlights how important it is for all people concerned to invest in today’s workforce to close the skill gap and create better future opportunities.

Practical Implications: This chapter’s findings imply a severe shortage of human intellectual capital in India and a need to bridge this gap in the Indian labour market.

Corporate social responsibility (CSR) promotes society, reduces risk, and encourages ethical business practices. Due to its relevance, we study how CSR influences firms' sustainable development. We analyze data from 427 New York Stock Exchange (NYSE)-listed firms from 2008 to 2022. The Refinitiv environmental and social score is used to measure CSR, whereas for firms' sustainable development we rely on corporate sustainable growth rate (SGR) and market-based metrics. The analysis employs various econometric techniques, including ordinary least square, fixed effect regression, two-stage least square, generalized method of moment, and simultaneous quantile regression. The results indicate that CSR has a positive and significant effect on firms' sustainable development across all models. This relationship supports the notion that socially responsible business can contribute to long-term financial sustainability in line with “stakeholder theory”, indicating that companies should accommodate the concerns of various stakeholders, including society and the environment, to achieve sustainable development. We evaluate how the conditional distributions of SGR and firms’ value are affected by CSR, categorizing them into high, moderate, and low regimes. The quantile regression estimates indicate that the effect of CSR is more pronounced at upper quantiles, followed by moderate and low regimes. These findings underscore the importance of considering CSR in assessing the SGR and enterprises market value. We also confirm that our results are robust under range of different econometrics' methods. Finally, we enlighten current literature, and our research has useful policy implications for management and investors.