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Disruptive technologies are accelerating global growth. Artificial intelligence (AI) has the potential to transform the idea of delivering value to end users. On the other hand, the growth of Industry 5.0 has given rise to the concept of humanizing technology, and AI is a promising technology with the potential to contribute to business success. Nevertheless, the idea of value creation in the field of AI is novel, so it is necessary to define the meaning of value by understanding the context of AI applicability in different environments and industries. In this chapter, the author uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) procedure to conduct an SLR that provides interesting insights into the focus, industries, and methodologies and approaches used in existing research. Following the initial literature review on the state of the art of AI and value creation, the author also offers a reflection on the strategic implications of AI in the field of marketing, postulating a macrovalue creation framework that addresses the existence of implications on three different levels: emerging markets, Sustainable Development Goals, and adoption issues. Therefore, this chapter examines the value creation perspectives of AI to understand the current research focus and future directions.

Introduction: The Udaan Scheme was implemented in response to enduring conflict, economic downturn, and employment scarcity. Under the Rangarajan Committee, the scheme aimed to address unemployment in a selected region through skill development programmes. Based on practical experience, Udaan aimed to build a competitive workforce for India and the global economy.

Purpose: The purpose of the study is to evaluate the success ratio of the Udaan Scheme in addressing the employment challenges faced by the youth.

Need of the study: The chapter highlights the potential of the scheme to be a part of a resilient industry for job employability in politically disturbed areas.

Methodology: The compiled data were analysed using a spreadsheet collected from online sources, providing information on the number of registrations for the skill development programme between March 2012 and May 2018, that is, the programme’s implementation in the pre-UT era, mainly sourced from the Udaan Impact Assessment Report and the Review of the Udaan Scheme in Jammu and Kashmir (J&K).

Findings: The programme, which provided professional training and increased the job-securing capacity of youth, has had a dismal success rate despite the government’s investment of Rs 246 crore. The initiative has employed less than 10,000 individuals, or at most 10% of the target population, falling short of its claimed goals.

Significance of the study in the global market: The scheme addresses unemployment and career development for educated youth, enhancing India’s economic growth and global competitiveness. By providing skill development and exposure to the corporate sector, it empowers youth and attracts international business opportunities. It aligns with global efforts to bridge the skills gap and showcases India’s commitment to human capital development in a conflict-driven state.

The development of information technologies has led to a considerable transformation in human resource management from conventional or commonly known as personnel management to modern one. Data mining technology, which has been widely used in several applications, including those that function on the web, includes clustering algorithms as a key component. Web intelligence is a recent academic field that calls for sophisticated analytics and machine learning techniques to facilitate information discovery, particularly on the web. Human resource data gathered from the web are typically enormous, highly complex, dynamic, and unstructured. Traditional clustering methods need to be upgraded because they are ineffective. Standard clustering algorithms are enhanced and expanded with optimization capabilities to address this difficulty by swarm intelligence, a subset of nature-inspired computing. We collect the initial raw human resource data and preprocess the data wherein data cleaning, data normalization, and data integration takes place. The proposed K-C-means-data driven cuckoo bat optimization algorithm (KCM-DCBOA) is used for clustering of the human resource data. The feature extraction is done using principal component analysis (PCA) and the classification of human resource data is done using support vector machine (SVM). Other approaches from the literature were contrasted with the suggested approach. According to the experimental findings, the suggested technique has extremely promising features in terms of the quality of clustering and execution time.

To predict the future of the business and implement successful changes, a credit analyst must make quick decisions about the economics and assets of their clients. Because the marketplace is constantly changing, companies that lack the interpersonal skills necessary to communicate with their customers run the risk of falling behind the competition and becoming obsolete. The objective of this research was to assess whether credit analysts in Peruvian banks that used digital resources also improved their communication and interpersonal skills. The study was quantitative in nature, with an applied and correlational design that lacked an experimental component. The sample consisted of 109 credit analysts from four different Peruvian banks (Interbank, Scotiabank, BBVA, and BCP). Two questionnaires were used in this survey; both were submitted to expert review for validation before being submitted for use, and their reliability was determined using Cronbach's alpha. In terms of use of digital resources (59.5%) and mastery of interpersonal skills (61.3%), credit analysts were at the average. Conclusions the p-value for the correlation between credit analysts' use of digital resources and their soft skills in Peruvian banks was less than 0.05, indicating a direct and strong link between these two factors. The Rho correlation coefficient was 0.738.

The overall aim of this chapter is to focus on the process of, and issues warranting consideration for, the evaluation of educational interventions. In particular, to outline some key considerations for educators to follow when assessing the evidence-base for interventions they might be considering for use in their practice. Also, important considerations for those wishing to evaluate the effectiveness of an intervention they have initiated, as well as a useful checklist which summarises this all. Recognising that some readers of this chapter might be practitioners rather than researchers, it has been written with the practitioner in mind in, hopefully, a simple and practical way. There are, however, further opportunities for additional reading and resources signposted throughout for those who wish to read up on any of these areas more. In addition to those cited throughout and referenced in the Reference List at the end. There is also a section that provides the author’s Additional Recommended Readings and Resources to follow-up on. Readers might also want to refer to Chapter 3 in this book which discusses Single versus Multiple PPI approaches.

The current study aims to analyze the role of International Federation of Accountants (IFAC) in sustainability issues and its impact on the attitude of practitioners (auditors) in industrial companies. The current study relies on the analytical method, one of the tools of the inductive approach, by examining the literature of researchers, international and local organizations, publications, series, alerts, and topics dealt with by the IFAC, as well as reviewing studies, theoretical and applied research, periodicals, books, and statistics. And specialized publications for this subject, which is related to other sciences – such as – environmental science, economic, and political sciences. The study reached many results, the most important of which are: (1) The first half of the current decade has seen high interest from the IFAC, has led to the issuance of International Auditing and Assurance Standards Board (IAASB) international standard on assurance engagements 3410, (GHG) Statements. (2) Sustainability has become important to a growing number of enterprises, and may have a significant influence, in certain cases, the financial statements, also became the sustainability of the topics under increasing attention from users of financial statements. Thus, the financial statements will need a practitioner to take into consideration sustainability issues and a private greenhouse gas when auditing the financial statements. This study is distinguished by analyzing the role of the IFAC and the IAASB for the period from 1998 to 2023 regarding sustainability issues.

Exposing the hidden lives of female public relations (PR) practitioners requires deep connection with those lives. Stories need to be uncovered, interrogated, and ultimately told, to shine a light on the lived experiences of those working in PR. The methods used to collect these stories require deep immersion in the field and the ethnographic method is ideal for this. Ethnographic research methods have long been utilised to gain insights into the lived experiences of individuals and communities. This chapter provides an understanding of the strengths and limitations of ethnographic research methods in capturing the nuances of women's experiences of working in PR.

Organisational ethnography is an established field in business studies and has been used to investigate disciplines cognate to PR, including advertising and media, but, to date, has failed to be fully explored in PR research. This chapter examines the potential for ethnography to open new areas of PR theory and considers its potential as a means of bridging the gap between PR theory and practice.

Ethnography is not without its limitations; key concerns surround objectivity, the role of the researcher, and that of the participant, and ethics. Nonetheless, this method would appear to offer huge potential for the study of PR practices; the diverse nature of the sector makes it a rich area to study.

This chapter explores the potential of this method to offer an opportunity to investigate areas such as working practices, ethics in practice, power, gender, diversity, and culture.

Introduction: Cost competitiveness, customer focus, and sustainability compliance are essential for new-age firms to survive and succeed in the VUCA market environment. This study examines how automobile corporations have improved cost competitiveness, productivity, and product quality.

Purpose: This study examines the importance of cost competitiveness, customer focus, and sustainability compliance for the long-term survival of organisations in VUCA markets, looking at the practical efforts made by automobile corporations to enhance cost competitiveness, productivity, and quality.

Methodology: The study utilises a comprehensive analysis of the strategies and initiatives implemented by the selected automobile companies. It involves a review of relevant literature, case studies, financial data analysis, and interviews with key industry experts, providing a holistic understanding of the actions taken by these organisations to achieve their goals.

Findings: The study reveals that cost competitiveness, customer focus, and sustainability compliance are critical factors for the long-term survival and success of organisations in the automotive industry. The analysed automobile companies have undertaken practical efforts to improve cost competitiveness, enhance productivity, and ensure high-quality products, enabling them to navigate the challenges and maintain a competitive edge.

Significance: The findings of this study contribute to a deeper understanding of the importance of cost competitiveness, customer focus, and sustainability compliance in the automotive industry. It highlights the need for organisations to constantly monitor both qualitative and quantitative profit to avoid complacency and ensure long-term efficiency. The study’s insights are relevant to businesses operating in other sectors, as they face similar challenges in the VUCA market environment.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.