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There is continual evidence of ineffective e-Learning programmes that are set amid emerging information and communication technology (ICT) tools by higher education (HE) providers. While many of the existing accounts outline the potential of integrating such educational technology into their teaching and learning practice, other studies point out the adoption challenges of such programmes. This chapter tackles this dilemma in two respects. Firstly, through an examination of the limitations surrounding the instructional systems design (ISD) models while urging the need for empirical evidence and ratification processes to substantiate these models as they relate to online instructional environments. Secondly, through the investigation of the effectiveness offered by ICT tools under different instructional environments in order to facilitate the effective application of e-Learning. Field evaluation in the form of a series of 2×3 factorial quasi-experiments was conducted at four higher education institutions in Saudi Arabia. The empirical results confirm the validity of the ISD model and reliably captured its effects in improving learners’ performance under three instructional delivery modes. The empirical evidence reveals the extent of effectiveness of the proposed prescriptive ISD model enabling an improved design of ICT-based HE instructional strategies. On a managerial level, the findings facilitate the delivery mode decision making by HE providers in terms of the congruence of technology integration under each of the three learning experiences. The calibrated assessment measures provide a discussion to extend the practical implication of the current e-Pedagogical practice in the e-Learning industry.

As avatars are increasingly becoming popular, both scholars and businesses are acknowledging the vast potential that avatars hold for the future. Despite this growing interest in avatars, no review articles have attempted to provide a comprehensive overview of avatar literature and its implications for consumers. The present review addresses this gap using the combination of descriptive analysis (for corpus performance), bibliometric analysis (for corpus performance and emerging themes), and thematic analysis (for emerging themes and implications as well as future research opportunities). We conducted a review of 47 Scopus-indexed articles from 34 journals between year 2006 and 2023. By examining the corpus performance of avatar literature, the emerging themes, and future research opportunities, this review offers scholars a comprehensive overview of the subject matter.

Purpose: This chapter aims to perform text analysis to investigate the academic area delimitated by economic and financial performance and money laundering.

Need for the study: The findings contribute to the body of literature by providing important insights in terms of money laundering and financial performance.

Methodology: In order to achieve the research objective, further than 640 papers were retrieved from the Web of Science from 1994 to 2022, concentrating on the most referenced documents found in the superior quartile.

Findings: The empirical findings emphasise that the article with the unique words Fraud Detection System: A Survey by Abdallah A., Maarof M. A., and Zainal A., examines a complete and systematic assessment of the concerns and obstacles that impede the performance of fraud detection systems. Furthermore, topic modelling findings highlighted the presence of four main topics: topic 1 – identified by ‘performance’, ‘firms’, ‘financial’, ‘fraud’, and ‘board’; topic 2 – described in terms of ‘fraud’, ‘accounting’, ‘evidence’, ‘audit’, and ‘research’; topic 3 – identified by ‘firms’, ‘fraud’, ‘financial’, ‘CEO’, and ‘results’ while topic 4 – identified through ‘fraud’, ‘detection’, ‘data’, ‘cost’, and ‘card’.

Practical implications: This study will act as a guide for researchers of the financial performance field to explore the scientific publications in the field of money laudering.

Purpose of paper – This paper sets out to introduce the special issue on corporate governance in less developed and emerging economies. It summarises and reflects on themes and findings raised in the papers in the volume.

Design/methodology/approach – The findings reported in the paper are based on desk research and review of the papers contained in the volume.

Findings – The paper finds that the adoption of appropriate corporate governance systems is becoming a central issue in less developed and emerging economies. Factors such as the 1997 Asian financial crisis, the adoption of international donor led reforms, and the globalisation of capital markets are among the factors that are driving corporate governance reforms in less developed and emerging economies.

Research limitations/implications – The pressure from international donors has compelled some less developed and emerging economies to adopt corporate governance models developed in the West with no modification. The paper argues that while it is imperative for less developed and emerging economies to reform their corporate governance systems, it is important that these systems are adapted to suite the specific needs of individual countries.

Originality/value of paper – The paper is a summary of studies exploring various corporate governance issues in less developed and emerging economies. The issues addressed in these studies are important to understand corporate governance issues in both the private and public sectors in less developed and emerging economies.

Introduction: The Internet has tremendously transformed the computer and networking world. Information reaches our fingertips and adds data to our repository within a second. Big data was initially defined as three Vs, where data come with greater variety, increasing volumes and extra velocity. Big data is a collection of structured, unstructured and semi-structured data gathered from different sources and applications. It has become the most powerful buzzword in almost all the business sectors. The real success of any industry can be counted based on how the big data is analysed, potential knowledge is discovered and productive business decisions are made. New technologies such as artificial intelligence and machine learning have added more efficiency to storing and analysing data. This big data analytics (BDA) becomes more valuable to those companies, focusing on getting insight into customer behaviour, trends and patterns. This popularity of big data has inspired insurance companies to utilise big data at their core systems and advance the financial operations, improve customer service, construct a personalised environment and take all possible measures to increase revenue and profits.

Purpose: This study aims to recognise what big data stands for in the insurance sector and how the application of BDA has opened the door for new and innovative changes in the insurance industry.

Methodology: This study describes the field of BDA in the insurance sector, discusses the benefits, outlines tools, architectural framework, the method, describes applications in general and specific and briefly discusses the opportunities and challenges.

Findings: The study concludes that BDA in insurance is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however, there remain challenges to overcome.

Section 529 college savings plans are tax-favored investment vehicles, which saw tremendous growth after the Economic Growth and Tax Relief Reconciliation Act of 2001 expanded 529 plan benefits to include tax-free distributions for qualified higher education expenses. However, regulators, the press, and fund advisors criticized the Section 529 college savings plan industry for inadequate and nonuniform disclosures of investor information, such as historical returns, fees, taxes, and underlying investments. We investigate consumers’ investment choices after a disclosure regime change in 2003 and find that after enhanced disclosures became widely available, investors selected fewer plans offered exclusively through brokers, increasingly chose portfolios based on past investment performance, but remained unresponsive to state tax benefit disclosures. We also analyze the plans’ performance and find evidence that 529 investors are constrained to invest in portfolios with high, return-eroding fees. Nearly 20 percent of the portfolios have a statistically significant negative alpha, the measure of risk-adjusted excess return, while less than 1 percent have a statistically significant positive alpha.

Road user charging has been proposed as a solution to the uncontrolled growth of traffic and congestion in urban areas. In the absence of evidence from real world applications, modelling techniques provide the best information about the potential impacts and benefits of different charging approaches. This research has employed an elastic demand network equilibrium model, as part of the well established SATURN suite of computer programs, to represent a series of alternative road user charging systems which have been proposed for practical application.

Results have been obtained for both the impacts of charges on the volume and spatial distribution of road travel demand and for aggregate measures of network performance, such as travel distances, times and costs. Some interesting issues have emerged regarding the overall performance of charging systems in comparison with prior expectations and the specific impacts of charges related to travel conditions, which attempt to approximate the economic theories of marginal cost pricing. In addition, doubts are raised regarding the ability of steady-state equilibrium models to provide plausible representations of behavioural responses to charges which may vary significantly in time and space. It is suggested that alternative modelling techniques may provide superior user response predictions.

Online teaching particularly through Open Distance and e-Learning (ODeL) has become a phenomenon in the twenty-first century. ODeL and blended approaches inevitably lead to increasing dependence on electronic communication systems. The University of South Africa (Unisa), where the author teaches, enables students through its Learner Management System to interact with lecturers and e-tutors online. The responsibilities of e-tutors are of an educative and technical nature. Their roles include guiding and assisting students, encouraging active participation, responding to their queries and grading their assignments. In addition, e-tutors provide notifications and assign tasks or activities that students are expected to complete and submit. In several cases, these forms of assistance are absent, when there is a lack of follow-up within the response period which is 24 hours – missing notifications and lack of guidance – rendering these e-tutors ineffective. The chapter provides strategies that were analyzed and implemented to motivate effective tutoring and enhance student participation learning. The author draws on her analysis as a virtual ethnographer and long-term participant observer as an e-tutor and lecturer who supervised e-tutors and taught a large number of students – 2,500. The objective of the chapter is to encourage effective tutoring that can enhance students’ success.

This chapter examines organizational and instructional responses of California's high schools to the introduction of a High School Exit Examination through interviews with 47 high school principals across the state. I found that most schools changed little about their organizational structure, and provided little support for students until after they failed the exam. Findings also indicate that the exit exam influenced the curriculum most significantly in low-performing schools and in low-track classes within higher performing schools. While the exit exam spurred some positive changes, it also led to unintended consequences inside classrooms.