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During the COVID-19 pandemic, lockdowns were implemented to achieve two goals: (1) to reduce the number of COVID-19 cases and (2) to reduce the number of COVID-19 deaths. In this paper, the authors aim to look at empirical evidence on how effectively lockdowns achieved these goals among small island developing states (SIDS) and for one specific SIDS economy, Guam.

The authors reviewed existing studies to form two hypotheses: that lockdowns reduced cases, and that lockdowns reduced deaths. Defining a lockdown as a positive value for Oxford COVID-19 government response tracker, OxCGRT's stringency index, the authors tested the above hypotheses on 185 countries, 27 SIDS economies and Guam using correlation and regression analyses, and using different measures of the strictness, duration and timing of the lockdown.

The authors found no evidence to support the hypothesis that lockdowns reduced the number of cases based on data for all 185 countries and 27 SIDS economies. While the authors found evidence to support the hypothesis in the case of Guam, the result required an unrealistically and implausibly long time lag of 365 days. As to the second hypothesis that lockdowns reduced the number of deaths, the authors found no evidence to support it for 185 countries, 27 SIDS economies as well as Guam.

From the review of the existing literature, the authors are the first to conduct this type of study among SIDS economies as a group and on Guam.

Secure mental health services in one UK region have acted within a network to develop a range of involvement practices. A new quality benchmarking tool has been created to appraise the implementation of these involvement practices. The purpose of this paper is to report upon a qualitative evaluation of this development.

Staff and service users involved in the co-production of the benchmarking tool were engaged in a series of focus groups and participatory inquiry approaches enacted in the course of scheduled network meetings. Data thus collected was subject to thematic analysis.

Four distinct themes were identified which were titled: Taking time, taking care; The value not the label; An instrument of the network; and All people working together. These are discussed in relation to recent theorising of co-production.

Effectively, this study represents a case study of developments within one region. As such, the findings may have limited transferability to other contexts.

Staff and service users can work together effectively to the benefit of each other and overall forensic services. The benchmarking tool provides a readymade mechanism to appraise quality improvements.

Despite a prevailing culture of competition in wider health-care policy, cooperation leads to enhanced quality.

The benchmarking tool is a unique development of a longstanding involvement network, demonstrating the positive implications for enacting co-production within secure services.

The Chinese government hopes to achieve the goal of benefiting citizens by building a National Integrated Online Government Service Platform (NIOGSP). However, citizens' low adoption of the platform makes it difficult for the government to achieve its goal. Research on the influencing factors of citizen adoption of NIOGSP can help the government fully understand the concerns and needs of its citizens and take targeted measures to increase citizen adoption.

First, this research builds a model of the citizen adoption process, including attention, retention and motivation, based on an observational learning model. Next, research variables are determined based on social cognitive theory, literature review and real-world needs. Finally, based on the questionnaire survey and structural equation model, the influencing factors of each stage of the citizen adoption process model are studied and the relationship between the three stages of the model is verified.

Results show that perceived usefulness (PU) and self-efficacy (SE) positively affect attention. SE positively affects retention, while perceived privacy (PP) negatively affects retention. PU, social influence, PP and anxiety positively affect motivation.

The conclusion of this study can provide reference for governments in various countries to establish and improve online one-stop government. In addition, this study verifies the citizen adoption process model and finds that there is no obvious causal relationship between attention and retention, but both have positive effects on motivation.

From May 2024, Victoria (Australia) will mandatorily raise the minimum house energy rating standards from 6 to 7 stars. However, the latest data shows that only 5.73% of new Victorian houses were designed beyond 7-star. While previous literature indicates the issue’s link to the compliance behaviour of building practitioners in the design phase, the underlying behavioural determinants are rarely explored. This study thus preliminarily examines building practitioners’ compliance behaviour with 7-star Australian house energy ratings and beyond.

Using a widely-applied method to initially examine an under-explored phenomenon, eight expert interviews were conducted with building practitioners, a state-level industry regulator and a leading national building energy policy researcher. The study triangulated the data with government-led research reports.

The experts indicate that most building practitioners involved in mainstream volume projects do not go for 7 stars, mainly due to perceived compliance costs and reliance on standardized designs. In contrast, those who work on custom projects are more willing to go beyond 7-star mostly due to the moral norms for a low-carbon environment. The experts further agree that four behavioural determinants (attitudes towards compliance, subjective norms, perceived behavioural control and personal norms) co-shape building practitioners’ compliance behaviour. Interventions targeting these behavioural determinants are recommended for achieving 7 stars and beyond.

This study demonstrates the behavioural determinants that influence building practitioners’ compliance decisions, and offers insight regarding how far they will go to meet 7 stars. It can facilitate the transition to 7 stars by informing policymakers of customized interventions to trigger behaviour change.

The recent outbreak of Coronavirus disease has caused significant disruptions around the world. The global pandemic severely affects the education sector. However, amid the crisis, educators are resilient and resourceful and develop innovative ideas and learning designs to engage the students as much as possible. Educators in the special and inclusive education sector face more challenges due to the nature of students. The effective use of technology and mindset are the keys to success in this endeavour. This chapter discusses the institutional policies, good practices and practical ideas to overcome the difficulties in inclusive and special education students.

Significant progress towards the provision of a more equitable and inclusive education system in Ireland has been made in recent years. Through an interrogation of the research that has influenced changes in national policy and practices, this chapter includes a discussion of associated literature, which addresses national inclusive education priorities in Ireland. Building upon a method for reviewing the literature applied in Ireland as part of a major longitudinal study (Rose et al., 2010), a discussion of the current situation is presented in relation to progress towards the Education for All Goals and key issues for further scrutiny are proposed.

This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.

This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.

There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.

The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.

The purpose of this study is to explore the economic impact of financial restatements by major customers on the audit opinion of their suppliers, showing that non-financial information disclosure potentially helps auditors make better assessments.

Using a sample of China’s listed firms from 2007 to 2021, the authors aim to find the relationship between customers’ financial restatements and their suppliers’ audit opinions. Heckman selection model, placebo tests and other robustness checks are used as well.

The findings reveal that customers’ financial restatements have a significant effect on the likelihood of suppliers receiving modified audit opinions. This relationship is pronounced when suppliers face a higher level of financial constraints, exhibit poorer accounting conservatism or receive more negative media coverage. Additionally, this effect occurs through increased business risk and information risk, which heightens auditors’ perceived audit risk. Moreover, the study highlights the influence of switching costs, auditor expertise and restatement severity on this relationship.

Risks originating from customers can spread along the supply chain, emphasizing the necessity for auditors to give heightened attention to both the audited firms and their customer information. Moreover, regulators should carefully consider the important impact of customer information disclosures to maximize the protection of the interests of external information users.

This study not only confirms the crucial role of customer information disclosures in annual reports for stakeholders and auditors but also contributes to the existing literature on customer–supplier relationships.

Significant progress towards the provision of a more equitable and inclusive education system in Ireland has been made in recent years. National policy initiatives have been supported by the implementation of new assessment and resourcing models and procedures that aim to ensure appropriate support of children described as having special educational needs. A focus upon teacher training and professional development and consideration of education in the post-compulsory years have resulted in changes aimed at improving access and quality of services. This chapter through an interrogation of the research that has influenced changes in national policy and practices, and a scrutiny of associated literature, discusses both the successes achieved towards addressing national inclusive education priorities, and those areas which remain a challenge and in need of further investigation. Building upon a method for reviewing the literature developed by the authors and applied in Ireland as part of a major longitudinal study (Rose, Shevlin, Winter, & O'Raw, 2010) a discussion of the current situation is presented in relation to progress towards the Education for All Goals and key issues for further scrutiny are proposed.

The current study has drawn attention to investigating the impact of social media influencers’ (SMIs) authenticity on followers buying behavior by using followers who have an ongoing relationship with an influencer and are knowledgeable about the influencer. The study further intends to reveal the mediating effect of parasocial interaction on the relationship between SMI's authenticity and followers' purchase behavior.

The study has analyzed data from an online survey of 458 participants (Instagram followers) using structured equation modeling (CB-SEM) to investigate the relationship among authenticity attributes, parasocial interaction and followers' purchase behavior.

CB-SEM results reveal that authenticity attributes positively influence followers' buying behavior. The findings from mediation analysis specify that parasocial interaction mediates the relationship between authenticity attributes (sincerity, truthful endorsement and visibility) and buying behavior excluding expertise, uniqueness attributes.

The findings of the study reinforce the need to use authentic influencers by the marketers for the brand endorsements. Further, the findings of the study can benefit marketers in implementing strategic practice of social media influencer marketing.

The study overcomes the limitations of preceding studies by using Instagram followers who are well-informed about SMIs and have an ongoing relationship with them. This study has uniquely combined the behavioral data from real influencer campaigns with followers' assessment of an influencer's authenticity.