Search results

The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

Clinically, it is often observed that autistic people may have a heightened need for rules and may find rule violations very distressing. It is clinically plausible that autistic individuals may be prone to hyper-morality and greater reactivity and adverse experiences arising from moral threats and violations. Such adverse experiences may, in some instances, lead to moral distress (MD) or in more extreme cases moral injury. Thus, this study aims to examine how MD can operate in the context of autism.

The authors explore clinical hypotheses on how MD can intersect with different features of autism by drawing on clinical and research knowledge of autism spectrum disorder and how it contextualises experiences of morality.

Based on a review of the literature and theory, the authors hypothesise that autistic individuals may be more prone to MD where they have a lower threshold for MD. As a result of this lower threshold, they may have more frequent exposure to MD, experience more immediate and intense subjective reactions to moral transgressions, for more protracted periods. Also, they may find it more difficult to over-ride and neutralise moral outrage. As a result, they may be more susceptible to mental health sequelae and impaired social and occupational functioning. Practical recommendations are made for clinicians supporting people with autism with a propensity for MD or moral injury, to improve their quality of life.

Practical recommendations are made for clinicians supporting people with autism with a propensity for MD or moral injury, to improve their quality of life.

Understanding MD in an autistic context is important for detecting and treating the adverse impacts of MD on autistic individuals. Importantly, erroneous preconceptions about moral reasoning in autism need to be mitigated to fully understand the moral experiences and harness the many strengths of people with autism.

This study employs Stein Rokkan's methodological approach to analyse state formation in the Greater Middle East. It develops a conceptual framework distinguishing colonial, populist and democratic pacts, suitable for analysis of state formation and nation-building through to the present period. The framework relies on historical institutionalism. The methodology, however, is Rokkan's. The initial conceptual analysis also specifies differences between European and the Middle Eastern state formation processes. It is followed by a brief and selective discussion of historical preconditions. Next, the method of plotting singular cases into conceptual-typological maps is applied to 20 cases in the Greater Middle East (including Afghanistan, Iran and Turkey). For reasons of space, the empirical analysis is limited to the colonial period (1870s to the end of World War 1). Three typologies are combined into one conceptual-typological map of this period. The vertical left-hand axis provides a composite typology that clarifies cultural-territorial preconditions. The horizontal axis specifies transformations of the region's agrarian class structures since the mid-19th century reforms. The right-hand vertical axis provides a four-layered typology of processes of external intervention. A final section presents selected comparative case reconstructions. To the authors' knowledge, this is the first time such a Rokkan-style conceptual-typological map has been constructed for a non-European region.

While most West European nations were formed around pre-existing entities that could be called “countries” before the modern age, this was not the case in the Middle East. Some entities, like Egypt, did have a clear political and cultural identity before colonialism, others, like Algeria, did not. This chapter discusses the four states of the Maghreb: Morocco, Algeria, Tunisia and Libya, through the perspective of “country creation” going into and coming out of colonial rule. We can see here two “models” of fairly similar types of historical development, one showing a gradual process through a protectorate period to relatively stable modern nations, another through violent conquest and direct colonization ending in violent liberation and military and wealthy but fragile states. The article asks whether these models for the history of country creation and the presence or absence of pre-colonial identities can help explain the modern history and nature of these states in the Arab Spring and the years thereafter. Then, a more tentative attempt is made to apply these models to two countries of the Arab east, Syria and Iraq. While local variations ensure that no model can be transferred directly, it can show the importance of studying the historical factors that go into the transition from geographical region to a country with people that can form the basis of a nation.

This whistleblowing case study engages students in discussions about when and how to disclose differences of opinion on a revenue recognition matter with higher-ups in an organization. Factors to consider include the morality of whistleblowing, confidentiality obligations, the rules of conduct in the American Institute of Certified Public Accountants (AICPA) Code, Sarbanes–Oxley Act (SOX), Dodd–Frank, and the US Supreme Court ruling in Digital Realty, Inc. v. Somers that addresses when to report matters to the Securities and Exchange Commission (SEC). Case questions are designed to promote students’ critical thinking skills, ethical reasoning skills, and decision-making. A flowchart of AICPA ethics rule 2.130.020 (Subordination of Judgment) provides the framework for making decisions when differences exist in financial reporting. The case provides learning objectives, implementation guidance, and teaching notes. The case was used in an accounting ethics course taught at the undergraduate senior level but can also be used in auditing, fraud examination, and advanced financial reporting courses.

Warranty-based big data analysis has attracted a great deal of attention because of its key capabilities and role in improving product quality while minimizing costs. Information and details about particular parts (components) repair and replacement during the warranty term, usually stored in the after-sales service database, can be used to solve problems in a variety of sectors. Due to the small number of studies related to the complete analysis of parts failure patterns in the automotive industry in the literature, this paper focuses on discovering and assessing the impact of lesser-studied factors on the failure of auto parts in the warranty period from the after-sales data of an automotive manufacturer.

The interconnected method used in this study for analyzing failure patterns is formed by combining association rules (AR) mining and Bayesian networks (BNs).

This research utilized AR analysis to extract valuable information from warranty data, exploring the relationship between component failure, time and location. Additionally, BNs were employed to investigate other potential factors influencing component failure, which could not be identified using Association Rules alone. This approach provided a more comprehensive evaluation of the data and valuable insights for decision-making in relevant industries.

This study's findings are believed to be practical in achieving a better dissection and providing a comprehensive package that can be utilized to increase component quality and overcome cross-sectional solutions. The integration of these methods allowed for a wider exploration of potential factors influencing component failure, enhancing the validity and depth of the research findings.

This study investigates the individual and binary (i.e. combined) effects of institutional dimensions of open government data (which include instructional, structural and accessible rules) on scientific research innovation, as well as the mediating roles that researchers' perceived data usefulness and data capability play in between.

Based on a sample of 1,092 respondents, this study uses partial least squares structural equation modeling (PLS-SEM) and polynomial regression with response surface analysis to evaluate the direct and indirect effects of individual and binary institutional dimensions on scientific research innovation.

The findings demonstrate that instructional, structural and restricted access data have a positive effect on scientific research innovation in the individual effect. While the binary effect of institutional dimensions produces varying degrees of scientific research innovation. Furthermore, this study discovers that the perceived usefulness and data capability of researchers differ in the mediating effect of institutional dimensions on scientific research innovation.

Theoretically, this study contributes new knowledge on the causal links between data publication institutions and innovation. Practically, the research findings offer government data managers timely suggestions on how to build up institutions to foster greater data usage.

The main purpose of our study is to investigate the impact of daily leader humor behaviors on healthcare workers’ daily psychological state and behavioral outcomes.

Based on the conservation of resources (COR) theory, this study proposes that daily leader humor behaviors are positively related to healthcare workers’ daily positive affect, which in turn affects their next-day helping behaviors towards patients. These predictions hinge on healthcare workers’ difficulty in maintaining display rules. We conducted a lagged experience sampling methodology (ESM) survey of 621 complete daily observations from 93 healthcare workers who work in direct contact with patients at a large public hospital in China across consecutive 10 working days.

Results of multilevel path analysis demonstrate that daily leader humor behaviors are positively related to healthcare workers’ same-day positive affect, and this positive affect enhances their next-day helping behaviors towards patients. Furthermore, healthcare workers’ higher difficulty in maintaining display rules attenuates the benefits of daily leader humor behaviors.

Building on the COR theory and adopting a diary research design, this study shows daily fluctuations in leader humor behaviors and proposes a mechanism through which daily leader humor behaviors indirectly affect healthcare workers’ next-day helping behaviors. Thus, our study disclosed possible means for healthcare organizations to improve service quality.

This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.

The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.

Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.

An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.