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This paper aims to contribute to the analysis concerning how inflation forecasts from different economic agents (professional forecasters and consumers) lead to varying levels of central bank credibility and how it affects the monetary policy interest rate and its expectations.

Based on the Brazilian economy data from June 2007 to May 2022, the authors provide evidence that is useful for search mechanisms that improve the conduct of monetary policy through the management of inflation expectations. The authors perform several ordinary least squares and generalized method of moments regressions inspired by the Taylor rule principle. In brief, the benchmark model considers that the monetary policy interest rate and its expectations respond to departures of inflation expectations to the target (a proxy for central bank credibility) and the level of economic activity.

The main result of the analysis is that inflation expectations from professional forecasters and consumers imply different perceptions of central bank credibility that affect the monetary policy interest rate and expectations for horizons until one year ahead.

The novelty that the authors bring from the analysis is that the authors calculate central bank credibility by taking into account the “public beliefs” of different economic agents. Furthermore, the authors analyze the effect of central bank credibility from professional forecasters and consumers on the monetary policy interest rate and its expectations.

First-line leaders across the emergency services are instrumental in leading the development of a workforce fit to face current and future challenges. As such in addition to utilising their specific craft, leaders need to be equipped to understand and apply evidence-based practices. With a focus on first-line leadership in policing, this paper will have both national and international resonance for those organisations attempting to embed an evidence-based culture.

The paper utilises a review of literature to develop a viewpoint identifying challenges and benefits of the adoption of evidence-based policing (EBP) by first-line leaders.

First-line leaders, whether police officers, police staff or volunteers, require opportunities to develop their own knowledge, understanding and skills of applying EBP in the workplace. Acknowledging challenges exist in the widespread adoption of EBP, such learning, at the appropriate educational level, will enable leaders to effectively champion the adoption of EBP, informing both their own decision-making and professional practices as well as those across their teams.

The first-line leader role is highly influential, as such, it is essential that these leaders develop their knowledge, understanding and application of EBP in the workplace in order to lead the expected cultural change.

This paper provides a current framework for the understanding of the context and potential impact of educationally levelled formal leadership learning required to champion the broad adoption of EBP across policing.

This paper aims to examine the Canadian financial sector’s reaction to opportunities and risks created by the green bond market in a low-carbon and climate-resilient (LCR) economy.

The authors used a concurrent mixed methodological approach that undertakes an online survey and semistructured interviews with critical green bond market stakeholders.

The most significant market driver in Canada is the reputational benefit for stakeholders, i.e. its ability to meet the high demand for sustainable finance and the marketing potential of its green credentials. The major market barriers are transactional costs, i.e. additional tracking required for reporting purposes, lack of market liquidity and identification of environmental impact or additionality. Canadian green bonds are also more likely to be evaluated on their green impact than their global market peers.

Limitations of this study include its focus on Canada, which may exclude or not apply to drivers and barriers in other green bond markets.

The paper helps create an accounting-based conceptual framework for key motivations and barriers that affect financial decision-making regarding green bonds.

The authors identify economic and policy-related barriers and drivers for green bonds, addressing the financing gap for the LCR economy.

To the best of the authors’ knowledge, this study is the first to identify and compare Canadian green bond market drivers and barriers and to examine relevant stakeholder- and policy-related approaches that can be targeted to scale this market effectively.

This paper aims to develop a comprehensive model on intra- and interpersonal emotion regulation (ER) in hospitality and tourism (H&T) service encounters.

A critical review and reflection of ER research from multiple disciplines was conducted. Methodologies appropriate for investigating ER were also reviewed.

A comprehensive framework was proposed to outline key influential factors, processes and consequences of intra- and interpersonal ER in service encounters in the H&T industry. Methodologies integrating advanced tools were suggested to measure complex and dynamic emotion generation and regulation processes in social interactions from a multimodal perspective.

The researchers developed a comprehensive conceptual model on both intra- and interpersonal ER based on a critical review of the most recent psychological research on ER. Various theoretical and methodological considerations are discussed, offering H&T scholars a solid starting point to explore dynamic emotion generation and regulation processes in complex social settings. Moreover, the model provides future directions for the expansion of ER theories, which have been mostly developed and tested based on laboratory research.

The proposed model addresses two critical issues identified in emotion research in the H&T field: the lack of a dynamic perspective and the neglect of the social nature of emotions. Moreover, the model provides a roadmap for future research.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

To ensure the motion attitude and stable contact force of massage robot working on unknown human tissue environment, this study aims to propose a robotic system for autonomous massage path planning and stable interaction control.

First, back region extraction and acupoint recognition based on deep learning is proposed, which provides a basis for determining the working area and path points of the robot. Second, to realize the standard approach and movement trajectory of the expert massage, 3D reconstruction and path planning of the massage area are performed, and normal vectors are calculated to control the normal orientation of robot-end. Finally, to cope with the soft and hard changes of human tissue state and body movement, an adaptive force tracking control strategy is presented to compensate the uncertainty of environmental position and tissue hardness online.

Improved network model can accomplish the acupoint recognition task with a large accuracy and integrate the point cloud to generate massage trajectories adapted to the shape of the human body. Experimental results show that the adaptive force tracking control can obtain a relatively smooth force, and the error is basically within ± 0.2 N during the online experiment.

This paper incorporates deep learning, 3D reconstruction and impedance control, the robot can understand the shape features of the massage area and adapt its planning massage path to carry out a stable and safe force tracking control during dynamic robot–human contact.

The rise of cryptocurrencies and other digital assets has triggered concerns about regulation and security. Governments and regulatory bodies are challenged to create frameworks that protect consumers, combat money laundering and address risks linked to digital assets. Conventional approaches to confiscation and anti-money laundering are deemed insufficient in this evolving landscape. The absence of a central authority and the use of encryption hinder the identification of asset owners and the tracking of illicit activities. Moreover, the international and cross-border nature of digital assets complicates matters, demanding global coordination. The purpose of this study is to highlight that the effective combat of money laundering, legislative action, innovative investigative techniques and public–private partnerships are crucial.

The focal point of this paper is Australia’s approach to law enforcement in the realm of digital assets. It underscores the pivotal role of robust confiscation mechanisms in disrupting criminal networks operating through digital means. The paper firmly asserts that staying ahead of the curve and maintaining an agile stance is paramount. Criminals are quick to embrace emerging technologies, necessitating proactive measures from policymakers and law enforcement agencies.

It is argued that an agile and comprehensive approach is vital in countering money laundering, as criminals adapt to new technologies. Policymakers and law enforcement agencies must remain proactively ahead of these developments to efficiently identify, trace and seize digital assets involved in illicit activities, thereby safeguarding the integrity of the global financial system.

This paper provides a distinctive perspective by examining Australia’s legal anti-money laundering and counterterrorism financing framework, along with its law enforcement strategies within the realm of the digital asset landscape. While there is a plethora of literature on both asset confiscation and digital assets, there is a noticeable absence of exploration into their interplay, especially within the Australian context.

People donate to charities with the aim of improving society. Yet, many charities fail to use donations efficiently or have ineffective interventions. The authors explore the strategic operational priorities and processes that enable charities to efficiently implement their interventions and have a positive impact on society.

The authors first review the literature on charities to gain a deeper understanding of the current state of knowledge on charity operations. The authors then employ the lens of paradox theory and perform a qualitative investigation of six case studies to explore various aspects of the operations of charities that are known for being cost-effective.

The authors reveal how the strategic operational decisions of charities, as well as the processes they implement, help them resolve the tensions arising from the cost-effectiveness paradox. The authors show that cost-effective charities make strategic operational decisions that help maintain two diverging priorities: prioritizing the status quo and prioritizing change in how they deliver value. Another set of strategic decisions helps balance these two diverging priorities. The authors then show how these charities create and then maintain cost-effective operations.

The authors address recent calls for research on non-profit organizations in the field of operations management. To authors’ knowledge, it is the first in-depth study of exemplary charity operations. The results can be used by charity executives as a benchmarking tool when they develop and implement their charitable interventions and by government agencies and potential donors when they select charities for their donations. Finally, the results should have implications for other organizations trying to have a positive societal impact.

This study aims to analyse how the adoption of Industry 4.0 technologies can help different types of agri-food supply chains introduce and manage innovations in response to the challenges and opportunities that emerged following the COVID-19 pandemic.

A systematic literature review methodology was used to bring together the most relevant contributions from different disciplines and provide comprehensive results on the use of I4.0 technologies in the agri-food industry.

Four technological clusters are identified, which group together the I4.0 technologies based on the applications in the agri-food industry, the objectives and the advantages provided. In addition, three types of agri-food supply chains have been identified and their configuration and dynamics have been studied. Finally, the I4.0 technologies most suited for each type of supply chain have been identified, and suggestions on how to effectively introduce and manage innovations at different levels of the supply chain are provided.

The study highlights how the effective adoption of I4.0 technologies in the agri-food industry depends on the characteristics of the supply chains. Technologies can be used for different purposes and managers should carefully consider the objectives to be achieved and the synergies between technologies and supply chain dynamics.