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The purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is based on P-wave earthquake early-warning and multiple ways of rapid treatment.

The paper describes the key technologies that are involved in the development of the system, such as P-wave identification and earthquake early-warning, multi-source seismic information fusion and earthquake emergency treatment technologies. The paper also presents the test results of the system, which show that it has complete functions and its major performance indicators meet the design requirements.

The study demonstrates that the high speed railways earthquake early-warning system serves as an important technical tool for high speed railways to cope with the threat of earthquake to the operation safety. The key technical indicators of the system have excellent performance: The first report time of the P-wave is less than three seconds. From the first arrival of P-wave to the beginning of train braking, the total delay of onboard emergency treatment is 3.63 seconds under 95% probability. The average total delay for power failures triggered by substations is 3.3 seconds.

The paper provides a valuable reference for the research and development of earthquake early-warning system for high speed railways in other countries and regions. It also contributes to the earthquake prevention and disaster reduction efforts.

Despite the widespread use and application of resilience, much uncertainty about the conceptualization and operationalization in the context of tourism destinations still exists. The purpose of this paper is to provide a conceptual elaboration on destination resilience and to introduce a model for an improved understanding of the concept.

Taking a conceptual research approach, this paper seeks to untangle the fuzziness surrounding the destination and resilience concept by providing a new interpretation that synthesizes theories and concepts from various academic disciplines. It analyses the current debate to derive theoretic baselines and conceptual elements that subsequently inform the development of a new “Destination Resilience Model”.

The contribution advances the debate by proposing three key themes for future resilience conceptualizations: (1) the value of an actor-centered and agency-based resilience perspective; (2) the importance of the dynamic nature of resilience and the (mis)use of measurement approaches; (3) the adoption of a dualistic resilience perspective distinguishing specified and general resilience. Building on these propositions, we introduce a conceptual model that innovatively links elements central to the concepts of destination and risk and combines different narratives of resilience.

The contribution advances the debate surrounding destination resilience by critically examining the conceptualization and operationalization of destination resilience within previous research and by subsequently proposing a “Destination Resilience Model” that picks up central element of the three new frontiers identified in the conceptually driven review. The innovative integration strengthens the comprehension of the resilience concept at destination level and supports building future capacities to manage immediate adverse impacts as well as novel and systemic risks.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.

In this case study, we examine how a citrus peel valorising company based in the Netherlands was able to adopt a circular business model while navigating regulatory, managerial, and supply chain-related barriers.

In-depth, semi-structured interviews with key personnel in the company, notes from field observations, photographs of the production process, and documents from a legal judgement served as data for this single, qualitative case study. Data were coded inductively using the in vivo technique and were further developed into four themes and a case description.

Results from our study indicate that the regulatory and political contexts in the Netherlands were critical to the company’s success. Like in the case of most fruitful industrial symbioses, partnerships founded on mutual trust and economically appealing value propositions played a crucial role in ensuring commercial viability. Collaborating with larger corporations and maintaining transparent communication with stakeholders were also significant contributing factors. Lastly, employees’ outlook towards circularity combined with their willingness to learn new skills were important driving factors as well.

In addition to expanding the scholarship on the adoption of circular business models, this research offers novel insights to policymakers and practitioners. It provides empirical evidence regarding the importance of public awareness, adaptable legislation, and harmonised policy goals for supporting sustainable entrepreneurship in the circular economy.

This paper aims to identify and report the differential effects of activity control and capability control on role stressors, which subsequently affect salespeople’s job satisfaction and sales performance.

Drawing on job demands-resources (JD-R) theory, the authors defined active control and customer demandingness as the job demands and capability control as the job resource, and designed their relationship with role stressors, which are indicated as role ambiguity, role conflict and role overload. The authors enrolled a sample of 223 industrial salespeople from pharmaceutical companies. After collecting the data, the authors used structural equation modeling using AMOS to test and estimate causal relationships along with a two-step approach to examine the interaction effect. The authors have also tested the simple slope of two-way interactions. All of the measured variables were identical to those used in previous studies.

The study findings indicate that behavior-based control can be counterproductive. Reducing activity control can decrease role stress, increase job satisfaction and improve job performance; increasing capability control, however, can reduce role stress and increase job satisfaction and performance. It is also important to acknowledge the external environment of the sales context in which behavior-based control is most effective: whereas high customer demandingness and capability control are related to reduced role stress, high customer demandingness and activity control are related to increased role stress.

Sales managers should recognize that different control management regimes reinforce or mitigate salespeople’s job stressors and outcomes under specific conditions (i.e. work environments marked by higher or lower customer demandingness).

Drawing on JD-R theory, the research shows that a behavior control (i.e. activity control and capability control) has differential, and even opposite, psychological consequences.

This study seeks to examine the relationship between macroeconomic shock indicators, namely geopolitical risk (GPR), global economic policy uncertainty (GEPU) and financial stress (FS), and returns as well as volatilities on seven carefully selected stock markets in Africa. Specifically, the study intends to unravel the co-movement and interdependence between the respective macroeconomic shock indicators and each of the stock markets under consideration across time and frequency.

This study employed wavelet coherence approach to examine the strength and stability of the relationships across different time scales and frequency components, thereby providing valuable insights into specific periods and frequency ranges where the relationships are particularly pronounced.

The study found that GEPU, Financial Stress (FS) and GPR failed to induce significant influence on African stock market returns in the short term (0–4 months band), but tend to intensify in the long-term band (after 6th month). On the contrary, stock market volatilities exhibited strong coherence and interdependence with GEPU, FSI and GPR in the short-term band.

This study happens to be the first of its kind to comprehensively consider how the aforementioned macro-economic shock indicators impact stock markets returns and volatilities over time and frequency. Further, none of the earlier studies has attempted to examine the relationship between macro-economic shocks, stock returns and volatilities in different crisis periods. This study is the first of its kind in to employ data spanning from May 2007 to April 2023, thereby covering notable crisis periods such as global financial crisis (GFC) and the COVID-19 pandemic episodes.

The literature on public procurement (PP) has increased significantly in recent years, and, to date, several reviews have been conducted to study this relevant subject. Nevertheless, a bibliometric analysis of the PP knowledge domain is still missing. To fill this knowledge gap, a bibliometric review is carried out to investigate the current state of PP research.

A total of 640 journal articles are selected from the Scopus database for the final analysis. The performance indicators of the literature are identified and explained through bibliometric analysis. Furthermore, the conceptual and intellectual structures are studied through a keyword co-occurrence network and bibliographic coupling.

The results of the review indicate that PP research has increased significantly in recent years. The top ten most productive journals, countries, authors and academic institutions are identified. The findings from the keyword co-occurrence network reveal six main research themes including innovation, corruption and green public procurement (GPP). By applying bibliographic coupling, the focus of PP research revolves around seven thematic areas: GPP, corruption, the role of small and medium-sized enterprises (SMEs) in PP, electronic PP, innovation, labour standards and service acquisition. The research potential of each thematic area is evaluated using a model based on maturity and recent attention (RA).

To the best of the authors' knowledge, this is the first study to successfully organise, synthesise and quantitatively analyse the development of the PP domain amongst a large number of publications on a large time scale.

This research aims to explore whether or how organizations adopt people analytics (PA), its value and potential socio-technical factors that can enable or hinder PA projects by disrupting and reshaping human resource management. We do this by focusing on the Italian context.

We conduct a scoping review of data collected between 2018 and 2022 via Google Alerts (GA), a content change detection and notification service that is gaining popularity in scholarly research.

Our findings suggest that the diffusion of PA applications in Italy, especially those of a descriptive nature, is growing. Most of the existing PA applications are positioned in a positive technocratic light, envisioning the value of PA for both employees and organizations. The value for the latter appears to be direct, while the value for employees is realized through organizational initiatives. The findings also suggest that while enablers can vary between PA application types, the barriers, especially technological and environmental, are generic for both descriptive and predictive/prescriptive PA applications.

Theoretically, we propose a framework for analyzing PA applications, their values, enablers and barriers. Methodologically, we present and describe in detail a novel approach, drawing on GA that can be used to study PA in specific contexts. Practically, our study serves as a helpful point of reference for managers planning or implementing PA in Italy, for benchmarking PA in Italy over time and for comparative international studies.

This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.

The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.

The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.

Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.

There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.