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This paper presents a realist evaluation of leadership within an integrated care system (ICS) in England. This paper aims to examine which aspects of leadership are effective, for whom, how and under what circumstances.

Realist evaluation methodology was used, adopting prior realist review findings as the theoretical framework to refine explanations of how and why leadership within an ICS is effective. Between January and November 2023, 23 interviews with ICS leaders took place, alongside 7 meeting observations and documentary analysis. The Realist And Metanarrative Evidence Syntheses: Evolving Standards (RAMESES) guidance informed the study design, conduct and reporting.

The findings highlight two overarching infrastructural contexts influencing leadership in ICSs: the impact of the post-COVID-19 pandemic legacy and the differences between health and social care regulatory and financial environments. Findings demonstrate that ICS leaders identified a strong sense of purpose as crucial for guiding decisions and creating a psychologically safe environment for open, honest discussions, fostering calculated risk-taking. Whilst a shared vision directed priority setting, financial pressures led to siloed thinking. Leadership visibility was linked to workforce morale, with supportive leadership boosting morale amidst evolving ICS landscapes and confidence in data-driven decisions supported prevention activities. However, financial constraints hindered responsiveness and innovation in addressing health inequalities.

By examining ICS leadership post-COVID-19 pandemic and amidst varying regulatory and financial environments, this study contributes to the emerging literature on systems leadership and offers practical guidance for leaders navigating the complexities of integrated care.

This research proposes a viable method of slab and shore load computation for the partial striking technique utilized in high-rise construction projects to optimize the use of horizontal formwork. The proposed Partial Striking Simplified Method (PSSM) is designed to be utilized by industry practitioners to schedule the construction operations of casting floors in order to control the formwork costs incurred throughout the completion of a project.

The article presents the PSSM for calculating slab and shore loads in multi-story building construction. It introduces the concept of “clearing before striking,” where shore supports are partially removed after a few days of pouring fresh concrete. The PSSM procedure is validated through numerical analysis and compared to other simplified approaches. Additionally, a user-friendly Python program based on the PSSM procedure is developed to explore the capability of the PSSM procedure and is used to study the variations in slab load, shoring level, concrete grade and cycle time.

The study successfully developed a more efficient and reliable method for estimating the loads on shores and slabs using partial striking techniques for multi-story building construction. Compared to other simplified approaches, the PSSM procedure is simpler and more precise, as demonstrated through numerical analysis. The mean of shore and slab load ratios are 1.08 and 1.07, respectively, which seems to have a slight standard deviation of 0.29 and 0.21 with 3D numerical analysis. The Python program developed for load estimation is effective in exploring the capability of the proposed PSSM procedure. The Python program's ability to identify the floor under maximum load and determine the specific construction stage provides valuable insights for multi-story construction, enabling informed decision-making and optimization of construction methods.

High-rise construction in Indian cities is booming, though this trend is not shared by all the country's major metropolitan areas. The growing construction sector in urban cities demands rapid construction for efficient utilization of formwork to control the construction costs of project. The proposed procedure is the best option to optimize the formwork construction cost, construction cycle time, the suitable formwork system with optimum cost, concrete grade for the adopted level of shoring in partaking and many more.

The proposed PSSM reduces the calculation complexity of the existing simplified method. This is done by considering the identical slab stiffness and identical shore layout for uniform load distribution throughout the structure. This procedure utilizes a two-step load distribution calculation for clearing phase. Initially, the 66% prop load of highest floor level is distributed uniformly over the lower interconnected slabs. In the second step, the total prop load is removed equally from all slabs below it. This makes the load distribution user-friendly for the industry expert.

The purpose of this research is to establish a robust numerical framework for the calibration of macroscopic constitutive parameters, based on the analysis of polycrystalline RVEs with computational homogenisation.

This framework is composed of four building-blocks: (1) the multi-scale model, consisting of polycrystalline RVEs, where the grains are modelled with anisotropic crystal plasticity, and computational homogenisation to link the scales, (2) a set of loading cases to generate the reference responses, (3) the von Mises elasto-plastic model to be calibrated, and (4) the optimisation algorithms to solve the inverse identification problem. Several optimisation algorithms are assessed through a reference identification problem. Thereafter, different calibration strategies are tested. The accuracy of the calibrated models is evaluated by comparing their results against an FE2 model and experimental data.

In the initial tests, the LIPO optimiser performs the best. Good results accuracy is obtained with the calibrated constitutive models. The computing time needed by the FE2 simulations is 5 orders of magnitude larger, compared to the standard macroscopic simulations, demonstrating how this framework is suitable to obtain efficient micro-mechanics-informed constitutive models.

This contribution proposes a numerical framework, based on FE2 and macro-scale single element simulations, where the calibration of constitutive laws is informed by multi-scale analysis. The most efficient combination of optimisation algorithm and definition of the objective function is studied, and the robustness of the proposed approach is demonstrated by validation with both numerical and experimental data.

Though anger as an emotion is an important determinant of negotiation outcomes, the extant literature presents mixed and contradictory findings. We propose that the effect of anger in intercultural negotiations depends on the power and personality orientation of the counterpart negotiators.

Based on data from 429 working professionals in the USA, we conducted two experimental studies in which they responded to an angry Chinese counterpart.

We find that the intercultural negotiation outcomes depend on the three-way interaction between anger, power and personality orientation. Our findings suggest that US action-oriented negotiators conceded more in a high-power condition than in a low-power condition while responding to an angry Chinese counterpart, while US state-oriented negotiators showed no difference in concession size regardless of their power and counterpart’s anger.

Our work is unique in establishing three-way interactive effects of power, personality and emotions in intercultural negotiation outcome relationships. Our findings are specific to an intercultural negotiation context consisting of negotiators from low-status, low-power-distance countries (e.g. the USA) with their counterparts from high-status, high-power-distance countries (e.g. China).

This paper aims to investigate the bond strength of metakaolin-based geopolymer mortar with cement mortar.

The mortar-mortar bond strength is assessed by slant shear and split tensile tests; pure shear strength is evaluated by Mohr’s criterion for result validation. Metakaolin-based geopolymer mortar is cast over the cured cement mortar specimen with two levels of surface roughness: smooth or grooved interface. The influence of the alkaline solution to metakaolin ratio on geopolymer bond strength is studied. Compressive strength, ultrasonic pulse velocity, permeability and flow table tests are also performed.

The paper’s findings are highlighted as follows: (1) strong mortar-mortar bond properties achieved for geopolymer mortar in all tests and conditions and validated by Mohr’s criterion and pure shear, (2) a lower alkaline solution to metakaolin ratio achieves higher bond strength to Portland cement mortar and (3) geopolymer mortar has higher compressive strength and ultrasonic pulse velocity than cement mortar at all curing ages; additionally, it is more flowable and less permeable.

The full replacement of Portland cement with metakaolin, a more sustainable cementitious material, will contribute to the decarbonization of the construction industry.

Limited research has been carried out on the bond strength of metakaolin-based geopolymer mortar to Portland cement mortar. Also, computing the pure shear using Mohr’s circle criterion of metakaolin-based geopolymer to validate the results can be considered original.

This study aims to empower cruise academia to assert their role as enablers, and potentially drivers, of sustainable, responsible and resilient cruise futures.

This contribution represents a synthesis and a critical reflection of cruise-related research-review literature over the last four decades, assessing its impact and potential in terms of influencing the evolution and future developments of cruise tourism.

Cruise research between the 1980s and the first decade of this century could be characterised as “ship-centric” and managerially focused. Over the last decade and up to the aftermath of the COVID-19 pandemic, cruise research has become increasingly “cruise-destination centric”, with sustainability emerging as a dominant theme. Diverging somewhat from the public and media emphasis on environmental concerns and risks, academic research tends to focus on the economic aspects of sustainability. Nonetheless, and despite aiming for practical relevance, cruise research tends to remain reactive and lags behind industry trends.

This paper proposes a shift from a “applied” to an “applicable” research paradigm, inspiring researchers to proactively shape the industry‘s future by embracing “what-ifs” in their thematic scope. Such a paradigm calls for a normativity-enriched methodological diversity, as well as the inclusion of transformational relevance as an indicator of research impact.

Public perceptions of cruise tourism have changed over the years, evolving from that of a promising holiday niche to a symbol of unsustainable mass tourism. In this context, cruise scholars are offered guidance for transcending the polarising debate of growth versus de-growth/limits while increasing the relevance and transformational impact of cruise scholarship.

这篇论文是对过去四十年来与邮轮旅游相关的研究评论文献的综述和批判性反思, 评估其在影响邮轮旅游的演变和未来发展方面的影响和潜力。

总体目标是增强邮轮学术界的能力, 使其能够在可持续、负责任和有弹性的邮轮未来发展中发挥促进者和潜在推动者的作用。

20 世纪 80 年代至本世纪头十年的邮轮研究可以说是 “以船为中心”, 以管理为重点。 在过去的十年中, 直到 COVID19 大流行之后, 邮轮研究越来越 “以邮轮目的地为中心”, 可持续发展成为主导主题。 与公众和媒体强调的环境问题和风险有些不同, 学术研究往往侧重于可持续发展的经济方面。 尽管如此, 邮轮研究尽管以实际相关性为目标, 但仍倾向于被动应对, 落后于行业发展趋。

本文提出了从 “应用 “研究范式向 “适用 “研究范式的转变, 激励研究人员通过在其主题范围内接受 “假设”, 积极塑造行业的未来。这种范式要求在方法上丰富规范性, 并将变革相关性作为衡量研究影响力的指标。

多年来, 公众对邮轮旅游的看法发生了变化, 从充满希望的度假小众旅游发展成为不可持续的大众旅游的象征。在此背景下, 为邮轮学者提供了指导, 以超越增长与去增长/限制的两极化争论, 同时提高邮轮学术研究的相关性和变革性影响。

Esta contribución representa una síntesis y una reflexión crítica de la literatura de investigación-revisión relacionada con los cruceros durante las últimas cuatro décadas, evaluando su impacto y potencial en términos de influencia sobre la evolución y futuros desarrollos del turismo de cruceros.

El objetivo general es capacitar al mundo académico de los cruceros para hacer valer su papel como facilitadores, y potencialmente impulsores, de futuros cruceros sostenibles, responsables y resilientes.

La investigación sobre cruceros entre los años 80 y la primera década de este siglo, podría caracterizarse como “centrada en el barco” y enfocada a la gestión. Durante la última década y hasta las secuelas de la pandemia de COVID19, la investigación sobre cruceros se ha vuelto cada vez más “centrada en los cruceros-destino”, con la sostenibilidad emergiendo como tema dominante. Apartándose un tanto del énfasis público y mediático en las preocupaciones y riesgos medioambientales, la investigación académica tiende a centrarse en los aspectos económicos de la sostenibilidad. No obstante, y a pesar de aspirar a la relevancia práctica, la investigación sobre cruceros tiende a seguir siendo reactiva y se queda rezagada con respecto a las tendencias del sector.

Este documento propone un cambio de un paradigma de investigación “aplicado” a otro “aplicable”, que inspire a los investigadores a configurar de forma proactiva el futuro de la industria, abarcando los “y si…” en su ámbito temático. Dicho paradigma exige una diversidad metodológica enriquecida por la normatividad, así como la inclusión de la relevancia transformadora como indicador del impacto de la investigación.

La percepción pública del turismo de cruceros ha cambiado a lo largo de los años, evolucionando desde la de un nicho vacacional prometedor a la de un símbolo del turismo de masas insostenible. En este contexto, se ofrece a los estudiosos de los cruceros una guía para trascender el polarizante debate de crecimiento frente a decrecimiento/límites, al tiempo que se aumenta la relevancia y el impacto transformador de los estudios sobre cruceros.

Formwork design and construction for reinforced concrete buildings take significant time, effort and money. Construction procedures are time-consuming for designers and costly for the contractor. Poor engineering decisions have led to several workplace accidents in the construction industry. This paper aims to present an integrated building information modeling – genetic algorithm (BIM-GA) model to automate formwork design, 3D visualization and optimization.

Data are precisely extracted from a 3D structural model and used to optimize formwork design based on available formwork components and prices. Optimization models are made using GA approach. A library of 3D formwork components was modeled and stored using Revit. The optimized design solution thereafter would be visualized automatically in Revit to readily acquire formwork quantities schedules and shop drawings.

A case study illustrating the proposed approach demonstrated that using BIM will reduce formwork design, quantification and drawing time by more than 50% of the traditional approach with safer design and accurate results due to process automation and optimize cost for the given data.

This research introduces an innovative integrated BIM and GA model for the optimization and automation of slab formwork design, which has significantly benefited the construction industry. The utilization of GA in the optimization process allows for the attainment of an optimal formwork design, ultimately leading to a reduction in construction cost and time.

This paper aims to find the best method to predict the friction coefficient of textured 45# steel by comparing different machine learning algorithms and analytical calculations.

Five machine learning algorithms, including K-nearest neighbor, random forest, support vector machine (SVM), gradient boosting decision tree (GBDT) and artificial neural network (ANN), are applied to predict friction coefficient of textured 45# steel surface under oil lubrication. The superiority of machine learning is verified by comparing it with analytical calculations and experimental results.

The results show that machine learning methods can accurately predict friction coefficient between interfaces compared to analytical calculations, in which SVM, GBDT and ANN methods show close prediction performance. When texture and working parameters both change, sliding speed plays the most important role, indicating that working parameters have more significant influence on friction coefficient than texture parameters.

This study can reduce the experimental cost and time of textured 45# steel, and provide a reference for the widespread application of machine learning in the friction field in the future.

The purpose of this paper is to examine failures in internal and external controls associated with sovereign wealth funds (SWFs), using three caselets to illustrate the fraud triangle theory factors.

This study uses a qualitative research approach. Caselets are used to illustrate the fraud triangle factors associated with SWFs.

Ideally, SWFs would be characterized by opacity and the strategic flexibility to advance political goals, but this operational agility facilitates an environment ripe for fraud, in large part because there is little transparency with regard to their regulatory structure. Elements of the fraud triangle inherent in the structure of SWFs contribute to the fraud found in the three case examples.

The authors use three SWF fraud cases rather than statistical sampling of all SWFs, which limits the generalizability of the findings. Future research should explore additional recommendations for the evaluation of SWF governance.

The overlap between public sector governance and SWF governance creates an environment amenable to fraud, and as a result, fraud has occurred in several SWFs. Governance recommendations should take into account the lessons learned from previous SWF fraud cases.

Ideally, SWFs would be characterized by opacity and the strategic flexibility to advance political goals, but this operational agility may also facilitate an environment ripe for fraud, in large part because there is little transparency with regard to their regulatory structure.

To the best of the authors’ knowledge, this paper is the first to identify the fraud triangle risk factors associated with sovereign wealth funds using SWF fraud caselets.

Data-driven models are increasingly being used to predict the fatigue life of many engineering components exposed to multiaxial loading. However, owing to their high data requirements, they are cost-prohibitive and underperforming for application scenarios with limited data. Therefore, it is essential to develop an advanced model with good applicability to small-sample problems for multiaxial fatigue life assessment.

Drawing inspiration from the modeling strategy of empirical multiaxial fatigue models, a modular neural network-based model is proposed with assembly of three sub-networks in series: the first two sub-networks undergo pretraining using uniaxial fatigue data and are then connected to a third sub-network trained on a few multiaxial fatigue data. Moreover, general material properties and necessary loading parameters are used as inputs in place of explicit damage parameters, ensuring the universality of the proposed model.

Based on extensive experimental evaluations, it is demonstrated that the proposed model outperforms empirical models and conventional data-driven models in terms of prediction accuracy and data demand. It also holds good transferability across various multiaxial loading cases.

The proposed model explores a new avenue to incorporate uniaxial fatigue data into the data-driven modeling of multiaxial fatigue life, which can reduce the data requirement under the promise of maintaining good prediction accuracy.