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The purpose of this paper is to improve the problem of kinematics incompatibility of human–exoskeleton in the existing rigid lower-limb exoskeleton (LLE).

In this paper, following an introduction, the motion characteristics of the human knee joint and the design method of the exoskeleton were introduced. A kinematics model of the LLE based on cross-four-bar linkage was obtained. The structural parameters of the LLE mechanism were optimized by the particle swarm optimization algorithm. The predefined trajectories used in the optimization process were derived from the ankle joint, not the instantaneous center of rotation of the knee joint. Finally, the motion deviation of the optimization result was simulated, and the human–exoskeleton coordination experiment was designed to compare with the traditional single-axis knee joint in terms of comfort and coordination.

The lower limb exoskeleton mechanism obtained in this paper has a good tracking effect on human movement and has been improved in terms of comfort and coordination compared with the traditional single-axis knee joint.

The customized exoskeleton design method introduced in this paper is relatively simple, and the obtained exoskeleton has better movement coordination than the traditional exoskeleton. It can provide a reference for the design of lower limb exoskeleton and lower limb orthosis.

Digital twins provide enormous opportunities for smart buildings. However, an up-to-date intellectual landscape to understand and identify the major opportunities of digital twins for smart buildings is still not enough. This study, therefore, performs an up-to-date comprehensive literature review to identify the major opportunities of digital twins for smart buildings.

Scientometric and content analysis are utilised to comprehensively evaluate the intellectual landscape of the general knowledge of digital twins for smart buildings.

The study uncovered 24 opportunities that were further categorised into four major opportunities: efficient building performance (smart “building” environment), efficient building process (smart construction site environment), information efficiency and effective user interactions. The study further identified the limitations of the existing studies and made recommendations for future research in the methodology adopted and the research domain. Five research domains were considered for future research, namely “real-time data acquisition, processing and storage”, “security and privacy issues”, “standardised and domain modelling”, “collaboration between the building industry and the digital twin developers” and “skilled workforce to enable a seamless transition from theory to practice”.

All stakeholders, including practitioners, policymakers and researchers in the field of “architecture, engineering, construction and operations” (AECO), may benefit from the findings of this study by gaining an in-depth understanding of the opportunities of digital twins and their implementation in smart buildings in the AECO industry. The limitations and the possible research directions may serve as guidelines for streamlining the practical adoption and implementation of digital twins for smart buildings.

This study adopted scientometric and content analysis to comprehensively assess the intellectual landscape of relevant literature and identify four major opportunities of digital twins for smart building, to which scholars have given limited attention. Finally, a research direction framework is presented to address the identified limitations of existing studies and help envision the ideal state of digital twins for smart buildings.

This study scrutinised Shanghai junior high school teachers’ emotions and emotion management strategies in relation to teachers’ work settings and content. A mixed-methods approach was applied to collect data via field observations, interviews, and a quantitative survey. The aim of this study was two-fold. Firstly, it aimed to identify the typical work settings in which teachers experienced work-related emotions. Secondly, it aimed to reveal teachers’ priority work in school and how it affected teachers’ choices of emotion management strategies.

The data were analysed through the lens of emotional labour theories and professional agency theories. Findings showed that classroom teaching and the professional learning community activities were two typical settings in which the teachers experienced the most intensive emotions. Most Shanghai teachers managed their momentary emotions by either genuinely expressing their emotions that matched their roles and the scenario, or by purposely suppressing emotions to meet social and organisational expectations. Furthermore, most teachers adopted the long-term mood regulation strategy by aligning their emotions with long-term goal achievement in the future. As professional agents, the Shanghai teachers did not only manage their own emotions at work using these two strategies, but also managed students’ emotions as part of the moral education.

The study employs two independent experimental studies to collect data. It focuses on the matching effect between advertising appeals and product types. The Elaboration Likelihood Model serves as the theoretical framework for understanding the cognitive processing involved in consumers' responses to these advertising appeals and product combinations.

This paper aims to investigate the impact of advertising appeals on consumers' intentions to purchase organic food. We explored the interaction between advertising appeals (egoistic vs altruistic) and product types (virtue vs vice) and purchase intention. The goal is to provide insights that can enhance the advertising effectiveness of organic food manufacturers and retailers.

The analysis reveals significant effects on consumers' purchase intentions based on the matching of advertising appeals with product types. Specifically, when egoistic appeals align with virtuous products, there is an improvement in consumers' purchase intentions. When altruistic appeals match vice products, a positive impact on purchase intention is observed. The results suggest that the matching of advertising appeals with product types enhances processing fluency, contributing to increased purchase intention.

This research contributes to the field by providing nuanced insights into the interplay between advertising appeals and product types within the context of organic food. The findings highlight the importance of considering the synergy between egoistic appeals and virtuous products, as well as altruistic appeals and vice products. This understanding can be strategically employed by organic food manufacturers and retailers to optimize their advertising strategies, thereby improving their overall effectiveness in influencing consumers' purchase intentions.

This study explores the influence of female executives on the misalignment between corporate ESG commitments and practices, a phenomenon known as ESG decoupling. It also enhances the understanding of female power on affecting ESG decoupling under different ownership settings.

This study uses a quantitative research design to explore the impact mechanism of female executives’ proportion on corporate ESG decoupling under different ownership contexts based on a sample of 2,585 firm-year observations from publicly traded Chinese companies between 2011 and 2021.

Based on agency theory, upper echelons theory and gender socialization theory, our findings indicate that (1) female executives are significantly effective in reducing ESG decoupling, and (2) this effect is more pronounced in non-state-owned enterprises (non-SOEs) compared to state-owned enterprises (SOEs).

This study contributes original insights into the ESG decoupling literature by demonstrating the external influences of corporate governance structure, particularly in the context of China’s unique corporate ownership environment. It also provides strong social implications by highlighting the role of gender dynamics in corporate governance, corporate social responsibility (CSR) behaviors and ESG alignment.

Over the past two decades, building information modeling (BIM) has been promoted as one of the most disruptive innovations across the global architecture, engineering and construction (AEC) community. Nevertheless, despite its widely propagated benefits, BIM adoption in various localities is not progressing excitingly. BIM as an innovation developed from a presumed, general context may not fit well with the specific regulatory, social and cultural settings of a locality. This study aims to tackle the lukewarm local BIM adoption by developing a deployment framework for BIM localization.

Drawing upon the diffusion of innovation (DoI) theory, a longitudinal case study is designed and conducted by engaging closely with a top cost consultancy company in Hong Kong for forty-one months.

The findings refuted the “one-size-fits-for-all” view to use a standardized BIM for international users. Rather, an organization needs to undergo a series of localization works to integrate global BIM in its specific local context. The deployment framework outlines the BIM dimensions (i.e. technology, process and protocol) and the mechanisms (i.e. configuration, coupling and reinterpretation) of BIM localization that go through the three “A”s (i.e. analysis, adaption and assimilation) process under a firm's network and contextual factors.

This study improves our understanding of sluggish BIM adoption by attributing it to the gap between general BIM development and the local, unique BIM use context. Proposing the deployment framework, the study also offers a handy tool for prospective executives to localize BIM and harness its power in their respective organizations and localities.

The purpose of this paper is to develop a new conceptual life cycle performance measurement system (PMS) based on stage level key performance indicators (KPIs) to measure the performance of build–operate–transfer (BOT) projects.

This study uses a literature review to reveal the deficiencies of existing PMSs for public–private partnership (PPP) projects. Based on these deficiencies, four recommendations were proposed for developing a PMS. The validation of these recommendations was performed via focus group discussion sessions conducted with 12 experts. Then, a conceptual framework was developed based on the validated recommendations and the additional recommendations emerged during focus group discussions. Finally, the recommendations proposed by the focus group were tested by a questionnaire survey, the findings of the Friedman test and descriptive analysis validated these recommendations.

Findings of the focus group discussion, Friedman test and descriptive analysis indicated that the PMS should have four crucial features to develop an efficient, effective and comprehensible PMS for the BOT project. Firstly, non-financial and financial KPIs should be integrated. Secondly, the PMS should be developed as a process-based system with stage level KPIs. The performance of the BOT projects should be monitored and reviewed continuously, however the most important KPIs should be used for continuous performance measurement to increase the applicability of the system and allocate the resources more efficiently.

This survey was conducted on experts who have experience with BOT projects located in Turkey, therefore, judgments of experts might be affected by external factors specific to Turkey such as geopolitical situations, investment environment. However, due to the nature of BOT projects, the experience of experts can also be utilized at the international level.

This is the first time a PMS has been developed to measure the performance of a BOT project. In addition, this system has unique features when compared with the PMS proposed in the literature. Especially, the stage level KPIs and continuous performance measurement with the most important KPIs throughout each stage has never been used. This research provides both public sector and private entities with an insight into effectively measure, control and manage their BOT infrastructure projects' performances throughout their life cycles.

In recent decades, interest in digital transformation (DX) within the architecture, engineering, and construction (AEC) industry has significantly increased. Despite the existence of several literature reviews on DX research, there remains a notable lack of systematic quantitative and visual investigations into the structure and evolution of this field. This study aims to address this gap by uncovering the current state, key topics, keywords, and emerging areas in DX research specific to the AEC sector.

Employing a holistic review approach, this study undertook a thorough and systematic analysis of the literature concerning DX in the AEC industry. Utilizing a bibliometric analysis, 3,656 papers were retrieved from the Web of Science spanning the years 1990–2023. A scientometric analysis was then applied to these publications to discern patterns in publication years, geographical distribution, journals, authors, citations, and keywords.

The findings identify China, the USA, and England as the leading contributors in the field of DX in AEC sector. Prominent keywords include “building information modeling”, “design”, “system”, “framework”, “adoption”, “model”, “safety”, “internet of things”, and “innovation”. Emerging areas of interest are “deep learning”, “embodied energy”, and “machine learning”. A cluster analysis of keywords reveals key research themes such as “deep learning”, “smart buildings”, “virtual reality”, “augmented reality”, “smart contracts”, “sustainable development”, “building information modeling”, “big data”, and “3D printing”.

This study is among the earliest to provide a comprehensive scientometric mapping of the DX field. The findings presented here have significant implications for both industry practitioners and the scientific community, offering a thorough overview of the current state, prominent keywords, topics, and emerging areas within DX in the AEC industry. Additionally, this research serves as an invaluable reference and guideline for scholars interested in this subject.