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1 – 10 of 15The issue of energy efficiency is becoming increasingly prevalent globally due to factors such as the expansion of the population, economic growth and excessive consumption that…
Abstract
Purpose
The issue of energy efficiency is becoming increasingly prevalent globally due to factors such as the expansion of the population, economic growth and excessive consumption that is not sustainable in the long run. Additionally, healthcare facilities and hospitals are facing challenges as their operational costs continue to rise. The research aim is to develop strategic frameworks for managing green hospitals, towards energy efficiency and corporate governance in hospitals and healthcare facilities.
Design/methodology/approach
This research employs a qualitative case study approach, with a sample of ten hospitals examined through interviews with senior management, executives and healthcare facilities managers. Relevant data was also collected from literature and analysed through critical appraisal and content analysis. The research methodology is based on the use of grounded theory research methodologies to build theories from case studies.
Findings
The research developed three integrated conceptual strategic frameworks for managing hospitals and healthcare facilities towards energy efficiency, green hospital initiatives and corporate governance. The research also outlined the concepts of green hospitals and energy efficiency management systems and best practices based on the conclusions drawn from the investigated case studies.
Research limitations/implications
The study is limited to the initiatives and experiences of the healthcare facilities studied in the Middle East and North Africa (MENA) region.
Originality/value
The research findings, conclusions, recommendations and proposed frameworks and concepts contribute significantly to the existing body of knowledge. This research also provides recommendations for hospital managers and policymakers on how to effectively implement and manage energy efficiency initiatives in healthcare facilities.
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Kai Hänninen, Jouni Juntunen and Harri Haapasalo
The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive…
Abstract
Purpose
The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.
Design/methodology/approach
Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.
Findings
Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.
Research limitations/implications
The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.
Practical implications
This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.
Originality/value
This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.
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Classification of remote sensing images (RSI) is a challenging task in computer vision. Recently, researchers have proposed a variety of creative methods for automatic recognition…
Abstract
Purpose
Classification of remote sensing images (RSI) is a challenging task in computer vision. Recently, researchers have proposed a variety of creative methods for automatic recognition of RSI, and feature fusion is a research hotspot for its great potential to boost performance. However, RSI has a unique imaging condition and cluttered scenes with complicated backgrounds. This larger difference from nature images has made the previous feature fusion methods present insignificant performance improvements.
Design/methodology/approach
This work proposed a two-convolutional neural network (CNN) fusion method named main and branch CNN fusion network (MBC-Net) as an improved solution for classifying RSI. In detail, the MBC-Net employs an EfficientNet-B3 as its main CNN stream and an EfficientNet-B0 as a branch, named MC-B3 and BC-B0, respectively. In particular, MBC-Net includes a long-range derivation (LRD) module, which is specially designed to learn the dependence of different features. Meanwhile, MBC-Net also uses some unique ideas to tackle the problems coming from the two-CNN fusion and the inherent nature of RSI.
Findings
Extensive experiments on three RSI sets prove that MBC-Net outperforms the other 38 state-of-the-art (STOA) methods published from 2020 to 2023, with a noticeable increase in overall accuracy (OA) values. MBC-Net not only presents a 0.7% increased OA value on the most confusing NWPU set but also has 62% fewer parameters compared to the leading approach that ranks first in the literature.
Originality/value
MBC-Net is a more effective and efficient feature fusion approach compared to other STOA methods in the literature. Given the visualizations of grad class activation mapping (Grad-CAM), it reveals that MBC-Net can learn the long-range dependence of features that a single CNN cannot. Based on the tendency stochastic neighbor embedding (t-SNE) results, it demonstrates that the feature representation of MBC-Net is more effective than other methods. In addition, the ablation tests indicate that MBC-Net is effective and efficient for fusing features from two CNNs.
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Yufang Cheng, Meng-Han Lee, Chung-Sung Yang and Pei-Yu Wu
The purpose of this study was to develop the augmented reality (AR) educational program combined with the instructional guidance for supportive learning, which enhanced the…
Abstract
Purpose
The purpose of this study was to develop the augmented reality (AR) educational program combined with the instructional guidance for supportive learning, which enhanced the thinking process cooperative discussion and problem-solving skills in chemistry subject.
Design/methodology/approach
The method used the quasi-experimental research design. Of the 45 students who attended this experiment, only 25 with low achievement qualified in operating the AR learning system of saponification and transesterification environment (ARLS-STE) system.
Findings
These results confirmed that the AR educational program could have increased substantial benefits in improvements of students’ knowledge and the ability of the thinking process for the participants with the lowest score. In semi-structured interviews, most of participants enjoyed manipulating the ARLS-STE system, which was realistic, motived and interesting for learning science subjects.
Originality/value
The low-achieving students have often been known with a low learning capability, and they lack in developing constructional knowledge, despite being keen for learning. Regarding educational concerns for this population, providing orientated learning and supportive materials could increase their learning effects. Virtual worlds are an efficient learning tool in educational setting. The AR can offer visual concepts and physical interaction for students with low achievement in learning. Thus, this study investigates the acceptability of an educational program designed in the ARLS-STE, which involves the learning effects of academic knowledge and the capability of thinking process for students with low achievement. The ARLS-STE system was developed for this proposal, based upon the marker-based AR technologies combined with hands-on manipulation.
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Asli Pelin Gurgun, Kerim Koc and Handan Kunkcu
Completing construction projects within the planned schedule has widely been considered as one of the major project success factors. This study investigates the use of…
Abstract
Purpose
Completing construction projects within the planned schedule has widely been considered as one of the major project success factors. This study investigates the use of technologies to address delays in construction projects and aims to address three research questions (1) to identify the adopted technologies and proposed solutions in the literature, (2) to explore the reasons why the delays cannot be prevented despite disruptive technologies and (3) to determine the major strategies to prevent delays in construction projects.
Design/methodology/approach
In total, 208 research articles that used innovative technologies, methods, or tools to avoid delays in construction projects were investigated by conducting a comprehensive literature review. An elaborative content analysis was performed to cover the implemented technologies and their transformation, highlighted research fields in relation to selected technologies, focused delay causes and corresponding delay mitigation strategies and emphasized project types with specific delay causes. According to the analysis results, a typological framework with appropriate technological means was proposed.
Findings
The findings revealed that several tools such as planning, imaging, geo-spatial data collection, machine learning and optimization have widely been adopted to address specific delay causes. It was also observed that strategies to address various delay causes throughout the life cycle of construction projects have been overlooked in the literature. The findings of the present research underpin the trends and technological advances to address significant delay causes.
Originality/value
Despite the technological advancements in the digitalization era of Industry 4.0, many construction projects still suffer from poor schedule performance. However, the reason of this is questionable and has not been investigated thoroughly.
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Junping Qiu, Qinze Mi, Zhongyang Xu, Tingyong Zhang and Tao Zhou
Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to…
Abstract
Purpose
Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.
Design/methodology/approach
We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.
Findings
The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.
Originality/value
Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.
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Yingjie Ju, Jianliang Yang, Jingping Ma and Yuehang Hou
The objective of this study is to explore the impact of a government-supported initiative for operational security, specifically the establishment of the national security…
Abstract
Purpose
The objective of this study is to explore the impact of a government-supported initiative for operational security, specifically the establishment of the national security emergency industry demonstration base, on the profitability of local publicly traded companies. Additionally, the study investigates the significance of firms' blockchain strategies and technologies within this framework.
Design/methodology/approach
Using the differences-in-differences (DID) approach, this study evaluates the impact of China's national security emergency industry demonstration bases (2015–2022) on the profitability of local firms. Data from the China Research Data Service (CNRDS) platform and investor Q&As informed our analysis of firms' blockchain strategy and technology, underpinned by detailed data collection and a robust DID model.
Findings
Emergency industry demonstration bases have notably boosted enterprise profitability in both return on assets (ROA) and return on equity (ROE). Companies adopting blockchain strategies and operational technology see a clear rise in profitability over non-blockchain peers. Additionally, the technical operation of blockchain presents a more pronounced advantage than at the strategic level.
Originality/value
We introduced a new perspective, emphasizing the enhancement of corporate operational safety and financial performance through the pathway of emergency industry policies, driven by the collaboration between government and businesses. Furthermore, we delved into the potential application value of blockchain strategies and technologies in enhancing operational security and the emergency industry.
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Nam Bui, Christoph Merschbrock and Bjørn Erik Munkvold
This paper aims to explore how open innovation communities contribute to the adoption of building information modelling (BIM) in the construction industry.
Abstract
Purpose
This paper aims to explore how open innovation communities contribute to the adoption of building information modelling (BIM) in the construction industry.
Design/methodology/approach
The paper presents a cross-case analysis of two construction communities, buildingSMART Norway and the BIM Vietnam Community. Data were collected based on 21 semi-structured interviews conducted with industry experts actively engaged in these two communities. The theoretical basis for the study was open innovation and the institutional intervention model, which delineates institutional actions related to the adoption of new information technology.
Findings
The findings show both similarities and differences in the way in which the communities contribute to industrial practice. Both communities use similar knowledge channels and repositories but apply different approaches to innovation creation and diffusion. In addition, trust can support BIM innovation in the community context.
Originality/value
The comparison of buildingSMART Norway and the BIM Vietnam Community in accelerating BIM innovation allows for exploring how open innovation communities support BIM adoption in the construction industry. The findings provide insights for construction communities into creating and diffusing BIM innovation. In addition, the examples of gaining benefits from community innovation activities are useful for construction firms and practitioners.
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Toritseju Begho and Shuainan Liu
People often look to the opinions and actions of others to guide their food choices, especially when they are uncertain or unfamiliar with a particular food. This influence can be…
Abstract
Purpose
People often look to the opinions and actions of others to guide their food choices, especially when they are uncertain or unfamiliar with a particular food. This influence can be positive or negative depending on the context and can have an impact on food consumption and health outcomes.
Design/methodology/approach
The paper analysed data from 500 young adult consumers in China and employed a multi-study design to examine various aspects of social proof and herd behaviour in food choices. Experiment 1 examined the influence of testimonials from an influential person on buying decisions and eating behaviour. Experiment 2 explored whether herd behaviour drives food options. Experiment 3 assessed the influence of social proof on food choices. Chi-square tests of independence were conducted to examine the relationship between social proof and food choice, as well as herd behaviour and food decision-making. Several logit regression analyses were performed to identify the factors that drive consumers' susceptibility to social proof and herding.
Findings
The results indicated that the source of feedback, whether from an influential person or a family member, did not have a statistically significant effect on the likelihood of following the food guide recommendations. The preference for a healthier food option was stronger than following the herd. In contrast, social proof in the form of reviews and ratings influenced participants' choices. The paper highlights the usefulness for stakeholders and policymakers seeking to promote healthier eating habits.
Originality/value
The originality lies in its comprehensive approach, combining multiple experiments and analytical methods.
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