Integrating LINE BOT and Building Information Model to develop construction information management system

In the lifecycle of construction projects, the participation of various specialized members often leads to challenges in recording or retrieving information in real time. This can result in missing data or inaccurate project control decisions, due to the inability to access essential information swiftly and accurately. Recognizing the ubiquitous use of instant messaging platforms on mobile phones and the widespread adoption of Building Information Modeling (BIM) for information storage and management, this research proposes an innovative integration of chatbots with BIM to establish a robust construction information management system. Utilizing “LINE”, a popular communication software, as the foundation, this study develops four specialized chatbots (LINE BOTs) tailored for different phases of construction projects, namely design, construction, and maintenance. These chatbots employ a rule-based and conversational approach to aid construction personnel in real-time recording and retrieval of project information. During the maintenance phase, users can also access relevant equipment objects through the BIM model using mobile smart devices, further improving maintenance efficiency. Moreover, the chatbots are equipped with a string-matching mechanism to enhance the precision of data recording and retrieval processes. The effectiveness of this system is demonstrated through a case study on a public construction project

Decision-making of corporate clients during strategic briefing process according to knowledge acquisition types

Organizational clients with limited experience in strategic briefing often face challenges in identifying building project outcomes for achieving a competitive edge in their business. Communication with practitioners during strategic briefing facilitates clients in acknowledging the importance of timely decision-making and being involved in a knowledge spiral to acquire the information. Knowledge-acquisition by clients can lead to behavioral changes, both within themselves and their organizations. This study classifies knowledge-acquisition types (KATs) and investigates the potential for rational decision-making in briefings. A framework, developed through a literature review and practical insights, is validated by introducing the Action Research approach with stakeholders across ten building projects in sectors: manufacturing, retail, and public enterprises. The framework, refined during interactions among researchers, clients and service providers, identifies KAT1 as the domain knowledge, KAT2 as the administrative knowledge, and KAT3 is the facility knowledge of clients. KAT4, the difference between groups with and without construction-project experiences, relates to the procedures for achieving strategic objectives. This involves understanding the project and organizational characteristics through knowledge accumulation and managing client interactions to ensure successful projects. The Action Research framework facilitates knowledge exchange among clients and practitioners, empowering corporate clients to effectively achieve strategic objectives through group decision-making

Fixed point approximation of contractive-like mappings using a stable iterative family and its dynamics via quadratic polynomials

This study aims at presenting a novel bi-parametric family of iterative methods for computing the fixed points of a contractive-like mapping. We thoroughly analyze the strong and stable convergence of the proposed technique and explore its applicability across various problem domains. Regarding convergence, it is proven that for several operators, the Mann iteration is analogous to the proposed multi-step class, and vice-versa. Moreover, numerical tests demonstrate the superior performance of the new procedures compared to existing three-step schemes. We further examine the dynamic behavior of several fixed-point iterative techniques when applied to quadratic polynomials. Based on the outcomes of these experiments, it can be concluded that the proposed family demonstrates both validity and effectiveness

Exploring justice perceptions in online banking recovery: gender moderation and behavioral outcomes

The study addresses the recovery from service failures in online banking. It focuses on the three dimensions of perceived recovery justice – namely, distributive justice (DJ), procedural justice (PJ), and interactional justice (IJ) – and investigates their impact on post-recovery satisfaction (PRS), the moderating effect of gender, and further, the influences of PRS on customer trust (CT), affective commitment (AFFC), and customers’ behavioral intentions (CBI). The study uses partial least squares structural equation modelling to examine the data collected in Egypt from 445 respondents who experienced a service failure with online banking. The results show that the three dimensions of perceived recovery justice – DJ, PJ, IJ – exert positive influences on PRS, and gender moderates the effects of PJ and IJ on PRS: procedural justice makes women exhibit higher levels of PRS. In contrast, interactional justice makes men encounter higher levels of PRS. The results also show that PRS positively influences CBI through its direct and indirect effects (via CT and AFFC). Furthermore, PRS mediates the positive effects of DJ, PJ, and IJ on customers’ behavioral intentions. The study outcomes have significant theoretical and practical implications for online banking

Multifractal analysis of Bitcoin price dynamics

This research employs Multifractal Detrended Fluctuation Analysis (MFDFA) to investigate multifractal properties in financial variables, including Bitcoin prices and economic indicators. Spanning 2019–2022, the analysis reveals multifractal scaling not only in Bitcoin prices, but also in economic indicators such as inflation rates and energy commodity prices. The non-linear singularity spectra unveil the multifaceted nature of scaling properties. Temporal analysis exposes intriguing trends in multifractality with implications for market efficiency. Furthermore, correlation analysis unveils connections among multifractal properties. For instance, a positive correlation between oil prices and Bitcoin suggests similar market forces. The log-log plot of fluctuation function Fq versus lag size demonstrates a power-law relationship, characteristic of multifractal systems. The empirical data’s alignment in log-log space suggests self-similarity in the Bitcoin time series, supporting multifractality. The calculated Hurst exponents values suggest varying degrees of multifractality across the years, with 2021 exhibiting the highest degree and 2022 the lowest. Furthermore, an asymmetry index (0.5767) deviating from 0.5 indicates that the multifractal nature of the Bitcoin market is not symmetric. This research enhances risk assessment and portfolio optimization in finance. It challenges the Efficient Market Hypothesis (EMH), emphasizing the significance of MFDFA in comprehending financial market and economic factor’s relationships

The study of factors affecting on COSO ERM success and its consequences: an empirical research of Thai-listed companies

The goal of this study was to look at the causes and effects of the COSO ERM success of the companies listed on the Thai Stock Exchange. The internal resources and capabilities including effective AIS design, top management support, and internal auditor competency are assumed to become the antecedents of COSO ERM success. Moreover, the consequences of COSO ERM success are sustainable value creation, achieve strategy and goal, promote efficiency and effectiveness, financial reporting quality, and compliance with law. Thai-listed firms were used as research subjects, and data from the chief internal control was collected via a mail survey process and a questionnaire. The overall findings show that successful COSO ERM is influenced positively and significantly by effective AIS design, top management support, and internal auditor competency. Additionally, the achievement of strategy and goals, promotion of efficiency and effectiveness, quality of financial reporting, and legal compliance are all positively impacted by COSO ERM success. Moreover, achieve strategy and goal, promote efficiency and effectiveness, financial reporting quality, compliance with law all have a positive, significant impact on the creation of sustainable value. Overall, the results demonstrate that excellent AIS design, top management backing, and internal auditor expertise are required for a company to develop both COSO ERM success and long-term sustainable value generation

Framework for deep reinforcement learning in Webots virtual environments

Reinforcement learning (RL) algorithms, particularly deep reinforcement learning (DRL), have shown transformative potential in robotics by enabling adaptive behaviour in virtual environments. However, a comprehensive framework for efficiently testing, training, and deploying robots in these environments remains underexplored. This study introduces a standardized, open-source framework designed specifically for the Webots simulation environment. Supported by a robust methodology, the framework integrates innovative design patterns and the digital twin (DT) concept with three distinct design patterns for structuring agent-environment interaction, notably including a novel pattern aimed at improving sim-toreal transferability, to enhance RL workflows. The proposed framework is validated through experimental studies on both a model the inverted pendulum and a production-grade Pioneer 3-AT robotic platform. The experiments highlight the framework’s ability to bridge the gap between virtual training and real-world implementation. All resources, including the framework, methodology, and experimental configurations, are openly accessible on GitHub

Apartment prices, the business cycle and time on market: Evidence from Bucharest

The issue of time on market (TOM) correlation with the sale price remains under-explored considering the importance and complexity of the housing market. This paper argues that TOM is influenced by variables other than transaction prices and tests the hypothesis that the business cycle is important in explaining the dynamics of TOM and driving transaction prices in the housing market. In testing this hypothesis, the paper investigates the role of transaction prices and TOM in the housing market in Bucharest, Romania using granular observations of 32,000 price listings over the period 2013–2017, a time-scale that captures the economic recovery phase following the global financial crisis. The analysis shows that spatial correlation is strong for TOM rather than weak and that reinforcing spatial effects evidenced among TOM in transactions of closed units would reflect the strong clustering in prices but are balanced in a type of (contrary sign) distribution effect that diminish the whole spatial impact in TOM in similar size, describing a corrective mechanism leading to a more balanced impact on TOM. Results show that GDP affects transaction prices pro-cyclically (0.062%) and with persistence (0.054%), while only GDP growth (the cycle) influences TOM (0.352%)

Estimating spatiotemporal heterogeneous effects of haze pollution on housing rents in China

Severe haze pollution significantly affects urban life quality and employment location choices, which in turn impact rental housing demand and housing rents. While numerous studies have delved into the effects of haze pollution on the real estate market, with a particular focus on housing prices, there is a notable scarcity of research on its impact within China’s rental housing market. This study employs spatial panel data encompassing 289 Chinese cities from 2015 to 2021 and applies a Geographically and temporally weighted regression (GTWR) model to investigate the spatiotemporal heterogeneous effects of haze pollution on housing rents in urban China. Our results indicate that the GTWR model’s goodness-of-fit surpasses that of the OLS, GWR, and TWR models. The results of the GTWR model reveal that haze pollution has a negative effect on housing rents in China, with the eastern region experiencing a notably stronger negative impact than the western region. Moreover, this negative impact becomes increasingly stronger over time. In addition, population, economic, and social factors significantly impact housing rents in Chinese cities. These findings offer valuable insights into the relationship between haze pollution and housing rents, assisting policymakers in assessing the economic value of air pollution control in urban China

Decoding the knowledge space of ‘Architectural and Urban Traditions’ utilising a metadata framework

This article explores the discourse on Architectural and Urban Traditions (AUT), examining its evolution expressions, and manifestations as a knowledge space. Utilising a Metadata Framework (MF) based on six lines of inquiry–scale, discipline, geographical diversity, typology, governance, and investigation methods–this research systematically examines the relationship between various research dimensions as perceived, researched, and interpreted by academics and scholars. It involves text mining and content analysis to enable deeper, data-driven exploration of evolving themes and patterns within the AUT knowledge space. The MF is implemented through the case of the International Association for the Study of Traditional Environments (IASTE), which is identified based on its focus and longstanding contribution to the discourse since the late 1980s. The study demonstrates how the two pillars of IASTE–Traditional Dwellings and Settlements Review (TDSR) and the biennale conferences (recently annual conferences) have shaped the discourse on traditional environments. It primarily contributes to the field by advancing the application of the Metadata Framework (MF) as a systematic tool for mapping the evolution of AUT discourse, providing valuable insights for future research. Key findings reveal a significant rise in technological integration and governance studies, sustained interest in studying intangible cultural heritage, and growth in linking this with advanced technologies. Conclusions are drawn to elucidate evolving, emerging, and declining themes and areas within the overall knowledge space of architectural and urban traditions