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To address the issues of low localization and mapping accuracy, as well as map ghosting and drift, in indoor degraded environments using light detection and ranging-simultaneous localization and mapping (LiDAR SLAM), a real-time localization and mapping system integrating filtering and graph optimization theory is proposed. By incorporating filtering algorithms, the system effectively reduces localization errors and environmental noise. In addition, leveraging graph optimization theory, it optimizes the poses and positions throughout the SLAM process, further enhancing map accuracy and consistency. The purpose of this study resolves common problems such as map ghosting and drift, thereby achieving more precise real-time localization and mapping results.

The system consists of three main components: point cloud data preprocessing, tightly coupled inertial odometry based on filtering and backend pose graph optimization. First, point cloud data preprocessing uses the random sample consensus algorithm to segment the ground and extract ground model parameters, which are then used to construct ground constraint factors in backend optimization. Second, the frontend tightly coupled inertial odometry uses iterative error-state Kalman filtering, where the LiDAR odometry serves as observations and the inertial measurement unit preintegration results as predictions. By constructing a joint function, filtering fusion yields a more accurate LiDAR-inertial odometry. Finally, the backend incorporates graph optimization theory, introducing loop closure factors, ground constraint factors and odometry factors from frame-to-frame matching as constraints. This forms a factor graph that optimizes the map’s poses. The loop closure factor uses an improved scan-text-based loop closure detection algorithm for position recognition, reducing the rate of environmental misidentification.

A SLAM system integrating filtering and graph optimization technique has been proposed, demonstrating improvements of 35.3%, 37.6% and 40.8% in localization and mapping accuracy compared to ALOAM, lightweight and ground optimized lidar odometry and mapping and LiDAR inertial odometry via smoothing and mapping, respectively. The system exhibits enhanced robustness in challenging environments.

This study introduces a frontend laser-inertial odometry tightly coupled filtering method and a backend graph optimization method improved by loop closure detection. This approach demonstrates superior robustness in indoor localization and mapping accuracy.

This study aims to examine the impact of mandatory CEO/CFO certification introduced in the new Indian Companies Act (CA) 2013 on the earnings quality of reported annual and quarterly net income of Indian listed companies.

Using rounding up of earnings as a proxy for earnings quality, the study is based on annual and quarterly reported net income of 4,128 sample companies during two years prior and two years after the CA 2013. The analysis of reported net income is based on the left-most second single digits with an emphasis on zero as the second single digit. The percentage difference between the actual and theoretical second single digits in reported net income is used for rounding up analysis. Benford’s Law is used to derive the theoretical percentage appearance of second single digits.

The existence of statistically significant deviation prior to CA 2013 and insignificant deviation post CA 2013 between the actual and theoretical percentage appearance of zero and nine of annual net income implies the increase in quality of earnings due to mandatory certification of annual financial statements. However, there is no improvement in the quality of earnings of quarterly net income as the certification of quarterly results is not mandatory.

The authors recommend that CEO/CFO certification of quarterly financial results should also be made mandatory.

The positive impact of regulatory initiatives on the earnings quality of publicly listed companies operating in a weak enforcement environment within an emerging market is the contribution.

The global market for cloud gaming is growing rapidly. How gamers evaluate the service quality of this emerging form of cloud service has become a critical issue for both researchers and practitioners. Building on the literature on service quality and software as a service, this study develops and validates a gamer-centric measurement instrument for cloud gaming service quality.

A three-step measurement instrument development process, including item generation, scale development and instrument testing, was adopted to conceptualize and operationalize cloud gaming service quality.

Cloud gaming service quality consists of two second-order constructs of support service quality and technical service quality with seven first-order dimensions, namely rapport, responsiveness, reliability, compatibility, ubiquity, smoothness and comprehensiveness. The instrument exhibits desirable psychometric properties.

Practitioners can use this new measurement instrument to evaluate gamers' perceptions toward their service and to identify areas for improvement.

This study contributes to the service quality literature by utilizing qualitative and quantitative approaches to develop and validate a new measurement instrument of service quality in the context of cloud gaming and by identifying new dimensions (compatibility, ubiquity, smoothness and comprehensiveness) specific to it.

The study aims to explain co-creation by exploring the relationships between people, processes, connection points, and artifacts within a museum context.

Data were gathered through in situ participant observations and semi-structured interviews. This research involved an international cohort of tourists, exploring their experiences at a Parisian destination service provider – a perfume museum.

The findings show an increasing willingness of museum visitors to be involved in all stages of the co-creation experience. They also highlight the key role played by service providers in facilitating the visitors’ involvement in the co-creation of their personal fragrance, allowing both parties to enhance their knowledge through interactions, which are likely to generate shared values. Nurturing this exchange promotes novelty and uniqueness of museum visiting experiences.

This study offers several contributions to the existing body of knowledge on co-creating memorable museum visiting experiences. It highlights the importance of incorporating both human (i.e. visitors and museum staff) and non-human elements, such as processes, points of connection and artifacts, for successful co-creation. Also, this study argues that, in addition to organizational learning, visitors’ experienced outcomes can be categorized into three types: cognition-oriented, emotion-oriented and action-oriented outcomes.

Achieving success requires museums to adopt a fresh perspective toward visitors, engaging them in the co-creation process rather than merely regarding them as transient observers. Managers play a crucial role in fostering social connections by establishing channels of interaction to facilitate the exchange of knowledge between visitors and museums in both directions.

This study sheds light on how co-creation in a museum context can be achieved. In contrast to the model proposed by Payne et al. (2009), this study examines experienced outcomes through the viewpoints of both visitors and instructors/facilitators. In addition, most previous studies in the museum context focus on experience co-creation, highlighting its intangible and hedonic aspects such as entertainment and esthetics. This study expands this by incorporating a tangible element – creating a customized product (i.e. a perfume). Furthermore, it reveals that the emotions experienced extend beyond customer engagement, brand advocacy and pleasure to include pride, accomplishment and a sense of brand ownership.

This study aims to analyse the antecedents and consequences of consumer participation behaviour in the hotel industry. It investigates how citizenship behaviour influences the link between participation and switching intention. It also investigates hotel innovativeness, brand identification and consumer value co-creation using the frameworks of innovation diffusion theory, social identity theory and social exchange theory. By combining different academic perspectives, the study provides a thorough grasp of the elements that influence consumer behaviour and loyalty to hospitality brands.

This study used a descriptive-analytical approach to survey 526 guests who stayed at five-star hotels affiliated with chains in Egypt. The hotels were chosen using stratified random sampling, which ensured representation across multiple segments. For practical reasons, convenience sampling techniques were used to pick research participants. To test the study hypotheses, structural equation modelling was used, which provided a strong statistical analysis to assess the correlations between variables and validate the suggested theoretical framework.

The research indicates that hotel innovativeness has a substantial impact on consumers’ brand identification and involvement behaviour, but not their propensity to move brands. The relationship between participation behaviours and intention to switch is mediated by consumer citizenship behaviour.

The cross-sectional study methodology may not address causal linkages or developmental difficulties because it only collected data at one point in time. A longer study period is required, and the sample group’s breadth is restricted to five-star hotel guests from Egypt’s chain-affiliated hotels.

This study offers a thorough methodology for assessing how hotel innovation influences consumer brand identification. It also looks at how consumer brand identification affects involvement and switching intentions. The study also investigates the moderating influence of consumer citizenship behaviour in the link between involvement and switching intentions.

This research paper aims to investigate the predictors and outcomes of immersive technology adoption in tourism.

PLS-SEM is used for data collected from tourists visiting the UAE and Egypt to examine predictors and consequences of adoption.

It is revealed that perceived ease of use, enjoyment, immersion, usefulness and attitude towards technology predict immersive technology adoption. It is also revealed that the adoption affects tourists’ perceived value and engagement, which, in turn, affects tourists’ satisfaction and loyalty.

The study has integrated a research model that combines both antecedents and consequences of immersive technology adoption where few empirical investigations were revealed to draw conclusions on this research area. Also, missing relations have been included and tested in the research model.

Effective knowledge management in large academic institutions is crucial for fostering innovation and improving educational practices. However, these institutions often face challenges, such as data fragmentation, siloed information systems and the complexity of integrating different data sources from various departments with complex hierarchical structures. To address these problems, the authors proposed a data fabric strategic framework that improves and enhances knowledge management by leveraging ontologies and knowledge graphs. This study aims to investigate the potential of knowledge graphs, ontological knowledge modelling and knowledge representation to improve knowledge management in large academic institutions. It also describes how technology can enhance knowledge accessibility and exchanges and improve decision-making processes based on insights from complex educational systems.

This study uses coordination theory as a foundational framework to analyse intricate data systems in preparation for constructing, the Wizard of Oz method to facilitate the systematic organisation and management of information and the execution of an ontology-based data fabric framework and knowledge graphs. The authors propose a data fabric strategic framework aimed at improving knowledge management by leveraging ontologies and knowledge graphs.

The final evaluation demonstrates that this approach effectively breaks down data silos, promotes research collaboration and improves decision-making processes in large academic settings, offering solution-oriented data fabric technologies applicable to universities and university federations globally.

The proposed system provides a more efficient way of managing and connecting fragmented academic resources, improving accessibility for both learners and educators. By interconnecting and streaming knowledge management process, the system can reduce not only operational costs but also expenses on doing scientific research.

Academic institutions prioritise time efficiency when acquiring vital data for improved scientific results. This emphasis extends beyond data governance to focus on how collective intelligence might improve organisational performance. The academic community has enhanced data utilisation through the implementation of data fabric technologies to improve data accessibility and data line tracking.

To support digital humanities research more effectively and efficiently, this study develops a novel Knowledge Graph Analysis Tool of People and Organizations (KGAT-PO) for the Digital Humanities Research Platform for Biographies of Chinese Malaysian Personalities (DHRP-BCMP) based on artificial intelligence (AI) technology that would not only allow humanities scholars to look at the relationships between people but also has the potential for aiding digital humanities research by identifying latent relationships between people via relationships between people and organizations.

To verify the effectiveness of KGAT-PO, a counterbalanced design was applied to compare research participants in two groups using DHRP-BCMP with and without KGAT-PO, respectively, to perform people relationship inquiry and to see if there were significant differences in the effectiveness and efficiency of exploring relationships between people, and the use of technology acceptance between the two groups. Interviews and Lag Sequential Analysis were also used to observe research participants’ perceptions and behaviors.

The results show that the DHRP-BCMP with KGAT-PO could help research participants improve the effectiveness of exploring relationships between people, and the research participants showed high technology acceptance towards using DHRP-BCMP with KGAT-PO. Moreover, the research participants who used DHRP-BCMP with KGAT-PO could identify helpful textual patterns to explore people’s relationships more quickly than DHRP-BCMP without KGAT-PO. The interviews revealed that most research participants agreed that the KGAT-PO is a good starting point for exploring relationships between people and improves the effectiveness and efficiency of exploring people’s relationship networks.

The research’s limitations encompass challenges related to data quality, complex people relationships, and privacy and ethics concerns. Currently, the KGAT-PO is limited to recognizing eight types of person-to-person relationships, including couple, sibling, parent-child, friend, teacher-student, relative, work, and others. These factors should be carefully considered to ensure the tool’s accuracy, usability, and ethical application in enhancing digital humanities research.

The study’s practical implications encompass enhanced research efficiency, aiding humanities scholars in uncovering latent interpersonal relationships within historical texts with high technology acceptance. Additionally, the tool’s applications can extend to social sciences, business and marketing, educational settings, and innovative research directions, ultimately contributing to data-driven insights in the field of digital humanities.

The research’s originality lies in creating a Knowledge Graph Analysis Tool of People and Organizations (KGAT-PO) using AI, bridging the gap between digital humanities research and AI technology. Its value is evident in its potential to efficiently uncover hidden people relationships, aiding digital humanities scholars in gaining new insights and perspectives, ultimately enhancing the depth and effectiveness of their research.

This study aims to investigate the effects of financial aid via zakat and the perceived learning–teaching process on the educational outcomes of undergraduate students in Malaysia.

Approximately 350 zakat recipients (mustahiq) were selected to evaluate their educational outcomes, measured by the learning process, student readiness and academic performance. Partial least squares (PLS) regression was used to test the selected samples and approve the hypothesis.

In accordance with the underlying theories, the results of the PLS regression highlighted several major findings: financial aid, through zakat indeed increases positive effects in the learning process; zakat aid is found to increase student readiness in the education process and academic performance of undergraduate students; and student readiness in the education process plays a significant role in mediating the effect between zakat aid and the learning process and academic performance. This study also demonstrates that the learning process is equally important for student readiness and academic performance.

Importantly, this study contributes novelty by exploring the impact of zakat in education, specifically the higher education sector, because previous studies have enormously discussed zakat as a poverty-mitigating topic. The findings of this study are essential for zakat stakeholders to understand the contribution of zakat to developing human capital, particularly post-COVID-19 in Malaysia.

This study investigates the impact and role of digital twin technology in building automation (DTBA) from a sustainability viewpoint. It aims to enhance the understanding of how DTBA can boost efficiency, optimize quality and support sustainable practices in contemporary construction. By exploring the integration of DTBA with sustainable practices, the study seeks to demonstrate how DT can revolutionize building management and operations, leading to significant improvements in resource efficiency, environmental impact and overall operational excellence.

This research employs a bibliographic analysis and systematic review of 176 publications from the past five years (January 1, 2019 to December 31, 2023), focusing on the application and development of DTBA. The study methodically analyzes current trends, identifies research gaps and suggests future directions by synthesizing data from various studies, offering a comprehensive overview of the current state of DTBA research. The approach combines quantitative and qualitative analyses to provide robust insights into the advancements and challenges in the field.

The review identifies key development areas in DTBA, such as energy and environmental management, resource utilization within a circular economy and technology integration and interoperability. It highlights the necessity for further research to maximize DTBA’s potential in sustainable building automation. The findings suggest that while significant progress has been made, there is a critical need for innovations in data interoperability, predictive analytics and the integration of renewable energy sources to fully realize the benefits of DTBA in enhancing building sustainability.

This paper provides a thorough review of DTBA from a sustainability perspective, offering valuable insights into its current applications and future development potential. It serves as a crucial resource for researchers and practitioners looking to advance sustainable practices in the construction sector using DT technology. By bridging the gap between theoretical research and practical applications, the paper underscores the transformative potential of DTBA in driving sustainable development and provides a roadmap for future research and innovation in the field.