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A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.

The purpose of this study is to explore a new assembly process planning and execution mode to realize rapid response, reduce the labor intensity of assembly workers and improve the assembly efficiency and quality.

Based on the related concepts of digital twin, this paper studies the product assembly planning in digital space, the process execution in physical space and the interaction between digital space and physical space. The assembly process planning is simulated and verified in the digital space to generate three-dimensional visual assembly process specification documents, the implementation of the assembly process specification documents in the physical space is monitored and feed back to revise the assembly process and improve the assembly quality.

Digital twin technology enhances the quality and efficiency of assembly process planning and execution system.

It provides a new perspective for assembly process planning and execution, the architecture, connections and data acquisition approaches of the digital twin-driven framework are proposed in this paper, which is of important theoretical values. What is more, a smart assembly workbench is developed, the specific image classification algorithms are presented in detail too, which is of some industrial application values.

This research is aimed at preparing landslide susceptibility using spatial analysis and soft computing machine learning techniques based on convolutional neural networks (CNNs), artificial neural networks (ANNs) and logistic regression (LR) models.

Using the Geographical Information System (GIS), a spatial database including topographic, hydrologic, geological and landuse data is created for the study area. The data are randomly divided between a training set (70%), a validation (10%) and a test set (20%).

The validation findings demonstrate that the CNN model (has an 89% success rate and an 84% prediction rate). The ANN model (with an 84% success rate and an 81% prediction rate) predicts landslides better than the LR model (with a success rate of 82% and a prediction rate of 79%). In comparison, the CNN proves to be more accurate than the logistic regression and is utilized for final susceptibility.

Land cover data and geological data are limited in largescale, making it challenging to develop accurate and comprehensive susceptibility maps.

It helps to identify areas with a higher likelihood of experiencing landslides. This information is crucial for assessing the risk posed to human lives, infrastructure and properties in these areas. It allows authorities and stakeholders to prioritize risk management efforts and allocate resources more effectively.

The social implications of a landslide susceptibility map are profound, as it provides vital information for disaster preparedness, risk mitigation and landuse planning. Communities can utilize these maps to identify vulnerable areas, implement zoning regulations and develop evacuation plans, ultimately safeguarding lives and property. Additionally, access to such information promotes public awareness and education about landslide risks, fostering a proactive approach to disaster management. However, reliance solely on these maps may also create a false sense of security, necessitating continuous updates and integration with other risk assessment measures to ensure effective disaster resilience strategies are in place.

Landslide susceptibility mapping provides a proactive approach to identifying areas at higher risk of landslides before any significant events occur. Researchers continually explore new data sources, modeling techniques and validation approaches, leading to a better understanding of landslide dynamics and susceptibility factors.

This paper aims to examine the antecedents of adoption intention of profit-sharing investment deposits (PSID) among Moroccan customers.

Applying an extended version of diffusion of innovation (DOI) theory and using a non-probability sampling technique with convenience approach, a quantitative survey was developed and administered to 171 Islamic banking users. Structural equation modeling was then used to evaluate the significance of relationships between the various variables under study using SPSS 21.0 and AMOS 26.0 statistical packages.

Empirical findings of the structural analysis indicated a significant direct relationship between adoption intention and six out of seven variables: perceived relative advantage, perceived compatibility, perceived complexity, perceived risk, religiosity and social influence, all of which had a significant effect on Moroccan customers’ intention to invest their funds in profit-sharing based deposit instruments, whereas customer awareness exerted an insignificant positive effect.

The absence of a longitudinal study tracking the actual adoption behavior is the main limitation of this study. Furthermore, data were collected solely from Islamic banking users. Finally, despite being insightful, the empirical findings should be generalized with caution since the sample was purposely selected by the banks’ management.

This study implied that participatory banks should pay substantial attention to risk perceptions, as PSID adoption intention is typically inhibited by high perceived risks associated with these products. Moreover, this study provides great indications to Moroccan regulators and policymakers on a number of issues related to this emerging business.

To the best of the authors’ knowledge, this paper represents the first attempt to confirm the effectiveness of the Rogers’ DOI in examining the intention to adopt a financial innovation in the Moroccan context. It is also the first of its kind to address customers’ apprehensions regarding profit-sharing investment products.

This study aims to conceptualize, rethink and systematize methods used for measurement and evaluation (M&E) corporate communication.

The reflection is based on 462 key English-language books and papers devoted to M&E in the fields of corporate communication and public relations from the 1970th to 2023. Keywords in the titles and abstracts found the necessary materials. A critical analysis of the central concepts, models and methods described in the literature was conducted. As a result, a new model that unifies and structures the M&E toolkit is proposed for discussion.

Despite the significant contribution to developing a wide range of M&E models, they are still not perfect and universal. In addition, this system of approaches is continuously self-evolving and changing under the influence of digital innovations, so it requires steady rethinking and updating. On the other hand, most previous studies focused on communication management processes, losing focus on communication aspects. This led to the need for an alternative view based on proven theories to fill this gap. The proposed model combines quantitative and qualitative M&E methods for the five main components of corporate communication (communicator, audience, content, channels and result), covering a wide range of tools, from statistical and sociological research to big data analysis and neuro research.

This work contributes to developing the M&E theory of corporate communication, systematizing existing methods and opening new research perspectives. From a practical point of view, companies can use the presented approach for a more accurate and objective internal evaluation of the main components of corporate communication.

Maintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.

A computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.

Computer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R² is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.

In this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.

Misinformation surrounding the Sustainable Development Goals (SDGs) has contributed to the formation of misbeliefs among the public. The purpose of this paper is to investigate public sentiment and misbeliefs about the SDGs on the YouTube platform.

The authors extracted 8,016 comments from YouTube videos associated with SDGs. The authors used a pre-trained Python library NRC lexicon for sentiment and emotion analysis, and to extract latent topics, the authors used BERTopic for topic modeling.

The authors found eight emotions, with negativity outweighing positivity, in the comment section. In addition, the authors identified the top 20 topics discussing various SDGs and SDG-related misbeliefs.

The authors reported topics related to public misbeliefs about SDGs and associated keywords. These keywords can be used to formulate social media content moderation strategies to screen out content that creates these misbeliefs. The result of hierarchical clustering can be used to devise and optimize response strategies by governments and policymakers to counter public misbeliefs.

This study represents an initial endeavor to gain a deeper understanding of the public’s misbeliefs regarding SDGs. The authors identified novel misbeliefs about SDGs that previous literature has not studied. Furthermore, the authors introduce an algorithm BERTopic for topic modeling that leverages transformer architecture for context-aware topic modeling.

This study aims to examine the historical development, present state and potential future directions of the integration between building information modeling (BIM) and life cycle assessment (LCA) in the field of construction. Additionally, this paper identifies current problems while offering insight into worldwide BIM research trends.

This study uses text mining on unstructured abstracts, a novel approach not previously documented in BIM research. By conducting a comprehensive systematic assessment of academic literature, this work uses advanced bibliometric approaches to examine the developmental trajectory of the integration of BIM and LCA. The research incorporates co-citation and keyword co-occurrence mapping, providing a complex visual depiction of the interconnectedness of information across different periods.

The results of this analysis reveal the historical development of the integration of BIM and LCA, including its roots and the initial research that established the foundation for further investigations. The aforementioned seminal works signify the inception of the discipline, serving as a source of inspiration for current scholarly investigations. Currently, there is a complex network of interdisciplinary cooperation that can be observed, combining knowledge and perspectives from the fields of design, engineering, construction and sustainability.

This research contributes novelty to the scholarly discourse by offering a holistic and up-to-date panorama of the dynamic BIM and LCA research landscape. It identifies emerging trends, influential contributors and uncharted territories, thus providing a foundation for scholars to contribute meaningfully to the advancement of knowledge in sustainable construction practices.

This paper aims to highlight the expanding link between facility management (FM) and building automation and control systems (BACS) through a review of literature. It examines the opportunities and challenges of BACS for facility managers and proposes solutions for mitigating the risks associated with BACS implementation.

This paper reviews various research papers to explore the positive influences of BACS on FM, such as support with strategic decision-making, predictive maintenance, energy efficiency and comfort improvement. It also discusses the challenges of BACS, including obsolescence, interoperability, vendor lock-in, reliability and security risks and suggests potential solutions based on existing literature.

BACS offers numerous opportunities for facility managers, such as improved decision-making, energy efficiency and comfort levels in office buildings. However, there are also risks associated with BACS implementation, including obsolescence, interoperability, vendor lock-in, reliability and security risks. These risks can be mitigated through measures such as hardware and software obsolescence management plans, functional requirement lists, wireless communication protocols, advanced feedback systems and increased awareness about BACS security.

To the best of the authors’ knowledge, no prior academic research has been conducted on the expanding link between FM and BACS. Although some papers have touched upon the opportunities and challenges of BACS for FM, this paper aims to provide a comprehensive overview of these findings by consolidating existing literature.

This paper aims to examine the congruency effects of physically embodied robots in service encounters, which addressed a significant research gap concerning the synthesis of robot design elements (e.g., appearance and voice) and their service purposes.

Grounded in congruity theory and human-robot interaction literature, this study conducted a pretest and two experimental studies revealing the need to view robot design holistically and recognizing the pivotal role of congruity in shaping consumers’ service robot adoption. The moderating role of service purposes (utilitarian vs hedonic) was also investigated in terms of robot design and consumer reactions.

Consumers generally tend to favor robots with congruent designs, particularly for utilitarian service purposes. The serial mediation through perceived congruence and perceived intelligence explains such a favorite tendency.

This study advances service robot design research by highlighting the critical role of congruity in enhancing consumer engagement. It supports the use of comprehensive, congruent designs for services with utilitarian purposes and recommends adaptable designs for hedonic settings.

This study addressed the research gap by examining service robot design from a holistic perspective. The research findings highlight the importance of congruency effects in service robot design and deployment and provide valuable insights and guidelines to industry practitioners for optimal investment in service robots.