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The purpose of this study is to understand how to improve the recognition of biodiversity knowledge for engineering students, using a case study in the context of Norway.

A case study based on an elective course for engineering students was carried out. The course is related to sustainability and also explicitly focuses on biodiversity topics and causality for loss of biodiversity. Data was collected through questionnaires to students to understand their motivations and perceptions about the course, and through interviews with study programme coordinators, to understand their perspectives regarding sustainability and biodiversity education for engineering programmes.

Three main conclusions are established: the best approach is to incorporate biodiversity content into existing courses, rather than having a specific course dedicated to biodiversity; more knowledge on biodiversity is seemingly increasing the understanding of its importance, thus, students should be exposed to these topics early in their studies; and some strategies to improve the current course are related to being more specific on how to deal with biodiversity in different contexts (such as working life and different industries), offering a higher number of examples, and linking biodiversity with other environmental impacts.

To the best of the authors’ knowledge, this study is the first to address the recognition of biodiversity knowledge in engineering programmes at a Norwegian university. The case study provides valuable insights that can be used to improve the integration of biodiversity knowledge into engineering programmes. Moreover, the methods used provide innovative and more reliable tools to better address the perceptions of stakeholders.

This study aims to propose a collaborative knowledge-based ontological research model for designing a collaborative product development process (PDP) while considering different design for X techniques.

This study follows a thematic literature analysis to identify the key design concepts needed to assess environmental, service, safety, manufacture and assembly, supply chain and quality concerns in developing a collaborative PDP.

The proposed model provides a guide for methodology, engineering and ontology evaluation metrics (verification, assessment and validation). The findings benefit both practitioners and managers because they address the key knowledge taxonomy needed to assist them in storing information, promoting teamwork and making decisions in a collaborative PDP while incorporating various design for X approaches and product life cycles.

This study introduces a novel knowledge-based collaborative ontological research model, which is specifically designed to tackle the challenges of developing collaborative products in the contemporary landscape. The model presents a significant and valuable contribution to the field by introducing an ontological approach for acquiring, representing and leveraging knowledge in a computer-interpretable format to support the design of collaborative products. In addition, it provides a comprehensive guide for evaluating the effectiveness and efficacy of the ontology developed.

This paper aims to curate open research knowledge graph (ORKG) with papers related to ontology learning and define an approach using ORKG as a computer-assisted tool to organize key-insights extracted from research papers.

Action research was used to explore, test and evaluate the use of the Open Research Knowledge Graph as a computer assistant tool for knowledge acquisition from scientific papers.

To extract, structure and describe research contributions, the granularity of information should be decided; to facilitate the comparison of scientific papers, one should design a common template that will be used to describe the state of the art of a domain.

This approach is currently used to document “food information engineering,” “tabular data to knowledge graph matching” and “question answering” research problems and the “neurosymbolic AI” domain. More than 200 papers are ingested in ORKG. From these papers, more than 800 contributions are documented and these contributions are used to build over 100 comparison tables. At the end of this work, we found that ORKG is a valuable tool that can reduce the working curve of state-of-the-art research.

This study aims to investigate the influence of requirement engineering (RE) on project performance (PP) in the context of NEOM* in Saudi Arabia. The study also aims to examine the relationship between three components of RE, evolving market needs (ECN), market changes (MC) and technological advancements (TA), on PP, through the mediating influence of effective communication (EC), change readiness (CR) and stakeholder engagement (SE). Further, the study aims to examine the moderating effect of team cohesion (TC) on the RE–PP relationships.

A research framework is developed by drawing on the resource-based theory and with the support of empirical evidence and rational arguments to propose a set of hypotheses relating to the constructs in the framework. The hypotheses are tested through survey data collected from individual employees working on different projects across NEOM. A total of 336 useable responses were collected that were analyzed through covariance-based structural equation modeling using AMOS v.28.

The results show although ECN and TA both have a positive impact on PP, MC had no significant relationship with PP. In terms of the mediation hypotheses, EC, CR and SE all partially mediate the relationships between ECN and TA with PP. However, there was no mediating effect in the relationship between MC and PP. Moreover, EC, CR and SE themselves have a significant positive influence on PP. Finally, TC proved to be a significant moderator between ECN and PP and TA and PP, but not in the case of MC and PP.

This study makes three novel contributions. First, most prior empirical studies examined the overall impact of RE on PP; however, the current study provides a more nuanced insight into the relationships between the three components of RE (i.e. ECN, MC and TA) and PP. Second, the mediating roles of EC, CR and SE between components of RE and PP present a finer-grained understanding of how project resources are linked to project success goals through features of the project team. Third, moderating influence of TC with regard to a higher possibility of success for projects are highlighted through this discovery.

With shorter product cycles and a growing number of knowledge-intensive business processes, time consumption is a highly relevant target factor in measuring the performance of contemporary business processes. This research aims to extend prior research on the effects of knowledge transfer velocity at the individual level by considering the effect of complexity, stickiness, competencies, and further demographic factors on knowledge-intensive business processes at the conversion-specific levels.

We empirically assess the impact of situation-dependent knowledge transfer velocities on time consumption in teams and individuals. Further, we issue the demographic effect on this relationship. We study a sample of 178 experiments of project teams and individuals applying ordinary least squares (OLS) for regression analysis-based modeling.

The authors find that time consumed at knowledge transfers is negatively associated with the complexity of tasks. Moreover, competence among team members has a complementary effect on this relationship and stickiness retards knowledge transfers. Thus, while demographic factors urgently need to be considered for effective and speedy knowledge transfers, these influencing factors should be addressed on a conversion-specific basis so that some tasks are realized in teams best while others are not. Guidelines and interventions are derived to identify best task realization variants, so that process performance is improved by a new kind of process improvement method.

This study establishes empirically the importance of conversion-specific influence factors and demographic factors as drivers of high knowledge transfer velocities in teams and among individuals. The contribution connects the field of knowledge management to important streams in the wider business literature: process improvement, management of knowledge resources, design of information systems, etc. Whereas the model is highly bound to the experiment tasks, it has high explanatory power and high generalizability to other contexts.

Team managers should take care to allow the optimal knowledge transfer situation within the team. This is particularly important when knowledge sharing is central, e.g. in product development and consulting processes. If this is not possible, interventions should be applied to the individual knowledge transfer situation to improve knowledge transfers among team members.

Faster and more effective knowledge transfers improve the performance of both commercial and non-commercial organizations. As nowadays, the individual is faced with time pressure to finalize tasks, the deliberated increase of knowledge transfer velocity is a core capability to realize this goal. Quantitative knowledge transfer models result in more reliable predictions about the duration of knowledge transfers. These allow the target-oriented modification of knowledge transfer situations so that processes speed up, private firms are more competitive and public services are faster to citizens.

Time consumption is an increasingly relevant factor in contemporary business but so far not been explored in experiments at all. This study extends current knowledge by considering quantitative effects on knowledge velocity and improved knowledge transfers.

Taking a co-creation perspective and integrating knowledge-based and resource-based perspectives, the authors examine the role of customer participation in organizational performance and project success. The authors also investigate the mediating role of knowledge integration and the moderating role of requirement risk for these relationships in uncertain contexts.

The authors undertook two studies. The first study was carried out in 2018 in which the authors drew on survey data from 150 information technology (IT) sector employees and examined the mediating role of knowledge integration in the relationship of customer participation with organizational performance and project success. In the second study undertaken in 2020, the authors drew on data from 92 IT and telecom sector employees and examined the moderating role of requirement risk in the relationship between customer participation and knowledge integration. Study 2 was conducted during the COVID-19 pandemic when employees were largely working from home and were more sensitive to risks and uncertainty about the scope and system requirements. Both studies were survey-based, and analysis was carried out using structural equation modeling.

The authors’ two-study examination indicated that knowledge integration positively mediates the relationship of customer participation with organizational performance and project success during the co-creation process. Furthermore, the authors demonstrate that when requirement risks are high, customer participation relationship with knowledge integration is weaker.

The authors show that integrating customer knowledge is critical to project success and organizational performance. By identifying risk uncertainties and environmental contingencies, the authors highlight the constraints of customer participation for knowledge integration, organizational performance and project success. The authors provide some key study findings based on survey data obtained from project teams during two periods (normal and pandemic).

The extreme nature of fire makes structural fire engineering unique in that the load actions dictating design are intense and neither geographically nor seasonally bound. Simply, fire can break out anywhere, at any time and for any number of reasons. Despite the apparent need, the fire design of structures still relies on expensive fire tests, complex finite element simulations and outdated procedures with little room for innovation. This paper aims to discuss the aforementioned issues.

This primer highlights the latest state of the art in this area with regard to performance-based design in fire structural engineering. In addition, this short review also presents a series of examples of successful implementation of performance-based fire design of structures from around the world.

A comparison between global efforts clearly shows the advances put forth by European and Oceanian efforts as opposed to the rest of the world. In addition, it can be clearly seen that most performance-based fire designs are related to steel and composite structures.

In one study, this paper presents a concise and global view to performance-based fire design of structures from success stories from around the world.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

Industry 4.0 is exacerbating the need for offsite construction (OSC) adoption, and this rapid transformation is pushing the boundaries of construction skills towards extensive modernisation. The adoption of this modern production strategy by the construction industry would redefine the position of OSC. This study aims to examine whether the existing skills are capable of satisfying the needs of different OSC types.

A critical literature review evaluated the impact of transformative technology on OSC skills. An existing industry standard OSC skill classification was used as the basis to develop a master list that recognises emerging and diminishing OSC skills. The master list recognises 67 OSC skills under six skill categories: managers, professionals, technicians and trade workers, clerical and administrative workers, machinery operators and drivers and labourers. The skills data was extracted from a series of 13 case studies using document reviews and semi-structured interviews with project stakeholders.

The multiple case study evaluation recognised 13 redundant skills and 16 emerging OSC skills such as architects with building information modelling and design for manufacture and assembly knowledge, architects specialised in design and logistics integration, advanced OSC technical skills, factory operators, OSC estimators, technicians for three dimensional visualisation and computer numeric control operators. Interview findings assessed the current state and future directions for OSC skills development. Findings indicate that the prevailing skills are not adequate to readily relocate construction activities from onsite to offsite.

To the best of the authors’ knowledge, this research is one of the first studies that recognises the major differences in skill requirements for non-volumetric and volumetric OSC types.