Search results

The purpose of this study is to investigate the significance and impact of strategic knowledge management (SKM) practices and organisational change capacity (OCC) in improving strategic thinking and strategic orientation in small and medium-sized enterprises (SMEs) and their contribution in overall improvement of entrepreneurial performance.

Quantitative research methodology using partial least square structural equation modelling with data of 296 sample from the target group as managers and owners from various SMEs in the UK has been used in the study.

The findings suggest that SMEs that invest in SKM and OCC are more proficient at adjusting to fluctuations in the business landscape and develop effective strategies that lead to improved entrepreneurial performance. The study provides evidence that SKM encompasses more than just the acquisition and use of information. It also involves the establishment of a learning and innovation culture that facilitates strategic thinking and direction. Similarly, OCC is not just about implementing change but also about developing the agility and flexibility to adapt to market changes, consumer demands and technology.

According to the research, SMEs may boost their entrepreneurial performance and keep a competitive advantage in the modern, dynamic business environment by investing in SKM and OCC. The capacity of SMEs to implement SKM and organisational change should be encouraged and supported by policymakers and practitioners, who should also offer the necessary tools and assistance to do so.

This study offers a valuable addition to the previously published works on SKM and OCC within SMEs. It offers empirical data that highlights the significance of SKM and OCC in fostering strategic thinking, strategic orientation and ultimately, boosting entrepreneurial performance. The study also highlights the challenges faced by SMEs in implementing SKM and OCC and provides recommendations for overcoming these challenges.

Manufacturing firms must embrace smart technologies and develop complex leadership approaches to achieve sustainability. Using the dynamic capability theory, this paper aims to examine the influence of the adoption of industry 4.0 technologies (AT) and paradoxical leadership (PL) on corporate sustainable performance (CSP) of manufacturing small-medium enterprises (SMEs) in Malaysia. Moreover, organisational ambidexterity (OA) is a mediator and strategic flexibility (SF) is a moderator in the study.

The study is a cross-sectional, quantitative study design that collected 395 usable responses through a simple random sampling technique and a close-ended structured questionnaire. Structural equation modelling (SEM) procedures were followed to analyse the data.

The statistical outcome implies that the AT significantly influence CSP and OA and mediate with CSP in the presence of OA. Moreover, PL shows a significant impact on OA, is insignificant on CSP and mediates with OA and CSP. The authors found a significant association between OA and CSP; however, SF did not provide evidence of a moderate effect.

The findings of this study clarify the role that organisational capabilities (OA, AT, PL and SF) play in fostering sustainability. The authors suggest incorporating SMEs from different geographies in other sectors by applying diverse methodologies and relevant constructs.

The result injects new perspectives into policy, managerial and individual levels. Installing OA, AT, PL and SF makes SMEs sustainable.

The empirical validation of the influence of OA and AT on CSP and the interaction of PL and SF enriches the organisational and entrepreneurial literature.

This study aims to explore the key drivers contributing to supply chain resilience, with specific attention on agility, absorptive capacity and ambidexterity. It focuses on the roles of supply chain absorptive capacity (SCAC), supply chain ambidexterity (SCAB), supply chain agility (SCAG) and supply chain flexibility (SCF) in enhancing supply chain resilience (SCR).

A survey based on a questionnaire with established scales for SCAC, SCAB, SCAG, SCF and SCR was conducted among professionals in various industries within India, receiving 356 responses. Structural equation modeling is used to test the hypothesis.

The study reveals significant relationships between SCAC, SCAB, SCAG and SCR. SCAC and SCAB are positively correlated with SCAG, which in turn positively influences SCR. Further, SCF directly influences SCR and moderates the relationships between SCAC/SCAB and SCAG, enhancing the agility and resilience of the supply chain. These findings underline the importance of integrating knowledge management, adaptability and flexibility in supply chain strategies to cope with the dynamic business environment.

The uniqueness of this study lies in its integrated investigation of absorptive capacity, ambidexterity, agility and supply chain flexibility, with a specific focus on the moderating role of flexibility. This research is unique in demonstrating how these dynamic capabilities transform disruptions into innovative and growth opportunities for supply chain management.

Since 2011, the Extremism Risk Guidance (ERG 22+) has been the primary risk assessment framework used for terrorist and violent extremist offenders in England and Wales. The aim of this study was to conduct a rapid evidence assessment to examine the research literature on the ERG22+ factors and to identify possible significant new and emerging knowledge around potential new factors.

Searches were conducted of the Google Scholar database to identify relevant literature published between 2012 and 2020. In total, 29 documents were identified, which examined new radicalisation models and frameworks, 339 were identified, which explored to some extent one or more of the current ERG factors, and a further 138 articles were identified, which focused on potentially relevant additional issues/factors.

Most of the ERG factors were the focus of substantial research activity between 2012 and 2020. Six factors, however, received very little research attention. Potential implications of these trends are considered. Ten research themes were identified with the potential to either form new factors or which could play a significant role in the updating or revision of some existing factors.

This paper is the first rapid evidence assessment on the ERG22+ risk factors. It provides an important picture of the published scientific research of potential relevance in this area and helps to inform the review process for the ERG22+.

This study establishes an ontology-based framework for rework risk identification (RRI) by integrating heterogeneous data from the information flow of the prefabricated construction (PC) process. The main objective is to enhance the automation level of rework management and reduce the degree of reliance on human factors and manual operations.

The proposed framework comprises four levels aimed at managing dispersed rework risk knowledge and integrating heterogeneous data. The functionalities were realised through an integrated ontology that aligned the rework risk ontology with the PC ontology. The ontologies were developed and edited with Protégé. Ultimately, the potential benefit of the framework was validated through a case study and an expert questionnaire survey.

The framework is proven to effectively manage rework risk knowledge and can identify risk objects, clarify risk factors, determine risk events, and retrieve risk measures, thereby enabling the pre-identification of prefabricated rework risk (PRR) and improving the automation level. This study is meaningful and lays the foundation for the application of other computer methods in rework management research and practice in the future.

This research provides insights into the application of ontology to solve rework risk issues in the PC process and introduces a novel risk management method for future prefabricated project research and practice. The findings have significant theoretical value in terms of enriching the methods of risk assessment and control and the information management system of prefabricated projects.

Current practices for inspecting highway construction predominantly rely on manual processes, which result in subjective assessments, errors and time inefficiencies. The purpose of this study is to address the inefficiencies and potential inaccuracies inherent in manual highway construction inspections. By leveraging computer vision and ontology reasoning, the study seeks an automated and efficient approach to generate structured construction inspection knowledge in the format of checklists for construction activities on highway construction job sites.

This study proposes a four-module framework based on computer vision and ontology reasoning to enable the automatic generation of checklists for quality inspection. The framework includes: (1) the interpretation of construction scenes based on computer vision, (2) the representation of inspection knowledge into structured checklists through specification processing, (3) the connection of construction scenes and inspection knowledge via ontology reasoning and (4) the development of a prototype for the automatic generation of checklists for highway construction.

The proposed framework is implemented across four distinct highway construction scenarios. The case demonstrations show that the framework can interpret construction scenes and link them with relevant inspection knowledge automatically, resulting in the efficient generation of structured checklists. Therefore, the proposed framework indicates considerable potential for application in the automatic generation of inspection knowledge for the quality inspection of highway construction.

The scientific and practical values of this study are: (1) the establishment of a new method that promotes the automated generation of structured inspection knowledge for highway construction by integrating computer vision and ontology reasoning and (2) the development of a novel framework that provides efficient and immediate access to inspection knowledge related to what needs to be inspected at highway construction job sites.

This paper examines how Russian multinational enterprises (MNEs) operating in the metallurgical industry strategise under the highly complex conditions of their home institutional environment.

The findings are based on a qualitative multiple-case study of eight Russian metallurgical MNEs that took place in 2014–2015. The authors conducted 34 semi-structured interviews, made observations and took reflexive field notes.

The analysis reveals that Russian MNEs utilise four different strategies–cooperation, persuasion, avoidance and adaptation–when dealing with federal and regional home governments. These MNEs simultaneously utilise multiple strategies while capitalising on their own organisational attributes.

Unlike many other studies, this paper examines institutional complexity within two distinct layers of the Russian Government, regional and federal, rather than considering the aggregate notion of “home government”. The paper also identifies and analyses MNEs’ specific strategies to navigate different layers of institutional complexity.

In recent decades, interest in digital transformation (DX) within the architecture, engineering, and construction (AEC) industry has significantly increased. Despite the existence of several literature reviews on DX research, there remains a notable lack of systematic quantitative and visual investigations into the structure and evolution of this field. This study aims to address this gap by uncovering the current state, key topics, keywords, and emerging areas in DX research specific to the AEC sector.

Employing a holistic review approach, this study undertook a thorough and systematic analysis of the literature concerning DX in the AEC industry. Utilizing a bibliometric analysis, 3,656 papers were retrieved from the Web of Science spanning the years 1990–2023. A scientometric analysis was then applied to these publications to discern patterns in publication years, geographical distribution, journals, authors, citations, and keywords.

The findings identify China, the USA, and England as the leading contributors in the field of DX in AEC sector. Prominent keywords include “building information modeling”, “design”, “system”, “framework”, “adoption”, “model”, “safety”, “internet of things”, and “innovation”. Emerging areas of interest are “deep learning”, “embodied energy”, and “machine learning”. A cluster analysis of keywords reveals key research themes such as “deep learning”, “smart buildings”, “virtual reality”, “augmented reality”, “smart contracts”, “sustainable development”, “building information modeling”, “big data”, and “3D printing”.

This study is among the earliest to provide a comprehensive scientometric mapping of the DX field. The findings presented here have significant implications for both industry practitioners and the scientific community, offering a thorough overview of the current state, prominent keywords, topics, and emerging areas within DX in the AEC industry. Additionally, this research serves as an invaluable reference and guideline for scholars interested in this subject.

This study provides a comprehensive analysis of the transition from Building Information Modelling (BIM) to digital twins (DT) in the construction industry. Specifically, the research explores the current state (themes and trends) and future directions of this emerging research domain.

A multi-stage approach was employed that combines scientometric and systematic review approaches. The scientometric analysis involves quantitative assessment of scientific publications retrieved from the Web of Science database – using software tools like VOSviewer and HistCite. The systematic review involved a rigorous synthesis and evaluation of the existing literature to identify research gaps, themes, clusters and future directions. Clusters obtained from the scientometric analysis of the co-occurrence network were then used as a subject base for a systematic study.

Emergent findings reveal a rapidly growing interest in BIM-DT integration, with over 90% of publications since 2020. The United Kingdom, China and Italy are the leading contributing countries. Five prominent research clusters identified are: (1) Construction 4.0 technologies; (2) smart cities and urban environments; (3) heritage BIM and laser scanning; (4) asset and facility management; and (5) energy and sustainability. The study highlights the potential of BIM-DT integration for enhancing project delivery, asset management and sustainability practices in the built environment. Moreover, the project’s life cycle operation phase has garnered the most attention from researchers in this field compared to other phases.

This unique study is comprehensive in its approach by combining scientometric and systematic methods to provide a quantitative and qualitative evaluation of the BIM-DT research landscape. Unlike previous reviews that focused solely on facility management, this study’s scope covers the entire construction sector. By identifying research gaps, challenges and future directions, this study establishes a solid foundation for researchers exploring this emerging field and envisions the future landscape of BIM-DT integration in the built environment.