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This paper aims to identify and provide a theoretical explanation for the barriers that hinder the adoption of emerging technologies in the architecture, engineering and construction industry, irrespective of the company’s size, specialization or geographical location. In addition, the paper proposes potential areas for future research in this domain.

A list of barriers hindering the adoption of emerging technologies was identified and clarified using a systematic literature review of various scientific sources.

Twenty-five barriers were recognized and explained and some suggestions for future research studies were provided.

The barriers related to a specific country or region or to a specific technology were excluded.

By providing a deeper comprehension of the barriers hindering the adoption of emerging technologies, this review is expected to encourage their adoption in the industry. Furthermore, it could prove valuable in devising effective strategies for the successful implementation of these technologies.

The purpose of this study is to examine employees' perceived influence of the learning organization culture and learning goal orientation on their knowledge sharing attitude and intention across multiple industries. In connecting these concepts, the researchers incorporated theories of the knowledge-based firm, goal orientation and reasoned action.

A survey was used to collect data from a total of 323 responses from eight South Korean organizations to examine the influence of organizational and individual learning factors on employees' knowledge sharing. Structural equation modeling showed that the proposed research model was supported by item internal consistency and model-fits.

Results indicated that employees' learning goal orientation, knowledge sharing attitude and learning organization culture positively influence employees' knowledge sharing intention. This study highlights that those employees are more likely to share knowledge when employees with high learning goal orientation form a positive attitude toward knowledge sharing in a learning supportive culture and structure.

This study added to the literature of learning organizations by identifying a strong positive connection between the learning organization culture and employees' knowledge sharing. The theoretical contribution of this study lies in which the important roles were extended that the learning goal orientation exerts on employee behaviors when they perceive the organization valuing learning.

At the onset of the COVID-19 pandemic, social distancing measures and diffuse communication by media led to consumers’ uncontrolled product purchases worldwide. This phenomenon was described as a psychological effect experienced by fictitious scarcity, anxiety and herd mentality exacerbated by the media. This exploratory study aims to analyze the impact of risk communication on the perceived risk from the psychological dimension of consumer behavior amid the COVID-19 pandemic.

An exploratory study was conducted through an electronic survey one week after implementing social distancing measures in Puerto Rico. With a sample of 353 participants, the data analysis was carried out by PLS-SEM, partial least squares structural equations (PLS-MGA), multi group test (MGA) and hierarchical component models to answer the research hypotheses.

The results revealed that risk communication activates the perceived psychological risk during the COVID-19 pandemic, and the way in which the consumer faces the psychological risk is explained by the perceptions of scarcity and the bandwagon effect.

To the best of the authors’ knowledge, this study is a pioneer in presenting relationships between risk communication and perceived risk in consumer behavior, a topic that needs to be addressed in the academic literature. The research makes significant contributions to the study of consumer behavior by empirically validating the three phases of the Conchar model – risk framing, risk assessment and risk evaluation – where risk communication offers an excellent delineation to understand the consumer’s behavior during a pandemic.

The commonly used e-procurement systems still show unsatisfactory implementation outcomes because many organisations are still unable to effectively interpret the initial adoption decision. The e-procurement systems are generally developed at organisational level, but their usage is at individual level, by the employees particularly. This paper examined technology acceptance model’s (TAM) key antecedents, involving e-procurement systems usage by employees in their daily activities. This study aims to examine the impact of factors affecting e-procurement acceptance among users through the mediating role of users’ attitude. The commonly used e-procurement systems still show.

TAM was applied and expanded in this study, in exploring the factors impacting the employees’ e-procurement acceptance. This study used quantitative method, and questionnaires were distributed to 200 users in Jordanian public shareholding firms. The collected data were quantitatively analysed using PLS modelling.

Significant TAM relationships involving e-procurement were affirmed. The expanded TAM in the scrutiny of antecedents showed that content, processing and usability affected perceived usefulness, while perceived convenience did not affect the usefulness factor. Furthermore, it was noticed that perceived ease of use was affected by usability and training, while perceived connectedness was not affected by usability and training.

The results demonstrated the necessity of e-procurement training. Furthermore, at the start of the implementation stage, effective design on system navigation and system usability, and consistent support, could increase use effectiveness and acceptance. Also, expedient information and buyer–supplier product flows should be made available.

Most organizations invest a lot of time and money in installing e-procurement systems to deliver their goods at the right time and at the right price. However, many of these e-procurement systems have failed due to low acceptance among users. Thus, to the best of the authors’ knowledge, this is the first study that used TAM and theory of planned behaviour in examining the effects of perceived convenience, perceived connectedness, content, training, processing and usability factors, in Jordanian firms. Lastly, the focus of this study was on the individual employee’s acceptance, rather than on the organisational-level adoption, as the unit of analysis, to provide insight on how organisations can achieve maximally from e-procurement investments and from other comparable technologies of e-supply chain management.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

The principal research objective entails examining the nexus between green supplier selection and green performance while scrutinizing the moderating role of governance mechanisms, specifically process control and outcome control, in shaping this association.

To assess our hypotheses, this study obtained data from Chinese manufacturing sectors and utilized regression analysis on a dataset consisting of 295 samples.

This study enriches the sustainable supply chain management literature by emphasizing the influence of green supplier selection on a firm’s green performance and the moderating effects of outcome and process control, offering practical insights for industry professionals.

This study enriches the sustainable supply chain management literature by emphasizing the influence of supplier selection on a firm’s environmental performance and the moderating effects of outcome and process control, offering practical insights for industry professionals.

This study aims at two objectives, i.e. first, to identify the core elements of the Islamic fintech ecosystem, and second, to use the identified core elements to analyse the development of such an ecosystem in Indonesia.

This work combines data analytics of text mining with qualitative analysis of human intelligence in two steps. First, knowledge discovery of the Islamic fintech ecosystem’s core elements using a sample of eight academic articles totalling 102 pages and 75,082 words. Second, using the identified core elements from step one to explore such ecosystem development in Indonesia. This stage employs a sample of 11 documents totalling 371 pages and 143,032 words from cyberspace.

The core elements of the Islamic fintech ecosystem identified are financial customers, fintech startups, government, technology developers, traditional financial institutions and fatwa (Islamic legal opinion). Furthermore, the development of the Islamic fintech ecosystem in Indonesia is examined under these identified core elements, providing critical insights into the Islamic fintech ecosystem currently established in the country's industry.

This study primarily used semi-structured data from cyberspace. Traditional approaches to qualitative data collection, e.g. focused group discussions and interviews, may be beneficial for future studies in addressing the Islamic fintech ecosystem issues.

Academia worldwide may benefit from this work in incorporating knowledge of Islamic fintech ecosystem’s core elements into Islamic finance literature. Specifically, fintech stakeholders in Indonesia may be advantaged to understand how far the Islamic fintech ecosystem has grown in the country.

The rise of unethical fintech peer-to-peer lending shows social problems in Indonesia’s fintech industry. The finding derives social implications that elucidate the current state of the country’s Islamic fintech ecosystem.

Using a kind of big data (i.e. semi-structured text data) from cyberspace and applying steps of text mining combined with qualitative analysis, may contribute to the creation of novelties for qualitative research on financial issues.

To solve the shortcomings of existed search and rescue drones, search and rescue the trapped people trapped in earthquake ruins, underwater and avalanches quickly and accurately, this paper aims to propose a four-axis eight-rotor rescue unmanned aerial vehicle (UAV) which can carry a radar life detector. As the design of propeller is the key to the design of UAV, this paper mainly designs the propeller of the UAV at the present stage.

Based on the actual working conditions of UAVs, this paper preliminarily estimated the load of UAVs and the diameters of propellers and designed the main parameters of propellers according to the leaf element theory and momentum theory. Based on the low Reynolds number airfoil, this paper selected the airfoil with high lift drag ratio from the commonly used low Reynolds number airfoils. The chord length and twist angle of propeller blades were calculated according to the Wilson method and the maximum wind energy utilization coefficient and were optimized by the Asymptotic exponential function. The aerodynamic characteristics of the designed single propeller and coaxial propeller under different installation pitch angles and different installation distances were analyzed.

The results showed that the design of coaxial twin propellers can increase the load capacity by about 1.5 times without increasing the propeller diameter. When the installation distance between the two propellers was 8 cm and the tilt angle was 15° counterclockwise, the aerodynamic characteristics of the coaxial propeller were optimal.

The novelty of this work came from the conceptual design of the new rescue UAV and its numerical optimization using the Wilson method combined with the maximum wind energy utilization factor and the exponential function. The aerodynamic characteristics of the common shaft propeller were analyzed under different mounting angles and different mounting distances.

Public–private partnership (PPP), a project financing arrangement between private investors and the public sector, has revolutionized the approach to the funding and development of public infrastructure worldwide. However, the increasing cases of financial risks and poor financial risk management related to the model threaten the sustainability and financial success of PPP projects leading to huge financial investment losses. This study aims to review existing literature to establish the key measures to control the financial risks of sustainable PPP projects.

A PRISMA-compliant systematic literature review method was used in this study. Data were sourced from academic databases consisting of 56 impactful peer-reviewed journal articles.

The review outcomes demonstrate 41 critical factors (measures) in mitigating the financial risks of sustainable PPP projects. They include minimum revenue guarantee, strategic alliance with private investors, financial transparency and accountability and sound macroeconomic policies. The principal results of the study were categorized and conceptualized into a financial risk management maturity model for sustainable PPP projects. Lastly, the study reveals that further studies and project policies must focus more on addressing financial challenges relating to climate risks, and health and safety concerns such as COVID-19 outbreak that have negative impacts on PPP projects.

The results provide essential research gaps and directions for future studies on measures to mitigate the financial risks of sustainable PPP projects. However, this study used small but significant existing publications.

A checklist and a conceptual maturity model are provided in this study to help practitioners to learn and improve upon their practices to mitigate the financial risks of sustainable PPP projects.

This study contributes to managerial measures to reduce huge losses in financial investments of PPP projects and the attainment of sustainability in public infrastructure projects with a financial risk maturity model.

Blockchain technology offers numerous venues for supply chain applications and research. However, the connections between specific blockchain features and future applications have been unclear to date in its evolution. The purpose of this study is to fill this void.

The authors advance the understanding of blockchain in supply chain management by providing a new research framework built on unique blockchain features as applied across core supply chain functions.

This study’s framework is a feature-function matrix that integrates four overarching supply chain functions (i.e. supplier management, logistics, production processes and customer management) with nine blockchain features (i.e. traceability/provenance, accessibility, visibility, immutability, distributed/shared ledger, validity, peer-to-peer transacting, pseudonymity and programmability). This study’s feature-function framework is supported by a structured, systematic review of reviews using PRISMA methods. The authors use the framework to present a future blockchain research agenda in supply chain management.

The authors provide a new blockchain feature/supply chain function framework and provide a structured path for future research.