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Blockchain has the potential to facilitate a paradigm shift in the construction industry toward effectiveness, transparency and collaboration. However, there is currently a paucity of empirical evidence from real-world construction projects. This study aims to systematically review blockchain adoption barriers, investigate critical ones and propose corresponding solutions.

An integrated method was adopted in this research based on the technology–organization–environment (TOE) theory and fuzzy decision-making trial and evaluation laboratory (DEMATEL) approach. Blockchain adoption barriers were first presented using the TOE framework. Then, key barriers were identified based on the importance and causality analysis in the fuzzy DEMATEL. Several suggestions were proposed to facilitate blockchain diffusion from the standpoints of the government, the industry and construction organizations.

The results highlighted seven key barriers. Specifically, the construction industry is more concerned with environmental barriers, such as policy uncertainties (E2) and technology maturity (E3), while most technical barriers are causal factors, such as “interoperability (T4)” and “smart contracts' security (T2)”.

This study contributes to a better understanding of the problem associated with blockchain implementation and provides policymakers with recommendations.

Identified TOE barriers lay the groundwork for theoretical observations to comprehend the blockchain adoption problem. This research also applied the fuzzy method to blockchain adoption barrier analysis, which can reduce the uncertainty and subjectivity in expert evaluations with a small sample.

The purpose of this paper is to propose a cross-enterprises framework to achieve a higher level of sharing of knowledge and services in manufacturing ecosystems.

The authors describe the development of the emerging open manufacturing and discuss the model of knowledge creation processes of manufacturers. The authors present a decentralized framework based on blockchain and edge computing technologies, which consists of a customer layer, an enterprise layer, an application layer, an intelligence layer, a data layer, and an infrastructure layer. And a case study is provided to illustrate the effectiveness of the framework.

The authors discuss that the manufacturing ecosystem is changing from integrated and centralized systems to shared and distributed systems. The proposed framework incorporates the recent development in blockchain and edge computing that can meet the secure and distributed requirements for the sharing of knowledge and services in manufacturing ecosystems.

The proposed framework provides a more secure and controlled way to share knowledge and services, thereby supports the company to develop scalable and flexible business at a lower cost, and ultimately improves the overall quality, efficiency, and effectiveness of manufacturing services.

The proposed framework incorporates the recent development in edge computing technologies to achieve a flexible and distributed network. With the blockchain technology, it provides standards and protocols for implementing the framework and ensures the security issues. Not only information can be shared, but the framework also supports in the exchange of knowledge and services so that the parties can contribute their parts.

For mitigating biocorrosion induced by sulfate-reducing bacteria (SRB) in seawater, the zwitterionic molecule layer (ZML) of poly (sulfobetaine methacrylate) is grafted onto B10 surface by chemical vapor deposition and surface-initiated atom transfer radical polymerization.

Energy-dispersive spectroscopy-attenuated total reflectance Fourier transform infrared spectroscopy and static contact angle measurements are used to characterize the as-formed layer.

After surface modification, B10 can significantly reduce SRB adhesion, demonstrating the good antifouling property. Further, the biocorrosion inhibition is investigated by potentiodynamic polarization and electrochemical impedance spectroscopy, indicating that ZML exhibits high resistance to biocorrosion with inhibition efficiency of approximately 90 per cent.

ZML performs a dual feature, i.e. antifouling film and corrosion inhibitor, for the biocorrosion inhibition.

The purpose of this paper is to propose a precise time-optimal path tracking approach for robots under kinematic and dynamic constraints to improve the work efficiency of robots and guarantee tracking accuracy.

In the proposed approach, the robot path is expressed by a scalar path coordinate and discretized into N points. The motion between two neighbouring points is assumed to be uniformly accelerated motion, so the time-optimal trajectory that satisfies constraints is obtained by using equations of uniformly accelerated motion instead of numerical integration. To improve dynamic model accuracy, the Coulomb and viscous friction are taken into account (while most publications neglect these effects). Furthermore, an iterative learning algorithm is designed to correct model-plant mismatch by adding an iterative compensation item into the dynamic model at each discrete point before trajectory planning.

An experiment shows that compared with the sequential convex log barrier method, the proposed numerical integration-like (NI-like) approach has less computation time and a smoother planning trajectory. Compared with the experimental results before iteration, the torque deviation, tracking error and trajectory execution time are reduced after 10 iterations.

As the proposed approach not only yields a time-optimal solution but also improves tracking performance, this approach can be used for any repetitive robot tasks that require more rapidity and less tracking error, such as assembly.

The purpose of this paper was to explore the comparative influential factors affecting the behavioral intention and actual usage of mHealth services in two distinct national environments, i.e. China and Bangladesh, in relation to the international expansion of mHealth services.

In this study, widely accepted Unified Theory of Acceptance and Use of Technology (UTAUT) with two additional variables, i.e. Perceived Reliability and Price Value have been selected as a theoretical framework. Primary data were collected from existing mHealth users among generation Y in both China and Bangladesh. A total of 296 and 250 questionnaires were deemed as usable for data analysis for Bangladesh and China, respectively.

Performance expectancy and social influence had significant impact on the adoption intention of mHealth services for both countries. Effort expectancy and price value were insignificant factors for Bangladesh, whereas facilitating condition and perceived reliability were insignificant for China.

The insights from this study could benefit mHealth services providers and those policymakers who seek to enter the Chinese and the Bangladeshi healthcare market. The dimensions identified in the study are based on a full assessment of mHealth usages experiences. Global service providers can use the dimensions identified by the paper to better assess their service performance on an international level.

The paper is unique in that it is one of the first cross-country examinations of influential factors affecting the adoption of mHealth services in two different countries. This study confirms the applicability of extended UTAUT model in the context of mHealth services among the generation Y in developing countries such as China and Bangladesh.

Blockchain technology (BT) is setting world-shattering standard in all type of transactions in business. BT has the prospective to drastically transform supply chain (SC). The main challenge is to enhance trust among the SC stakeholders. This paper aims to identify and prioritize the factors and its challenges that influence the adoptability of BT in SC. The prioritization of these factors will be helpful to the practitioners to decide the strategy of implementing the BT in SC.

The factors influencing adoption of BT are identified from the review of literature and expert opinion is used to rank the factors influencing the adoptability of BT in SC using grey relational analysis (GRA).

We identified and prioritized key factors: inter-organizational trust and relational governance as organizational challenge, data transparency and data immutability as technological challenge, interoperability and product type as operational challenge and social influence and behavioral intention as social challenge that influences adoptability of BT in SC.

The priority of these factors will guide future researchers and industry practitioners to plan rational and financial strategy for implementing BT in SC.

Ant colony algorithm is widely used in recent years as a heuristic algorithm. It provides a new way to solve complicated combinatorial optimization problems. Having been enlightened by the behavior of ant colony's searching for food, positive feedback construction and distributed computing combined with certain heuristics are adopted in the algorithm, which makes it easier to find better solution. This paper introduces a series of ant colony algorithm and its improved algorithm of the basic principle, and discusses the ant colony algorithm application situation. Finally, several problems existing in the research and the development prospect of ACO are reviewed.