Search results

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.

This paper aims to enhance the machining accuracy of hybrid robots by treating the moving platform as the first joint of a serial robot for direct position measurement and integrating external grating sensors with motor encoders for real-time error compensation.

Initially, a spherical coordinate system is established using one linear and two circular grating sensors. This system enables direct acquisition of the moving platform’s position in the hybrid robot. Subsequently, during the coarse interpolation stage, the motor command for the next interpolation point is dynamically updated using error data from external grating sensors and motor encoders. Finally, fuzzy proportional integral derivative (PID) control is applied to maintain robot stability post-compensation.

Experiments were conducted on the TriMule-600 hybrid robot. The results indicate that the following errors of the five grating sensors are reduced by 94%, 93%, 80%, 75% and 88% respectively, after compensation. Using the fourth drive joint as an example, it was verified that fuzzy adaptive PID control performs better than traditional PID control.

The proposed online error compensation strategy significantly enhances the positional accuracy of the robot end, thereby improving the actual processing quality of the workpiece.

This method presents a technique for achieving online error compensation in hybrid robots, which promotes the advancement of the manufacturing industry.

This paper proposes a cost-effective and practical method for online error compensation in hybrid robots using grating sensors, which contributes to the advancement of hybrid robot technology.

This paper aims to investigate the preparation of Nano-Al₂O₃ lubricant, as well as the effect of surface modification of Al₂O₃ on friction and wear properties.

The chemical parameters such as the energy levels of the Highest Occupied Molecular Orbital, the Lowest Unoccupied Molecular Orbital and the Fukui indices of seven modifiers, including myristic acid myristyl ester, glycerol trioleate, acetyl monoethanolamine, docosanamide, Tween-60, dodecyl dihydroxyethyl amine oxide and sodium dodecyl sulfate (SDS), are calculated by using the Materials Studio software. Meanwhile, the adsorption energies of these seven modifiers on Al₂O₃ nanoparticles are also calculated. Based on the simulation results, SDS and Tween-60 were identified as the most effective surface modifiers. Modified lubricants were prepared with Al₂O₃ nanoparticles at varying concentrations (0.1–0.4 Wt.%). Their tribological properties, including the maximum nonseizure load (P_B) and the coefficient of friction (COF), were evaluated using a four-ball wear tester. The worn surfaces were analyzed by scanning electron microscopy and three-dimensional profilometry.

The results indicate that SDS improves both the extreme pressure and anti-wear performance of the lubricant. The lubricant achieves optimal performance when combined with 1.0 Wt.% SDS and 0.2 Wt.% nano-Al₂O₃. At this combination, the value of PB reaches 209 N, and the value of COF is approximately 0.072. Compared to the unmodified Al₂O₃ lubricant with a COF of 0.086, this represents a 23% reduction in COF.

Modified Al₂O₃ lubricants demonstrate superior lubrication performance and effectively reduce the COF, providing valuable insights for the practical application of nanolubricants.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0353/

This study aims to investigate the micro mechanism of macro rheological characteristics for composite modified asphalt.Grey relational analysis (GRA) was used to analyze the correlation between macro rheological indexes and micro infrared spectroscopy indexes.

First, a dynamic shear rheometer and a bending beam rheometer were used to obtain the evaluation indexes of high- and low-temperature rheological characteristics for asphalt (virgin, SBS/styrene butadiene rubber [SBR], SBS/rubber and SBR/rubber) respectively, and its variation rules were analyzed. Subsequently, the infrared spectroscopy test was used to obtain the micro rheological characteristics of asphalt, which were qualitatively and quantitatively analyzed, and its variation rules were analyzed. Finally, with the help of GRA, the macro-micro evaluation indexes were correlated, and the improvement efficiency of composite modifiers on asphalt was explored from rheological characteristics.

It was found that the deformation resistance and aging resistance of SBS/rubber composite modified asphalt are relatively good, and the modification effect of composite modifier and virgin asphalt is realized through physical combination, and the rheological characteristics change with the accumulation of functional groups. The correlation between macro rutting factor and micro functional group index is high, and the relationship between macro Burgers model parameters and micro functional group index is also close.

Results reveal the basic principle of inherent-improved synergistic effect for composite modifiers on asphalt and provide a theoretical basis for improving the composite modified asphalt.

This paper divides the dyadic supply chain into three power structures according to the relative channel power of the supply chain members and consequently examines the optimal supply chain pricing decisions when both suppliers and retailers are concerned with fairness issues.

Three models are constructed, namely the Stackelberg game model with the supplier as the leader, the Nash game model with the balance of power and another Stackelberg game model with the retailer as the leader. The equilibrium solutions are solved, and their results are analyzed.

The retail price of a product increases with an increase in the fairness concerns of the leader in a supply chain in which the supplier or retailer is the leader, while the fairness concerns of the member with less channel power have no effect on the retail price. In a power-balanced supply chain, both suppliers and retailers increase their retail prices as their fairness concerns increase. The relative size of the members’ fairness concerns affects member profits and total supply chain profits.

The main contributions are as follows: First, this paper proposes a new approach to studying supply chain pricing strategy, considering fairness concerns and power structure. Secondly, three game models are constructed. The Nash equilibrium solution is introduced to study the fairness of supply chain participants in pricing decisions and overall supply chain profitability. Finally, the supply chain management theory is expanded by this study on pricing decisions and supply chain performance.

This study aims to explore the relationship between brand image and buying intentions, which is crucial in understanding consumer buying behaviour. This study aims to review the literature, identify research trends and further suggests research directions for future study.

A bibliometric analysis was conducted on 402 research articles extracted from the Scopus database, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. The study includes performance analysis, science mapping and network visualization, with VOSviewer and Biblioshiny software for the analysis. It examines publication trends, prolific countries, institutions, authors, highly cited papers, keyword co-occurrence and thematic evolution for a comprehensive analysis.

The study reveals the increasing scholarly interest of researchers in brand image and purchase intention over time and identified various research themes. Results state that Brand image and purchase intention themes remained central throughout both time zones (1995–2012 and 2013–2024). Emerging themes of the field include green marketing, corporate social responsibility, influencer marketing and entrepreneurial marketing.

This research study makes an addition to the body of literature by identifying the research hotspots and areas that need further investigation. Further, the thematic evolution of the brand image and purchase intentions illustrates how perception at various consumer levels and decision-making process has shifted over time in response to changing market dynamics. This study is of quite paramount importance for a vast group of stakeholders including researchers, businesses, brand managers, policy makers, marketing professionals and future research scholars.