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This paper aims to refine the mechanisms affecting the two-way technology spillover and carbon transfer interactions between supply chain enterprises, and to guide their reduction of carbon emissions.

This study formulates a supplier-led Stackelberg game model to explore the effects of the interactions between two-way technology spillover effects and carbon transfers in decentralized and centralized decision-making scenarios. The optimized Shapley value is introduced to coordinate across the supply chain and determine the overall profits lost in the decentralized scenario.

Emission reductions by the low-carbon manufacturer are negatively correlated with the carbon transfers. Vertical technology spillovers promote carbon reduction, whereas horizontal technology spillovers inhibit it. The vertical technology spillovers amplify the negative effects of the carbon transfers, whereas the horizontal technology spillovers alleviate these negative effects. When the vertical technology spillover effect is strong or the horizontal technology spillover effect is weak in the centralized scenario, the carbon reduction is negatively correlated with the carbon transfers. Conversely, when the vertical technology spillover effect is weak or the horizontal technology spillover effect is strong, the enterprise’s carbon reduction is positively correlated with the carbon transfers. An optimized Shapley value can coordinate the supply chain.

This study examines the effects of carbon transfers on enterprises from a micro-perspective and distinguishes between vertical and horizontal technology spillovers to explore how carbon transfers and different types of technology spillovers affect enterprises’ decisions to reduce carbon emissions.

Green construction is increasingly vital in promoting sustainability within the construction industry. The development and promotion of green construction technologies are central to this endeavor. However, existing evaluations mainly target building components, construction projects or certain construction processes. There is a notable absence of research into the greenness of construction technologies. Assessing the greenness of construction technologies is crucial for streamlining resource utilization and reducing waste. To address this gap, this study aims to establish a Greenness of Construction Technologies (GCT) evaluation model using the method of analytic network process (ANP).

Green construction is increasingly vital in promoting sustainability within the construction industry. The development and promotion of green construction technologies are central to this endeavor. However, existing evaluations mainly target building components, construction projects or certain construction processes. There is a notable absence of research into the greenness of construction technologies. Assessing the greenness of construction technologies is crucial for streamlining resource utilization and reducing waste. To address this gap, this study establishes a GCT evaluation model using the method of ANP.

Among the four formwork technologies of plastic, steel, plywood and wooden formwork, the plastic formwork exhibits the best performance in terms of environmental friendliness, economic and social effects, while facing issues like material wastage and low static strength. The results align with practical observations which validates the model’s applicability.

This research contributes to the field by introducing the concept of greenness into construction technology evaluation for the first time. The establishment of the GCT evaluation model promotes the adoption of green construction technologies and advances sustainable practices in the construction industry.

Trust plays a crucial role in overcoming uncertainty and reducing risks. Uncovering the trust mechanism in the sharing economy may enable sharing platforms to design more effective marketing strategies. However, existing studies have inconsistent conclusions on the trust mechanism in the sharing economy. Therefore, this study aims to investigate the antecedents and consequences of different dimensions of trust (trust in platform and trust in peers) in the sharing economy.

First, we conducted a meta-analysis of 57 related articles. We tested 13 antecedents of trust in platform (e.g. economic benefits, enjoyment, and information quality) and eight antecedents of trust in peers (e.g. offline service quality and providers’ reputation), as well as their consequences. Then, we conducted subgroup analyses to test the moderating effects of economic development level (Developed vs Developing), gender (Female-dominant vs Male-dominant), platform type (Accommodation vs Transportation), role type (Obtainers vs Providers), and uncertainty avoidance (Strong vs Weak).

The results confirm that all antecedents and consequences significantly affect trust in platform or peers to varying degrees. Moreover, trust in platform greatly enhances trust in peers. Besides, the results of the moderating effect analyses demonstrate the variability of antecedents and consequences of trust under different subgroups.

This paper provides a clear and holistic view of the trust mechanism in the sharing economy from an object-based trust perspective. The findings may offer insights into trust-building in the sharing economy.

Rice agroecosystems must grow sustainably to meet the increasing demand for food. A fish-rice co-culture was introduced to conserve rice agroecosystems in farming communities. This study aims to assess the technical, socio-economic and environmental outcomes as the pillars of sustainability.

This study employs a mixed qualitative-quantitative approach to assess a sustainable intensification programme's impact on sustainability. Data were collected using group discussions and self-assessment surveys. The study sites cover East Java and West Java provinces.

This study found that rice-fish co-culture improved the sustainability of the farming system. Farmers applied pest and disease management and partially substituted inorganic fertilisers with organic ones. The outcomes were apparent in the diversity of harvested products. Economically, the rice yield increased, the production costs decreased and the resultant increased income. Environmentally, the fish-rice co-culture was sound because of ecological inputs. The population of natural enemies of pests increased. Socially, fish-rice co-culture was acceptable to the community since there was no conflict with the local governments, local norms and religions and the existing farming practices of other crops.

This study was based on five groups as case studies, such that the result might not represent the general condition.

The study's methodology was supported by valid economic theories and data directly gathered from farmers.

The paper aims to study the constraint solutions of the periodic coupled operator matrix equations by the biconjugate residual algorithm. The new algorithm can solve a lot of constraint solutions including Hamiltonian solutions and symmetric solutions, as special cases. At the end of this paper, the new algorithm is applied to the pole assignment problem.

When the studied periodic coupled operator matrix equations are consistent, it is proved that constraint solutions can converge to exact solutions. It is demonstrated that the solutions of the equations can be obtained by the new algorithm with any arbitrary initial matrices without rounding error in a finite number of iterative steps. In addition, the least norm-constrained solutions can also be calculated by selecting any initial matrices when the equations of the periodic coupled operator matrix are inconsistent.

Numerical examples show that compared with some existing algorithms, the proposed method has higher convergence efficiency because less data are used in each iteration and the data is sufficient to complete an update. It not only has the best convergence accuracy but also requires the least running time for iteration, which greatly saves memory space.

Compared with previous algorithms, the main feature of this algorithm is that it can synthesize these equations together to get a coupled operator matrix equation. Although the equation of this paper contains multiple submatrix equations, the algorithm in this paper only needs to use the information of one submatrix equation in the equation of this paper in each iteration so that different constraint solutions of different (coupled) matrix equations can be studied for this class of equations. However, previous articles need to iterate on a specific constraint solution of a matrix equation separately.

Knowing financial and economic information beforehand benefits in planning and developing policies for every country especially for a developing country like Thailand and for other Asian countries. Unfortunately, missing data or non-response plays an essential role in many areas of studies including finance and economics. Eradication of missing data in a proper way before further analysis can gain remarkable outcomes and can be effective for planning policies. This review on the generalized regression estimators for population total can be applied to financial, economic and other data when missing data are present.

The generalized regression estimators for estimating population total, including the variance estimators under unequal probability sampling without replacement with missing data are explored under the reverse framework. Applications to financial and economic data in Thailand are also reviewed.

The review of literatures related to the proposed estimator shows the best performance, giving smaller variances in all scenarios.

The generalized regression estimators can assist in estimating financial and economic data that contain missing values with different missing mechanisms and can be used in other applications which help gain more superior estimators.

To improve the robustness of carrier-based unmanned aerial vehicle (UAV) with actuator faults attitude tracking control system, this paper aims to propose a fixed-time backstepping (FXTBSC) fault-tolerant control based on a fixed-time extended state observer.

A fixed-time extended state observer (FXTESO) is designed to estimate the total disturbance including nonlinear, coupling, actuator faults and external disturbances. The integration of backstepping control and fixed-time technology ensures fixed-time convergence.

The simulation results of tracking the desired attitude angle show that the anti-interference, fault tolerance and tracking accuracy of FXTBSC-FXTESO are better than the BSC-ESO control method.

Different from the traditional BSC-ESO, the convergence speed and convergence accuracy of FXTBSC-FXTESO proposed in this paper are better than conventional extended state observer. And the fixed time controller has the advantages of high tracking accuracy, fault tolerance and anti-interference ability.

This study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).

A composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.

First, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.

First, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

This study aims to investigate the formation and characteristics of Taylor bubbles resulting from short-time gas injection in liquid-conveying pipelines. Understanding these characteristics is crucial for optimizing pipeline efficiency and enhancing production safety.

The authors conducted short-time gas injection experiments in a vertical rectangular pipe, focusing on Taylor bubble formation time and stable length. Computational fluid dynamics simulations using large eddy simulation and volume of fluid models were used to complement the experiments.

Results reveal that the stable length of Taylor bubbles is significantly influenced by gas injection velocity and duration. Specifically, high injection velocity and duration lead to increased bubble aggregation and recirculation region capture, extending the stable length. Additionally, a higher injection velocity accelerates reaching the critical local gas volume fraction, thereby reducing formation time. The developed fitting formulas for stable length and formation time show good agreement with experimental data, with average errors of 6.5% and 7.39%, respectively. The predicted values of the formulas in glycerol-water and ethanol solutions are also in good agreement with the simulation results.

This research provides new insights into Taylor bubble dynamics under short-time gas injection, offering predictive formulas for bubble formation time and stable length. These findings are valuable for optimizing industrial pipeline designs and mitigating potential safety issues.