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This research aims to investigate consumers' food waste prevention behaviour through the lens of an extended theory of planned behaviour. The extension includes the examination of the role of social media usage in affecting consumers' decision-making process of food waste prevention behaviour.

A survey questionnaire is developed based on measurement items of previously validated studies. 210 samples are collected and analysed using partial least squares structural equation modelling (PLS-SEM).

The results show that social media usage has a significant influence on attitude and injunctive norms. In addition, intention can be predicted by injunctive norms, moral norms and perceived behavioural control but not attitude. Lastly, the intention to reduce food waste is a significant predictor of food waste prevention behaviour.

Overall, the extended theory of planned behaviour is useful in explaining consumers' food waste prevention behaviour. Interestingly, this study reveals that a negative attitude towards food waste behaviour does not translate into the intention to engage in food waste prevention behaviour. Furthermore, it is found that social media usage plays a significant in shaping consumers' attitudes towards food waste and injunctive norms.

Social media influencers (SMIs) have become an important source of influence that affects consumer behaviours in their decision-making processes. As such, this justifies scholarly attention in understanding how SMIs transfer their meanings to endorsed brands and drive consumers’ positive behavioural intentions. With the intention to fill this knowledge gap, this paper aims to examine the impact of SMIs’ credibility, as manifested by trustworthiness, attractiveness and expertise, along with the moderating effects of materialism, on followers’ purchase intention.

Self-administrated online surveys were used to collect data from Instagram users. A total of 191 usable data were collected and analysed using partial least square structural equation modelling.

The results show that SMIs’ trustworthiness and expertise are significant predictors of followers’ purchase intention. Moreover, the moderating effect of materialism on the relationship between attractiveness and purchase intention is significant. Notably, the influence of attractiveness on purchase intention is greater when materialism is high.

This research contributes to the SMI literature by examining the influence of SMIs’ trustworthiness, attractiveness and expertise, along with the moderating effect of materialism, on followers’ purchase intention.

The purpose of this paper is to determine the role of environmental concern on brand preference. The authors also examine whether the proposed relationship is contingent upon the individual’s income.

A conceptual model is proposed based on the theory of buyer behaviour and environmental concern. Model is empirically validated by conducting a survey using self-administered questionnaire. Measurements for each construct were adapted from literature. Partial least square based structural equation modelling is used for the hypotheses testing and confirmatory factor analysis is used for the validation of measurement model.

The authors found that brand preference is influenced by environmental concern and attitude towards the environment-friendly product. Further, social influence indirectly affects brand preference via environmental concern and attitude towards the environment-friendly product. The authors also found that income significantly moderates the relationship between social influence and environmental concern.

This paper provides useful guidance for the marketers of environment-friendly products for marketing to people with different income.

This paper is a study of the current trends and conditions of electronic resources for Chinese studies, based on a recent survey on the Internet of 29 Chinese libraries in North America and eight Chinese libraries in China, Taiwan and Hong Kong. The survey discussed current electronic resources for Chinese studies, with a union list of major Chinese language databases currently used in libraries in Asia and the US. Current views on the use and development of electronic resources for Chinese studies were summarised.

This chapter reports on an ethnographic case study of how a group of elementary school teachers designed technology enhanced learning with mobile technology (e.g. notebooks, tablet computers and mobile phones) to facilitate students’ development of literacy and twenty-first century competencies. These teachers designed the school’s literacy pedagogical approach, leveraging the use of technology, namely digital storytelling. The school in this case study is one of the eight Future Schools in Singapore under the FutureSchools@Singapore program. The school has been providing one-to-one mobile computing learning devices and wireless Internet access for its students. The introduction of technology in the classroom makes it possible for twenty-first century competencies to be integrated into literacy development. The conversational framework is used as a framework to examine how the design of the digital storytelling pedagogical approach brings about the various teaching–learning activities – acquisition, inquiry, practice, production, discussion and collaboration. The use of digital storytelling as an approach to integrate information communication technology (ICT) into the classroom has not only modified how ICT is being used in the school, it has redefined how ICT could be used to engage young learners. It has fundamentally transformed conventional storytelling with the use of current state-of-the-shelf (i.e. easily and widely available) technologies. This case study also outlines the processes involved in improving the design of digital storytelling over the years by the teachers. The ecosystem of the school is also taken into consideration and described in detail. Findings suggest the importance of the collaborative efforts of the teachers in the continuous improvements made to this design. The adoption of a learning design framework, such as the one used in this study, can be beneficial to ensure a systematic approach to the design of learning. In addition, the availability of technological infrastructure and computing devices are necessary for the seamless use of technology in the classroom. The just-in-time learning approach is adopted for students to learn technology as they are developing their digital stories.

The purpose of this paper is to investigate the effects of the environment of a virtual community (users’ interactions inside and outside of a community which are defined as the fundamental and supplemental interaction (FI and SI), respectively) on its users’ knowledge sharing (KS) and the underlying cognitive mechanism.

A survey was conducted among the users who had experience of participating in a domain knowledge specific online community. A total of 479 valid observations were collected. Structural equation modeling was used to test the research model and hypotheses.

The empirical results show that the fundamental interaction (FI) not only directly affects users’ knowledge acquisition (KA) and contribution, but also indirectly affects users’ KA and contribution partially through the users’ self-efficacy and outcome expectation. While the supplemental interaction (SI) negatively affects users’ KA, it positively affects the users’ knowledge contribution and this effect is also partially mediated by the users’ self-efficacy and outcome expectation. The mediators of self-efficacy and outcome expectation play distinct role on users’ KA and contribution in virtual communities (VCs).

This research conceptualizes the users’ interaction inside and outside of a particular virtual community as FI and SI, respectively, and reveals the mechanism how they affect users’ KA and contribution. The results shed light on the literature of KS in VCs and extend social cognitive theory's application into a complex environment with blended interactions in a virtual world. The research also provides insights for virtual community designers, administrators and users.

To improve the efficiency, accuracy and adaptivity of the parameter inversion analysis method of a rockfill dam, this study aims to establish an adaptive model based on a harmony search algorithm (HS) and a mixed multi-output relevance vector machine (MMRVM).

By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. Therefore, the finite element method with time consumption can be replaced by the MMRVM. Because of its excellent global search capability, the HS is used to optimize the kernel parameters of the MMRVM and the material parameters of a rockfill dam.

Because the parameters of the HS and the variation range of the MMRVM parameters are relatively fixed, the HS-MMRVM can imbue the inversion analysis with adaptivity; the number of observation points required and the robustness of the HS-MMRVM are analyzed. An application example involving a concrete-faced rockfill dam shows that the HS-MMRVM exhibits high accuracy and high speed in the parameter inversion analysis of static and creep constitutive models.

The applicability of the HS-MMRVM in hydraulic engineering is proved in this paper, which should further validate in inversion problems of other fields.

An adaptive inversion analysis model is established to avoid the parameters of traditional methods that need to be set by humans, which strongly affect the inversion analysis results. By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. To reduce the data dimensions and verify the model’s robustness, the number of observation points required for inversion analysis and the acceptable degree of noise are determined. The confidence interval is built to monitor dam settlement and provide the foundation for dam monitoring and reservoir operation management.

The purpose of this study is to develop a stochastic finite element method (FEM) to solve the calculation precision deficiency caused by spatial variability of dam compaction quality.

The Choleski decomposition method was applied to generate constraint random field of porosity. Large-scale laboratory triaxial tests were conducted to determine the quantitative relationship between the dam compaction quality and Duncan–Chang constitutive model parameters. Based on this developed relationship, the constraint random fields of the mechanical parameters were generated. The stochastic FEM could be conducted.

When the fully random field was simulated without the restriction effect of experimental data on test pits, the spatial variabilities of both displacement and stress results were all overestimated; however, when the stochastic FEM was performed disregarding the correlation between mechanical parameters, the variabilities of vertical displacement and stress results were underestimated and variation pattern for horizontal displacement also changed. In addition, the method could produce results that are closer to the actual situation.

Although only concrete-faced rockfill dam was tested in the numerical examples, the proposed method is applicable for arbitrary types of rockfill dams.

The value of this study is that the proposed method allowed for the spatial variability of constitutive model parameters and that the applicability was confirmed by the actual project.

This paper investigates the vibration compaction mechanism and evaluates the impact of vibration frequencies on the stability of coarse-grained soil, aiming to optimize the subgrade filling process.

This study examines the vibratory compaction behavior of coarse-grained soils through indoor vibration tests and discrete element simulations. Focusing on angular gravel (breccias) of varying sizes, the simulations were calibrated using parameters such as Young’s modulus, restitution and friction coefficients. The analysis highlights how particle shape influences compaction, revealing mesoscopic mechanisms that drive macroscopic compaction outcomes.

This study investigates the influence of vibration frequency on the compaction behavior of coarse-grained soils using discrete element simulation. By analyzing particle contact and motion, the mesoscopic mechanisms driving compaction are explored. The study establishes a positive linear correlation between contact force anisotropy (Cv) and deformation, demonstrating that higher anisotropy leads to greater structural disruption. Additionally, the increase in sliding contact percentage (SCP) at higher frequencies indicates instability in the skeletal structure, driven by uneven contact force distribution. These findings reveal how frequency-induced stress concentration affects the stability and deformation of the soil skeleton.

This research explores the effect of various vibration frequencies on the compaction behavior of coarse-grained soils, examining microscopic interactions to reveal their impact on soil stability and deformation.

The purpose of this paper is to investigate the effect of doping element on the microwave absorption performance of hexagonal nano boron nitride (h-nBN)-reinforced basalt fabric (BF)/epoxy composites. A new type of hybrid composite that will be produced by the use of boron nitride as an additive that leads to increased radar absorption capability will be developed and a new material that can be used in aeronautical radar applications.

This study is focused on the microwave absorption properties of h-nBN doped basalt fabric-reinforced epoxy composites. Basalt fabric (BF)/epoxy composites (pure composites) and the BF/h-nBN (1 Wt.% h-nBN doped composites) hybrid composites were fabricated by vacuum infusion method. Phase identification of the composites were performed using X-ray diffraction (XRD), the 2θ scan range was from 10 to 60 with the scanning speed of 3°/min and surface morphologies of the composites were investigated using scanning electron microscopy (SEM). Microwave properties of samples were investigated through transmission/reflection measurements in Agilent brand 2-Port PNA-L Network Analyzer in the frequency range of 3–18 GHz. The prepared sample is positioned between two horn antennas with and without metal plate.

Experimental results show that h-nBN doped composite was synthesized successfully and the produced hexagonal nano boron nitride-added fiber laminated composite material has good absorption behavior when they are used with metallic sheets and good for isolation applications at many points in the 3–18 GHz band.

This paper will contribute to the literature on the use of basalt fabric, which are new types of fibers, and hexagonal nano boron nitride and the effects of boron nitride on radar absorption properties of composite material. It presents detail characterization of each composite by using XRD and scanning electron microscopy.