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At present, teaching methods based on 2D drawings are still commonly used for educating students on the location of steel reinforcement bars in concrete. However, traditional teaching methods have limitations as students can find it difficult to understand 2D drawings. This study aims to develop an interactive and collaborative augmented reality environment (ICARE) using augmented reality (AR) technology to improve students' engagement in learning.

This study develops an ICARE prototype, which is organized into two stages: (1) The augmented teaching environment comprising of models and interactive components; (2) The AR collaborative application which uses Photon Unity Networking (PUN) plugin and Azure spatial anchors cloud service. The AR-based teaching environment runs with Universal Windows Platform (UWP) to enable development in the HoloLens 2 through Microsoft Visual Studio.

An experimental study was conducted, where 60 students were divided into three groups employing Drawings-based, building information modeling (BIM)-based and AR-based methods for teaching. After the test, the three groups of students were requested to complete a questionnaire. According to the analysis of the experimental results, the ICARE can improve students' comprehension, memory of learned materials and their ability to read and understand steel reinforcement drawings improving the quality of teaching, especially interactivity and engagement.

As illustrated in the experiments, the developed ICARE has outstanding performance over conventional approaches in civil engineering courses that can improve students' comprehension and memory of knowledge and their ability to read and understand steel bar drawings. This study provides empirical evidence that AR is a promising technology that can be integrated with traditional classroom instruction and can improve students' comprehension and memory of knowledge and their ability to read and understand steel bar drawings.

Recently, the concept of financial technology (FinTech) has attracted extensive attention from international organisations and regulators, in particular, how to achieve a “win–win” situation between financial institutions' FinTech innovation and effective regulation has become a hot topic. This study purposes to explore the evolutionary game relationship between FinTech innovation and regulation by constructing both static and dynamic earmarking game models.

A simulation experiment was conducted using primary data obtained from a commercial bank in China.

The results of the theoretical analysis of evolutionary game models were consistent with the corresponding simulation results, proving the validity of the proposed evolutionary game models. It was also found that the dynamic earmarking game model was more stable and effective than the static earmarking game model in promoting FinTech innovation and regulation. Furthermore, when the regulators utilised a dynamic earmarking mechanism, the evolutionary path of financial institutions and regulators' behaviour strategies took the shape of a spiral and eventually converged to a central point, indicating the existence of an evolutionary stable strategy and Nash equilibrium. Finally, because the behaviour strategies of financial institutions were mainly influenced by the regulators' policies, the regulators were inspired to adjust the corresponding regulation policies on FinTech innovation.

This study bridges the knowledge gap in the existing literature on financial innovation and regulation, in particular by establishing evolutionary game models from the perspective of financial earmarking policies. Also, the case study for simulation experiments can gain a more intuitive insight into FinTech innovation and financial earmarking policies.

This study is aimed to explore the dynamic performance incentive model for a flexible PPP contract to handle uncertainties based on supervision during the long-time concession period, so as to ensure operation performance and benefits of the public sector while protecting the economic benefit of the private sector, thus avoiding unnecessary renegotiation.

The microeconomic and principal–agent theories and relevant studies on the basic incentive model and flexible contract are fully utilized. The procedure for developing the dynamic incentive model and the assumptions about the quantitative relationships among fundamental variables or factors are first proposed. The static incentive model without incentive parameter adjustment and then the dynamic incentive model allowing incentive parameter adjustment are successively developed. Finally, the propositions regarding the valid adjustment ranges of the incentive parameter with respect to the economic, social and hybrid benefits of the public sector and the economic benefit of the private sector are suggested.

The dynamic incentive model enables to achieve a flexible contract to handle uncertainties on the PPP project to ensure the benefits of the public sector while protecting the benefit of the private sector. The economic, social and hybrid benefits of the public sector and the economic benefit of the private sectors can be respectively realized through adjusting the reward–punishment coefficient under different adjustment ranges and different importance. The incentive model is able to ensure the benefits of the public sector while protecting the benefit of the private sector by controlling the private sector's effort level unknown to the public sector.

The dynamic incentive model helps implement a flexible PPP contract to handle uncertainties during the operation period, thus controlling the effort level of the private sector and ensuring the benefits of the public sector while protecting the economic benefit of the sector. It enables to clarify the quantitative relationships between the operation performance, the benefits of the stakeholders, the effort level of the private sector and the reward–punishment coefficient. This study contributes to the domain knowledge of the incomplete contract theory for designing a flexible PPP contract with dynamic incentive and supervision mechanism by applying the microeconomic and principal–agent theories.

The purpose of this paper is to establish the influence of shopping motivations on Chinese fashion retail engagement relative to demographics, monthly spend on fashion items and high street/electronic commerce (e-commerce) preference. This is to determine how international fashion retailers should design more effective retails channels, expanding upon established theory in Hedonic and utilitarian motivations. While earlier research suggests shopping motivations associate with demographics while influencing retail channel preference and consumer spending, much of this exploration is Western focused, with all variables being influential. However, the degree to which these apply to China, and the unique fingerprint of influential motivations remains unknown. This paper answers these questions to allow international retailers to develop more efficient marketing strategies and design more effective retail channels.

In all, 403 Chinese consumers generalisable to the broader population were surveyed on their hedonic and utilitarian motivations to shop for fashion apparel in high street and e-commerce environments. Statistical analysis was commenced through direct logistic regression and MANOVA.

Demographics have limited association with shopping motivations, with gender and age only producing small effect sizes, while occupation, income and education has no significance. High street store preference is influenced by adventure and social shopping and e-commerce preference only by idea shopping. Spending over ¥1k per month on fashion apparel is influenced by gratification and idea shopping, and regular spending habits inspired by value shopping.

This empirical paper characterises the fingerprint of shopping motivations’ influence as singular to China while proving their limitation and need for a wider plethora of influential factors to be recognised.

With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion.

The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods.

Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level.

Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.

Interpersonal interaction can influence consumers’ purchase intention in social commerce (s-commerce). This paper aims to identify interpersonal interaction factors as well as the mediating effect of relationship quality between interpersonal interaction factors and consumers’ purchase intention in s-commerce.

This study explores new dimensions of interpersonal interaction in s-commerce by integrating interaction between consumers and online vendors and that between consumers and online recommenders in s-commerce. An online questionnaire was used to collect the data, and partial least squares structural equation modeling (PLS-SEM) was employed for data analysis.

The results indicate that interpersonal interaction factors of both online vendors and online recommenders positively affect swift guanxi and initial trust between consumers and online vendors. Swift guanxi and initial trust positively affect consumers’ purchase intention. Initial trust partially mediates between interpersonal interaction factors and purchase intention while swift guanxi does not mediate between perceived similarity of online recommenders and purchase intention.

The findings can be used to guide vendors in s-commerce platforms to make good use of platform features to improve interpersonal interaction. Meanwhile, s-commerce platforms should be enhanced with efficient interaction tools to help cultivate relationship quality between consumers and online vendors.

This study combines social exchange theory, trust transfer theory and relationship quality theory to investigate the factors that influence swift guanxi and initial trust between consumers and online vendors, which extends the study of interpersonal interaction and enriches the dimensions of relationship quality in the context of s-commerce.

The literature shows that e-commerce adoption brings many benefits to farmers and agricultural businesses. However, the literature offers very limited guidance on the most effective ways for them to utilize e-commerce platforms. In this study, we unfold how a farmer's choice between endogenous (their own) vs. exogenous (third-party) e-commerce platforms should be aligned with the external (support from agricultural cooperative) and internal (usage of quality labels) resources they can leverage and the performance goals they want to achieve (market expansion vs. price premium).

Our study draws on transaction cost economics (TCE) and resource-based theory (RBT) to test the conceptual model with data from a cross-sectional survey of 324 farmers from two provinces in PR China.

Our findings show that external and internal resources shed additional light on the effectiveness of endogenous vis-à-vis exogenous e-commerce platforms. For farmers who rely on exogenous e-commerce, support from an agricultural cooperative appears to be critical in increasing their market expansion. On the other hand, farmers seeking to earn a price premium should focus on developing their own e-commerce platforms, while at the same time emphasizing the quality labels of their agricultural products.

Farmers should pay close attention to the value-added benefits provisioned through farmers' cooperatives, as well as the benefits of acquiring quality labels for their agricultural products. However, the decision to utilize these resources should be aligned with the chosen e-commerce platform (endogenous vs. exogenous) as well as with the performance goal the farmer wants to achieve.

Our work goes beyond the traditional focus on transaction costs and efficiency of e-commerce channels and provides specific insights into when an endogenous or exogenous e-commerce model might provide benefits for farmers. On top of this, we argue and show that this decision should reside with the farmer's ability to leverage external and internal resources, envisioned through support from an agricultural cooperative and the quality labels of agricultural products.

Virtual try-on apps (VTOs) hold great potential to transform online apparel shopping, yet their acceptance by consumers has been lukewarm. By drawing on two theories – Sirgy’s theory of the self and Sundar’s theory of interactive media effects (TIME) – the study tests a PLS model with two new constructs: Photo Satisfaction and Consumer Inspiration, and their impact on Adoption Intention.

This mixed methods study examines the effects from personalization and customization affordances in the latest generation of apparel VTOs. The proposed model was tested in a quasi-experimental within-subjects design, as 61 female participants completed a goal-directed and an exploratory apparel shopping task using two VTO apps available on the market.

Inspiration induced from the customization affordance in the exploratory task influenced Adoption Intention as strongly as Fit Confidence did. For both conditions, users’ satisfaction with their avatar picture had a stronger effect on Perceived Augmentation than the individual trait of Body Esteem. The study also demonstrates how TIME’s Sense of Agency component could help theorize positive consumer responses to mobile marketing technology, which in our study were induced via the app’s Mix and Match feature. Also demonstrated was that Perceived Augmentation could be influenced by body-image affective judgments made during the pre-task VTO avatar creation phase.

VTO’s customization feature “Mix and Match” appears vital for the adoption of such apps for exploratory m-shopping of apparel. Also important is the satisfaction with one's photograph during the avatar-creation phase. We further suggest that apparel retailers work with Augmented Reality developers to include dynamic avatar capability as well as social sharing affordances in VTOs.

60 billion USD worth of returns occur annually in the online apparel retail industry, mostly related to fitting problems, not to mention the larger carbon footprint from the increased transportation. A more wide-spread adoption of VTOs can not only help with these problems but also lighten the traffic in brick and mortar fitting rooms, a potential hazard at this time of pandemic.

This is the first study to examine Consumer Inspiration in the context of online apparel retailing and to demonstrate the importance of Photo Satisfaction during the avatar-creation phase in influencing the subsequent user experience in apparel VTOs.

The purpose of this paper is to identify the design elements of environmental features that affect consumer experience in shopping malls and develop a comprehensive understanding of the relationship between architectural design and consumer experience.

Through the systematic literature review, 13 design elements were obtained and then verified through interviews of 30 professional designers. The obtained elements were made into a questionnaire to collect data across China from 1,016 consumers of different groups. Data were analyzed using cluster analysis, principal component analysis and difference analysis.

The results show that design elements that influence consumer experience in shopping malls are a four-dimensional construct: visual atmosphere, physical environment comfort, space structure and business planning, among which space structure and business planning play a larger role in the consumer experience. In addition, the perception differences of consumers for those elements are significant due to the individual differences.

This paper comprehensively investigates the architectural design elements affecting consumer experience in the Chinese mall context. Moreover, it provides unique insights about the relationship between architectural design and consumer experience by exploring the categories, weights and perception differences of those elements.

The aim of this research is to improve the responsiveness of the healthcare network of a large city to a major earthquake, by applying a combined methodology to reduce human suffering and death.

Scenario analysis, a non-linear programming (NLP) model, and the analytical network process are sequentially applied to find the “best location pattern”.

When considering the occurrence of major earthquakes in cities with high population density, as a rule of thumb, the location of healthcare facilities should prioritize areas characteristically overcrowded and/or that were built based on poor standards of seismic resistance.

The proposed research design does not include a cost criterion in the set of decision variables involved. Furthermore, the results derived from the NLP-model are restricted by the input simulation data.

The performance of the “best location pattern” is compared with the current location of healthcare facilities in terms of their distances to the affected zones. Metropolis areas worldwide with similar conditions to the city under consideration could be benefited from applying the general methodology for relocation of healthcare facilities described in this research.

This research implements a diverse combination of methodologies to examine the problem of relocating of healthcare facilities in a large city in the wake of an assumed earthquake. In addition, to the best of authors' knowledge, this is the first study of its kind that proposes improvements in the responsiveness of the healthcare facilities' network in the city in question.