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Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

Knowledge-building (KB) pedagogy is a framework that promotes collective inquiry towards the continual resolution of knowledge problems that are relevant to a community (Bereiter & Scardamalia, 1993). Scardamalia (2002) proposes 12 principles to define KB pedagogy. The aim of this study is to provide a review that analyses the influences of these principles on empirical investigations on KB and the importance of technology in such investigations in order to understand the research trends on this pedagogy. The sample was selected from the most recent products published in the Web of Science database. The content analysis performed showed that researchers focussed mainly on the aspects related to a balanced distribution of knowledge and the improvement of ideas in a KB community. Results of this research suggest the addition of a sixth principle in KB pedagogy, that is, a technological principle. The latter highlights that KB is mediated by technology, which in turn facilitates communicating and sharing ideas within a community.

Previous studies investigate factors affecting project outcomes. Yet, it has not been fully explored regarding which factors differentiate healthy projects from distressed projects in the early stage of the project delivery process. The purpose of this study is to investigate the links between project-planning factors and project outcomes in the closing phase.

The authors use a longitudinal survey method to examine the predictability of project-planning factors. Subsequently, the authos employ confirmatory factor analysis and hierarchical logit regression to develop project-distress classification models.

Analysis of 90 capital projects shows that performance variation in the project planning phase explains a substantial portion of project distress at completion. Subsequent univariate logit analysis shows that S5 (quality of scope control system) and Tn1 (new practices and technologies) variables have the strongest predictive abilities. Hierarchical logit analysis further shows that a combination of 15 metrics in the project-distress measurement model produces strong and stable predictive power.

This study assesses how well performance variation in the project-planning phase predicts project distress before construction phase. It does not assume the reported results apply to all types of projects. Nonetheless, future studies could generalize our findings by incorporating more types of projects.

This study takes a systematic approach, combining longitudinal survey, measurement theory and hierarchical logit analysis to identify distressed projects early, offering managers an opportunity to take early corrective actions. Practitioners may use this approach to investigate other types of projects and further refine the project-distress classification model into a project-specific model, thereby reflecting projects' unique characteristics.

Researchers have long sought to understand how risks in supply chains (SCs) affect firm performance. Yet, they have not fully subjected claims of how SC risks affect firm financial performance to theoretical and empirical scrutiny. The purpose of this paper is to investigate the links between SC risks and firm financial performance.

The author analyzes how SC risks affect firm financial performance from the perspective of marginal financial performance (MFP) using survey and financial statement data. The author employs structural equation modeling to examine the hypotheses using 106 Taiwanese listed companies across 20 industries.

The findings regarding the importance of industry-specific risk, organizational risk, internal business process risk, and demand risk are consistent with prior studies. The author finds that demand risk has an MFP of −0.20, the highest negative effect among the risk variables. The findings also show that industry-specific risk possesses an MFP of −0.16, the second-highest negative effect, despite having no direct effect on financial performance.

This paper examines how SC risks affect MFP via combining survey and financial statement data. It does not assume the reported MFP estimates apply to all businesses in other countries. However, future research could triangulate our findings.

This study combines survey and financial data to analyze how SC risks affect firm financial performance. Specifically, it provides a methodology for estimating quantitative cause-effect relationships between SC risk and firm financial performance, an important topic that receives less research interest in the field of supply chain management.

When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are difficult to achieve a balance between rating prediction accuracy and complexity. Therefore, the purpose of this paper is to propose an accurate and effective model to predict users’ ratings of products for the accurate recommendation of products to users.

First, we introduce an attention mechanism that dynamically assigns weights to user preferences, highlighting key interaction information and enhancing the model’s understanding of user behavior. Second, a fold embedding strategy is employed to segment user interaction data, increasing the information density of each subset while reducing the complexity of the attention mechanism. Finally, a masking strategy is integrated to mitigate overfitting by concealing portions of user-item interactions, thereby improving the model’s generalization ability.

The experimental results demonstrate that the proposed model significantly minimizes prediction error across five real-world datasets. On average, the evaluation metrics root mean square error (RMSE) and mean absolute error (MAE) are reduced by 9.11 and 13.3%, respectively. Additionally, the Friedman test results confirm that these improvements are statistically significant. Consequently, the proposed model more accurately captures the intrinsic correlation between users and products, leading to a substantial reduction in prediction error.

We propose a novel collaborative filtering model to learn the user-item interaction matrix effectively. Additionally, we introduce a fold embedding strategy to reduce the computational resource consumption of the attention mechanism. Finally, we implement a masking strategy to encourage the model to focus on key features and patterns, thereby mitigating overfitting.

College student’s mental health issues have emerged as a significant public health concern. The urban campus environment, being the primary habitat for college students, plays a crucial role in influencing their mental health.

Based on survey data from 34 Chinese universities and 1173 college students in 2021, this study utilized deep learning and street view images to explore the relationship between various urban campus landscapes, college students' exercise participation, and mental health.

The study revealed substantial variations in campus landscape features, particularly in terms of spatial openness. While green campus landscapes (measured by the Green View Index and Normalized Difference Vegetation Index) showed no significant impact on exercise participation or mental health, the Sky View Factor did. Higher levels of campus openness and exercise frequency were associated with better mental health. The study also underscored that the influence of urban campus landscapes on college students' mental health was mediated by their exercise participation. Notably, spatial openness emerged as the most prominent differentiating factor among urban campus landscape attributes, significantly affecting students' exercise participation and mental health.

Thus, fostering open campus environments and reducing spatial constraints are vital steps in creating a sustainable urban landscape that can help alleviate potential negative effects on college students' mental health issues.

This paper employs nationwide, large-scale field survey data to provide the first empirical evidence on the impact of human educational capital on the acquisition of health entitlement among Chinese migrant workers. The findings of this study hold significant practical implications for the formulation of policies aimed at improving the health protection of migrant workers, as well as for socioeconomic policies during China's transitional period.

Using the IVProbit model, this research examines how human educational capital influences the attainment of health entitlement among migrant workers in China by analyzing the impact and mechanism of education on health entitlement. The study is based on the China Migrants Dynamic Survey (CMDS) data from 2018, which include 100,177 observations.

For migrant workers in China, higher levels of education have a significant positive effect on the acquisition of health entitlements, including medical insurance, health records and health education. The positive impact of human educational capital on health entitlements is more significant for non-provincial cities and young-generation migrant workers. The results also show that human educational capital can influence the acquisition of health entitlements through mediators such as financial status, social integration and health status.

This study represents the first empirical attempt to evaluate the influence of human educational capital on the access of migrant workers in China to health rights and interests. Additionally, the study develops a theoretical framework to examine how the impact of human educational capital varies across migrant workers with different characteristics and their access to health entitlements.

Public safety issues are highly concerned by the state and public. As an emerging network technology and industrial mode, Internet of Things (IoT) has great application prospect because of its architecture advantages and technical features, and has drawn wide attention from all walks of life. With the development of IoT, especially the putting forward of concept of public safety IoT, IoT has been a certain degree of application in the field of public safety. Because of that, public safety regulatory technology is improved. The paper aims to discuss this issue.

By summarizing scholars’ research results, this paper analyzes the application of IoT in public safety regulation, points out the challenges in application, and then puts forward some suggestions, pointing out IoT development prospects in the area of public safety regulation.

The application of IoT in the field of public safety from the perspective of IoT architecture and the perspective of the main technologies of IoT is paid attention. And this market that IoT added to other services in the public sector would generate $4.6 trillion of net profit globally in the next decade. Therefore, government leaders and public safety organizations should start exploring the full potential that IoT could offer to public safety.

The research will develop the theory of IOT, which is valuable to strengthen the IOT technology innovation and the application extension. The application of IOT in public safety will enhance the ability to supervise the public safety and guarantee the safe social condition for people’s life. So it is valuable in theory and in practice.

Cyber physical system (CPS) has attracted much attention from industry, government and academia due to its dramatic impact on society, economy and people’s daily lives. Scholars have conducted a number of studies on CPS. However, despite of the dynamic nature of this research area, a systematic and extensive review of recent research on CPS is unavailable. Accordingly, this paper conducts an intensive literature review on CPS and presents an overview of existing research on CPS. The purpose of this paper is to identify the challenges of studying CPS as well as the directions for future studies on CPS.

This paper examines existing literatures about CPS from 2006 to 2018 in Compendex, presenting its definition, architectures, characteristics and applications.

This study finds that CPS is closely integrated, diversified and large-scale network with complex multiple time scales. It requires dynamic reorganization/reconfiguration, mass computing, and closed, automated and control circuits. Currently, CPS has been applied in smart manufacturing, medical systems, smart city and smart libraries. The main challenges in designing CPS are to develop, to modify, to integrate abstractions and to set predictable timing of openness and physical interconnection of physical devices. Furthermore, security is a key issue in CPS.

This study adds knowledge to the existing literature of CPS by answering what the current level of development on CPS is and what the potential future research directions of CPS are.