University and college laboratories are important places to train professional and technical personnel. Various regulatory departments in colleges and universities still rely on traditional laboratory management in research projects, which are prone to problems such as untimely information and data transmission. The present study aimed to propose a new method to solve the problem of data islands, explicit ownership, conditional sharing, data safety, and efficiency during laboratory data management. Hence, this study aimed to develop a data-centered lab management system that enhances the safety of lab data management and allows the data owners of the labs to control data sharing with other users. The architecture ensures data privacy by binding data ownership with a person using a key management method. To achieve data flow safely, data ownership conversion through the process of authorization and confirmation was introduced. The designed lab management system enables laboratory regulatory departments to receive data in a secure form by using this platform, which could solve data sharing barriers. Finally, the proposed system was applied and run in different server environments by implementing data security registration, authorization, confirmation, and conditional sharing using SM2, SM4, RSA, and AES algorithms. The system was evaluated in terms of the execution time for several lab data with different sizes. The findings of this study indicate that the proposed strategy is safe and efficient for lab data sharing across domains.

With the growth of university chemistry experiment projects, the corresponding laboratory safety risks are increasing year by year for scientific research personnel, and specialized equipment. However, accident data are not stored systematically for lack of a safety platform to collect accident information, share the causes of accidents, and predict safety risks. To solve these problems, we designed a laboratory accident system to store and share related data, and predict risk levels. In this paper, the majority of chemistry laboratory accidents were manually collected by Python software (version 3.10.11) and were categorized based on their risk level. Moreover, the variable factors that generated risk were analyzed using Spsspro, which facilitates the construction of a meaningful forecasting model of laboratory safety via Stata. It is worth noting that the registered laboratory accident data in the proposed chemistry accident system were based on the data ownership safety architecture. The chemistry accident system can break through data barriers using confirmation and authorization key algorithms to trace non-tampered data sources in a timely manner when an emergency accident happens. Meanwhile, the proposed system can use our designed accident risk model to predict the risk level of any experimental project. It can also be recommended as an appropriate safety education module.

The tourism shoppers’ purchasing behaviors have critical effects to economies, but there are few of comprehensive review that integrates and synthesis the finding of literature on tourism purchasing behavior systematic from past, present and future perspective. As the international tourists consuming volume have decreased in average, the purchasing behavior has changed into online, planned characters especially under the conflict from COVID 19, this paper tries to find the way to solve this problem for the tourism retailing industries development and the market demand. The methods of this paper is to use the theory of tourist classification and duty-free products classification for research shoppers’ sample identification and duty free products wish lists audition, customers purchasing methods is to analyze the gap, Citespace is used here to fill the gap with domain knowledge and visualize the finding of 150 papers on tourism purchasing behavior published from 2010 to 2020. The finding of this research is: i) Lotte, King Power, Dubai international duty free can be Asia representative research shops, Chinese international tourists can be the research target group; ii) Fragrances & cosmetic, wines & spirits, fashion & accessories and personal luxury goods can be selected as the 4 duty free products categories; iii) Chinese tourism shoppers have the purchasing gap between oversea and domestic products, both those kinds of products can be acquired online and offline; iv) Multiple emergent themes in the existing corpus, the theory of planned behavior and online communication are the key domain knowledge to fill this gap. So, a questionnaire is urgent to design based on this research result to find out the decision tree nodes and then compose the decision-making model for duty free industry and tourism shoppers effectively.

This study explores Chinese tourists' purchase intentions for personal luxury goods in Asia-Pacific duty-free shops using an integrated Affect Behavior Cognition (ABC) model of attitude, incorporating subjective norms. Factor analysis and K-means clustering were employed to segment the market based on demographics and purchasing behavior. Three distinct customer segments emerged: the ``All-Participation Group'' highly involved in all purchasing decision factors, focusing on product performance, price, and shopping convenience; the ``Product-Oriented Group'' prioritizing product performance and cost-effectiveness, with a preference for convenient search channels; and the ``Perceived Control & Promotion Group'' influenced by promotions, cautious about product damage, and favoring easy and secure purchasing channels. These findings offer actionable insights for duty-free shops to develop targeted marketing strategies tailored to each segment's needs and preferences. This study advances the academic understanding of customer behavior in the luxury goods market and provides practical implications for customer-centric marketing in the duty-free retail sector.