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This study aims to explore the impact of applying a blockchain-based information system in the international students’ administrative workflow in the context of a public research university in the USA.

Specifically, a prototype of the blockchain-based information system was developed and tested. The system has the potential advantages of being more efficient, more transparent, faster and safer.

The results show that digital registration could increase student registration efficiency with a blockchain-based application.

There are also some limitations of this study. As an early exploration of the use of blockchain technology in higher education, this study could be further extended in several aspects: different institutions (e.g. private vs public school) may have different operational strategies towards international student affairs. The different administrative processes should be discussed in the context of different institutions, and thus the proposed system should be tested and evaluated based on the requirements of different institutions. Use experience and feedback from different users such as university administrators and students should be considered and investigated with respect to the necessary improvement of the proposed system. The extensibility and scalability of the system should be assessed to accommodate any potential modifications of the administrative process.

The findings show that a blockchain-based information management system has the potential to improve data transmission efficiency and protect information privacy.

The presentation of in-vehicle warnings information at risky driving scenarios is aimed to improve the collision avoidance ability of drivers. Existing studies have found that driver’s collision avoidance performance is affected by both warning information and driver’s workload. However, whether moderation and mediation effects exist among warning information, driver’s cognition, behavior and risky avoidance performance is unclear.

This purpose of this study is to examine whether the warning information type modifies the relationship between the forward collision risk and collision avoidance behavior. A driving simulator experiment was conducted with waring and command information.

Results of 30 participants indicated that command information improves collision avoidance behavior more than notification warning under the forward collision risky driving scenario. The primary reason for this is that collision avoidance behavior can be negatively affected by the forward collision risk. At the same time, command information can weaken this negative effect. Moreover, improved collision avoidance behavior can be achieved through increasing drivers’ mental workload.

The proposed model provides a comprehensive understanding of the factors influencing collision avoidance behavior, thus contributing to improved in-vehicle information system design.

The significant moderation effects evoke the fact that information types and mental workloads are critical in improving drivers’ collision avoidance ability. Through further calibration with larger sample size, the proposed structural model can be used to predict the effect of in-vehicle warnings in different risky driving scenarios.

The tech giants Alibaba and Tencent compete on many fronts. This case focuses on three areas where they have competed very hard: new retailing, mobile payment, and ride-hailing. At the beginning of 2018, Alibaba and Tencent were gathering retail investments in bids to battle each other for shoppers' digital wallets. Key to the battle is China's mobile payment market, worth more than 200 trillion RMB, where Alibaba and Tencent are going head to head. The giants are not only directly competing in the payment platform area but also extensively fighting in other areas, such as ride-hailing, where they invested in and supported Didi and Kuaidi, respectively. To enhance understanding, this case also briefly goes through the history of the two giants. The purposes, methods, and consequences of their platform competition deserve an in-depth discussion

For the basic problems on platform innovation, such as platform innovation connotation and characteristics, the driving mechanism and the influence mechanism are less been studied. This study aims to explore how to achieve platform innovation in traditional service enterprises.

Based on the theory of enterprise network and binary learning, respectively, this paper discusses the behavior of binary learning based on network structure and network impact on efficiency and innovative platform innovation, and analyzed the realization of the platform innovation path.

The research draws the following conclusions: the network structure-based exploitative learning can promote the efficiency platform innovation, while the network behavior-based exploratory learning can promote the novelty platform innovation. The interaction between network structure and network behavior embedded in traditional services is more conducive to exploratory learning so as to promote novelty platform innovation, and the platform innovation of traditional service enterprises is a process from efficiency-oriented to novelty-oriented. The innovation effect generated by exploratory learning based on network behavior is much higher than that generated by exploitative learning based on network structure. The theoretical contributions of this study are as follows: first, this study compares the similarities and differences between service innovation of platform-oriented enterprises and platform innovation of service enterprises. On this basis, it clearly defines the concept of platform innovation and divides it into two categories: efficiency platform innovation and novelty platform innovation. Second, it reveals the two paths for traditional service enterprises to realize platform innovation, and the interaction between these two paths are also explored, which promotes the scenario-based and dynamic study of platform innovation in traditional service enterprise. The conclusion of this study provides theoretical reference for traditional service enterprises to carry out platform innovation.

Theoretical contribution of this paper lies in: first, the concept of platform innovation is clearly defined. Current research about platform innovation is mainly around the innovation of platform enterprise and the platform innovation of traditional enterprise, but there is no document that makes clear distinction; some literature even equates innovation of platform enterprise with platform innovation of traditional enterprise. In this paper, through a detailed literature review and analysis, clearly define the concept of platform innovation and divided into efficiency platform innovation and novel platform innovation, which has made theoretical contribution to the depth of the research. Second, expand the platform innovation research of traditional service industry. In recent years, the platform innovation research of traditional enterprise has become a hot spot, but they focus on the attention of the platform transformation of traditional manufacturing industry, such as Haier; the traditional service industries seem to be “empty,” but, in fact, the traditional service industry platform innovation is of great significance and more worth looking forward to. In this paper, the longitudinal case studies can promote academic concerns focus on the traditional service industry, and also provides the theory instruction practice. Third, it promotes the platform innovation research of traditional enterprise and dynamic analysis. Based on the theory of enterprise network and binary learning, respectively, it discusses the behavior of binary learning based on network structure and network impact on efficiency and innovative platform innovation, and analyzed the realization of the platform innovation path. On the one hand, it enriches the research type of platform innovation; on the other hand, the dynamic evolution mechanism of platform innovation research can make up for the deficiency of the existing literature.

Pharmacy services start right from prescribing medicines and continue as the medication’s effect is monitored. Hospital and community pharmacy staff promote rational prescribing and medicine use. Consequentially, pharmacy is a complex and busy field. Often there are peak workload hours when patients must wait, which is associated with patient dissatisfaction that may negatively affect patient experience and the organisation’s reputation. The purpose of this paper is to enlist techniques, methods and technological advancements that have been successfully employed to reduce patient waiting time.

A database search was conducted in 2017 to locate articles addressing methods and technologies that reduce pharmacy waiting time. The literature revealed various techniques and technologies like queuing theory, tele-pharmacy, evidence-based pharmacy design, automated pharmacy systems (robotics), system modelling and simulation and the Six Sigma method for identifying potential problems associated with increased wait time.

The authors conclude that various techniques and methods, including automated queuing technology, tele-pharmacy, automated pharmacy devices/machines for quick and accurate filling and dispensing, computer simulation modelling, evidence-based pharmacy infrastructure for smooth workflow and Six Sigma can maintain customer satisfaction, reduce waiting time, attract new customers, decrease workload and improve the organisation’s reputation.

The authors conclude that various techniques and methods, including automated queuing technology, tele-pharmacy, automated pharmacy devices/machines for quick and accurate filling and dispensing, computer simulation modelling, evidence-based pharmacy infrastructure for smooth workflow and Six Sigma methodology can maintain customer satisfaction, reduce waiting time, attract new customers, decrease workload and improve the organisation’s reputation.

The authors carried out a literature search and identified the techniques that have been successfully implemented to reduce pharmacy patient waiting time and methods that can identify potential process behind medication dispensation delays.