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The purpose of this paper is to illustrate the new technical demands and reliability challenges to printed circuit board (PCB) designs, materials and processes when the transmission frequency increases from Sub-6 GHz in previous generations to millimeter (mm) wave in fifth-generation (5G) communication technology.

The approach involves theoretical analysis and actual case study by various characterization techniques, such as a stereo microscope, metallographic microscope, scanning electron microscope, energy dispersive spectroscopy, focused ion beam, high-frequency structure simulator, stripline resonator and mechanical test.

To meet PCB signal integrity demands in mm-wave frequency bands, the improving proposals on copper profile, resin system, reinforcement fabric, filler, electromagnetic interference-reducing design, transmission line as well as via layout, surface treatment, drilling, desmear, laminating and electroplating were discussed. And the failure causes and effects of typical reliability issues, including complex permittivity fluctuation at different frequencies or environments, weakening of peel strength, conductive anodic filament, crack on microvias, the effect of solder joint void on signal transmission performance and soldering anomalies at ball grid array location on high-speed PCBs, were demonstrated.

The PCB reliability problem is the leading factor to cause failures of PCB assemblies concluded from statistical results on the failure cases sent to our laboratory. The PCB reliability level is very essential to guarantee the reliability of the entire equipment. In this paper, the summarized technical demands and reliability issues that are rarely reported in existing articles were discussed systematically with new perspectives, which will be very critical to identify potential reliability risks for PCB in 5G mm-wave applications and implement targeted improvements.

Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.

The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.

The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.

First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.

The purpose of this study is to explore the coopetition relationships between platform owners and complementors in complementary product markets. Drawing on the coopetition theory, the authors examined the evolutionary trends of the coopetition relationships between platform owners and complementors and explore the main influence factors.

The authors used Lotka–Volterra model to analyze the coopetition relationship between platform owners and complementors, including the evolutionary trends as well as the results. Considering the feasibility of sample data collection, simulation is used to verify the effects of different factors on the evolution of coopetition relationships.

The results show that there are four possible results of the competition in the complementary products market. That comprises “winner-take-all for platform owners,” “winner-take-all for complementors,” “stable competitive coexistence” and “unstable competitive coexistence,” where “stable competitive coexistence” is the optimal evolutionary state. Moreover, the results of competitive evolution are determined by innovation subjects’ interaction parameters. However, the natural growth rate, the initial market benefits of the two innovators and the overall benefits of the complementary product markets influence the time to reach a steady state.

The study provides new insights into the entry of platform owners into complementary markets, and the findings highlight the fact that in complementary product markets, platform owners and complementors should seek “competitive coexistence” rather than “winner-takes-all.” Moreover, the authors also enrich the coopetition theory by revealing the core factors that influence the evolution of coopetition relationships, which further enhance the analysis of the evolutionary process of coopetition relationships.

Higher education institutions have a critical role in creating and disseminating the knowledge required to address the complex global challenges faced by global society, as summarized in the Sustainable Development Goals (SDGs). This role of higher education is linked with the concept of internationalization, which has recently been called upon to help contribute to tackle the global challenges and meet the SDGs, particularly through more attention to “Internationalization at Home” (IaH). This paper aims to examine the role of higher education in addressing the SDGs, especially with respect to the links between IaH and the SDGs.

A case study of the International Campus of Zhejiang University (iZJU) is conducted to illustrate how iZJU, which is a pioneer of “Internationalization at Home” and an exemplar of sustainable campus in China, contributes to the value of the SDGs and makes an impact.

The authors examine the practice of IaH at iZJU in the dimensions of organization, curriculum, people and campus, and the authors find evidence from the iZJU model in addressing the value of the SDG4, 6, 7, 11, 13, 14, 15, 16 and 17.

First, the authors contribute to the literature on the role of higher education in addressing the SDGs, especially with respect to the links between IaH and the SDGs. Second, the authors contribute to the IaH literature by examining IaH from a Chinese perspective, as there has been little exploration of what IaH means beyond the European context. Third, the authors build on the analytical framework in the IaH literature in the dimensions of organization, curriculum and people and extend with a new dimension of campus. Fourth, the authors show that IaH is a comprehensive approach to include both curriculum internationalization and campus internationalization.

This research presents machine learning models for predicting international tourist arrivals in Indonesia during the COVID-19 pandemic using multisource Internet data.

To develop the prediction models, this research utilizes multisource Internet data from TripAdvisor travel forum and Google Trends. Temporal factors, posts and comments, search queries index and previous tourist arrivals records are set as predictors. Four sets of predictors and three distinct data compositions were utilized for training the machine learning models, namely artificial neural networks (ANNs), support vector regression (SVR) and random forest (RF). To evaluate the models, this research uses three accuracy metrics, namely root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE).

Prediction models trained using multisource Internet data predictors have better accuracy than those trained using single-source Internet data or other predictors. In addition, using more training sets that cover the phenomenon of interest, such as COVID-19, will enhance the prediction model's learning process and accuracy. The experiments show that the RF models have better prediction accuracy than the ANN and SVR models.

First, this study pioneers the practice of a multisource Internet data approach in predicting tourist arrivals amid the unprecedented COVID-19 pandemic. Second, the use of multisource Internet data to improve prediction performance is validated with real empirical data. Finally, this is one of the few papers to provide perspectives on the current dynamics of Indonesia's tourism demand.

Unlike traditional industries, the e-cigarette is an epoch-making innovative product originating in China and occupying an absolute competitive advantage in the international market. The traditional A-U model describes the laws and characteristics of technological innovation in developed countries. In contrast, the inverse A-U model depicts the process of “secondary innovation” in late-developing countries through digestion and absorption. This paper aims to find out that if the e-cigarette, as a “first innovation” industry in a late-developing country, conform to the A-U model or conform to the “inverse A-U model”.

This paper takes the patent data of e-cigarettes from 2004 to 2021 as the research object, and uses Python’s Jieba segment words to divide product innovation and process innovation, and then uses statistical analysis methods to conduct empirical analyses on these data.

Thus, an improved A-U model suitable for the e-cigarette industry is proposed. In this model, product innovation in the e-cigarette industry appeared earlier than process innovation, but the synchronous development of product and process innovation is not lagging. The improved A-U model in the e-cigarette industry is not only different from the traditional A-U model but also does not conform to the inverse A-U model.

It is conducive to expanding and clarifying the theoretical contribution and applicable boundaries of the A-U model and has sparked thinking and exploration of the A-U model in e-cigarettes and emerging industries.

On this basis, suggestions on the development path and countermeasures of the e-cigarette industry are put forward.

Based on the e-cigarette industry, this paper takes patents as the research object and provides the method of dividing product innovation and process innovation, and proposes an A-U model suitable for the e-cigarette industry on this basis. By comparing the traditional A-U model with the inverse A-U model in latecomer countries, the background and causes of e-cigarette A-U model heterogeneity are analyzed from different stages and overall morphology. Based on this, the heterogeneity characteristics of e-cigarette innovation are summarized and sorted out.

Consumers may enjoy the information sharing and social support made available when a social media platform is used for pre-purchase research; however, do consumers reevaluate the privacy and security of the platform differently when ordering and payment capabilities are added? As social media systems have evolved into social commerce platforms (SCPs), individuals are often faced with whether to complete a purchase they have been researching or switch to a traditional e-commerce platform to complete the transaction. This research examines consumer trust formation in the SCP channel and how consumer interest and engagement in the channel are maintained and influence consumer decisions to purchase via the SCP.

Based on trust and involvement literature, a research model was conceptualized to capture consumer beliefs about SCP privacy and security and whether the SCP can be trusted, using these inputs into subsequent consumer interest, engagement and decisions on whether to use the SCP for purchasing. The research model was empirically tested using the panel data's structural equation modeling (AMOS) (n = 405). The data showed acceptable reliability and convergent validity, while the original research model provides predictive validity and theory-confirming insights.

Results confirm that consumer perceptions of privacy and security play a crucial role as decision criteria, informing their judgments of whether a new social commerce channel can be trusted enough to conduct purchases. Further, consumer trust supports their interest in the SCP, resulting in enduring and enhanced behavioral use and, to a lesser extent, purchase intent. Still, a majority of this sample declined to purchase using the SCP and rather preferred to transact on tried and trusted traditional e-commerce sites.

This study is among the first to examine trust formation in new SCPs, where consumers are deciding to expand their engagement level from social and informational to commercial.