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Taiwan is one of several leading countries in the mobile music context. Accordingly, Taiwan's experiences in promoting mobile music service diffusion are of importance and interest to international practitioners and researchers. Applying Rogers' innovation diffusion theory, this study aims to employ econometric models to investigate whether the diffusion of mobile music service adoption is affected by external influences (e.g. mass media advertising, salespeople, and service providers), internal influences (e.g. interactions and imitations among acquaintances), or a combination of such influences.

To determine which influence best explained the diffusion of mobile music adoptions, the external, internal, and Von Bertalanffy mixed influence diffusion models were tested in this study. GNUS, a strongly functional language and environment to statistically explore data sets, was used to estimate the parameters of each model. The performance of each diffusion model was then examined using the Akaike AIC and Schwarz BIC statistics.

Findings indicated that the Von Bertalanffy mixed influences model best describes the diffusion pattern of mobile music service adoption and that acquaintances' influence in terms of interactions is the dominant factor influencing mobile music service adoption decision in Taiwan.

How managers of a mobile music service provider can use the internal and external influences interchangeably to effectively accelerate the mobile music diffusion at the different stage of product lifecycle is presented in this study. Indeed, the mobile music service is one of the most important industries worldwide not only because its penetration rate in many countries is over 50 percent, but also because of its killer applications. In light of this, the study contributes highly to theoretical and empirical examinations because the diffusion of the mobile music services within a society is the essence of the development/usage of the m‐commerce or music industries.

A simple approach is developed for modelling the distribution of dopant in crystals grown by the Czochralski technique. Allowance is made for the temperature dependence of the diffusivity and for the diffusion of dopant behind the moving boundary. It is found that the effect can make a significant difference to the final dopant distribution. The diffusion process is modelled using a discrete method, previously developed for situations in which the boundary is static.

The microstructure and properties of Zn-Sn coating on sintered Nd-Fe-B magnets were investigated by the grain boundary diffusion process, to improve the corrosion resistance of magnet surface and explore the feasibility of realizing the lower-temperature grain boundary diffusion.

The Zn-Sn coating was deposited on sintered Nd-Fe-B magnets by magnetron sputtering, and then the Zn-Sn coated magnets were put into the vacuum tube furnace for grain boundary diffusion process. The morphology and structure of Zn-Sn coating as well as its mechanical properties and corrosion resistance were investigated.

Results showed that the particle size of vacuum diffusion-treated Zn-Sn coating increased and the particle agglomeration was weakened with increasing diffusion temperature, and the non-vacuum diffusion-treated Zn-Sn coating was oxidized to generate SnO₂ and ZnO compounds. The binding force of coating first increased and then decreased with increasing diffusion temperature, and the maximum binding force was obtained at 540 °C. The binding force and corrosion resistance of non-vacuum diffusion-treated Zn-Sn coating were higher than the vacuum diffusion-treated Zn-Sn coating at the same diffusion temperature.

The Zn-Sn coating after diffusion treatment can provide complete protection, and the coating elements diffusion can be carried out at the same temperature as the secondary aging of sintered Nd-Fe-B magnets. Simultaneously, further diffusion process optimization needs to be completed because the diffusion depth is very low and only about 10 µm, which does not meet the requirements of traditional grain boundary diffusion method.

It has been recently shown that diffusion of dopant during doping of inhomogeneous structure could be accelerated or decelerated in comparison with diffusion of dopant in structure with averaged diffusion coefficient. As a continuation of previous work, the purpose of this paper is to introduce an approach of estimating the limited value of acceleration of the dopant diffusion by choosing the dependence of the dopant diffusion coefficient on the coordinates.

The authors analyzed relaxation of concentration of dopant during diffusion in inhomogeneous material. The authors determine conditions for maximal acceleration and deceleration of diffusion of dopant. The authors introduced analytical approach for analysis of dopant diffusion in inhomogeneous material.

The authors determine conditions for maximal acceleration and deceleration of diffusion of dopant.

It has been shown that dopant diffusion could be decelerated essentially to a greater extent, rather than accelerated.

The primary objective of this study is to tackle the enduring challenge of preserving feature integrity during the manipulation of geometric data in computer graphics. Our work aims to introduce and validate a variational sparse diffusion model that enhances the capability to maintain the definition of sharp features within meshes throughout complex processing tasks such as segmentation and repair.

We developed a variational sparse diffusion model that integrates a high-order L₁ regularization framework with Dirichlet boundary constraints, specifically designed to preserve edge definition. This model employs an innovative vertex updating strategy that optimizes the quality of mesh repairs. We leverage the augmented Lagrangian method to address the computational challenges inherent in this approach, enabling effective management of the trade-off between diffusion strength and feature preservation. Our methodology involves a detailed analysis of segmentation and repair processes, focusing on maintaining the acuity of features on triangulated surfaces.

Our findings indicate that the proposed variational sparse diffusion model significantly outperforms traditional smooth diffusion methods in preserving sharp features during mesh processing. The model ensures the delineation of clear boundaries in mesh segmentation and achieves high-fidelity restoration of deteriorated meshes in repair tasks. The innovative vertex updating strategy within the model contributes to enhanced mesh quality post-repair. Empirical evaluations demonstrate that our approach maintains the integrity of original, sharp features more effectively, especially in complex geometries with intricate detail.

The originality of this research lies in the novel application of a high-order L₁ regularization framework to the field of mesh processing, a method not conventionally applied in this context. The value of our work is in providing a robust solution to the problem of feature degradation during the mesh manipulation process. Our model’s unique vertex updating strategy and the use of the augmented Lagrangian method for optimization are distinctive contributions that enhance the state-of-the-art in geometry processing. The empirical success of our model in preserving features during mesh segmentation and repair presents an advancement in computer graphics, offering practical benefits to both academic research and industry applications.

Due to the cross-network effect, two-sided users communicate with each other, producing a coupling network. To study the spread of platform self-operation in two-sided users' marketing and purchasing tactics, this paper considers the differences in reputation acquired by platform-owned and third-party operating channels.

This study proposes a two-layer network with cross-network links: one layer represents the social network of consumers, while the other layer represents the competitive network of buyers. A closed system of differential equations, based on the binary dynamics of the stochastic network, is developed to study the trend and stability points of the platform self-operation dissemination. Then the overall benefits of platform are analyzed to unify the platform diffusion and pricing strategies.

The degree of difference in social influence and cross-network effects affect diffusion synergistically. Cross-network effects hinder diffusion when there is a significant difference of social influence between consumers and sellers but promote diffusion when there is little difference of social influence between consumers and sellers. Additionally, the network weights and reputation gap exhibit a nonlinear correlation with diffusion. For pricing strategy of the platform, it can achieve maximum profit when the pricing of self-operated goods and third-party-operated goods is equal.

This study considers the complex network architecture created by bilateral markets and the dynamic influence of group interactions on product. Additionally, this study takes reputation into account when considering the price and dissemination tactics of various operating channels, offering guidelines for platforms to control merchants and mediate disputes between various operating channels.

The present study aimed to examine the relationship between information and communication technologies (ICT) diffusion, financial development and economic growth in the panel of developing countries for 2005–2019.

The study employed the principal component analysis (PCA) to extract the index of ICT diffusion. First-generation panel unit root tests such as Levine Lin Chu (LLC), Im Pesaran Shin (IPS), Augmented Dickey-Fuller (ADF) and Phillips and Perron (PP) were employed to check the stationarity of the variables. Pedroni and Kao co-integration techniques were used to examine the existence of the long-run relationship, and co-integration coefficients were estimated using FMOLS and dynamic ordinary least squares (DOLS). The panel Granger causality approach examined the short-run and long-run causality.

The results confirmed that ICT diffusion, financial development and trade openness accelerate growth, whereas inflation dampens economic growth. Further, the causality test showed bidirectional causality between ICT growth and financial development growth but a unidirectional causality from financial development to ICT diffusion in developing countries.

The study recommends synchronizing public and private sector investment for a synergistic effect on ICT infrastructure and adequate investment in the financial sector to increase the growth rate in developing countries. Economic policies should be adopted toward incentives and subsidies to ensure affordable ICT services for disadvantaged communities. Also, training programs focussing on enhancing digital literacy to enable all segments of the population to use digital platforms for financial services are recommended.

Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.

This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.

The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.

This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.

Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.

Information and communication technology (ICT) has the potential to address and reduce income inequality. However, since 1980, income inequality in the United States has caused concerns for researchers, policymakers and the public. Entrepreneurs and managers can take advantage of information technologies, while those in the middle and the bottom see fewer benefits. Meanwhile, countries such as Iceland are more capable of using ICT infrastructure to reduce income inequality, which contributes to the well-being of its citizens. This research study explores the relationship between infrastructure diffusion and income inequality through Rogers’s diffusion of innovations theory.

To answer the research questions, the author assessed the data through a series of regression analyses using SPSS. The authors used Power BI software to chart the relationships between ICT infrastructure diffusion and income inequality by country and in the United States by state and region.

The results show diffusion of innovations theory’s tenets do not necessarily hold, because a significant negative relationship exists between infrastructure diffusion and income inequality, especially in countries with emerging economies. In the United States, this relationship significantly differs by region.

This research contributes to research by expanding economic and sociology work to the IS domain, while providing conflicting evidence for diffusion of innovations theory. The research also provides suggestions for practice, such as more focused ICT infrastructure investments and regulations.

The purpose of this paper is to develop a model that allows determining the boron concentration profile in silicon based on duration and temperature of the diffusion process.

The model was developed on the basis of the Fick’s second law, which is fundamental for describing the diffusion process. The explicit scheme of the finite difference method was used in the conducted simulations. Results of measurements made using the secondary ion mass spectrometry (SIMS) were used as template dopant concentration profiles. Solution of boric acid in ethanol is the dopant source for which this model was developed.

Based on the conducted simulations, it was proposed that besides the influence of electric field of ionized dopants, which is already described in literature, an appropriate factor reflecting the influence of the threshold concentration on the coefficient of diffusion of boron in silicone should also be introduced.

The developed model enables determination of the boron concentration profile in silicon consistent with the results of SIMS measurements. A factor taking into account the influence of threshold concentration on the coefficient of diffusion was introduced. The influence of concentration of boric acid in the dopant solution on the concentration profile was also considered.