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The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation.

In view of the four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of the MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers, respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on the MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy.

Research results show that, compared with monolayer Fuzzy Cognitive Map, the MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned.

This paper constructs the MFCM model, which is a new approach based on several monolayer FCMs, to study the policy diffusion mechanism.

The time series of the federal funds rate has recently been extended back to 1928, now including several episodes during which interest rates remained near the lower bound of zero. This series is analyzed, using the method of indirect inference, by applying recent research on bounded time series to estimate a set of bounded parametric diffusion models. This combination uncouples the specification of the bounds from the law of motion. Although Louis Bachelier was the first to use arithmetic Brownian motion to model financial time series, he has often been criticized for this proposal, since the process can take on negative values. Most researchers favor processes such as geometric Brownian motion (GBM), which remains positive. Under this framework, Bachelier's proposal remains valid when specified with bounds and is shown to compare favorably when modeling the federal funds rate.

The aim of this study is to examine the trend over time of the demand for .it domain names.This study first assesses whether there is a phase of growth and expansion or at a point of saturation. Second, this research can be useful also to compare researches that have considered other internet metrics and other models.

This paper describes the forecasting methods used to analyze the internet diffusion in Italy. The domain names under the country code top-level domain “.it” have used as metrics. To predict domain names .it the seasonal auto regressive integrated moving average (SARIMA) model and the Holt-Winters (H-W) methods have been used.

The results show that, to predict domain names .it the SARIMA model is better than the H-W methods. According to the findings, notwithstanding the forecast of a growth in domain names, the increase is however limited (about 3%), tending to reach a phase of saturation of the market of domain names .it.

In general many authors have studied internet diffusion applying statistical models that follow an S-shaped behavior. On the other hand, the more used diffusion models that follow an S-shape not always provide an adequate description of the Internet growth pattern. To achieve this goal, this paper demonstrates how the time series models, in particular SARIMA model and H-W models, fit well in explaining the spread of the internet.

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.

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.

Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.

The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.

Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.

The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

This paper aims to investigate the moisture diffusion behavior in a system-in-package module systematically by moisture-thermalmechanical-coupled finite element modeling with different structure parameters under increasingly harsh environment.

A finite element model for a system-in-package module was built with moisture-thermal-mechanical-coupled effects to study the subsequences of hygrothermal conditions.

It was found in this paper that the moisture diffusion path was mainly dominated by hygrothermal conditions, though structure parameters can affect the moisture distribution. At lower temperatures (30°C~85°C), the direction of moisture diffusion was from the periphery to the center of the module, which was commonly found in simulations and literatures. However, at relatively higher temperatures (125°C~220°C), the diffusion was from printed circuit board (PCB) to EMC due to the concentration gradient from PCB to EMC across the EMC/PCB interface. It was also found that there exists a critical thickness for EMC and PCB during the moisture diffusion. When the thickness of EMC or PCB increased to a certain value, the diffusion of moisture reached a stable state, and the concentration on the die surface in the packaging module hardly changed. A quantified correlation between the moisture diffusion coefficient and the critical thickness was then proposed for structure parameter optimization in the design of system-in-package module.

The different moisture diffusion behaviors at low and high temperatures have seldom been reported before. This work can facilitate the understanding of moisture diffusion within a package and offer some methods about minimizing its effect by design optimization.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

The basic purpose of this study is to increase the installation rate of mobile games and their life cycle. Little research has been conducted into the competitive market of mobile games and word-of-mouth (WOM), advertisement and quality simultaneously. In this paper, the authors aim to assist developers with a better understanding of how to invest in the game industry.

The primitive modeling has been made based on the Bass diffusion model and its extensions using features related to the game industry. Modeling and simulation have been performed using the system dynamics method.

The results show that if game developers only focus on advertising at the introduction of the game to the market, and neglect quality features, uninstall rate of adopters increases and the game life cycle decreases. And if developers only focus on the quality improvement of the game, and ignore advertisement, they couldn't create enough WOM and thus game installation wouldn't grow enough to create revenue. Furthermore, as long as the pleasure of the game is high for its adopters, developers shouldn't give up on investing in advertising to create even higher WOM. And also in communities with higher levels of variety-seeking among game players, quality is important at the start and advertisement is vital in the following steps of the game life cycle. And if the contact rate among people is high, developers could focus on quality more than the advertisement.

Even though WOM in mobile game installation is crucial, fewer studies have been done in this area and they only address the problem using qualitative or statistical methods. The quantitative system dynamics approach based on the Bass diffusion model, used in this research, fixes the shortcomings of the previous studies. Moreover, due to serious competition in the mobile game industry, only those developers can remain in the market who can predict the future trend of the game market. Furthermore, game development is a creative process and its key factors include engaging the gamers and monetizing.

The purpose of this paper is to offer a new analysis and understanding of the notion of deinstitutionalization. Deinstitutionalization of taken-for-granted practices as a natural consequence of ever-increasing entropy seems to directly contradict the major institutional thesis, namely, that over time isomorphic forces increase and, as a result, possibilities for deinstitutionalization decrease culminating in the impossibility of abandoning in highly institutionalized fields.

This paper is conceptual in nature. Oliver’s 1992 paper on deinstitutionalization is taken as a key text on the subject and as a starting point for building an alternative theory of deinstitutionalization. More broadly, institutional theory and organizational literature on diffusion/adoption are reviewed and synthesized.

The authors argue that possibilities for deinstitutionalization have been overestimated in institutional literature and offer a revisited account of deinstitutionalization vs institutional isomorphism and institutionalized vs highly diffusing-but-not-institutionalized practices. A freedom for choice between alternative practices exists during the pre-institutional stage but not when the field is already institutionalized. In contrast, institutionalized, taken-for-granted practices are immutable to any sort of functional and political pressures and they use to persist even when no technical value remains, thus deinstitutionalization on the basis of a functional dissatisfaction seems to be a paradox.

By revisiting the nature and patterns of deinstitutionalization, the paper offers a better conceptual classification and understanding of how organizations adopt, maintain and abandon organizational ideas and practices. An important task of this paper is to reduce the scope of application of deinstitutionalization theory to make it more focused and self-consistent. There is, however, still not enough volume of studies on institutional factors of practices’ abandonment in institutional literature. The authors, therefore, acknowledge that more studies are needed to further improve both the former deinstitutionalization theory and the framework.

The authors offer a solution to this theoretical inconsistency by distinguishing between truly institutionalized practices and currently popular practices (highly diffused but non-institutionalized). It is only the latter that are subject to the norms of progress that allow abandoning and replacing existing organizational activities. Deinstitutionalization theory is, thus can be applied to popular practices that are subject to reevaluation, abandonment and replacement with new optimal practices while institutions are immutable to these norms of progress. Institutions are immutable to deinstitutionalization and the deinstitutionalization of optimal practices is subject to the logic of isomorphic convergence in organizational fields. Finally, the authors revisit a traditional two-stage institutional diffusion model to explain the possibility and likelihood of abandonment during different stages of institutionalization.