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Gas insulated systems, such as gas insulated lines (GIL), use insulating gas, mostly sulfur hexalfluoride (SF₆), to enable a higher dielectric strength compared to e.g. air. However, under high voltage direct current conditions, charge accumulation and electric field stress may occur, which may lead to partial discharge or system failure. Therefore, numerical simulations are used to design the system and determine the electric field and charge distribution. Although the gas conduction shows a more complex current–voltage characteristic compared to solid insulation, the electric conductivity of the SF₆ gas is set as constant in most works. The purpose of this study is to investigate different approaches to address the conduction in the gas properly for numerical simulations.

In this work, two approaches are investigated to address the conduction in the insulating gas and are compared to each other. One method is an ion-drift-diffusion model, where the conduction in the gas is described by the ion motion in the SF₆ gas. However, this method is computationally expensive. Alternatively, a less complex approach is an electro-thermal model with the application of an electric conductivity model for the SF₆ gas. Measurements show that the electric conductivity in the SF₆ gas has a nonlinear dependency on temperature, electric field and gas pressure. From these measurements, an electric conductivity model was developed. Both methods are compared by simulation results, where different parameters and conditions are considered, to investigate the potential of the electric conductivity model as a computationally less expensive alternative.

The simulation results of both simulation approaches show similar results, proving the electric conductivity for the SF₆ gas as a valid alternative. Using the electro-thermal model approach with the application of the electric conductivity model enables a solution time up to six times faster compared to the ion-drift-diffusion model. The application of the model allows to examine the influence of different parameters such as temperature and gas pressure on the electric field distribution in the GIL, whereas the ion-drift-diffusion model enables to investigate the distribution of homo- and heteropolar charges in the insulation gas.

This work presents numerical simulation models for high voltage direct current GIL, where the conduction in the SF₆ gas is described more precisely compared to a definition of a constant electric conductivity value for the insulation gas. The electric conductivity model for the SF₆ gas allows for consideration of the current–voltage characteristics of the gas, is computationally less expensive compared to an ion-drift diffusion model and needs considerably less solution time.

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 importance of champion leaders including tech-savvy leaders to digital government has been highlighted in the literature. Meanwhile, what was in the authors’ interest to explore was the role of business-savvy leaders or non-governmental digital champions as units of analysis, those who mobilized people's interest in digitalization and bypassed governmental barriers through this popular mobilization. They could be considered policy entrepreneurs for understanding policy change in the digitalization of the health sector. This study sought to shed light on the barriers and drivers of digital health in Iran.

The researchers conducted interviews with actors of digital health businesses in Iran, including the Health Information Technology Center affiliated to the Ministry of Health and Medical Education (MOHME) administrative body and authorities, private companies active in digital health and health service providers. The purposive sampling method was applied, and 15 experts with relevant and valuable experiences as well as maximum variation to obtain representativeness and rich data were interviewed. Trustworthiness criteria were also used to assure the quality of the results. The data were analyzed based on directed content analysis using the MAXQDA10 software.

It was found out how popular diffusion was effective to overcome barriers to health digitalization. Access to the internet and diffusion of information technology helped the net-enabled businesses to connect directly to people and provide services to them. Diffusion of these services forced the public sector to adjust itself, and thus MOHME banned digital consultation services because of the so-called “insecure and unknown physicians”, following the increased popularity of digital services diffusion, but they were not able to resist popular diffusion of new technology. Hence, it was allowed to work. The main barriers to telemedicine spreading in Iran have been divided into five main categories including government incapacity for digital health governance, conflict of interest, professional obligations for information transparency, protection of patients' rights and data security and privacy.

As a game changer in digital health governance in Iran, popular diffusion will determine the future of digital health. To the best of the authors’ knowledge, this study is among the first ones to explore digital health governance in relation to the private digital health business in Iran with a public policy approach.

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.

Nowadays, online platforms which provide products or services try to implement their homegrown communities to facilitate users' social interactions. Reviewers' activities in these communities can reflect their interests. Based on the theory of homophily, the authors aim to explore the impacts of the reviewer preference similarity and opinion similarity on the rate of product diffusion.

First, the authors construct reviewer similarity network based on their common interests and propose typical network metrics to measure reviewer preference similarity. Second, the authors measure reviewer opinion similarity with natural language processing. Finally, based on a panel data from an online video platform in China, both the fixed-effect and random-effect panel data models are constructed.

The authors find that reviewer preference similarity has a positive effect on the product diffusion, whereas reviewer opinion similarity has a negative effect on the diffusion. Furthermore, temporal distance moderates the relationship between reviewer similarity and the product diffusion. As a double-edged sword, review preference similarity hinders product diffusion in the initial phase, whereas benefits it in the later phase. Reviewer opinion similarity is always detrimental to product diffusion, especially in the initial phase.

This paper extends the understanding of homophily from the micro peer level to the group level by constructing reviewers' similarity network and highlights the important role of reviewer preference similarity and opinion similarity in product diffusion. The results also provide important insights for managers to design and implement diversity strategies for better product adoption in the community context.

The main research target of this paper is to capture the network effects using the case of mobile cellular telephony, identified in European telecommunication markets, and its determinants enhancing the process of digital technologies diffusion.

This research relies on panel and dynamic panel regression analysis. The empirical sample covers 30 European countries, and the period for the analysis is set for 2000–2019.

This work contributes by examining the network effects identified on European telecommunication markets that drive the process of digital technologies diffusion, but it also extends the understanding of the latter by tracing major determinants of fast network expansion, e.g. prices of access to and use of, per capita income, urbanisation, population density, accessibility of fixed telephony infrastructure. The main findings support the initial supposition that the installed base strongly enhances diffusion of new technologies, while other factors, for example, prices, are not of prime importance.

This research has certain managerial implications. The unveiled network effects driving adoption of technological innovations constitute a significant determinant of implementation of differentiation strategy by telecommunication companies. Due to network effects consumers' propensity to join the network is valued higher than the prices of services offered, which is crucial not only from the perspective of the company's pricing strategy but also enables telecommunication companies to introduce to the market new products and/or services concentrating on increasing its quality and usability rather than future prices.

This is the first work that empirically verifies the intercompanies and interpersonal diffusion of cellular telephony, hypothesising that this process relies on unique network effects.

Cross-laminated timber (CLT) is an innovative construction material that provides a balanced mix of structural stiffness, fabrication flexibility and sustainability. CLT development and innovation diffusion require close collaborations between its supply chain architectural, engineering, construction and manufacturing (AECM) stakeholders. As such, the purpose of this study is to provide a preliminary understanding of the knowledge diffusion and innovation process of CLT construction.

The study implemented a longitudinal social network analysis of the AECM companies involved in 100 CLT projects in the UK. The project data were acquired from an industry publication and decoded in the form of a multimode project-company network, which was projected into a single-mode company collaborative network. This complete network was filtered into a four-phase network to allow the longitudinal analysis of the CLT collaborations over time. A set of network and node social network analysis metrics was used to characterize the topology patters of the network and the centrality of the companies.

The study highlighted the scale-free structure of the CLT collaborative network that depends on the influential hubs of timber manufacturers, engineers and contractors to accelerate the innovation diffusion. However, such CLT supply collaborative network structure is more vulnerable to disruptions due to its dependence on these few prominent hubs. Also, the industry collaborative network’s decreased modularity confirms the maturity of the CLT technology and the formation of cohesive clusters of innovation partners. The macro analysis approach of the study highlighted the critical role of supply chain upstream stakeholders due to their higher centralities in the collaborative network. Stronger collaborations were found between the supply chain upstream stakeholders (timber manufacturers) and downstream stakeholders (architects and main contractors).

The study contributes to the field of industrialized and CLT construction by characterizing the collaborative networks between CLT supply chain stakeholders that are critical to propose governmental policies and industry initiatives to advance this sustainable construction material.

The aim of this conceptual study is to analyze the effects of state-of-the-art research streams on supply chain risk management (SCRM) based on organizational theoretical background and direct future research toward the use of other related organizational theories. This paper seeks to provide a framework for understanding various organizational theories that can impact the understanding of SCRM.

A systematic literature review on articles published from 1998 to 2020 was conducted manually in the following databases: Emerald, Science Direct, Taylor & Francis Online, and Wiley online library. Among these articles, the paper by Smeltzer and Siferd (1998) is the first article published on the topic. Therefore, that serves as a starting point for the papers' analysis. A total of 109 articles have been selected and reviewed in detail.

The results of the study indicate that the articles which utilize theories in SCRM research have been mostly published in the last three years. The quantitative and case studies have been prevalently applied methods in the articles. In total, 34 theories are listed from the investigated articles. The four commonly studied theories among these are the information processing theory, transaction cost theory, contingency theory, and resource-based view.

This paper is the pioneer in the sense that the paper specifically and directly reviews the SCRM literature in terms of organizational theory usage. For future research, this study offers a diffusion of innovation (DOI) theory that explains the factors which can affect the adoption or diffusion of SCRM practices.

This study examines the influence of different user innovator mindsets on new product development (NPD) performance. The current research explores the relative impact of a product-focused user innovator mindset vs a customer-focused mindset on feedback volume and feedback diversity and investigates the effect of each type of feedback on product improvement and product diffusion.

This study examines these relationships using two distinct types of data. Data on user innovator mindset, feedback characteristics and user innovator improvisation were obtained via an online survey. Archival data on NPD performance measures were acquired directly from an online research database, and results were obtained using confirmatory factor analysis.

The authors find that while neither type of user innovator mindset directly influences NPD performance, user innovators, who are highly customer-focused, have a significant advantage in sourcing knowledge from users in the form of a higher volume of feedback and more diverse feedback. In turn, feedback volume appears to positively influence product improvement, while feedback diversity positively influences product diffusion. Finally, the effect of both types of feedback on product improvement is enhanced for user innovators who are highly improvisational.

This research highlights the important role that customer focus plays in directly obtaining knowledge from customers (i.e. customer feedback) and the effects of that feedback on NPD performance. This study provides evidence that a user innovator's interest in accurately understanding the needs of their peers improves their access to external knowledge and enhances their innovation efforts.

To empirically study the direct and mediating relationships between blockchain technology adoption strategy (BCTAS), electronic supply chain management diffusion (eSCMD), entrepreneurial orientation (EO) and human resources information system (HRIS) in Egyptian banks. This paper aims to connect the dots and show the relationships linking these related constructs after the emergence of this breakthrough blockchain technology.

The authors have undertaken a thematic review of relevant multidisciplinary business management literature and then developed a conceptual model. This model was examined through adopting a mixed-methods approach, through which 300 quantitative questionnaires were filled by information technology (IT) staff at 12 banks in Egypt utilising a snowball sample. Besides, 20 qualitative interviews were carried out with international and Egyptian blockchain experts for exploratory and explanatory purposes. The suggested hypotheses were tested using structural equation modelling.

The results revealed that EO affects positively and significantly BCTAS and HRIS. BCTAS affects positively and significantly both HRIS and eSCMD. Concerning the linkage between external/supply chain and internal/organisational information diffusion, HRIS has a positive and significant effect on eSCMD. The direct EO–eSCMD relationship is not supported. Yet, indirectly, BCTAS mediates significantly EO–eSCMD and EO–HRIS relationships. Further, HRIS mediates significantly the indirect BCTAS–eSCMD relationship.

The findings of this research shed light on the benefits and challenges of adopting BCTAS within emerging markets in general and Egyptian banking in specific, which can support an effective and efficient decision-making process undertaken by strategic and functional banking managers with EO in similar emerging economies.

Conceptually and empirically, it is the first article that investigated direct and mediating EO–BCTAS–HRIS–eSCMD relationships in a promising banking industry of an emerging market. It solved an interdisciplinary research puzzle by piecing together the relevant contemporary literature on production, operations and SC management, entrepreneurship, HR management and strategic technology adoption.