Pandemics uncertainty and informational globalization in CEE countries: The role of innovation diffusion

The Covid-19 pandemic has dramatically changed how information is shared and processed worldwide. The COVID-19 pandemic has profoundly affected the globalization of information, causing shifts in communication, information dissemination, and technology. This paper investigates the impact of pandemics-related uncertainty on the index of de facto informational globalization (the measure based on high-technology exports, international patents, and used internet bandwidth). The paper uses the panel dataset of 18 Central and Eastern European (CEE) countries from 1990 to 2020. The results indicate that pandemics-related uncertainty negatively affects the informational globalization level in the CEE economies. The findings are robust in utilizing different estimation techniques and considering NATO member CEE countries.

Assessing the environmental impacts of renewable energy sources: A case study on air pollution and carbon emissions in China

This study investigates the impact of renewable and non-renewable energy sources on carbon emissions in the context of China's 14th Five-Year Plan (2021-2025). The plan emphasises a "Dual-control" strategy of simultaneously setting energy consumption limits and reducing energy intensity for GDP (gross domestic product) in order to meet the targets of the five-year plan. Using a comprehensive dataset of Chinese energy and macroeconomic information spanning from 1990 to 2022, we conduct a Granger causality analysis to explore the relationship between energy sources and the level of air pollution. Our findings reveal a unidirectional link, wherein renewable energy contributes to a reduction in air pollution, while non-renewable energy sources lead to an increase. Despite the government's investment in renewable energy, our results show that China's economy remains heavily reliant on traditional energy sources (e.g., fossil fuels). This research is the first systematic examination of the interplay between energy usage and carbon emissions in the Chinese context. Our findings provide valuable insights for policy and market strategies aimed at promoting carbon neutrality and driving technological advancements in both government and industries.

How to promote the adoption of intelligent spray technology in farmers' cooperatives? --Based on the perspective of evolutionary game

In order to accelerate the development of smart agriculture and realize the green transformation of agriculture, the coupling of prospect theory and evolutionary game theory is introduced. Construct a two-party evolutionary game model for the adoption of intelligent spray technology in farmers' cooperatives, analyze the evolution of farmers' cooperatives and government strategy selection and its influencing factors according to the replication dynamic equation, and conduct numerical simulation experiments through Matlab software. The results show that the adoption of intelligent spray technology by farmers' cooperatives and the government's choice of subsidies are the two optimal stable states of the evolutionary system. The government's subsidy policy can effectively stimulate farmers' cooperatives to adopt intelligent spray technology, but when the government subsidy coefficient is greater than or equal to 70%, the decision-making evolution of the government and farmers' cooperatives is unstable. The increase in farmers' awareness of pesticide hazards, the scale of operation of farmers' cooperatives, the price of high-quality agricultural products, and the sensitivity of farmers' cooperatives to profits and losses contribute to the promotion of intelligent spray technology, and the damage probability of intelligent spray technology has a restraining effect.

The role of accelerator programmes in supporting the adoption of digital health technologies: A qualitative study of the perspectives of small- and medium-sized enterprises

Objective

Evidence-based digital health technologies are increasingly important in delivering care to an ageing population with constrained resources. In the United Kingdom, accelerator programmes (APs) have been developed to support the adoption of digital health technologies within the National Health Service. This study aims to explore the perspectives of stakeholders using APs.

Methods

Stakeholders representing nine small -and medium-sized enterprises (SMEs) that were engaged with three different APs (n = 9). Semi-structured interviews were conducted with key informants between April and September 2018. Framework analysis of the data was performed to explore their perspectives on APs.

Results

Four key themes were generated. Informants reported the need to generate evidence before and during the programme, appreciating different types of evidence and their importance. Informants identified several key factors that were a catalyst for success, including involvement in the programme and access to individuals and organisations that were crucial for support. However, several barriers were identified at the programme and system levels. Finally, informants identified key supporting processes that enhanced the adoption of their innovations.

Conclusion

SMEs that develop digital health technologies report that, while APs are useful in supporting the adoption of these technologies, some issues remain. These relate to the emphasis on traditional research evidence that remains a challenge for SMEs to generate. Also, several system-level barriers to innovation in healthcare persist. As APs and SMEs continue to create an entrepreneurial ecosystem, there is increased potential for the development of supporting processes and infrastructure to accelerate the efficient and timely adoption of new digital health technologies.

A multilevel, multi-mode framework for standardization in digital B2B platform eco-systems in international cargo transportation-A multiple case study

Standardization is gaining importance for digital platform eco-systems as they try to balance both stability and flexibility of their core as well as their boundary resources. Our knowledge on which factors influence standardization processes in business-to-business (B2B) focused digital platform eco-systems remains limited. Using three B2B platform eco-systems from the cargo transportation and seaport eco-system context, we apply a multiple case study to investigate which factors affect the standardization mode and the standard adoption. Based on 19 interviews and a systematic coding procedure, we identified 24 factors and cluster them into four overarching themes. We show the relatedness between standardization and innovation research, identify standard characteristics as the most important theme of factors and show that standardization has to be seen as a dynamic and interconnected process, as some factors are interdependent but the controllability varies between factors. Lastly, implications of these results and future research directions are discussed.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12525-022-00551-1.

Innovation diffusion: how homogenous networks influence the uptake of community-based injectable contraceptives

Background

Studies have shown that social networks influence health behaviors, including the adoption of health innovations. This study explored the potential for early adopters of community health worker-delivered injectable contraceptives (CHWDIC) to influence the uptake of this innovation by women in their social networks.

Methods

This Social Network Analysis (SNA) study was conducted in Gombe, Nigeria. Twenty women who were early adopters of the CHWDIC were recruited. Each participant (ego) listed ten women of reproductive age (alters) with whom they related. An interviewer-administered questionnaire was used to collect from each ego, data about the nature of her relationship with each alter (ego-alter relationship), whether she talked about CHWDIC with each alter, and whether her listed alters talked to each other about CHWDIC (alter-alter relationship). Data were also collected on age, marital status and education level for each ego and alter. Data were analyzed with UCINET social network analysis software. Variables of interest include homophilia (similarity), density (number of ties as a proportion of possible ties), degree (popularity) and betweeness (frequency of connecting actor pairs who otherwise might not communicate).

Results

There were 20 egos and 200 alters. Between two thirds (alters) and three quarters (egos) of the women were 30 years or older. All of the egos and 196 (98%) of alters were married. Most of the networks had similar (homophilic) actors according to certain sociodemographic characteristics - ethnicity, age, education and type of marriage. More than 90% of the networks had density greater than 50%, suggesting high cohesion in most networks. The majority of actors in these networks used injectable contraceptives. In some of the networks, few actors with the highest prominence (betweeness centrality) were not users of injectable contraceptives.

Conclusion

The study illustrates the application and feasibility of ego SNA in identifying champions and opinion leaders among women of reproductive age group. It also shows the influence of social networks on the diffusion of community-based injectable contraceptives, and how homophilic and dense networks may have positive health externality. The interrelatedness of network members’ decision to adopt a health innovation was also demonstrated by the findings of this study.

Collective behavior

The resurgence of interest in collective behavior is in large part due to tools recently made available for conducting laboratory experiments on groups, statistical methods for analyzing large data sets reflecting social interactions, the rapid growth of a diverse variety of online self-organized collectives, and computational modeling methods for understanding both universal and scenario-specific social patterns. We consider case studies of collective behavior along four attributes: the primary motivation of individuals within the group, kinds of interactions among individuals, typical dynamics that result from these interactions, and characteristic outcomes at the group level. With this framework, we compare the collective patterns of noninteracting decision makers, bee swarms, groups forming paths in physical and abstract spaces, sports teams, cooperation and competition for resource usage, and the spread and extension of innovations in an online community. Some critical issues surrounding collective behavior are then reviewed, including the questions of "Does group behavior always reduce to individual behavior?""Is 'group cognition' possible?" and "What is the value of formal modeling for understanding group behavior?"

Social learning strategies in networked groups

When making decisions, humans can observe many kinds of information about others' activities, but their effects on performance are not well understood. We investigated social learning strategies using a simple problem-solving task in which participants search a complex space, and each can view and imitate others' solutions. Results showed that participants combined multiple sources of information to guide learning, including payoffs of peers' solutions, popularity of solution elements among peers, similarity of peers' solutions to their own, and relative payoffs from individual exploration. Furthermore, performance was positively associated with imitation rates at both the individual and group levels. When peers' payoffs were hidden, popularity and similarity biases reversed, participants searched more broadly and randomly, and both quality and equity of exploration suffered. We conclude that when peers' solutions can be effectively compared, imitation does not simply permit scrounging, but it can also facilitate propagation of good solutions for further cumulative exploration.