Telecommunications Policy最新文献

Ubiquitous high-speed fiber-based and mobile broadband availability is a key economic policy goal in the European Union and other developed countries. Policymakers seek to boost economic growth, productivity, and employment, especially in remote areas, through ambitious broadband targets and substantial public funding. This paper reviews the existing (empirical) literature on high-speed broadband Internet and its socioeconomic impact on key outcome variables. Our main findings are that (i) the socioeconomic benefits in terms of economic growth, productivity, house prices, and education, as well as economic resilience, are high but are also subject to diminishing returns beyond a certain broadband quality level, (ii) the effects on employment are more ambiguous, (iii) the positive socioeconomic effects take hold only after broadband adoption on the demand side, but not with mere availability on the supply side, and (iv) the effects of broadband differ significantly for urban vs. rural and high-skilled vs. low-skilled workers for some of the outcome variables. Based on these findings, we develop recommendations for a cost-effective and efficient broadband policy and identify an agenda for research.

There is an intrinsic relationship between innovation and digitalization, marked by the specific and structural socioeconomic characteristics of our regions and countries. These characteristics explain the territory heterogeneity and determine in many cases specific paths for the next digital transformations in the EU.

But there are some issues countries cannot ignore: are all these economical efforts around innovation well addressed to foster digital transformation? To what extent a country or a region offers a different behavior across this intime relationship between digitalization and innovation?

Innovation is a complex concept built by a multitude of interacting aspects that do not necessarily work synergistically: a framework of conditions, innovation activities, investment, and economics impacts. The consequential results of cross-cutting drivers, such as digitalization, are often difficult to assess, as the achievement of certain targets may also inadvertently hinder progress towards others. Our study describes a comprehensive and systematic European country-based analysis of statistical associations between both, digitalization and innovation indicators operating at several different levels to understand better these apparent contradictions.

The Affordable Connectivity Program (ACP) represents a historic investment by the federal government to address the digital divide. Its goals are both to increase the rate of broadband adoption and make it easier for low-income households to sustain service. But what have been the drivers of ACP enrollment? We know a great deal about trends in adoption and the geography of enrollment among eligible households. But those metrics – especially a focus on enrollment rates among eligible households – are only so useful in explaining ACP sign-ups.

This invites analysis that investigates the drivers of ACP enrollment in a comprehensive way, which this paper proposes to do. The paper hypothesizes that ACP enrollment decisions are not solely individual (i.e., that a household's enrollment decision is structured only by income level), but also influenced by community-wide considerations, such as housing costs, share of occupied houses, presence of anchor institutions such as public libraries, and population density (i.e., whether a place is urban or rural). The paper develops a regression model that predicts ACP enrollment rates among eligible households at the 5-digit zip code geography as a function of the variables discussed above, as well as others such as the racial and ethnic make-up of a zip code area. The analysis also controls for existing levels of broadband subscriptions and computer ownership in a given area. The difference between predicted and actual ACP enrollment rates at the 5-digit zip code level is proposed as a metric of ACP performance. These findings are supplemented with a geographically weighted regression (GWR) model that allows the relationship between each explanatory variable and ACP enrollment to vary by locality. This allows for analyzing and visualizing how these relationships vary across space.

The empirical findings show that high levels of economic distress are a strong determinant of ACP enrollment in a given area, but social and community-wide indicators are important as well. The GWR results demonstrate that important differences in these relationships exist across geographies. Understanding spatial variations in ACP performance can help policymakers and other stakeholders better target resources to address the digital divide.

Indices to measure the extent and penetration of information in an economy are static measures. Information, however, is a dynamic, expanding resource. Information is produced when data from digital computers articulate with human-generated systems where they are transformed into information. Economic information is effective when it fuels technological innovations contributing to total factor productivity (TFP) growth. This paper develops a theoretical model to measure effective economic information (EEI) as a dynamic process. Using systemic design thinking, design systems in data value chains are embedded within their TFP-information absorption ecosystem. The system's characteristics of human capital, economic, institutional, and regulatory factors determine the quality and amount of EEI produced. The EEI measurement model uses differential equations allowing for the dynamic expansion of information to include information-knowledge spillovers. Empirical tests for EEI on TFP for EU countries show that EEI is the key driver for TFP growth, while IT investment alone is only a necessary condition. EEI-type measures direct policy attention towards improving TFP-information absorption ecosystems and supporting the adaption of design processes that are more suitable for their TFP-information absorption ecosystems. Both are necessary to connect IT investment to TFP growth.

This project examines how state broadband policies diffused among the states in the United States over the last 30-year period utilizing a network approach and the State Broadband Explorer dataset curated by the Pew Charitable Trusts’ Broadband Access Initiate. The 621 valid state broadband policies in the U.S. (until January 2021) have been categorized into six main themes: broadband programs, competition and regulation, definitions, funding and financing, infrastructure access, and legislative intent. Our analytical strategy follows a two-step process: (1) to identify the latent network of broadband policy diffusion across the states using the NetInf algorithm; (2) to identify the nodal and dyadic variables that predict the observed diffusion flows. Our objective for the second step is to test out two competing hypotheses: the geographic learning model and the (co-)partisan learning model, which privilege geographic proximity and ideological affiliation respectively as the primary drivers of policy diffusion. The results show that geographic contiguity is the most significant factor predicting broadband policy diffusion. However, the results also identify the low salience of political factors in predicting broadband policy diffusion. Among nodal factors, only one namely divided government (of sender states) is a significant predictor of a diffusion tie. Among dyadic factors, there is one variable that supported political homophily as a significant predictor of diffusion flows (i.e., both states sharing the same type of legislative control). Partisanship appears to be much less of a driver of broadband policy in the U.S. context.

As regulators began prohibiting online platforms from collecting personal data based on the “take-it-or-leave-it” basis, platform firms must adopt more refined user consent rules such as the pay-or-consent approach. Ensuring sufficient user options could increase the welfare of privacy-sensitive users but reduce the efficiency of data-driven business models. To balance the benefits and costs of enhanced privacy protection, regulators should understand the diversity in users' attitudes toward behavioral data collection in free online platforms. Tradeoffs among privacy, conveniences, and free services based on users' heterogeneous preferences are considered to investigate the user's different privacy attitudes in free online platforms. Three distinct user groups were found: the first one reluctantly accepts the “take-it-or-leave-it” condition because of the lack of alternatives, the second one accepts it for free services, and the third one accepts it because it does not matter. These three user segments constituted 32.9%, 47.0%, and 20.1% of all the respondents, respectively. The pay-or-consent approach can be justifiable in terms of balancing the benefits and costs of the privacy regulations if it properly reflects privacy-sensitive users' willingness to pay for privacy.

Mobile payment presently leads the fintech market as an alternative tool for daily transactions. Mobile payment research has remained limited to the field of technological research, but the need for research from a social science perspective has burgeoned. Therefore, it is paramount to suggest guidelines for future studies by identifying deficiencies that are yet to be discovered in the existing research. This paper first examines the research trends related to mobile payment by conducting an analysis of relevant literature from 2013 to 2023. Following that, it identifies the gap between the current state of academic research and the mobile payment research required by experts by using the analytic hierarchy process. The results indicate that current research on mobile payment tends to focus on the field of business and utilizes user surveys to provide industrial implications, whereas experts demand policy studies in the field of finance that utilize a more diversified research approach. The findings suggest valuable implications for academic researchers, industries, and governments with respect to mobile payment solutions.

This study suggests a method to analyze, theorize, and conceptualize public participation in policymaking. Participation is a fundamental component of democracy and is derived from the right to actualize the public's sovereignty by participating in the shaping of collective life. Empirically focusing on consultation procedures that were integrated into setting the policy on network neutrality in the United States and Israel (2009–2017), we present an analytical model to study participation in policymaking processes. The findings of this study call for a reflection on the role of participation in public policy design and its importance. We argue that any assessment of citizens' participatory instances should be separated from institutionalized policymaking and disconnected from the principle of formal decision-making, as participation and institutionalized decision-making are separate fields with a different logic. We further suggest a definition of participation and enumerate its advantages.

As many Over-The-Top (OTT) users opt for mobile devices, mobile network traffic surges. However, current mobile communication technology faces difficulties. To provide a stable video content consumption experience to users, reliable alternatives must be found to resolve the limitation of the conventional approach. Accordingly, wireless Device-to-Device (D2D) caching networks have gained attention as a reliable alternative. Considering it can reduce network-related overheads, save related costs, and improve OTT video consumption environment, there is a high possibility that telecommunication operators want to commercialize this technology. To commercialize wireless D2D caching networks, users need to share their resources, such as personal information, smartphone storage, and battery. This study explores the decision-making process of mobile OTT users regarding D2D caching adoption on their mobile devices in Korea. An online survey of 94 respondents was conducted in South Korea. By using the analytic hierarchy process (AHP) approach, this study devised an evaluation model that includes three major factors: perceived benefits, perceived costs, and perceived situational conditions. The results reveal that risks, rather than situational factors and benefits, predominantly influence user intentions and strategies. Streaming video content via mobile data or Wi-Fi is viewed as the most feasible choice. Moreover, users show a preference for pre-downloading video content over adopting wireless D2D caching networks on their mobile devices. The findings provide a guideline for understanding the responses of mobile OTT service users and their priorities in responding to adopting wireless D2D caching networks.

As a novel form of infrastructure, 6G is poised to become an indispensable component of the future digital economy and serves as a solid guarantee for the development of human society. Given that technological innovation inherently possesses purpose and direction, its progress cannot be divorced from the correct value orientation. However, scholarly attention towards investigating the value proposition of 6G remains limited. Establishing a scientific and rational value system assumes paramount importance in shaping future investments and deployments of 6G and fostering advancements in associated technologies. This paper presents a comprehensive analysis of the value proposition of 6G, examining it from multiple perspectives including economic, social, ecological, cultural, and strategic dimensions. In addition, we explore the four vertical value dimensions of nation, industry, firm and individual. By integrating the technology life cycle framework into our consideration, we elucidate how value is realized and evolves across different stages. The primary objective of this paper is to enhance comprehension regarding the value of 6G and forthcoming technologies while extensively expounding on the potential contributions of 6G towards future economic and social development.