Internet Investment Research Articles

Infrastructure and Structural Change in Africa

Abstract Past investments in electricity, Internet, and road infrastructure, in isolation and bundled, have contributed to structural transformation and economic development in Africa. Using new data on the expansion of the road, electricity, and Internet networks over the past two decades, the paper shows that having access to both paved roads and electricity has led to a significant reallocation of labor from agricultural to both manufacturing and services. Adding access to fast Internet has had a major impact on structural change, with an even larger impact on reallocating labor away from agriculture. The paper then uses a spatial general-equilibrium model to quantify the impacts of future regional transport investments, bundled with electricity and Internet investments, on economic development in countries in the Horn of Africa and Lake Chad region.

Экономические интересы и риски участников операций с цифровыми финансовыми активами

Based on empirical materials on the investment practice of the Russian financial market, the article examines the economic interests of participants in operations with digital financial assets as well as the risks to which they are exposed in these investment relations. The authors identify coinciding and immanent to each of the participants in the operations target intentions that the participants are interested in implementing. The participants are the Bank of Russia, the investor, the operator of the information system in which the issue of digital financial assets is carried out, the recipient of the investment, and the bank of the operator of the information system. The risks specific to each of these participants are disclosed and analyzed, and the authors substantiate proposals for the prevention and relief of the identified risks likely when conducting operations and digital financial assets. The dynamics of the admission of information system operators and operators of the exchange of digital financial assets to the financial market are being studied, and the composition and volume of their operations for the issuance of digital financial assets for the period 2022–2023 are being critically assessed. The dynamics of the number of recipients of investments (persons issuing digital financial assets and the total volume of attracting resources from investors through the issuance of digital financial assets) are investigated. The dynamics of the growth of the number of individual investors in the Russian financial market are considered using the example of their client accounts with positions on securities; proposals are made on the need to adopt a targeted federal program to train citizens in behavior in the field of Internet investment. A methodological matrix of interests-risksmeasures has been formed for participants in operations with digital financial assets, which provides for the allocation of overlapping and immanent interests-risks-measures and discloses mandatory preventive measures. Which should be applied by each of the participants in operations with digital financial assets to ensure timely and full execution of settlements between them and stable turnover of digital financial assets in the investment segment of the Russian financial market.

Sectoral risk contagion and quantile network connectedness on Chinese stock sectors after the COVID-19 outbreak

PurposeThis study aims to explore the risk spillover effects among different sectors of the Chinese stock market after the outbreak of COVID-19 from both Internet sentiment and price fluctuations.Design/methodology/approachThe authors develop four indicators used for risk contagion analysis, including Internet investors and news sentiments constructed by the FinBERT model, together with realized and jump volatilities yielded by high-frequency data. The authors also apply the time-varying parameter vector autoregressive (TVP-VAR) model-based and the tail-based connectedness framework to investigate the interdependence of tail risk during catastrophic events.FindingsThe empirical analysis provides meaningful results related to the COVID-19 pandemic, stock market conditions and tail behavior. The results show that after the outbreak of COVID-19, the connectivity between risk spillovers in China's stock market has grown, indicating the increased instability of the connected system and enhanced connectivity in the tail. The changes in network structure during COVID-19 pandemic are not only reflected by the increased spillover connectivity but also by the closer relationships between some industries. The authors also found that major public events could significantly impact total connectedness. In addition, spillovers and network structures vary with market conditions and tend to exhibit a highly connected network structure during extreme market status.Originality/valueThe results confirm the connectivity between sentiments and volatilities spillovers in China's stock market, especially in the tails. The conclusion further expands the practical application and theoretical framework of behavioral finance and also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management across stock sectors.

Terra Luna and the Future of Internet Investments: Towards a Framework for Investors’ Protections

Terra Luna and the Future of Internet Investments: Towards a Framework for Investors’ Protections

Qualitative interviews with physicians: Overcoming barriers to access to bring telehealth to older adults during COVID-19

Introduction: While the COVID-19 pandemic increased telehealth uptake, concerns surrounding access to telehealth visits emerged for older adults, especially those that are under-resourced, rural, and non-English speaking. We aimed to identify strategies employed by physicians to improve access to medical care via telehealth for older adults during the pandemic. Methods: Using purposeful sampling, we recruited physicians for 30-minute semi-structured interviews. The interviews focused mainly on telehealth’s usability for older patients, and specific strategies physicians employed to facilitate access to care for older adults with varied needs and skills. Interviews were coded using NVivo software and analyzed using framework matrix analysis. Results: Of 48 physicians (geriatrician n = 18, primary care n=15, emergency n=15) interviewed, median age was 37 (interquartile range 34-45), and 27 (56%) were women. Our data suggests that older adults who were under-resourced, rural, or non-English speaking faced greater challenges in using telehealth. Physicians addressed these barriers with strategies tailored to individual patient needs and practice setting resources. Strategies included employing auditory augmentation and speech modifications to enhance understanding, using caregivers and home services to overcome inexperience with navigating technology, device distribution programs for those without equipment access, and real-time interpreter technologies. Physicians reported that telehealth was successful in reducing transportation barriers, whether due to distance or mobility impairments, especially among older adult populations and reducing “no-show” appointment rates. Conclusions: Adoption of strategies to overcome technological and systemic barriers may improve equitable access to age-friendly telehealth for older adult patients. Physicians reported optimism that telehealth could be used to expand access to medical care for older adults with the right technological infrastructure, payment models, and support. Although challenges remain, they may be overcome with additional technical training for clinicians and patients, investment in telehealth infrastructure and broadband internet, and policy changes to promote telehealth access for this diverse patient population.

Modelling the Language of Cyber Scammers: A Forensic Linguistics Analysis of Malaysian Illegal Investment Scheme

Over the last few years, there are growing concerns over the astronomical increase of reported cases of illegal internet investment schemes in Malaysia. Although the Central Bank of Malaysia (CBM) regulates and supervises financial institutions in order to combat illegal investment scheme through Financial Services Act 2013 (FSA 2013) and Islamic Financial Services Act 2013 (IFSA 2013), they do not protect the consumers should they choose to deal with the illegal financial service providers. The large financial losses have a negative impact fiscally on investors’ socioeconomic. Hence, this study is proposed to analyse Malaysian illegal internet investment scammers’ language properties to provide cyber defense for the public. Using Zhang and Wildermuth’s (2009) content analysis process, this study intends to examine the linguistic strategies used by scammers in their websites to deceive their targets. This study will focus on several websites identified by CBM as the primary data source. Semi-structured interviews will be conducted with personnel from relevant government agencies. For triangulation purposes, individuals who have experienced investing and willing to share their experiences and data will be interviewed. All data will be coded and categorised, and emergent themes will be presented to answer research questions. With great hope, this study’s results will help provide comprehensive public education about these scams’ linguistics strategies as a strong defense against them. The results may also help the authorities develop better crime prevention methods and contribute to the criminal justice system in presenting more significant linguistic evidence in the court of law.

Spatial Aggregation Analysis and Systemic Risk Prevention of Internet Finance Based on Neural Network Model

With the development of science and technology, the application of neural network model is more and more extensive. In order to avoid the outbreak of financial crisis, economists and policy makers around the world pay special attention to the timely warning of financial crisis. If we can make an accurate early warning of the economic crisis, the government and regulatory agencies will have more time to deal with the possible risks and avoid major interference to economic growth. Based on this, this paper studies the spatial aggregation analysis and systemic risk prevention of Internet Finance Based on neural network model. Based on BP neural network, this paper constructs a spatial econometric model by using spatial econometric analysis method, and analyzes the empirical results of financial spatial aggregation. The results show that the Moran’s I value of China’s Internet finance index in December 2019 is 0.372, P value is 0.001, Moran’s I value of Internet payment is 0.395, P value is 0.002, Moran’s I value of Internet monetary fund is 0.357, P value is 0.001, Moran’s I value of Internet investment and financing is 0.324, P value is 0.002, Moran’s I of Internet insurance is 0.313, P value is 0.001. The results show that there is spatial agglomeration in the development of Internet finance in China. In addition, this paper also studies the systemic risk of Internet finance, analyzes its causes and puts forward corresponding preventive measures.

Characteristics Influencing Digital Technology Choice in Digitalization Projects of Energy Industry

Abstract Digitalization projects are actively underway in the energy industry, such as the power industry and oil and gas industry. However, there has been no in-depth and quantitative analysis of the relationships between the participants, industry, and technology of digital projects. Therefore, this study focused on which technologies are invested according to key characteristics such as the types of participants and industries driving digitalization projects. This study also examined whether there are differences in technology choices depending on the degree of clean energy exposure. Based on statistics from Bloomberg New Energy Finance (BNEF), a total of 711 projects were analysed using multinomial logistic regression (MNLR). As a result, the proportion of Analytics software was generally higher in the whole industry, and the energy industry was more likely to invest in Analytics software than in other industries. Comparing the power, oil and gas sectors, there was a high probability of investment in Internet of Things (IoT) in the power sector and Automation in the oil and gas sector. In the type of cooperation between energy companies and industrial companies, the probability of investing in Analytics software was significantly higher. In the case of cooperation between energy companies and information and communications technology (ICT) companies, in the oil and gas sector, Analytics software and Cloud/Data accounted for a large proportion. This study provides insight into the effect of characteristics of energy digitalization projects on the technology choice.

Internet Penetration and Regional Financial Development in China: Empirical Evidence Based on Chinese Provincial Panel Data

The Internet has revolutionized the patterns of financial development and economic growth. To assess the impacts of internet penetration on the financial industry, this paper analyzed ten-year Chinese provincial panel data and concluded that regional Internet penetration accelerates financial development. Furthermore, the efficiency of Internet investment in underdeveloped provinces is better than that in developed provinces. More meaningfully, Internet penetration promotes the transparency of the securities market and regional financial participation. This indicates that Internet technology facilitates the advancement of the finance industry and the securities market.

The Relationship between the Internet and Foreign Direct Investments in Turkey: The Toda-Yamamoto Causality Approach

This study aims to determine the relationship between foreign direct investments and the internet in Turkey. The relationship in question is researched by using annual variables for the 1993-2017 periods with the help of Toda-Yamamoto causality testing. According to the findings acquired, there is a bi-directional causal relationship between foreign direct investments and the internet. The importance of this conclusion is that it detects the increase in foreign direct investments as the number of internet users in Turkey increases. Accordingly, it can be stated that investments in the internet use can promote the inflow of foreign direct investments.

Modelling the Diffusion of Investment Decisions on Modular Social Networks

In the financial market, information and investment behaviors disseminate in investor social networks, and different contagion patterns may cause diverse investment trends. Prior studies have investigated the impact of investor social networks, but few have considered community structure. In this paper, we study the impact of the community structure of investor social networks on the diffusion of internet investment products. A two-stage diffusion model is proposed, and the clustering coefficient and modularity of an investor social network are considered. The results show that both modularity and the clustering coefficient have an impact on the diffusion velocity and scale and that the impact is most evident at the stage of explosive growth. The negative influence of a large modularity can be hardly mitigated by adjusting other factors. Furthermore, a decrease in modularity and an increase in the clustering coefficient can better facilitate diffusion when the temporary investment rate is high and can partly offset the negative impact of information discarding and divestment.

The Impact of Herding Tendency in Modular Networks on the Diffusion of Internet Investment Products

In this paper, we aim to study the impact of the shift in herding tendency on the diffusion of internet investment products in modular social networks. The epidemic spreading mechanism is applied and numerical analyses are conducted. The results suggest that the increase in herding tendency slows down the diffusion process and postpones the outbreak time of the diffusion, but such negative effects can be compromised when the independent acceptance willingness is high. When independent acceptance willingness is low, the limited extent of the herding tendency increases the diffusion scope. In addition, the expansion of the propagation lifetime or the increase of the clustering coefficient increases the threshold so that the herding tendency has an effect on outbreak size. Further, the growth of the herding propensity tends to magnify the positive influence of the clustering coefficient and the negative effect of the modularity.

IoT and BDA in the Brazilian future logistics 4.0 scenario

Abstract Paper aims This paper aims to identify the degree of interest and expected return time on investment in Internet of Things (IoT) and Big Data Analytics (BDA) technologies by Brazilian logistics companies. Originality A logistics system that meets the requirements imposed by Industry 4.0 is known as Logistics 4.0. According to the current scientific literature, IoT and BDA technologies are the most promising for the Logistics 4.0 applications. Studies on the adoption of these technologies in Brazil are still embryonic and this paper collaborates to narrow this knowledge gap. Research method Exploratory research was conducted using the quantitative approach. Main findings The evidence of the interest in investment in IoT and BDA by Brazilian logistics companies, confirming the current literature. Implications for theory and practice The identification of the intended practical applications for Iot and BDA, as well as the expected difficulties in the implementation of these Technologies.

Internet of Things and Their Coming Perspectives: A Real Options Approach

Internet of things is developing at a dizzying rate, and companies are forced to implement it in order to maintain their operational efficiency. The high flexibility inherent to these technologies makes it necessary to apply an appropriate measure, which properly assesses risks and rewards. Real options methodology is available as a tool which fits the conditions, both economic and strategic, under which investment in internet of things technologies is developed. The contribution of this paper is twofold. On the one hand, it offers an adequate tool to assess the strategic value of investment in internet of things technologies. On the other hand, it tries to raise awareness among managers of internet of things technologies because of their potential to contribute to economic and social progress. The results of the research described in this paper highlight the importance of taking action as quickly as possible if companies want to obtain the best possible performance. In order to enhance the understanding of internet of things technologies investment, this paper provides a methodology to assess the implementation of internet of things technologies by using the real options approach; in particular, the option to expand has been proposed for use in the decision-making process.

How to create an online investment and its impact on economic growth in Iran and comparing it with seven developed and developing countries including China, Japan, Malaysia, Korea, Indonesia, India and Singapore

This research is a description of correlational type in terms of applied purpose and methodology, because it seeks to discover the relationships of each of the variables of the research and It is applicable because its expected results can be applied in Iran. The statistical population of this study includes data on Iran and the seven developed and developing countries of China, Japan, Malaysia, Korea, Indonesia, India and Singapore, which are data for 2016 and 2017. According to the limited population of the statistical community, the whole number method has been used to determine the sample size. In this research, the tools for evaluating and measuring the considered variables are time series. To analyze the data of this research, Excel software has been used. The outcomes indicate that Internet investment affects economic growth in Iran and the seven developed and developing countries of China, Japan, Malaysia, Korea, Indonesia, India and Singapore.

Impact of information spread and investment behavior on the diffusion of internet investment products

Social networks play an important role in financial markets because the information diffusion in social networks influences the participation of investors. Prior studies have investigated the impact of investor social networks, but few have explored the impact of investment behavior based on information spread in social networks. In this paper, we propose a model for studying the influence that information dissemination and investment behavior in social networks have on the adoption of internet investment products. Information spread process, temporary investment, regular investment and divestment are considered. The results show that the positive influence of regular investment and the negative impact of divestment are not sensitive to the time scale. In addition, the positive impact of regular investment rate is obvious only when the temporary investment rate is not too small, and vice versa. Furthermore, the negative influence of divestment and the information rejection can hardly be offset by increasing the regular investment rate.

Information content of web-based stock ratings: the case of Motley fool CAPS data

PurposeThe purpose of this paper is to answer a fundamental question – are individual stock picks by a particular internet investment community informative enough to beat the market? The author observes that the stock picks by the CAPS community are reflective of existing information and portfolios based upon CAPS community stock rankings do not generate abnormal returns. The CAPS community is good at tracking existing performance but, it lacks predictive ability.Design/methodology/approachThe study uses a unique data set of stock ratings from Motley Fools CAPS community to determine the information content embedded in these ratings. Observing predictive ability of this web-based stock ratings forum will raise questions about the efficiency of the financial markets. The author forms stock portfolios based on stocks’ star ratings, and star rating changes, and test if the long-short portfolio strategy generates significant α after controlling for single, and multi-factor asset pricing models, such as Fama-French three-factor model and Carhart four-factor model.FindingsThe paper finds no evidence that the CAPS community ratings contain “information content,” which can be exploited to generate abnormal returns. CAPS community ratings are good at tracking existing stock performance, but cannot be used to make superior forecasts to generate abnormal returns. The findings are consistent with the efficient market hypothesis. Furthermore, the author provides evidence that CAPS community ratings are themselves determined by stock performance rather than the other way around.Originality/valueThe study employs a unique data set capturing the stock ratings of a very popular web-based investment community to evaluate its ability to make better than random forecasts. Besides applying well-accepted asset pricing models to generate α, the study conducts causality tests to discern a causal relation between stock ratings and stock performance.

AN INVESTMENT PORTFOLIO RECOMMENDATION SYSTEM FOR INDIVIDUAL E-COMMERCE USERS

Choosing appropriate portfolio which can maximize the revenue in a bearable risk level is the most crucial decision for investors. Traditionally, this kind of decision requires a great deal of efforts and time, and usually made by financial professionals. It’s difficult for people without professional knowledge to choose appropriate investment portfolio by themselves. The objective of this paper is to develop a recommendation system which can recommend specific investment plan for different risk preference Internet investors. In the proposed recommendation system, the VaR method is used to measure the risk level of securities and risk preference of investors. In addition, a collaborative filtering algorithm is adopted to recommend portfolio that satisfy risk preference and requirements of investors, by considering the investor’s history behavior and the history behavior of nearest neighbor investors with similar risk preference. Finally, experiments are conducted to demonstrate the feasibility of the proposed recommendation system.

Connected for Development? Theory and evidence about the impact of Internet technologies on poverty alleviation

Based on the assumption that increased access to internet services boosts economic growth and improves the well‐being of the poor, governments in both developed and emerging regions are heavily investing in internet connectivity projects. This article reviews the existing evidence as to the impact of internet technologies on various development dimensions, and articulates the empirical evidence into an analytical framework that seeks to identify the micro‐linkages between internet adoption and poverty alleviation. The review suggests that the development pay‐offs of internet technologies are ambiguous due to two interrelated effects. First, because effective appropriation requires a range of skills as well as complementary investment in human capital and organizational changes. This tends to favour well‐educated workers and firms with more innovative capacity and access to finance. Second, because the positive effects of internet dissemination on market co‐ordination and political institutions grow exponentially with adoption levels. As a result, while the evidence indicates that advanced economies are reaping significant benefits from internet investments, the returns for less advanced economies, and in particular for the fight against poverty in these regions, remain uncertain.

The Impact of Mobile Payments on the Internet Inclusive Finance

<p>Expanding the degree of financial inclusion is one of the important ways to deepen the effect of the Internet. Internet finance in China greatly reduces the information asymmetry and decreases the transaction costs between financial participants, which to some extent promotes the reform of financial systems in China. Besides the elite and center institutional arrangements, some so-called grassroots or civilian financial structures appear. Thus the finance has begun to show a trend of financial disintermediate. This paper selected some variables to build a measure system, based on the 2015 Household Financial Survey. It firstly analyzed the correlation of variables and tested the variance factors through the analysis of use frequency of mobile payment and its transaction amount, meanwhile through the analysis of the impact of family investment structure on the Internet investment transactions. Then it used principal component analysis method to analyze multiple variables in reduced dimensionality. After that it tested ADF unit root and Granger causality of screened indexes, and established a stepwise multivariate linear regression model. Finally, this paper illustrated that the expansion of mobile payment transaction had an impact on the increase in the Internet financial investment transactions based on the empirical analysis and theoretical deduction, and then the paper gave some relevant recommendations.</p>