Investment Risk Research Articles

Is the country’s preparedness for epidemics and pandemics an FDI location factor? An empirical analysis using panel data

Purpose This study aims to validate the hypothesis that a country’s preparedness for epidemics and pandemics, as measured by the GHS Index, significantly influences inward FDI inflows. By examining panel data from 2019 to 2021, the research seeks to elucidate the impact of heightened epidemic and pandemic preparedness on investment behavior, thereby highlighting the importance of health resilience and preparedness in attracting foreign investment and fostering economic growth and development. Design/methodology/approach The study uses panel data spanning 181 countries from 2019 to 2021 and uses logarithmic regression models to analyze the impact of a country’s preparedness for epidemics and pandemics, as measured by the Global Health Security (GHS) Index, on inward Foreign Direct Investment (FDI) inflows. Auxiliary variables including GDP, labor supply, openness rate, inflation rate and political stability are incorporated. Robust weighted least squares estimation techniques are used to account for potential heterogeneity and panel data characteristics. Findings The study reveals a consistent and statistically significant positive relationship between a country’s GHS score and inward FDI, indicating that destinations with robust health systems are more attractive to investors. Higher GHS scores correlate with reduced investment risk, improved business continuity during health crises and enhanced health-care infrastructure, leading to a healthier and more productive workforce. Research limitations/implications While the study provides valuable insights into the relationship between epidemic and pandemic preparedness and inward FDI inflows, several limitations exist. The analysis relies on cross-sectional data from a relatively short timeframe (2019–2021), limiting the ability to capture long-term effects. Additionally, the study focuses on the GHS Index as a measure of preparedness, overlooking other potential determinants of FDI attractiveness. Future research could explore a broader range of health security indicators and incorporate longer-term data to provide a more comprehensive understanding of the relationship. Originality/value This study contributes to the literature by examining the previously underexplored relationship between a country’s epidemic and pandemic preparedness, as measured by the GHS Index and inward FDI inflows. By using panel data analysis and robust econometric techniques, the research provides empirical evidence supporting the positive impact of robust health systems on FDI attractiveness. The findings underscore the importance of prioritizing public health initiatives and epidemic preparedness as integral components of attracting and retaining foreign investment, thereby fostering economic resilience and sustainable development in host countries.

The Influence of Financial Literacy and Islamic Business Ethics on Investment in Islamic Financial Instruments: The Mediating Role of Risk Attitude and the Moderating Role of Religious Knowledge

Current challenges in the Islamic banking sector highlight the urgent need to understand the factors influencing ethical and informed investment decisions. This study aims to analyze the impact of financial literacy and Islamic business ethics on investment in Islamic financial instruments, focusing on the mediating role of risk attitude and the moderating role of religious knowledge. Data were collected through a primary method by distributing questionnaires to 300 bank customers and students in Aceh, Indonesia. The model employed is Structural Equation Modeling-Partial Least Squares (SEM-PLS) using Smart PLS software. The findings reveal that financial literacy significantly positively impacts investment decisions and risk attitudes. Islamic business ethics also significantly influence both investment decisions and risk attitudes. Religious knowledge positively affects investment decisions, while risk attitude has a positive impact on investments. However, the moderating effects of risk attitude and religious knowledge on investment are not significant. Risk attitude serves as a crucial mediator in the relationship between financial literacy and investment, as well as between Islamic business ethics and investment. The study underscores the importance of financial literacy, Islamic business ethics, religious knowledge, and risk attitude in shaping investment behavior in the Islamic finance sector, and highlights the need for integrating ethical practices to enhance investment outcomes.

COMPARATIVE ANALYSIS OF PENSION SCHEME IN NIGERIA AND UNITED KINGDOM: BRIDGING THE GAP

Objective: This study conducts a comparative analysis of pension schemes in Nigeria and the United Kingdom, examining key dimensions to provide a comprehensive understanding of each system. Theoretical Framework: The research objectives focus on comparing the structural frameworks, types of pensions available (state, occupational, and personal), and adequacy of pension benefits. Method: Utilizing a non-doctrinal methodology, the study assesses investment strategies, administrative efficiency, and risk management practices to identify strengths and weaknesses. Research and Discussion: The findings reveal that the pension scheme in the United Kingdom is more robust than Nigeria's. Notably, the UK's pension scheme exhibits a gender bias, with males receiving higher income accruals than females. In contrast, Nigeria's contributory pension scheme neglects the informal sector, unlike the UK's more inclusive approach. The study's implications suggest that collaboration between Nigeria and the UK can bridge the gaps in their pension schemes. Research Implication: This research contributes to the existing body of knowledge by highlighting areas for improvement in Nigeria's pension scheme. The results provide valuable insights for policymakers and stakeholders seeking to enhance the effectiveness and sustainability of pension systems. Originality and Value: The comparative analysis offers a unique perspective on the strengths and weaknesses of each system, informing potential reforms. Ultimately, this study aims to promote dialogue and cooperation between Nigeria and the UK to develop more equitable and efficient pension schemes. By addressing these gaps, both countries can better ensure the financial security and well-being of their citizens in retirement.

Examining the Financial Literacy of Healthcare Professionals: A Research on a Provincial Health Directorate.

This research aimed to assess the financial literacy levels of healthcare professionals working at a Provincial Health Directorate and examine their relationships with various financial domains. The study utilized a cross-sectional online survey. The financial literacy scale was employed to assess the financial knowledge and compentencies of healthcare professionals, providing a structured evaluation of their understandig across various financial domains. Statistical analyses, including correlation analysis, independent samples t-test, and one-way ANOVA, were performed using SPSS-25 and R programs. A total of 240 participants took part, comprising 52.1% males and 47.9% females, aged between 20 and 65 years. Younger healthcare professionals (p=.017) and males (p=.001) demonstrated higher financial literacy levels. Significant correlations were found between financial literacy and domains such as investment instruments, debt and risk management, and personal finance management. Weak but positive relationships were observed between financial literacy and digital assets, indicating emerging trends in digital finance awareness. For instance, males exhibited higher proficiency in investment instruments and debt management, while younger professionals displayed higher knowledge in investment areas. The findings underscore the importance of targeted financial education for healthcare professionals, highlighting the need for sector-specific training programs. Enhanced financial literacy is essential for improving financial decision-making, ultimately benefiting both personal financial well-being and professional performance in the healthcare sector.

Credit Scoring Model Weighted by Investment and Financing Decisions: Case Study in a Building Supply Store

Current literature provides various models for credit risk analysis, called Credit Scoring Models (CSMs). However, these models are not suited to the majority of Micro and Small Enterprises (MSEs). This is compounded by a lack of technical knowledge of microentrepreneurs linked to the high costs and complexity of the CSMs. These issues are significant as 99% of Brazilian companies are MSEs. Therefore, this paper aims to propose a CSM for an MSE that commercializes construction materials in São Paulo, Brazil. This research is quantitative and characterized as a case study whose CSM is based on the Naive Bayes algorithm implemented in Microsoft Office Excel 2016. This model calculates the probability of default and adherence by weighting the results based on the Modern Finance Theory with the Cost of Denying and the Cost of Granting. The application of the model demonstrates that the successes in approvals (70%) and disapprovals (66%) of Credit Sales were significant with a result of R$ 32.20 thousand and an increase in net profit by 124.2%. We have evidenced that the proposed CSM is able to weigh the risk in investment and financing decisions for the Credit Sales of an MSE. This paper provides a low-cost CSM, adapted to reality and easy to handle and implement in MSEs. This research is a reference to the development of CSMs focused on the credit concessions conducted by MSEs.

PARADIGM DEVELOPMENT OF LAND RELATIONS AND HIGH-TECHNOLOGICAL LAND USE

The study substantiates that land resources are a strategic resource, the socio-economic development of society depends on the rationality and efficiency of their use. The economic content of the concept of «land relations» is generalized and it is revealed that they are a component of social relations, arise in the process of interaction of society with natural resources and regulate the norms of behavior of business entities of the agricultural sector of the economy within the framework of land legislation. The basis of land relations is the category of land ownership, therefore changes and development of organizational and legal forms of land ownership are perhaps the most important condition. It is worth noting that land relations in agriculture are part of production relations and can be both stimulating and restraining factors for the rational use of agricultural land and high-tech land use. It was found that land legislation in Ukraine remains fragmentary and often inconsistent between all regulatory acts, and changes to individual regulations and legal mechanisms cause risks for investors and landowners, which creates legal uncertainty and complicates the implementation of the efficiency of land resources use. High-tech land use is a direction of modern agrarian development aimed at increasing the efficiency of agriculture, preserving natural resources and ensuring food security. Systematizing the problems and directions of development of land relations and high-tech land use, it was highlighted that the main priority remains the implementation of the social function of land ownership and land use, which ensures the most efficient land use of land plots for their intended purpose. Thus, the main guidelines of land policy are the stability and effectiveness of the functioning of the system of land relations and agricultural land use, aimed at ensuring the country's food security and increasing the well-being of the population. The development of land relations and high-tech land use should be based on maximum consideration of natural, economic and social conditions and environmental requirements for preserving the environment, protecting land resources and restoring their fertility, increasing the productivity of the land fund, as well as limiting the negative impact of economic activity on flora and fauna, etc.

Do Bank Linkages Facilitate Foreign Direct Investment? An Analysis of Global Evidence

Foreign direct investment (FDI) is essential for enhancing economic resilience and promoting sustainable development. However, inefficiencies in financial connectivity and capital allocation have hindered the facilitation of FDI. Bank linkages between countries in the global sectors of multinational enterprises (MNEs) offer potential solutions to these challenges. In this paper, we focus on whether sustainable FDI can benefit from consolidating bank linkages, which are measured for each pair of countries in each year as the number of bank pairs in both countries that are connected through cross-border syndicated lending. Using the gravity model, we provide empirical evidence based on cross-border data to support the following conclusions: (1) Bank linkages can sustainably enhance the host country’s attractiveness to FDI through information, external financing, and international financial services channels. (2) This positive effect is pronounced in host countries with lower financial development, weaker institution quality, and higher investment risk while remaining insignificant for OECD countries. (3) Bank linkages exhibit a lagged impact on FDI, but newly established bank linkages are more conducive to inward FDI than those established earlier. In this paper, we offer some policy implications for emerging economies and suggest that emerging economies should continue to deepen their financial openness and strengthen international bank links through various means to attract more inward FDI.

Research on Financial Investment Risk Assessment Techniques and Applications

In recent years, the financial markets have undergone rapid development and significant volatility, leading to a pronounced urgency and complexity in investment risk assessment. This study explores the technologies and applications of financial investment risk evaluation, offering an in-depth analysis of the theoretical foundations and practical operations of quantitative, qualitative, and hybrid assessment methodologies. Traditional quantitative techniques, such as the Value at Risk (VaR) model, provide crucial objective data support, while qualitative approaches enrich the breadth of risk identification through expert opinions and seasoned experience. Hybrid methods synergistically combine the strengths of both, adapting to the intricacies of the market environment. The integration of big data and artificial intelligence technologies injects innovative momentum into risk assessment, enabling more precise and timely risk monitoring. Case applications span multi-layered risk management strategies within banks, insurance companies, and hedge funds, offering valuable insights for diverse financial institutions. The study posits that efficient risk assessment relies not only on technological advancements but also necessitates consideration of market dynamics and regulatory environment fluctuations. Continual innovation and practical optimization are pivotal in addressing future challenges.

Forecasting Equity Premium in the Face of Climate Policy Uncertainty

ABSTRACTThis study examines the role of the US climate policy uncertainty (CPU) index in forecasting the equity premium, employing shrinkage methods such as LASSO and elastic net (ENet) to dynamically select predictors from a dataset spanning April 1987 to December 2022. Alongside CPU, other uncertainty predictors like economic policy uncertainty (EPU), geopolitical risk (GPR), and the volatility index (VIX) are considered to assess their complementary roles in out‐of‐sample (OOS) equity premium forecasting. The results reveal that while CPU alone cannot consistently predict the equity premium, it provides crucial complementary information when combined with other predictors, leading to a statistically significant OOS of 1.231%. The relationship between CPU and the equity premium is time varying, with a stronger influence observed during periods of economic downturn or heightened uncertainty, as demonstrated by wavelet coherence analysis. This study also identifies CPU's significant impact on industry‐specific returns, particularly in climate‐sensitive sectors, offering valuable insights for investment strategies and risk management in an era of increasing CPU.

Effects of a defined‐contribution retirement plan on teacher attrition

AbstractIn 2006, Alaska reformed its defined‐benefit (DB) Teacher Retirement System by creating a mandatory 401(k)‐style defined‐contribution (DC) plan for new hires. The new plan increased benefit portability and transferred the investment risk from the employer to the employee. Using individual teacher data for 2005–2017, we show that the reform increased teacher attrition. We also observe, however, that it did not lead to the loss of human capital. The paper contributes to the discussion of the design of DB–DC transitions that can maintain incentives for public‐sector employment.

Problems and challenges of development of Ukraine: investment and personnel aspect

In the conceptual and methodological sense, the article considers war as a force majeure factor, the action of which has multifaceted negative consequences in the form of increasing risks of physical destruction of human and material resources, deterioration of their quality parameters, in particular, the mental and physical state of health of the population. The magnitude and scope of the loss of national wealth as a result of the full-scale war of the Russian Federation against Ukraine deepened the previously formed contradictions and asymmetries of a diverse nature in the economic system of our country. Socio-economic consequences are manifested in large-scale emigration, the appearance of forcibly displaced persons, a shortage of qualified labor, an asymmetry between demand and its supply in the domestic labor market, and a decrease in the number of jobs. Restoration of life-supporting objects of national wealth is considered as an objective prerequisite for the existence and victory of our state in this war. The article substantiates the leading role of state regulation in recovery by using a set of forms and methods of centralized influence on its organization and planning, presents the principles of participation of international partners in it. In the context of the leading role of the regulatory influence of the state on the reconstruction processes of Ukraine, the need for a systematic approach to solving the tactical and strategic tasks of restoring the economic potential of our country is substantiated. When developing and choosing a model for its restoration, priority should be given to the economic interests of domestic investors, employers, and workers. It was determined that its implementation allows to ensure the achievement of multifaceted positive results in the reconstruction of the economy of Ukraine. Objectively necessary prerequisites for the latter are the management of modernization processes by representatives of Ukrainian entrepreneurship, whose activities are based on the principles and principles of corporate social responsibility of business. In the conditions of war, this involves ensuring the functioning and development of enterprises located in the territory controlled by our state, employment of forcibly displaced persons, improvement of their welfare, compliance with laws and payment of all taxes, establishment of public-private partnership between socially responsible business and state institutions. Investing in rebuilding the economic potential of Ukraine is considered an objective phenomenon that is under the influence of state regulatory levers, the use of which is aimed at creating a favorable investment climate in the country. The negative impact on its state due to the lack of effective taxation, imperfection of land legislation, irrationality of the banking system, the absence of a national state credit investment company functionally aimed at identifying investment priorities with their technical and economic justification, control over the provision of benefits, the annexation of Crimea, the occupation of parts of the eastern oblasts and the conduct of military operations there, shelling of populated areas, which increases the likelihood of investment risks.

A portfolio optimization model under uncertain random environment

<p>Uncertain events frequently occur in today’s financial markets. Consequently, the issue of portfolio selection is becoming increasingly significant. This paper thoroughly considers the complexities of stock returns in real-world scenarios and employs uncertain differential equations (UDE), uncertain time series analysis (UTSA), stochastic differential equations (SDE), and random time series analysis (RTSA) to predict stock returns, thereby enhancing the accuracy of these predictions. Furthermore, this paper addresses investors’ preferences and the limitations of using variance as a measure of investment risk. It introduces a risk preference factor and proposes an uncertain random mean-lower variance model. Finally, a genetic algorithm is utilized to solve the model, and numerical simulations are conducted to demonstrate the model’s practicality.<strong></strong></p>

Pengaruh Overconfidence Dimoderasi Gender terhadap Keputusan Investasi pada Generasi Milenial di Karawang

This research aims to examine the influence of overconfidence on investment decisions of the millennial generation in Karawang and evaluate whether gender variables can moderate this relationship. This research uses a survey research design. There is an independent variable, namely overconfidence and a dependent variable (dependent) investment decisions. This research focuses on the millennial generation population in Karawang, which numbers around 1,029,290 people. Meanwhile, the sample used was the millennial generation in Karawang who were active in investment activities, totaling 268 respondents. In this research, verification analysis uses Simple Linear Regression Analysis to test whether or not there is an influence of overconfidence on investment decisions. The next test to see whether the influence of the moderating variable (gender) can strengthen or weaken the overconfidence variable on investment decisions, the Moderated Regression Analysis (MRA) test is used. The research the results show that overconfidence has an influence on the investment decisions of the millennial generation. This generation tends to make investment decisions with a high level of self-confidence, which can lead to investment risks. However, gender is not able to moderate the relationship between overconfidence and investment decisions, meaning that both men and women show the same pattern regarding the influence of overconfidence on their investment decisions. Based on these findings, it is recommended to improve financial education to help the millennial generation make more rational and wise investment decisions.

Aligning common prosperity with sustainable development goals 3 and 7 through sustainable insurance

This paper develops a capped-call option model to evaluate sustainable insurance for achieving common prosperity. It integrates policyholder protection (Sustainable Development Goal 3 (SDG 3)) and the cap-and-trade mechanism (SDG 7) in modeling the Gini coefficient, thereby connecting SDGs 3 and 7 with common prosperity. The main findings are as follows. Life insurance policies that prioritize saving features enhance policyholder protection (SDG 3) but can detract from common prosperity. This impact is magnified when the regulatory cap within the cap-and-trade scheme for carbon-intensive manufacturers becomes stricter. High investment risks for carbon-intensive manufacturers reduce policyholder protection but support common prosperity. A stricter cap-and-trade scheme (SDG 7) also reduces policyholder protection and contradicts common prosperity. This paper avoids concluding any inherent inconsistency between the SDGs and common prosperity, as our analysis is based on the structure-conduct-performance paradigm rather than a macro perspective. Policymakers should carefully balance objectives between SDG 3 and common prosperity to ensure that policies promoting individual security do not compromise broader societal well-being and economic equality, as outlined by the SDGs.

Clean energy challenges and innovation opportunities in Kazakhstan

Abstract Kazakhstan has pledged to transition to a low-carbon economy by implementing national policies and strategies that promote clean energy innovation. However, Kazakhstan is still falling short of its expected targets for energy transition, and there is a lack of knowledge regarding the country’s challenges and opportunities for clean energy development. Towards this end, the current study identifies and assesses the enablers and barriers related to clean energy innovation in Kazakhstan. Using the combination of SWOT analysis, survey data from 41 experts and the DEMATEL decision support tool, we evaluated the key factors affecting Kazakhstan’s clean energy innovation and their implications for energy transition. Assessment results show that the immature business environment, underpinned by technological, institutional, and socioeconomic factors, is perceived as a high-impact constraint for clean energy innovation and green finance deployment in Kazakhstan. Skilled labour shortages, high reliance on hydrocarbons and low retail energy prices are significant challenges to Kazakhstan’s clean energy innovation. The low-profit margin and high investment risk in clean energy projects are identified as transition barriers in the power and energy-intensive industries. In contrast, Kazakhstan’s endowments of resources critical for developing clean energy technologies (rare earth metals, uranium, gas) and the potential of low-carbon investments (e.g. carbon storage) are perceived as prominent enablers of clean energy innovation. Results are consistent across expert subgroups (academia, industry, NGOs, etc). Findings call for policy support to modern and attractive business environments, capacity, and human capital development. The findings can provide helpful insights for countries in Central Asia and beyond with similar socioeconomic structures that aim for a timely energy transition.

Impact of AI on Investment Decision and Financial Inclusion of Rural India: A Study on Young Rural Women Near Ranchi District

Abstract: The integration of Artificial Intelligence (AI) into the financial sector has revolutionized investment decision-making, offering a powerful tool to empower individuals in making informed choices about their financial future. This research paper explores the impact of AI on the investment decisions of rural consumers, shedding light on the transformative potential of AI in promoting financial inclusion in underserved regions. Rural consumers in emerging economies face unique challenges in accessing financial services and making sound investment decisions. The study aims to investigate how AI technologies, including machine learning algorithms and predictive analytics, can address these challenges by providing personalized investment advice, risk assessments, and portfolio optimization for rural consumers. It examines the key factors that influence the adoption and acceptance of AI-driven investment solutions among rural populations. Through a mixed-method research approach, including surveys, interviews, and data analysis, this paper analyses the application of AI in rural investment decision-making. It discusses the benefits of AI, such as improved risk management, increased financial literacy, and enhanced access to financial markets. Additionally, the research assesses potential concerns, including data privacy, ethical considerations, and the need for human oversight in AI-driven investment processes. The findings suggest that AI can bridge the financial literacy gap in rural areas and enhance the investment decision-making capabilities of rural consumers. However, this transformation requires a holistic approach, encompassing not only the development and deployment of AI technology but also regulatory frameworks and educational initiatives to ensure its responsible and equitable use. In conclusion, this research paper highlights the pivotal role of AI in democratizing access to financial opportunities for rural consumers, ultimately contributing to greater financial inclusion and economic growth in rural regions. It offers valuable insights for policymakers, financial institutions, and technology developers aiming to leverage AI to improve investment decisions and financial well-being for rural populations.

UCB and Thompson Sampling Algorithms in Long-Term Investing

In the rapidly evolving financial markets, traditional investment strategies are increasingly being replaced by advanced algorithms. Among these, the Upper Confidence Bound (UCB) and TS algorithms, which originate from the multi-armed bandit framework, have demonstrated significant potential across various sectors. This study utilizes historical stock data from companies during the period from 2019 to 2024 to evaluate the performance of these algorithms in long-term investment strategies. The research aims to identify how these algorithms manage investment risks and maximize returns under varying market conditions. The results reveal distinct behaviors of UCB and TS in the financial markets: UCB performs better in markets with lower volatility, while TS exhibits stronger adaptability in high-volatility environments, thereby enhancing potential returns. Through a detailed comparison of UCB and TS in long-term investment scenarios, this study provides valuable insights into the strategic application of these algorithms. It offers investment strategy guidance for investors and financial strategists and supplies effective information for economic decision-making in relevant fields.

An innovative method for short-term forecasting of blockchain cryptocurrency price

Cryptocurrency market sentiment is relatively unstable, which makes cryptocurrency price an attribute of high volatility. Accurate forecasting methods help to clarify the volatility trend of the cryptocurrency price, thereby reducing the investment risk of participants in the cryptocurrency market. Therefore, this research proposed a new method for short-term forecasting of the cryptocurrency price based on a small sample. This study took three typical blockchain cryptocurrencies (Bitcoin, Ethereum, Litecoin) as experimental objects, chose data intervals with different volatility trends in the U.S. stock indices between 2022 and 2023 as sample data, and used grey correlation analysis to select core affecting variables. Furthermore, this study built a grey multivariate convolution model with prioritized accumulating novel information for conducting prediction experiments on blockchain cryptocurrency price. The research findings demonstrate that the proposed model achieves high prediction accuracy in all experiments, and the model accuracy is superior to the comparison models. This study proposes a scientific prediction approach for blockchain cryptocurrency price, which can guide financial investors in developing and analyzing quantitative financial trading strategies to a certain extent. Meanwhile, this study provides a specific reference for relevant government departments to strengthen cryptocurrency regulation, prevent financial risks, and maintain financial stability.

Evaluating the financial case for investing in, or divesting from, tobacco investments.

Tobacco Free Portfolios urges institutions to pledge against investing in, and to withhold financial services from, tobacco companies. Their goal is to create a 'tobacco-free world'. They argue that without financial and investor support, these companies' operations will become less sustainable. To assess the financial rationale for investing in, or divesting from, tobacco companies. Using data sourced from Bloomberg from 2008 to 2023, we evaluate historical sales volumes, real revenue, real gross profit per cigarette, stock performance and price-to-earnings trends for nine leading listed global tobacco companies. Cigarette sales volumes have steadily declined from 2008 to 2023. Despite efforts to diversify towards novel products, revenues from these products remain small, and cigarettes remain the primary revenue source. Excluding inorganic growth, six of the nine companies experienced real revenue declines from 2008 to 2023. Since 2016, many companies experienced declines in real gross profit per cigarette, indicating that they find it increasingly difficult to offset reduced cigarette sales through net-of-tax price increases. Since 2016, all nine tobacco companies' stocks have substantially underperformed the market. This stands in contrast to the 2008-2016 period, during which all nine companies' stocks substantially outperformed the market. Tobacco companies have experienced deteriorating financial performance since 2016, amidst ever-escalating regulation. It remains unclear whether the growth in novel products will be rapid enough to mitigate the decline in cigarette sales. This uncertainty poses heightened risks for investors, and there is a real possibility of continued poor stock performance.

Dynamic Adaptive Charging Network Planning Under Deep Uncertainties

Charging infrastructure is the backbone of electromobility. Due to new charging behaviors and power distribution and charging space constraints, the energy demand and supply patterns of electromobility and the locations of current refueling stations are misaligned. Infrastructure developers (charging point operators, fleet operators, grid operators, vehicle manufacturers, and real-estate developers) need new methodologies and tools that help reduce the cost and risk of investments. To this extent we propose a transport-energy-demand-centric, dynamic adaptive planning approach and a data-driven Spatial Decision Support System (SDSS). In the SDSS, with the help of a realistic digital twin of an electrified road transport system, infrastructure developers can quickly and accurately estimate key performance measures (e.g., charging demand, Battery Electric Vehicle (BEV) enablement) of a candidate charging location or a network of locations under user-specified transport electrification scenarios and constraints and interactively and continuously calibrate and/or expand their network plans as facts about the deep uncertainties about the supply side of transport electrification (i.e., access to grid capacity and real-estate and presence of competition) are gradually discovered/observed. This paper describes the components and the planning support of the SDSS and how these can be used in competitive and collaborative settings. Qualitative user evaluations of the SDSS with 33 stakeholder organizations in commercial discussions and pilots have shown that both transport-energy-demand-centric and dynamic adaptive planning of charging infrastructure planning are useful.