Search Results (84)

Accurately predicting the success of startup financing is critical for strategic business planning and informed investor decision-making. Traditional financing prediction models typically focus on a company’s financial indicators to explore the impact of factors such as resource allocation and strategic choices on financing success, yet they often overlook the important role of social media as an external source of information in influencing financing performance. To address this gap, this paper focuses on the role of social media sentiment in predicting startup financing success and proposes a decision support system (DSS) framework that integrates multi-source data. Specifically, this study combines financial data from the Crunchbase platform with company-related social media news data from Twitter. The BERTweet model is used to perform sentiment analysis on the social media texts, extracting sentiment features such as polarity and intensity to capture public attitudes and expectations toward the company. Subsequently, financial indicators, social media numerical features, and sentiment features are combined to construct a decision support system for predicting financing success using a deep neural network (DNN). Experimental results show that the decision support system incorporating social media data significantly outperforms traditional decision support systems in prediction accuracy, with sentiment features further enhancing the model’s ability to identify a company’s financing performance. Our study provides strong support for understanding the profound influence of public sentiment, offering practical guidance for startups to optimize financing strategies and for investors to make informed decisions. Full article

The emergence of online brokerage platforms, mobile banking applications, and commission-free trading has altered the investment landscape, renewing commercial and scholarly interest in retail investors. In light of these changes, the present study aims to provide a structural overview of the current state of research on the behaviour of retail investors. Based on a dataset of 386 articles sourced from the Web of Science database, this study employs a composite bibliometric approach of a co-word and co-citation analysis as well as a network analysis to determine preceding scientific discourses, current research themes, and potential avenues for future research. The co-word analysis identifies seven distinct research themes: (1) implications for financial performance; (2) information behaviour; (3) behavioural biases and investor characteristics; (4) investor attention; (5) attitudes towards financial risks; (6) socially responsible investing; and (7) complex financial retail instruments. Incorporating applicable research on individual investors, private investors, and household investors from referenced articles, the co-citation analysis reveals nine preceding scientific discourses. Additionally, the network analyses highlight the concepts and publications currently shaping and likely to influence future research in this field. The present study contributes to the academic discourse by mapping the intellectual landscape of retail investor behaviour, suggesting avenues for future research, and offering valuable insights for navigating this dynamic field. Full article

In the digital age, investing in e-gold is increasing in popularity. This study’s objective is to assess the moderating role of dispositional innovativeness between fintech adoption and the intention to invest in e-gold, as well as to understand investors’ behavioral intentions. This study uses the theory of planned behavior model to analyze the data. We prepared a structured questionnaire to collect data from Maharashtra, a state in India, and used PLS-SEM for analytical purposes. We also used focus group interviews to validate the findings from PLS-SEM. Our evidence shows that attitude, subjective norms, and perceived behavioral control significantly impact fintech adoption and the intention to invest in e-gold. This study also confirmed that dispositional innovativeness moderates the relationship between fintech adoption and the intention to invest in e-gold. This study implies that policymakers can redesign the regulation of digital assets to promote transparency, security, and faith in the fintech platform by recognizing the interest rate in e-gold. Full article

This study explores the impact of environmental, social, and governance (ESG) factors on profitability and market capitalization within the European automotive industry. Since the industry is confronted with environmental and regulatory challenges, ESG contributions are valuable to know for strategic decision making and investor attitude. With panel data from 60 automotive firms listed on the Eurostoxx 600 index from 2011 to 2022, the research utilizes panel regression techniques, such as the generalized method of moments, to control for possible endogeneity. The findings show that the social aspect of ESG has a positive effect on return on assets (ROA), illustrating that socially responsible efforts can strengthen operating performance. In contrast, environmental performance weakly negatively affects ROA, probably because substantial sustainability-related expenses are incurred. Governance has no significant impact on profitability. For market valuation, as captured by Tobin’s Q, social factors are negatively correlated, indicating investor doubt regarding quick returns on social investments, while governance is positively but weakly correlated. These results highlight the multifaceted nature of ESG integration in the automotive industry, with the implication that firms need to delicately trade off between sustainability initiatives and profitability and investor expectations. Full article

This paper presents a robust multi-period portfolio optimization framework that integrates interval analysis, entropy-based diversification, and downside risk control. In contrast to classical models relying on precise probabilistic assumptions, our approach captures uncertainty through interval-valued parameters for asset returns, risk, and liquidity—particularly suitable for volatile markets such as cryptocurrencies. The model seeks to maximize terminal portfolio wealth over a finite investment horizon while ensuring compliance with return, risk, liquidity, and diversification constraints at each rebalancing stage. Risk is modeled using semi-absolute deviation, which better reflects investor sensitivity to downside outcomes than variance-based measures, and diversification is promoted through Shannon entropy to prevent excessive concentration. A nonlinear multi-objective formulation ensures computational tractability while preserving decision realism. To illustrate the practical applicability of the proposed framework, a simulated case study is conducted on four major cryptocurrencies—Bitcoin (BTC), Ethereum (ETH), Solana (SOL), and Binance Coin (BNB). The model evaluates three strategic profiles based on investor risk attitude: pessimistic (lower return bounds and upper risk bounds), optimistic (upper return bounds and lower risk bounds), and mixed (average values). The resulting final terminal wealth intervals are [1085.32, 1163.77] for the pessimistic strategy, [1123.89, 1245.16] for the mixed strategy, and [1167.42, 1323.55] for the optimistic strategy. These results demonstrate the model’s adaptability to different investor preferences and its empirical relevance in managing uncertainty under real-world volatility conditions. Full article

This study examines the key factors influencing investment decisions through decision tree regression, grounded in behavioral finance theory. By analyzing a comprehensive dataset incorporating behavioral, demographic, and financial variables—including investment attitudes, decision-making behaviors, financial education, age, income, and education—this study identifies significant predictors of investment outcomes. While the model shows moderate predictive performance (R² = 0.185; MAPE = 172.96%), it identifies hierarchical relationships among behavioral, cognitive, and demographic predictors. These results highlight the complexity of investment decisions and the need for integrative, behavioral-driven approaches in predictive modeling. Investment attitudes (25.88%), decision-making behaviors (19.53%), and financial education (16.68%) emerge as the most influential variables, while traditional demographic factors such as income and age have a lower impact. The hierarchical structure of the decision tree highlights critical decision-making patterns, particularly regarding speculative behaviors and investment attitudes. These findings challenge classical models of rationality by emphasizing the dominant role of behavioral factors in investment decision making. This study contributes to bridging computational modeling with financial economics, demonstrating the utility of decision tree regression in uncovering complex investor behavior. Practical implications include enhancing personalized financial advisory services and designing targeted financial literacy programs to improve decision-making efficiency. These insights, while exploratory, can guide future research and decision-support systems in behavioral finance. Full article

Despite calls to counter unsustainable urbanization, dense, concrete, and overheated urban spaces remain a reality. However, ideological assumptions and priorities related to creating livable urban spaces are only a part of a broader chain of actions that is the construction investment process (CIP), and its participants (Theoreticians, Investors, Designers, Contractors, Controllers, and Users) can play a significant role in addressing negative urban changes through their attitudes. The starting point for analyzing attitudes was Jung’s theory, which led to identifying key attitudes: Thinking, Feeling, Perception, Intuition, Creativity, and Equilibrium. This study aimed to determine the values reflected in CIP participants’ attitudes, identified through individual in-depth interviews with selected experts. Statements were divided into phrases referring to specific features or values and were subjected to qualitative (and limited quantitative) content analyses, supplemented by thematic and sentiment analyses. Feeling emerged as the most frequently mentioned value, followed by Thinking. Designers and Investors attracted the most attention, while Designers and Users were seen as the most controversial groups due to the values and stances they represented. Contractors (especially general and specialized) received the most favorable evaluations. This study concludes with a detailed characterization of the attitudes and values of the CIP participants, highlighting their contributions to the CIP. Full article

The purpose of this study is to analyze the factors influencing the attitudes of women investors in the context of Islamic unit trust funds in Malaysia, with a focus on women’s religiosity and on the perceived religiosity of fund providers. Using the UTAUT model, the study examines data from a survey of 263 Muslim women in Malaysia and considers seven key factors: risk aversion, religiosity, price sensitivity, and Islamic financial literacy on the side of the investing women and past performance, perceived religiosity, and perceived risk on the side of the fund providers. The findings indicate that the perceived religiosity of a fund provider has a significant and positive impact on attitude, with positive moderating effects on the women’s own religiosity and Islamic financial literacy, and a negative moderating effect on the women’s price sensitivity. The study also discusses the practical implications of these findings and offers recommendations for fund providers. Full article

There is growing recognition that build-to-rent (BTR), a novel institutional asset class, could improve rental affordability and housing choice in Australia. Despite favourable market conditions and increasing demand, Australia’s BTR sector remains underdeveloped compared to the US and UK. Although the asset class has attracted significant foreign institutional capital, there is little interest from domestic institutional funds. This contrasting investment behaviour between foreign and domestic funds has brought a new dimension to the debates on BTR in Australia. The study uses qualitative research design to examine institutional investor behaviour towards BTR in Australia. Interviews were conducted with experienced BTR investors across three countries—Australia, the US, and the UK—to understand the barriers and investment behaviour towards BTR. The study finds that the key barriers hindering BTR growth in Australia include unfavourable tax treatment, complex planning processes, and insufficient affordable housing incentives. Institutional investors’ decisions are influenced by firm characteristics, operational capabilities, and risk attitudes. Due to risk considerations, Australian superfunds prefer stabilised assets over new developments. Also, sustainability and ESG factors are increasingly important considerations in BTR investment decisions. The research highlights the need for a supportive regulatory environment, efficient property management, and innovative financing solutions to boost BTR investments. To accelerate BTR growth in Australia, policymakers should address tax disparities, streamline planning processes, and enhance affordable housing incentives. Developing BTR-responsive financial instruments could reduce financing costs and attract more institutional capital to the sector. Full article

This study aims to describe and assess the impact of critical infrastructure (CI) cybersecurity issues on the sustainable development of smart cities. This study highlights the integration of PayTech systems into the broader CI landscape, highlighting their impact on maintaining economic stability and ensuring the smooth operation of city services. Key companies within smart regions, particularly those operating in the payment industries, are essential to maintaining the functionality of critical services. These companies facilitate the processing of services provided to citizens, enabling access to vital municipal services. As key players in the PayTech and online e-commerce sectors, they form a crucial part of modern critical infrastructure, operating within an ever-evolving digital environment. This study examines the recovery processes employed after cyberattacks, focusing on the differing perspectives of internal and external professionals. It identifies significant differences in the perceptions of recovery strategies among internal stakeholders, such as investor relations (IR) teams, reputation management (RM) experts, and Chief Information Security Officers (CISOs), who represent critical infrastructure companies. Additionally, it explores the roles of external auditors, who provide impartial emergency support and perform specialized recovery tasks. Importantly, this study underscores the current attitudes toward future information security strategies and their influence on the financial recovery and reputation of reliable companies following cyber incidents. This research contributes to the existing knowledge by shedding light on the perspectives of both a company’s internal and external specialists involved in the recovery process and cyber resilience strategies in critical infrastructure sectors. Full article

The world’s 300 largest pension funds manage assets for more than USD 21 trillion. A strict orientation to environmental, social, and good governance (ESG) in the investment portfolio of pension funds can play a key role in triggering the economy toward a sustainable transition. Can responsible pension plans be an attractive investment opportunity for young people? Since the performance of pension funds depends on the demographic characteristics of investors, other than the financial results of investment portfolios, this study aimed to test the convenience of ESG-oriented pension plans for young contributors aged 20–29 with different risk propensities and attitudes towards sustainability. The analysis was started using accurate data provided by an Italian pension fund, observed from 2012 to 2022. The methods applied were a Monte Carlo simulation of the individual actuarial balances, the expected utility, and the willingness to pay. The results show that ESG-oriented pension funds are convenient for young people who invest in riskier lines. Still, it is sufficient for a light green preference to persuade young contributors to invest in ESG-oriented funds and balanced lines. The results of the study can support pension fund managers in defining and offering appropriate ESG lines suitable for younger investors. Full article

In the competitive hospitality sector, the adoption of Artificial Intelligence (AI) is essential for enhancing operational efficiency and improving customer experiences. This study explores how key entrepreneurial traits—Entrepreneurial Orientation (EO), Entrepreneurial Self-Efficacy (ESE), and Perceived Business Performance (PBP)—influence managers’ attitudes toward adopting AI in small- and medium-sized enterprises (SMEs). Ts research utilizes data from 287 respondents, gathered through field research with a survey designed to measure the relationships among constructs, employing structural equation modeling (SEM) for analysis. Results reveal that PBP and certain ESE dimensions, such as Initiating Investor Relationships and Developing New Products, have only a modest positive effect on AI adoption. In contrast, EO—specifically Proactiveness and Innovativeness—exhibits a weak negative impact. Importantly, none of these factors directly affect managers’ attitudes toward AI. Instead, this study highlights that managers’ positive attitudes are the strongest predictors of AI adoption, aligning with the Technology Acceptance Model (TAM). The findings offer new insights into key entrepreneurial factors driving AI adoption and emphasize the need for targeted education and supportive policies to facilitate AI integration in hospitality SMEs. Fostering a positive perspective on AI is more important for adoption than overcoming skepticism, as negative attitudes do not influence AI adoption. Full article

Understanding the psychological factors that influence investment decisions is crucial for predicting stock investment retention. This study investigates the mediating role of the Big Five personality traits in stock investment retention, utilizing a modified version of the theory of planned behavior. By examining the influence of investors’ perceived risk and attitudes toward stock investment, data collected via an online survey with The Association of Thai Securities Companies (ASCO) were analyzed using Structural Equation Modeling (SEM). The findings reveal that extraversion, openness, and conscientiousness significantly impact attitudes toward stock investing, which in turn affects investment retention. However, personality traits do not directly influence risk perception. This research provides unique empirical evidence of the independence between the Big Five personality traits and risk perception among Thai stock investors, underscoring the importance of personality in shaping investment behavior through its effect on attitudes. Full article

Hyperbolic discounting is a psychological phenomenon in which individuals prioritize smaller immediate rewards over larger future rewards. Time-inconsistent behavior is deemed irrational as it negatively impacts savings and investment, investment in financial knowledge, and long-term financial and personal well-being. This study hypothesizes that improving financial knowledge, promoting positive financial behavior, and fostering a future-oriented financial attitude can mitigate hyperbolic discounting bias and that these three components of financial literacy enable investors to make long-term economic decisions maximizing utility. We analyzed the responses of 114,170 active investors in Japan to examine the interactions between financial knowledge, behavior, and attitude. Our findings reveal a strong negative relationship between these dimensions and hyperbolic discounting, underscoring their crucial role in shaping individuals’ intertemporal preferences. For researchers, our results highlight the need to integrate multidimensional aspects of financial literacy into investigations of intertemporal discounting behaviors. Policymakers should implement holistic financial education programs that improve knowledge, transform behavior, and shape attitudes. Financial institutions and advisors should prioritize programs that mitigate hyperbolic discounting tendencies among clients. This study represents a significant advancement in the research on financial literacy, offering a comprehensive framework for future studies and practical applications aimed at improving financial decision-making outcomes. Full article

This study explored the key considerations of commercial property investors acting under conditions of economic uncertainty across the following three dimensions: market fundamentals, institutional, and behavioural factors. Over the past few decades, a series of exogenous shocks to the global economy has impacted property performance, investment volumes, and investor perceptions. Acknowledging that uncertainty further complicates investment decision-making, a mixed-methods research approach was adopted to examine the perspectives of 5 experts and 412 property investors. The findings revealed that, while most investors express negative responses to uncertainty and adopt more cautious attitudes, others are more aggressive and attempt to capitalise on emerging opportunities. Market fundamentals are not the only key consideration; access to information and investors’ behaviour all impact how decisions are made under these conditions. In particular, wealthy and more experienced investors make more comprehensive decisions, considering all three dimensions, while aggressive investors may disregard data in favour of intuition. Behavioural biases such as the bandwagon effect and fear of missing out (FOMO) all influence decisions and are sometimes exacerbated by media narratives. Practically, these considerations underscore the complexity of decision-making under conditions of uncertainty and how different investors attempt to navigate market volatility. Full article