Search results

Due to the disruptive nature of digital transformation, firms can hardly ignore the further digitalisation of processes and business models. Implementing such initiatives triggers enormous investments in infrastructure and software, making the evaluation of digital investments crucial for a firm’s competitive situation.

Given the dynamics and uncertainties inherent in digital transformation, a qualitative, inductive research approach based on semi-structured interviews with high-level finance executives has been employed.

Our findings indicate widespread dissatisfaction with traditional investment appraisal methods for evaluating digital investments. Data also suggest that non-financial considerations are frequently taken into account, albeit implicitly, as participants struggled to clearly conceptualize these criteria.

The literature indicates important research gaps regarding the applicability and usage of traditional, predominantly financial, investment appraisal methods in digital contexts. This research enhances our understanding of digital investment evaluation, by (i) developing an exploratory conceptual framework of potential qualitative evaluation criteria and (ii) providing an in-depth and detailed understanding of the barriers to implementing investment appraisal methods.

This paper investigates the relationship between managerial sentiment and corporate investment in emerging capital markets. Further, we begin with the assertion that the positive impact of managerial sentiment on corporate investment varies according to the corporate life cycle. Lastly, we investigate whether the relationship between managerial sentiment and corporate investment can be moderated by factors like (1) economic policy uncertainty/geo-political risk, (2) size of the firm, (3) financial constraint, (4) industrial competition, and (5) Environmental Social and Governance (ESG) rating.

This study has considered Indian listed companies (465 firms) for the period spanning from 2003–2004 to 2022–2023. This study constructs the managerial sentiment using a novel large language model-financial bidirectional encoder representation from the Transformers (FinBERT), as well as on management discussion and analysis reports. Then, we employ fixed effect regression to investigate the relationship between managerial sentiment and corporate investment. Additionally, we use propensity score matching, two-stage least squares instrumental variables, and a two-step system generalized method of moments approach for robustness tests.

The findings show a positive and significant relationship between managerial sentiment and corporate investment. Additionally, our results demonstrate that this relationship is evident only during the growth and maturity phase of the corporate life cycle. Moreover, uncertainty pertaining to the economy and geopolitical issues, firm size, financial health, industry dynamics, and ESG disclosure also play a crucial role in shaping the investment-sentiment relationship.

The study is unique because it determines the relationship between managerial sentiment and corporate investment by using the novel FinBERT model. In addition, we have introduced a corporate life cycle, which is an essential aspect of our study. Additionally, this research was conducted in an emerging market with more information asymmetry and weaker disclosure rules. Thus, other emerging markets can benchmark the outcomes.

This research article aims to systematically explore the association between digitalisation and individual investors’ behavioural biases. Through an extensive exploration of digitalisation modes and their various serviceable avenues in the investment arena, the study aims to elucidate the impact of behavioural biases on individual investors’ investment decision-making processes.

The study employs Interpretative Phenomenological Analysis (IPA) to gain insights into behavioural finance and the associated behavioural biases of investors in digitalisation. IPA, a qualitative method grounded in heuristic, phenomenological, and idiographic elements, facilitates the exploration of individual investor experiences and the role of digitalisation and behavioural biases within.

Investors are categorised into two groups – decision seekers and decision makers – based on their digital inclination and the purpose behind using digital tools. The attributes of these segments are detailed under the sub-themes of Digital Inclination, Market Cognizance, Sophistication and Maturity, Sophomorism and Perception of Digitalisation. The study also identifies the specific behavioural biases pertinent to each segment. Additionally, it introduces a novel section on the insights related to human emotions, behaviour and sentiment within financial markets.

The essence of the current article is the application of the IPA method to the field of behavioural finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive understanding of both, digitalisation and behavioural biases that affect the individual investor’s decision-making. It offers valuable insights for researchers, academicians and scholars in behavioural finance, enhancing the understanding of how behavioural biases influence investment decisions.

The purpose of this paper is to elucidate the performance discrepancies between shariah-compliant and non-shariah-compliant exchange-traded funds (ETFs), aiming to enrich the academic and practical understanding of Islamic finance‘s nuances in the ETF sector.

Initiating with a broad literature review to cement a theoretical backdrop on Islamic investment principles and the mechanics of shariah-compliant ETFs, the research progresses to devise a comparative analytical framework. This framework focuses on assessing ETF performance through metrics like net asset value returns and volatility, specifically analyzing Blackrock ETFs to draw distinctions in portfolio outcomes and asset compositions.

The examination highlights discernible variances in portfolio performance between shariah-compliant and their conventional counterparts, presenting instances where shariah-compliant ETFs, such as ISUS from Blackrock, deliver competitive returns despite their generally lower net assets compared to conventional ETFs like VUSA from Vanguard. Moreover, the ISUS ETF‘s holdings investigation revealed discrepancies with AAOIFI standards, questioning its strict Shariah compliance and adding depth to the analysis of Islamic financial instruments‘ integrity.

This paper significantly advances the scholarly dialogue on Islamic financial practices within the ETF landscape, providing empirical evidence of performance differentials and compliance intricacies. While prior research has touched upon Islamic investing, this study pioneers a detailed comparative scrutiny, equipped with a novel methodological approach, to dissect the shariah-compliant ETFs‘ operational and ethical frameworks, offering invaluable insights for investors, financial analysts and Islamic finance scholars.

The study aims to identify and understand the underlying behavioral tendencies and motivations influencing investor sentiments and examines the relationship between these underlying factors and investment decisions during the COVID-19-induced financial risks.

The study uses the primary data and information collected from 300 Indian retail equity investors using a nonprobability sampling technique, specifically purposive and snowball sampling. This research uses the insights from Phuoc Luong and Thi Thu Ha (2011) and Shefrin (2002) to delineate behavioral factors influencing investment decisions. Structural equation modeling estimates the causal relationship between underlying behavioral factors and investment decisions during the COVID-19-induced financial risks.

The study establishes that the “Regret Aversion,” “Gambler’s Fallacy” and “Greed” significantly influence investment decisions, and provide a comprehensive understanding of how psychological motivations shape investor behavior. Notably, “Mental Accounting” and “Conservatism” exhibit insignificance, possibly influenced by the unique socioeconomic context of the pandemic. The research contributes to 35% of variance understanding and prompts the researchers and policymakers to tailor investment strategies aligned to these behavioral tendencies.

The findings hold policy implications for investors and policymakers and provide tailored recommendations including investor education programs and regulatory measures to ensure a resilient and informed investment community in the context of India's evolving financial landscapes.

Theoretically, behavior tendencies and motivations have been strongly linked to investment decisions in the stock market. Yet, empirical evidence on this relationship is limited in developing countries where investors focus on risk management. To the best of the authors’ knowledge, this study is among the first to document the influence of underlying behavioral tendencies and motivation factors on investment decisions regarding retail equity in a developing country.

This study investigates the dynamic interactions between the financing of entrepreneurship through Private Equity and several factors, such as stock market valuations, gross domestic product and consumer prices, and the effect of monetary policy in the decision for investments.

Our methodology consists in applying a panel vector autoregression approach that allows testing the causality of the variables of interest without assuming any specific direction. We disaggregate private equity to venture capital investments and later stage private equity and we uncover their asymmetric response to the examined factors. All types of investments are shown to be affected by GDP, stock prices, consumer prices and interest rates. However, the effect of the latter three variables are evidently more pronounced in later stage private equity compared to venture capital.

Our findings contribute to the understanding of the motives behind Venture Capital and Private Equity financings and uncover novel paths of the transmission of monetary policy to entrepreneurial finance.

The novelty of this research concerns the investigation of the monetary policy impact on investment decisions, including venture capital and private equity. This article provides significant highlights for the first time in the relative literature, offering new knowledge in the investment decision-making process in a dynamic framework.

In the modern financial landscape, Artificial Intelligence (AI) is gaining prominence, offering significant economic advantages. This research paper aims to investigate the impact of Behavioural Biases (BB) such as Overconfidence Bias (OCB), Fear of Missing Out (FOMO), Herding Bias (HB) and Regret Aversion Bias (RAB) on Investment Decision-Making (IDM). Additionally, it explores how the AI-led Adoption of Digital Advisory Services (ADAS) moderates these biases among Gen Z investors in India.

The study utilized a convenience sampling method, gathering 457 responses from Gen Z investors in India through an online survey questionnaire. The data was analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM).

The results confirm a significant relationship between OCB, FOMO, HB and RAB on IDM. The study also found that ADAS significantly moderated the relationship between FOMO and IDM, as well as between HB and IDM. However, the moderation effect of ADAS was not supported for the relationships between OCB and IDM, and RAB and IDM.

This research offers valuable insights for academics, individual investors, fintech companies and policymakers. It highlights how behavioural biases affect IDM and underscores the importance of AI-enabled digital services in helping Gen Z investors recognize and manage these biases. Policymakers can use these insights to establish standards for AI use, ensuring regulatory compliance and promoting ethical conduct in AI-driven investment decisions.

The novelty of this study lies in its conceptual approach, particularly in examining the moderation role of ADAS in addressing behavioural biases among Gen Z investors.

By comparing and contrasting the two scenarios of power producers investing in renewable energy and electricity sellers investing in renewable energy, we explore the conditions under which profit growth and carbon emission reduction can be realized, and provide a theoretical basis for decision-making on renewable energy investment by electric power companies as well as for government policy formulation.

This paper constructs a game model of a grid supply chain consisting of a leader generator and a follower seller in the context of the C&T mechanism, considering two scenarios in which the generator and the seller invest in renewable energy. Conclusions are drawn by comparing and analyzing the equilibrium solutions in different scenarios.

The scenario where electricity sellers invest in renewable energy exhibits a higher investment volume compared to the scenario involving power generators. In scenarios where power producers invest in renewable energy, electricity sellers achieve lower profits than power generators, while scenarios with electricity seller' investments yield higher profits for them. Increasing the cost coefficient of renewable energy investment reduces investment volume, electricity prices and electricity demand, leading to decreased profits for electricity seller but increased profits for power generator. A rise in the preference coefficient for renewable energy results in increased profits for electricity seller but decreased profits for power generator.

Addressing a literature gap in the context of low carbon, this study examines the investment scenario of electricity sellers in low carbon technologies, complementing existing research focused on power generators and consumers. The findings enrich knowledge in low carbon investment. By analyzing the investment decisions of both power producers and electricity sellers, this study explores the practical implications of renewable energy investments on the decision-making and operational dynamics of power supply chain enterprises. It sheds light on their profitability and investment strategies.

This study aims to explore the underlying issues of behavioural biases in relation to stock market participation and the challenges of individual investors in Bangladesh. The study identifies behavioural biases affecting individuals’ stock market participation, their circumvention strategies and the importance of financial knowledge in encouraging the participation of individuals in the stock market.

Semi-structured interviews were used in this study to gather information from industry researchers, individual investors, brokers and institutional advisors. Twenty-two experts were contacted, and 13 agreed to participate in the interviews. The study then uses the thematic analysis method to report its findings.

This research shows that investors’ behavioural biases (such as loss aversion, herding, trust, gambler’s fallacy and risk tolerance) are among Bangladesh’s primary drivers of stock market participation. Circumvention strategies (such as poor corporate governance and agency costs) also play a part in individuals’ participation. These influences are in addition to the obvious factors of investment risks, poor infrastructure, poor regulation enforcement and the need for more sufficient investment products.

This study conducted 13 interviews with expert subjects, which is a small sample size. However, the findings achieved saturation and cannot be ignored. Future research should use quantitative or experimental methods with a large sample size to validate the current findings.

This study is pioneering in the Bangladesh stock market, exploring the behavioural biases of investors’ participation in the market. This paper provides valuable insights into investor participation by discovering the underlying behavioural biases that have been continually ignored; these insights may also be relevant in frontier markets in Asian countries.

This study aims to investigate physical capital investments for Azerbaijan in the context of Sustainable Development Goals (SDGs) 6 and 7.

Drawing on the conceptual frameworks of Soto et al. (2020) and Gaspar et al. (2019), this study adopts peer analysis in quantifying investment policy recommendations for Azerbaijan based on data from the World Bank, International Monetary Fund, United Nations Population Fund, the State Statistical Committee of the Republic of Azerbaijan and the US Energy Information Administration.

This study estimates that Azerbaijan invests approximately $1.47bn in their energy sector for 2020–2030 and that total spending on water and sanitation infrastructure increases by 1.91 percentage points of GDP by 2030.

Investment decision-making for physical capital based on the United Nations SDGs is an underresearched yet important topic. This study fills this void for Azerbaijan through peer country analysis.