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The purpose of this study is to explore and understand, how strong financial literacy influences the cognitive biases of students in Germany while investing. Second, it also evaluates the most influential cognitive biases that students encounter when undertaking their investment decisions within this environment.

A quantitative approach is used to assess the relationship between financial literacy and students’ investment-related cognitive biases by using the frameworks proposed by Clercq (2019) and Pompian (2012).

The results advocate that the students’ financial literacy positively impacts their cognitive biases within the investment process. It additionally revealed the most significant biases regarding students’ investment decision-making and proposed the possible reasons behind their behavioral distortions.

The study provides a detailed review of the behavioral tendencies of the younger generation while investing and creates recommendations for prospective researchers.

This research lies at the junction of the behavioral finance field, suggesting that it assists in developing a theoretical framework of cognitive biases within students’ financial decisions. Furthermore, it serves as an addition to the financial management subject course that would provide valuable insights about, first and foremost, financial literacy and subsequently, the theory behind the investment process.

This is an acceptable fact that firms put efforts to maximize shareholders wealth but there is growing demand that firms are also accountable to various stakeholders associated directly or indirectly with the firms' business activities. Investors now evaluate firm's performance not only from financial perspective but also consider environment, social, and governance (ESG) factors when taking investment decision. ESG is not visible in firm's annual financial reports but investors do not deny its significance when valuing firms. There are increasing interests in ESG by communities, professionals, and government bodies, and all are interested to keep it as part of firms' regular activity and have to relate it with firm performance and efficiency that affects firm value. Still, there are difficulties in integration of ESG factors into investment decision-making, but efforts are being put to overcome all the issues. Firms which consider ESG are in a good position to achieve their long-term financial goals as they are likely to attract capital, lower borrowing costs, mitigate risks, and maximize shareholders value.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

This study aims to establish the factors affecting the financial investment decision-making of an investor, with specific reference to investors’ emotions and how various events such as festivals, the pandemic and sports matches affect their investors’ investment decision-making. The authors further intend to understand the role of these investor emotions in creating stock market anomalies.

Twenty-nine semistructured exploratory interviews with fund managers from the top 10 asset management companies in India, who deal with individual investors regularly, were taken. The interviews were conducted to identify and describe the underlying ideas and sentiments that influence an individual’s investment behavior.

Although risk and return are the primary motivators of investment decisions, fund managers’ daily interactions with individual investors are affected by unpredictability and technical ambiguity, and investing is an inherently emotionally arousing process, according to the findings of the in-depth interviews.

To the best of the authors’ knowledge, this study is one of the first studies in Indian market to report the views of financial professionals about the emotional aspect of investors in making an investment decision. With most of the research conducted using quantitative methods, the current study brings in the perspective of financial professionals using primary data.

The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

When is it more profitable for multinational manufacturers to manufacture in high-cost environments and when in low-cost environments? While the literature offers many cues to answer this question, too little empirical research directly addresses this. In this study, we quantitatively and empirically investigate the financial effect of companies' production footprint in low-cost and high-cost environments for different types of production networks.

Using the data of 770 multinational manufacturing companies, we analyze the relationship between production footprints and profitability during four calendar semesters in 2018 and 2019 (N = 2,940), investigating the moderating role of companies' production network type.

We find that companies with networks distinguished by both high levels of product complexity and process sophistication profit the most from producing to a greater extent in high-cost countries. For these companies, shifting production to low-cost countries would be associated with negative performance implications.

Our findings suggest that the production geography of companies should be attuned to their network type, as defined by the companies' process sophistication and product complexity. Manufacturing in low-cost countries is not always the best choice, as doing so can adversely affect profits if the products are highly innovative and the production processes are complex.

We contribute to the scarce empirical literature on managing global production networks and provide a data-driven analysis that contributes to answering some of the enduring questions in this critical area.

The aim of this study is to understand the levels (i.e. mild vs intense) of task conflict (TC) expressions between angel investors and entrepreneurs at the post-investment stage and how it affect angel investors’ follow-on investment intentions with the same entrepreneur.

Survey data was gathered from 71 angel investors in China. Mplus was used to test the proposed research model.

This study found that angels perceive affective conflict (AC) when engaged in intense TC, unlike the case for mild TC expressions. Furthermore, the analysis shows that, unlike mild TC expressions, intense TC expressions impede angels’ reinvestment intentions when they perceive ACs. Other results indicate that when angels perceive that entrepreneurs are not open to coaching, the prominence of mild TC expression is sharply mitigated and becomes as detrimental as intense TC expressions.

This study only focused on one specific aspect of the angel–entrepreneur post-investment relationship: The effect of their TC expressions on angels’ reinvestment intentions. By no means do the authors imply that TC expression in the angel–entrepreneur post-investment relationship is the only factor that matters to angel investors in their follow-on investment intentions with the same entrepreneur.

The findings suggest that entrepreneurs should pay careful attention to TC that may arise between them and their financiers. TCs are not entirely detrimental, but their negative effect might depend on how they are expressed. An appropriate level of TC may also improve enterprise performance and collaboration. Thus, angels and entrepreneurs should set clear goals and performance standards, where task interactions mainly focus on the goals and expected outcomes.

Prior to this study, little was known about whether all TCs potentially lead to ACs. By distinguishing between levels (i.e. mild vs intense) of TC expressions between angels and entrepreneurs, this study adds a novel aspect to it by showing that TC, in and of itself, does not necessarily lead to AC but can lead to AC once its intensity grows.

This study aims to empirically examine environment, social, and governance (ESG) as an effective strategy to reduce major impediments for a corporation in the form of costs of capital (COC) and systematic risk, especially for emerging markets such as India.

A sample of 114 Indian firms from eight prominent industries based on Thomson Reuters classification (TRBC) are used in the study. A panel regression with industry-fixed effects is carried out to account for industry heterogeneity. For robustness, the authors also carry out a matched sample analysis.

The authors observe a negative and significant relationship between ESG performance with COC and systematic risk, respectively. For the pillar-wise analysis, the authors observe that only governance performance is negatively and significantly related to COC whereas the environmental and social performances are negative and insignificant. For ESG pillar level analysis for beta, the authors observe that all pillars are negative and significant, thus making a case for how firms can fine-tune their ESG strategies according to each pillar.

As the ESG concept is still in a very nascent stage, data availability is a definite challenge in India.

As ESG is increasingly becoming relevant for multiple stakeholders, this study aims to provide evidence that can potentially guide the regulators, practitioners, and academicians to address the contemporary needs of these stakeholders, while also doing good for the firm in the traditional sense.

The transition to a sustainable economy is a challenge for emerging economies, especially for a country like India where stakeholders are not only varied but also huge in number. With this study's contribution towards an incremental understanding of ESG, Indian regulators and policymakers can bring forward mandates as to ESG compliances that are rewarding for the firms and give them enough impetus towards complying with ESG norms.

The extant literature on ESG majorly discusses the relationship between ESG performance and financial performance. This study addresses the lacuna of the relationship of ESG with COC and beta in the Indian context.

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the authors address the role of position–practice relations and irresistible causal forces in this conduct.

The authors examine SID-making (SIDM) practices in four case organisations operating in highly competitive markets, conducting interviews with managers at various levels and analysing company documents. Drawing on strong structuration theory, the authors show how managerial decision makers draw upon their knowledge of organisational context when exercising agency in SIDs.

The authors provide insights into how SIDM behaviour, specifically agents’ conduct, is shaped by a combination of position–practice relations and the agents’ comprehension of their organisation’s context.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice. Particularly, the authors contribute to this literature by identifying irresistible causal forces and illuminating why actors might not resist in SIDM processes, despite having the potential to do so.

This paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.

In this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.

The main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.

It is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.