Manisha Yadav and Gaurav Dixit
Motivated by the evidence highlighting the role of sentiments and cognitive biases in investors' decision-making, this study examines a novel behavioral finance-based asset…
Abstract
Purpose
Motivated by the evidence highlighting the role of sentiments and cognitive biases in investors' decision-making, this study examines a novel behavioral finance-based asset pricing model incorporating the prospect theory framework in the Indian equity market. Specifically, the study’s primary objective is to investigate the importance of Prospect Theory Value (PTV) in the cross-sectional pricing of stocks.
Design/methodology/approach
The empirical findings rely on data taken from NIFTY 500 and BSE S&P 500 stocks, encompassing daily, weekly and monthly observations. The analysis employs diverse statistical techniques, including Ordinary Least Squares (OLS), Fama–Macbeth Cross-section Regressions, Panel Fixed Effect and Quantile Regression.
Findings
The study demonstrates an asymmetric association between PTV and subsequent stock returns. The findings maintain their robustness even when factoring in stock-specific attributes such as market capitalization and book-to-market ratio, market beta and indicators related to lottery-like behavior such as skewness and MAX. This observed pattern persists when analyzing data at various frequencies, including daily, weekly and monthly intervals. Loss aversion behavior dominates among Indian equity investors, contrary to lottery preferences in the US equity market.
Originality/value
As far as the authors are aware, the study is the first to introduce a new behavioral finance-motivated stock return predictor (PTV) in the Indian stock market. The study also marks the pioneering use of a novel method that evaluates the predictability of PTV across various sections of the conditional return distribution using quantile regression.
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This study aims to analyse entrepreneurial behaviour in the context of crowdfunding and investigate various behavioural factors that impact entrepreneurs’ capacity to secure…
Abstract
Purpose
This study aims to analyse entrepreneurial behaviour in the context of crowdfunding and investigate various behavioural factors that impact entrepreneurs’ capacity to secure capital for their businesses through crowdfunding. It highlights gaps in the literature and offers insights into entrepreneurial crowdfunding behaviour.
Design/methodology/approach
The study conducted a hybrid literature evaluation, utilizing both bibliometric analysis and a Theory-Context-Methodology (TCM) framework-based approach. For quality assessment of the articles we use Qualsyst Analysis tool. A total of 177 relevant publications, published between 2013 and 2024, were reviewed to provide a comprehensive overview of the research in this field.
Findings
The analysis reveals a growing body of literature on entrepreneurial crowdfunding behaviour, with a significant increase after 2018. Business & Management emerged as the field with the most publications (64), and the United States contributed the highest number of studies (45), followed by Germany (25) and France (14). The study categorizes the literature and identifies a niche area that remains under-explored.
Research limitations/implications
The study provides actionable insights for entrepreneurs on how to adapt crowd-funding campaign strategies, with particular attention to the growing trend of sustainability in business. Additionally, it offers a road-map for future researchers to build on existing theories, methodologies, and contextual factors related to entrepreneurial crowdfunding behaviour.
Originality/value
This review is one of the few studies combining bibliometric analysis with the TCM framework to map the entrepreneurial crowdfunding literature. It identifies key gaps in research and offers future directions for the development of this field.
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This study aims to evaluate the failure behavior of glass fiber-reinforced epoxy (GFRE) laminate subjected to cyclic loading conditions. It involves experimental investigation and…
Abstract
Purpose
This study aims to evaluate the failure behavior of glass fiber-reinforced epoxy (GFRE) laminate subjected to cyclic loading conditions. It involves experimental investigation and statistical analysis using Weibull distribution to characterize the failure behavior of the GFRE composite laminate.
Design/methodology/approach
Fatigue tests were conducted using a tension–tension loading scheme at a frequency of 2 Hz and a loading ratio (R) of 0.1. The tests were performed at five different stress levels, corresponding to 50%–90% of the ultimate tensile strength (UTS). Failure behavior was assessed through cyclic stress-strain hysteresis plots, dynamic modulus behavior and scanning electron microscopy (SEM) analysis of fracture surfaces.
Findings
The study identified common modes of failure, including fiber pullouts, fiber breakage and matrix cracking. At low stress levels, fiber breakage, matrix cracking and fiber pullouts occurred due to high shear stresses at the fiber–matrix interface. Conversely, at high stress levels, fiber breakage and matrix cracking predominated. Higher stress levels led to larger stress-strain hysteresis loops, indicating increased energy dissipation during cyclic loading. High stress levels were associated with a more significant decrease in stiffness over time, implying a shorter fatigue life, while lower stress levels resulted in a gradual decline in stiffness, leading to extended fatigue life.
Originality/value
This study makes a valuable contribution to understanding fatigue behavior under tension–tension loading conditions, coupled with an in-depth analysis of the failure mechanism in GFRE composite laminate at different stress levels. The fatigue behavior is scrutinized through stress-strain hysteresis plots and dynamic modulus versus normalized cycles plots. Furthermore, the characterization of the failure mechanism is enhanced by using SEM imaging of fractured specimens. The Weibull distribution approach is used to obtain a reliable estimate of fatigue life.
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Amir Schreiber and Ilan Schreiber
In the modern digital realm, artificial intelligence (AI) technologies create unprecedented opportunities and enhance tactical security operations. This study aims to address the…
Abstract
Purpose
In the modern digital realm, artificial intelligence (AI) technologies create unprecedented opportunities and enhance tactical security operations. This study aims to address the gap in using AI to strategically produce holistic cybersecurity risk profiles.
Design/methodology/approach
This paper uses a rigorous AI-powered method to conduct cybersecurity risk profiles tailored to individual enterprises, investigating sources of threat and guiding defense strategies. This paper built a real working demo application based on real security databases and used it to build company-specific cybersecurity risk profiles.
Findings
This paper demonstrated a robust, automated process for developing tailored cybersecurity risk profiles in three case studies across different industries. The AI application produced coherent outputs, validated by experts as accurate.
Research limitations/implications
This study lays the groundwork for further research, allowing for refinement by integrating additional resources, such as near-real-time alerts from external or internal sources.
Practical implications
The escalating threat landscape highlights the need for organizations to adopt AI for cybersecurity management, leveraging tools that assist in defining and refining cybersecurity risk profiles to enhance defense measures.
Social implications
Using AI-generated cybersecurity risk profiles supports efforts to create a safer digital environment for organizations, their employees and their customers, aligning with the growing reliance on AI in daily life.
Originality/value
Unlike most papers, this paper uses an AI application to address contemporary challenges in creating holistic, non-tactical profiles that can be refined and contextualized by the organizations while achieving automation in key processes and integrating multiple resources.
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Neeraj Kumar, Mohit Tyagi and Anish Sachdeva
This study aims to discover the key performance indicators (KPIs) of the agricultural cold supply chain (ACSC) and analyze their consequences on the performance of ACSC within the…
Abstract
Purpose
This study aims to discover the key performance indicators (KPIs) of the agricultural cold supply chain (ACSC) and analyze their consequences on the performance of ACSC within the bounds of Indian topography.
Design/methodology/approach
The KPIs have been explored based on the literature review both in global and Indian context and domain expert's opinions. The interdependency characteristics and cause–effect relationship among the KPIs have been analyzed using a fuzzy decision-making trial and evaluation laboratory (f-DEMATEL) approach.
Findings
The findings extracted from the empirical assessment of the problem find strong compliance with the notions of theoretical model assessment. The results highlight that the cost of product waste and operating and performance costs are the two most important performance indicators of an Indian ACSC. Furthermore, governmental policies and regulations and the effectiveness of cold chain (CC) equipment also have a high degree of influencing characteristics on ACSC performance.
Research limitations/implications
To connect the study with practicalities, the assessment of the KPIs is allied with real-time practices by clustering the beliefs of Indian professionals. Therefore, the decision-making behavior of the experts might be influenced by geographical constraints. However, the key findings provide advantages to the ACSC players, a bright hope for future food security and a significant profit for farmers.
Originality/value
The presented paper encompasses various aspects of the ACSC, including theoretical and empirical perspectives exercised to contemplate the system dynamics, which inculcates the essence of the associated practicalities. Thus, this study has various practical contributions relevant to managerial and societal perspectives.
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Oluwatoyin Esther Akinbowale, Mulatu Fekadu Zerihun and Polly Mashigo
A functional financial sector is a major driver of economic development. The purpose of this paper is to provide a comprehensive understanding of existing research findings, gaps…
Abstract
Purpose
A functional financial sector is a major driver of economic development. The purpose of this paper is to provide a comprehensive understanding of existing research findings, gaps in knowledge and emerging trends in the field of banking and finance.
Design/methodology/approach
By conducting a systematic literature review, a total of 98 peer-reviewed articles whose focus and relevance match with the subject matter were reviewed and synthesised to answer the research questions. Multiple regression was also carried to investigate the relationship amongst the identified probable factors affecting financial inclusions.
Findings
The outcome of this study highlighted some factors mitigating the growth of the banking sector in the Sub-Saharan Africa (SSA). These include excessive or stringent regulations, market segmentation, high interest rates, information asymmetry, low credit status and uneven distribution of credit amongst others.
Practical implications
Some of the policy recommendations that could aid the development of the banking sector in SSA include: development and deepening of interbank markets, financial inclusion, improvement of overall market efficiency through redistribution of liquidity within the banking system, improvement of price and encouragement of competition. This study recommends financial inclusion by formulating policies that balances the capital adequacy requirements with the risk of insolvency to ensure credit flows and promotes financial stability via effective operations financial institutions.
Originality/value
This study contributes valuable insights to the understanding of banking and financial regulations in SSA, informing both academic research and policy development in the region.