1. MACHINE LEARNING MODELS OUTPERFORM TRADITIONAL MODELS IN IDENTIFYING NON-COMPLIANCE OF ORGANIZATIONS – EVIDENCE FROM INDIAN FIRMS
Authors: DIKSHA BHARDWAJ and SUNITA DANIEL
Abstract
This study aims to establish an effective model to detect organizations’ financial statements non-compliance for the early identification of any possible misrepresentation by an organization in future. The research period is 2017- 2021 and companies’ data has been collected from the website moneycontrol.com which is part of Network18 and is a prominent Indian website providing stock market news, business news and financial statements of companies operating in India. The income statement, balance sheet and cash flow statements has been scraped from the website using R software. This study uses traditional and machine learning models to detect financial statements non-compliance as per auditors’ report published on Moneycontrol website. Traditional models such as Beneish M Score and Benford’s law have been used to detect non-compliance. Since, traditional models gave lesser accuracy, machine learning models (Random Forest, ANN and AdaBoost) were used to identify the non-compliance. Sensitivity analysis was performed to check the accuracy of the model and it was found that the boosting technique AdaBoost had the highest accuracy in prediction of non-compliance of the firms.
Keywords: Financial statements, Beneish M-Score, Benford’s law, Machine Learning, Web Scraping, Random Forest, ANN, AdaBoost.
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2. A SOCIAL CAPITAL APPROACH TO ENTREPRENEURIAL ECOSYSTEM AND INNOVATION: CASE STUDY OF COSMETIC MANUFACTURING MSMES
Authors: Dr. DEEPMALA BAGHEL
Abstract
Despite being recognised as drivers of innovative development, Micro, Small, and Medium-Sized Enterprises (MSMEs) frequently confront resource limitations. Therefore, enhancing the ecosystem is contingent on the entrepreneurs’ social capital, which is crucial for the success of MSMEs. This study applies the social capital approach to analyse the entrepreneurial ecosystem enrichment and its impact on the innovation process of cosmetics MSMEs. The qualitative case study of six cosmetic manufacturing MSMEs explores that social capital is a multifaceted asset to MSMEs. Through an in-depth thematic analysis of three dimensions of social capital (structural, relational, and cognitive), this study states that the innovation process is supported by the synergistic transformation of one dimension of social capital into another. Entrepreneurs sharing the common norms, rules, and language enrich their cognitive as well as relational aspects of ecosystem. The study suggests that as network ties, trust, and norms collectively influence innovation in firms, hence, social capital needs to be studied with its contextualization in the ecosystem.
Keywords: Entrepreneur, Innovation, Cosmetics, MSME, Social capital, Trust.
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3. GLOBAL RESEARCH TREND AND FUTURISTIC RESEARCH DIRECTIONVISUALIZATION OF WORKING CAPITAL MANAGEMENT USING BIBLIOMETRIC ANALYSIS
Authors: POOJA SHARMA, Dr. SUSHIL KUMAR MEHTA and Dr. JYOTSNA SHARMA
Abstract
Purpose – The purpose of this research is to undertake a bibliometric analysis of working capital management. The study examines papers from time period 1974-2023and performed performance analysis, co-citation analysis, bibliographic coupling and scientific mapping. Design/methodology/approach – The study examines 174 articles retrieved from the Scopus database using bibliometric analysis, performance analysis and thematic clustering. The study looked at the scientific productivity of papers, prolific authors, most influencing papers, institutions and nations, keyword co-occurrence, thematic mapping, co-citations and authorship and country collaborations. VOSviewer was as a tool in the research to conduct the performance analysis and thematic clustering.The watchword "Working Capital Management" was used to include only English-language articles. Findings – The most productive year was 2022 with 26 publications. Martínez and García- are the most protuberant authors with 708 citations. The findings of the study shows that the most influential institutions are ‘The Department of Management and Finance, Faculty of Economy andBusiness and Department of Management and Finance, Faculty of Economics and Business, The University of Murcia, Spain with 381 & 297 citations. Among,thecountry analysis,Spain with 744 citations stands first of all other nations for publication on Working Capital Management. Kärri is the most productive author with 7 documents. Country-wise analysis reveals that the United States is the most productive country for Working Capital Management research with 40 documents.The authors also identified seven thematic clusters of Working Capital Management. Research limitations/implications – It informs and directs researchers on the current state of study in the field of Working Capital Management.The present study has quite a few implications forSmall & Medium enterprise managers, entrepreneurs, financial managers, academicians and scholars. It also outlines future research directions in this field.Present study provides an inclusive acquaintance about the working capital management till date. Originality/value – This is the first study which provides the performance analysis and scientific mapping of the all published documents on working capital management between the time periods 1974-2023
Keywords: Working Capital Management, Bibliometric analysis, Co-citation analysis, Bibliographic coupling.
4. THE DETERMINANTS OF STOCK PRICES: NEW EVIDENCE FROM NSE
Authors: RAVINDRA BABU S, SHIVAPRASAD G, GAYATHRI R, VINOTH KUMAR V and BANDARU SRINIVASA RAO5
Abstract
The determinants of stock prices are a significant area of research for investors, stockbrokers, and fund managers. This research paper analyzes the impact of the macroeconomic factors like GDP, Money supply, Interest rate, Consumer Price Index, Exchange Rate, Inflation rate, and S&P US Index on the Nifty 50 index from April 2000 to December 2023 using ADF, VECM and VDA analysis. The study also conducted the panel data analysis of the firm-specific variables like EPS, Net worth, P/E ratio, Book value, ROCE, and Debt-equity ratio on the Dividend Yield of the 22 stocks of the Nifty Index from April 2000 to December 2023. The study indicates book value per share (B.V.) and debt-equity ratio (D/E) positively and substantially influence dividend rates. In contrast, earnings per share (EPS) and the share price per earnings ratio (P/E) have a significant negative relationship to NSE-listed companies' dividend return. Investors, relationship managers, and market participants should consider B.V., EPS, P/E and D/E ratios as the essential variables for investment. According to the study, the analysis indicates that GDP, Interest rate, Inflation rate, Monetary policy, Exchange rate, and U.S. stock index are important macro economic determinants affecting the stock price.
Keywords: Macroeconomic, Gross Domestic Production, Debt-equity ratio, Vector Error Correction Model, Panel Data Analysis
5. EVALUATION OF D’AVENI’S NEW 7S FRAMEWORK TO THRIVE IN HYPER-COMPETITIVE MARKETS THROUGH BUSINESS MODEL INNOVATION
Authors: DEBIPRASAD MUKHERJEE and SANTOSH KUMAR PRUSTY, PHD
Abstract
Purpose – This research aims to evaluate D'Aveni's 7S Framework, including Strategy, Structure, Systems, Shared Values, Skills, Style, and Staff to thrive in hyper-competitive market through business model innovation (BMI).
Design/ Methodology/ Approach – This study performs a narrative literature review and synthesis, focusing on key literature on strategic tools and frameworks, business model innovation, hyper-competitive markets, and D'Aveni's 7S Framework. The study evaluates how D'Aveni's 7S Framework can provide valuable insights to guide the managers towards BMI.
Findings – This paper underscores and reaffirms the significance of business model innovation in exerting a substantial influence on competitive positioning within the hyper-competitive business landscape. In the context of hyper-competitive markets, the efficacy of BMI manifests through its engagement with critical facets such as Value Proposition, Operational Efficiency, Market Segmentation, Collaboration, and the capacity to navigate disruption. In this regard, D'Aveni's 7S framework, encompassing seven critical elements – Strategy, Structure, Systems, Shared Values, Skills, Style, and Staff – encapsulates the multifaceted dimensions of achieving and sustaining a competitive edge through BMI. This interplay highlights the complex and interdependent nature of business model innovation in shaping organizational competitive positioning and underscores its pivotal role in the present-day competitive business landscape.
Originality – This paper represents a comprehensive exploration of the literature to investigate the intricate relationship between business model innovation (BMI) and each individual component of D'Aveni's well established 7S framework. While both BMI and the 7S framework have been subjects
of considerable research and scholarly attention, both are used in silos. The synthesis of these two areas is notably underexplored. It marks the inaugural effort in systematically exploring this intersection, potentially contributing the validity of using Daven’s 7S framework for BMI in the practice.
Keywords— Business Model Innovation, D’Aveni’s New 7S, Competitive Positioning, Hyper Competitive Market, Sustainable Competitive Advantages, Value Proposition, Stakeholder Satisfaction, Strategic Soothsaying, Market Segmentation, Market Dynamics.