Industry-specific Factors Research Articles

Leveraging corporate governance characteristics for stock crash risk assessment

Causing considerable losses for individual investors, stock crashes are also potential triggers for wider financial crises. In contrast to existing research that primarily focuses on specific corporate governance characteristics in relation to stock crash risk, in this study, we construct a set of corporate governance attributes and employ machine learning techniques for a comprehensive assessment of stock crash risk. Through empirical analysis in the Chinese stock market, we find that our corporate governance attributes are effective indicators of stock crash risk, yielding statistically significant and economically meaningful crash risk assessment. Additionally, our heterogeneity tests suggest that firms with less concentrated shareholding result in superior assessment accuracy. This observation is consistent with prior findings that increased retail investor participation enhances corporate governance transparency, thereby contributing to better assessment performance. Industry-wise, the performance of crash risk assessment for real estate companies is higher than that for cultural, sports, and entertainment sectors. We speculate that these variations stem from industry-specific factors, such as business logic, operational models, and profit mechanisms. Our results also suggest that characteristics related to shareholder meetings are pivotal in assessing crash risks for manufacturing companies, while board-related features are essential for real estate firms. Overall, this study contributes to current literature by validating the feasibility of employing corporate governance characteristics to assess crash risk and by exploring the economic value of crash risk assessment. Furthermore, we discuss several valuable insights into the Chinese stock market through heterogeneity analysis.

Estimating Determinants of Contractualization of Workers in Organized Sector in India

The structural adjustment programme adopted in 1990 led to the removal of all existing pre-reform regulations and restrictions imposed on the Indian industries. This radically transformed India’s trade relations with international markets. The liberalization of Indian economy on one hand accelerated foreign capital as well as technology influx while on the other hand increased competition for the domestic economy. Thus the increased openness and flexibility arising from the economic transformation prompted the domestic producers to resort to alternative informal routes of employment thereby leading to increased contractualization of employment substituting of regular workers by contract workers in the manufacturing industries. Thus this paper is an empirical study which focuses on exploring and identifying the industry specific factors which are affecting the degree of casualization in Organized manufacturing sector of India. Panel regression using STATA has been used and the econometric analysis reveals that average firm size, value of output, capital intensity, profit per worker and welfare benefits for workers have considerable favourable effect on the employment of contractual workers while trade union activity and the ratio of male to female workers employed have significant negative impact on contract worker employment in the manufacturing industries of the organized sector in India. Keywords: contractualization, capital intensity, trade union activity, feminization, panel regression JEL Classification: C33, J21, L60

The role of human-capital in artificial intelligence adoption

We study the role of human-capital on the early adoption and diffusion of Artificial Intelligence (AI) technologies. We do this using recently released EUROSTAT data on AI-adoption across European countries and industries in 2021. We find that pre-existing differences in human-capital are a key driver of differences in AI-adoption. Our estimates suggest that one-third-to half of AI-adoption is linked to differences in available human-capital across country-industry cells. This relationship holds even when we account for country and industry specific factors. Moreover, higher clustering of university educated workers in firms appears crucial for AI-adoption. This effect is particularly strong for the following AI technologies: (i) those assisting the automation of processes and (ii) those that enable physical movements of machinery. Within firms, human-capital fosters the use of AI in processes associated with production, management and logistics. Despite documenting the automative nature of the AI technologies adopted, we find no evidence for them leading to employment declines (at least by 2021).

Empowerment through event management: A project management approach for women entrepreneurs

This review paper explores the unique challenges women entrepreneurs face in the event management industry and proposes strategies for their empowerment. Women in this sector encounter various barriers, including gender bias, limited access to funding, insufficient networking opportunities, and difficulties balancing professional and personal responsibilities. Societal expectations and industry-specific factors further exacerbate these challenges, hindering women's advancement. The paper highlights the importance of promoting gender equality, improving access to financial resources, enhancing networking and mentorship opportunities, and supporting work-life balance. Additionally, it emphasizes the need to increase women's visibility in leadership roles within the industry. The recommendations aim to create a more inclusive and supportive environment for women entrepreneurs, fostering their growth and innovation in event management. Future research directions are suggested to identify best practices for supporting women entrepreneurs and to provide data-driven insights for policy and industry practices.

Analysis of Tax Impact on Employee Retention in the Hospitality Industry

This qualitative research investigates the intricate relationship between taxation policies and employee retention within the hospitality industry. Employing a systematic literature review, the study examines the impact of tax incentives and management strategies on employee satisfaction and organizational practices. Through rigorous data collection and thematic analysis, key findings emerge, revealing the nuanced dynamics at play. The research underscores the significance of tax incentives in fostering employee loyalty and commitment, albeit contingent upon organizational culture, industry-specific factors, and perceived fairness. Additionally, it highlights the challenges posed by compliance costs and the ethical dilemmas associated with aggressive tax planning. The study contributes to a deeper understanding of the complex interplay between taxation policies, organizational responses, and employee outcomes, offering insights for both academia and industry practitioners.

TRANSPARENCY IN CORPORATE GOVERNANCE: ITS ROLE IN MITIGATING FINANCIAL RISKS AND IMPROVING PERFORMANCE METRICS

In-depth analysis of the vital role that openness plays in corporate governance is provided in this paper, with particular attention to how it improves organizational performance measures and reduces financial risk. Transparent corporate governance processes are more important than ever in a time of growing complexity in global business operations and elevated stakeholder expectations. Using a mixed-methods approach, this study combines qualitative insights from in-depth interviews with business executives, regulators, and governance experts with quantitative analysis of financial data from 500 publicly traded companies across several industries. The study's five-year duration, from 2019 to 2023, enables a thorough analysis of trends and causal connections. Based on reduced stock price volatility, fewer substantial financial restatements, and improved credit ratings, our results show a clear positive association between more corporate transparency and better financial risk management. Additionally, the study shows that businesses with more open governance processes routinely beat their less open competitors on a number of important performance criteria, such as customer happiness, employee productivity, and return on equity (ROE). The study also reveals complex connections between particular transparency metrics and performance results, emphasizing the necessity of customized strategies for improving openness depending on organizational and industry-specific factors. These revelations aid in the creation of an all-encompassing framework for putting corporate transparency into practice and gauging its effectiveness, offering practitioners, legislators, and scholars studying corporate governance useful direction.

Examining the Triggers, Signals, and Implications of Corporate Implosion: Lessons and Intervention Strategies for Private Universities in Africa

Corporate implosion, characterized by sudden organizational collapses and significant financial repercussions, necessitates a comprehensive understanding of its triggers, signals, and potential intervention strategies. This paper employs a literature review and synthesis approach to delve into existing corporate implosion research specifically focusing on defining triggers, early signals, and viable rescue mechanisms. The study investigates triggers contributing to corporate implosions, focusing on financial mismanagement and leadership failures. It underscores the intricate interplay between internal and external elements in the context of organizational failures. Through thoroughly examining existing literature, the paper aims to contribute to a deeper understanding of the dynamics leading to corporate implosions. Furthermore, this research extends its scope to explore the closure of private universities, particularly within the African context. The analysis highlights industry-specific factors that contribute to the closure of private universities, encompassing aspects such as market demand, program relevance, financial stability, governmental regulations, economic conditions, demographic shifts, and technological advances. By broadening the investigation to include private universities in Africa, the study offers insights into the unique challenges faced by educational institutions in the region. Ultimately, the findings of this study are intended to inform decision-makers and stakeholders in private universities about the multifaceted nature of challenges that can lead to closures. Recognizing these triggers and signals is crucial for implementing timely and effective interventions to safeguard the stability and sustainability of private universities in Africa.

Comparative Analysis of Key Success Factors in S&OP: Focusing on Manufacturing and Retail Industry in South Korea

The global supply chain is facing unprecedented challenges due to pandemics, geopolitical tensions, volatile commodity prices, and rapid changes in consumer demand. The Sales and Operations Planning (S&OP) process can be an important solution by integrating supply and demand with business strategy and operational planning. However, previous studies have developed single frameworks or maturity models without considering industry-specific factors, overlooking the structural and operational characteristics of different industries that can have a significant impact on the approach and success factors of S&OP. Therefore, this study identifies and compares the key success factors of S&OP in the manufacturing and retail industries using the Analytic Hierarchy Process (AHP) technique. The results show clear differences in the prioritization of success factors between two industries. In the manufacturing industry, strategic support and leadership were evaluated as the most critical factor, while in the retail industry, operational processes were emphasized. In addition, the relative importance was concentrated on the top-ranked factor in the manufacturing industry, but the relative importance was distributed among several factors in the retail industry. This study provides valuable insights into the critical success factors for S&OP implementation in different industries and offers an understanding of how industry-specific characteristics influence the effectiveness of S&OP strategies.

Working Capital Management in Different Sector

Effective working capital management is crucial for the financial health and sustainability of businesses across industries. This research paper aims to investigate and compare the working capital management practices adopted by companies in different sectors. The study employs a mixed-methods approach, combining quantitative analysis of financial data with qualitative insights gathered through interviews with industry experts. The research analyzes the working capital management performance of companies operating in various sectors, including manufacturing, retail, technology, and services. Key metrics such as liquidity ratios, inventory turnover, receivables collection period, and payables deferral period are evaluated to assess the efficiency and effectiveness of working capital management strategies employed by firms in each industry. Furthermore, the paper examines the impact of industry-specific factors such as demand volatility, supply chain dynamics, technological advancements, and regulatory environments on working capital management practices. By comparing and contrasting the findings across different industries, this study provides valuable insights into the factors influencing working capital management decisions and identifies best practices that can be adapted by companies to optimize their working capital efficiency and enhance overall financial performance. The research contributes to the existing literature by offering a comprehensive analysis of working capital management practices across diverse industries, highlighting industry-specific challenges and opportunities. The findings of this study have practical implications for managers, investors, and policymakers seeking to improve working capital management strategies and enhance the competitiveness and resilience of businesses in today's dynamic economic landscape.

Theoretical Aspects of Organizational Risk Management

Risk is multifaceted and complex, shaped by the industry-specific factors and inherent uncertainties. Risk assessment is a dynamic process that involves identifying, analyzing, and evaluating potential hazards to make informed decisions about risk mitigation. In industrial settings, this process is necessary to create a safe working environment and protect the overall well-being of the organization. Effective risk assessment involves the use of multiple factors and methods to address different types of risks. The article discusses the means, ways and methods used by enterprises to effectively assess risks. In addition, the strategies are studied - financial, operational, organizational, economic, credit and technical risks, which are used to assess different types of risks. Keywords: Risk, risk assessment, interest rate, financial, operational, organizational, credit risk.

A Review of Empirical Capital Structure Research in Different Industries

The choice of capital structure is an important aspect of a firm's financial decision-making, and the differences between industries make it challenging for firms to develop a capital structure strategy. The right capital structure is critical to a firm's financial position, competitiveness, risk management, and strategic development. Existing capital structure theories provide different perspectives to understand the choice and impact of a firm's capital structure. However, the proposed assumptions are all ideal and irrational, differing significantly from the real capital market situation. By reviewing existing empirical research, this paper aims to analyze the variability of corporate capital structure choices under different industries and the influencing factors behind them. Based on the analysis of industry-specific factors affecting capital structure choices, industries are broadly categorized into three major groups: capital-intensive industries, labor-intensive industries, and innovative industries. Through case studies and empirical research on each industry, it explores how different industries' unique economic and operational characteristics shape enterprises' strategic choices in capital structure.

Stock price forecast model for CATL based on BP neural network regression

With the introduction of the "Dual Carbon" policy and the increasing environmental awareness among residents, the new energy vehicle industry is experiencing positive growth momentum. New energy vehicles use non-traditional energy sources as their power supply, effectively reducing carbon emissions, enhancing energy efficiency, and contributing to the improvement of China's existing energy landscape, thus supporting environmental protection and the early realization of "carbon peak" and "carbon neutrality" goals. Contemporary Amperex Technology Co., Ltd. (CATL), a prominent and competitive player in China's emerging clean energy industry, focuses on researching, developing, manufacturing, and marketing power battery and energy storage systems specifically designed for new energy vehicles. Moreover, in recent years, machine learning and deep learning have gained wide application in various domains, including stock price prediction and financial investment. This paper constructs a stock price prediction model for CATL based on a BP neural network regression, considering factors related to traditional energy, carbon trading, environmental aspects, and industry-specific factors.

Patterns of Resource Allocation and Divisional Budgets: The CEO's Strategic Lens Across Various Industries

This paper explores how Chief Executive Officers (CEOs) across various industries adapt their resource allocation and divisional budgeting strategies in response to contemporary business challenges. It aims to shed light on the evolving role of CEOs in steering organizational success through strategic initiatives, highlighting the shift from traditional, efficiency-focused models to flexible, value-driven approaches. By conducting a qualitative analysis of recent literature, the study examines patterns in strategic decision-making, focusing on the balance between operational needs and strategic goals amidst changing market conditions. The research emphasizes the impact of industry-specific factors, such as market volatility and organizational size, on these strategic adaptations. Findings reveal a significant trend towards more adaptable and strategic resource management practices among CEOs, moving beyond short-term operational efficiency to support long-term goals. This shift is evident across different sectors, including healthcare, manufacturing, and e-commerce, though the extent and nature of its implementation vary according to each industry's unique challenges and opportunities. The study underscores the importance of strategic adaptability for organizational resilience and success in a rapidly evolving business landscape.

Challenges in the Relationship between Liquidity and Profitability: Perspectives from a Literature Review

Purpose: The purpose of the literature review is to examine and synthesize the current state of knowledge in the literature on the relationship between liquidity and profitability in companies. It aims to understand the importance of these two variables for the financial performance and long-term viability of organizations. Theoretical framework: The theoretical framework focuses on the importance of liquidity and profitability in the business context. Key concepts related to the ability of companies to service their debts (liquidity) and whether they are viable and generate profits over time (profitability) will be addressed. Factors such as capital intensity, competition, and industry-specific risks, which may influence the relationship between the two variables, are also considered. Design/Methodology/Approach: The design of the literature review involved the review and synthesis of a total of 250 articles related to liquidity and profitability. Of this number, 61 articles were selected from academic platforms such as SCOPUS, LATINDEX and others. A mixed approach was presented to address the topic, combining different perspectives and methodological approaches. Results: The results of the review revealed several gaps in the study of the relationship between liquidity and profitability. These include the lack of longitudinal cross-country studies, which limits the understanding of differences in financial performance in different contexts. It was also found that factors such as capital intensity, competition and sector-specific risks may cause heterogeneous relationships between liquidity and profitability across business sectors. Social, practical and research implications: The social implications of this review highlight the importance of maintaining good liquidity and profitability management in companies, as their ability to service debt and generate sustainable profits over time is derived from these variables. Business practices need to consider industry-specific factors to understand how they can influence the relationship between liquidity and profitability. From a research point of view, this review identifies the need for more longitudinal cross-country comparative studies and a sectoral approach for a more complete understanding of the relationship between these financial variables. Originality/value: The originality and value of this review lies in its mixed approach and synthesis of a significant number of academic articles related to liquidity and profitability. By highlighting research gaps and emphasizing the importance of a sectoral approach, this review provides valuable insights for future research and financial practices in the corporate context.

Is it the end of the technology acceptance model in the era of generative artificial intelligence?

PurposeThe technology acceptance model (TAM) is a widely used framework explaining why users accept new technologies. Still, its relevance is questioned because of evolving consumer behavior, demographics and technology. Contrary to a research paper or systematic literature review, the purpose of this critical reflection paper is to discuss TAM's relevance and limitations in hospitality and tourism research.Design/methodology/approachThis paper uses a critical reflective approach, enabling a comprehensive review and synthesis of recent academic literature on TAM. The critical evaluation encompasses its historical trajectory, evolutionary growth, identified limitations and, more specifically, its relevance in the context of hospitality and tourism research.FindingsTAM's limitations within the hospitality and tourism context revolve around its individual-centric perspective, limited scope, static nature, cultural applicability and reliance on self-reported measures.Research limitations/implicationsTo optimize TAM's efficacy, the authors propose several strategic recommendations. These include embedding TAM within the specific context of the industry, delving into TAM-driven artificial intelligence adoption, integrating industry-specific factors, acknowledging cultural nuances and using comprehensive research methods, such as mixed methods approach. It is imperative for researchers to critically assess TAM's suitability for their studies and be open to exploring alternative models or methods that can adeptly navigate the distinctive dynamics of the industry.Originality/valueThis critical reflection paper prompts a profound exploration of technology adoption within the dynamic hospitality and tourism sector, makes insightful inquiries into TAM's future potential and presents recommendations.

Relationship between tea industry specific factors and tea companies share prices: empirical evidence from an emerging economy

Relationship between tea industry specific factors and tea companies share prices: empirical evidence from an emerging economy

Relationship between tea industry specific factors and tea companies share prices: empirical evidence from an emerging economy

Relationship between tea industry specific factors and tea companies share prices: empirical evidence from an emerging economy

Artificial Intelligence Adoption in the Manufacturing Sector: Challenges and Strategic Framework

In today’s competitive business landscape, manufacturing organizations are increasingly recognizing the potential of artificial intelligence (AI) to enhance productivity, efficiency, and cost-effectiveness. Despite AI’s transformative applications across various sectors, its adoption within the manufacturing industry remains underexplored, with many firms facing unique challenges such as organizational complexity, legacy systems, and a shortage of specialized digital skills. This study conducts a comprehensive literature review to identify the key factors influencing AI adoption in manufacturing, categorizing them into technological, organizational, and external dimensions. Technological factors include perceived benefits, system compatibility, data quality, cost and IT infrastructure, while organizational factors encompass top management support, employee competencies, and organizational readiness. External influences involve government regulations, competitive pressures, and vendor support. By synthesizing findings from multiple empirical studies, we develop a conceptual framework based on the Technology-Organization-Environment (TOE) model, highlighting how these dimensions interact to shape AI adoption decisions. The proposed framework highlights the critical role of leadership commitment, strategic alignment of AI initiatives, and the necessity for robust technological infrastructure. It also emphasizes the impact of external factors such as supportive government policies and market competitiveness on accelerating AI integration. The study’s implications are significant for academics seeking to fill research gaps, industry practitioners aiming for successful AI implementation, and policymakers interested in fostering an environment conducive to technological advancement. While the framework offers a structured approach to understanding AI adoption in manufacturing, the study acknowledges the need for empirical validation. Future research should test the framework across different manufacturing sectors and regions to account for industry-specific factors and regional variations. By addressing these areas, organizations can better navigate the complexities of AI adoption, enhancing competitiveness and innovation in the manufacturing sector.

Factors Influencing Adoption of Blockchain Technology in Jordan: The Perspective of Health Care Professionals

Aim/Purpose: This paper investigates the user acceptability of blockchain technology in the healthcare sector, with a specific focus on healthcare professionals in Jordan. Background: The study seeks to identify the factors that affect healthcare professionals’ use and acceptance of blockchain technology in Jordan. Methodology: The study’s research framework integrates factors from the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). A questionnaire was distributed to collect data from 372 healthcare professionals in Jordan, and the results were analyzed using structural equation modeling based on the Partial Least Square (PLS) technique. Contribution: While only a few previous studies have explored blockchain technology acceptance in the healthcare sector using either the TAM or the UTAUT, this study uniquely integrates elements from both models, offering a novel approach that provides a comprehensive understanding of the factors that influence the acceptance of blockchain technology among healthcare professionals in Jordan. The findings can assist decision-makers in developing strategies to enhance the adoption rate of blockchain technology in the Jordanian healthcare sector. Findings: The study revealed that usability, convenience, privacy and security, cost, and trust significantly impact the perceived usefulness of blockchain technology. The findings also suggest that healthcare professionals are more likely to have a positive attitude towards blockchain-based healthcare systems if they perceive them as useful and easy to use. Attitude, social influence, and facilitating conditions were found to significantly impact behavioral intention to use. Recommendations for Practitioners: Stakeholders should focus on developing blockchain-based healthcare systems that are easy to use, convenient, efficient, and effort-free. Recommendation for Researchers: Researchers may compare the acceptance of blockchain technology in the healthcare sector with other industries to identify industry-specific factors that may influence adoption. This comparative analysis can contribute to a broader understanding of technology acceptance. Impact on Society: Successful adoption of blockchain technology in the healthcare sector can lead to improved efficiency, enhanced protection of healthcare data, and reduced administrative burdens. This, in turn, can positively impact patient care and lead to cost savings, which contributes to more sustainable and accessible healthcare services. Future Research: Future research may explore integrating blockchain technology with other emerging technologies, such as artificial intelligence and sidechain, to create more comprehensive and innovative healthcare solutions.

FACTORS INFLUENCING INFORMATION TECHNOLOGY INVESTMENTS IN SOUTH AFRICAN SMALL AND MEDIUM SIZE ENTERPRISES: A CONCEPTUAL STUDY

Small and medium-sized businesses (SMEs) are essential to South Africa's development and economic progress. Information technology (IT) expenditures have become crucial for SMEs to stay competitive in the quickly changing digital market. The purpose of this study is to examine the variables affecting IT investments in South African SMEs. The paper provides a thorough examination of the literature, the technique used, the findings, and a discussion of the implications through a conceptual study. The study's findings were derived from an analysis of 15 of the best and most relevant journal articles out of a total of 200 that were obtained and evaluated through Google Scholar that are related to factors impacting IT investments in South African SMEs. The objective was to aggregate the views of many scholars on the issues affecting IT investments in South African SMEs from their writings. The study's findings indicates that financial constraints, perceived return on investment (ROI), industry-specific factors, technological complexity and skills, perceived risk, outside influences, organisational culture, and leadership are among the factors that affect IT investments in South African SMEs. With regards to the study's findings, it is recommended that SMEs should work to understand and address the factors influencing information technology investments in South Africa so they can make informed IT investment decisions, and policymakers should foster an environment that encourages the uptake of technology and the expansion of this industry.