PEOPLE: International Journal of Social Sciences
Not a member yet
1507 research outputs found
Sort by
IMPACT MODEL OF SOME FACTORS ON ORGANIZATIONAL PERFORMANCE
Get PDFThis research explores the effects of human resource management practices, organizational culture, organizational innovation, and intellectual capital on organizational performance, with a focus on enterprises in Vietnam. Utilizing foundational theories such as the Resource-Based View and Dynamic Capability Theory, the study integrates these elements to provide a comprehensive understanding of their combined impact. The methodology employs Structural Equation Modeling to analyze data collected from representative firms, ensuring robust insights. Findings demonstrate that human resource management practices significantly influence employee satisfaction and productivity, while an innovation-oriented organizational culture enhances adaptability and creativity. Furthermore, investment in intellectual capital drives competitive advantage, and organizational innovation directly contributes to improved performance outcomes. These results offer critical implications for both academic research and practical applications, providing strategies for business leaders to enhance operational effectiveness and sustain competitive performance in dynamic markets
LEADERSHIP IN CRISIS MANAGEMENT: BUILDING RESILIENT BUSINESS MODELS: Received: 13th September 2024 Revised: 12th October 2024, 28th November 2024, 12th December 20224 Accepted: 29th September 2024
No full textThis study explores the role of individual leadership in crisis management, focusing on how different leadership styles contribute to the development of resilient business models. Through cross-cultural and cross-sectoral case studies, the research identifies transformational, transactional, servant, and situational leadership styles as key factors in navigating crises. The findings suggest that transformational and servant leadership are particularly effective in fostering resilience, while transactional leadership, although useful in the short term, may require supplementation for long-term success. The study underscores the importance of cultural and sectoral contexts in shaping leadership practices and offers future directions for research in leadership development and crisis preparedness
ANALYZING PUBLIC HEALTH CONCERNS THROUGH TEXT MINING AND SOCIAL NETWORK ANALYSIS: A CASE STUDY OF COVID-19 PUBLIC OPINION ANALYSIS FROM ONLINE COMMUNITY FORUMS IN TAIWAN
Get PDFIn the past, many quantitative studies in public health relied on traditional descriptive statistical data and less on analyzing unstructured text data. However, in the era of close online communication, a huge amount of text information related to public health issues is generated in online communities every day. COVID-19 pandemic should be one of the most important public health events in Taiwan since 2020. Many people express their views and feelings on the epidemic issue in online forums. In this research, the aim is to apply text mining and social network analysis to analyze the sentiment and topics related to COVID-19 in PTT, the most popular online community forum of social media in Taiwan. We used topic modeling to extract COVID-19 related topics and keywords, as well as sentiment analysis to explore the attitudes and emotional tendencies of the online community towards various issues, and data visualization methods such as word clouds and network graphs to present the research results. Additionally, we plan to conduct cluster analysis on the authors and accounts of the articles to determine if there is a phenomenon of specific groups influencing the COVID-19 public opinion. The expected outcome of this research is to provide a reference for the implementation of public health policies and to promote the value of sentiment analysis in public health management.
After conducting text mining analysis on the articles published in the COVID-19 forum of PTT in 2021, especially the period of Taiwan's COVID-19 escalation from June to August 2021. The overall discussion volume and sentiment can be roughly divided into three peaks. The first peak started to rise in mid-May and reached its peak in mid-June. The second peak occurred in mid-July, and the negative sentiment was significantly higher than the positive sentiment. The last peak occurred in late August and had the highest discussion volume among the three peaks. In each peak of sentiment, negative sentiment was mostly higher than positive sentiment. Our suggestion is to focus on the following research results that Public health managers can use daily text mining results by our way to assist in judging public reactions under current epidemic policies, and the positive and negative sentiment levels in sentiment analysis can reflect whether policies may lead to a crisis outbreak. Observing the subsequent changes in sentiment can avoid affecting the implementation effectiveness of the next policy or causing a more serious public opinion crisis. This research hopes to promote the value of sentiment analysis in public health management by visualizing the complex online forum opinions into easy-to-understand charts, which can serve as a reference for decision-makers in judging online public opinion
KNOWLEDGE IS POWER: HOW SUBSIDIARY CREATE KNOWLEDGE BY RELATIONAL EMBEDDEDNESS AND KNOWLEDGE SPILLOVERS
Get PDFIn this study, the relationship between environmental competitiveness and knowledge creation in subsidiaries is examined, suggesting that external relational embeddedness serves as a mediator and knowledge spillover acts as a moderator of this relationship. We analyzed a sample of 189 subsidiaries in Shanghai, Mainland China. The findings indicate that environmental competitiveness has a positive effect on the external embeddedness of subsidiaries. Specifically, subsidiary external relational embeddedness not only directly affects subsidiary absorptive capacity and knowledge creation but also has a fully mediating effect on this relationship. Regarding the effect of knowledge spillovers, only unconscious knowledge spillovers allow subsidiaries to expand their relational networks, increase their sources of knowledge, and notably increase their opportunities for knowledge creation. Both the theoretical and empirical implications are further discussed
ANALYZING THE RELATIONSHIP BETWEEN INDUSTRIAL POLICY AND ENTREPRENEURIAL ECOSYSTEM: Received: 30th November 2023; Revised: 04th January 2024, 07th February 2024; Accepted: 12th February 2024
No full textThis article discusses the importance and articulation of innovation policy from the point of view of the entrepreneurial ecosystem approach. The paper takes the form of a literature review. To this end, the authors describe the analysis of industrial policy based on the entrepreneurial ecosystem approach proposed by Stam (2018). The research finds that innovation policy plays a crucial role in a competitive entrepreneurial environment to achieve creative destruction. The Policy tries to solve the problems that hinder the interaction of the factors that make up the entrepreneurial ecosystem. Different policy tools should be developed to formulate policies for the entrepreneurial ecosystem. Additionally, successful innovation policy tools in one ecosystem could be applied in another ecosystem
PRIVATE EQUITY FUND SELECTION - A MACHINE LEARNING APPROACH
Get PDFThe following aims to train a range of supervised machine learning models to predict the probability of a private equity (PE) fund exceeding a public market equivalent (PME) measure of 1 based on the information the PE investor would have at the time of fundraising. Past literature has studied a range of factors that appear to drive the performance of PE funds such as targeted fund size, management experience, fund specialization level, state of the industry, and the overall economy. The article investigates the predictive power of these factors. The models are based on a sample of 1,233 Buyout (BO) funds and 689 are Venture Capital (VC) funds sourced from Preqin. The results suggest some degree of predictability in VC funds with the top performing models reaching an out of sample accuracy score of 75% vs a base rate of 70%. For BO funds, the results are less promising with the top models only reaching an out of sample accuracy score of 60%, while failing to surpass the base rate of 61%. Overall, complex machine learning models, such as boosted decision tree-based algorithms and feedforward neural networks, fail to consistently outperform simpler models in both fund categories, which can be attributed to the limited sample size. Many macroeconomic and fund-specific in the variables analysis look to be valuable performance indicators for both the categories of funds. The impact is more profound and statistically significant for VC funds, especially in the case of macroeconomic factors
COPYRIGHT ISSUE IN ARTIFICIAL INTELLIGENCE APPLICATIONS OF SMART PRODUCTION AND AUTONOMOUS SYSTEMS
Get PDFBackground: In recent years, the use of artificial intelligence in the field of production and design has increased. As a result, in smart production and autonomous systems, the concepts of copyright and rights ownership on the works produced have become increasingly complex. In addition, there is no sufficient legal regulation regarding the rights of the software side of the system, the content providers and the commercial parties with whom they have agreements, in the productions made by autonomous systems through artificial intelligence software. In addition to the ownership of the work, the copyright of the elements in the content of the work and those who produce these elements also emerge as an important problem in productions made with artificial intelligence.
Purpose of Study: In this study, it is aimed to examine the copyright issue in artificial intelligence applications of smart production and autonomous systems.
Sources of Evidence: In the research, a literature review was conducted and semiotic analysis and content analysis were conducted based on academic studies. According to the results obtained, analyzes were made regarding the deficiencies in copyright and the main problems arising from field applications in smart production and autonomous systems made through artificial intelligence.
Main Argument: The main argument of the research is that copyright is an important problem in both the short and long term in smart production and autonomous systems produced through artificial intelligence.
Conclusions: Although DSM Directive 2019/790/EU, which was issued in 2016 and came into force in 2019, regulates digital copyrights, there are serious deficiencies regarding the ownership of the system or work and the legal regulations regarding smart productions and autonomous systems produced through artificial intelligence. While DSM Directive 2019/790/EU targets a uniform digital market, the copyright issue in artificial intelligence applications shows that this regulation is also inadequate. Regarding the AI Act, there is not yet sufficient regulation or implementation data regarding copyrights. The United States Copyright Office published in 2023 points out similar deficiencies in artificial intelligence and copyrights. Existing copyright regulations are insufficient today, especially for smart products produced by autonomous systems. One of the most important sources of the problem is that the work, its ownership, the types of work, and the commercial and moral values of the work are not fully defined. For a solution, comprehensive and advanced studies are needed regarding the copyrights of artificial intelligence
AN INVESTIGATION OF THE FLUCTUATION IN LANGUAGE LEARNING MOTIVATION OVER TIME: A QUALITATIVE CASE STUDY
Get PDFIn SLA, the variation of motivation when learning a language is a significant research area (Kikuchi, 2015). It has been established that motivation fluctuates, and that high and low levels of motivation alternate during language learning cycles (Albalawi & Al-Hoorie, 2021; Kikuchi, 2015, 2019). This research aims to comprehend and investigate the complexity of motivation fluctuation across language learning experiences which involves demotivation and remotivation. It focuses on the language learning motivation fluctuations of female students who studied general English in Saudi Arabia for more than six years at the school level up until their first year of university at the age of nineteen. It considers the dynamic and changing nature of motivation and its context-specific nature. It explores motivation fluctuation with broad perspective considering typical and atypical, academic, and non-academic as well as internal and external factors that lead to language learners’ demotivation in English language learning and the demotivation process. It also explores how language learners get remotivated after experiencing demotivation in language learning, including factors, opportunities, and challenges. To help understand this transient nature and process, this research adopts a qualitive design and will utilize thick data captured through narrative inquiry. It aims to capture language learners’ motivation fluctuation, their loss of that motivation, as well as their regaining of it. The term "language learner" describes a person who is consciously involved in the process of acquiring, developing, or improving their skill in one or more languages that can be considered foreign or second languages and may take place in formal settings like universities and institutions or through independent study utilizing alternative resources (Littlewood, 1984)
FACTORS AFFECTING THE DECISION MAKING TO CHOOSE DANCE SCHOOL IN BANGKOK METROPOLITAN AREA
Get PDFThis study investigates factors influencing the decision-making process of individuals choosing dance schools in the Bangkok Metropolitan Area. Using a mixed-methods approach, the research combines quantitative surveys and qualitative interviews to identify key determinants such as location, reputation, cost, curriculum, and instructor qualifications. Findings reveal that while cost and location are significant, the reputation of the school and instructor qualifications play crucial roles. The study aims to provide insights for dance school administrators to better understand their target market and improve their offerings. Objectives include studying the demographic characteristics of those who choose dance schools in Bangkok, examining consumer behavior toward the dance school industry, and analyzing the importance of the marketing mix (product, price, distribution channel, promotion, process, image, and presentation) for prospective students. Methods involve a quantitative approach with descriptive research and surveys. Cluster 1 is diverse in gender, with many young adults and middle-aged respondents, including students, private company officers, and lower to mid-income earners. Consumer behavior in this cluster shows a balanced interest in various dance courses, lower study expenses, a preference for evening study times, and a high preference for weekend study times. Cluster 2 is predominantly female, younger, and more diverse in occupation and income levels, with higher education levels and higher income earners. This cluster focuses on finding special skills and talents, with a strong preference for specific dance courses (especially K-pop Dance), more diverse and higher study expenses, balanced study times throughout the day, and varied main study times, including weekends and combined times. In conclusion, the importance of the marketing mix (7Ps) segments consumers into two clusters in this study
DETERMINANTS OF THE ORGANIZATIONAL PERFORMANCE OF BUSINESSES IN NINH THUAN PROVINCE
Get PDFThis research explores the critical factors influencing organizational performance in businesses based in Ninh Thuan Province, Vietnam. Leveraging key theoretical frameworks, including Resource-Based View and Dynamic Capability Theory, the study evaluates the impacts of human resource management practices, organizational culture, organizational innovation, intellectual capital, and organizational citizenship behavior (OCB). Using Structural Equation Modeling, data from 412 senior and middle-level managers were analyzed to validate the proposed hypotheses. The findings highlight that organizational culture exerts the most significant influence on performance, followed closely by OCB, intellectual capital, HRM practices, and organizational innovation. These results underscore the interplay between these factors, emphasizing the need for a robust organizational culture, strategic HRM, and proactive engagement in intellectual capital development. The study provides a comprehensive foundation for managerial strategies aimed at improving organizational efficiency, fostering innovation, and ensuring sustainable growth in competitive markets