Journal of Business and Management Studies最新文献_第2页

The Impact of Algorithm Management on Employee Job Satisfaction: Exploring the Mediating Role of Job Autonomy and the Moderating Effect of Employee Attitude: A Case Study on Two Premier Universitas Muhammadiyah (UMS and UMY) 算法管理对员工工作满意度的影响：探索工作自主性的中介作用和员工态度的调节作用：对两所顶级穆罕默迪亚大学（穆罕默迪亚大学和穆罕默迪亚青年大学）的案例研究

Journal of Business and Management Studies Pub Date : 2024-06-12 DOI: 10.32996/jbms.2024.6.3.20

Nakayenga Sharifah, Farid Wajdi, I. Susila, Nur Achmed

{"title":"The Impact of Algorithm Management on Employee Job Satisfaction: Exploring the Mediating Role of Job Autonomy and the Moderating Effect of Employee Attitude: A Case Study on Two Premier Universitas Muhammadiyah (UMS and UMY)","authors":"Nakayenga Sharifah, Farid Wajdi, I. Susila, Nur Achmed","doi":"10.32996/jbms.2024.6.3.20","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.3.20","url":null,"abstract":"This study delves into the intricate relationships among algorithm management, job autonomy, employee attitudes, and job satisfaction in the higher education landscape of Universitas Muhammadiyyah in Indonesia (UMS and UMY). Employing a quantitative methodology with a sizable sample of 550 individuals, comprising 250 respondents, and data collection encompassed surveys and interviews, yielding 215 responses. Ensuring the reliability of survey tools through test-retest and Cronbach's alpha analysis utilized Microsoft Excel, SPSS, and Smart PLS. Key hypotheses were tested, highlighting the positive impact of algorithm management on job autonomy. Additionally, the study explored job autonomy's positive effect on employee job satisfaction and its mediating role in the relationship between algorithm management and Job satisfaction. Employee attitudes were scrutinized as moderators of these relationships, and their positive influence on job satisfaction was established. The findings reveal the significant implications of algorithm management on both job autonomy and job satisfaction. Job autonomy was found to empower employees, leading to increased satisfaction and reduced stress, and employee attitude has no connection between algorithms management and job satisfaction. Therefore, these findings illuminate the intricate interplay between algorithm management, job autonomy, employee attitudes, and job satisfaction in the context of higher education.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":"14 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141355297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Green Human Resource Management Practices and Environment Sustainability: From Empirical Evidence 绿色人力资源管理实践与环境可持续性：从经验证据看

Journal of Business and Management Studies Pub Date : 2024-06-10 DOI: 10.32996/jbms.2024.6.3.19

Anne Kalei

{"title":"Green Human Resource Management Practices and Environment Sustainability: From Empirical Evidence","authors":"Anne Kalei","doi":"10.32996/jbms.2024.6.3.19","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.3.19","url":null,"abstract":" \u0000Green human resource management, if well designed and implemented, is undeniably one of the avenues that is envisaged to contribute towards the actualization of the Sustainable Development Goals (SDGs). This paper set out to interrogate the extant literature on Green Human Resource Management (GHRM) Practices and their nexus to environmental sustainability. One of the emerging issues within business communities is the campaign of going green (GG). GHRM is a drive which helps to create a green workforce that can understand and appreciate green culture in businesses and institutions. It is paramount to note that human resource and their systems are the basic foundation of any business. It is a fact that the human resource function in an organization is responsible for planning and executing those eco-friendly policies to create a green environment. The study was mainly a desktop, where a review and synthesis of the existing empirical literature was undertaken. The main sources of the data and information for purposes of this paper were largely relevant reports, journals and books. Past writings indicate that there is a growing need for the integration of environmental management into Human Resource Management (HRM) research practice. This article pursues an integrated view of the literature on Green HRM. It examines and interrogates the current empirical literature in the area of green human resource management with a view to pointing out and synthesizing the gray areas and suggesting a way forward towards enriching knowledge and practice in the area of green human resource management. Finally, the paper suggests some key HR initiatives towards creating and nurturing GHRM practices and behaviour for environmental sustainability. This article draws together the extant literature in this area in suggesting managerial implications and research direction in GHRM. Hence, the papers demystifies the debate and discussion on GHRM and suggests new fronts that requires research focus.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141363322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Entrepreneurial Education and Intention: Basis for an Enhanced Entrepreneurial Mindset among Engineering Students at Guandong Industry and Trade Vocational School, China 创业教育与创业意向：中国广东工贸职业技术学校工科学生创业心态提升的基础

Journal of Business and Management Studies Pub Date : 2024-06-08 DOI: 10.32996/jbms.2024.6.3.17

Zhenbo Yang

{"title":"Entrepreneurial Education and Intention: Basis for an Enhanced Entrepreneurial Mindset among Engineering Students at Guandong Industry and Trade Vocational School, China","authors":"Zhenbo Yang","doi":"10.32996/jbms.2024.6.3.17","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.3.17","url":null,"abstract":"This research focuses on exploring the impact of entrepreneurial education on the entrepreneurial intentions of engineering students at Guangdong Industry and Trade Vocational School in China. The study aims to investigate how factors such as self-efficacy, motivation, and entrepreneurial education influence students' intentions to pursue entrepreneurship. By employing a quantitative descriptive research design, data was collected through structured questionnaires from a diverse sample of students. Statistical analyses, including multiple linear regression and Pearson correlation, were used to examine the relationships between variables. The findings revealed significant correlations between self-efficacy, motivation, entrepreneurial education, and entrepreneurial intention. The study underscores the importance of integrating entrepreneurial education into engineering curricula to foster a culture of innovation and entrepreneurship among students. These results have implications for educational institutions seeking to enhance students' entrepreneurial mindset and readiness for the business world.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Consumers’ Continuous Usage towards Improved Operations and Management of Cross-Border E-Commerce Websites in Jinjiang, Fujian Province, China 消费者对福建晋江跨境电子商务网站运营管理改进的持续使用情况

Journal of Business and Management Studies Pub Date : 2024-06-08 DOI: 10.32996/jbms.2024.6.3.16

Tianfa Luo

{"title":"Consumers’ Continuous Usage towards Improved Operations and Management of Cross-Border E-Commerce Websites in Jinjiang, Fujian Province, China","authors":"Tianfa Luo","doi":"10.32996/jbms.2024.6.3.16","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.3.16","url":null,"abstract":"This research paper delves into the dynamics of cross-border e-commerce in Jinjiang, China, focusing on consumer behavior and platform preferences. The study aims to investigate the factors influencing consumers' continuous usage of cross-border e-commerce websites, such as perceived ease of use, perceived usefulness, perceived security, service quality, and customer satisfaction. Through a quantitative descriptive study, data was collected from 384 consumers using structured surveys and questionnaires. Statistical analyses, including multiple linear regression and Pearson correlation, revealed the significance of these factors in shaping consumer behavior. The findings highlight the importance of tailoring marketing strategies to meet diverse consumer needs and preferences in the competitive e-commerce landscape. By understanding these factors, businesses can enhance customer satisfaction, and loyalty, and ultimately drive long-term growth and sustainability. The implications derived from this study provide valuable insights for stakeholders to navigate the evolving online retail environment effectively.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":" 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141370340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implications of Generative Al and Machine Learning on Automotive Industry Development & Reduction of Carbon Footprint: An Analysis of the U.S. Economy Perspective 生成式人工智能和机器学习对汽车行业发展和减少碳足迹的影响：美国经济视角分析

Journal of Business and Management Studies Pub Date : 2024-06-05 DOI: 10.32996/jbms.2024.6.3.15

Md Sumon Gazi

{"title":"Implications of Generative Al and Machine Learning on Automotive Industry Development & Reduction of Carbon Footprint: An Analysis of the U.S. Economy Perspective","authors":"Md Sumon Gazi","doi":"10.32996/jbms.2024.6.3.15","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.3.15","url":null,"abstract":"The U.S. automotive industry is instrumental to the economy and contributes significantly to the American GDP, employment, and global trade. The principal objective of this research paper is to examine the implications of Generative AI and ML in advancing the automotive industry from the U.S. economic perspective. Generative AI is the latest frontier in artificial intelligence software development, where algorithmic generation can be achieved across various types of content: text, images, audio, and video. The generative AI in the Automotive market at the global level had witnessed boisterous growth and commanded a value of approximately $389.47 million by 2023. The analysis exposed that North American regions are dominating the market, which was attributed to high technological infrastructure, along with partnerships among automotive companies with research institutes and universities to foster AI innovations. Application analysis exposed that Advanced Driver Assistance Systems (ADAS) had the biggest market share, indicating a strong focus on developing and implementing Generative AI technologies to enhance driver safety and vehicle autonomy. Followed by, Connected Car Technologies, representing growing efforts towards implementing generative AI solutions that will improve vehicle connectivity, infotainment, and user experience. The impact of Generative AI and Machine Learning can be witnessed in terms of virtual prototyping, generative automotive designs, consolidation with the CAD system, supply chain optimization, Sensor Fusion and Perception Enhancement as well as automotive manufacturing process optimization.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":"38 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141384453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Monetary Policy Challenges and Strategies in the Globalization: An Analysis of the Federal Reserve's Approach to the Trilemma 全球化背景下的货币政策挑战与战略：分析美联储应对三难困境的方法

Journal of Business and Management Studies Pub Date : 2024-04-25 DOI: 10.32996/jbms.2024.6.2.18

Guofang Ji

引用次数: 0

Product Demand Forecasting with Neural Networks and Macroeconomic Indicators: A Comparative Study among Product Categories 利用神经网络和宏观经济指标进行产品需求预测：产品类别比较研究

Journal of Business and Management Studies Pub Date : 2024-04-23 DOI: 10.32996/jbms.2024.6.2.17

Tuan Ngoc Nguyen, Mahfuz Haider, Afjal Hossain Jisan, Md Azad Hossain Raju, Touhid Imam, Md Munsur Khan, Abdullah Evna Jafar

{"title":"Product Demand Forecasting with Neural Networks and Macroeconomic Indicators: A Comparative Study among Product Categories","authors":"Tuan Ngoc Nguyen, Mahfuz Haider, Afjal Hossain Jisan, Md Azad Hossain Raju, Touhid Imam, Md Munsur Khan, Abdullah Evna Jafar","doi":"10.32996/jbms.2024.6.2.17","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.2.17","url":null,"abstract":"In the fiercely competitive global corporate arena, the intricacies of demand forecasting in the retail sector have become a focal point. While previous research has delved into various methodologies, it consistently overlooks the distinct performances of forecasting models within different retail product categories. Understanding these variations in prediction performances is pivotal, enabling firms to fine-tune forecasting models for each category. This study bridges this gap by scrutinizing the prediction performances of models tailored to different product categories. Building on recent research, we incorporate external macroeconomic indicators like the Consumer Price Index, Consumer Sentiment Index, and unemployment rate, alongside time series data of retail sales spanning various categories. This amalgamated dataset is employed to train a Long Short Term Memory model, projecting future demand across product categories. We further extend the analysis by identifying features that contribute most towards explaining product demand and quantifying their strength. The fitted models yield comprehensive insights into their performances and pinpoint the product categories warranting more focused model development.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":"131 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140668859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rich Dad, Poor Dad's Financial Freedom Road Map 富爸爸，穷爸爸》的财务自由路线图

Journal of Business and Management Studies Pub Date : 2024-04-22 DOI: 10.32996/jbms.2024.6.2.16

Guanlin Zhu

{"title":"Rich Dad, Poor Dad's Financial Freedom Road Map","authors":"Guanlin Zhu","doi":"10.32996/jbms.2024.6.2.16","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.2.16","url":null,"abstract":"With the rapid development of the global economy, trade between nations is becoming more and more closer in the context of economic globalization. People's pursuit of a happy life has also reached a new level, with financial freedom being a goal that an increasing number of people are pursuing on their path to happiness. The objective of this research is to examine in detail the ideas of financial freedom presented in the book “Rich Dad Poor Dad” and to investigate how these ideas may be more effectively applied to individual financial planning in order to attain financial independence, taking into account the current socioeconomic climate. This study employs a range of research methodologies, such as the literature research method, case study method, and qualitative analysis method. It begins by introducing the idea and significance of financial freedom, then analyzes the book's central financial concepts, and finally offers recommendations and strategies for achieving financial freedom in the context of the contemporary socioeconomic environment. The paper concludes by summarizing the findings and anticipating the direction of additional research on financial independence. Changing one's financial concepts, investing in financial education, and generating passive income are the keys to achieving financial freedom, according to this study, which was conducted after extensive research and analysis of the book Rich Dad, Poor Dad. People can also become more financially independent by having a deeper understanding of these concepts.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":"99 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Regional Business Performance: Leveraging Business and Data Analytics in Logistics & Supply Chain Management for USA's Sustainable Growth 优化地区业务绩效：利用物流和供应链管理中的业务和数据分析促进美国的可持续增长

Journal of Business and Management Studies Pub Date : 2024-04-20 DOI: 10.32996/jbms.2024.6.2.14

Md Sumon Gazi

{"title":"Optimizing Regional Business Performance: Leveraging Business and Data Analytics in Logistics & Supply Chain Management for USA's Sustainable Growth","authors":"Md Sumon Gazi","doi":"10.32996/jbms.2024.6.2.14","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.2.14","url":null,"abstract":"The logistics and supply chain management (SCM) sector plays a paramount role in the economic development and growth of countries. In the USA, the effectiveness and efficiency of logistics and SCM functions directly influence regional organizational performance and long-term economic sustainability. The prime objective of this research is to explore the phenomenon of optimizing regional business performance through the application of data and business analytics in logistics and supply chain management for the sustainable growth of the US economy. In this study, the researcher employed machine learning methodologies, specifically ANN, RNN, and SVM, to forecast lead times for purchasing aluminum products. In the research, historical data was collected from the database of one of the aluminum-producing companies in the USA for the last 10 years. In particular, a sample of 38,500 orders of aluminum profiles was adopted for the current study. Retrospectively, the Recurrent Neural Network and the Support Vector Machine displayed the most favorable outcomes in predicting lead time in the supply chain. Particularly, RNN had the least Mean Average Error (MAE) on the testing set (447.72), followed by SVM (453.04), MLR (453.22), and NN (455.41). By deploying these algorithms, the government can optimize inventory degrees, minimize stockouts, and reduce excess inventory. This results in enhanced efficiency, diminished carrying costs, and elevated consumer satisfaction, leading to cost savings and heightened profitability for government companies within the supply chain.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":" 1076","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140681886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Algorithmic Trading Strategies: Leveraging Machine Learning Models for Enhanced Performance in the US Stock Market 算法交易策略：利用机器学习模型提高美国股市表现

Journal of Business and Management Studies Pub Date : 2024-04-20 DOI: 10.32996/jbms.2024.6.2.13

N. Gurung, Sumon Gazi, Md zahidul Islam, Md Rokibul Hasan

{"title":"Algorithmic Trading Strategies: Leveraging Machine Learning Models for Enhanced Performance in the US Stock Market","authors":"N. Gurung, Sumon Gazi, Md zahidul Islam, Md Rokibul Hasan","doi":"10.32996/jbms.2024.6.2.13","DOIUrl":"https://doi.org/10.32996/jbms.2024.6.2.13","url":null,"abstract":"In the recent past, algorithmic trading has become exponentially predominant in the American stock market. The principal objective of this research was to explore the employment of machine learning frameworks in formulating algorithmic trading strategies tailored for the US stock market. For this investigation, an array of software tools was employed, comprising the Pandas library for data manipulation and analysis, the Python programming language, the Scikit-learn library for machine learning algorithms and analysis metrics, and the LIME library for explainable AI. In this study, the researcher gathered an extensive dataset from the Amazon Stock Exchange, spanning from October 19, 2018, to October 16, 2022. The dataset comprised a wide range of parameters related to Amazon's stock data, facilitating a rigorous analysis of its market performance. Five models were subjected to the experiment, notably Ridge Regression, Ada-Boost, Light-GBM, XG-Boost, Linear Regression, and Cat-Boost. From the experiment result, it was evident that the XG-Boost attained the highest R-squared (99.24%) and accuracy (99.23%) among all the algorithms. From the above results, the analyst inferred that the XG-Boost was able to learn a more complex and accurate model of the stock exchange data compared to the other algorithms. XG-Boost algorithm can be utilized to back-test distinct trading strategies on historical data, enabling investors to evaluate their efficiency before risking real capital. By assessing a wide array of factors, the XG-Boost algorithm can assist investors in selecting stocks with a higher probability of outperforming the market.","PeriodicalId":505050,"journal":{"name":"Journal of Business and Management Studies","volume":"112 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140680866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0