International Journal of Information Management Data Insights最新文献_第8页

Examining the effect of AI-BDA on manufacturing firm performance: An Indian approach 研究人工智能-BDA 对制造业公司业绩的影响：印度的方法

International Journal of Information Management Data Insights Pub Date : 2024-11-16 DOI: 10.1016/j.jjimei.2024.100306

Vaibhav S. Narwane , Pragati Priyadarshinee

{"title":"Examining the effect of AI-BDA on manufacturing firm performance: An Indian approach","authors":"Vaibhav S. Narwane , Pragati Priyadarshinee","doi":"10.1016/j.jjimei.2024.100306","DOIUrl":"10.1016/j.jjimei.2024.100306","url":null,"abstract":"<div><div>Manufacturing firms face an uncertain and continuosly changing environment because of innovations, technological changes, and globalization. To cope with this quick and uncertain environment, firms need to be flexible. Artificial Intelligence (AI) and Big Data Analytics (BDA) are must for manufacturing firms to achieve the flexibility in procurement to manufacturing to marketing. This study explores role of AI-BDA played between Supply Chain Flexibility (SCF) and Supply chain firms performance(SCFP) through six hypothesis. A sample data of 297 responses from forty Indian manufacturing firms were collected. Exploratory and confirmatory factorial analysis were used to analyse the collected data. Out of six hypothesis, four hypothesis are supported. The results show positive impact of AI, BDA and SCF on supply chain firm performance. Also AI positively impacts on BDA. However two hypothesis not supported are positive effect of AI and BDA on SCF needs further investigated. The study can guide decision makers to understand role of AI and BDA to improve supply chain performance.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100306"},"PeriodicalIF":0.0,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blockchain-based conceptual model for enhanced transparency in government records: a design science research approach 基于区块链的提高政府记录透明度概念模型：一种设计科学研究方法

International Journal of Information Management Data Insights Pub Date : 2024-11-14 DOI: 10.1016/j.jjimei.2024.100304

Eid M Alotaibi , Hussein Issa , Mauricio Codesso

引用次数: 0

Enhancing gender equity in resume job matching via debiasing-assisted deep generative model and gender-weighted sampling 通过去伪存真辅助深度生成模型和性别加权抽样加强简历职位匹配中的性别平等

International Journal of Information Management Data Insights Pub Date : 2024-11-01 DOI: 10.1016/j.jjimei.2024.100283

Swati Tyagi , Anuj , Wei Qian , Jiaheng Xie , Rick Andrews

{"title":"Enhancing gender equity in resume job matching via debiasing-assisted deep generative model and gender-weighted sampling","authors":"Swati Tyagi , Anuj , Wei Qian , Jiaheng Xie , Rick Andrews","doi":"10.1016/j.jjimei.2024.100283","DOIUrl":"10.1016/j.jjimei.2024.100283","url":null,"abstract":"<div><div>Our work aims to mitigate gender bias within word embeddings and investigates the effects of these adjustments on enhancing fairness in resume job-matching problems. By conducting a case study on resume data, we explore the prevalence of gender bias in job categorization—a significant barrier to equal career opportunities, particularly in the context of machine learning applications. This study scrutinizes how biased representations in job assignments, influenced by a variety of factors such as skills and resume descriptors within diverse semantic frameworks, affect the classification process. The investigation extends to the nuanced language of resumes and the presence of subtle gender biases, including the employment of gender-associated terms, and examines how these terms’ vector representations can skew fairness, leading to a disproportionate mapping of resumes to job categories based on gender.</div><div>Our findings reveal a significant correlation between gender discrepancies in classification true positive rate and gender imbalances across professions that potentially deepen these disparities. The goal of this study is to (1) mitigate bias at the level of word embeddings via a debiasing-assisted deep generative modeling approach, thereby fostering more equitable and gender-fair vector representations; (2) evaluate the resultant impact on the fairness of job classification; (3) explore the implementation of a gender-weighted sampling technique to achieve a more balanced representation of genders across various job categories when such an imbalance exists. This approach involves modifying the data distribution according to gender before it is input into the classifier model, aiming to ensure equal opportunity and promote gender fairness in occupational classifications. The code for this paper is publicly available on <span><span>GitHub</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100283"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Metaverse in financial industry: Use cases, value, and challenges 金融业的 Metaverse：用例、价值和挑战

International Journal of Information Management Data Insights Pub Date : 2024-10-26 DOI: 10.1016/j.jjimei.2024.100302

Mubashar Iqbal , Sabah Suhail , Fredrik Milani , Yana Halas

引用次数: 0

Overview of the future impact of wearables and artificial intelligence in healthcare workflows and technology 可穿戴设备和人工智能对医疗保健工作流程和技术的未来影响概述

International Journal of Information Management Data Insights Pub Date : 2024-10-18 DOI: 10.1016/j.jjimei.2024.100294

Perry A. LaBoone, Oge Marques

引用次数: 0

Smart dairy: Unleashing emerging ICT-enabled lean dairy supply chains through data-driven decision-making 智能乳品：通过数据驱动决策，释放新兴信息和通信技术带来的精益乳品供应链

International Journal of Information Management Data Insights Pub Date : 2024-10-17 DOI: 10.1016/j.jjimei.2024.100297

Upendra Kumar , Ravi Shankar

引用次数: 0

The influence of AI competency and design thinking skills on innovative entrepreneurial competency: The role of strategic intelligence amongst new age entrepreneurs in Thailand 人工智能能力和设计思维能力对创新创业能力的影响：泰国新时代企业家中战略情报的作用

International Journal of Information Management Data Insights Pub Date : 2024-10-11 DOI: 10.1016/j.jjimei.2024.100301

Narinthon Imjai , Chawapong Nui-Suk , Berto Usman , Phiphop Somwethee , Somnuk Aujirapongpan

{"title":"The influence of AI competency and design thinking skills on innovative entrepreneurial competency: The role of strategic intelligence amongst new age entrepreneurs in Thailand","authors":"Narinthon Imjai , Chawapong Nui-Suk , Berto Usman , Phiphop Somwethee , Somnuk Aujirapongpan","doi":"10.1016/j.jjimei.2024.100301","DOIUrl":"10.1016/j.jjimei.2024.100301","url":null,"abstract":"<div><div>This study investigates the impact of Artificial Intelligence (AI) competency and design thinking skills on the innovative capacities of new-age entrepreneurs in Thailand, based on a sample of 187 students enrolled in business management and entrepreneurship programs. Utilizing Structural Equation Modeling (SEM) and factor analysis, the study evaluates how these competencies influence entrepreneurial innovation. The findings reveal that both AI competencies and design thinking skills significantly enhance the innovation capacity of entrepreneurs. The study underscores the importance of cultivating these skills to improve competitiveness and adaptability in the digital age. Moreover, it presents policy recommendations and necessary training initiatives to effectively integrate AI and design thinking into the entrepreneurial processes of new age entrepreneurs in Thailand. These strategic directions aim to equip them with the requisite skills to navigate evolving challenges within the business sector, thus preparing them for successful entrepreneurial endeavors in increasingly digital market environments.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100301"},"PeriodicalIF":0.0,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The tale of two sides in the 2019 anti-CAA protest—An analytical framework 2019 年反《反垄断法》抗议活动中的双方故事--一个分析框架

International Journal of Information Management Data Insights Pub Date : 2024-10-11 DOI: 10.1016/j.jjimei.2024.100300

Bhaskarjyoti Das , Krithika Ragothaman , Raghav T. Kesari , Sudarshan T.S.B.

{"title":"The tale of two sides in the 2019 anti-CAA protest—An analytical framework","authors":"Bhaskarjyoti Das , Krithika Ragothaman , Raghav T. Kesari , Sudarshan T.S.B.","doi":"10.1016/j.jjimei.2024.100300","DOIUrl":"10.1016/j.jjimei.2024.100300","url":null,"abstract":"<div><div>The 2019 anti-CAA protest in India witnessed massive Twitter participation from people on both sides. It was unique compared to most online social movements that showcase people’s movements against authority. The article offers a framework for a big data-driven outside-in analysis of such online social movements. Unlike most existing research focusing on a particular aspect of such a movement, the framework presented examines mobilization and counter-mobilization from various angles. The work systematically juxtaposes the proponents and opponents using statistical analysis, text mining, and graph analysis techniques. Different aspects such as users, content, themes and focus of the conversations, conversational patterns, instrumentation of virality, leadership styles, emotions, and toxicity of the discourse have been considered. The study also examines them as types of frame alignment effort as per Frame Alignment Theory. The framework proposed by this work can be successfully employed to understand any future online social movement and any inductive research using user-generated Big Data.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100300"},"PeriodicalIF":0.0,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Customers' sentiment on food delivery services: An Arabic text mining approach 顾客对送餐服务的看法：阿拉伯语文本挖掘方法

International Journal of Information Management Data Insights Pub Date : 2024-10-10 DOI: 10.1016/j.jjimei.2024.100299

Dheya Mustafa , Safaa M. Khabour , Ahmed S. Shatnawi

{"title":"Customers' sentiment on food delivery services: An Arabic text mining approach","authors":"Dheya Mustafa , Safaa M. Khabour , Ahmed S. Shatnawi","doi":"10.1016/j.jjimei.2024.100299","DOIUrl":"10.1016/j.jjimei.2024.100299","url":null,"abstract":"<div><div>The Covid-19 pandemic has accelerated the shift in organizations' strategies toward innovative online services. Customer reviews on platforms for online ordering and delivery are a vital source of information about how well a business is performing. Businesses that provide food delivery services (FDS) seek to leverage consumer input to locate areas where customer satisfaction could be raised. Sentiment analysis (SA) has been the subject of an enormous amount of English-language research. Despite Arabic's increasing popularity as a writing language on the Internet, not much study has been conducted on sentiment analysis of Arabic up to this point, with a limited number of publicly available resources for Arabic SA such as datasets and lexicons. The present study collects FDS-related reviews in Arabic to conduct extensive emotion mining, taking advantage of Natural Language Processing, feature selection, and Machine Learning techniques to elicit personal judgments, identify polarity, and recognize customers’ feelings in the FDS domain. To demonstrate that the proposed approach is suitable for analyzing human perceptions of FDS, we designed and carried out excessive experiments that assess the utility of each phase. Our highest categorization accuracy was 90 % using Mutual Information with the SVM classifier. The study's findings provide various managerial insights for improving their plans and service delivery, as well as revealing the main reasons for consumer complaints. It also demonstrates how future academics might harness the power of online business reviews in Arabic using a variety of text-mining approaches.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100299"},"PeriodicalIF":0.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predictive model for customer satisfaction analytics in E-commerce sector using machine learning and deep learning 利用机器学习和深度学习分析电子商务领域客户满意度的预测模型

International Journal of Information Management Data Insights Pub Date : 2024-10-07 DOI: 10.1016/j.jjimei.2024.100295

Hoanh-Su Le , Thao-Vy Huynh Do , Minh Hoang Nguyen , Hoang-Anh Tran , Thanh-Thuy Thi Pham , Nhung Thi Nguyen , Van-Ho Nguyen

{"title":"Predictive model for customer satisfaction analytics in E-commerce sector using machine learning and deep learning","authors":"Hoanh-Su Le , Thao-Vy Huynh Do , Minh Hoang Nguyen , Hoang-Anh Tran , Thanh-Thuy Thi Pham , Nhung Thi Nguyen , Van-Ho Nguyen","doi":"10.1016/j.jjimei.2024.100295","DOIUrl":"10.1016/j.jjimei.2024.100295","url":null,"abstract":"<div><div>In Vietnam's rapidly expanding e-commerce landscape, there is a critical need for advanced tools that can effectively analyze customer feedback to boost satisfaction and loyalty. This paper introduces a two-step predictive framework merging deep learning and traditional machine learning to analyze Vietnamese e-commerce reviews. Utilizing a dataset of 10,021 reviews on Tiki, Shopee, Sendo, and Hasaki between 2015 and 2023, the framework first employs fine-tuned deep learning models like BERT and Bi-GRU to extract aspect-based sentiments from reviews, tailored for the nuances of the Vietnamese language. Subsequently, machine learning algorithms like XGBoost predict customer satisfaction by integrating sentiment analysis with e-commerce data such as product prices. Results show BERT and Bi-GRU yield over 70% sentiment accuracy, while XGBoost achieves 80%+ satisfaction prediction accuracy. This framework offers a potent solution for discerning customer sentiments and enhancing satisfaction in Vietnam's dynamic e-commerce landscape.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100295"},"PeriodicalIF":0.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0