IEEE Engineering Management Review最新文献_第7页

Data Conversion in ERP SaaS Implementation With Generative AI 基于生成式AI的ERP SaaS实施中的数据转换

IEEE Engineering Management Review Pub Date : 2024-09-02 DOI: 10.1109/EMR.2024.3452682

Himanshu Kubba

{"title":"Data Conversion in ERP SaaS Implementation With Generative AI","authors":"Himanshu Kubba","doi":"10.1109/EMR.2024.3452682","DOIUrl":"https://doi.org/10.1109/EMR.2024.3452682","url":null,"abstract":"Enterprise resource planning (ERP) implementation necessitates efficient data conversion, traditionally characterized by labor-intensive tasks, such as validation checks, field mapping, and transformations. While effective, these methods are time-consuming and costly. With the advent of generative artificial intelligence (Gen AI), data conversion has been revolutionized, significantly reducing manual intervention. Traditional methods, often labor-intensive and costly, are replaced by automated Gen AI solutions. This innovation not only reduces technical effort and business involvement but also accelerates project timelines and lowers costs. This article explores the implementation of a Gen AI-driven solution that automates data extraction, validation, and mapping, enhancing accuracy and efficiency. Utilizing advanced technologies, such as SQL, Python pandas, and PyTorch, this approach reimagines the workflow, enabling faster and more reliable ERP implementations with minimal disruption. By harnessing the power of machine learning and neural networks, the system evolves continuously, offering a scalable and robust solution for modern enterprises navigating the complexities of digital transformation. The adoption of Gen AI in data conversion thus represents a pivotal advancement, enabling faster, more reliable ERP implementations, and fostering greater operational resilience and adaptability.","PeriodicalId":35585,"journal":{"name":"IEEE Engineering Management Review","volume":"52 6","pages":"15-18"},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455268","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

Understanding and Enhancing Electric Vehicle Adoption in India: A Practice-Oriented Approach 理解和提高电动汽车在印度的采用：一个以实践为导向的方法

IEEE Engineering Management Review Pub Date : 2024-09-02 DOI: 10.1109/EMR.2024.3453554

Alok Raj;Rajeev Ranjan Kumar

引用次数: 0

Logistics Sprawl: A Systematic Literature Review 物流蔓延：一个系统的文献综述

IEEE Engineering Management Review Pub Date : 2024-08-19 DOI: 10.1109/EMR.2024.3443240

El Yadari Manal;Jawab Fouad;Moufad Imane

引用次数: 0

Unlocking the Future of Farming: A Review of Metaverse Integration in Agriculture 开启农业的未来：农业中的元宇宙整合综述

IEEE Engineering Management Review Pub Date : 2024-08-02 DOI: 10.1109/EMR.2024.3437655

Hanan Almessabi;Mousa Al-kfairy

{"title":"Unlocking the Future of Farming: A Review of Metaverse Integration in Agriculture","authors":"Hanan Almessabi;Mousa Al-kfairy","doi":"10.1109/EMR.2024.3437655","DOIUrl":"https://doi.org/10.1109/EMR.2024.3437655","url":null,"abstract":"This article reviews 51 scholarly articles to explore integrating metaverse technologies within agriculture. Key findings reveal that the metaverse can enhance precision farming by enabling real-time monitoring of soil conditions and crop health and optimizing inputs such as water, fertilizers, and pesticides. In addition, it facilitates immersive training and educational experiences for farmers, promoting advanced skills and knowledge without physical constraints. Simulating various farming scenarios under different climatic and soil conditions improves preparedness and resilience against climate change. However, the review highlights several challenges to adopting metaverse technologies in agriculture, including technological, economic, and sociocultural barriers such as the digital divide, significant infrastructural investments, and potential resistance from traditional farming sectors. Data privacy and security issues, interoperability among diverse systems, and high deployment costs present further obstacles. The study evaluates the agricultural sector's readiness to integrate advanced technologies like the metaverse, considering existing infrastructure, the availability of technical expertise, and the community's openness to technological innovations. The insights gained provide valuable guidance for policymakers and stakeholders to strategically plan and facilitate the adoption of metaverse technologies, aiming for a sustainable and efficient future in agriculture.","PeriodicalId":35585,"journal":{"name":"IEEE Engineering Management Review","volume":"53 3","pages":"128-143"},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299253","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

Stage-Gate Is Not Waterfall… Find Out Why and How 舞台门不是瀑布，找出原因和方式

IEEE Engineering Management Review Pub Date : 2024-07-12 DOI: 10.1109/EMR.2024.3426228

Robert G Cooper

引用次数: 0

Exploring the Effectiveness of OKRs in Enhancing Company Objectives: A Comparative Study okr提升公司目标的有效性：比较研究

IEEE Engineering Management Review Pub Date : 2024-07-10 DOI: 10.1109/EMR.2024.3426327

Juan M. Criado;Gema Gutiérrez;Javier Garzás;Emilio L. Cano;M. Teresa González de Lena;Javier M. Moguerza

{"title":"Exploring the Effectiveness of OKRs in Enhancing Company Objectives: A Comparative Study","authors":"Juan M. Criado;Gema Gutiérrez;Javier Garzás;Emilio L. Cano;M. Teresa González de Lena;Javier M. Moguerza","doi":"10.1109/EMR.2024.3426327","DOIUrl":"https://doi.org/10.1109/EMR.2024.3426327","url":null,"abstract":"The use of management by objectives (MBOs) methodologies, particularly the objectives and key results (OKRs) framework, has gained widespread attention in recent years as a means of improving organizational performance. This article aims to show that OKRs, a key MBO method, can enhance company performance and employee satisfaction. We conducted a comparative and retroactive analysis of MBO methods used in the 20th and 21st centuries, and surveyed 238 people in nine countries and various companies and positions. We analyzed the results of the survey and compared the variables associated with best practices in the OKR methodology. Our study examined a diverse range of companies, positions, qualifications, and ages, which provides an analysis of whether or not OKRs are being used in the organization and a comprehensive understanding of how OKRs can be implemented across in different contexts. By identifying the best variables associated with optimal performance and employee satisfaction, this article provides practical guidance for organizations seeking to adopt OKR methodology. Furthermore, this article can contribute to the development of best practices in the area of management by objectives, particularly in the context of OKRs, leading to more effective and efficient goal-setting practices in organizations.","PeriodicalId":35585,"journal":{"name":"IEEE Engineering Management Review","volume":"53 2","pages":"110-121"},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925084","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

Modern Machine Learning Solution for Electricity Consumption Management in Smart Buildings 智能建筑用电管理的现代机器学习解决方案

IEEE Engineering Management Review Pub Date : 2024-07-08 DOI: 10.1109/EMR.2024.3424408

Sandeep Kumar Gautam;Vinayak Shrivastava;Sandeep S Udmale;Amit Kumar Singh;Sanjay Kumar Singh

{"title":"Modern Machine Learning Solution for Electricity Consumption Management in Smart Buildings","authors":"Sandeep Kumar Gautam;Vinayak Shrivastava;Sandeep S Udmale;Amit Kumar Singh;Sanjay Kumar Singh","doi":"10.1109/EMR.2024.3424408","DOIUrl":"https://doi.org/10.1109/EMR.2024.3424408","url":null,"abstract":"Effective management of electricity consumption (EC) in smart buildings (SBs) is crucial for optimizing operational efficiency, cost savings, and ensuring sustainable resource utilization. Accurate EC prediction enables proactive decision-making, ensuring that resources are allocated efficiently to meet actual demand levels while maintaining occupant comfort. Population growth, building expansion, and technology usage swiftly escalate electricity demand, thus necessitating economical EC management strategies and assist consumers to better understand and strategically plan their EC. To address these challenges, this article proposes a novel approach based on a hybrid prediction model combining temporal convolutional networks (TCNs) and gated recurrent units (GRU). This approach capitalizes on the strengths of both TCN and GRU. TCN is adept at efficiently identifying diverse patterns, particularly within the complex working environments of SBs, by effectively capturing high- and low-frequency information. Subsequently, GRU is leveraged to address the long-term dependencies within the data, enhancing the accuracy of EC prediction. In this article, the results demonstrate the effectiveness of the proposed hybrid model, outperforming competitive methods with an impressive mean absolute error score. This underscores the potential of this approach to improve energy management practices significantly within SB environments, ultimately enhancing both operational efficiency and occupant satisfaction.","PeriodicalId":35585,"journal":{"name":"IEEE Engineering Management Review","volume":"53 1","pages":"54-62"},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143845332","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

Blockchain and Enhancing Online Retail Consumer Value b区块链和提升网上零售消费者价值

IEEE Engineering Management Review Pub Date : 2024-07-05 DOI: 10.1109/EMR.2024.3423312

Yanji Duan

引用次数: 0

Manager's Practical Toolkit to Improve Password Security in Organizations 经理的实用工具包，以提高密码安全的组织

IEEE Engineering Management Review Pub Date : 2024-07-04 DOI: 10.1109/EMR.2024.3423360

Danuvasin Charoen;Warut Khern-am-nuai

引用次数: 0

A Research Agenda for Strategic Alignment in Sales and Operations Planning 销售和运营计划中战略一致性的研究议程

IEEE Engineering Management Review Pub Date : 2024-07-02 DOI: 10.1109/EMR.2024.3421914

Jerry Shanahan;Frédéric Adam;Seamus O'Reilly

{"title":"A Research Agenda for Strategic Alignment in Sales and Operations Planning","authors":"Jerry Shanahan;Frédéric Adam;Seamus O'Reilly","doi":"10.1109/EMR.2024.3421914","DOIUrl":"https://doi.org/10.1109/EMR.2024.3421914","url":null,"abstract":"This article addresses the challenge of achieving strategic alignment in sales and operations planning. A conceptual framework emerges providing the basis for research propositions to guide empirical investigation to improve understanding for practice. An integrative literature review was employed to synthesize a broad range of literature. With considerable attention given to the need for strategic alignment in sales and operations planning (S&OP), achieving this has proven difficult in practice. This article employs contingency theory to classify themes arising from existing literature into contingency, response, and performance variables. Delving deeper, resource-based view theory provides insight into the feedback loop between response and contingency variables and the application of dynamic capabilities view theory reveals a cyclical adjustment capability that supports a growth-oriented mindset. The findings provide insights into the organizational mindset shift from control to growth, which is required to achieve strategic alignment. Manufacturing organizations, including start-ups, small to medium enterprises, and large companies, struggle to achieve strategic alignment in S&OP and, therefore, fail to trigger longer term decision making. The conceptual framework provides guidance for managers to reflect on their S&OP practices and develop action plans to achieve strategic alignment to extract the full value from their S&OP processes.","PeriodicalId":35585,"journal":{"name":"IEEE Engineering Management Review","volume":"53 2","pages":"41-62"},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143925174","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