Xiahui Liu , Qianwang Deng , Saibo Liu , Guiliang Gong , Qiang Luo
{"title":"Collaboration and sustainability-driven requirement prioritization for cloud platform planning oriented to value chain lifecycle services","authors":"Xiahui Liu , Qianwang Deng , Saibo Liu , Guiliang Gong , Qiang Luo","doi":"10.1016/j.cie.2025.110973","DOIUrl":null,"url":null,"abstract":"<div><div>Requirements analysis is an essential part of the functional planning for cloud platforms. Traditional requirements analysis tends to focus on the customer perspective, rarely considering the dominant role of core manufacturers in the value chain. Integrating service collaboration, sustainable benefits and smart features into the lifecycle service implementation, we first establish the multi-stakeholder, multi-dimensional requirement framework from the perspective of customers, core manufacturers and their partners, including a novel closed-loop business collaboration requirement framework and the sustainable value co-creation framework. Rather than treating value requirements and service requirements as two separate parts, we propose a multi-stage decision model based on Quality Function Deployment (QFD) to establish the connections between service requirements and sustainable value achievement. Thus, the critical service requirements are determined from a holistic perspective of the interaction intensity of the service requirements and their contribution to sustainability. Then, the sensitivity analysis and comparative experiments are performed to verify the effectiveness of the proposed decision model and the necessity of considering judgment reliability in requirements decision. Our research work can guide core enterprises to optimize resource allocation in the value chain, and also provide decision support for the functional module planning of the cloud platform.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"203 ","pages":"Article 110973"},"PeriodicalIF":6.7000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360835225001196","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Requirements analysis is an essential part of the functional planning for cloud platforms. Traditional requirements analysis tends to focus on the customer perspective, rarely considering the dominant role of core manufacturers in the value chain. Integrating service collaboration, sustainable benefits and smart features into the lifecycle service implementation, we first establish the multi-stakeholder, multi-dimensional requirement framework from the perspective of customers, core manufacturers and their partners, including a novel closed-loop business collaboration requirement framework and the sustainable value co-creation framework. Rather than treating value requirements and service requirements as two separate parts, we propose a multi-stage decision model based on Quality Function Deployment (QFD) to establish the connections between service requirements and sustainable value achievement. Thus, the critical service requirements are determined from a holistic perspective of the interaction intensity of the service requirements and their contribution to sustainability. Then, the sensitivity analysis and comparative experiments are performed to verify the effectiveness of the proposed decision model and the necessity of considering judgment reliability in requirements decision. Our research work can guide core enterprises to optimize resource allocation in the value chain, and also provide decision support for the functional module planning of the cloud platform.
期刊介绍:
Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.