Mohamed Assaf , Sena Assaf , Xinming Li , Mohamed Al-Hussein
{"title":"一个多用户游戏为基础的系统规划模块化建设活动","authors":"Mohamed Assaf , Sena Assaf , Xinming Li , Mohamed Al-Hussein","doi":"10.1016/j.eswa.2025.130050","DOIUrl":null,"url":null,"abstract":"<div><div>Supply chain (SC) planning in modular construction (MC) can be challenging because it requires interconnected and complex activities among various teams and across different project stages. Recently, game engines have been increasingly used to resolve these challenges, as they create realistic virtual environments and simulations of possible scenarios before actual project implementation. However, game engine applications have been restricted to single-user and centralized models, limiting real-time collaboration among MC teams. Within a Design Science Research methodology, this study proposes an intelligent game-based modular planning (GAMMOD) system, supported by multi-user functions, which is flexible in terms of access, allowing for either non-immersive or immersive mode, depending on the available hardware tools, for collaborative planning of the MC-SC. The GAMMOD system integrates a blockchain protocol for data security in the non-immersive mode, while the immersive mode relies on user credentials authorization. The GAMMOD system considers both numerical key performance indicators, such as sustainability, cost, and time, as well as practical ones, including road dimensions, module clearance, and possible clashes. Two distinct case studies, representing different MC types, are presented to illustrate the features of the GAMMOD system. The evaluation tests of the GAMMOD system conducted by 14 MC experts have shown a general consensus on its functionality, with 80% to 100% of the participants agreeing or strongly agreeing on the GAMMOD system’s performance. Additionally, the GAMMOD system demonstrated a usability score of 75.7, surpassing the established threshold of 70. The GAMMOD system is expected to help MC stakeholders make informed, collaborative decisions and develop a shared understanding of decision feasibility, potential conflicts, and constraints before the commencement of the MC project.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"299 ","pages":"Article 130050"},"PeriodicalIF":7.5000,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multi-user game-based system for planning modular construction activities\",\"authors\":\"Mohamed Assaf , Sena Assaf , Xinming Li , Mohamed Al-Hussein\",\"doi\":\"10.1016/j.eswa.2025.130050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Supply chain (SC) planning in modular construction (MC) can be challenging because it requires interconnected and complex activities among various teams and across different project stages. Recently, game engines have been increasingly used to resolve these challenges, as they create realistic virtual environments and simulations of possible scenarios before actual project implementation. However, game engine applications have been restricted to single-user and centralized models, limiting real-time collaboration among MC teams. Within a Design Science Research methodology, this study proposes an intelligent game-based modular planning (GAMMOD) system, supported by multi-user functions, which is flexible in terms of access, allowing for either non-immersive or immersive mode, depending on the available hardware tools, for collaborative planning of the MC-SC. The GAMMOD system integrates a blockchain protocol for data security in the non-immersive mode, while the immersive mode relies on user credentials authorization. The GAMMOD system considers both numerical key performance indicators, such as sustainability, cost, and time, as well as practical ones, including road dimensions, module clearance, and possible clashes. Two distinct case studies, representing different MC types, are presented to illustrate the features of the GAMMOD system. The evaluation tests of the GAMMOD system conducted by 14 MC experts have shown a general consensus on its functionality, with 80% to 100% of the participants agreeing or strongly agreeing on the GAMMOD system’s performance. Additionally, the GAMMOD system demonstrated a usability score of 75.7, surpassing the established threshold of 70. The GAMMOD system is expected to help MC stakeholders make informed, collaborative decisions and develop a shared understanding of decision feasibility, potential conflicts, and constraints before the commencement of the MC project.</div></div>\",\"PeriodicalId\":50461,\"journal\":{\"name\":\"Expert Systems with Applications\",\"volume\":\"299 \",\"pages\":\"Article 130050\"},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2025-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert Systems with Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0957417425036668\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Systems with Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957417425036668","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A multi-user game-based system for planning modular construction activities
Supply chain (SC) planning in modular construction (MC) can be challenging because it requires interconnected and complex activities among various teams and across different project stages. Recently, game engines have been increasingly used to resolve these challenges, as they create realistic virtual environments and simulations of possible scenarios before actual project implementation. However, game engine applications have been restricted to single-user and centralized models, limiting real-time collaboration among MC teams. Within a Design Science Research methodology, this study proposes an intelligent game-based modular planning (GAMMOD) system, supported by multi-user functions, which is flexible in terms of access, allowing for either non-immersive or immersive mode, depending on the available hardware tools, for collaborative planning of the MC-SC. The GAMMOD system integrates a blockchain protocol for data security in the non-immersive mode, while the immersive mode relies on user credentials authorization. The GAMMOD system considers both numerical key performance indicators, such as sustainability, cost, and time, as well as practical ones, including road dimensions, module clearance, and possible clashes. Two distinct case studies, representing different MC types, are presented to illustrate the features of the GAMMOD system. The evaluation tests of the GAMMOD system conducted by 14 MC experts have shown a general consensus on its functionality, with 80% to 100% of the participants agreeing or strongly agreeing on the GAMMOD system’s performance. Additionally, the GAMMOD system demonstrated a usability score of 75.7, surpassing the established threshold of 70. The GAMMOD system is expected to help MC stakeholders make informed, collaborative decisions and develop a shared understanding of decision feasibility, potential conflicts, and constraints before the commencement of the MC project.
期刊介绍:
Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.