[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3063":3,"related-3063":67},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"primary_topic":9,"secondary_topics":21,"classification":22,"search_phrases":39,"slug":40,"view_count":15,"doi":41,"paper":42,"created_at":66},3063,"The Impact of AI-Powered Decision Support Systems on Decision-Making Effectiveness","https:\u002F\u002Fdoi.org\u002F10.26877\u002Fasset.v8i4.2432","AI-powered Decision Support Systems (AI-DSS) enhance analytical capabilities through advanced data processing, predictive analytics, and intelligent decision support. This study investigates the impact of AI-powered DSS on decision-making effectiveness across multiple sectors. A quantitative research design was employed using a structured questionnaire distributed to 33 professionals and decision-makers experienced in AI-based DSS. Decision-making effectiveness was assessed through decision accuracy, decision-making speed, operational efficiency, and user satisfaction. Data were analyzed using descriptive statistics, Pearson correlation, and simple linear regression. The results show a moderate positive correlation between AI usage and decision-making effectiveness (r = 0.550, p \u003C 0.001). Regression analysis further demonstrates that AI utilization significantly predicts decision-making effectiveness (B = 0.265, t = 3.664, p \u003C 0.001). These findings indicate that greater utilization of AI-powered DSS is associated with improved decision outcomes, particularly in decision accuracy, response speed, and operational efficiency. The study also demonstrates the applicability of AI techniques, including machine learning, neural networks, fuzzy logic, and Bayesian modelling, across diverse industrial contexts. Overall, the findings provide empirical evidence that AI-powered DSS contribute significantly to organizational decision-making effectiveness across multiple sectors.","人工智能驱动的决策支持系统（AI-DSS）通过先进的数据处理、预测分析和智能决策支持增强分析能力。本研究探讨了人工智能驱动的决策支持系统在多个行业中对决策有效性的影响。研究采用定量研究设计，使用结构化问卷，向33位具有基于人工智能的决策支持系统经验的专业人士和决策者发放。决策有效性通过决策准确性、决策速度、运营效率和用户满意度进行评估。数据采用描述性统计、皮尔逊相关和简单线性回归进行分析。结果显示，人工智能使用与决策有效性之间存在中等程度的正相关（r = 0.550，p \u003C 0.001）。回归分析进一步表明，人工智能的使用显著预测决策有效性（B = 0.265，t = 3.664，p \u003C 0.001）。这些发现表明，人工智能驱动的决策支持系统使用程度越高，决策结果越好，尤其是在决策准确性、响应速度和运营效率方面。研究还展示了人工智能技术（包括机器学习、神经网络、模糊逻辑和贝叶斯建模）在不同工业场景中的适用性。总体而言，研究结果提供了实证证据，表明人工智能驱动的决策支持系统对多个行业中的组织决策有效性具有显著贡献。",null,"Advance Sustainable Science Engineering and Technology","2026-09-18T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"研究AI决策支持系统对决策效能的影响，属通用管理信息系统议题，未涉及三农或农业信息化场景，相关性不足。",[19],{"name":10,"url":6},[12],[],{"status":23,"locked":14,"version":24,"method":25,"evidence":26},"needs_review","2026-10-22.2","rules",{"candidates":27,"agricultural_evidence":14,"reason":38},[28],{"code":29,"score":30,"supported":31,"title":32,"abstract":34,"tags":37},"I2",17,true,[33],"decision support",[35,36,33],"机器学习","machine learning",[],"农业相关性需要复核",[],"TheImpactofAI-PoweredDecisionSupportSyst-3063","10.26877\u002Fasset.v8i4.2432",{"doi":41,"openalex_id":43,"authors":44,"venue":10,"cited_by_count":15,"oa_url":57,"card":58,"direction":64,"ingested_from":65},"W7213533827",[45,48,51,54],{"name":46,"orcid":47},"Edi Priyanto","https:\u002F\u002Forcid.org\u002F0000-0002-9819-7598",{"name":49,"orcid":50},"Nur Wening","https:\u002F\u002Forcid.org\u002F0000-0002-9513-5201",{"name":52,"orcid":53},"Rianto Rianto","https:\u002F\u002Forcid.org\u002F0000-0002-5058-4580",{"name":55,"orcid":56},"Tri Gunarsih","https:\u002F\u002Forcid.org\u002F0000-0001-6827-2510","https:\u002F\u002Fjournal2.upgris.ac.id\u002Findex.php\u002Fasset\u002Farticle\u002Fdownload\u002F2432\u002F1735",{"tldr":59,"method":60,"finding":61,"direction":62,"opportunity":63},"研究AI决策支持系统对多行业决策效果的影响，发现使用越多效果越好。","对33名AI-DSS使用者问卷调查，用相关与回归分析。","AI使用与决策效果中度正相关，能显著预测决策准确性、速度与效率。","农业人工智能与决策模型","可将该框架迁移到农业场景，验证AI-DSS对农户与农企决策效果的因果影响。","智慧农业 \u002F 农业物联网","openalex","2026-09-21T23:30:10.625088Z",{"total":15,"page":68,"page_size":68,"items":69},1,[]]