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Journals / Verimlilik Dergisi / 2026 / Cilt: 60 Sayı: 4

Making Sensory Conflicts Visible: Modelling the Risk of Conflict in the Workplace Using LLM-Based Simulations

Duyusal Çatışmaları Görünür Kılmak: LLM Tabanlı Si̇mülasyonlarla İşyeri̇nde Çatışma Ri̇ski̇nin Modellenmesi

Seçil Pelin Aka(HALİÇ ÜNİVERSİTESİ)0000-0003-0915-990X
Berna Güner0000-0002-0410-9914
Pages
1215–1232
Publication Date
2026-10-21
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Findings: The findings indicate that significant sensory clustering emerges among workers under constant environmental conditions.

📌 3 Key Takeaways

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Objective & Hypothesis:Purpose: This study aims to reveal how sensory sensitivity differences in fixed indoor environments, such as open offices, produce distinct risk patterns in employees through a cumulative sensory load, performance loss, and the need for breaks, and to make visible the patterns extending to conflict risk through large language model (LLM) -based simulations.
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Key Findings & Data:Method: Seventy persona with different sensory sensitivities were analyzed under fixed office parameters (700 lux light, 28°C, medium intensity scent) using Python.
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Conclusion & Impact:Findings: The findings indicate that significant sensory clustering emerges among workers under constant environmental conditions.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:İşyeri Duyusal Çevresi · Örgütsel Çatışma · Ajan Tabanlı Modelleme

Abstract

Purpose: This study aims to reveal how sensory sensitivity differences in fixed indoor environments, such as open offices, produce distinct risk patterns in employees through a cumulative sensory load, performance loss, and the need for breaks, and to make visible the patterns extending to conflict risk through large language model (LLM) -based simulations. Method: Seventy persona with different sensory sensitivities were analyzed under fixed office parameters (700 lux light, 28°C, medium intensity scent) using Python. The cumulative sensory load index, performance loss, and break needs at the end of three weeks were examined, and the resulting data were converted into risk patterns within Mind Studio using an agent-based modeling and simulation approach. Findings: The findings indicate that significant sensory clustering emerges among workers under constant environmental conditions. Simulation outputs suggest that differences in sensory sensitivity can lead to social labeling and conflict risk through break needs, performance loss, and behavioral dissociation. Originality: This study's originality lies in combining a persona-based sensory load index with simulation analysis, transforming the mechanisms behind labeling and conflict risk into a manageable early warning framework. It also demonstrates that agent-based modeling can serve as a decision support tool for organizational decision making within Society 5.0.

Özet

Amaç: Bu çalışma, açık ofis gibi sabit iç ortam koşullarında duyusal hassasiyet farklarının çalışanlarda kümülatif duyusal yük, performans kaybı ve mola ihtiyacı üzerinden nasıl ayrışan risk örüntüleri ürettiğini ve büyük dil modeli (large language model-LLM) tabanlı simülasyonlar ile çatışma riskine uzanan örüntülerini görünür kılmayı amaçlamaktadır. Yöntem: Çalışmada farklı duyusal hassasiyetlere sahip yetmiş temsili profilin sabit ofis parametreleri (700 lux ışık, 28°C, orta yoğunlukta koku) altında Python programlama dili kullanılarak üç hafta sonundaki kümülatif duyusal yük endeksi, performans kayıpları ve mola alma ihtiyaçları analiz edilmiştir. Elde edilen sayısal veriler, ajan tabanlı modelleme ve simülasyon yaklaşımı çerçevesinde Mind Studio ortamında risk örüntülerine dönüştürülerek yorumlanmıştır. Bulgular: Bulgular, sabit çevresel koşullar altında çalışanlar arasında belirgin bir duyusal kümelenme ortaya çıktığını göstermektedir. Simülasyon çıktıları, duyusal hassasiyet farklılıklarının mola ihtiyacı, performans kaybı ve davranışsal ayrışma üzerinden sosyal etiketleme ve çatışma riskine zemin hazırlayabileceğine işaret etmektedir. Özgünlük: Çalışmanın özgünlüğü, duyusal verileri teknoloji yönetimi perspektifiyle ele alarak temsili profil temelli duyusal yük endeksini simülasyon analizi ile birleştirmesi ve böylece heterojen duyusal profillerin etiketleme ve çatışma riskine giden olası mekanizmaları yönetilebilir bir erken uyarı çerçevesine dönüştürmesidir. Ayrıca ajan tabanlı modelleme ve simülasyonların, Toplum 5.0 bağlamında örgütsel karar süreçlerini destekleyen uygulanabilir bir karar destek yaklaşımı olarak kullanılabileceğini göstermektedir.

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Cite This Article

Aka, S. P., Güner, B. (2026). Making Sensory Conflicts Visible: Modelling the Risk of Conflict in the Workplace Using LLM-Based Simulations. Verimlilik Dergisi, Cilt: 60 Sayı: 4, 1215–1232. https://doi.org/10.51551/verimlilik.1936064

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