Analytics and Intelligent Decision Support for Green IS and Sustainability Applications
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Item Optimizing a Sensor Network's Granularity to Mitigate Urban Heat Island Effect at 2032 Brisbane Olympics(2025-01-07) Schoe, Celine; Tuczek, Matthias; Degirmenci, Kenan; Breitner, Michael H.In anticipation of the 2032 climate-positive Olympic Games in Brisbane, we address the Urban Heat Island (UHI) effect optimizing the granularity of a sensor network in the Northshore Hamilton Priority Development Area (PDA), i.e., the location of the Athletes' Village, for efficient environmental monitoring and the provision of a Green Information System (IS). We use spatio-temporal sensor data and leverage advanced interpolation techniques to optimize both temporal and spatial granularity settings. Results and findings from our granularity analysis reveal an optimal temporal granularity at one-hour intervals, providing the optimal trade-off balance between computational efficiency and sufficient detail for urban planning. Finer temporal resolutions do not significantly enhance prediction accuracy. Spatial analysis further helps decision makers to balance trade-offs between economic costs and prediction accuracy, eliminating unnecessary sensors in the network.Item Multi-criteria-based approach in Environmental Performance Index evaluation(2025-01-07) Bajdor, Paula; Korpysa, JaroslawThe Environmental Performance Index (EPI) is one of the primary indices illustrating the activities of individual countries in striving to increase environmental efficiency. Its value for each country is calculated based on many partial factors, covering three levels of this indicator. It shows the country's ability to increase environmental performance and identifies areas requiring further improvement. The weights of individual EPI partial factors are calculated using a simple additive method. However, the use of ICT in this area still needs to be improved - the lack of DSS is evident. Thus, we propose a Decision Support System framework using TOPSIS and sensitivity analysis, one of the most popular MCDM methods, and standard deviation to determine objective weights, thus taking into account the multi-factor nature of the EPI index. Then, based on the analyses, we create a ranking of countries regarding their environmental efficiency. As a result, it is visible that the leaders of countries achieving high environmental efficiency are Finland, France, and Germany. In last place are the Czech Republic, Slovakia, and Hungary.Item An Integrated Theoretical Model to Predict the Intention to Use Energy Monitoring Applications. Evidence from Germany(2025-01-07) Wichmann, Johannes; Behn, Oliver; Degirmenci, Kenan; Leyer, Michael; Barros, AlistairEnergy consumption monitoring systems are becoming increasingly sophisticated, yet their adoption to support environmentally friendly decision-making remains low. In this paper, we develop an integrated theoretical model based on Reasoned Action Approach, Unified Theory of Acceptance and Use of Technology 2, and the Self-Efficacy Theory to analyze energy monitoring adoption in a smart home context. We apply the model to empirically test the intention of German consumers to adopt an application for monitoring their energy consumption. Our results show that our model explains the intention to use energy monitoring applications, with common constructs, but highlight the important role of governmental support as a major novelty. We provide practical implications for development processes of energy monitoring applications and theoretical implications by proposing a new integrated model.Item A Petri-net Model for Propagation of Corrupted Data in a Networked System(2025-01-07) Woodard, Mark; Sedigh Sarvestani, Sahra; Hurson, AliThis paper introduces a Petri net model for the propagation of corrupted data in networked systems, including cyber-physical systems. The model abstracts data storage, processing, and communication of a system to estimate the rate and extent of propagation of corrupted data. This facilitates simulation and analysis of the effects of data corruption without requiring a domain-specific simulator. We illustrate the approach by applying it to an IEEE 57-bus smart grid system and analyzing the rate and extent of data corruption - measures of system survivability. The proposed model, with its potential to enable decision support crucial to the sustainability of critical infrastructures, also plays a vital role in shedding light on the propagation of corrupted data and the potential failures that result, providing valuable insights for system design and sustainable operation.Item Digital Nudging to Reduce Product Returns in E-Commerce: Investigating Consumers' Intentions and Environmental Implications(2025-01-07) Schmitz, Julian; Selter, Jan-Lukas; Fota, Anne; Schramm-Klein, HannaProduct returns in online fashion shopping pose significant environmental challenges. However, the frequency of clothing returns has increased, potentially intensifying climate change. To address this issue, behavioral interventions, such as digital nudging, hold promise for guiding consumers toward more environmentally friendly choices. Conducting an online experiment with 352 participants, we aimed to investigate the influence of DNs, such as default, social norm, graphical, incentive, and framing on consumers’ pro-environmental and purchase-usage related behavior. Moreover, drawing on goal framing theory, a second online experiment with 246 participants examines the mediating influence of consumers’ goal motivations. Our findings demonstrate that digital nudging effectively encourage pro-environmental behavior in fashion online shopping. Additionally, the study reveals the critical role of hedonic, normative and gain goal frames in shaping pro-environmental attitudes.Item Unveiling Green Facades: Detecting Greenwashing Tendencies in Corporate Sustainability Reports(2025-01-07) Motz, Marvin; Uzun, Seyyid; Hariharan, Anuja; Weinhardt, ChristofGreenwashing poses a significant challenge to the fight against climate change by undermining trust in corporate sustainability claims. This study introduces the Greenwashing Tendency Score (GTS), an automated method designed to detect greenwashing tendencies in corporate sustainability reports. By leveraging sentiment and alignment analysis techniques in conjunction with ESG ratings, the GTS quantifies discrepancies between reported and actual sustainability performance. We applied our methodology to 36 DAX40 companies over the years 2020 to 2022. Our key findings reveal substantial variations in greenwashing tendencies among these companies, emphasizing the need for more transparent and reliable sustainability reporting. The GTS emerged as a scalable, reproducible, and objective tool that can aid investors, regulators, NGOs, and companies in identifying and addressing greenwashing practices. This research not only contributes to the sustainable finance literature but also provides actionable insights for stakeholders committed to fostering accountability and integrity in corporate sustainability communications.Item Leveraging Analytics to Understand Food Consumption and Waste in Achieving Personalized Nudging(2025-01-07) Lu, Yang; Li, Shuyang; Wang, Jing; Kanu, IfeyinwaManaging food waste is pivotal in advancing sustainable consumption practices. This study investigates how various factors such as food type, consumer spending, socio-economic characteristics, and demographics correlate with food waste patterns, utilizing data analytics and statistical analysis. Drawing on studies in green information systems (IS) and digital nudging, we propose three strategic nudging designs: pre-existing nudges based on food type characteristics, configurable nudges tailored to demographic and socio-economic profiles, and dynamic nudges responsive to evolving consumer behaviors. These interventions are designed to utilize behavioral insights to promote more sustainable consumer habits and present a novel methodology for substantially reducing food waste.Item Introduction to the Minitrack on Analytics and Intelligent Decision Support for Green IS and Sustainability Applications(2025-01-07) Wahbeh, Abdullah; Scharl, Arno; El-Gayar, Omar