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Making wiser decisions in organizations: insights from inter-processual self theory and transcendental anthropology
Get PDFCurrent approaches in decision making, influenced by rationalist and pragmatist paradigms, offer notable strengths but fail to adequately address human growth, moral depth, and relational dynamics. Rationalist models emphasize universal principles and cognitive processing, offering structured approaches at the expense of human relationality and cultural diversity. Pragmatist approaches focus on adaptability and social context and provide flexibility but their morally relativistic stance leads to ethical inconsistency. To address these gaps, we integrate Leonardo Polo’s transcendental personalist philosophy and the Inter-processual Self (IPS) Theory to redefine decision making as an opportunity for personal and relational growth. Grounded in anthropological insights, this framework prioritizes the human person as the center of moral action and decision making, fostering personal and relational growth through the transcendentals of personal love, knowledge, and freedom. We argue that this enriched perspective addresses critical limitations of existing models, enabling decision making to serve as a source of systemic wisdom and sustainable growth. By applying this framework to organizational contexts, we show how it enhances personal growth, and persons’ transcendent motivation for virtues involving inter-relational growth and wisdom. Our approach offers a holistic and transformative lens to rethink decision making as a catalyst for individual and collective flourishing, providing actionable insights to meet contemporary challenges in business and society
Determinants of carbon dioxide exposure for residents and staff of nursing homes: a field monitoring study in Spain
Get PDFProviding high air quality is crucial to the health and well-being of older people living in nursing homes. A measurement study was undertaken in 22 communal rooms of five nursing homes in Spain to investigate the effects of heating, ventilation, and air-conditioning (HVAC) systems, room characteristics, and occupant activities on the indoor air quality. The study included 196 periods of data collection (equivalent to 5282 measurements). To the authors’ knowledge, this is the first study of indoor air quality in Spanish nursing homes. The study found that mean CO2 concentrations were consistently below established standards, although notable peaks were evident due to specific activities. Natural and cross ventilation had a clear role in maintaining CO2 concentrations below recommended levels. The findings indicate that lower occupancy density may be required in rooms where high-CO2-generating activities take place, such as gym–physiotherapy rooms. The results showed that the older residents and staff were both more thermally comfortable at higher CO2 concentrations. This suggests that striking a balance between air quality and thermal comfort is necessary. The study provides useful insights for the design of ventilation systems and spatial layouts of nursing homes, which can achieve higher levels of indoor air quality and occupant well-being
A multi-model analysis of the decadal prediction skill for the North Atlantic ocean heat content
Get PDFDecadal predictions can skilfully forecast upper-ocean temperatures in many regions worldwide. The North Atlantic, in particular, shows high predictive skill for the ocean heat content (OHC). This multi-model study analyses eight CMIP6 climate models with comparable decadal prediction (Decadal Climate Prediction Project, DCPP) and historical (HIST) ensembles to document differences in North Atlantic (NA) upper-OHC skill and investigates the underlying causes. The decadal predictions consistently identify two main regions with high predictive capacity and added value of initialization: the Labrador Sea (LS) and the eastern North Atlantic. A region east of the Grand Banks (EGB) is also found to exhibit negative skill scores, with its extent and location varying widely across models, possibly due in part to observational uncertainties affecting both forecast verification and local initialization.
Special attention is given to the Labrador Sea and its surroundings, a region characterized by high inter-model spread in OHC prediction skill in both DCPP and HIST experiments. These differences hinder the identification of the relative contributions of external forcings and internal variability to local OHC predictability. To address this, we explore the relationship between the local OHC skill in the HIST ensemble and various mean-state properties in the Labrador Sea, revealing a strong link between the skill in those experiments and both the mean local surface fluxes and density stratification.
Benchmarking these mean-state properties against observations and reanalyses suggests that the multi-model mean likely offers the most realistic estimate of the forced signal, accounting for approximately 16 % of the total OHC variance in the Labrador Sea. These findings underscore the critical role of stratification and atmospheric forcing biases in shaping predictive skill and highlight the potential of multi-model ensembles to advance our understanding of decadal predictability
Interactions between subpolar and subtropical jet streams lead to extreme rainfall events over the north Indian subcontinent in June 2013 and July 2023
Get PDFNorth Indian Subcontinent (NIS) is prone to disastrous and life-threatening floods during the summer monsoon period primarily due to its close proximity with the Himalayan foothills. Indian Meteorological Department (IMD) reported that during June 13-19, 2013, the Uttarakhand state in north India experienced a cumulative total of 322 mm rainfall, a 847% weekly departure against the long-term average rainfall (1971-2020) of 34 mm. After a decade, another state in the same region, Himachal Pradesh, received an unprecedented 223 mm of rainfall in just 4 days, viz 7-11 July 2023, a 436% deviation from the cumulative climatological rainfall of 41.6 mm for 4 days (July 7-11). It is shown that the atmospheric water vapor is transported towards NIS by two monsoon low pressure systems during the June 2013 event. In contrast, during the July 2023 flood, the monsoon trough shifted southward, resulting in the moisture transport pathway predominantly over the northern Indian Ocean. In conjunction, it was shown through upper-level air tracing that southward movement of the subpolar jet stream creates a trough in the subtropical jet stream, which intrudes along the western boundary of NIS, leading to upper-level divergence. This pattern was observed in both flood events. By leveraging the mass-conserving nature and unique capability of a Lagrangian tracing model to track atmospheric water backward in time, our novel analysis of the 2023 flood reveals that two evaporative sources near Madagascar and the western Indian Ocean were key contributors, and inland evaporation played a comparatively lesser role as compared to the 2013 case. The Bay of Bengal served primarily as a vapor transport pathway rather than a direct moisture source for both events. This novel Lagrangian approach, which exposes separate drivers of extreme monsoon rainfall, upstream and at lead times of days-weeks, has the potential to be used more extensively and operationally
Examining global trends of satellite-derived water quality variables in shallow lakes
Get PDFLakes are a vital resource for freshwater supply and key sentinels of climate change, and it is projected that global warming will more persistently affect hydrology, nutrient cycling and biodiversity. In this context, shallow lakes are considered particularly sensitive to a changing environment and it is essential to acknowledge their water quality conditions and recent trends to guide effective water resource management and mitigation strategies. The European Space Agency Climate Change Initiative (ESA-CCI) offers globally consistent satellite observations of the Lakes Essential Climate Variable (ECV) including satellite products such as chlorophyll-a (Chl-a), turbidity and surface water temperature (LSWT) for over 2000 lakes during 1992-2020. From this dataset, we extracted a subset of 347 lakes with mean depth ≤ 3m distributed globally to investigate a long-term timeseries (2002-2020) for Chl-a and turbidity. Theil-Sen trend analysis showed that Chl-a did not change significantly in 33% of lakes, significantly increased in 45% and decreased in 22% of the lakes, while turbidity significantly increased in 60% and decreased in 17% of lakes. Most lakes with increasing Chl-a and turbidity trends were located in lowland areas, and had relatively large areas (surface area > 50 km2). Further analysis revealed that the majority of lakes showed a concurrent increase in both Chl-a (48%) and turbidity (50%) with LSWT, indicating the potential influence of climate warming on lake water quality. A structural equations model-based analysis used for modelling the interactions between climatic, socioeconomic features and water conditions overall showed that Chl-a and turbidity had a concurrent positive increase with population and gross regional product in most lakes. This finding suggests that the impact of human population growth in lake catchments represents an important factor driving pressures on the water quality of shallow lakes
Going beyond net zero: digital twins for achieving socio-ecological sustainability in the built environment
Get PDFPurpose – In this paper, we review and discuss the contemporary research on large-scale digital twins to identify the extent of socio-ecological and systems thinking in the context of sustainable built environment. We unpack the techno-rationalist view that relies on technology for problem-solving and argue that digital twins can facilitate a more nuanced assessment of sustainability challenges, including social equity, cultural preservation, and ecological resilience.
Design/methodology/approach – We conducted a content analysis-based review of studies drawing from Scopus and Web of Science databases using search strings to identify studies that develop complex, socio-ecologically aligned digital twins at neighborhood and city scales. We excluded studies that focused on a single building or a technology, as well as those that were situated in physical sciences, such as energy fuels, chemistry, or mathematics, to understand the extents of system complexity and interdisciplinary thinking, types of integrated data, digital twin maturity and underlying challenges for future research directions.
Findings – The findings illustrate the early stages of the digital twin development with respect to complex systems. Despite the relatively few studies reporting more mature and complex digital twin models, we illustrate how large-scale digital twin developments remain largely domain-specific, with projects yet to be seen as interventions within larger complex systems.
Originality/value – We contribute to the understanding of applying systems thinking in the development of socio-ecological urban digital twins. We identify key considerations and propose a preliminary framework for creating purpose-driven digital twins, aiming to foster more impactful questions regarding their purpose and value and to support interdisciplinary dialogue
Flexible estimation of parametric prospect models using hierarchical Bayesian methods.
Get PDFIn this paper, we present a flexible approach to estimating parametric cumulative Prospect Theory using hierarchical Bayesian methods. Bayesian methods allow us to include prior knowledge in estimation and heterogeneity in individual responses. The model employs a generalized parametric specification of the value function allowing each individual to be risk-seeking in low-stakes mixed prospects. In addition, it includes parameters accounting for varying levels of model noise across domains (gain, loss, and mixed) and several aspects of lottery design that can influence respondent behaviour. Our results indicate that enhancing value function flexibility leads to improved model performance. Our analysis reveals that choices within the gain domain tend to be more predictable. This implies that respondents find tasks in the gain domain cognitively less challenging in comparison to making choices within the loss and mixed domai