Future Uncertainty Research Articles

Scenario Planning in Pam Jaya For 2030 in Dealing with Future Uncertainties

Access to clean and safe drinking water is a fundamental human right and a cornerstone of public health and sustainable urban development. PAM JAYA has taken full operational control, assuming responsibility for providing and distributing clean water to DKI Jakarta. To meet its targets by 2030 and navigate future uncertainties for PAM JAYA, this research employs scenario planning to better identify driving forces, develop scenarios, and formulate strategies. This research addresses the key focal issue and research objectives regarding the extensive strategies PAM JAYA should adopt over the next six years to achieve its business targets. A qualitative research approach, utilizing semi-structured interviews, predicts multiple future scenarios. Seventeen driving forces were identified, leading to two critical uncertainties: Law Enforcement and Tariff Adjustment. Four scenarios emerged: Harmony Era, Strict Era, Lax Prosperity Era, and Injustice Era. Exploring the implications and strategic options for each scenario equips PAM JAYA to manage future uncertainties. Early warning signals are produced for each scenario, serving as leading indicators to guide PAM JAYA’s direction.

Adaptive Control Strategies for Enhanced Integration of Solar Power in Smart Grids Using Reinforcement Learning

Integrating solar power into smart grids is challenging because of the variable nature of solar energy. This study focuses on implementing reinforcement learning (RL) using a Deep Q-Network algorithm to enhance the stability and efficiency of a grid. A custom environment was designed using OpenAI Gym, in which real-time simulation of grid operations was conducted using real-time data on solar power, weather, and other grid metrics. The trained RL agent exhibited high predictability in optimally distributing the load and managing the battery storage, with R-squared = 0.886, mean average error = 1,173,046.55 Wh, and root mean squared error = 2,075,515.10 Wh. The model effectively captured the seasonality and daily variations in solar power generation. Forecasting using the proposed model provides insights into future energy trends and uncertainties. The reward function will be further refined and scaled for more complex energy systems by incorporating additional variables and hybrid approaches. This study highlights the potential of RL-based adaptive control strategies for developing more efficient and resilient integration of renewable energy sources into smart grids.

A Systematic Review of the Evolution of the Concept of Resilience in the Construction Industry

Despite the growing importance of resilience in the construction sector, the existing literature often focuses on specific systems or functions without integrating a holistic view of resilience. Hence, there is a pressing need for comprehensive research that synthesizes these dimensions to provide a clearer framework for resilience in the construction industry. To find the inherent patterns and trends of resilience, we carried out research from the perspective of three elements defining resilience (the subject of resilience, the influencing factors, and the subject’s ability). In this systematic review, 70 articles were rigorously handpicked from Web of Science, Scopus, and authoritative journals and divided into 6 major categories and 24 subcategories for quantitative and temporal analyses. The evolution of resilience in the construction industry is investigated in this review, shifting from specific systems facing defined impacts to addressing the complexities of diverse and unpredictable disruptions within VUCA (volatile, uncertain, complex, and ambiguous) environments. As Industry 4.0 and digital transformation progress, the significance of functional resilience across various system levels becomes apparent, necessitating a reconstitution into structural, operational, and supply chain resilience. This study encourages the use of advanced methodologies like big data, AI, and high-level architecture (HLA) federated simulations to predict disruptions and optimize resilience strategies, thus providing a robust foundation for handling future uncertainties.

How Plans Prepare for Future Uncertainty: Integrating Land Change Modeling and the Plan Integration for Resilience Scorecard™

How Plans Prepare for Future Uncertainty: Integrating Land Change Modeling and the Plan Integration for Resilience Scorecard™

Leveraging Natural Ecosystems to Reoptimize Education and Training for Great Power Competition in the Air Force Medical Service.

Organizations today are complex, hyperdimensional, and continuously changing in response to the environment. Over the past decade, the Military Health System has seen continuous organizational change to transform healthcare delivery, and the Air Force Medical Service (AFMS) is currently transitioning to an Air Force Medical Command (AFMEDCOM) structure to best prepare for Great Power Competition and other challenges ahead. The current state of the enterprise involves decision making, resourcing, and execution of education and training that is largely decentralized in nature. To support these efforts, in February 2024, a team of diverse AFMS stakeholders gathered in Washington, D.C. to examine the future of medical education and training for the U.S. Air Force in a new way: through systems theory and ecosystem mapping. This ecosystem approach enables development of an organizational structure and process for change that considers how all stakeholders relate, what external factors threaten the desired transformation, and how the resulting enterprise could become more resilient with future uncertainty and change. This paper discusses the theory behind the ecosystem approach and how it was used to develop a transformed model for the AFMS to organize its education and training. Additionally, a dialogue is presented on how this unique methodology to understanding stakeholder relationships can be leveraged in the re-optimization efforts for Great Power Competition.

The Materiality of Absence in Paul Auster’s Poetry and Fiction

ABSTRACT Through mapping the blank landscapes and stones in Paul Auster’s writing, and through the employment of a framework that reads Auster alongside twenty-first-century theories of minimalist aesthetics, this article demonstrates how his early poetry and later fiction frequently explore a politics of erasure. The intersection of an austere literary style with contextually flat representations of crumbling stones, work, and conspicuously omitted power structures affords a previously unacknowledged environmental context underpinning Auster’s thinking. By recalling his early poetry and later novels that dramatise comparable scenarios of labour and loss under the shadow of external threat, I explore how frequent representations of erasure echo environmental and cultural anxieties related to memory and future uncertainty.

ESG-Driven Investment Decisions in Photovoltaic Projects

As global climate change intensifies and environmental awareness increases, investing in renewable energy has become a primary economic and social development priority. Photovoltaic (PV) projects, as a clean and sustainable energy technology, have garnered significant attention due to their notable environmental and economic benefits. However, traditional investment evaluation methods such as net present value (NPV) analysis fail to adequately capture the flexibility and future uncertainties inherent in PV project investments. This paper presents a case study analysis proposing a delay option model that incorporates environmental, social, and governance (ESG) factors, providing a more scientific and flexible investment decision framework for PV projects. The case study results indicate that considering ESG factors significantly enhances the investment value of PV projects. This model not only provides comprehensive support for PV project investment decisions but also underscores the importance of establishing stringent carbon trading markets and policy incentive mechanisms to promote the widespread adoption and sustainable development of renewable energy projects.

Research on the Socio-Spatial Resilience Evaluation and Evolution of the Central Area of Beijing in Transitional China

In recent decades, the increasing threats of global climate change, natural disasters, and epidemics have brought extensive attention to resilience theory. However, most studies focus on the physical aspects of cities, overlooking the significance of the social perspective. This study addresses this gap by using social areas as the core spatial unit for analysis. By constructing a scientific indicator system and employing the set pair analysis method, this study comprehensively evaluates the multidimensional resilience levels of Beijing’s central area during its transitional period (1990–2020). The findings reveal that socio-spatial divisions, which emphasize the network structure of social relations and the dynamic changes in social spaces, are more suitable than traditional administrative divisions as fundamental units for resilience assessment. During Beijing’s transitional period, the comprehensive resilience of the central area and all social areas steadily increased, although social capital resilience faced the challenges of loss and slow recovery. Social areas with a unique internal connection, such as those based on ethnicity, exhibited more positive social capital resilience development. Additionally, social areas with lower population diversity and greater homogeneity tended to have higher comprehensive resilience and a more positive trend in social capital resilience development, whereas highly heterogeneous social areas faced significant constraints in resilience development. These findings may provide valuable insights for cities and communities to enhance their capacity to address future uncertainties and assist policymakers in making informed governance decisions.

Sequential investment decisions for mining projects using compound multiple volatility real options approach

Managers evaluating investment decisions in mining projects have reported using the net present value approach (NPV). However, NPV has the drawback of collapsing variations from uncertainties in future project cash flows into a fixed expected project value today. Ignoring future uncertainties and contingencies can lead managers to make incorrect up-front binary decisions, such as investing in or abandoning the project now. The real options analysis approach (ROA) instead captures variations from uncertainties as volatilities in project value and allows flexibility in investment decisions to be contingent on information as it is revealed. Managers we consulted agreed that ROA is superior to NPV in principle, but too complex to apply in practice. The advanced mathematics and restrictive assumptions required by analytical ROAs make them especially impractical for real-world projects exposed to multiple uncertainties. Furthermore, real-world projects are often multistage and involve valuing a compound option, which is an option on an underlying option, for sequential investment decisions. Extant numerical compound ROAs have been applied to such projects but suffer from various drawbacks. Amongst other issues, they combine variations from multiple uncertainties into a consolidated volatility of project value. This conceals the impact of each source of uncertainty, resulting in inaccurate project valuation and incorrect investment decisions. We present an innovative compound multiple volatility real options approach (C-MVR) to value a multistage project while accommodating separate volatilities of project value arising from multiple uncertainties for making sequential investment decisions. The resultant value is termed the compound enhanced net present value. Implementing C-MVR for a real coal mining project demonstrates how other ROAs can be seen as inaccurate simplifications that produce erroneous investment decisions. C-MVR provides a rigorous and versatile approach that can be applied to many investment decisions across various industries.

The Radical Instability of the Present

This article uses Muhammad Khudayyir's novel-memoir Basrayatha as a loose theoretical framework to explore the ramifications of a not-yet-built infrastructure, tracing how late Ottoman officials, intellectuals, and engineers thought about the not-yet-built Baghdad Railway and the land it was meant to transform. Examining how railway boosters, Ottoman officials, and engineers located the region's “truth” and future in a lost past, the article argues that making this connection depended on cultivating material and discursive absence in the “ruined” present. The article highlights how practical techniques for making place into the kind of “space” where homogenous time could march forward coexisted with grandiose visions of future prosperity inspired both by the distant past and by the present of places like Egypt. In contrast to analyses that have emphasized the uncertainty of past and/or future, this article argues that the present was the problem because it was fundamentally unknowable—and that this very unknowability allowed railway advocates to absent the extended present of ruin from an idea of the truth of Iraq, instead drawing a direct line between past and future prosperity.

Hygrothermal resilience of typical lightweight steel-framed wall assemblies in hot-humid areas under future climate uncertainty

Ensuring the hygrothermal performance of lightweight steel-framed (LSF) wall assemblies is critical for the sustainability of LSF buildings in hot-humid regions; however, climate change poses new challenges. Therefore, this study aimed to bridge the gap in understanding the characteristics of hygrothermal load changes and the hygrothermal resilience of different LSF wall assemblies. Future climate data for each decade of this century (from 2030 to 2090), under various carbon emission scenarios, were generated based on a typical meteorological year (TMY) for hot-humid areas to evaluate the impact of climate change on hygrothermal loads. The hygrothermal resilience of four typical LSF wall assemblies, with either ventilated rainscreen cladding or face-sealed stucco cladding, with or without external insulation, was evaluated through simulation and comparative analysis. The results indicated that the thermal load would increase with increasing carbon emissions and over time, with the annual average external temperature peaking at 25.8 °C by the end of this century. The frequency of months with a high or critical moisture load would increase, although the moisture load may fluctuate across scenarios and years. Consequently, the cooling and dehumidification loads may increase by 52–60 % and 40–88 %, respectively. The hygrothermal risk within the walls may increase, with maximum increases of 2.8–8.0 % in the annual average relative humidity, 2.7–3.0 °C in the annual average temperature, and 10–35 % in the wetness duration. However, the impacts could be reduced by using ventilated rainscreens and external insulation, with further precautions needed to mitigate the increasing hygrothermal risk in areas with thermal bridges and rainwater leakage, as well as at the outer interface of the external insulation. These findings could provide a reference for the design of LSF buildings adapted to climate change in hot-humid areas.

COVID-19’s Psychological Threats and Future Career Anxiety among University Students

The COVID-19 pandemic brought different intolerable and uncomfortable situations that ruined the students' academic performance, career opportunities, and social lives through depression, anxiety, fear, uncertainty, and mental illness. In this study, we examined the psychological threats of the COVID-19 among Egypt’s public-sector university students. We employed quantitative methods in this study and used a questionnaire to collect cross-sectional data. The Structural Equation Modeling (SEM) results show that Fear of COVID-19 (FoC) has a positive effect of on Depression from COVID-19 (DfC), Future Career Anxiety (FCA) and Uncertainty of COVID-19 (UoC). In addition, DfC and UoC have positive effects on FCA. Finally, DfC and UoC positively mediate the association between FoC and FCA. This study's findings help policymakers and university authorities shape policies to reduce Egypt’s public sector university students ‘psychological problems due to the COVID-19 pandemic. Moreover, this study’s findings assist with the adjustments caused by the complex and rapidly changing pandemic situation.

How universities study the future: A critical view

Despite recent rapid advances in technology, a skilled workforce continues to play the most important role in the development of national economies. People’s roles as operators, managers, or innovators are rapidly evolving to meet changing social needs. Traditionally, universities and higher education (HE) systems have been responsible for supplying the required knowledge and human resources. However, in the modern world, the nature of these needs is constantly changing, and uncertainties are dominating the socioeconomic future. To address this need, many researchers have attempted to explore how HE can cope with future uncertainties and evolve as a social system, yet there is no comprehensive analysis of methodological guidelines that provide insights into how to develop HE future scenarios. To fill this gap, this research takes a deep literature review approach, conducted by the authors, to examine published and peer-reviewed studies in the area of HE scenario planning over the decade from January 2010 to 2023. This study investigates the exploration of plausible futures by research teams at three levels - global/international, regional/national, and local/university. The findings show that there is a lack of foresight knowledge, which increases the risk of failure exponentially over time. To address these shortcomings, this study proposes a framework for future studies, including environmental factors that will impact higher education and methodological recommendations to equip researchers for the challenges ahead. It also emphasizes the need to appreciate the complexity of HE systems and the role of wildcards and weak signals in shaping future disruptive trends. This research offers valuable guidance to researchers seeking to engage in scenario development for HE in the face of uncertainty.

Indonesia’s social protection system: the relevance of informal social protection to strengthen adaptation to climate change

ABSTRACT Social protection is praised as a multipurpose instrument to protect the most vulnerable people and ensure socioeconomic development. Recently, this approach has also been recognized by climate scientists. Over the past few decades, Indonesia, a highly exposed and vulnerable country facing climate change, has increased its efforts to protect all marginalized and vulnerable groups. However, the high uncertainty of social and economic impacts triggered by climate and environmental change increases pressure on the social protection system, leading to a rising need for deeper and broader coverage, especially among the most vulnerable people. This paper argues that vulnerable groups have built their own systems to be socially protected, which we refer to as informal social protection (ISP). Given that there is little reference to these particular structures in the literature on social protection, this study aims to explore their relevance and potential challenges. Jakarta, a highly urbanized and vulnerable city, was used as a case study. The city is simultaneously challenged by the increasingly adverse impacts of climate change. Gaps in formal social protection (FSP) will be analysed using qualitative and quantitative data to assess how and to what extent the most vulnerable groups are protected and whether ISP structures can fill the identified gaps. The results show that ISP can function as a solution to protect marginalized and vulnerable groups; however, more information is needed to ensure security considering long-term developments and increased future uncertainties. HIGHLIGHTS OF THIS STUDY FSP coverage in Indonesia still has gaps due to unregistered target groups, such as the missing middle population and informal sector workers. The uncertainty of the social and economic impacts caused by climate change increases pressure on the social protection system, leading to a greater need for broader coverage. ISP provides vulnerable groups with flexibility, local specificity, mutual benefits and reciprocity, collective decision-making, social cohesion, and trust. ISP involves community-based adaptation and support from NGOs to enhance ISP and make it more adaptive. ISP supports vulnerable groups affected by the unintended consequences of adaptation measures implemented by the government.

Bootstrap-after-bootstrap for autoregressive models: an application to Indonesian value of export oil and gas

This research focuses on predicting the value of oil and gas exports in Indonesia, employing a hybrid methodology that combines autoregressive models and a bootstrap approach. Specifically, this research applies the bootstrap-after-bootstrap approach to showcase its effectiveness in improving the accuracy of parameter estimates. Analysis results indicate that the autoregressive model with an order of p=2 minimizes the AIC, BIC, and HQ values, yielding AIC=9.833775, BIC=10.03125, and HQ=9.883440, respectively. Consequently, the AR(2) model emerges as the optimal choice for predicting Indonesia's export value of oil and gas. This research utilizes varying numbers of bootstrap replications (B=100, 250, 500, 1000, and 10000) to assess the impact on prediction intervals. Prediction intervals exhibit less smoothness for B=100 and B=250, whereas B=500 and B=1000 result in a considerably smoother pattern. The highest level of smoothness is achieved for B=10000. The findings underscore that bootstrap-after-bootstrap prediction intervals provide the most accurate and conservative assessment of future uncertainty. Moreover, predictive analysis for the upcoming five periods indicates a projected decline in the export value of oil and gas in Indonesia. Overall, this research demonstrates the efficacy of the bootstrap-after-bootstrap approach in enhancing the precision of predictions and providing robust insights into future uncertainties surrounding Indonesia's oil and gas export market.

Climate stress testing for water systems: Review and guide for applications

AbstractTogether with other “bottom‐up” methods, climate stress testing is becoming a prominent approach for climate change impact assessment of water systems. Compared with traditional approaches, stress testing is: (i) more focused on exploring the vulnerabilities of the system at hand; (ii) potentially more inclusive, being amenable to stakeholder involvement and (iii) well suited to identify robust policy options that better account for the deep uncertainty associated with multiple plausible futures. Stress testing is rapidly evolving and giving rise to new techniques and concepts, but few articles provide an accessible overview that can serve as an introduction to the field. Here, we review the underlying principles and concepts of climate stress testing, providing a guide to the main decisions involved in practical application. Topics include selection of stressors, characterizing and exploring the exposure space and data generation including the use of stochastic data. In a complex world where water decisions are made in the context of wider socio‐ecological systems, stress testing and other bottom‐up methods can support decisions that are not only robust to future uncertainty but also regarded as legitimate by affected communities.This article is categorized under: Engineering Water > Sustainable Engineering of Water Science of Water > Water and Environmental Change Water and Life > Stresses and Pressures on Ecosystems

Resistance to Change: Human Resources Issues in the Implementation of Industry 4.0 Technology

This research explores resistance to change in implementing Sustainable Development Goals (SDGs) through Industry 4.0 technology in Human Resources (HR) management. A review of 15 articles across sectors such as finance, education, and business reveals that resistance stems from factors like insufficient technological skills, fear of job insecurity, cultural reluctance, and inadequate support from senior management. These barriers hinder organizational progress, stifle innovation, and diminish competitiveness in the market. HR management must adopt a comprehensive approach involving skills development, fostering an innovation-friendly culture, and clear communication during change processes. Key challenges include managerial reluctance, future uncertainties, and employee concerns about career impacts. Effective strategies to combat resistance encompass transparent communication, employee involvement in decision-making, skills enhancement through training, and incentivizing cooperation. By comprehending resistance factors, their ramifications, and employing targeted strategies, organizations can adeptly navigate technological transformations, thereby ensuring successful integration of Industry 4.0 technologies aligned with SDGs.

Forecasting daily total pollen concentrations on a global scale.

There is evidence that global anthropogenic climate change may be impacting floral phenology and the temporal and spatial characteristics of aero-allergenic pollen. Given the extent of current and future climate uncertainty, there is a need to strengthen predictive pollen forecasts. The study aims to use CatBoost (CB) and deep learning (DL) models for predicting the daily total pollen concentration up to 14 days in advance for 23 cities, covering all five continents. The model includes the projected environmental parameters, recent concentrations (1, 2 and 4 weeks), and the past environmental explanatory variables, and their future values. The best pollen forecasts include Mexico City (R2(DL_7) ≈ .7), and Santiago (R2(DL_7) ≈ .8) for the 7th forecast day, respectively; while the weakest pollen forecasts are made for Brisbane (R2(DL_7) ≈ .4) and Seoul (R2(DL_7) ≈ .1) for the 7th forecast day. The global order of the five most important environmental variables in determining the daily total pollen concentrations is, in decreasing order: the past daily total pollen concentration, future 2 m temperature, past 2 m temperature, past soil temperature in 28-100 cm depth, and past soil temperature in 0-7 cm depth. City-related clusters of the most similar distribution of feature importance values of the environmental variables only slightly change on consecutive forecast days for Caxias do Sul, Cape Town, Brisbane, and Mexico City, while they often change for Sydney, Santiago, and Busan. This new knowledge of the ecological relationships of the most remarkable variables importance for pollen forecast models according to clusters, cities and forecast days is important for developing and improving the accuracy of airborne pollen forecasts.

Building towards organisational resilience and complexity leadership: a case study of impacts and changes in a Dutch blood establishment during COVID-19

ObjectivesThis study examined how one large blood-related establishment coped and adapted during the first 1.5 years of the pandemic by evaluating the impacts and changes on its resources, communication, collaborations,...

Qualifying uncertainty of precipitation projections over China: mitigating uncertainty with emergent constraints

Predicting future mean precipitation poses significant challenges due to uncertainties among climate models, complicating water resource management. In this study, we introduce a novel methodology to mitigate uncertainty in future mean precipitation projections over China on a grid-by-grid basis. By constraining precipitation parameters of the Gamma distribution, we establish emergent constraints on parameters, revealing significant correlations between historical and future simulations. Our analysis spans the periods 2040–2069 and 2070–2099 under low-to-moderate and high emission scenarios. We observe reductions in uncertainty across most regions of China, with constrained mean precipitation indicating increases in monsoon regions and decreases in non-monsoon zones relative to raw projections. Notably, the observed 30%–40% increase in mean precipitation for the whole of China underscores the efficacy of our methodology. These observationally constrained results provide valuable insights into current precipitation projections, offering actionable information for water resource planning and climate adaptation strategies amidst future uncertainties.