Post-pandemic tourist hotels confront simultaneous demand contraction and cost escalation. Drawing on value-chain theory and service-sector information systems (IS) literature, the authors propose a data-driven cost-control framework that links front-desk, housekeeping, food-and-beverage, and back-office workflows. A multi-input/multi-output panel was first constructed from listed-hotel annual reports and on-site surveys; cost-efficiency and driver weights were then simultaneously estimated by Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP). Relative efficiency scores reveal that 32% of properties operate under increasing returns to scale, while cross-departmental collaboration contributes 1.7-times more to total-factor productivity than isolated technological investment. Hidden resource waste—undetectable under traditional accounting—is quantified and traced to three inter-process hand-offs, providing IS-based improvement paths.

This study examines the persistent global problem of time and cost overruns in hydropower projects, with emphasis on India. Although hydropower is central to renewable energy strategies and grid stability, project implementation is often hindered by major delays and budget escalations. Since 2000, international data indicate average cost overruns above 30% and schedule delays over 18% (Ansar et al., 2014). The research identifies the root causes of these overruns, evaluates their prevalence in India, reviews case studies, compares national and global trends, and analyses factors such as regulatory complexity, geological challenges, technological integration, and managerial practices. It also highlights best practices to improve project outcomes. Both technical and non-technical factors drive overruns. Technical contributors include complex engineering demands, construction inefficiencies, procurement delays, contractor underperformance, and frequent rework (Debnath, 2025). Nontechnical drivers include environmental and social issues, lengthy approval processes, community opposition, political instability, natural disasters, funding constraints, and global disruptions (Debnath, 2025). Cost escalations stem from direct factors—rising material prices, design changes, unforeseen site conditions, and inaccurate estimates—and indirect ones such as inflation, interest burdens, exchange rate volatility, increased overheads, and contractual disputes (Flyvbjerg, 2006). Case studies from India and abroad show varied causes, including difficult geology, social resistance, land acquisition challenges, financial gaps, and weaknesses in planning and design (World Bank, 2020). These overruns affect not only project viability but also economic development, environmental sustainability, and societal welfare. Addressing them requires comprehensive mitigation across all project stages: rigorous planning, strong risk management, effective contract administration, strict construction oversight, and early stakeholder engagement. Adoption of technologies like BIM and digital project management tools can further enhance efficiency (International Hydropower Association, 2021). Sustainable and resilient hydropower development depends on improved governance, technology uptake, and supportive policy frameworks (Central Electricity Authority, 2022).

Background: The oil and gas industry frequently face budget overrun issues. Project costs increase, stakeholders are dissatisfied, and overall performance suffers. To avoid this, it is important to find effective methods for preventing or mitigating the risk of cost overruns. Aim: The objective of the study is to analyze the relationship between resource-related factors, such as labor, equipment, and material factors, and cost overruns in the oil and gas projects in Kazakhstan. Materials and methods: A structured survey consisting of 15 resource-related risk factors was distributed to experienced professionals working in the oil and gas sector. A total of 172 valid responses were gathered. The data were evaluated using descriptive statistics, econometric methods and partial-least squares structural equation modeling (PLS-SEM) to assess reliability, validity, causal relationships, and regressed variables. Results: The empirical analysis shows that labor-related risks, including labor shortages, low productivity, and labor incompetence, have the most substantial and statistically significant impact on cost overruns. Material-related and equipment-related risks demonstrate a moderate yet meaningful effect. All three latent constructs exhibit internal consistency and convergent validity. Furthermore, change orders and financial difficulties are also strong contributors to cost escalations. Conclusion: The study concludes that effective resource planning is critical for minimizing cost overruns and ensuring the successful execution of oil and gas projects in Kazakhstan. Improving workforce competency, enhancing material supply reliability, and efficiently providing physical resources are recommended practices for overall project management body of knowledge.

Design changes are among the most common factors affecting construction project performance, particularly in terms of cost and schedule. This study aims to analyze the impact of design changes on project cost and duration in several luxury residential construction projects located in South Jakarta. Data were collected through questionnaires distributed to 30 respondents consisting of contractors, consultants, and site supervisors involved in these projects. The collected data were analyzed using descriptive statistics, correlation analysis, and simple linear regression with SPSS software. The results of the analysis show that design changes have a moderate and statistically significant positive relationship with project duration (r = 0.486, Sig. = 0.006), indicating that more frequent or extensive design revisions tend to extend project completion time. Conversely, the correlation between design changes and project cost was found to be weak and statistically insignificant (r = 0.212, Sig. = 0.261), implying that design modifications do not significantly contribute to cost escalation in these projects. The regression equation obtained for project duration is Y = 13.591 + 0.465X, indicating that each unit increase in design changes adds 0.465 units of time to project completion. These findings suggest that while design changes are inevitable in high-end residential projects, their time impact is more pronounced than their cost impact. Therefore, effective design coordination, early design finalization, and structured change management are essential to mitigate schedule delays and enhance project performance.

Interhospital transfer (IHT) is essential for providing timely access to specialist surgical care, particularly in geographically dispersed health systems yet is consistently associated with increased morbidity, mortality, and healthcare resource use. This review synthesises contemporary evidence on IHT, outlining key challenges and proposed strategies for improvement. A literature search of MEDLINE and PubMed was conducted using predefined search terms, limited to English-language articles published within the past 10 years and involving adults aged >16 years. Relevant studies examining IHT processes, outcomes, delays and mitigation strategies were reviewed and synthesised narratively. IHT frequently occurs due to deficits in local resources, acuity capability, or specialist expertise. Across studies, transferred surgical patients experience longer hospital stays, higher costs, and significantly increased mortality, with up to threefold higher in-hospital mortality compared with directly admitted patients. Major contributors to adverse outcomes include systemic delays, inadequate communication and handover, limited specialist availability in regional hospitals, and logistical constraints. Time-critical subspecialities are particularly vulnerable to transfer-related delays, which strongly predict mortality and cost escalation. Up to 20-30% of transfers may be clinically unnecessary. Proposed mitigation strategies include implementation of standardised transfer pathways, improved communication systems, telemedicine utilisation, and targeted enhancement of regional surgical capacity. IHT remains indispensable for accessing specialist emergency surgical care but is consistently associated with delayed treatment and worse outcomes. Addressing modifiable system factors is essential to improving safety and efficiency. These findings provide essential context for ongoing analyses of IHT practices and associated healthcare costs in regional Australia.

This study undertakes a systematic exploration and computational modeling of the intricate dynamics shaping the convergence and equilibrium between traditional IT governance frameworks and the emergent paradigms of cloud governance. It posits that the lack of harmonization across these domains heightens organizational exposure to critical risks—including security breaches, regulatory non-compliance, cost escalation, operational disruptions, and erosion of stakeholder trust—which may ultimately culminate in financial losses, legal liabilities, and impeded innovation. Drawing upon a mixed-methods research design that synthesizes qualitative literature analysis with advanced risk modeling and a demonstrative workflow, the study formulates a comprehensive risk assessment framework that addresses governance fragmentation, cybersecurity vulnerabilities, and misalignment with enterprise objectives. The findings underscore that cloud governance introduces novel oversight mechanisms which, when effectively integrated with conventional IT governance, facilitate an enterprise-wide governance posture and reinforce organizational agility. Beyond mitigating risks, the analysis reveals that cloud adoption can function as a catalyst for governance innovation by enabling scalable architectures, operational adaptability, and enhanced cost efficiency. The proposed risk modeling framework, complemented by a structured methodology for governance integration, yields risk-informed strategic insights to guide organizations in reconciling IT and cloud paradigms—thereby advancing operational resilience and sustaining long-term competitive advantage in cloud-intensive environments.

Construction price indices play a critical role in shaping construction activity and determining the economic success of building projects in Germany, where they can serve as central inputs to cost planning and to updating trade-level project budgets over the planning and construction horizon. This paper develops a forecasting framework for 35 sub-construction price indices for office buildings, providing granular inputs for cost escalation and risk assessment. We employ regularized vector autoregressive models with exogenous variables (VARX) implemented via the BigVAR package and estimate them in a model-vintage design for an unbalanced panel. These high-dimensional models are benchmarked against compact VARX and vector error-correction models (VECM) that jointly forecast each target index with a small macroeconomic block consisting of the gross domestic product (GDP) and the three-month interbank rate. Candidate specifications are evaluated using mean absolute percentage error (MAPE) and out-of-sample root mean square error (RMSE), and the final forecasting model for each index is selected based on ex post MAPE. The results show that regularized VARX models capture dynamic interdependencies among the sub-indices and, for most series, outperform the VARX and VECM benchmarks. The resulting forecasts provide practitioners with trade-specific escalation factors that can support budgeting, contract design, and the mitigation of cost risk in office-building projects.

This research paper explores the digital transformation of pricing strategies within construction development companies, proposing a paradigm shift from static, reactive models to dynamic, data-driven approaches. The study rigorously analyzes the limitations of traditional pricing methods, specifically the "cost-plus" and market-based strategies, in the context of high market volatility and information asymmetry typical of the real estate sector. The primary objective is to synthesize the application of Building Information Modeling (BIM), Big Data analytics, and Artificial Intelligence (AI) into a unified strategic framework. The research identifies that 5D BIM technology fundamentally enhances the accuracy of the "cost floor" by automating quantity take-offs, while Machine Learning (ML) algorithms provide predictive capabilities for material cost escalation. Furthermore, the evolution of the Hedonic Price Model (HPM) into Automated Valuation Models (AVM) utilizing Big Data is examined as a critical tool for determining the "price ceiling" based on perceived customer value. A central contribution of this study is the development of a conceptual architecture for a dynamic pricing system. This system integrates internal cost data with external market signals in real-time, utilizing optimization algorithms to maximize profitability between the cost floor and market ceiling. The research demonstrates that the integration of digital tools forms a comprehensive pricing architecture in which Pmin is derived from cost optimization technologies, Pmax is calculated through market analytics, and the final optimal price is determined through dynamic optimization algorithms. The paper also presents a case study of the Ukrainian real estate market, highlighting a strategic bifurcation between "Deep Tech" approaches focused on cost optimization and "Client-Facing Tech" focused on value creation. The study concludes that the optimal strategy requires the convergence of these approaches. Recommendations are provided for implementing an integrated digital tools that leverages AI to ensure transparency and trust while employing dynamic pricing engines for commercial efficiency.

Purpose We develop an uncertainty-aware, Explainable Artificial Intelligence (XAI)-enabled probabilistic framework to predict and explain delay-driven cost risk in construction, accounting for time-varying exposures driven by supply reliability, regulatory cadence and labor stability. Design/methodology/approach Using data from 46 US high-rise projects, we estimate a hierarchical competing-risks Weibull survival model with time-varying covariates and project-level random effects via HMC/NUTS. We link posterior predictive delay exceedance to a stochastic cost overrun layer and integrate XAI through posterior-aware SHAP (global and local importances with 95% credible bands), interaction effects, and counterfactual recourse. Decision-curve analysis quantifies net benefit across operational trigger thresholds. Findings Relative to non-XAI baselines, the approach improves time-to-event discrimination and calibration (e.g. median C-index 0.81 vs 0.73; IBS reduction −0.027; both with 95% credible intervals). Global explanations identify supply reliability as the dominant driver, with a positive supply-regulation interaction. Scenario analyses show median reductions of 11–20% in cost overruns under feasible interventions (e.g. reliability uplift and buffer policies), with uncertainty reported. Practical implications The suggested framework provides a clear and interpretable information to the project managers both locally and globally. It recognizes the actual counterfactual activities that are associated with procurement scheduling and vertical logistics, it determines the decision-thresholds whose anticipated benefits are clearly outlined. All these characteristics allow more active, transparent and evidence-based management of complex project risks. Originality/value As far as we can determine, this paper is the first attempt to integrate hierarchical competing-risks Weibull modeling with uncertainty-aware explainable AI and a structural interdependence between schedule delay and cost escalation in a high-rise construction. The result is an interpretable, more practically oriented decision-support system that converts the findings of the analysis into practical directions to managers.

Housing development is a long-term investment that requires careful planning to avoid financial risks and unexpected cost escalation. This study highlights the importance of implementing Cost-Benefit Analysis (CBA) as a comprehensive assessment tool for evaluating the feasibility of residential construction projects. Using a descriptive qualitative approach, data were collected through literature review and documentation, and analyzed using key feasibility indicators such as Net Present Value (NPV), Internal Rate of Return (IRR), Benefit Cost Ratio (BCR), Payback Period (PP), and Life Cycle Cost (LCC). The findings show that applying CBA provides a holistic understanding of the economic, social, and environmental benefits associated with the project, while also helping to minimize risks and optimize long-term investment value. Therefore, CBA serves as an essential instrument for ensuring that housing development projects are implemented effectively, efficiently, and sustainably.

Contract variations are a common phenomenon in building projects, often leading to time overruns, cost escalations, and dissatisfaction among stakeholders. Despite numerous studies on variation orders, there is limited empirical evidence on their effects on building project delivery within the Nigerian context. This study assessed the effects of contract variations on building construction delivery, with a view to identifying critical causative factors, their impacts on performance, and possible mitigation strategies. A quantitative research approach was adopted using a structured questionnaire administered to 100 construction professionals comprising clients, consultants, and contractors, with a response rate of 92%. Descriptive and inferential analyses were conducted using Frequency, Mean Item Score (MIS), and Spearman’s rho correlation. The findings revealed that the most significant factors responsible for contract variations were consultants’ lack of experience, design complexity, and additional client instructions (MIS = 5.00 each). The major effects identified included time overruns and end-user dissatisfaction (MIS = 5.00), while loss of efficiency due to work interruption (MIS = 4.84) was the most critical impact on project performance. A strong positive correlation was observed between consultant experience and time overrun, indicating a direct relationship between technical expertise and project timelines. The study further established that loss of profit (MIS = 4.26) and reduced organisational performance were major consequences at the organisational level. Key mitigation strategies include effective communication, proper site investigation, comprehensive design documentation, and interdisciplinary collaboration. The study concludes that effective management of contract variations can significantly enhance project delivery outcomes, cost performance, and client satisfaction in building projects.

Contract variations are a common phenomenon in building projects, often leading to time overruns, cost escalations, and dissatisfaction among stakeholders. Despite numerous studies on variation orders, there is limited empirical evidence on their effects on building project delivery within the Nigerian context. This study assessed the effects of contract variations on building construction delivery, with a view to identifying critical causative factors, their impacts on performance, and possible mitigation strategies. A quantitative research approach was adopted using a structured questionnaire administered to 100 construction professionals comprising clients, consultants, and contractors, with a response rate of 92%. Descriptive and inferential analyses were conducted using Frequency, Mean Item Score (MIS), and Spearman’s rho correlation. The findings revealed that the most significant factors responsible for contract variations were consultants’ lack of experience, design complexity, and additional client instructions (MIS = 5.00 each). The major effects identified included time overruns and end-user dissatisfaction (MIS = 5.00), while loss of efficiency due to work interruption (MIS = 4.84) was the most critical impact on project performance. A strong positive correlation was observed between consultant experience and time overrun, indicating a direct relationship between technical expertise and project timelines. The study further established that loss of profit (MIS = 4.26) and reduced organisational performance were major consequences at the organisational level. Key mitigation strategies include effective communication, proper site investigation, comprehensive design documentation, and interdisciplinary collaboration. The study concludes that effective management of contract variations can significantly enhance project delivery outcomes, cost performance, and client satisfaction in building projects.

U.S. higher education faces mounting existential pressures—enrollment declines, cost escalation, political skepticism, and administrative managerialism that prioritizes short-term institutional survival over long-term scholarly mission. Despite widespread critique, business management faculty have largely failed to mount effective resistance to managerialist interventions, even as these practices erode academic autonomy and institutional purpose. This paradox deepens when considering that many senior administrators implementing managerial reforms lack formal training in management and strategy, sometimes producing poorly conceived interventions that damage institutions while expanding administrative ranks. This essay examines why business faculty—who possess expertise to recognize problematic management practices—often remain complicit in or complacent toward managerialism. Drawing on identity theory and organizational scholarship, we argue that typical business faculty identities neither frame managerialism as a personal threat nor create obligation to apply professional expertise to institutional challenges. Before mounting effective response, business management faculty may need to cultivate alternative identities as stewards of organizational practice, not merely teachers of management abstracted from institutional context.

As the global energy landscape shifts decisively toward electrification, high-performance, cost-effective energy storage technologies are essential to enable the transition to Net Zero and a sustainable energy future. From decarbonizing transportation to stabilizing renewable-rich power grids, the role of the battery is a central enabler. Among next-generation chemistries, lithium-sulfur (Li-S) batteries stand out as particularly compelling candidates for a range of applications, offering gravimetric energy densities significantly higher than current lithium-ion systems. The appeal of Li-S technology lies not only in its potential high gravimetric energy density, but also in its ability to decouple performance from the supply chain vulnerabilities and material cost escalations currently plaguing other battery chemistries. In principle, Li-S systems could provide lightweight, high-energy storage at a low cost, with applications from automotive to high-endurance aerial platforms and through to scalable grid storage.A wealth of academic research has made great strides in understanding and improving various aspects of the LiS battery, from electrode and electrolyte development, through understanding the mechanisms of reversible charge and discharge, the challenges of the polysulfide shuttle and degradation mechanisms, with strategies for their suppression. The vast majority of this work has however, been performed and demonstrated at coin cell level, with the move to understanding performance and challenges at pouch cell rarely undertaken academically.As part of the UK’s Faraday Institution ‘Lithium Sulfur Technology Accelerator’ (LiSTAR) )project , the move from coin cell to prototype multilayer pouch cell (MLP) has been undertaken, with recent demonstration of a 5Ah MLP of more than 50 stacked electrode layers by the authors.This talk will present the journey from early-stage coin cells through to engineered 5Ah prototype MLPs, highlighting the many challenges and solutions encountered along the way. It will discuss the move from high binder, low loading electrodes typically found in lab scale research, through to low binder, high loading electrodes produced via reel-to-reel coating. Considering electrolytes, the sulfur:electrolyte ratio will discussed in light of practical considerations, illustrating the limitations that are encountered as we move to more lean systems often suggested. Furthermore, the engineering challenges encountered as the system moves from coin through single layer and multilayer pouch will be discussed, along with the optimisation of pressure on cells during testing/operation and how this differs from coin to pouch. The development process will be presented in line with improvements (or not) in electrochemical performance and particularly, sulfur utilisation and lifetime throughout, with additional insights from cell postmortem.

Abstract - Urban street development projects in India are increasingly challenged by complex planning deficiencies, fragmented execution mechanisms, and on-site management inefficiencies. This review paper synthesizes insights from twenty empirical and conceptual studies to identify, evaluate, and consolidate the major planning and execution challenges faced during urban street infrastructure development. The collective analysis reveals that inefficiencies often originate from overlapping factors such as inadequate project planning, poor coordination among stakeholders, delayed decision-making, financial constraints, and design-related ambiguities. Site-based challenges particularly concerning material management, equipment allocation, traffic diversion planning, and utility relocation—emerge as recurrent sources of delay and cost escalation. Studies on Indian contexts highlight that unclear project scopes, weak communication channels, insufficient risk assessment, and lack of integrated scheduling tools contribute significantly to time and cost overruns. Comparative findings from both Indian and international case studies underscore the universal importance of adopting structured project management frameworks, enhanced site supervision, and stakeholder collaboration mechanisms. Furthermore, the integration of digital technologies such as BIM, GIS, and remote monitoring tools has been identified as a transformative approach to improving planning accuracy, progress tracking, and coordination efficiency at the site level. The synthesis concludes that a shift from conventional top-down planning to adaptive, site-based management frameworks supported by real-time data systems and participatory decision-making can substantially improve execution reliability, sustainability, and public service continuity in urban street development projects. This review thus provides a consolidated foundation for policymakers, urban planners, and project managers to implement data-driven, site-responsive strategies that address the persistent planning and execution challenges in India’s evolving urban infrastructure landscape. Keywords: Adaptive Management, BIM Integration, Cost Overrun, Execution Challenges, GIS Application, Infrastructure Development, Planning Efficiency, Project Coordination, Site-Based Approach, Urban Street Development

Machine learning-based cost prediction in pediatric allogeneic bone marrow transplantation: Development and validation of an interactive clinical decision support tool

ABSTRACT This article presents the benefits of using Bayesian algorithms to fit regime‐switching models to daily financial returns data in order to design trading strategies. Our study focuses on a Gaussian hidden Markov model (HMM). We show how the application of a simple smoothing technique preserves the hidden Markov structure and facilitates regime detection even in instances of highly volatile data. The effectiveness of a trading strategy, based on regime detection, may be hindered by a high rate of false signals, leading to numerous trades and, consequently, an escalation in transaction costs. By reducing variance through data smoothing, we enhance the persistence of regimes over time. We validate our statistical learning procedures using synthetic data prior to their application to real‐world financial data.

BackgroundCutaneous malignant melanoma represents a notable public health issue, characterized by a rapidly increasing incidence, particularly among younger populations. Despite progress in early detection and treatment modalities, this rising trend exacerbates the healthcare system’s burden. Limited research has been conducted on the impact of comorbidities on overall and melanoma-specific healthcare costs incurred by patients with melanoma. The objective of this study is to assess how various comorbidity patterns influence healthcare costs in this patient population.MethodsThis retrospective cohort study reviewed data from the Regional Cancer Registry of the Veneto Region (RTV) for melanoma diagnoses in 2019 and 2021. Patients were grouped into specific comorbidity clusters using latent class analysis, and the effect of these patterns on melanoma healthcare costs was evaluated from a health system perspective, considering only the direct costs incurred by the regional health care service.ResultsThe study included 2,978 cases of incident melanoma. The 2,114 patients with comorbidity data available were categorized into three comorbidity clusters: Circulatory-Metabolic-Respiratory, Psychosocial-Pregnancy related, and Multiorgan-Trauma. The mean unadjusted overall and melanoma-specific cumulative expenditure per patient increased with the number of comorbidities: melanoma-specific healthcare resources were € 13,537 (no comorbidity), € 16,828 (one comorbidity), € 20,396 (Multiorgan-Trauma cluster). Hospitalizations were the primary driver of cost escalation, particularly for patients with Multiorgan-Trauma comorbidities.ConclusionComorbidity patterns significantly impact melanoma management and related healthcare costs. Understanding these patterns can help optimize resource allocation and improve patient management strategies.

This paper strives to assess the current health condition of the concrete of the bridge deck of Markham bridge of Papua New Guinea (PNG). The existing quality of concrete is tested through non- destructive testing (NDT) method. Schmidt hammer is used to assess the health condition. Vertical values were used for calculation of the in-situ compressive strength of concrete at 24 locations spanning along the entire length and breadth of the bridge deck. The compressive strengths at various locations related to the surface hardness based on empirical and statistical approach were calculated. The current quality of concrete in most of the locations is typically fair, not good. At one location, the compressive strength is calculated to be 18 MPa which is not acceptable for reinforced concrete construction and indicates need of immediate attention of the authority for pre-emptive measures to protect the bridge from further deterioration and untoward event in future. The School of Civil Engineering may be engaged with the Department of Works and Highways (DOWH) of PNG for more rigorous studies on the rehabilitation or replacement issues with the cost escalation for this purpose.

This study explores the critical role of project planning and risk assessment in minimizing delays within metro rail projects, with a specific focus on Indian urban infrastructure. Metro systems, as complex and capital-intensive undertakings, frequently encounter schedule overruns and cost escalations due to inadequate planning, fragmented coordination, and insufficient risk anticipation. Through a mixed-methods approach involving quantitative data analysis and qualitative insights from project case studies—including Delhi, Hyderabad, Mumbai, and Kolkata Metro—the research investigates how structured planning and proactive risk management contribute to improved project performance. We show that projects that have well-defined planning frameworks, stable risk assessment practices and strong stakeholder coordination have significantly fewer days of project delay than projects without these mechanisms. The study also highlights the potential of new technologies, such as Building Information Modelling (BIM) and Earned Value Management (EVM) to improve monitoring and predictive decision making. The paper concludes that, through the combination of comprehensive planning and ongoing risk assessment, projects are completed on time and institutional responsibility, sustainability, and governance in the infrastructure sector are reinforced.