Search Results (230)

In an ever-evolving digital environment, organizations must adopt advanced technologies for real-time big data processing to maintain their competitiveness and growth. However, selecting appropriate technologies is a challenge, particularly for small and medium-sized enterprises (SMEs). This study develops a literature review to analyze the methodologies used in the selection of technologies, with a special focus on those associated with the Industry 4.0. Knowledge Development Process-Constructivist (ProKnow-C) method, which was used to build a bibliographic portfolio, examining approximately 3400 articles published between 2005 and 2024, from which 80 were selected for a detailed analysis. The main methodological contributions come from research articles, the ScienceDirect database, the Expert Systems with Applications Journal, studies conducted in Turkey, and publications from the year 2023. The results highlight the predominant use of multi-criteria techniques, emphasizing hybrid approaches that combine various decision-making methodologies. In particular, the analytic hierarchy process (AHP) and TOPSIS methods were employed in 51.25% of the analyzed cases, either individually or in combination. It is concluded that technology selection should be based on flexible and adaptive approaches tailored to the organizational context, aligning long-term strategic objectives to ensure business sustainability and success. Full article

The scientific investment decision of Park-level Integrated Energy System (PIES) projects is of great significance to energy enterprises for improving the efficient utilization of funds, promoting green and low-carbon transformation, and achieving the goal of carbon neutrality. This paper proposed a two-stage investment framework that integrates a multi-objective 0–1 programming model with a multi-criteria decision-making (MCDM) technique to determine the optimal PIES project investment portfolios under the constraint of quota investment. First, a multi-objective (MO) 0–1 programming model was constructed for typical PIES projects in Stage-I, which considers economic and environmental benefits to obtain Pareto frontier solutions, i.e., PIES project portfolios. Second, an evaluation index system from multiple dimensions was established, and a hybrid MCDM technique was adopted to comprehensively evaluate the Pareto frontier solutions in Stage-II. Finally, the proposed model was applied to an empirical case, and the simulation results show that the decision framework can achieve the best overall benefit of PIES project portfolios with maximal economic benefit and minimum carbon emissions. In addition, the robustness analysis was performed by changing the indicator weights to verify the stability of the proposed framework. This research work could provide a theoretical tool for investment decisions regarding PIES projects for energy enterprises. Full article

Our society is facing serious challenges from global warming and environmental degradation. Scientists have identified carbon dioxide as one of the causes. Our society is embracing carbon offset as a way to field the challenges. The purpose of carbon offset is trying to cancel out the large amounts of carbon dioxide by investing in projects that reduce or remove emissions elsewhere. Examples of carbon offset projects are planting trees, renewable energy projects, and capturing methane from landfills or farms. Not all carbon offset projects are equally effective. In stock markets, investors eagerly pursue carbon offset. Namely, investors favor carbon offset in addition to risk and return when investing. Therefore, investors supervise risk, return, and carbon offset. Investors’ pursuits raise the question of how to model carbon offset for investments. The traditional answer is to adopt carbon offset screening and engineer portfolios by stocks with good carbon offset ratings. However, Nobel Laureate Markowitz emphasizes portfolio selection rather than stock selection. Moreover, carbon offset is composed of multiple components, ranging from business, social, economic, and environmental aspects. This multifaceted nature requires more advanced models than carbon offset screening and portfolio selection. Within this context, we systematically formulate multiple-objective portfolio selection models that include carbon offset. Firstly, we extend portfolio selection and treat carbon offset as a whole. Secondly, we separate carbon offsets into different components and build models to monitor each component. Thirdly, we innovate a model to monitor each component’s expectation and mitigate each component’s risk. Lastly, we optimize the series of models and prove the models’ properties in theorems. Mathematically, this paper makes theoretical contributions to multiple-objective optimization, particularly by proving the consistency of efficient solutions during objective classification and model evolution, describing the structure of properly efficient sets for multiple quadratic objectives, and elucidating the optimization’s sensitivity analyses. Moreover, by coordinating the abstract objective function, our formulation is generalizable. Overall, this paper’s contribution is to model carbon offset investments through multiple-objective portfolio selection. This paper’s methodology is multiple-objective optimization. This paper’s achievements are to provide investors with greater precision and effectiveness than carbon offset screening and portfolio selection through engineering means and to mathematically prove the properties of the model. Full article

Urban decarbonisation requires governance models that overcome the fragmentation and rigidity of traditional urban planning. This article presents a systemic and digital framework for managing urban decarbonisation portfolios aligned with the EU Mission for Climate-Neutral and Smart Cities. Grounded in systems thinking and portfolio theory, this study develops an analytical taxonomy and an interactive digital tool to support strategic coordination, multistakeholder collaboration, and adaptive decision-making. The framework is empirically validated through the case of Madrid’s Climate City Contract, demonstrating its functionality and transferability. Using a mixed-method approach—combining co-creation workshops, interviews, document analysis, and iterative prototyping—this research maps interdependencies among projects, actors, and levers of change. The digital tool enables real-time visualisation of collaboration patterns, gaps, and synergies, enhancing strategic foresight and coordination capacity. Findings reveal that 75% of initiatives in Madrid’s CCC address climate adaptation, 80.36% are linked to knowledge generation, and key anchor projects serve as integrative hubs within the portfolio. This study concludes that the portfolio approach strengthens systemic innovation and reflexive governance by integrating digital infrastructures with collaborative planning processes. While challenges persist—including data integration, institutional capacity, and political dynamics—this research offers a replicable methodology for embedding mission-oriented strategies into urban governance. The digital portfolio emerges as a complementary governance tool that enhances transparency, organisational learning, and alignment across governance levels. Full article

Transformative digitally integrated pedagogy can enrich learning experiences, diversify the curriculum and broaden access to industry-relevant advanced clinical education for remote learners in medical education. Clinical skills are characterised as the portfolio of practical and interpersonal skills required by practicing clinicians. The purpose of this project was to design a new wholly online post-professional university subject for clinicians in different healthcare disciplines to advance these skills, which would traditionally be taught and assessed in-person. Our methodology included critically reviewing existing evidence of relevant medical skills which need to be included in the curriculum and approaches to their assessment. We designed a subject which dovetailed learning experiences with continuing clinical practice, and developed a new framework for remote video assessment of practical skills. Our pedagogical approaches included a backwards design coupled with a Four-Component Instructional Design Model (4C-ID) approach, which increased access and contextualised learning opportunities for diverse and practicing clinicians. Our narrative synthesis critically shares our experience and insights of embracing digital-technology opportunities while problem-solving to move past barriers. Our impact evaluation and experiential insights offer a platform to reimagine emerging possibilities for future digitally integrated education in medical education and other clinical-skills professions. Full article

This paper examines the impact of various uncertainty channels on stock market returns in Saudi Arabia, with a focus on the Tadawul All Share Index (TASI). It examines factors such as Saudi-specific Geopolitical Risk, Global Oil Price Uncertainty, Climate Policy Uncertainty, and U.S. Monetary Policy Uncertainty. Using monthly data from November 1998 to June 2024 and the Local Projections (LP) methodology, the study examines how these uncertainties impact market returns across various time horizons, taking into account potential structural breaks and nonlinear dynamics. Our findings indicate significant variations in the market’s response to the uncertainty measures across two distinct periods. During the first period, geopolitical risks have a strong positive impact on market returns. Conversely, the second period reveals a reversal, with negative cumulative effects, suggesting a shift in risk–return dynamics. Oil Price Uncertainty consistently exhibits a negative impact in both periods, highlighting the changing nature of oil dependency in the Saudi market. Additionally, Climate Policy Uncertainty is becoming more significant, reflecting increased market sensitivity to global environmental policy changes. Our analysis reveals significant asymmetries in the effects of various uncertainty shocks, with Monetary Policy Uncertainty exhibiting nonlinear effects that peak at intermediate horizons, while commodity-related uncertainties exhibit more persistent impacts. These findings, which remain robust across various tests, offer critical insights for portfolio management, policy formulation, and risk assessment in emerging markets undergoing substantial economic changes. Full article

This study examines the dynamic relationship between changes in construction contract amounts across the diversified business areas within the portfolios of Korean construction firms and their overall business performance using a vector error correction model. It aims to provide a detailed evaluation of the effectiveness and characteristics of diversification strategies in the construction industry. This analysis employs key variables, including the debt ratio, return on total assets, diversification index, and construction contract amounts in domestic and overseas building, civil engineering, and plant construction projects. Two distinct models are used: Model A investigates the relationship between the debt ratio and diversification while Model B explores the relationship between the return on total assets and diversification. The time series data for the analysis spans from Q1 2002 to Q4 2021 on a quarterly basis. The results indicate that Korean construction firms have actively expanded into overseas markets to enhance their financial soundness. However, while such diversification efforts facilitate short-term capital acquisition, they have a negative impact on long-term business performance. When technological capabilities remain constant, lowering prices to increase contract volume may ultimately erode long-term profitability. Therefore, rather than focusing solely on expanding contract volumes through diversification, it is essential to first objectively assess the strengths of each business sector and focus on strengthening core competencies and expertise before pursuing further diversification. Full article

Jordan, which depends largely on imported fuel, is confronted with an increasing demand for energy due to regional socio-political dynamics and population growth. This dependence highlights the necessity of locally supplied, sustainable energy sources to reduce environmental damage and economic vulnerability. Thus, the goal of this study is to categorize these sources based on their priorities for use, as well as to develop and evaluate sustainable RE technologies. In order to diversify the energy portfolio, lessen reliance on fossil fuels, and offer suggestions for sustainable growth, this study investigates renewable energy sources (RES) in Jordan. A model is developed to study and evaluate RES technologies and introduce actions for their exploitation. In order to prioritize renewable energy sources and improve energy independence and sustainability, this paper looks at renewable energy technologies that are feasible for Jordan, using a variety of MCDM methodologies. This study emphasizes Jordan’s urgent need for green, sustainable energy, highlighting solar, hydropower, and wind projects as the most advantageous options, promoting energy independence. The outcomes designate the applicability of the proposed model and integrated tools for analyzing renewable energy technology. The findings assist a shift toward energy independence and sustainability by providing decision-makers with a systematic, data-driven method for prioritizing green energy investments. Full article

To address environmental challenges, governments globally have implemented a range of carbon reduction policies. Based on their mechanisms of action, this study categorizes these policies into regulatory (e.g., carbon taxes and cap-and-trade) and supportive measures (e.g., production cost subsidies, low-carbon technology subsidies, and low-carbon product subsidies). By integrating these approaches, six distinct policy combinations were identified. A supply chain network equilibrium model, incorporating manufacturers, retailers, and demand markets, was developed using variational inequality theory to assess the effectiveness of these combinations. Numerical simulations were conducted with a modified projection algorithm, and the Borda method was applied to evaluate equilibrium outcomes, specifically production levels and emission reductions, under each policy combination, revealing synergies between policies. The analysis revealed three key findings: (1) Among supportive policies, the combination of low-carbon product subsidies with regulatory policies is the most effective, while production cost subsidies are relatively weaker; (2) carbon tax policies combined with supportive policies outperform carbon trading; (3) a higher intensity of regulatory policies enhances the incentive effects of supportive policies. This research offers valuable guidance for governments seeking to design evidence-based policy portfolios that effectively balance emission reduction goals with economic development priorities. Full article

This paper presents the development and analysis of a bridge bearing database consistent with the 2020 Italian Guidelines (LG2020), currently enforced by the Italian law for risk classification and management of existing bridges. The database was developed by putting together the contribution of 24 research teams from 18 Italian universities in the framework of a research project foreseen by the agreement between the High Council of Public Works (CSLP, part of the Italian Ministry of Transportation) and the research consortium ReLUIS (Network of Italian Earthquake and Structural Engineering University Laboratories). This research project aimed to apply LG2020 to a set of about 600 bridges distributed across the Italian country, in order to find possible issues and propose modifications and integrations. The database includes almost 12,000 bearing defect forms related to a portfolio of 255 existing bridges located across the entire country. This paper reports a preliminary analysis of the dataset to provide an overview of the bearings installed in a significant bridge portfolio, referring to major highways and state roads. After a brief state of the art about the main bearing types installed on the bridges, along with inspection procedures, the paper describes the database structure, showing preliminary analyses related to bearing types and defects. The results show the prevalence of elastomeric pads, representing more than 55% of the inspected bearings. The remaining bearings are pot, low-friction with steel–Teflon surfaces and older-type steel devices. Lastly, the study provides information about typical defects for each type of bearing, while also underscoring some issues related to the current version of the LG2020 bearing inspection form. Full article

Area-wide coordinated urban regeneration is a strategic approach to upgrading urban functions, enhancing the allocation efficiency of land resources, and enhancing the overall urban environment from a project portfolio perspective. However, implementing area-wide coordinated urban regeneration faces significant challenges, including project delays, terminations, and difficulties in achieving investment returns. These challenges are particularly acute in smaller Chinese cities. While most previous research has paid attention to large Chinese cities, they usually neglect the risks associated with urban regeneration from an area-wide project portfolio perspective. To address this gap, this research develops a comprehensive list of risk indicators for area-side coordinated urban regeneration based on project portfolio management theory. Stakeholder opinions on the likelihood and impact of these risk indicators were collected by a questionnaire survey. A risk evaluation method, integrating the C-OWA operator and grey cluster analysis, was proposed to assess these risks. Risk management and control strategies were then proposed based on different risk levels. A case study of the coordinated urban regeneration of Yancheng’s Chaoyang area was conducted to evaluate comprehensive risk levels and provide tailored recommendations for risk control. This study offers practical guidance for urban planners and policymakers to improve decision-making in small cities and contributes new insights into risk management in the field of urban development. Full article

Offshore wind energy has become a critical component of global efforts to transition toward low-carbon and sustainable energy systems, and although Taiwan’s advantageous geographical position has accelerated its progress in this domain, many of Taiwan’s upcoming offshore wind projects remain in a pre-construction phase, raising questions about their viability for complementary wave energy integration. To address this challenge, this study proposes a hybrid Cross-Efficiency Slacks-Based Measure (CE-SBM) Data Envelopment Analysis (DEA) model. Thirteen announced offshore wind projects were evaluated using spatial and resource-related input variables and energy-centric output variables. The self-efficiency results from the SBM stage highlighted several projects—most notably Zhu Ting, Wo Neng, and Chu Tin—as highly effective in resource utilization under their own weighting schemes. However, the subsequent cross-efficiency analysis added a consensus-based perspective, revealing a clear performance hierarchy and identifying inefficiencies in projects such as Greater Changhua Northeast and Winds of September. These findings underscore the value of combining DEA-based models with slacks-based and cross-efficiency features to guide multifaceted energy development. By prioritizing projects with robust efficiency profiles, policymakers and stakeholders can expedite Taiwan’s broader adoption of integrated wind–wave energy systems, ultimately fostering a more reliable and sustainable marine energy portfolio. Full article

The management of public institutions is focused not only on providing and improving public services but also on managing the physical infrastructure that these institutions use—buildings for provision of such services. The focus of this paper is on decision support to the management of individual buildings and the set of such buildings (portfolio) during the planning phase. More precisely, it is directed towards support towards both the decision-maker (DM) and decision-making process (DMP) when planning construction activities/projects such as maintenance, renovation, reconstruction, extension, construction, design/preparation of project-technical documentation, etc. The aforementioned DMP includes the processing of a large amount of diverse data (technical, economic, social, etc.) expressed differently—numerically or descriptively, as well as in different units of measurement, simultaneously taking into account the different wishes and attitudes of stakeholders (consequently meeting their often conflicting goals and criteria). The above indicates that it is a complex and ill-defined multi-criteria problem faced by the DM/planner. On top of that, and knowing that the DM usually does not have all the necessary knowledge and skills, this paper proposes how to overcome these issues by supporting the DM within the DMP during such a planning process. The proposed concept promotes an integral (considering relevant aspects of this management problem) and inclusive (taking into account the views of relevant stakeholders) approach to managing complex construction projects and their portfolios. It is methodologically based on the logic of decision support systems and multi-criteria analysis. The multi-criteria methods used include the Preference Ranking Organization METhod for Enrichment Evaluation (PROMETHEE) for the evaluation and comparison of alternatives in an integral manner, as well as the Analytic Hierarchy Process (AHP) for determining the weights of criteria and achieving an inclusive and consistent approach to relevant stakeholders (based on the goal tree approach). The concept was tested on the planning of infrastructure management at a university in the Republic of Croatia, and it was proven to be useful because it provided the DM with a basis for decision making. The usefulness of the concept was confirmed by the concordance of the plan obtained using the concept and the activities/projects actually realized. Full article

This work presents a multi-stage stochastic optimization model intended to improve investment decision-making for energy projects by incorporating uncertainty in contexts and changes in market pricing. In contrast to conventional deterministic models, which generally concentrate on a singular stage while neglecting the intricacies associated with policy and market uncertainties, our methodology incorporates Conditional Value at Risk as a pivotal risk metric. Across a span of five years, the model predicts how investments will be distributed among three types of electricity projects: Solar Farm, Wind Farm, and Hydro Plant. The stochastic model strategically allocates an investment of USD 16.5 million to achieve an expansion in the capacity of 925 megawatts and an expected portfolio return of USD 1,822,500. Notably, the model maintains a Conditional Value at Risk of USD 100,000 and an impressive Sharpe Ratio of 18.2250, demonstrating its ability to offer improved risk-adjusted returns. This study illustrates the effectiveness of stage stochastic optimization in enhancing diverse and robust renewable energy portfolios. Full article

Urban watersheds undergo significant ecological change due to increased imperviousness, flashy hydrologic processes, channel evolution, the loss of riparian zones, and the fragmentation of movement corridors. Watershed restoration seeks to address these challenges simultaneously through site-scale actions coordinated at the basin scale. Ecological benefits, social outcomes, and monetary costs represent common metrics to inform decision-making on these programs. However, decision-making at the site and watershed scale may differ, and the accuracy and resolution of benefit and cost data should vary as project needs dictate. This paper presents a case study of urban stream restoration in Utoy Creek, Atlanta, Georgia, USA, where multiple partner organizations are planning a portfolio of stream restoration projects. Analyses were conducted to assess ecological benefits, social outcomes, and monetary costs at the watershed scale to inform site selection, at the site scale to guide restoration design, and then again at the watershed scale to identify an effective portfolio of sites. These scales each presented unique technical challenges and required the adaptation of analytical methods to suit decision-making needs. This case study is not presented as a comprehensive approach applicable in all urban systems, but instead a template for urban restoration practitioners to adapt to their unique watershed and planning contexts. Full article