Search Results (96)

Construction industry largely produces long-life, unique, and inflexible products; and combined with dispersed supply chains, it makes material tracking difficult. Thus, to achieve a circular economy (CE) in construction, there is a need for managing material information at the asset level to support reuse and recovery. This study explores the solutions for a CE in construction, and adopts a critical review, and a systematic search and review process. Initially the critical review for CE solutions revealed that maintaining authentic material information via material passports (MPs) and adopting industrialised construction (IC) for resource efficiency and flexibility are the key actions for CE implementation. As initial findings suggested the implementation of MPs in IC as imperative for a CE in construction, it was deemed necessary to develop a framework for MPs’ creation and management in IC. Thus, a further critical review was conducted to explore MPs and IC in detail, and a systematic search and review process extracted the actual information that goes into MPs, which was further categorised under various IC lifecycle processes at different stages of lifecycle, to present the incorporation of MPs into IC. The knowledge of MP processes and information in IC from this review is the vital component for the development of a necessary information management framework for MPs. This study can also be a basis for further research on the application of digital technologies and managerial actions required to realise operational MPs in IC, which is required for material circularity in construction. Full article

Selecting an appropriate business development model is central to strategic decision-making in economic and business management. These models shape sustainable growth, long-term scalability, and strategic flexibility. Existing evaluation methods rely on heuristic or qualitative judgments that lack transparency, reproducibility, and sensitivity to evaluation criteria. To address these limitations, this study introduces a hybrid multi-criteria decision-making (MCDM) framework that integrates VIKOR, entropy weighting, and simulation to evaluate 35 business development models derived from 245 real-world cases. The evaluation covers six strategic criteria: scalability, adaptability, risk exposure, financial sustainability, implementation complexity, and market relevance. Entropy weighting assigns criterion importance based on data variability, and simulation generates input sets for sensitivity and stability analysis. Results highlight Cross-Border Investment, Tiered Access, and Crowd-Backed models as top-performing strategies across multiple dimensions. By combining multiple tools in a unified framework, the research advances MCDM methodology and supports strategic business development planning under uncertainty. This contribution strengthens both academic insight and managerial practice in economics and business management. Full article

Industry 5.0 transforms industrial ecosystems via artificial intelligence (AI), human–machine collaboration, and sustainability-focused innovations. This systematic literature review examines Industry 5.0′s role in energy transition through digital transformation, sustainable supply chains, and energy efficiency strategies. Key findings highlight AI-driven smart grids, blockchain-enabled energy transactions, and digital twin simulations as enablers of low-carbon, adaptive industrial operations. This review uniquely integrates technological, managerial, and policy perspectives, providing actionable insights for policymakers and industry leaders. Industry 5.0 enhances innovative energy management, renewable energy integration, and flexible energy distribution, strengthening resilience and sustainability. It fosters environmental responsibility, social impact, and circular economy principles, laying the foundation for a low-carbon economy and accelerating the global energy transition. Full article

This study evaluates the economic viability of the South Pasopati Coal Project in Indonesia, addressing market volatility, carbon pricing policies, and the country’s energy transition towards Net Zero Emissions (NZE). Given Indonesia’s reliance on coal and the increasing global shift toward renewable energy, traditional valuation methods such as Discounted Cash Flow (DCF) may not adequately capture uncertainty and strategic flexibility. The study applies Real Options Valuation (ROV), integrating Monte Carlo Simulation (MCS) and Binomial Lattice Modeling, to assess project feasibility under various scenarios. The research compares three valuation scenarios: the base scenario (eastern route), an alternative scenario (western route), and a carbon pricing scenario. Results indicate that while the DCF method estimates a positive Net Present Value (NPV) for the base scenario, it fails to incorporate price volatility risks. The ROV method, however, captures managerial flexibility and provides a more robust valuation, showing an Expanded NPV (ENPV) that better reflects market uncertainties. Findings suggest that implementing ROV improves decision-making, particularly in volatile markets. The study underscores the necessity for Indonesia to adopt more flexible valuation frameworks to enhance investment decisions in the coal sector while aligning with international environmental standards. Full article

Cloud computing represents a groundbreaking technological change that transforms traditional IT operational paradigms, driving significant improvements in supply chain efficiency and unlocking new value through digital capabilities. Despite its growing influence, empirical research on this subject remains limited, with unclear explanations of the specific ways cloud computing enhances supply chain operations. The precise mechanisms through which it influences supply chain dynamics are yet to be fully explored. This study employs survey data from Chinese enterprises utilizing cloud computing, applying Smart PLS 3.0 for partial least squares structural equation modeling (PLS-SEM) to assess how cloud-based technical competencies affect supply chain outcomes. Grounded in IT capability theory, we conceptualize cloud computing’s technical dimensions as Flexible IT Infrastructure and Cloud/Business Synergy while incorporating supply chain governance as a mediator and market uncertainty as a moderator to clarify the relationship between cloud capabilities and performance. Our findings advance both scholarly and managerial perspectives on cloud computing’s role in modern supply chains. Full article

Considering the inherent characteristics of long-term agreements, public–private partnership (PPP) projects are confronted with diverse uncertainties and external challenges. However, existing research has devoted limited attention to the resilience of PPP projects. This study seeks to identify governance factors influencing PPP project resilience and analyze the interconnections among these factors in fostering such resilience. A governance framework for PPP project resilience is proposed, comprising thirteen governance factors across four dimensions: institutional, organizational, contractual, and managerial factors. The interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) techniques are adopted to explore the hierarchical relationships and interactive mechanisms among these governance factors in a systematic view. The findings reveal that strategic alliances, risk allocation and transfer, flexible contracting, and long-term relationship management represent core governance factors critical to enhancing project resilience. Institutional factors are identified as the most foundational determinants within the governance system, while contractual and managerial factors act as mediating elements facilitating the translation of institutional foundations into operational resilience. This study deepened the understanding of the practitioners with regard to the key governance factors and their inter-relationships, which can help systematically enhance the resilience of PPP projects. Full article

Increasing supply chain uncertainty due to market volatility has heightened the need for more flexible procurement strategies. While procurement through long-term forward contracts provides supply stability and cost predictability, it limits adaptability. Option contracts offer procurement flexibility, but require additional upfront premiums. Meanwhile, the spot market enables real-time purchasing without prior commitments, enhancing flexibility but exposing buyers to price volatility. Despite the growing adoption of portfolio procurement—combining forward contracts, option contracts, and spot market purchases—the existing research primarily examines these channels in isolation or in limited combinations, lacking an integrated perspective. This study addresses this gap by developing a comprehensive procurement model that simultaneously optimizes procurement decisions across all three channels under uncertain demand and fluctuating spot prices. Unlike prior studies, which often analyze one or two procurement channels separately, our model presents a novel, holistic framework that balances cost efficiency, risk mitigation, and adaptability. Our findings demonstrate that incorporating the spot market significantly enhances procurement flexibility and profitability, particularly in environments with high demand uncertainty and price volatility. Additionally, sensitivity analysis reveals how fluctuations in spot prices and demand uncertainty influence optimal procurement decisions. By introducing a new, practical approach to portfolio procurement, this study provides managerial insights that help businesses navigate complex and uncertain supply chain environments more effectively. However, this study assumes unlimited spot market capacity and reliable suppliers, highlighting a limitation that future research should address. Full article

In today’s competitive industrial landscape, effective performance measurement is crucial for achieving operational success. Key Performance Indicators (KPIs) are widely used to track progress, but their implementation often lacks a comprehensive framework that considers both financial outcomes and managerial insights. A quali-quantitative analysis model is introduced to optimize the implementation of KPIs in industrial settings, demonstrated through a case study of a Cambodian charcoal factory. By integrating Cost–Benefit Analysis (CBA) and Fuzzy Analytic Hierarchy Process (FAHP), the model combines both quantitative financial analysis and qualitative managerial evaluations to assess and rank a selected set of KPIs. This dual approach ensures a more comprehensive understanding of KPI impacts, enabling informed decision-making. The results highlight the critical need for balancing measurable financial benefits with qualitative insights, particularly in industries within developing nations that are forced to compromise in constrained environments, and where both economic outcomes and strategic considerations are essential for sustainable growth. Furthermore, the proposed model has universal applicability across different industrial contexts, providing a flexible and adaptable framework for KPI selection beyond the specific case study analyzed. Full article

Supply chain resilience (SRES) is essential for firms aiming to alleviate the impact of interruptions and maintain operational continuity and sustainability in performance. In the context of the FMCG industries of Pakistan and Saudi Arabia, characterized by intricate and vulnerable supply chains, there exists an urgent necessity for solutions that bolster resilience. This study examines the influence of critical factors resilient suppliers (RS), transportation capacity (TC), flexibility (FLEX), network complexity (NC), and supply chain dynamism (SPD) on SRES. A quantitative methodology was utilized, examining survey data from 611 participants with Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). The results indicate that RS and TC are essential for directly improving SRES, whereas FLEX and SPD facilitate increased adaptability and reactivity. The NCA emphasizes the need to control NC to avert bottlenecks that may impede resilience. This study indicates that SRES emerges from the dynamic interplay of several elements, rather than from separate enhancements. Although NC exerts a negligible direct influence, adeptly managing complexity is crucial for reducing disruptions and inefficiencies. The results underscore that fortifying RS, TC, and FLEX in unison improves resilience and adaptation to market volatility and disturbances. This study provides various theoretical and managerial insights. A systems theory approach highlights the interdependence of supply chain components, whereas the Theory of Constraints (TOC) posits that excessive NC can hinder resilience. Management should concentrate on maximizing RS and TC until declining returns are evident, thereafter redirecting efforts towards improving FLEX and minimizing NC. Furthermore, optimizing processes and facilitating swift decision-making are essential for maintaining resilience. Full article

The untapped potential of wave energy offers another alternative to diversifying renewable energy sources and addressing climate change by reducing CO₂ emissions. However, development costs to mature the technology remain significant hurdles to adoption at scale and the technology often must compete against other marine energy renewables such as offshore wind. Here, we conduct a real option valuation that includes the uncertain market price of wholesale electricity and managerial flexibility expressed in determining future optimal decisions. We demonstrate the probability that the project’s embedded compound real option value can turn a negative net present value wave energy project to a positive expected value. This change in investment decision uses decision tree analysis, where real options are developed as decision nodes, and models the uncertainty as a risk-neutral stochastic process using chance nodes. We also show how our results are analogous to a financial out-of-the-money call option. Our results highlight the distribution of outcomes and the benefit of a staged long-term investment in wave energy systems to better understand and manage project risk, recognizing that these probabilistic results are subject to the ongoing evolution of wholesale electricity prices and the stochastic process models used here to capture their future dynamics. Lastly, we show that the near-term optimal decision is to continue to fund ongoing development of a reference architecture to a higher technology readiness level to maintain the long-term option to deploy such a renewable energy system through private investment or private–public partnerships. Full article

This research determines the contribution of Corporate Social Responsibility (CSR) to reducing financial risks and, consequently, to the sustainable development of companies in different sectors of the economy and at different phases of the economic cycle (using Russia as an example). The informational and empirical base comprises data on the dynamics of stock prices of sectoral indices of the Moscow Exchange’s total return “gross” (in Russian rubles): oil and gas, electricity, telecommunications, metals and mining, finance, consumer sector (retail trade), chemicals and petrochemicals, and transportation, as well as the “Responsibility and Openness” index in 2019 (before the crises), in 2020 (COVID-19 crisis), 2022 (sanction crisis), and 2024 (Russia’s economic growth). Economic–mathematical models, compiled through regression analysis, showed that the contribution of CSR to reducing the financial risks of companies is highly differentiated among economic sectors and phases of the economic cycle. The research presents a new sectoral perspective on counter-cyclical management of the financial risks of companies through CSR, enabling a deeper study of the cause-and-effect relationships of such management for the sustainable development of companies from different economic sectors. This is the theoretical significance of this research, its novelty, and its contribution to the literature. The research has practical significance, revealing previously unknown best practices for the sustainable development of companies from different economic sectors of Russia across different phases of the economic cycle. The systematized experience will be useful for forecasting the financial risks of companies during future economic crises in Russia and improving the practice of planning and organizing the financial risk management of Russian companies through CSR. The authors’ conclusions have managerial significance because they will help enhance the flexibility and efficiency of corporate financial risk management by considering the sectoral specifics and cyclical nature of the economy when implementing CSR. Full article

Background: Logistics operations are integral to manufacturing systems, particularly in the transportation processes that occur not only between facilities and stakeholders but also between warehouses and workstations within a facility. The design of functional areas and allocating goods to appropriate zones within the warehouse management system (WMS) are critical activities that substantially influence the efficiency of manufacturing logistics operations. Methods: This study develops a mixed-integer programming (MIP) model to optimize material flow and product routing in manufacturing. The model identifies efficient pathways, assigns products to routes, and determines the required material-handling equipment. It is implemented in Python (3.11.5) using the Pyomo (6.7.3) package and the CBC solver (2.10.11), with sensitivity analysis performed on constraints and decision variables to evaluate robustness. Results: The findings indicate that Material Flow 3 and Material-Handling Equipment 1 represent the optimal configurations for managing the majority of goods within the manufacturing system. Conclusions: The proposed mathematical model supports the decision-making process by enabling adjustments to the proportions of functional areas within the manufacturing logistics system, ensuring operational efficiency and flexibility in response to changing demands. Furthermore, the study offers managerial insights and suggests directions for future research. Full article

Reduced-impact logging is a key aspect of sustainable forest management in the Brazilian Amazon. Real Options Analysis (ROA) improves the evaluation of certified projects, increases their value, and supports investor confidence. This study evaluates the economic viability of a forest management investment project in certified areas of the Brazilian Amazon, using ROA to incorporate uncertainty and managerial flexibility into the decision-making process. The analysis focused on an Ombrophilous Dense Forest in its first cutting cycle, with 30 species of diameter at breast height ≥ 50 cm and a projected activity period of 30 years. Timber value was modeled using the mean reversion motion, and a binomial decision model was applied, incorporating options such as deferral, abandonment, and interruption. The deferral option should be exercised with a 100% probability, both in the joint calculation scenario and in separate analyses, highlighting the significant value of this managerial flexibility. In addition, when analyzed using ROA, the value of the project increased by 105% (USD 91,784,176) compared to the traditional net present value approach. The forest management investment project in the Brazilian Amazon is economically viable and the application of ROA reveals significant value added, demonstrating the importance of incorporating flexibility into investment decisions. Full article

Because disruption happens unpredictably and generates serious impact in supply chain and production environments in the real world, it is important to develop approaches to handle disruption. This paper investigates disruption handling in part input sequencing of flexible manufacturing systems (FMSs). An algorithm is proposed for FMS part input sequencing to handle machine breakage. Evaluation is performed for the proposed algorithm by simulation experiments and result analyses. Finally, conclusions are summarized with managerial implications discussed and further research works suggested. Full article

This study investigated non-instantaneous deteriorating items because not all products deteriorate immediately. In the high-tech product life cycle, the product demand increases linearly substantially in the growth stage and maintains a near-constant level in the maturity stage. This is a ramp-type demand rate. To satisfy the demand as shortages occur, partial backlogging is necessary. The advance-cash-credit payment scheme, comprising advance, cash, and credit payments, has gained popularity in business transactions to improve cash flow flexibility among supply chain participants. This study explored a partial backlogging inventory model with ramp-type demand for non-instantaneous deteriorating items under generalized payment. The proposed model also incorporated discounted cash flow analysis to account for the time value of the profit function. This study attempted to determine the optimal replenishment strategy to maximize the present value of the total profit. Finally, we conducted a sensitivity analysis to examine the efficacy of the proposed model and gain managerial insights. The optimal total profit rises with an increase in the permissible delay period and sale price but decreases with an increase in ordering and purchase costs. Then, the decision-maker can refer to the managerial insights to choose the appropriate parameter value for the operation. Full article