Search Results (62)

This paper addresses the very important and topical issue of the effective and efficient implementation of green and energy transition processes, taking into account social aspects and energy security. Due to climate change and the geopolitical situation, these processes are currently priorities for most countries and regions of the world. The opportunity to achieve success in their implementation lies in the implementation of the Open Innovation concept in a new model developed and presented in this paper. Its essence is an identified group of stakeholders in the processes under study (science, business, state, society, environment) and their specific positions, roles, and relationships. It was also important to analyze the mechanisms of cooperation and interaction between stakeholders, defining key forms and directions, as well as ways of harmonizing them, leading to synergy in innovation processes. A significant stage of the work was also the development of a RACI role and responsibility matrix, which enabled the precise assignment of functions to individual stakeholders in the developed model. Key challenges, barriers (technological, regulatory, organizational, and social), and factors conducive to the coordination of cooperation and interests of the identified stakeholder groups were also identified. To deepen knowledge and better understand the dynamics of this cooperation, a matrix was also developed to assess priorities and their impact on the energy sector within the open innovation model. This tool enables the identification of diverse perspectives in relation to key criteria such as energy security, innovation, social participation, and sustainable development. In addition, a set of indicators (in five key categories of the innovation ecosystem) was developed to enable multidimensional measurement of the effectiveness, efficiency, and scalability of the open innovation model in the energy sector. They also allow for the study of the impact of these factors on the sustainable development, security, and resilience of energy systems. The developed and presented concept of a model of cooperation between stakeholders using the Open Innovation model in the energy industry is universal in nature and can also be used in other sectors. Its application offers broad opportunities to support the management of transformation processes, taking into account the innovative solutions that are necessary for the success of these processes. Full article

Reverse Logistics (RL) plays a fundamental role in supply by addressing returns, undelivered or damaged products, exchanges, and environmental concerns, directly contributing to more sustainable supply chain practices. Although firms recognize the importance and benefits of this concept, their supply chain remains focused on direct logistics, often overlooking RL’s potential to enhance sustainability performance. The aim of this article is to analyse the interaction between the barriers that challenge or prevent the implementation of RL in Small and Medium-sized Enterprises (SMEs). First, a literature review identified 22 barriers to developing RL in SMEs. Then, through experts’ opinions gathered in a Focus Group (FG), an Interpretive Structural Modeling (ISM) model was used to understand the hierarchy relations between barriers, and a Matrix Cross Impact Matrix Multiplication (MICMAC) analysis was carried out to aggregate the barriers in four categories according to their influencing power and dependence. Applying the methodology to the Portuguese case resulted in an ISM model with seven hierarchical levels and a MICMAC diagram without dependent barriers. Moreover, six key barriers emerged, namely, Lack of adequate organizational structure and support for RL practices, Lack of corporate social responsibility, Complexity of the operation, Lack of shared understanding of best practices, Difficulty with members of the supply chain, and Lack of support from supply chain players, which proved to be the most critical as they are positioned at the highest hierarchical levels of the ISM model and fall within the independent variable quadrant of the MICMAC analysis, thus revealing a strong driving power over the other barriers. The findings highlight that overcoming these barriers is crucial for SMEs to unlock the full sustainability potential of RL and transition towards supply chain models that are greener through a reduced carbon footprint, improved resource efficiency, and the adoption of circular economy practices. Academically, this research advances the literature by applying the ISM–MICMAC approach to SMEs, offering novel insights into the structural role of barriers in reverse logistics implementation. Full article

As vision and mission statements embody the directions set forth by an organization, their connection to the Sustainable Development Goals (SDGs) must be made explicit to guide overall decision-making in taking strides toward the sustainability agenda. The semantic alignment of these strategic statements with the SDGs is investigated in a previous study, although several limitations need further exploration. Thus, this study aims to advance two contributions: (1) utilizing the capabilities of LLMs (Large Language Models) in text semantic analysis and (2) integrating fuzziness into the problem domain by using a novel intuitionistic fuzzy set extension of the PROBID (Preference Ranking On the Basis of Ideal-average Distance) method. First, a systematic approach evaluates the semantic alignment of organizational strategic statements with the SDGs by leveraging the use of LLMs in semantic similarity and relatedness tasks. Second, viewing it as a multi-criteria decision-making (MCDM) problem and recognizing the limitations of LLMs, the evaluations are represented as intuitionistic fuzzy sets (IFSs), which prompted the development of an IF extension of the PROBID method. The proposed IF-PROBID method was then deployed to evaluate the 47 top Philippine corporations. Utilizing ChatGPT 3.5, 7990 prompts with repetitions generated the membership, non-membership, and hesitance scores for each evaluation. Also, we developed a cohort-dependent SDG–vision–mission matrix that categorizes corporations into four distinct classifications. Findings suggest that “highly-aligned” corporations belong to the private and technology sectors, with some in the industrial and real estate sectors. Meanwhile, “weakly-aligned” corporations come from the manufacturing and private sectors. In addition, case-specific insights are presented in this work. The comparative analysis yields a high agreement between the results and those generated by other IF-MCDM extensions. This paper is the first to demonstrate two methodological advances: (1) the integration of LLMs in MCDM problems and (2) the development of the IF-PROBID method that handles the resulting inherently imprecise evaluations. Full article

Corporate sustainability is a multi-stakeholder approach with a Triple or Quadruple Bottom Line focused on long-term horizons and the creation of shared or triple value. The objective of this study is to present a theoretical framework for the implementation and measurement of corporate sustainability within companies and to propose a set of measurement scales for assessing levels of sustainability implementation. This study offers a novel conceptual model that enables the systematic classification and benchmarking of sustainability maturity levels in companies. The methodology involves a literature review and the application of the Dyllick–Muff matrix (2016), which identifies three distinct levels of sustainability: Sustainability 1.0, Sustainability 2.0, and Sustainability 3.0. This framework uses three dimensions: objectives (the “what”), value creation (the “why”), and organizational perspective (the “how”). The study highlights the scarcity of research on the practical implementation of sustainability. Furthermore, there is no widely adopted framework for measuring sustainability implementation. The diversity and fragmentation of existing sustainability measurement models make comparative analysis particularly challenging. This study concludes that the Dyllick–Muff matrix is a suitable tool for determining a company’s level of sustainability and for conducting comparative analyses across organizations. Full article

This study develops the Information Systems–Organizational Fit Alignment Model (ISOFAM) to evaluate information systems (IS) alignment during the pre-combination phase of mergers and acquisitions (M&A)—a critical yet underexplored stage in integration planning. Through constructivist grounded theory and the reanalysis of qualitative data from two anonymized M&A cases—one domestic (Slovenian) and one cross-border (European)—this study identifies four diagnostic dimensions: Technical Compatibility, Functional Complementarity, Cultural and Governance Fit, and Planning Maturity. ISOFAM is operationalized through visual tools, including the Risk–Opportunity Diagnostic Matrix, IS Misalignment Escalation Flowchart, and Temporal Integration Framework, which facilitate early alignment and strategic foresight. These contributions position IS as a strategic pre-combination priority, enhancing both theoretical and practical outcomes in digital M&A. Full article

This study first examines the potential of using Fourier-transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC) to extract molecular and organizational markers from human oral mucosa. These indicators are then examined in relation to age and pathophysiological conditions. Oral mucosa biopsies were collected from 38 patients during surgical procedures and analyzed using FTIR and DSC-validated protocols. The patients were divided into two age groups, namely 20–40 and 70–90 years. Vibrational markers of the lamina propria and epithelium, including lipid-to-protein and collagen-to-protein ratios and lipid order, were extracted from the FTIR spectra of both layers. Hydration levels and collagen thermal stability were determined from DSC thermograms of the entire biopsy. The preliminary findings of this study, which will require further validation in a larger patient cohort, indicate a significant decrease in bound water content and collagen denaturation temperature in the older population. This suggests that oral mucosa undergoes structural dehydration and collagen destabilization with age. Further comparisons within the older group revealed links between biophysical markers of the oral mucosa and chronic or local pathologies. Patients with cardiovascular diseases exhibit altered collagen organization, while patients with diabetes display differences in the lipid-to-protein ratio and the order of lipid chains in the epithelium. Gingivitis is associated with variations in the collagen-to-protein ratio, which supports the role of inflammation in extracellular matrix remodeling. Full article

Basic and translational cancer biology research requires model systems that recapitulate the features of human tumors. While two-dimensional (2D) cell cultures have been foundational and allowed critical advances, they lack the organizational complexity, cellular interactions, and extracellular matrix present in vivo. Mouse models have thus remained the gold standard for studying cancer. In addition to high cost and low throughput, mouse models can also suffer from reduced tumor heterogeneity and species-specific differences. Three-dimensional (3D) culture models have emerged as a key intermediary between 2D cell lines and mouse models, with lower cost and greater flexibility than mouse models and a more accurate representation of the tumor microenvironment than 2D cell lines. In neuroblastoma, an aggressive childhood cancer, 3D models have been applied to study drug responses, cell motility, and tumor–matrix interactions. Recent advances include the integration of immune cells for immunotherapy studies, mesenchymal stromal cells for tumor–stroma interactions, and bioprinted systems to manipulate matrix properties. This review examines the use of 3D culture systems in neuroblastoma, highlighting their advantages and limitations while emphasizing their potential to bridge gaps between in vitro, preclinical, and clinical applications. By improving our understanding of neuroblastoma biology, 3D models hold promise for advancing therapeutic strategies and outcomes in this childhood cancer. Full article

In order to explore the causative factors of falling accidents at high-rise building construction sites, this study collected 207 reports of these accidents from 2014 to 2024. We used the Human Factor Analysis and Classification System (HFACS) during sample collection, from the four perspectives of organizational impact, unsafe supervision, prerequisites for unsafe behavior, and unsafe behavior. In total, 21 important causal factors were identified, and the samples were classified according to these factors. Descriptive statistics, chi-square testing, and limit matrix analysis were mainly used. SPSS 27.01 was used to analyze the samples, and Super Decisions software was used to normalize the limit supermatrix and calculate the weight. Subsequently, innovative and comprehensive application of chi-square testing and correlation coefficients was applied to determine the correlation of factors, and ANP was used to determine the weight of the factors. According to the weight, we determined the key factors, levels, and paths, and the relationship between the causes of falling accidents in building construction was systematically studied. Finally, based on the key causal path and key factors, a corresponding pre-control strategy was proposed. The results show that the key factors are a lack of awareness of personnel safety, safety education and training, and on-site safety management and an absence of safety inspections and routine maintenance. The key causes are that labor companies are not qualified, there is a lack of on-site safety oversight, and personnel do not have a permit to work at significant heights and do not wear safety protection equipment properly. This study explores the shortcomings of safety management in the construction industry. In order to reduce the accident rate, it is very important to improve the level of decision-making regarding safety management by the government and construction industry. This study has the following limitations: firstly, the information obtained from the investigation report of high-rise building construction accidents is not adequate to fully reflect the situation of workers on-site, which inevitably leads to some deviations. Secondly, due to the high mobility of construction workers, it is very difficult to investigate psychological or physiological states that may have a potential impact on unsafe behavior. Full article

This study explores the information–communication discourse in modern recruitment by applying the Design Thinking (DT) methodology to enhance employee selection and integration strategies. By incorporating digital tools and empathetic approaches, this study examines innovative practices that improve candidate experience and ensure alignment with organizational culture. This study follows the DT framework, encompassing empathy, problem definition, and ideation, with a research sample including candidates, employees, and HR professionals. Methods such as desk research, interviews, diary methods, and P/C matrix diagonalization, supported by original metrics, assess the effectiveness of these approaches. The findings highlight that digital tools, particularly gamification and online assessments, significantly enhance recruitment quality, increase efficiency, reduce hiring time, and improve cultural alignment. Additionally, this study develops informational constructs of knowledge, skills, and attitudes, offering deeper insights into key factors for successful hiring. By integrating new media and technological solutions, this research contributes to transforming traditional recruitment practices into more candidate-centred processes. Further evaluation through complementary studies is recommended to determine the long-term impact of digital tools on recruitment outcomes and employee selection success. Full article

Manufacturing environments, characterized by dynamic changes and uncertainties, demand effective strategies to minimize disruptions. This study introduces an innovative approach that integrates engineering management principles with modular design to prioritize risk mitigation and enhance robustness in manufacturing processes. From a systems engineering perspective, all manufacturing activities are perceived as interconnected components within a unified system. Leveraging the Axiomatic Design (AD) theory and the Design Structure Matrix (DSM) method, the study modularizes manufacturing process architecture to effectively curb risk propagation and manage system complexity. This study identifies the most optimal design as a pivotal architectural configuration, significantly improving the structural robustness and stability of the System of Interest (SOI). Empirical evidence supports this design’s capability to reduce complexities, thereby enhancing robustness within the broader system architecture. Notably, the proposed approach results in a substantial reduction in complexity, with the most optimal design exhibiting an approximately 82.79 percent reduction in work volume compared to the original design. Our research underscores the critical relationship between manufacturing and engineering management. Effective collaboration between these domains optimizes resource allocation, decision-making processes, and overall organizational strategy, leading to improved production processes and increased efficiency. Importantly, the study demonstrates a significant enhancement in modularization, resulting in elevated overall robustness in manufacturing processes. This highlights the proactive involvement of engineering management in the design phase to address production challenges, ultimately optimizing system performance. Thus, this research contributes to both practical applications and academic discourse by offering a novel approach to enhancing the robustness in manufacturing processes. By integrating engineering management principles and modular design strategies, organizations can fortify their processes against disruptions and effectively adapt to evolving circumstances. Full article

Serverless computing services are offered by major cloud service providers such as Google Cloud Platform, Amazon Web Services, and Microsoft Azure. The primary purpose of the services is to offer efficiency and scalability in modern software development and IT operations while reducing overall costs and operational complexity. However, prospective customers often question which serverless service will best meet their organizational and business needs. This study analyzed the features, usability, and performance of three serverless cloud computing platforms: Google Cloud’s Cloud Run, Amazon Web Service’s App Runner, and Microsoft Azure’s Container Apps. The analysis was conducted with a containerized mobile application designed to track real-time bus locations for San Antonio public buses on specific routes and provide estimated arrival times for selected bus stops. The study evaluated various system-related features, including service configuration, pricing, and memory and CPU capacity, along with performance metrics such as container latency, distance matrix API response time, and CPU utilization for each service. The results of the analysis revealed that Google’s Cloud Run demonstrated better performance and usability than AWS’s App Runner and Microsoft Azure’s Container Apps. Cloud Run exhibited lower latency and faster response time for distance matrix queries. These findings provide valuable insights for selecting an appropriate serverless cloud service for similar containerized web applications. Full article

A380-Yb (Ytterbium) alloy was prepared by the ultrasonic melting casting method, and effects of hot extrusion on the microstructure and wear properties of the alloy were studied. The results indicate that the addition of rare earth Yb can refine the microstructure of the matrix alloy. After hot extrusion (extrusion ratio of 22.56) of the as-cast A380-Yb alloy, the secondary phase in its microstructure was further refined and the distribution became more uniform. EBSD (electron backscatter diffraction) organizational analysis shows that the average GND (geometrically necessary dislocation) density of extruded rare earth aluminum alloy is significantly increased, by 16.5 times that of the cast matrix alloy. In addition, there are a large number of grains parallel to the <111> orientation and <001> orientation in the extrusion direction. The alloy undergoes dynamic recrystallization during hot extrusion, and the proportion of small-angle grain boundaries is significantly reduced. Under the same friction and wear conditions, the wear rate and average friction and wear coefficient of the extruded rare earth aluminum alloy are relatively small, reduced by 53.8% and 42.6%, respectively, compared to the cast matrix alloy. Its wear mechanism is mainly abrasive wear and slight plastic deformation. In addition, the study also found that under fixed other wear conditions, as the friction speed increases, the wear rate of the extruded rare earth aluminum alloy shows a trend of first decreasing and then increasing. However, with the increase in load, its wear rate gradually increases, and the change in wear morphology is consistent with the trend of wear rate. When the wear rate is high, the wear mechanism of the extruded aluminum alloy is mainly delamination wear and adhesive wear, and is sometimes accompanied by severe plastic deformation. When the wear rate is low, its wear mechanism is mainly abrasive wear. Full article

Prefabricated construction (PC) is increasingly promoted in the construction sector for its potential benefits, including reduced resource assumption and improved quality. Accordingly, Lean methods are popularly applied to PC projects for optimizing operational processes and enhancing their performance in line with strategic objectives. A key factor in effectively implementing Lean to improve strategic control is developing specific strategies and planning that consider their complex interactions. Thus, this paper aims to propose a quantitative network-based model by integrating Interpretive Structural Modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) under complex network theory to develop a Lean implementation framework for effective strategy formulation. Specifically, 17 Lean implementation strategies for PC in the context of the Chinese prefabrication industry were identified via an extensive literature review and expert interviews. Then, ISM-MICMAC quantitatively identifies the direct and indirect relationships among strategies, while subsequent analysis of Topological Structure Weight (TSW) and Structural Degree Weight (SDW), as complex network parameters, is used to evaluate the importance of each strategy. The findings show that the strategic planning for Lean implementation in PC consists of four levels, i.e., foundation, organizational, technical, and control. Selecting appropriate Lean tools and technologies is crucial for PC implementation, which must be built on a top-level management team and foster a Lean culture. Moreover, it involves building a standardized system of processes and activities, enhancing both internal and external collaboration, and continuously improving processes in response to changes. On one hand, this in-depth network-based analysis offers practical insights for PC stakeholders, particularly in China, on Lean implementation in line with PC performance and strategic control and objectives. On the other hand, the network-based model can be future-implemented globally. Additionally, this study expands the current body of knowledge on Lean in PC by exploring the interrelationships of Lean implementation strategies. Full article

As the importance of defending against cyber attacks has increased, various studies have been conducted to analyze and utilize the reachability between hosts. Although this approach effectively explains asset-based threat responses by security personnel, it is limited as a means of strategic judgment by top decision makers considering the tasks of an organization in a large-scale network environment. The purpose of this study is to develop a method for simplifying the characteristics of the attack paths of a large number of hosts by projecting them to a higher-level organization and aiding in visualizing the impacts of threats. To achieve this, a methodology is presented that supports both strategic judgment by top decision makers, considering the tasks of lower-level organizational units, and asset-based responses. This is accomplished by analyzing asset-based impacts through the generation of a Multi-Step Reachability Matrix (MRM2) and the multi-threat synthesis of low-level threat diffusion paths at the asset level, while gradually abstracting the transition information of the corresponding threats to the higher-level organization. In this paper, the diffusion process is modeled through the connectivity between hosts, and it is expected that this approach will contribute to the development of a decision support model that meets the needs of both upper- and lower-level decision makers. This is achieved by reflecting a variety of factors that influence attack and defense. These factors include the importance of the organization’s mission or business to each asset, the criticality of the system function to which the asset belongs, the dependencies between assets, and the unique characteristics of the asset, including vulnerabilities, exploitation conditions, cyber resilience, and lifecycle costs. Full article

The increasing burden of vascular dysfunction on healthcare systems worldwide results in higher morbidity and mortality rates across pathologies, including cardiovascular diseases. Vasculopathy is suggested to be caused by the dysregulation of vascular niches, a microenvironment of vascular structures comprising anatomical structures, extracellular matrix components, and various cell populations. These elements work together to ensure accurate control of the vascular network. In recent years, autophagy has been recognized as a crucial regulator of the vascular microenvironment responsible for maintaining basic cell functions such as proliferation, differentiation, replicative senescence, and apoptosis. Experimental studies indicate that autophagy activation can be enhanced or inhibited in various pathologies associated with vascular dysfunction, suggesting that autophagy plays both beneficial and detrimental roles. Here, we review and assess the principles of autophagy organization and regulation in non-tumor vascular niches. Our analysis focuses on significant figures in the vascular microenvironment, highlighting the role of autophagy and summarizing evidence that supports the systemic or multiorgan nature of the autophagy effects. Finally, we discuss the critical organizational and functional aspects of the vasculogenic niche, specifically in relation to autophagy. The resulting dysregulation of the vascular microenvironment contributes to the development of vascular dysfunction. Full article