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4 Small and Medium-Sized Enterprises, Flash Flooding and Organisational Resilience Capacity: Qualitative Findings on Implications of the Catastrophic 2017 Flash Flood Event in Mandra, Greece
Authors: Antonis Skouloudis, Georgios Deligiannakis, Panagiotis Vouros, Konstantinos Evangelinos, Ioannis Nikolaou
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On November 15th, 2017, a catastrophic flash flood devastated the city of Mandra in Central Greece, resulting in 24 fatalities and extensive damages to the built environment and infrastructure. It was Greece’s deadliest and most destructive flood event for the past 40 years. In this paper, we examine the consequences of this event to small and medium-sized enterprises (SMEs) operating in Mandra during the flood event, which were affected by the floodwaters to varying extents. In this context, we conducted semi-structured interviews with business owners-managers of 45 SMEs located in flood inundated areas and are still active nowadays, based on an interview guide that spanned 27 topics. The topics pertained to the disaster experience of the business and business owners-managers, knowledge and attitudes towards climate change and extreme weather, aspects of disaster preparedness and related assistance needs. Our findings reveal that the vast majority of the affected businesses experienced heavy damages in equipment and infrastructure or total destruction, which resulted in business interruption from several weeks up to several months. Assistance from relatives or friends helped for the damage repairs and business recovery, while state compensations were deemed insufficient compared to the extent of the damages. Most interviewees pinpoint flooding as one of the most critical risks, and many connect it with the climate crisis. However, they are either not willing or unable to apply property-level prevention measures in their businesses due to cost considerations or complex and cumbersome bureaucratic processes. In all cases, the business owners are fully aware of the flood hazard implications, and since the recovery from the event, they have engaged in basic mitigation measures and contingency plans in case of future flood events. Such plans include insurance contracts whenever possible (as the vast majority of the affected SMEs were uninsured at the time of the 2017 event) as well as simple relocations of critical equipment within their property. The study offers fruitful insights on latent drivers and barriers of SMEs’ resilience capacity to flash flooding. In this respect, findings such as ours, highlighting tensions that underpin behavioural responses and experiences, can feed into: a) bottom-up approaches for devising actionable and practical guidelines, manuals and/or standards on business preparedness to flooding, and, ultimately, b) policy-making for an enabling environment towards a flood-resilient SME sector.
Keywords: Flash flood, small and medium-sized enterprises, organisational resilience capacity, disaster preparedness, qualitative study.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4913 Blockchain Based Hydrogen Market: A Paradigm-Shifting Innovative Solution for Climate-Friendly and Sustainable Structural Change
Authors: Volker Wannack
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Regional and global strategies focusing on hydrogen (H2) and blockchain technologies are fueling remarkable advancements. These strategies underpin the revolutionary 'Blockchain Based Hydrogen Market (BBH2)' project, with the primary objective of creating a Blockchain Minimum Viable Product (B-MVP) tailored to the hydrogen market. The B-MVP harnesses blockchain's capabilities, establishing a unified platform for secure, automated transactions via smart contracts. This innovation promises to reshape hydrogen logistics, trade, and transactions. The B-MVP carries transformative potential across diverse sectors, benefiting renewable energy producers, surplus energy-based hydrogen manufacturers, grid operators, and consumers. By implementing standardized, automated, tamper-proof processes, it bolsters cost-efficiency and enables transparent, traceable transactions. Its core mission is to verify the integrity of 'green' hydrogen, tracing its journey from renewable producers to end-users. This emphasis on transparency fosters economic, ecological, and social sustainability within a secure, transparent market. A standout feature of the B-MVP is its cross-border adaptability, obviating the need for nation-specific data storage, and broadening its global reach. This adaptability also spurs long-term job creation by establishing a dedicated blockchain operating firm. By attracting skilled labor and offering training, the B-MVP fortifies the hydrogen sector's workforce. Furthermore, it catalyzes innovative business models, luring more companies and startups, contributing to sustained job growth. For example, data analysis can tailor tariffs to offer demand-centric network capacities to producers and operators, providing tamper-proof pricing options to redistributors and end-customers. Beyond technological and economic progress, the B-MVP amplifies the prominence of national and international standards efforts. The region implementing the B-MVP becomes recognized as a pioneer in climate-friendly, sustainable, and forward-thinking practices, generating interest and attention beyond its geographic boundaries. Additionally, it fosters knowledge transfer between academia and industry, promoting scientific advancements, aligning with innovation management, and nurturing an innovation culture in the hydrogen sector. Through blockchain-hydrogen integration, the B-MVP champions comprehensive innovation, contributing to a sustainable future in the hydrogen industry. Implementation involves evaluating blockchain tech, developing smart contracts, and ensuring interoperability with existing systems. Scalability testing and data format development further validate the B-MVP's potential. BBH2 secures funding under the 'Technology Offensive Hydrogen,' a part of the Federal Ministry of Economics and Climate Protection's 7th Energy Research Program.
Keywords: Hydrogen, blockchain, sustainability, structural change.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1582 Affordable and Environmental Friendly Small Commuter Aircraft Improving European Mobility
Authors: Diego Giuseppe Romano, Gianvito Apuleo, Jiri Duda
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Mobility is one of the most important societal needs for amusement, business activities and health. Thus, transport needs are continuously increasing, with the consequent traffic congestion and pollution increase. Aeronautic effort aims at smarter infrastructures use and in introducing greener concepts. A possible solution to address the abovementioned topics is the development of Small Air Transport (SAT) system, able to guarantee operability from today underused airfields in an affordable and green way, helping meanwhile travel time reduction, too. In the framework of Horizon2020, EU (European Union) has funded the Clean Sky 2 SAT TA (Transverse Activity) initiative to address market innovations able to reduce SAT operational cost and environmental impact, ensuring good levels of operational safety. Nowadays, most of the key technologies to improve passenger comfort and to reduce community noise, DOC (Direct Operating Costs) and pilot workload for SAT have reached an intermediate level of maturity TRL (Technology Readiness Level) 3/4. Thus, the key technologies must be developed, validated and integrated on dedicated ground and flying aircraft demonstrators to reach higher TRL levels (5/6). Particularly, SAT TA focuses on the integration at aircraft level of the following technologies [1]: 1) Low-cost composite wing box and engine nacelle using OoA (Out of Autoclave) technology, LRI (Liquid Resin Infusion) and advance automation process. 2) Innovative high lift devices, allowing aircraft operations from short airfields (< 800 m). 3) Affordable small aircraft manufacturing of metallic fuselage using FSW (Friction Stir Welding) and LMD (Laser Metal Deposition). 4) Affordable fly-by-wire architecture for small aircraft (CS23 certification rules). 5) More electric systems replacing pneumatic and hydraulic systems (high voltage EPGDS -Electrical Power Generation and Distribution System-, hybrid de-ice system, landing gear and brakes). 6) Advanced avionics for small aircraft, reducing pilot workload. 7) Advanced cabin comfort with new interiors materials and more comfortable seats. 8) New generation of turboprop engine with reduced fuel consumption, emissions, noise and maintenance costs for 19 seats aircraft. (9) Alternative diesel engine for 9 seats commuter aircraft. To address abovementioned market innovations, two different platforms have been designed: Reference and Green aircraft. Reference aircraft is a virtual aircraft designed considering 2014 technologies with an existing engine assuring requested take-off power; Green aircraft is designed integrating the technologies addressed in Clean Sky 2. Preliminary integration of the proposed technologies shows an encouraging reduction of emissions and operational costs of small: about 20% CO2 reduction, about 24% NOx reduction, about 10 db (A) noise reduction at measurement point and about 25% DOC reduction. Detailed description of the performed studies, analyses and validations for each technology as well as the expected benefit at aircraft level are reported in the present paper.
Keywords: Affordable, European, green, mobility, technologies development, travel time reduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5371 Using Statistical Significance and Prediction to Test Long/Short Term Public Services and Patients Cohorts: A Case Study in Scotland
Authors: Sotirios Raptis
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Health and Social care (HSc) services planning and scheduling are facing unprecedented challenges, due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven approaches can help to improve policies, plan and design services provision schedules using algorithms that assist healthcare managers to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as Classification and Regression Trees (CART), Random Forests (RF), and Logistic Regression (LGR). The significance tests Chi-Squared and Student’s test are used on data over a 39 years span for which data exist for services delivered in Scotland. The demands are associated using probabilities and are parts of statistical hypotheses. These hypotheses, as their NULL part, assume that the target demand is statistically dependent on other services’ demands. This linking is checked using the data. In addition, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus, groups of services. Statistical tests confirmed ML coupling and made the prediction statistically meaningful and proved that a target service can be matched reliably to other services while ML showed that such marked relationships can also be linear ones. Zero padding was used for missing years records and illustrated better such relationships both for limited years and for the entire span offering long-term data visualizations while limited years periods explained how well patients numbers can be related in short periods of time or that they can change over time as opposed to behaviours across more years. The prediction performance of the associations were measured using metrics such as Receiver Operating Characteristic (ROC), Area Under Curve (AUC) and Accuracy (ACC) as well as the statistical tests Chi-Squared and Student. Co-plots and comparison tables for the RF, CART, and LGR methods as well as the p-value from tests and Information Exchange (IE/MIE) measures are provided showing the relative performance of ML methods and of the statistical tests as well as the behaviour using different learning ratios. The impact of k-neighbours classification (k-NN), Cross-Correlation (CC) and C-Means (CM) first groupings was also studied over limited years and for the entire span. It was found that CART was generally behind RF and LGR but in some interesting cases, LGR reached an AUC = 0 falling below CART, while the ACC was as high as 0.912 showing that ML methods can be confused by zero-padding or by data’s irregularities or by the outliers. On average, 3 linear predictors were sufficient, LGR was found competing well RF and CART followed with the same performance at higher learning ratios. Services were packed only when a significance level (p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, low birth weights, alcoholism, drug abuse, and emergency admissions. The work found that different HSc services can be well packed as plans of limited duration, across various services sectors, learning configurations, as confirmed by using statistical hypotheses.
Keywords: Class, cohorts, data frames, grouping, prediction, probabilities, services.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 460