Monetization Approach Research Articles

A Fair Crowd-Sourced Automotive Data Monetization Approach Using Substrate Hybrid Consensus Blockchain

This work presents a private consortium blockchain-based automotive data monetization architecture implementation using the Substrate blockchain framework. Architecture is decentralized where crowd-sourced data from vehicles are collectively auctioned ensuring data privacy and security. Smart Contracts and OffChain worker interactions built along with the blockchain make it interoperable with external systems to send or receive data. The work is deployed in a Kubernetes cloud platform and evaluated on different parameters like throughput, hybrid consensus algorithms AuRa and BABE, along with GRANDPA performance in terms of forks and scalability for increasing node participants. The hybrid consensus algorithms are studied in depth to understand the difference and performance in the separation of block creation by AuRa and BABE followed by chain finalization through the GRANDPA protocol.

Monetization of Ecosystem Services from Nature-Based Solutions for Agricultural Diffuse Pollution Control: Simplified Value Transfer Method at European Scale

When nature-based solutions (NBS) are developed with a primary scope, they also provide simultaneous additional economic, social, and environmental benefits, i.e., Ecosystem Services. A monetary assessment that accounts for these additional benefits is provided by this work, with a focus on Europe. Specifically, this is intended to evaluate nine identified benefits of those wetlands and buffer strips designed to primarily address agricultural diffuse pollution, which must surely be listed among the negative externalities of economic activities that NBS can help resolve. The aim of developing a simplified value transfer methodology for a rapid evaluation of NBS benefits with the adjusted unit Value Transfer method is to create an accessible solution when time, funding, or other constraints prevent the use of highly technical primary monetization approaches. The developed exercise allows us to gather insights from several primary valuation studies and to appropriately transfer the monetary valuation outcomes to new policy sites. In order to reduce the distance from the expected and required concrete achievements of the economic valuations, the study has been integrated with an case study located in the Venice lagoon catchment in Northwestern Italy. The results obtained are to be considered sound, with existing evidence showing that the most valuable benefits of the considered NBS are both water quality and recreation and tourism, to which is added, in the case of wetlands, water supply.

Cost–Benefit Analysis of Distributed Energy Systems Considering the Monetization of Indirect Benefits

Driven by market value, a co-benefits assessment framework to encompass various benefits arising from distributed energy systems is developed. Using a monetization approach, a quantitative analysis model is established to evaluate both direct and indirect benefits. According to the simulation results of typical distributed energy systems, the distributed photovoltaic (PV) system demonstrates superior economic performance compared with the gas-fired distributed energy system, highlighting its potential for widespread commercialization. Moreover, the inclusion of indirect benefits significantly enhances the economic viability of the distributed energy system. While the PV system exhibits a more favorable promotional impact, it also renders the gas-fired distributed energy system commercially feasible.

Assessing social performance in supply chain design and planning through a monetization approach

AbstractSustainable development is today a major concern, and within this supply chain’ environmental and social performances need to be considered. The social pillar of the supply chain is not easy to measure, and its quantification is a researcher's challenge. In addition, quantifying the social impact of a monetary unit, easily understood by decision‐makers, is an important step towards achieving global sustainable supply chain performance. This work intends to contribute to this challenge and develops a monetization approach for assessing supply chain's social performance, considering three main relevant social indicators: job creation, accidents and training. These are then integrated into an optimization‐based decision tool that can be used to design and plan a supply chain based on an informed decision. This operation research–based tool considers the economic and the social pillars independently or simultaneously, allowing the development of different analyses to reflect on the different trade‐offs that could be considered when designing and planning sustainable supply chains. A case study is utilized to demonstrate the tool's applicability, and a number of conclusions and insights are provided on how to strengthen supply chain sustainability.

Money Growth and Inflation: A Wavelet Analysis for a Monetization Approach to COVID 19

COVID 19 pandemic will cause a global economic contraction. The magnitude of shocks will impact the fiscal deficit and the public debt in all Countries. This paper provides an insight into the dynamic relationship between money growth and inflation for several Countries. The Morlet wavelet coherence model is employed since it allows the simultaneous examination of lead-lag effects and co-movements between the couple of variables in the different Countries. The overall results do not evidence a clear impact of the money growth on inflation. This outcome has relevant economic policy consequences considering that the monetization of the public debt can sustain the economic recovery. Thus, the pure monetary nature of the inflationary phenomenon can hardly be considered as a constraint in designing the measures to counteract the issue.

Quantifying the Risk of Wildfire Ignition by Power Lines Under Extreme Weather Conditions

Utilities in California conduct public safety power shut-offs (PSPSs) to eliminate the elevated chances of wildfire ignitions caused by power lines during extreme weather conditions. We propose wildfire risk aware operation planning problem (WRAP), which enables system operators to pinpoint the segments of the network that should be de-energized. Sustained wind and wind gust can lead to conductor clashing, which could ignite surrounding vegetation. The 3-D nonlinear vibration equations of power lines are employed to generate a dataset that considers physical, structural, and meteorological parameters. With the help of machine learning techniques, a surrogate model is obtained which quantifies the risk of wildfire ignition by individual power lines under extreme weather conditions. The cases illustrate the superior performance of WRAP under extreme weather conditions in mitigating wildfire risk and serving customers compared to the naive PSPS approach and another method in the literature. Cases are also designated to sensitivity analysis of WRAP to critical load-serving control parameters in different weather conditions. Finally, a discussion is provided to explore our wildfire risk monetization approach and its implications for WRAP decisions.

Application of the ecosystem services concept in stakeholder communication—Results of a workshop including a planning game at the Lower Mulde River (Dessau‐Roßlau, Germany)

AbstractThe concept of ecosystem services (ES) is a powerful tool for communicating with stakeholders because it highlights the benefits of ecosystems for people and demonstrates their economic importance through monetized values. However, this hypothesis has rarely been substantiated in the context of local landscape planning. To investigate which ecosystem services information formats (ESIF) stakeholders prefer in decision situations, we experimented with a highly conflictual planning situation about the Lower Mulde restoration in Germany. We invited local stakeholders to a so‐called ‘future vision workshop’. It included a paper‐based, noncompetitive planning game, which combined the freedom of choice with strict rules for justifying the proposed measures. We tested how often participants used different ESIFs to justify their decisions, focusing on quantification, monetization, and the default qualitative (ordinal‐scaled) format applied in landscape planning. A total of 17 representatives from stakeholder groups such as nature conservation, recreation, and local politics attended. We provided information on four ES and eight related measure proposals to the stakeholders, who used them to select, locate, and justify actions for the area's future development. The participants applied the ordinal‐qualitative format in more than two‐thirds of the decisions. Quantification and monetization were used with approximately equal frequency, mostly for measures that favoured flood risk regulation. Actions supporting habitat provision and biodiversity were justified exclusively in ordinal‐qualitative terms. Instead of our provided quantifications, some participants mentioned numbers they were already familiar with before. They also partly doubted our monetization approaches. In conclusion, we recommend combined and context‐specific uses of several ESIFs, while using the ordinal‐qualitative format as the basis. Furthermore, the participants appreciated the workshop and requested that the results be presented to the city council. The workshop also confirmed that the ES concept is challenging to understand, especially for laypeople unfamiliar with ES and landscape planning.

Applications of TLS and ALS in Evaluating Forest Ecosystem Services: A Southern Carpathians Case Study

Forests play an important role in biodiversity conservation, being one of the main providers of ecosystem services, according to the Economics of Ecosystems and Biodiversity. The functions and ecosystem services provided by forests are various concerning the natural capital and the socio-economic systems. Past decades of remote-sensing advances make it possible to address a large set of variables, including both biophysical parameters and ecological indicators, that characterize forest ecosystems and their capacity to supply services. This research aims to identify and implement existing methods that can be used for evaluating ecosystem services by employing airborne and terrestrial stationary laser scanning on plots from the Southern Carpathian mountains. Moreover, this paper discusses the adaptation of field-based approaches for evaluating ecological indicators to automated processing techniques based on airborne and terrestrial stationary laser scanning (ALS and TLS). Forest ecosystem functions, such as provisioning, regulation, and support, and the overall forest condition were assessed through the measurement and analysis of stand-based biomass characteristics (e.g., trees’ heights, wood volume), horizontal structure indices (e.g., canopy cover), and recruitment-mortality processes as well as overall health status assessment (e.g., dead trees identification, deadwood volume). The paper, through the implementation of the above-mentioned analyses, facilitates the development of a complex multi-source monitoring approach as a potential solution for assessing ecosystem services provided by the forest, as well as a basis for further monetization approaches.

Evaluating the Environmental Impact of Construction within the Industrialized Building Process: A Monetization and Building Information Modelling Approach.

Industrialization has been widely regarded as a sustainable construction method in terms of its environmental friendliness. However, existing studies mainly consider the single impact of greenhouse gas emissions or material consumption in the construction process of industrialized buildings, and pay less attention to ecological pollution and community interest, which leads to an insufficient understanding. There is an urgent need to systematically carry out accurate assessment of comprehensive construction environmental impact within industrialized building processes. Various methods, including face-to-face interviews, field research and building information modeling (BIM), were used for data collection. Four categories selected for the study included resource consumption, material loss, ecological pollution, and community interest. A life cycle assessment (LCA) model, namely input-process-output model (IPO), is proposed to analyze the construction environmental impact of the standard layer of industrialized buildings from four life cycle stages, namely, transportation, stacking, assembly and cast-in-place. The monetization approach of willingness to pay (WTP) was applied to make a quantitative comparison. Results reveal that the assembly stage has the largest impact on the environment at 66.13% among the four life cycle stages, followed by transportation at 16.39%, stacking at 10.29%, and cast-in-place at 7.19%. The key factors include power consumption, noise pollution, material loss, fuel consumption and component loss, which altogether account for more than 85% of the total impact. Relevant stakeholders can conduct their project using the same approach to determine the construction environmental performance and hence introduce appropriate measures to mitigate the environmental burden.

BBVA’s Data Monetization Journey

Data monetization occurs when companies convert data and analytics into financial returns. BBVA, a global financial group, established a data science center of excellence in 2014 to lead its data monetization activities. By 2017, BBVA had developed a rich data monetization portfolio by making preexisting data monetization activities more effective, by pursuing new data monetization approaches, and by investing in a larger number of data monetization projects. Based on BBVA’s efforts, we provide recommendations for others as they embark on their data monetization journeys.

An integrated environmental and health performance quantification model for pre-occupancy phase of buildings in China

To comprehensively pre-evaluate the damages to both the environment and human health due to construction activities in China, this paper presents an integrated building environmental and health performance (EHP) assessment model based on the Building Environmental Performance Analysis System (BEPAS) and the Building Health Impact Analysis System (BHIAS) models and offers a new inventory data estimation method. The new model follows the life cycle assessment (LCA) framework and the inventory analysis step involves bill of quantity (BOQ) data collection, consumption data formation, and environmental profile transformation. The consumption data are derived from engineering drawings and quotas to conduct the assessment before construction for pre-evaluation. The new model classifies building impacts into three safeguard areas: ecosystems, natural resources and human health. Thus, this model considers environmental impacts as well as damage to human wellbeing. The monetization approach, distance-to-target method and panel method are considered as optional weighting approaches. Finally, nine residential buildings of different structural types are taken as case studies to test the operability of the integrated model through application. The results indicate that the new model can effectively pre-evaluate building EHP and the structure type significantly affects the performance of residential buildings.

Free-to-play: About addicted Whales, at risk Dolphins and healthy Minnows. Monetarization design and Internet Gaming Disorder

IntroductionVideo games are not only changing due to technical innovation, but also because of new game design and monetization approaches. Moreover, elite gamer groups with financial in-game-investments co-finance all users of free-to-play-games. Besides questions on youth protection, the growing popularity of free-to-play games has fostered discussions on supposed associations to Internet Gaming Disorder (IGD). MethodChildren and adolescents using free-to-play browser games were examined in a German school-based representative study (N=3967; age range 12 to 18). Based on a clinical self-report AICA-S (Wölfling et al., 2011), students were categorized into non-problematic, risky, and addicted users. Psycho-social problems (SDQ; Goodman, 1997), perceived stress (PSS; Cohen, Kamarck & Mermelstein, 1983), coping strategies (BriefCOPE; Carver, 1997), and Average Revenue per (Paying) User (ARPU) were investigated as dependent variables. Furthermore, an industry classification (Freeloaders, Minnows, Dolphins, and Whales) for free-to-play gamers was used for additional relations regarding IGD, SDQ, PSS, BriefCOPE, and ARPU. ResultsAmong free-to-play gamers the prevalence of IGD amounted to 5.2%. Subjects classified with IGD displayed higher psycho-social symptoms than non-problematic users, reported higher degrees of perceived stress, and applied dysfunctional coping strategies more frequently. Additionally, we found a higher ARPU among subjects with IGD. ConclusionARPU is significantly associated with IGD. Whales share significant characteristics with addicted video gamers; Dolphins might be classified as risky consumers; Minnows and Freeloaders are rather non-pathological gamers. Vulnerability for stress, dysfunctional coping, and free-to-play gaming represent an unhealthy combination.

SensorHUB: An IoT Driver Framework for Supporting Sensor Networks and Data Analysis

The Internet of Things (IoT) is transforming the surrounding everyday physical objects into an ecosystem of information that enriches our everyday life. The IoT represents the convergence of advances in miniaturization, wireless connectivity, and increased data storage and is driven by various sensors. Sensors detect and measure changes in position, temperature, light, and many others; furthermore, they are necessary to turn billions of objects into data-generating “things” that can report on their status and often interact with their environment. Application and service development methods and frameworks are required to support the realization of solutions covering data collection, transmission, data processing, analysis, reporting, and advanced querying. This paper introduces the SensorHUB framework that utilizes the state-of-the-art open source technologies and provides a unified tool chain for IoT related application and service development. SensorHUB is both a method and an environment to support IoT related application and service development; furthermore, it supports the data monetization approach, that is, provides a method to define data views on top of different data sources and analyzed data. The framework is available in a Platform as a Service (PaaS) model and has been applied for the vehicle, health, production lines, and smart city domains.

Multi-objective methods for determining optimal ventilation rates in dwellings

The optimal ventilation rate in a dwelling is a trade-off between the requirement to minimize ventilation heat losses to help meet national greenhouse gas emission targets and the need to minimize adverse health impacts arising from exposure to cold temperatures and pollutants from indoor and outdoor origin. This paper presents approaches for exploring these trade-offs based on two implementations of multi-objective optimization that consider both energy efficiency and health impacts. Both methods aggregate the various performance criteria into a single criterion, but the first method monetizes the performance criteria, while the second method weights them in a more general way.Unlike in the monetization approach, the generalized multi-objective optimization approach is found to be robust against scaling of the health impacts and energy savings that is independent of the ventilation rate. As a result it is less sensitive to assumptions made in the models regarding heating system efficiency, absolute health burden level, and dwelling occupancy. It is however sensitive to assumptions regarding pollutant production rates and balance-point temperatures, which affect health impacts and energy savings in a way correlated with ventilation rate.A preliminary application of the methods to a typical UK flat and detached house finds that the optimal ventilation rate may vary with built form. Application of the generalized multi-objective optimization approach in which health impacts and energy savings are equally weighted, suggests an optimal annual average air change rate of 0.4/h for the detached house, and 0.7/h for the flat.

ASSIST-ME

This paper presents Advanced Software for Statewide Integrated Sustainable Transportation System Monitoring and Evaluation (ASSIST-ME), an application for visualizing and analyzing the output of transportation planning models in a geographic information system environment. ASSIST-ME was developed on a customized version of the ArcGIS 9.2 Developer Engine in the Microsoft .NET Framework. The tool is built on a flexible framework that allows for adoption of any traditional transportation planning model, as demonstrated with the output of two major transportation planning models on different software platforms: the New York Best Practice Model, running in TransCAD, and the North Jersey Regional Transportation Model–Enhanced, running in CUBE. ASSIST-ME allows agencies and planners to easily work with transportation planning model output, analysis of which is often time-consuming and requires extensive training. It offers four key functionalities: data visualization, demand analysis, path analysis, and benefit–cost analysis. Data visualization and demand analysis enable the user to work easily with direct model output; the custom path and cost analysis tools support analyses beyond those possible with other software packages. The benefit–cost analysis functions utilize the latest quantification–monetization approaches employed in research and by government agencies and require no external applications or procedures. This process can be used for any planning scenario, but ASSIST-ME also allows for customization to modify input data or analysis procedures according to the user's needs. ASSIST-ME incorporates data visualization, data analysis, and output reporting functionalities in a single user-friendly setting that requires minimal training or knowledge of the models themselves.

Monetization of health damages from road noise with implications for monetizing health impacts in life cycle assessment

There are decision situations where environmental impacts need to be compared with other costs or benefits that by their nature are expressed in terms of money. Supporting these decisions may require the expression of environmental impacts in monetary units. Using the example of health impacts from road noise we apply five different monetization approaches and quantify the monetary values of one year of sleep disturbance (CHF 2500–16 000) and interference with communication (1500–10 000). In Life Cycle Assessment many health endpoints need to be evaluated at the same time. Therefore, we illustrate here the transferability problem between health impacts measured in disability adjusted life years (DALYs) and monetized health impacts, using the example of health impacts due to 1000 truck kilometres. It is concluded that available monetization methods need careful adaptation for their use to monetize environmental health impacts, that the DALY accounting system may support the systematic monetization and the selection of relevant health endpoints, and that it may well be justified for LCA purposes to perform some novel primary willingness to pay studies.