Computational simulation and risk analysis: An introduction of state of the art research

Creating Quality-Based Smart Sustainable Public Parking Enterprises: A Methodology to Reframe Organizations into Smart Organizations

Enterprise sustainability is a key aim in the fourth industrial revolution era, requiring a new approach based on intelligent technologies that considers the new roles of leadership and sustainability as well as the new trends in emerging smart technologies, with a new focus on Society 5.0. Smart parking has a significant role in fostering the determinants of sustainability in public parking enterprises and achieving adequate mobility in smart cities. Thus, smart parking is the subject of the research presented in this paper. This study defines the vital processes, including leadership processes and technologies needed for smart parking, managed by innovative public parking enterprises. Having this in mind, trends, key facts, the results of present innovative technology enterprises, and methodologies for designing and establishing smart public parking enterprises are analyzed. This paper aims to determine the sustainability of parking enterprises in their current states by developing a MORSO methodology. The MORSO methodology includes independent variables, including the leadership level of the intelligent technologies used, quality of the business processes, and risk related to the business processes, and a dependent variable, the sustainability of smart public parking enterprises. The MORSO methodology also includes steps for the definition of indices related to variables that could be assessed by appropriate techniques such as using questionnaires. Finally, the MORSO methodology introduces steps by which statistical approaches and artificial neural networks (ANN) are applied to test hypotheses regarding correlations between independent and dependent variables. The results of the presented model case study application show that there are strong correlations between smart sustainability and leadership (0.769), quality (0.904), and risk (−0.884), respectively. Additionally, at the level of the presented case study, the results of the application of the ANN indicate that the values of the dependent variable in the following time period can be determined with high accuracy, based on the knowledge of the values from the previous period, with a regression coefficient value of R = 0.99482. Finally, in this way, the transition from existing public enterprises to sustainable smart public parking enterprises is envisioned.

Data Science for Finance: Best-Suited Methods and Enterprise Architectures

We live in an era of big data. Large volumes of complex and difficult-to-analyze data exist in a variety of industries, including the financial sector. In this paper, we investigate the role of big data in enterprise and technology architectures for financial services. We followed a two-step qualitative process for this. First, using a qualitative literature review and desk research, we analyzed and present the data science tools and methods financial companies use; second, we used case studies to showcase the de facto standard enterprise architecture for financial companies and examined how the data lakes and data warehouses play a central role in a data-driven financial company. We additionally discuss the role of knowledge management and the customer in the implementation of such an enterprise architecture in a financial company. The emerging technological approaches offer opportunities for finance companies to plan and develop additional services as presented in this paper.

The ALARP Principle in the Cost-Benefit Analysis for the Acceptability of Investment Risk

The process of allocating financial resources is extremely complex—both because the selection of investments depends on multiple, and interrelated, variables, and constraints that limit the eligibility domain of the solutions, and because the feasibility of projects is influenced by risk factors. In this sense, it is essential to develop economic evaluations on a probabilistic basis. Nevertheless, for the civil engineering sector, the literature emphasizes the centrality of risk management, in order to establish interventions for risk mitigation. On the other hand, few methodologies are available to systematically compare ante and post mitigation design risk, along with the verification of the economic convenience of these actions. The aim of the paper is to demonstrate how these limits can be at least partially overcome by integrating, in the traditional Cost-Benefit Analysis schemes, the As Low as Reasonably Practicable (ALARP) logic. According to it, the risk is tolerable only if it is impossible to reduce it further or if the costs to mitigate it are disproportionate to the benefits obtainable. The research outlines the phases of an innovative protocol for managing investment risks. On the basis of a case study dealing with a project for the recovery and transformation of an ancient medieval village into a widespread-hotel, the novelty of the model consists of the characterization of acceptability and tolerability thresholds of the investment risk, as well as its ability to guarantee the triangular balance between risks, costs and benefits deriving from mitigation options.

The dynamic links between carbon dioxide (CO2) emissions, health spending and GDP growth: A case study for 51 countries

This document investigated the causal relationship between carbon dioxide (CO₂) emissions, health spending and GDP growth for 51 countries (divided into three groups of countries: low-income countries; group of countries with lower and upper middle income; group of middle income countries) covering the annual period 1995-2013. Dynamic simultaneous-equations models and generalized method of moments (GMM) are used to investigate this relationship. The main results provide evidence of a causal relationship between the three variables. The empirical results show that there is a bidirectional causality between CO₂ emissions and GDP per capita, between health spending and economic growth for the three groups of estimates. The results also indicate that there is a unidirectional causality from CO₂ emissions to health spending, except low income group countries. We found that health plays an important role in GDP per capita; it limits its effect on a growing deterioration in the quality of the environment.

Highlighting Relationships of a Smartphone's Social Ecosystem in Potentially Large Investigations

Social media networks are becoming increasingly popular because they can satisfy diverse needs of individuals (both personal and professional). Modern mobile devices are empowered with increased capabilities, taking advantage of the technological progress that makes them smarter than their predecessors. Thus, a smartphone user is not only the phone owner, but also an entity that may have different facets and roles in various social media networks. We believe that these roles can be aggregated in a single social ecosystem, which can be derived by the smartphone. In this paper, we present our concept of the social ecosystem in contemporary devices and we attempt to distinguish the different communities that occur from the integration of social networking in our lives. In addition, we propose techniques to highlight major actors within the ecosystem. Moreover, we demonstrate our suggested visualization scheme, which illustrates the linking of entities that live in separate communities using data taken from the smartphone. Finally, we extend our concept to include various parallel ecosystems during potentially large investigations and we link influential entities in a vertical fashion. We particularly examine cases where data aggregation is performed by specific applications, producing volumes of textual data that can be analyzed with text mining methods. Our analysis demonstrates the risks of the rising "bring your own device" trend in enterprise environments.

Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management

In the big data era, systems reliability is critical to effective systems risk management. In this paper, a novel multiobjective approach, with hybridization of a known algorithm called NSGA-II and an adaptive population-based simulated annealing (APBSA) method is developed to solve the systems reliability optimization problems. In the first step, to create a good algorithm, we use a coevolutionary strategy. Since the proposed algorithm is very sensitive to parameter values, the response surface method is employed to estimate the appropriate parameters of the algorithm. Moreover, to examine the performance of our proposed approach, several test problems are generated, and the proposed hybrid algorithm and other commonly known approaches (i.e., MOGA, NRGA, and NSGA-II) are compared with respect to four performance measures: 1) mean ideal distance; 2) diversification metric; 3) percentage of domination; and 4) data envelopment analysis. The computational studies have shown that the proposed algorithm is an effective approach for systems reliability and risk management.

It's hard to be green: Reverse green value chain

Firms have recently discovered that it is not enough to optimize internal processes and relationships with partners along the value chain to create a sustainable competitive market position. A clear customer orientation, which acknowledges that consumer buying behavior is complex and includes many elements implied in the value chain, is required. As companies offering green products are no exception to this rule, this study analyzes consumer behavior in Europe from a reserve green supply chain management perspective, using descriptive analyses and a structural equation model, with data collected by Flash Barometer comprising 26,573 responses from 28 European countries. The results suggest that European consumers are conscious of the green concept, but are not willing to buy or pay more for these products since the value is unclear. Companies offering green products must therefore rethink their strategies, especially in terms of value proposition, communication strategies, and eco-labeling.