International Journal of Applied Decision Sciences
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International Journal of Applied Decision Sciences (7 papers in press)
Designing Information Ecosystems to Process Citizen Input and Improve Public Sector Decision Making by Ram Gopalan Abstract: Recent advances in technology and social media have enabled average, individual citizens to forcefully voice their opinions on various public-sector issues. To fully harvest this new tide of technology-enabled activism, information ecosystems must be proactively designed and scientifically managed to receive and process citizen input. In this paper, an activist is a term broadly used to connote any citizen interested in engaging in participative government, usually mediated by the use of technology. The collective set of measures that need to be rigorously undertaken to bring citizen activism to fruition is referred to as activism science in this paper. This position paper examines five case studies wherein citizen activism has already proved successful. The learnings from these case studies leads to a synthetic proposal for managing activism scientifically, incorporating citizen inputs, management science models, technology and data architectures and suitable participative process design. The proposed activism science framework (ASF) is applied to envision improvements in the delivery of online education and urban services. Keywords: Smart government; Open data portals; Public sector decision making. DOI: 10.1504/IJADS.2020.10023336
Probability of Informed Trading: a Bayesian Approach by Pedro Henrique Albuquerque, Yaohao Peng, Eduardo Nakano, Cibele Da-Silva, Leonardo Bosque Abstract: One of the most popular models for measuring information asymmetry of financial assets is the probability of informed trading model (PIN). Its theoretical foundation and its wide possibility of application made PIN a benchmark in insider trading studies. In view of the interpretability of PIN and its parameters, this study aims to evaluate and propose a Bayesian version for the probability of informed trading model. The proposed approach brings the possibility to include expert opinions about PIN parameters and represents a new contribution to the theoretical scope of market microstructure models. Keywords: Probability of Informed Trading; PIN; Bayesian Inference; Market Microstructure Model; Private Information; Information Asymmetry. DOI: 10.1504/IJADS.2020.10023337
Locating and Sizing Electric Vehicles Charging Stations in New Markets by SAFA BHAR LAYEB, MOHAMED AZIZ JEGHAM Abstract: In countries where there are a handful of electric vehicles (EV), installing appropriately charging stations could promote the usage of this emergent technology. In this work, we address the problem of locating and sizing EV charging stations in the specific context of a virgin market. First, we forecast the percentage of electric vehicles using a Bass diffusion model (BDM). Once the EV demand properly predicted, we adopt a set-covering-based approach through the formulation of linear programming models to locate and size the potential EV charging stations. The objective is to reduce weighted installation and access costs while ensuring that the stations are within a comfortable reach for the EV users. Without any loss of generality, we apply the overall scheme on the real case study of Tunis City, Tunisia, to propose the appropriate charging infrastructure deployment for the year 2025. Keywords: Transportation; Electric Vehicles; Charging Stations Locations; Linear Programming; Bass Diffusion Model. DOI: 10.1504/IJADS.2020.10023338
An Integrated Fuzzy Multi-criteria Decision Making Approach for Evaluating Suppliers Co-design ability in New Product Development by Detcharat Sumrit Abstract: There are many methods for managing the complexity and challenges of new product development (NPD) under faster emerging technology. Most firms use them to collaborate with external organisations for their co-design on new products. This study purposes to provide a measurement model by applying multi-criteria decision making (MCDM) approach to evaluate suppliers co-design capabilities in NPD in terms of product structural design and engineering, product concept and functional design, and process design. This MCDM includes fuzzy step-wise weight assessment ratio analysis (SWARA) to determine the relative weights of criteria and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) to rank the results of suppliers capabilities regarding to their co-design in NPD. Given the result, supplier with the highest collaboration performance rating is selected at first. The evaluation of suppliers collaboration is regarded as an essential starting point for management challenge to develop suppliers capabilities. Keywords: MCDM; multi-criteria decision making; Fuzzy SWARA; step-wise weight assessment ratio analysis; Fuzzy TOPSIS; technique for order preference by similarity to an ideal solution; new product development. DOI: 10.1504/IJADS.2020.10023340
A bi-level programming model of rough stochastic MRCPSP in large-scale hydropower construction project by Zhe Zhang, Xiaoling Song Abstract: This paper focuses on developing a bi-level programming model for rough stochastic multi-mode resource constrained project scheduling problem (RS-MRCPSP/bi-level). The metal structure installation project (MSIP) in Wudongde Hydropower Station is considered as the prototype, and then it is extended to be a generalised bi-level MRCPSP. In the upper level, the construction contractor is responsible for the investment on the activity, while the outsourcing partner is in charge of construction and implementation in the lower level. In order to deal with the rough stochastic parameters, the rough stochastic expected value operator is employed. Subsequently, in order to obtain the optimal schedule, an interactive method-based passive congregation particle swarm optimisation (IM-based PCPSO) is designed. Finally, a practical application for MSIP is presented to highlight the practicability of proposed model and solution method. Keywords: bi-level programming; multi-mode; RCPSP; rough stochastic parameters; PSO. DOI: 10.1504/IJADS.2020.10024139
Multifactor Capital Asset Pricing Model in Emerging and Advanced Markets using Two Error Components Model by Woraphon Yamaka, Songsak Sriboonchitta, Wachirawit Puttachai, Radamanee Noppasit, Paravee Maneejuk Abstract: We aim to explore the macroeconomic factors that are able to influence the return of the stock market in emerging and advanced markets. To find such factors, we analyse the data from three emerging countries and three developed countries. The multifactor capital asset pricing model (CAPM), which includes the overall market return and the selected macroeconomic variables, is employed to achieve our study. However, the assumption of CAPM, which displayed only one error term, has been concerned in our analysis as one error term may fail to capture and define the whole erroneousness in the model. Thus, we prove the existence of the second error components of the CAPM. In addition, the concept of a seemingly unrelated regression (SUR) model is also applied to join the CAPM of each country. As a consequent, we propose a new SUR model which compounds two errors to investigate the multifactor CAPM. Keywords: Emerging and Advanced Markets; Multifactor CAPM; Copula Approach; Seemingly Unrelated Regressions; Two Errors Component Model. DOI: 10.1504/IJADS.2020.10025015
A Bi-level Optimal Scheduling Model for Virtual Power Plants and Conventional Power Plants Considering Environmental Constraints and Uncertainty by Linpeng Nie, Huijuan Huo, Jun Dong Abstract: To effectively realise the distributed energy resources participating in the system scheduling and reduce pollutant emissions from conventional plants, a bi-level stochastic optimal model for conventional plants and VPPs was built considering the uncertainty and environmental constraints. Firstly, a method of scenario generation and reduction is proposed to simulate the output of WPP and PV based on interval method and Kantorovich distance. Secondly, a bi-level stochastic optimal scheduling model for VPPs and conventional plants in a day-ahead plan is constructed. Finally, different simulation scenarios are designed to verify the effectiveness of the proposed model. The results illustrate that the model can overcome the influence of uncertainty and realise optimal economic jointly dispatch for VPPs and conventional plants under environmental constraints, through VPP technology, distributed power generation resources can be integrated effectively and have good environmental effect. Plants with high environmental performance will gain a larger share and generate more power. Keywords: Environment economic dispatching; Virtual power plant; Stochastic programming; bi-level Model; Uncertainty.