R&D investment decision on smart cities: Energy sustainability and opportunity

2021 ◽  
Vol 153 ◽  
pp. 111554
Author(s):  
Marta Biancardi ◽  
Antonio Di Bari ◽  
Giovanni Villani
Keyword(s):  
Smart Cities ◽  
Investment Decision ◽  
Energy Sustainability ◽  
D Investment

scholarly journals European Option Based R&D Investment Decision Making under Uncertainties

2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Qing Miao ◽  
Boyang Cao ◽  
Minghui Jiang
Keyword(s):  
Decision Making ◽  
Research And Development ◽  
Joint Venture ◽  
Investment Decision ◽  
Optimal Investment ◽  
European Option ◽  
Project Investment ◽  
Research Joint Venture ◽  
Investment Decision Making ◽  
D Investment

This paper establishes the payoff models of the European option for research and development (R&D) projects with two enterprises in a research joint venture (RJV). The models are used to assess the timing and payoffs of the R&D project investment under quantified uncertainties. After the option game, the two enterprises can make optimal investment decision for the R&D project investment in the RJV.

Analyzing Manufacturer’s R&D Equilibrium in Defense Procurement

2011 ◽  
Vol 474-476 ◽  
pp. 1435-1439
Author(s):  
Sheng Li Chen ◽  
Xiao Dong Liu
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Investment Decision ◽  
Investment Decisions ◽  
Defense Procurement ◽  
Contest Theory ◽  
Investment Decision Making ◽  
Admission Criterion ◽  
The Government ◽  
D Investment

We formulate the model of R&D investment scale adjustment of defense procurement by applying game theory and contest theory and study the equilibrium of manufacturers’ R&D investment decision-making in defense procurement. We explore mainly the influence of valuation of monopolistic contract and differences among manufacturers’ abilities on investment. The conclusion shows that manufacturers’ investment equilibrium of R&D projects is what the government expects under certain conditions, however, manufacturers’ abilities effect on the investment equilibrium and makes it deviate from the government expectation. Therefore, the government must keep practically manufacturers’ anticipation about the monopolistic contact being consistent with government’s and set basic admission criterion to enable manufactures’ ability well-matched to induce the manufacturers’ investment decisions to the investment equilibrium that it desired.

R&D investment decisions of IPO firms and long-term future performance

2018 ◽  
Vol 17 (1) ◽  
pp. 78-108 ◽  
Author(s):  
Tatiana Fedyk ◽  
Natalya Khimich
Keyword(s):  
Stock Returns ◽  
Initial Public Offering ◽  
Investment Decision ◽  
Investment Decisions ◽  
Poor Performance ◽  
Net Income ◽  
Cross Sectional ◽  
Content Type ◽  
Public Offering ◽  
D Investment

Purpose The purpose of this paper is to link valuation of different accounting items to research and development (R&D) investment decisions and investigate how suboptimal R&D choices during initial public offering (IPO) are linked to future operating and market underperformance. Design/methodology/approach For firms with substantial growth opportunities, accounting net income is a poor measure of the firm’s performance (Smith and Watts, 1992). Therefore, other metrics such as R&D intensity are used by investors to evaluate firms’ performance. This leads to a coexistence of two strategies: if earnings are the main value driver, firms tend to underinvest in R&D; and if R&D expenditures are the main value driver, firms tend to overinvest in R&D. Findings The authors show that the R&D investment decision varies systematically with cross-sectional characteristics: firms that are at the growth stage, unprofitable or belong to science-driven industries are more likely to overinvest, while firms that are able to avoid losses by decreasing R&D expenditure are more likely to underinvest. Finally, they find that R&D overinvestment leads to future underperformance as evidenced by poor operating return on assets, lower product market share, higher frequency of delisting due to poor performance and negative abnormal stock returns. Originality/value While prior literature concentrates on R&D underinvestment as a tool of reporting higher net income, the authors demonstrate the existence of an alternative strategy used by many IPO firms – R&D overinvestment.

scholarly journals R&D investment decision and optimal subsidy

2001 ◽  
Vol 31 (2) ◽  
pp. 137-148 ◽  
Author(s):  
Jyh‐bang Jou ◽  
Tan Lee
Keyword(s):  
Investment Decision ◽  
D Investment

Performance aspiration, industrial search and R&D investment among chinese firms

2017 ◽  
Vol 11 (2) ◽  
pp. 270-283 ◽  
Author(s):  
Yiyi Su ◽  
Taoyong Su
Keyword(s):  
Investment Decision ◽  
Business Leaders ◽  
Ongoing Research ◽  
Content Type ◽  
Behavioral Determinants ◽  
Investment In China ◽  
The Relationship ◽  
D Investment ◽  
Moderating Role

Purpose This paper aims to examine the behavioral determinants of firm research and development (R&D) investment in China by looking into the interaction between performance aspiration and industrial search. Design/methodology/approach The author argues that the performance aspiration effect is strengthened in R&D-intensive industries based on the isomorphism rationale, whereas it is weakened by high industry R&D intensity owing to the differentiation rationale. Deriving from the isomorphism and differentiation rationales, the author developed a set of competitive hypotheses and empirically tested them by using a large panel data of 6,539 company-years from China for the period 2001-2003. Findings First, R&D intensity is positively related to the deviation of firm performance from aspiration. Second, industry R&D intensity negatively moderates the relationship between performance aspiration and firm R&D intensity for firms performing above aspiration. Therefore, the results provide support for the differentiation rationale. Originality/value The study contributes to the ongoing research that provides and tests the behavioral explanations for R&D and innovation. By delving into the moderating role of industry R&D intensity, the author advocate the need for contextualizing performance aspiration in industrial environments. The study informs policymakers and business leaders about the interaction between the external environment and internal decision process in R&D investment decision.

scholarly journals Energy Sustainability in Smart Cities: Artificial Intelligence, Smart Monitoring, and Optimization of Energy Consumption

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2869 ◽  
Author(s):  
Kwok Tai Chui ◽  
Miltiadis D. Lytras ◽  
Anna Visvizi
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithm ◽  
Urban Space ◽  
Performance Indicators ◽  
Smart Cities ◽  
Hybrid Genetic Algorithm ◽  
Value Added ◽  
Energy Utilization ◽  
Support Vector ◽  
Energy Sustainability

Energy sustainability is one of the key questions that drive the debate on cities’ and urban areas development. In parallel, artificial intelligence and cognitive computing have emerged as catalysts in the process aimed at designing and optimizing smart services’ supply and utilization in urban space. The latter are paramount in the domain of energy provision and consumption. This paper offers an insight into pilot systems and prototypes that showcase in which ways artificial intelligence can offer critical support in the process of attaining energy sustainability in smart cities. To this end, this paper examines smart metering and non-intrusive load monitoring (NILM) to make a case for the latter’s value added in context of profiling electric appliances’ electricity consumption. By employing the findings in context of smart cities research, the paper then adds to the debate on energy sustainability in urban space. Existing research tends to be limited by data granularity (not in high frequency) and consideration of about six kinds of appliances. In this paper, a hybrid genetic algorithm support vector machine multiple kernel learning approach (GA-SVM-MKL) is proposed for NILM, with consideration of 20 kinds of appliance. Genetic algorithm helps to solve the multi-objective optimization problem and design the optimal kernel function based on various kernel properties. The performance indicators are sensitivity (Se), specificity (Sp) and overall accuracy (OA) of the classifier. First, the performance evaluation of proposed GA-SVM-MKL achieves Se of 92.1%, Sp of 91.5% and OA of 91.8%. Second, the percentage improvement of performance indicators using proposed method is more than 21% compared with traditional kernel. Third, results reveal that by keeping different modes of electric appliance as identical class label, the performance indicators can increase to about 15%. Forth, tunable modes of GA-SVM-MKL classifier are proposed to further enhance the performance indicators up to 7%. Overall, this paper is a bold and novel contribution to the debate on energy utilization and sustainability in urban spaces as it integrates insights from artificial intelligence, IoT, and big data analytics and queries them in a context defined by energy sustainability in smart cities.

scholarly journals Contribution of Smart Cities to the Energy Sustainability of the Binomial between City and Country

2019 ◽  
Vol 9 (16) ◽  
pp. 3247 ◽  
Author(s):  
Villa-Arrieta ◽  
Sumper
Keyword(s):  
Urban Areas ◽  
Smart Cities ◽  
Energy Sustainability ◽  
Smart Systems ◽  
Increase Energy Efficiency ◽  
Global Trend ◽  
World Energy ◽  
Population Concentration ◽  
Urban Population Growth ◽  
The Relationship

Cities are at the center of the transition to a decarbonized economy. The high consumption of electricity in these urban areas causes them to be the main focus of greenhouse gas emissions. However, they have a high margin of capacity to increase energy efficiency and local energy generation. Along these lines, the smart urban management model has been proposed as a solution to the unsustainability of cities. Due to the global trend of population concentration in urban areas, cities tend to be representative of the population, energy consumption, and energy sustainability of their countries. Based on this hypothesis, this paper studied the relationship between the smart city model and the concept of energy sustainability. First, the research analyzed the relationship between urban population growth and energy sustainability; and then the self-consumption capacity of photovoltaic electricity of the main cities of the countries classified in the energy sustainability indicator (Energy Trilemma Index 2017) of the World Energy Council was analyzed. According to the results, the scope of action for self-consumption of photovoltaic electricity is broad and cities have the capacity to contribute significantly to the energy sustainability of their countries. Following the approach of other authors, the development of energy sustainability objectives and the installation of smart systems in distribution grids must be aligned with national objectives.

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