Research on Responsible Innovation Mechanism Based on Prospect Theory

Qu, Xiaoyu; Wang, Xiao; Qin, Xutian

doi:10.3390/su15021358

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…According to the actual conditions, 0 and 1 are the only choices for the three parties' strategies, and at this time, eight equilibrium points can be found at (0,0,0), (0,0,1), (0,1,1), (0,1,0), (1,1,1), (1,0,1), (1,0,1), (1,0,0), and (1,1,0). According to Friedman's theorem, the Jacobi matrix is stable when all the eigenvalues are negative, and it is an unstable point if at least one positive real value appears [29]. The Jacobi matrices of the three-party game are as follows:…”

Section: Jacobi Matrix and Equilibrium Pointsmentioning

confidence: 99%

Research on the Tripartite Evolutionary Game of Zero-Waste City Construction in China

et al. 2023

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The aim in mind in the construction of a zero-waste city is to recycle municipal solid waste in a more reasonable way in order to achieve the sustainable development of the urban environment. This goal is widely used internationally as a green development concept in urban management. However, when only the government takes the lead in the construction process, neglecting to engage and guide the participation of the public and of enterprises, the realization of a zero-waste city becomes challenging. Therefore, effective collaboration among all stakeholders would be a more effective approach to dealing with solid waste and creating an eco-friendly and livable urban environment. In this study, we adopted an evolutionary game model and selected three typical stakeholders—the government, the public, and enterprises—in order to examine the choice of tripartite strategies and their primary influencing factors based on prospect theory. This study found the following: (1) the selection of tripartite strategies at different stages of a zero-waste city’s construction is influenced by the expected benefits and costs; (2) the government’s leading role and related subsidies can promote the enthusiasm of enterprises and the public to participate in the construction of a zero-waste city; (3) tripartite participation in a zero-waste city’s construction can maximize benefits, and after a sustainable development model has been established, each stakeholder can choose to participate actively, even without government intervention; and (4) the construction of a zero-waste city requires long-term exploration and practice, and China is currently in a transition period from government-led to government-directed planning. Establishing a perfect reward and punishment mechanism is beneficial in promoting the active participation of the public and of enterprises. The authors of this paper studied the game process of stakeholders at each stage of a zero-waste city’s construction through prospect theory and explored the influences of important parameters on the strategic choice of each subject at the current stage by conducting numerical simulations, which has implications for the construction and sustainable development of a zero-waste city.

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Section: Jacobi Matrix and Equilibrium Pointsmentioning

confidence: 99%

Research on the Tripartite Evolutionary Game of Zero-Waste City Construction in China

et al. 2023

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“…Liu et al constructed a prospect theory-based game model to incentivize smallholder farmers to transition to green production [32]. Qu et al introduced prospect theory to construct an evolutionary game model and discussed how the government should incentivize firms to innovate [33].…”

Section: Current Study Of Prospect Theorymentioning

confidence: 99%

A Location-Based Crowdsensing Incentive Mechanism Based on Ensemble Learning and Prospect Theory

Liu,

Xu,

Deng

et al. 2023

Mathematics

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Crowdsensing uses the participants’ smart devices to form a new perception network. The coverage of crowdsensing’s tasks determines the quality of services. Under the constraint of budget and the number of participants, the platform needs to increase the participation duration of participants through incentive mechanisms to increase the coverage of tasks. There are two problems with the existing incentive mechanisms: (1) many incentives ignore the participants’ characteristics, and using a single incentive mechanism for different participants will make the incentive effect not reach the expectation; (2) many incentives will affect the effectiveness because of the decision problem caused by asymmetric information. Inspired by ensemble learning and prospect theory, this paper proposes the Incentive Mechanism based on Ensemble Learning and Prospect Theory (IMELPT). First, we propose the Deep-Stacking-Generation algorithm based on Dropout (DSGD), to predict the participants and distinguish whether they are long-term or short-term participants. If the participants are short-term, we incentivize them through the Short-term Participant Incentive Mechanism based on Prospect Theory (SPIMPT). We increase the participation duration by transforming the change in reward into asymmetric information that aligns the participant’s goal with the platform. If the participants are long-term participants, we motivate them through the Long-term Participant Incentive Mechanism (LPIM), to maintain the participation rate of participants by maximizing their utility. Theoretical analysis and experiments on real datasets demonstrated that IMELPT can reliably improve the coverage of crowdsensing tasks.

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Responsible Innovations as Tools for the Management of Financial Risks to Projects of High-Tech Companies for Their Sustainable Development

Popkova,

Xakimova,

Troyanskaya

et al. 2024

Risks

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This paper is devoted to the resolution of the problem of risk management in a high-risk market environment. The goal of this paper was to study the experience of and prospects for the use of responsible innovations as tools for managing the financial risks of high-tech companies’ projects for their sustainable development (using the example of companies in Russia’s IT sphere in 2022–2023). We used the SEM method to study the daily statistics of the Moscow Exchange in 2022–2023. As a result, we quantitatively measured the financial risks of Russian companies in the IT sphere in 2022–2023. The studied case experience of the IT sphere in 2022 confirmed that Russian high-tech companies actively implement responsible innovations based on ESG projects. Our main conclusion is that the financial risks of high-tech companies are reduced in the case of the implementation of responsible innovations. Therefore, it is advisable to implement responsible innovations for the sustainable development of high-tech companies in a high-risk market environment. The theoretical significance of our conclusions lies in the substantiation of the synergetic effect of financial risk management with the help of responsible innovations. The scientific novelty and contribution of this paper to the literature consist in its clarifying the sectorial (in the IT sphere) and market (in a high-risk market environment) specifics of managing the financial risks to companies. We also disclosed a poorly studied and largely unknown unique and leading experience of managing the financial risks of Russian high-tech companies in 2022–2023. The practical significance of our recommendations is that the compiled scenario can be used as a strategic benchmark for the most complete development of the potential of the sustainable development of Russian high-tech companies in 2024.

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Research on Responsible Innovation Mechanism Based on Prospect Theory

Cited by 3 publications

References 22 publications

Research on the Tripartite Evolutionary Game of Zero-Waste City Construction in China

Research on the Tripartite Evolutionary Game of Zero-Waste City Construction in China

A Location-Based Crowdsensing Incentive Mechanism Based on Ensemble Learning and Prospect Theory

Responsible Innovations as Tools for the Management of Financial Risks to Projects of High-Tech Companies for Their Sustainable Development

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