Incentive Model Research Articles

Інтеграція водневих технологій у транспортні двигуни внутрішнього згоряння: аналіз впливу на ефективність та екологічність

This article delves into the promising realm of hydrogen technologies in the transportation sector, highlighting their potential to significantly reduce harmful emissions and promote sustainable development. The discussion begins with a comprehensive review of current hydrogen internal combustion engine (ICE) technologies, examining the advancements that have been made and the technical solutions available to enhance the efficiency of these engines. It underscores the environmental benefits of hydrogen ICEs, such as the reduction of greenhouse gases and pollutants, and explores the economic advantages, including decreased dependency on fossil fuels and the creation of new job opportunities. Furthermore, the article discusses the social benefits of adopting hydrogen technologies, such as improved public health and the potential for innovation-driven economic growth. It also addresses the significant infrastructural challenges associated with the production, storage, transportation, and distribution of hydrogen. Potential solutions to these challenges are proposed, including investments in new technologies, expansion of production capacities, and the development of specialized infrastructure. The article provides detailed case studies of successful hydrogen technology implementations in various countries. In Japan, hydrogen-powered buses in Tokyo demonstrate the environmental and technological advancements achieved. Germany’s hydrogen trains by Alstom illustrate the transition from diesel to hydrogen in public transportation, showcasing economic and ecological benefits. South Korea's hydrogen taxis in Seoul highlight the social impact and infrastructural development necessary for widespread adoption. Lastly, California’s extensive network of hydrogen fueling stations supports the growing number of hydrogen cars, reflecting a successful model of public-private partnership and government incentives. Through these case studies, the article emphasizes the transformative potential of hydrogen technologies in creating a sustainable and clean future for transportation. It calls for continued investments in technology, infrastructure, and collaboration between governments and the private sector to overcome existing challenges and fully realize the benefits of hydrogen as a key energy source in the transportation sector.

Research on incentive and technological innovation models of biopharmaceutical companies

This article selects biopharmaceutical enterprises listed in high-tech industry as samples, using the Heckman selection model effectively avoid sample bias and according to linear analysis, this research tests the influence between senior management incentives and technological innovation based on the Chinese biopharmaceutical enterprises listed in high tech industry in a certain period. The empirical research results indicate that there is not a simple linear correlation between short-term salary incentives and technological innovation, and there is a curve relationship that first decreases and then increases among them; Long term equity incentives have a significant positive impact on technological innovation. This research aimed to find the maximum value of incentives, propose countermeasures and suggestions to avoid excessive salary incentives, appropriately improve the level of stock-based compensation, and establish a reasonable senior management incentive system for insight.

ТРУД И ЭКОНОМИЧЕСКИЕ ЦИКЛЫ – СИСТЕМНОЕ ВИДЕНИЕ

The subject of the study is the labor crisis as a permanent phenomenon of development economics, which is updated during periods of large-scale innovative transformations. The purpose of the paper is to develop a systematic understanding of the labor crisis. The relevance of the study is due to the aggravation of the labor crisis in the context of the emerging change in the technological structure. The scientific novelty lies in the development of a systematic understanding of the labor crisis and its socio-economic consequences. The research methods are system analysis, factor analysis, methods of expert assessments, and public opinion polls. The theoretical significance of the study is associated with determining the origins of the labor crisis and its substantive characteristics. The practical significance of the paper lies in the application of the research results to develop management decisions to quickly overcome the labor crisis. Of practical interest are recommendations for improving the system of professional training and retraining, and improving incentive models to achieve an increase in the level of personnel competence in the context of accelerating innovative development.

Trade credit contracting in a risk-averse supply chain under adverse selection and moral hazard

Trade credit, as an effective tool for integrating and coordinating material, information, and financial flows in supply chain management, is becoming increasingly widespread. We explore how a manufacturer can design optimal trade credit contracts when a risk-averse retailer hides its sales cost information (adverse selection) and selling effort level (moral hazard). We develop incentive models for a risk-averse supply chain when adverse selection and moral hazard coexist, which are then compared with the results under single information asymmetry (moral hazard). Moreover, we analyze the effects of private information and risk-aversion coefficient on contract parameters, selling effort level and the profit or utility of the supply chain. The study shows that when the degree of retailer’s risk aversion is within a certain range, reasonable trade credit contracts designed by the manufacturer can effectively induce the retailer to report its real sales cost and encourage it to exert appropriate effort. Furthermore, we find that the optimal trade credit period, optimal transfer payment, and retailer’s optimal sales effort level under dual information asymmetry are less than under single information asymmetry. Numerical analysis are conducted to demonstrate the effects of the parameters on decisions and profits.

Identification of cancer driver genes based on dynamic incentive model.

Cancer is a complex genomic mutation disease, and identifying cancer driver genes promotes the development of targeted drugs and personalized therapies. The current computational method takes less consideration of the relationship among features and the effect of noise in protein-protein interaction(PPI) data, resulting in a low recognition rate. In this paper, we propose a cancer driver genes identification method based on dynamic incentive model, DIM. This method firstly constructs a hypergraph to reduce the impact of false positive data in PPI. Then, the importance of genes in each hyperedge in hypergraph is considered from three perspectives, network and functional score(NFS) is proposed. By analyzing the relation among features, the dynamic incentive model is proposed to fuse NFS, the differential expression score of mRNA and the differential expression score of miRNA. DIM is compared with some classical methods on breast cancer, lung cancer, prostate cancer, and pan-cancer datasets. The results show that DIM has the best performance on statistical evaluation indicators, functional consistency and the partial area under the ROC curve, and has good cross-cancer capability.

A dynamic incentive mechanism for data sharing in manufacturing industry

Data sharing is a critical component in a blockchain traceability platform. Therefore, creating a reasonable incentive mechanism to ensure that all enterprises participate in data sharing is vital for blockchain platforms. Currently, many researchers employ evolutionary game theory to analyze problems related to data sharing. However, evolutionary game theory typically assumes that the population composed of enterprises is mixed uniformly. Enterprises in the manufacturing industry are not uniformly mixed, as they tend to have specific connections with each other due to the size of enterprises and volume of business. Therefore, a networked evolutionary game is introduced to solve this problem. Firstly, an incentive model for enterprises sharing data is established. Then, a scale-free network is employed to simulate the connections between enterprises. To comprehensively consider the individual and group benefits of enterprises in the game, this study designs a strategy update rule for networked evolutionary game based on Discrete Particle Swarm Optimization and Variable Neighborhood Descent algorithm. To tackle the challenge of determining reasonable incentive values in networked evolutionary games, this study proposes a dynamic incentive mechanism based on the Q-Learning algorithm. Finally, the experiments indicate that this method can successfully facilitate the stable involvement of enterprises in data sharing.

Enterprise Performance Management and Evaluation Incentive Model for Blockchain Technology and Big Data Algorithms

Enterprise Performance Management and Evaluation Incentive Model for Blockchain Technology and Big Data Algorithms

Data Sharing Scheme of Smart Grid Based on Identity Condition Proxy Re-Encryption

A large amount of high-value data are stored in smart grid data centers, but since the resource diversity of a single data center is limited, data sharing becomes especially important in conducting an effective data mining process. However, traditional data-sharing models often use centralized schemes without authentication of the shared objects, making it difficult to establish trust relationships and ensure data privacy. This makes it difficult to break through the problem of data islands. To solve the above problems, this paper proposes a blockchain-based data-sharing incentive model for edge smart grid scenarios. First, the model uses blockchain and proxy re-encryption technology to achieve the security and traceability of the smart grid data-sharing process. Secondly, the data-sharing incentive algorithm is designed using game theory to maximize the willingness of data owners to share data. Finally, the model in this paper is compared and analyzed with other existing data-sharing models, and the designed performance test shows that the scheme in this paper has significant advantages over the other literature schemes in terms of functionality and computational overhead, and the increase in costs is not significant, and the model can meet the requirements for large-scale data sharing in edge smart grid scenarios.

Research and Application of Performance Pay Platform Construction for College Teaching Staff Counting and Multi-scale Feature Fusion Networks

Abstract In this paper, a multi-scale feature fusion network is constructed by combining U-Net and Densebox algorithms, and feature extraction is performed by the deep residual network (ResNet). Taking colleges and universities as an example, a teacher reputation incentive model combining a multi-scale feature fusion network is established based on marginal productivity. The multi-scale feature fusion network is proposed to be used to realize the employee performance measurement level and personal appraisal system in the salary performance appraisal platform for teachers in colleges and universities. The appraisal test analysis of the teacher team’s performance and salary was carried out with the teacher team of School G as an example. The results show that the starting salary points of B1, C1, and D1 of the teacher team of school G are 2250, 1650, and 1260, respectively, in which the median difference in salary value between the highest grade B1 (9618) and the lowest grade I2 (784) is 8834 yuan. The performance pay management platform constructed in this paper effectively provides incentives and promotes the high-quality development of the university teaching team through strict assessment and fair distribution.

A configurational perspective on design elements and user governance engagement in blockchain platforms

AbstractBlockchain technology offers the potential to create an open, decentralised governance structure that empowers stakeholders to participate in decentralised engagement. However, how blockchain platforms configure their design elements to establish and maintain decentralised systems with high levels of user governance engagement requires further research. This study investigates the key design elements of blockchain platforms and their ideal configurations for promoting user governance engagement. Due to the complex and interdependent nature of the design elements, we adopt a configurational perspective accompanied by a fuzzy set qualitative comparative analysis (fsQCA) to uncover complex nonlinear relationships among key conditions that are relevant to decentralised governance. Our research identifies five key design elements that facilitate distributed governance (Access to decision rights, Process visibility, Protocol automation, Incentives for developers/miners, and Incentives for other stakeholders) based on existing blockchain governance literature. We analyse 14 unique blockchain platform cases that adopted on‐chain governance. Our fsQCA results reveal three ideal types of blockchain governance configurations that are sufficient for high generative user governance engagement: Centralised incentive model, Impartial incentive model, and Automation‐driven model, whereas achieving high evaluative governance engagement requires the presence of all the design elements (Comprehensive model). Also, we found Access to decision rights and Protocol automation are necessary conditions for generative governance engagement, and Access to decision rights together with Process visibility is a combined necessary condition for evaluative governance engagement. Relevant theoretical and practical implications for platform designers as well as methodological implications for applying QCA to emerging IS phenomena are discussed.

A value-based healthcare model for initiating and switching psoriasis therapies-Results from the prospective multicentre IMPROVE study.

Little is known about the therapeutic benefits of a value-based healthcare model compared to a traditional activity-based incentive model in psoriasis (PsO). This prospective non-interventional study evaluated an outcome-based, patient-centred management model for patients with PsO. In total, 49 patients with a Psoriasis Area and Severity Index (PASI) ≥3 who were starting or switching between treatments were included. Patients were assessed at baseline, 3 and 9 months. The patient benefit index (PBI) was calculated using predefined questionnaires. An expected PBI was calculated and adjusted for risk factors known to complicate treatment, that is overweight and smoking. The model remunerated the department on whether the observed PBI exceeded the expected PBI to incentivize over-performance. In total, 40 patients (80%) completed all three visits; 32.7% were smokers and 73.5% were overweight. Mean PASI at baseline was 11.5 (SD 9.1); PASI improved significantly from baseline through 3 months: mean reduction, 8.0 (SD 9.2), p < 0.001 and was maintained until 9 months: mean further reduction, 0.1 (SD 3.3), p = 0.893. The mean PBI was 2.5 (SD 1.3) and 2.8 (SD 1.1) at 3 and 9 months, respectively. A PBI ≥1 was achieved by 87.8% at 3 and 95.1% at 9 months. Overall, the department was remunerated a mean 2721.1 DKK (SD 4472.8) per patient. In subgroup analysis, the department was remunerated a mean of, respectively, 2428.6 (SD 5089.5), 2636.6 (SD 4471.3) and 3196.5 (SD 4497.1) DKK for patients with none, 1 or 2 risk factors, that is smoking or/and overweight. The model evaluated herein is the first value-based model to calculate remuneration from patient reported outcomes and showed to successfully predict the expected PBI and remunerate treatment based on whether the expected treatment goal was met or exceeded. This can be utilized in the patient-centred management of PsO.

Reputation incentive model of open innovation of scientific and technological-based SMEs considering fairness preference

The participation of external scientific research teams is an important support for the success of open innovation of scientific and technological-based small and medium enterprise (SMEs). The incentive mechanism should not only focus on traditional influencing factors but also on the scientific research innovation team’s internal characteristics and external environment. Considering the fairness preference of scientific research innovation teams, this paper constructs an open innovation reputation incentive model for scientific and technological-based SMEs and discusses the impact of relevant factors on the reputation and effort level of scientific research innovation teams under the situation of complete information and incomplete information. The results show that: (1) under the condition of complete information, the fairness preference of scientific research innovation teams is positively related to reputation incentive other than the effort level; (2) under the condition of incomplete information, the fairness preference of scientific research innovation teams has no significant impact on the reputation incentive but is negatively related to the effort level; (3) whether considering the fairness preference or not, the effort level and innovation capability of the scientific research innovation teams are positively correlated with the reputation incentive, while the effort cost, risk aversion coefficient, income distribution coefficient, and variance of external environment variable are negatively correlated with the reputation incentive; (4) the innovation ability of scientific research innovation teams is positively related to the effort level, while the effort cost, risk aversion coefficient, and variance of external environment variable are negatively related to the effort level.

HR POLICY OF THE HIGHER EDUCATION INSTITUTIONS IN CRISIS CHALLENGES

The article is aimed at researching new strategies for management decisions focused on the development of human resources in the context of crisis challenges.&#x0D; It has been established that management decisions in the field of educational management are currently being implemented under conditions of financial constraints, and, accordingly, the further high-quality functioning of the education system and its strategic development, in the face of crisis challenges, requires modeling a new paradigm of the realized importance of human resources in the national higher education space, which in turn stimulates the search for new approaches to the implementation of management strategies in the field of higher education and the creation of new non-standard concepts of HR management in war conditions.&#x0D; It is proved that in the current conditions of increased risks, the strategy of HR policy of a higher education institution is aimed at maintaining the effectiveness of educational and scientific activities of participants in the educational process through modernization of the HR management system, ensuring a safe educational space, changing models of incentives and motivation for the professional development of research and teaching staff, creating internal financial resources by expanding the practices of providing additional educational services by a higher education institution, directing such revenues to the professional development of research and teaching staff and the creation of safe conditions for professional activity.&#x0D; It is determined that the main measures to manage the development of the scientific and pedagogical potential of a modern Ukrainian higher education institution in today's conditions should be concentrated in four key areas: creating safe labour conditions; forming a system of incentives and motives for high-quality professional activities, including material incentives; creating conditions for continuous staff development to ensure their psychological comfort; focusing on additional educational services, focusing on additional educational services, project activities and interdisciplinary programs as a strategic direction to compensate the financial constraints of educational institutions. These measures will help to increase the competitiveness of educational institutions and the quality of educational programs.

A privacy-preserving federated learning with a secure collaborative for malware detection models using Internet of Things resources

The rise in malware attacks presents a growing security threat in today’s digital landscape, emphasizing the need for advanced malware detection methodology. While numerous detection systems utilizing methodologies like machine learning (ML) have been developed, they often fail to detect new and unknown malware in real time. This is because their malware datasets are generated with a very limited source and are not dynamic for up-to-date malware. Thus, with of the growth of the Internet of Things, malware have also increasingly grown, which makes current malware detection systems outdated in a short time. Therefore, IoT device resources can be exploited for building malware datasets having various types of malware families. In addition, the approach of collecting data from IoT devices and training them in a centralized cloud (CC) server is no longer acceptable due to this approach incurs significant security and privacy issues. This paper proposes PPFL-SC, an efficient privacy-preserving federated learning with a secure collaborative supporting verification. A group-oblivious signcryption cryptography is designed to be used as a privacy-preserving technique for federated learning. The CC server aggregates data without compromising individual data privacy. Moreover, the Stackelberg incentive model is designed as an incentive mechanism for encouraging IoT devices to collaborate through their heterogeneous dataset in a malware detection model. Thus, the proposed incentive mechanism is capable of increasing the participation of IoT devices and decreasing their dropping out during model updating. A security analysis confirms that PPFL-SC fulfills all security requirements for privacy-preserving federated learning. Real-world dataset experiments validate the efficiency and practicality of the proposed PPFL-SC.

An evolutionary analysis on the effect of tax incentives on R & D diffusion of wind power industry in complex network

The innovation performance of Chinese wind power enterprises has not been effectively improved, which may be caused by the behavior of enterprises using the information asymmetry between government and enterprises to camouflage R & D and obtain policies incentives. Therefore, this paper attempts to construct an evolutionary game model of tax incentives in complex network, introduces technology spillover and reputation cost, and discusses the diffusion of R & D in Chinese wind power industry. The results show that: (1) Reducing technology spillover not only contributes to the R & D diffusion, but also reduces the peak in the proportion of enterprises with camouflaging R & D. (2) Increasing reputation cost of violations can accelerate enterprises to reach the equilibrium and reduce the time that the proportion of the behavior with camouflaging R & D decreases. (3) The increase in incentives of lower tax rate for high-tech enterprises will create “lowland effect” for high-tech enterprises. And the increase in incentives of extra deduction for R & D expenses will increase the R & D diffusion of non-high-tech enterprises, while also suppressing the peak of the proportion in non-high-tech enterprises with camouflaging R & D.

Developing incentive mechanisms for long-term and short-term technological innovation in major engineering projects using principal-agent theory

PurposePromoting technological innovation is important to address the complexity of major engineering challenges. Technological innovations include short-term innovations at the project level and long-term innovations that can enhance competitive advantages. The purpose of this study is to develop an incentive mechanism for the public sector that considers short-term and long-term efforts from the private sector, aiming to promote technological innovation in major engineering projects.Design/methodology/approachThis study constructs an incentive model considering the differences in short-term and long-term innovation efforts from the private sector. This model emphasizes the spillover effect of long-term efforts on current projects and the cost synergy effect between short-term and long-term efforts. It also explores the factors influencing the optimal incentive strategies for the public sector and innovation strategies for the private sector.FindingsThe results indicate that increasing the output coefficient of short-term and long-term efforts and reducing the cost coefficient not only enhance the innovation efforts of the private sector but also prompt the public sector to increase the incentive coefficient. The spillover effect of long-term innovation efforts and the synergy effect of the two efforts are positively related to the incentive coefficient for the public sector.Originality/valueThis research addresses the existing gap in understanding how the public sector should devise incentive mechanisms for technological innovation when contractors acting as the private sector are responsible for construction within a public-private partnership (PPP) model. In constructing the incentive mechanism model, this study incorporates the private sector's short-term efforts at the project level and their long-term efforts for sustained corporate development, thus adding considerable practical significance.

Analysis of Tea Agroforestry System: The Case of Kyenjojo District in Uganda

Uganda is one of the countries in east Africa where agroforestry farming system has spread in twelve agro-ecological zones. Agroforestry practices are critical in all agro-based sectors like tea industry because of benefits like provision of fuel wood for curing tea. The purpose of this study was to understand the current agroforestry practices adopted by smallholder tea estate farmers and investigate options for scaling up the technology to alleviate the fuelwood scarcity faced by tea industries. The study involved a survey that was conducted in Kyenjojo district located in Western Uganda in June 2020. A total of 65 small holder tea farmers (respondents) were interviewed during the study. A purposive sampling method was used and data analyzed with SPSS to generate descriptive statistics that included frequencies, percentages, tables, graphs and charts. Results showed that shade was the most benefit of agroforestry trees by a proportion of 33% towards tea growing and followed by climate modification at 24%. Protection of the environment was also revealed as one of the leading benefits of tea agroforestry with a proportion of 34%, as well as trees acting as a source of poles at 23%. Eucalyptus at 34% was the most dominant agroforestry tree used at tea farm level as a woodlot, followed by Grevillea robusta at 28%. The most dominant adoption method of tea agroforestry practices at tea farm level was through farmers learning from fellow farmers at 34%, followed by adoption by trainings at 23%. Planting of agroforestry trees was the only remedy stated by farmers as an effort done to retain trees on farm. As a recommendation towards increased uptake of agroforestry at farm level, farmers identified certification and other factory-based incentives such as Rain Forest Alliance being the most important. Based on the identified benefits of tea-agroforestry systems, efforts should be made by Public, Private and Development partners to make all tea farmers aware of the existing and appropriate agroforestry practices while developing appropriate incentive models for increased adoption of tea agroforestry system in Uganda.

Design and Incentives of Equity Incentives in Chinese SOEs in Response to Environmental Uncertainty -- Case study of Hikvision based on grounded theory

High-tech companies are the most affected by restrictions on their ability to innovate. As the epitome of high-tech enterprise development in China, Hikvision actively explores and boldly innovates the equity incentive method and is always adapting to cope with internal and external environmental instability. This paper analyzes and compares the first four equity incentives based on the uncertainty factors and motivations of the internal and ex-ternal environment of the enterprise, takes this as the starting point, starts from the environmental motivations, and according to the constructively-rooted theory proposed by Glaser and Strauss, carries out programmed coding for the three dimensions of environmental factors, equity incentive plan selection and overall enterprise value enhancement. In this paper, we investigate the rationality of Hikvision's equity incentive policy setting, evaluate the effectiveness of the equity incentive policy, and predict the likelihood of equity lock-up under future environmental trends through tools such as excess return and return on equity. Based on the advantages and disadvantages, this paper puts forward the improvement of the equity incentive policy already implemented, and puts forward the universal suggestions on the application of equity incentive to deal with the environmental uncertainty, and establishes the equity incentive model for enterprises to deal with the uncertain environment to help enterprises make better management decisions.

The External Incentives Model Embedded: Evidence From the European Union's Eastern Neighbourhood

AbstractThe external incentives model (EIM) proved highly compelling in explaining Europeanization and rule adoption in countries from Central, Eastern and Southeast Europe. Building on the EIM, the present article seeks to contribute along three key objectives. First, it proposes to re‐evaluate the EIM for the Eastern European Neighbourhood Policy (ENP) region: Armenia, Azerbaijan, Georgia, Moldova and Ukraine. Second, the paper introduces a conceptual distinction between domestic transformation costs and regulatory costs. Third, it integrates and evaluates the EIM in a broader framework, incorporating domestic and alternative international conditions. The paper combines theory‐guided case comparisons and panel data analysis, based on a dataset with evidence collected from the Eastern ENP countries. The study corroborates the EIM and finds that higher domestic transformation costs lead to lower levels of democratic development and a positive cost–benefit balance of transformation, on the other hand, tends to encourage democratic consolidation in the Eastern ENP region.

Taxation of Charitable Giving in Terms of Martial Law in Ukraine: Legislative Novelties and Future Models

The purpose of the article was to reveal the conditions and consequences of key developments in the Ukrainian tax legislation, with respect to charitable donations by residents and non-residents in the context of the martial law regime, but de facto, large-scale war; as well as to determine models of development forecasting tax incentives for the post-war period of the restoration of Ukraine. Interdisciplinary descriptive, analytical and prognostic methods were used in the development of the research; in particular, comparative, situational and matrix analysis, interpolation and extrapolation of trends, conceptual and cognitive modelling. It is concluded that, Ukrainian tax policy is being significantly modernized by implementing a wide range of novelties related to key national taxes, namely: corporate income tax and individual income tax, to create the most favourable treatment for charitable donations by individuals, legal entities, charitable organizations and business entities. It is expected that the post-war legislative strategy for taxation of charitable giving will be different from the peacetime and wartime models.