Technology Resource Allocation Research Articles

The Role of Expectancy Theory in the Organizational Management Process in Innovative Entrepreneurial Enterprises

The expectancy theory, originally put forth by psychologist Viktor Frankl, is a psychological framework that offers insights into human motivation and conduct. This theory suggests that the amount of effort individuals exert is directly influenced by their anticipation of particular outcomes and the degree to which those outcomes are personally appealing. Essentially, individuals adjust their behavior based on their assessment of the effort required to achieve specific outcomes and the value they attach to those outcomes. Within the realm of innovative entrepreneurship, organizational management faces a range of challenges. Among these, the rapidly evolving business environment stands out, necessitating constant adaptability and proactive planning. Additionally, attracting and maintaining talent is crucial, as the success of any enterprise heavily relies on its ability to recruit and retain key individuals. Furthermore, the establishment of an organizational culture has a profound impact on employee satisfaction, loyalty, and their capacity for innovation. Resource management also plays a pivotal role, particularly in the efficient allocation of funds, time, and technological resources. Lastly, competitive market forces and the need for strategic adjustments are realities that innovative entrepreneurial ventures must navigate, demanding continuous strategic realignment to maintain competitiveness. Against this backdrop of complexity and dynamism, the application of expectancy theory offers valuable insights for organizational management. By understanding and applying this theory, innovative entrepreneurial ventures can more effectively stimulate employee motivation, refine incentive systems, enhance goal management, and foster employee growth and engagement. To a certain extent, these functions can assist enterprises in overcoming various challenges in organizational management processes, thereby bolstering overall organizational performance.

Inbound learning: revolutionizing educational paradigms

This paper explores the transformative potential of Inbound Learning in educational settings, integrating principles from inbound marketing to foster personalized, engaging, and effective learning experiences. Through a comprehensive literature review, the study examines the application of Inbound Learning strategies across diverse educational levels and contexts, highlighting significant improvements in student engagement, academic performance, and educator satisfaction. The methodology employed combines quantitative and qualitative approaches to assess the impact of these strategies, revealing a positive correlation between personalized educational content and improved learning outcomes. Challenges such as technological access, resource allocation, and teacher training are discussed, alongside future perspectives that suggest the integration of advanced educational technologies and policy support to overcome these barriers. The findings underscore the efficacy of Inbound Learning in meeting the contemporary needs of learners and educators, advocating for its broader adoption to revolutionize educational practices.

The Impact of Carbon Emissions Trading on the Total Factor Productivity of China’s Electric Power Enterprises—An Empirical Analysis Based on the Differences-in-Differences Model

Based on the panel data of China’s listed electric power enterprises, this paper adopts the differences-in-differences model to empirically analyze the pilot policy of carbon emissions trading’s impact on the total factor productivity of power enterprises in 2013. The study finds that the carbon trading pilot policy has a significant positive effect on the total factor productivity of power companies, and the two possible impact mechanisms are external cost compensation and additional income, and internal low-carbon technology innovation and resource allocation optimization. The conclusions above have been further confirmed by the parallel trend test and robustness test. The heterogeneity analysis demonstrates that there are differences in the regression results between state-owned enterprises and nonstate-owned enterprises. The possible reason is that state-owned enterprises are more likely to be affected by the carbon emissions trading system, and their asset-heavy model puts greater pressure on carbon emission reduction. Therefore, their demand for low-carbon technology innovation is more urgent; areas with stricter carbon emission verification are more sensitive to the implementation of carbon trading, and a reasonable increase in carbon verification can make the carbon trading market more effective. Based on the research results, this paper proposes to speed up the improvement of the national carbon trading market system, enhance the diversity and richness of the main market, improve the liquidity of the carbon trading market, broaden financing channels for electric power enterprises, and improve the carbon market supervision mechanism.

Challenges and Opportunities in Mobile Health Technologies for Cancer Pain Management: An Integrative Review

This article explores the evolving landscape of mobile cancer pain management, a critical aspect of healthcare innovation aimed at enhancing patient outcomes and accessibility to pain relief measures. Through a comprehensive analysis, the study examines the benefits, limitations, and potential strategies for overcoming the challenges associated with implementing mobile health technologies in the management of cancer-related pain. The discussion includes an evaluation of the effectiveness, patient adherence, and technological advancements in mobile health, alongside an assessment of the barriers hindering widespread adoption, such as cultural and technological literacy, resource allocation, and security concerns.

A balanced approach to standard-essential patent disputes: from the perspective of the sustainability of technological resources

Standard-essential patents (SEPs) are closely linked to technical standards and have the nature of public products. The combination of patents as private property rights with technical standards as public goods magnifies the exclusivity of patent rights, may hinder the application of technical standards and gives rise to a large number of legal disputes. Two solutions have been developed to alleviate this tension: a strong protection model that emphasizes the property rights nature of patents and a sharing model that emphasizes the public goods nature of technology standards. However, both options are detrimental to the efficiency of the allocation of technological resources and have led to conflicts in judicial decisions worldwide. To reconcile such conflicts, the courts should interpret the fair, reasonable and non-discriminatory principle flexibly according to the status of the parties to re-establish an equal relationship between SEP holders and technical standard implementers, thereby promoting the parties’ voluntary conclusion of patent licensing contracts. Effective measures include strengthening the obligation to negotiate licences between SEP holders and technical standard implementers and applying the principle of good faith to avoid ‘patent blackmail’ by patent holders and ‘reverse blackmail’ by technical standard implementers. Moreover, courts should be careful when deciding whether to adjudicate global licensing matters between parties to avoid judicial deadlock. These measures will ultimately contribute to the sustainability of technological resource creation and exploitation.

Does digital economy development affect urban environment quality: Evidence from 285 cities in China.

The impact of the digital economy (DE) on urban environmental quality (EQ) is a critical aspect of China's economic development. This study investigates the impact of DI on urban EQ using the data from prefecture-level cities spanning the period from 2011 to 2021 and updates some disparate conclusions of related studies. It is discovered that a non-linear correlation exists between DE and urban EQ. Currently, DE can effectively improve local city EQ. This conclusion remains valid even after robustness tests and endogeneity treatment. The impact of DE on improving EQ can be classified as the impact of technological innovation, industrial upgrading, resource allocation, infrastructure construction, environmental governance, and changes in public lifestyle. Heterogeneity analysis reveals that the influence of DE is particularly pronounced in cities located in central and eastern regions of China, those with higher levels of administrative management, resource-based urban areas, and those with more stringent environmental regulations.

Research on the Evaluation of Regional Scientific and Technological Innovation Capabilities Driven by Big Data

Scientific and technological innovation (STI) is an important internal driver of social and economic development. Reasonable evaluation of regional scientific and technological innovation (RSTI) capability helps discover shortcomings in the development of urban development and guides the allocation of scientific and technological resources and the formulation of policies to promote innovation. This paper analyzes new opportunities created by big data and artificial intelligence for the evaluation of RSTI capability, and based on this analysis, the collaborative evaluation schemes of multi-entity participation are investigated. In addition, considering the important value of unstructured data in evaluating STI, the Latent Dirichlet Allocation (LDA) topic model and sentiment analysis method are employed to analyze the construction of an evaluation indicator system that integrates scientific and technological news data. To fully utilize the respective advantages of human experts and machine learning in the field of complex issue evaluation, this paper proposes an RSTI capability evaluation model based on AHP-SMO human-machine fusion. This study promotes the integration of science and technology and economy and has theoretical and practical significance.

ЭФФЕКТИВНОСТЬ РЕАЛИЗАЦИИ ИНВЕСТИЦИОННО-СТРОИТЕЛЬНЫХ ПРОЕКТОВ

The article discusses issues of efficiency in managing investment and construction projects, optimal use of resources, innovation and minimizing financial risks. The need for comprehensive analysis and effective management for sustainable development of enterprises and technological optimization is emphasized. Efficiency is characterized as a key element in achieving set goals. The table presents the main characteristics of investment performance, quantitative and qualitative aspects, the relationship between invested resources and achieved results, methods for identifying and minimizing risks in design and construction activities. The article summarizes the factors influencing the effectiveness of the implementation of investment and construction projects and their impact on the activities of the organization. The impact of digitalization and modern construction methods on project performance through competent management, the use of technological innovations, strategic planning, effective budgeting, resource allocation and risk management is summarized.

The causal effect of carbon emission trading scheme on green TFP: Evidence from the Chinese transportation industry

While industries globally strive to meet the 1.5-degree target set forth in the Paris Agreement, the transport sector, as the largest emitter of carbon, has yet to sufficiently reduce its emissions. This study utilizes panel data spanning from 2007 to 2022 in China and employs a time-varying difference-in-differences (DID) method to examine the causal impact of the carbon emission trading scheme (ETS) on green total factor productivity (GTFP) within the transport industry. Our empirical analysis yields several key findings: First, the implementation of the ETS policy significantly enhances GTFP in the transport sector within pilot areas. Second, decomposition of GTFP indicators reveals that the ETS primarily improves green scale efficiency and fosters green innovation, driven by technological advancements and optimal resource allocation. Third, heterogeneity analysis demonstrates a notably stronger positive effect of the ETS on transport sector GTFP in the eastern region, with insignificant impacts observed in the central and western regions. Through rigorous robustness tests, these conclusions are consistently upheld. In sum, this paper provides robust empirical evidence supporting the efficacy of ETS in reducing emissions and presents valuable policy implications for fostering the green transition of the transport sector.

How do enterprises’ green collaborative innovation network locations affect their green total factor productivity? Empirical analysis based on social network analysis

Green collaborative innovation plays an increasingly prominent role in improving enterprises' green total factor productivity (GTFP). Using China's listed manufacturing enterprises' panel data from 2011 to 2022, this paper uses social network analysis to construct green collaborative innovation networks based on the data of joint applications for green patents. This paper then performs an empirical analysis to explore the impact of enterprises' green collaborative innovation network locations on their GTFP and the associated impact mechanism. The results show that (1) enterprises in the core position of a green collaborative innovation network can enhance their GTFP, and this conclusion remains robust after replacing explanatory variables and changing the sample selection scope and the estimation of instrumental variables; (2) differences in green collaborative innovation type, enterprise ownership structure and time stage lead to heterogeneity in the influence of green collaborative innovation network location on GTFP; and (3) enterprises in the core location of a green collaborative innovation network indirectly promote their GTFP through improving their technological innovation level and resource allocation efficiency. This paper provides a practical and feasible path for the promotion of GTFP and high-quality economic development from the perspective of a green collaborative innovation network.

Mobile communication channel resource allocation technology in interference environment based on clustering algorithm

The rapid development of urbanization has led to the gradual increase of urban residential density. Relatively speaking, the spectrum resources are increasingly scarce, which leads to the increasingly serious interference between communities, and the system performance is also greatly limited. Therefore, in order to improve the efficiency of spectrum resources and solve the problem of user interference between cells, the experiment combines the advantages of clustering by fast search and find of Density Peaks Clustering (DPC), and proposes a two-step clustering algorithm. This method is proposed based on the core idea of DPC after in-depth study of the downlink multi-cell orthogonal frequency division multiplexing system architecture. The proposed model is compared with Matching Pursuit (MP) algorithm and Graph-based algorithm with the sum of clustering distance Rs, 1.5⁢Rs. The results show that the two-step clustering algorithm can significantly improve the spectrum efficiency and network capacity while ensuring good quality of service under the condition of channel tension or not. In addition, the minimum SINR value of the two-step clustering algorithm can reach 75 dB. Compared with the 220 dB of the Graph-based algorithm with the clustering distance Rs, it has extremely obvious advantages. Therefore, the two-step clustering algorithm constructed in this study can effectively reduce system interference, and has certain research and application value in solving the problem of mobile communication channel resource shortage.

Does digital transformation restrict the carbon emission intensity of enterprises? Evidence from listed manufacturing enterprises in China

AbstractDigitalization and greening are key themes in global development, the manufacturing industry, as a major sector of energy consumption and carbon emissions, is in urgent need of transformation to realize energy conservation and emission reduction, digital transformation provides an opportunity for its green development. However, whether digital transformation can restrain the carbon emission intensity (CEI) of enterprises is still controversial. Based on the data of China's A‐share manufacturing listed companies from 2013 to 2020, this paper uses fixed effect model and intermediary effect model to explore the relationship between digital transformation and enterprise CEI and the influence path. the results show that: (1) Digital transformation has significantly reduced the CEI of manufacturing enterprises. (2) Mechanism analysis indicates that green technological innovation and resource allocation efficiency play a chain mediating role in this relationship. (3) Heterogeneity analysis shows that the carbon emission reduction effect of digital transformation is more significant when enterprises belong to an energy‐intensive manufacturing industry or face strong environmental regulations and industry competition. The analysis of this paper not only deepens enterprises' understanding of digital transformation and green development but also provides a policy basis for China to advocate the coordinated development of the digital economy and green economy.

Technological paradigm-based development strategy towards natural gas hydrate technology

Natural gas, the cleanest fossil fuel, accounts for 24% of global energy demand. As the demand rises, there is a higher technology requirement towards efficient gas storage and transportation. Therefore, based on the technology paradigm theory, this study developed a data analysis system based on bibliometric analysis and visualization techniques to reveal the development path for natural gas transportation technologies. It has identified that competition and diffusion stages of gas transportation technologies are common natural gas transportation technologies and adsorbed natural gas respectively, while the gas hydrates technology is in the shift stage. The importance of laws and policies in driving the technological evolution in these three stages was also examined. Natural gas hydrate’s superior energy storage capacity and moderate synthesis conditions make it a promising natural gas transportation technology. However, challenges, such as technological limitations, industrial realization, economic benefits, and environmental impacts hinder the paradigm shift. Therefore, an integrated natural gas transport system involving natural gas hydrate technology is proposed and associated policy recommendations are given in technological innovation, monitoring systems, and resource allocation to facilitate the development of natural gas hydrate transportation technology.

Unlocking the role of smart cities in technological innovation: evidence from China

ABSTRACTThis paper discusses the impact of smart city on technological innovation and the underlying mechanism. Based on county-level panel data in China from 2005 to 2020, we use the ‘smart city’ construction as a quasi-natural experiment to identify its impact on technological innovation. Our findings show that: (1) Smart city construction significantly promotes technological innovation. (2) Smart cities indirectly promote technological innovation through technology resource allocation, industry agglomeration effects, and entrepreneurial spirit. (3) Due to ‘digital divide’, the innovation effects of smart cities are more pronounced in eastern regions and cities with high levels of digital infrastructure and information technology talent endowment. (4) The ‘smart city’ pilots generate spatial spillover effects, which enhance the technological innovation level of neighbouring cities.

Assessment of the ABC2-SPH risk score to predict invasive mechanical ventilation in COVID-19 patients and comparison to other scores.

Predicting the need for invasive mechanical ventilation (IMV) is important for the allocation of human and technological resources, improvement of surveillance, and use of effective therapeutic measures. This study aimed (i) to assess whether the ABC2-SPH score is able to predict the receipt of IMV in COVID-19 patients; (ii) to compare its performance with other existing scores; (iii) to perform score recalibration, and to assess whether recalibration improved prediction. Retrospective observational cohort, which included adult laboratory-confirmed COVID-19 patients admitted in 32 hospitals, from 14 Brazilian cities. This study was conducted in two stages: (i) for the assessment of the ABC2-SPH score and comparison with other available scores, patients hospitalized from July 31, 2020, to March 31, 2022, were included; (ii) for ABC2-SPH score recalibration and also comparison with other existing scores, patients admitted from January 1, 2021, to March 31, 2022, were enrolled. For both steps, the area under the receiving operator characteristic score (AUROC) was calculated for all scores, while a calibration plot was assessed only for the ABC2-SPH score. Comparisons between ABC2-SPH and the other scores followed the Delong Test recommendations. Logistic recalibration methods were used to improve results and adapt to the studied sample. Overall, 9,350 patients were included in the study, the median age was 58.5 (IQR 47.0-69.0) years old, and 45.4% were women. Of those, 33.5% were admitted to the ICU, 25.2% received IMV, and 17.8% died. The ABC2-SPH score showed a significantly greater discriminatory capacity, than the CURB-65, STSS, and SUM scores, with potentialized results when we consider only patients younger than 80 years old (AUROC 0.714 [95% CI 0.698-0.731]). Thus, after the ABC2-SPH score recalibration, we observed improvements in calibration (slope = 1.135, intercept = 0.242) and overall performance (Brier score = 0.127). The ABC2-SPHr risk score demonstrated a good performance to predict the need for mechanical ventilation in COVID-19 hospitalized patients under 80 years of age.

Impact of Industrial Transformation and Upgrading Demonstration Zones on carbon emissions intensity in resource-based cities

Under the goal of dual-carbon, promoting the industrial transformation of resource-based cities is an important measure to achieve carbon emission reduction. As a result, this paper chooses the panel data for 108 resource-based cities spanning 2010 to 2019, systematically evaluates the effects of Industrial Transformation and Upgrading Demonstration Zones (ITUDZ) policy on the carbon emission intensity using the difference-in-differences (DID) method. The research results reveal that the establishment of ITUDZ significantly reduces the carbon emission intensity of resource-based cities. Robustness tests confirm the accuracy of these results. The intermediary mechanism suggests that the establishment of the ITUDZ suppresses carbon emission intensity through green technology innovation and resource allocation efficiency. The heterogeneity analysis demonstrates that both the eastern and western regions of resource-based cities exhibit a greater ability to reduce carbon emission intensity and the effect of regenerative cities is more pronounced.

Does smart city pilot policy promote the enterprises’ digitalisation? Evidence from a quasi-natural experiment in China

ABSTRACT With the growth of the digital economy, the strategic significance of the smart city pilot policy to ‘empower’ the digitalisation of enterprises has become prominent. This study examines the impact and mechanism of the smart city pilot policy on the digitalisation of enterprises using the difference-in-differences (DID) method. Findings show that (1) the digitalisation level of the enterprises in a pilot city exceeds that of the enterprises in a non-pilot city, demonstrating that the policy can facilitate enterprise digitalisation improvement; (2) the smart city pilot policy encourages enterprise digitalisation in two ways: technological innovation and optimal resource allocation; and (3) the heterogeneity test reveals that the policy has a promotion effect on the digitalisation of enterprises that belong to an industry that is related to the smart city, state-owned enterprises, and those located in the eastern region. This study has significant policy ramifications that may help enterprises further develop their digitalisation.

China's cities go carbon neutral: How can new-type urbanization policies improve urban carbon performance?

Although the growth of urbanization based on economic construction has produced an economic miracle, it has also brought up significant obstacles to the sustainable growth of the economy and society. China has established a new-type urbanization policy (NTUP) since 2014 to address the carbon emission issues brought on by traditional development. This paper presents the first theoretical analysis of the impact and mechanisms of the NTUP on carbon emission performance (CEP). This study employs the difference-in-differences (DID) approach to investigate the impact, spatial spillover effects, and mechanisms of the NTUP on CEP by adopting a panel dataset from 2003 to 2020 for China's 283 cities. The empirical findings indicate that (1) new-type urbanized cities' carbon emissions are lowered by 1.37 % compared with nonpilot cities, and their carbon emission efficiency is raised by 31.56 %. After several robustness and hypothesis tests, this finding is still true. (2) The NTUP has a spatial spillover effect on CEP, significantly improving CEP for cities in the [0,1000] km range. (3) The key mechanisms by which the NTUP influences CEP are green technology innovation, energy structure, industrial structure, and resource allocation. (4) The NTUP has a stronger effect on CEP in medium-sized cities, cities with medium economic development, and resource-based cities. Finally, a response is briefly proposed.

Analysis of Public Technology Collaborative Innovation Based on Private Technology: A Tripartite Evolutionary Game Approach

Public technology collaborative innovation serves as an essential driving force to implement the innovation-driven strategy as well as promote national and regional economic sustainable development. Moreover, strengthening the construction of public technology collaborative innovation system is likewise of great significance for strengthening the quality and technology level of enterprises, enhancing their independent innovation capability, and achieving strategic transformation. Particularly, collaborative innovation of public technology in accordance with mature private technology enables the efficient allocation of technological and economic resources. In practice, there are still issues including high innovation costs, insufficient motivation, and low efficiency of innovation. Existing research typically ignores the technical cooperation among multiple parties. An evolutionary game model of public technology collaborative innovation is established in this paper to examine the interaction mechanism among the government, enterprises, and technology owners. For the purpose of analyzing the dynamic evolution of public technology collaborative innovation behavior and its influencing factors, numerical simulation experiments were conducted with meaningful results: (1) Setting the cost and benefit allocation coefficient in a scientific manner contributes to system stability and promotes cooperation among game players. (2) Reasonable government subsidies and penalties can assist in the formation of an active technological innovation between the firm and the technology owner. (3) The pricing method of private technology transfer is a significant factor influencing the evolution process. Besides, the adoption of a technology pricing method on the basis of government interests is conducive to the formation of a stable tripartite win-win situation. The research on collaborative innovation of public technology is further expanded in this paper, offering a reference for the formulation of relevant policies aimed at promoting cooperation in public technology innovation.

The heterogeneous effect of financial technology on green total factor productivity in China

Due to the unbalanced and inadequate development of fintech among various provincial regions, this paper proposes a novel sparse quantile model to explore the heterogeneous impacts of fintech on green total factor productivity (GTFP) in the provinces of China based on the annual data from 2011 to 2020. Quantile estimators of the proposed method are used as empirical “location” measures for the heterogeneous influence of fintech on GTFP. Two nonparallel twin functions at each quantile level capture the unbalanced information between fintech and GTFP. The empirical results show that fintech effectively promotes the quality of economic growth in every province, while the effects of fintech on GTFP are heterogeneous and unbalanced. Specifically, the effects in high-green-development regions are more powerful than those in low-green-development regions. Moreover, the influencing strength of fintech on GTFP among provincial regions has become weaker in recent years. The impact mechanism test indicates that fintech mainly promotes GTFP through the upgrading of industrial structure. Based on these results, this paper discusses some policy recommendations, such as optimizing the allocation of financial technology resources, improving the quality of innovation, promoting the upgrading of industrial structure, and strengthening foreign exchange and cooperation for the sustainable development.