Search Results (305)

The goals of the European Union towards the energy transition imply profound changes in the energy field, so as to promote sustainable energy development while fostering economic growth. To achieve these changes, the incorporation of sustainable technologies supporting decentralisation, energy efficiency, renewable energy production, and demand flexibility is of vital importance. Blockchain has the potential to change energy services towards this direction. To optimally exploit blockchain, innovative business models need to be designed, identifying the opportunities emerging from unmet needs, while also considering potential risks so as to take action to overcome them. In this context, the scope of this paper is to examine the opportunities and the risks that emerge from the adoption of blockchain in four innovative business models, while also identifying mitigation strategies to support and accelerate the energy transition, thus proposing optimal approaches of exploitation of blockchain in energy services. The business models concern Energy Performance Contracting with P4P guarantees, improved self-consumption in energy cooperatives, energy efficiency and flexibility services for natural gas boilers, and smart energy management for EV chargers and HVAC appliances. Firstly, the value proposition of the business models is analysed and results in a comprehensive SWOT analysis. Based on the findings of the analysis and consultations with relevant market actors, in combination with the examination of the relevant literature, risks are identified and evaluated through a qualitative assessment approach. Subsequently, specific mitigation strategies are proposed to address the detected risks. This research demonstrates that blockchain integration into these business models can significantly improve energy efficiency, reduce operational costs, enhance security, and support a more decentralised energy system, providing actionable insights for stakeholders to implement blockchain solutions effectively. Furthermore, according to the results, technological and legal risks are the most significant, followed by political, economic, and social risks, while environmental risks of blockchain integration are not as important. Strategies to address risks relevant to blockchain exploitation include ensuring policy alignment, emphasising economic feasibility, facilitating social inclusion, prioritising security and interoperability, consulting with legal experts, and using consensus algorithms with low energy consumption. The findings offer clear guidance for energy service providers, policymakers, and technology developers, assisting in the design, deployment, and risk mitigation of blockchain-enabled business models to accelerate sustainable energy development. Full article

This theoretical essay aims to analyze some of the socio-economic innovations introduced by Platform Capitalism Specifically, it focuses on two main aspects: first, the digital platform as a radical organizational innovation. Digital platforms represent a structural novelty in the market economy, signaling a new organization of production and labor. Second, the essay examines the role of platforms in directly generating value through the concept of “network value”. To this end, it explores the function of “business intelligence” as a strategic and competitive tool. Finally, the paper discusses the key issues associated with platform capitalism, which could threaten its social sustainability and contribute to economic and financial instability. These issues include the increasing commodification of everyday activities, the devaluation of paid labor in favor of free production driven by platform users (the so-called prosumers), and the emergence of proprietary and financial monopolies. Hence, digital platforms do not inherently ensure comprehensive social and environmental sustainability unless supported by targeted economic policy interventions. Conclusively, it is emphasized that defining robust social welfare frameworks—which account for emerging value creation processes—is imperative. Simultaneously, policymakers must incentivize the proliferation of cooperative platforms capable of fostering experimental circular economy models aligned with ecological sustainability. Full article

In distribution networks, energy storage serves as a crucial means to mitigate power fluctuations from renewable energy sources. However, due to its high cost, energy storage remains a resource whose large-scale adoption in power systems faces significant challenges. In recent years, the emergence of shared energy storage business models has provided new opportunities for the efficient operation of multi-distribution networks. Nevertheless, distribution network operators and shared energy storage operators belong to different stakeholders, and traditional centralized scheduling strategies suffer from issues such as privacy leakage and overly conservative decision-making. To address these challenges, this paper proposes a Nash bargaining game-based optimal energy management and trading strategy for multi-distribution networks with shared energy storage. First, we establish optimal scheduling models for active distribution networks (ADNs) and shared energy storage operators, respectively, and then develop a cooperative scheduling model aimed at maximizing collaborative benefits. The interactive variables—power exchange and electricity prices between distribution networks and shared energy storage operators—are iteratively solved using the Alternating Direction Method of Multipliers (ADMM). Finally, case studies based on modified IEEE-33 test systems validate the effectiveness and feasibility of the proposed method. The results demonstrate that the presented approach significantly outperforms conventional centralized optimization and distributed robust techniques, achieving a maximum improvement of 3.6% in renewable energy utilization efficiency and an 11.2% reduction in operational expenses. While maintaining computational performance on par with centralized methods, it effectively addresses data privacy concerns. Furthermore, the proposed strategy enables a substantial decrease in load curtailment, with reductions reaching as high as 63.7%. Full article

This study investigates the relationship between disclosures related to Sustainable Development Goal 7 (SDG 7) and the financial profitability of Romanian commercial banks during the 2017–2023 period. Using an unbalanced panel dataset of 17 banks and applying fixed-effects regression models, the paper examines how transparency around energy-related sustainability practices influences various dimensions of bank profitability: recurring earning power (REP), loan yield (LY), return on assets (ROA), and return on equity (ROE). Macroeconomic energy indicators, such as the energy intensity level of primary energy (EnInt) and renewable energy consumption (REnC), are also controlled for. The findings indicate that SDG 7.1 disclosures are negatively associated with all profitability measures, except for LY, suggesting potential short-term trade-offs between sustainability transparency and financial outcomes. In contrast, SDG 7.2 disclosures positively impact REP, ROA, and ROE, underscoring the financial relevance of renewable energy financing. SDG 7.a disclosures show no significant relationship with profitability, indicating limited operational involvement in global energy cooperation. Additionally, higher energy intensity negatively affects REP and LY, supporting existing evidence that energy efficiency improves banking performance. These findings have implications for banking strategy, emphasizing the need to align sustainability disclosures with business priorities while recognizing the long-term benefits of green finance and energy efficiency. Full article

An airport slot is the core resource in the air transportation system. In most busy airports in China, airline demand significantly exceeds the available slot capacity. Scientific and reasonable slot allocation techniques and methods can improve the operational efficiency and benefits of multi-airport systems. Existing research has predominantly addressed slot allocation optimization for individual airports; however, there are differences in the functional positioning and resource allocation during multi-airport slot optimization, which makes cooperative optimization in the context of multi-airport slot allocation difficult. The dynamic sharing of airspace capacity in multi-airport systems is crucial for optimizing airport slot allocation and improving resource utilization efficiency. This study develops a multi-objective optimization model incorporating coupled airspace capacity relationships within multi-airport systems and the fairness of airlines and airports in order to realize the optimal utilization of multi-airport system resources, considering specialized 24 h airport slot coordination parameter patterns and slot firebreaks in China. Finally, the validity and scalability of the model are verified using real flight data from three airports in the Beijing airport terminal area, and simulations are conducted to verify the model. The findings provide a solid reference for the optimization of airport slot timetables in multi-airport systems, having both important theoretical value and practical significance. Full article

One of the emerging forms of cooperation in managing government projects is partnering (samspill) to address repetitive problems in large projects. Inefficiency, conflict, and cost volatility remain work issues in the public sector. Although risk sharing and incentive schemes are other aspects of partnering that are the subject of a significant amount of research, there is limited investigation into the softer aspects of partnering. The nature of partnering and how it is practiced depends on various components, such as trust, leadership, and culture; however, they are not well defined or appreciated. This paper investigates how these soft aspects are implemented and perceived in four mega Norwegian public construction projects that use a partnering model. In the present study, a qualitative research approach was adopted, and nine face-to-face interviews were conducted with project leaders from four case organizations in public sector healthcare, government, and education sectors. However, despite having similar contractual provisions, the projects exhibited varying degrees of collaboration success, indicating that formal agreements alone do not determine effective partnering. The outcomes from this study established that value-based leadership is central to the success of collaboration and should, therefore, be a priority when designing partnering in the public sector. Additionally, the results add to the existing debates regarding the application of soft values in the formal structures of the business and support the notion of leadership-based approaches in construction management, especially in the public domain. Full article

Enterprise digital transformation has emerged as a key strategy for enhancing innovation capacity in the age of the digital economy. This article aims to analyze the influence mechanism of digital transformation on corporate innovation and evaluate the mediating function of corporate innovation and cooperative cultures between digital transformation and corporate innovation capability. This work builds a panel data model based on data from Chinese A-share listed businesses from 2012 to 2021, empirically analyzes it using the Tobit model and the fixed effects model with instrumental variables technique, and uses the mediation effect test to uncover the course of action. According to the report, digital transformation significantly enhances creativity capability; second, corporate collaborative and innovation cultures mediate the relationship between digital transformation and innovation outcomes, and cultural capital becomes a crucial link; and third, the influence of digital transformation on corporate innovation capability is greater in state-owned enterprises, non-monopoly industries, and high-tech industries. According to the study, businesses should work to realize the dual-wheel drive of “technological investment + cultural cultivation” and establish an open and collaborative innovation ecosystem, while the government should intensify the development of digital infrastructure, enhance the supporting system, encourage cultural construction and talent supply, and create an environment that supports the synergistic development of digitization and innovation. Full article

This study addresses the increasing emphasis on sustainability and the importance of understanding how environmental risk influences business failure, a factor unexplored in traditional financial prediction models. Environmental risk, or environmental financial exposure, refers to the potential percentage of a company’s revenue at risk due to the environmental damage it causes. Previous research has not sufficiently integrated environmental variables into failure prediction models. This study aims to determine whether environmental risk significantly predicts business failure and how it interacts with conventional financial indicators. Utilizing data from 971 Spanish cooperative companies in 2022, including financial ratios, the VADIS bankruptcy propensity indicator, and the TRUCAM environmental risk score, the study employs the Extreme Gradient Boosting (XGBoost) machine learning algorithm, chosen for its robustness in handling multicollinearity and nonlinear relationships. The methodology involves training and validation samples, cross-validation for hyperparameter tuning, and interpretability techniques such as variable importance analysis and partial dependence plots. Results demonstrate that the variable related to environmental risk (TRUCAM) ranks among the top predictors, alongside liquidity, profitability, and labor costs, with higher TRUCAM values correlating positively with failure risk, underscoring the importance of sustainable cost management. These findings suggest that firms facing substantial environmental risk are more prone to financial distress. By incorporating this environmental variable into a machine learning framework, this work contributes to the interaction between sustainability practices and corporate viability. Full article

This project consists of a digital platform named Tri-Collab, where investors, entrepreneurs, and other agents (mainly talents) can cooperate on their ideas and eventually co-create. It is a digital means for this triad of actors (among other potential ones) to better adjust their requirements. It includes an app that easily communicates with a database of projects, innovation agents and their profiles, and the originality lies in the matching algorithm. Thus, co-creation can have better support through this assertive interconnection of players and their resources. This work also highlights the usefulness of the Canvas Business Model in structuring the idea and its dashboard, allowing a comprehensive view of channels, challenges and gains. Also, the potential of machine learning in improving matchmaking platforms is discussed, especially when technological advancements allow for forecasts and match people at scale. Full article

Diversification and business expansion have become key strategies for modern business development, prompting many large companies to move from singular service models to diversified service strategies, ultimately evolving into comprehensive service ecosystems. Therefore, an in-depth understanding of the evolutionary patterns of service ecosystems is crucial for formulating efficient and effective management strategies and helping enterprises to make informed decisions during the service innovation process. At present, research on the evolution of service ecosystems largely lacks sufficient theoretical underpinning and focuses on the supply–demand relationship relationship, which reduces the credibility of research conclusions and ignores the influence of multiple factors. In this paper, the Lotka–Volterra (LV) model is introduced to service ecosystems and the model as a ternary framework that captures competition–cooperation dynamics among atomic and composite services. In addition, an agent-based computational experiment is designed to integrate adversarial games for decision-making and genetic algorithms for service evolution. Furthermore, the results indicate that moderate competition $\alpha \approx 0.5$ among atomic services maximizes composite service innovation and excessive cooperation $\alpha \to 0$ stifles it. Full article

Facing the widespread cooperation among different agribusiness entities in China, this study explores the impact mechanism of land scale on farmers’ cooperation with new agricultural business entities (abbreviated as NABEs), including family farms, cooperatives, and agribusinesses. The effects of income within the cooperation mechanism are further analyzed. Based on survey data from 1558 farmers in 10 provinces, applying binary Logit regression and mediation effect models, the study finds the following: (1) The current land area, past growth of land, and future willingness to expand land all positively affect farmers’ cooperation with new agricultural business entities; (2) An inverted U-shaped relationship exists between land size and the proportion of farmers joining new agricultural business entities. The probabilities of joining family farms, cooperatives, and agribusinesses peak at land sizes of 2.65, 6.82, and 7.04 acres, respectively; (3) The current income situation has an intermediary effect on the cooperation between farmers and family farms, while the future income expectation has an intermediary effect on the cooperation between farmers and cooperatives and agribusinesses; (4) The effect of land scale on cooperation is more significant for farmers of village officials or agricultural organization members, full-time farmers, and those with green production and modern sales. This study proposes a development growth curve of farmers, which can be divided into “self-development–cooperation–transformation” stages, and gives solutions for each stage, to facilitate moderate-scale operations and long-term cooperation among various entities in the context of market reforms and social division of labor. Full article

The literature regarding innovation drivers is usually based on variables taken from some theoretical approach and validated within a methodology. Some authors have included COVID-19 as a driver for innovations. In this paper, we address the pandemic from a different viewpoint: trying to find if innovation drivers for European countries are the same in pre- and post-pandemic years. The automated general-to-specific model selection algorithm—Autometrics—is used. The main potentially relevant drivers for which data were available for both years and two proxies of innovation (patents and the Summary Innovation Index) were considered. The final models provided by Autometrics allow for valid inference on retained innovation drivers since they have passed a plethora of diagnostic tests, ensuring congruency. The attractiveness of the research system is the most impactful driver on the index in both years but other drivers indeed differ. SMEs’ business process innovation and their cooperation networks matter only in 2022. We found crowding-out effects of public funding of R&D (in both years, for the index). Sustainability was a driver in both periods. The ranking of common drivers also changes. Non-R&D innovation expenditures, the second most relevant before COVID-19, concedes to digitalization. Surprisingly, when patents are the proxy, digitalization is retained before COVID-19, with the attractiveness of the research system replacing it afterwards. Explanations for our findings are suggested. The main implications of our findings for innovation policy seem to be the facilitating role that the government should have in fostering linkages between stakeholders and the capacity the government might have to improve the attractiveness of the research system. Policies based on the public funding of R&D appear ineffective for European countries. Full article

Crop rotation emerges as a pivotal strategy addressing the decline in cultivated land quality and degradation and alleviating food production issues. However, the effective implementation of crop rotation policies remains challenging and requires further research. With the decline of the Chinese agricultural labor force, new agricultural business entities (NABEs), which encompass agricultural cooperatives, family farms, and agribusinesses, can play a significant role in agricultural modernization. Therefore, this research assesses how well NABEs encourage smallholders to adopt crop rotation practices, unraveling the mechanisms behind them and practical implementation pathways. Using survey data (n = 798) and the Tobit model, the findings of this research indicate the positive influence of NABEs in stimulating crop rotation among smallholders. This facilitation occurs via diverse mechanisms, including suitable access to land leasing, agricultural inputs, technical assistance, and market access. Additionally, the results indicate nuanced aspects, highlighting the heterogeneous impacts of NABEs across different contexts. Full article

With the development of new agricultural business entities in China, a complex competitive evolutionary dynamic has emerged among diversified agricultural business entities (abbreviated as ABEs), including farmers (traditional ABEs), cooperatives, agricultural enterprises, and family farms (new ABEs). Based on the Lotka–Volterra model, the dominance index, the Shannon–Wiener index of ecological theories, and the geo-detector, this study examines the spatiotemporal evolution and driving factors of ABEs’ structural changes across 286 Chinese cities from 2012 to 2021. Key findings include: (1) Farmers maintain absolute numerical dominance, but their relative advantage has declined. (2) The Shannon–Wiener index of diversified ABEs has increased significantly, indicating that differences between ABEs decreased, which means a trend toward structural homogenization. High Shannon–Wiener index values were observed in the Northeast Plain, Xinjiang, Hebei, Gansu, and Shanxi, while low values were concentrated in Yunnan, Guizhou, and the Guangdong-Guangxi region. Both areas experienced a shrinking trend. (3) Agricultural production factors such as multiple cropping indexes and theindustrial structure strongly explained the structural changes to ABEs, while the explanatory power of socio-economic factors can be enhanced after the interaction with agricultural production factors. (4) The relationship between farmers and new ABEs has shifted from a symbiotic relationship favoring farmers to a symbiotic relationship favoring new ABEs, with a significant spatial heterogenous layout among 286 cities. This study proposes a three-stage differentiation framework for ABEs: a simple structure dominated by traditional farmers, a competitive evolutionary dynamic among diversified ABEs, and a modernized structure led by new agricultural business entities. Based on these stages, this paper provides targeted recommendations for building a high-quality ABE system and advancing agricultural modernization. Full article

With the advancement of global digital transformation, data trading has become a pivotal element in value circulation and innovation among enterprises. In particular, pricing strategies in the industrial chain’s data trading process critically influence the cooperation and market competitiveness of upstream and downstream enterprises. To address this issue, this study develops a Business-to-Business data transaction pricing model tailored to a single industry chain. The model incorporates factors such as data scarcity, encryption protection efforts, and market demand dynamics. By employing a Stackelberg dynamic model, the study systematically examines the pricing strategies of upstream and downstream enterprises under various incentive mechanisms and evaluates the impacts of encryption protection efforts and incentive mechanism coefficients on the profitability of the industry chain. The experimental results reveal that introducing incentive mechanisms for downstream enterprises modestly increases the profits of both upstream and downstream entities. Meanwhile, incentivizing upstream enterprises yields a multiplier effect, significantly boosting their profits while causing a slight decline in the profitability of downstream enterprises. Full article