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The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes.

The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns.

The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%.

The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution.

Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland.

The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

This study aims to explore the factors influencing the evolution of emerging technology innovation network (ETIN) in combination with the key attributes and life cycle of emerging technologies, particularly the impact of multiple knowledge attributes and technology life cycle on the ETIN evolution.

This study collects 5G patent data and their citation information from the Derwent Innovations Index to construct a 5G technology innovation network (5GIN) as a sample network and conducts an empirical analysis of the 5GIN using the temporal exponential random graph model (TERGM).

The results indicate that during the 5GIN evolution, the network scale continues to expand and exhibits increasingly significant core-periphery structure, scale-free characteristic, small-world characteristic and community structure. Furthermore, the findings suggest that the multiple knowledge attributes based on the key attributes of emerging technologies, including knowledge novelty, coherence, growth and impact, have a significant positive influence on the ETIN evolution. Meanwhile, the temporal evolution of ETIN is also found to be correlated with the life cycle of emerging technologies.

This study extends the exploration of emerging technology research from a complex network perspective, providing a more realistic explanatory framework for the factors influencing ETIN evolution. It further highlights the important role that multiple knowledge attributes and the technology life cycle play within this framework.

This paper aims to investigate the vertical cooperative relationship between the core enterprise and the manufacturer within the platform ecosystem, specifically analyzing the optimal decision-making processes of both parties under the original equipment manufacturer (OEM) and original brand manufacturer (OBM) modes.

This paper uses game theory to analyze the problem, considering factors such as brand value difference, cross-selling and platform empowerment. It constructs the game models for both OEM and OBM modes and discusses the selection strategies for the cooperation mode.

The results indicate that the choice of cooperation mode by the manufacturer and the core enterprise depends on the relative size of their brand values. In cases of inconsistent choices, cooperation can be improved by designing a transfer payment contract. When the brand value is constant, the product price is comprehensively affected by cross-selling revenue, price elasticity coefficient, cost coefficient of sales effort and cost coefficient of platform empowerment. The enterprise reduces the price only when the potential revenue brought by increasing product sales exceeds the marginal profit brought by increasing product pricing; otherwise, it raises the sales price.

The platform ecosystem is emerging as a future direction for business mode development. However, there is a paucity of research on the cooperation modes between manufacturers and core enterprises within the platform ecosystem.

The purpose of this paper is to empirically analyze the impact of directors’ and officers’ (D&O) liability insurance on enterprise strategic change. It also explores the mediating role of litigation risk, the moderating roles of enterprise science and technology level and precipitation organizational slack between them. In addition, it examines the joint moderating roles of the top management team (TMT) external social network and enterprise science and technology level, and enterprise scale and precipitation organizational slack.

Using the unbalanced panel data of A-share listed companies in the Shanghai and Shenzhen stock exchanges of China from 2002 to 2020 as the research sample, this paper uses the ordinary least square method and fixed-effect model to study the relationship between D&O liability insurance and enterprise strategic change. The study also focuses on the mediating mechanism and moderating mechanisms between them.

The authors find that D&O liability insurance has an “incentive effect,” which can significantly promote enterprise strategic change. Litigation risk plays a partial mediating role between D&O liability insurance and enterprise strategic change. Enterprise science and technology level and precipitation organizational slack negatively moderate the relationship between D&O liability insurance and enterprise strategic change. TMT external social network and enterprise science and technology level, and enterprise-scale and precipitation organizational slack have joint moderating effects on the relationship between D&O liability insurance and enterprise strategic change.

This paper confirms the “incentive effect hypothesis” of the impact of D&O liability insurance on enterprise strategic change, which not only broadens the research perspective of enterprise strategic management but also further expands the research scope of D&O liability insurance. Besides, this paper thoroughly explores the influencing mechanisms between D&O liability insurance and enterprise strategic change, providing incremental contributions to the research literature in the field of enterprise risk management and corporate governance. The findings have practical guiding significance for expanding the coverage of D&O liability insurance, promoting the implementation of strategic changes and improving the level of corporate governance of Chinese enterprises.

Although information technology (IT) governance and IT capability have been extensively examined, the impact of IT governance mechanisms on IT-enabled dynamic capability (ITDC) with moderators has received less attention. This study investigates how the impact of IT governance mechanisms on firm performance is achieved through an ITDC through the moderating role of IT governance decentralization and a turbulent environment.

This study extends from the traditional view of IT capabilities and integrates dynamic capability theory to propose that IT governance is vital for the ITDC. Path analysis, hierarchical regression analysis and moderation analysis were performed using partial least squares (Smart PLS 3.0) as the data analysis methods. This study empirically tests the proposed mediated moderation model by using data collected from 254 firms in China to test the hypotheses.

Significant and impactful relationships are found in the model that includes turbulent environment moderating effects. Contrary to expectations, IT governance decentralization is also significant but not very strong.

This study’s findings have implications for investigating IT governance, IT-enabled capabilities and moderators. Accordingly, this study has implications for board and executive management to capitalize on dynamic IT capability, to keep pace with the challenges and turbulent conditions associated with business needs and for the productivity paradox in the context of Chinese firms.

This country-specific research study theoretically contributes to the IT governance, dynamic capabilities and turbulent environment in the information systems literature and proposes many practical guides to the board and executive management of companies in the Chinese context.

(1) The shear lag effect and its additional deflection contribution to composite beams based on spatial grid elements were presented. (2) A refined spatial grid element analysis method that can simultaneously obtain the internal forces, displacements and stresses of various parts of a composite beam.

A refined spatial grid element analysis method.

The proposed method can directly obtain the internal forces and displacements of the joints of the composite beam roof, floor and web.

To comprehensively comprehend the mechanical behavior of double-girder steel plate composite girder bridge structures and facilitate refined analysis, this paper introduces a refined spatial grid element analysis model applicable to both the global and local domains.

Technology innovation in enterprises is a powerful driver of national competitiveness and sustainable corporate development. At the same time, the regional innovation policy mix serves as a core factor at the macro level, guiding and influencing enterprise technology innovation. Therefore, this paper addresses a critical question in innovation studies: the impact of the regional innovation policy mix complexity on enterprise technology innovation. Additionally, we also investigated the internal mechanisms and boundary conditions within this framework.

A dual-mode network model of local government-regional innovation policy is developed to capture the complexity of the regional innovation policy mix. The complexity index is calculated iteratively using the R language. The paper employs quantitative and empirical analysis, drawing on a sample of 622 regional innovation-related policy documents from 31 Chinese provinces (municipalities and autonomous regions).

The results reveal an inverted U-shaped relationship between policy mix complexity and enterprise technological innovation. The analysis further shows that university-industry cooperation intensity mediates this relationship, while regional knowledge absorptive capability moderates the impact of regional innovation policy mix complexity on enterprise technological innovation.

This paper highlights the influence of regional innovation policy mix complexity on enterprise technological innovation and underscores the role of university-industry cooperation intensity and regional knowledge absorptive capability. The findings offer valuable insights into the dynamics of enterprise innovation and inform effective government policy governance for fostering innovation.

This study aims to explore blockchain potential for digital marketing (BlkChn-Mk-KAP) by developing and validating a measurement model for assessing the constructs of knowledge, attitude and practice (KAP) related to blockchain technology in digital marketing.

A four-study process was used. The first study reviewed the literature to develop a pool of possible measurement items. Using exploratory factor analysis and reliability assessments, Study 2 (n = 162) investigated the dimensionality of the items developed in Study 1. The factorial structure from Study 2 was validated in Study 3 (n = 204), and the measurement model invariance was assessed using covariance-based structural equation modelling (CB-SEM). Finally, in Study 4 (n = 203), the predictive validity of the BlkChn-Mk-KAP was tested using a CB-SEM approach, testing its constructs correlations with the perceived usefulness of blockchain for digital marketing.

The findings indicate that the BlkChn-Mk-KAP measurement model comprises three-dimensional multi-item scales: knowledge, attitude and practice.

This study introduces a promising BlkChn-Mk-KAP model to examine blockchain’s role in digital marketing. The authors acknowledge the sampling limitation in this research. To enhance the generalisability of the findings, future research should expand to different groups, including generation, gender and age. In addition, further exploration of the explicit links between blockchain knowledge, attitudes and subsequent digital marketing performance is warranted.

Educating employees about blockchain technology’s unique features can shape favourable attitudes and stimulate the utilisation of blockchain-enabled technologies in digital marketing practice. BlkChn-Mk-KAP can offer a reliable and valid instrument to benchmark marketers’ KAP of blockchain-powered digital marketing as they implement blockchain technology to gain a competitive advantage.

This study helps to adopt sustainable practices ensuring the wellbeing of the key stakeholders.

This research introduces the first validated conceptualisation and measurement model, BlkChn-Mk-KAP, to evaluate blockchain KAPs among digital marketing professionals.

This study investigates the nonlinear relationship between inventory leanness and ESG (environmental, social and governance) performance, exploring how market concentration and digital transformation moderate this connection in manufacturing enterprises.

Using a large panel data collected from Chinese listed manufacturing enterprises over the period from 2012 to 2021, this research employs the instrumental variable method combined with two-stage least squares estimators to explore the U-shaped relationship between inventory leanness and ESG performance. Furthermore, the moderating roles of market concentration and digital transformation are demonstrated.

The results reveal an inverted U-shaped relationship between inventory leanness and ESG performance, indicating that moderate lean inventory management enhances ESG outcomes, but excessive reduction hinders them. Additionally, market concentration and digital transformation positively moderate this relationship, suggesting that competitive market conditions and technological advancement mitigate the adverse effects of overly lean inventories.

Managers are advised to balance inventory management with market dynamics and embrace digital transformation to optimize ESG performance. Policymakers can leverage these insights to guide firms in sustainable inventory practices.

This study contributes to the literature by unveiling the nonlinear dynamics between inventory leanness and ESG performance and highlighting the moderating roles of market concentration and digital transformation.