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The purposes are to explore corporate financial management optimization in the context of big data and provide a sustainable financial strategy for corporate development.

First, the shortcomings of the traditional financial management model are analyzed under the background of big data analysis. The big data analytic technology is employed to extract financial big data information and establish an efficient corporate financial management model. Second, the deep learning (DL) algorithm is applied to implement a corporate financial early-warning model to predict the potential risks in corporate finance, considering the predictability of corporate financial risks. Finally, a corporate value-centered development strategy based on sustainable growth is proposed for long-term development.

The experimental results demonstrate that the financial early-warning model based on DL has an accuracy of 90.7 and 88.9% for the two-year financial alert, which is far superior to the prediction effect of the traditional financial risk prediction models.

The obtained results can provide a reference for establishing a sustainable development pattern of corporate financial management under the background of big data.

Aqueous zinc-ion battery has broad application prospects in smart grid energy storage, power tools and other fields. Co₃O₄ is one of the ideal cathode materials for water zinc-ion batteries due to their high theoretical capacity, simple synthesis, low cost and environmental friendliness. Many studies were concentrated on the synthesis, design and doping of cathodes, but the effect of process parameters on morphology and performance was rarely reported.

Herein, Co₃O₄ cathode material based on carbon cloth (Co₃O₄/CC) was prepared by different temperatures hydrothermal synthesis method. The temperatures of hydrothermal reaction are 100°C, 120°C, 130°C and 140°C, respectively. The influence of temperatures on the microstructures of the cathodes and electrochemical performance of zinc ion batteries were investigated by X-ray diffraction analysis, scanning electron microscopy, cyclic voltammetry curve, electrochemical charging and discharging behavior and electrochemical impedance spectroscopy test.

The results show that the Co₃O₄/CC material synthesized at 120°C has good performance. Co₃O₄/CC nanowire has a uniform distribution, regular surface and small size on carbon cloth. The zinc-ion battery has excellent rate performance and low reaction resistance. In the voltage range of 0.01–2.2 V, when the current density is 1 A/g, the specific capacity of the battery is 108.2 mAh/g for the first discharge and the specific capacity of the battery is 142.6 mAh/g after 60 charge and discharge cycles.

The study aims to investigate the effect of process parameters on the performance of zinc-ion batteries systematically and optimized applicable reaction temperature.

This study aims to explore whether digital platform capabilities (integration and reconstruction) affect technological innovation through knowledge bases in the dimensions of breadth and depth and the moderating role of organisational routines updating.

Hierarchical regression, mediation effect test macro and bootstrap were conducted to empirically analyse two waves of longitudinal survey data from 179 Chinese technology firms.

Results confirmed that knowledge bases (breadth and depth) mediated the effect of digital platform capabilities (integration and reconstruction) on technological innovation and that updating of organisational routines moderated the relationship between knowledge bases and technological innovation.

These findings offer guidance to firms that aim to achieve technological innovation and advantages, highlighting the importance of digital platform capabilities, knowledge bases and organisational routines updating.

Advancing from existing digital strategies and firm innovation literature, the authors provide a new perspective (knowledge bases) to respond to the information technology (IT) paradox and understand the role of digital platform capabilities in improving technological innovation.

Attentive to task-related information is the prerequisite for task completion. Comparing the cognition between attentive readers (AR) and inattentive readers (IAR) is of great value for improving reading services which has seldom been studied. To explore their cognitive differences, this study investigates the effectiveness, efficiency and cognitive resource allocation strategy by eye-tracking technology.

A controlled user study of two types of task, fact-finding (FF) and content understanding (CU) tasks was conducted to collect data including answer for task, fixation duration (FD), fixation count (FC), fixation duration proportion (FDP), and fixation count proportion (FCP). 24 participants were placed into AR or IAR group according to their fixation duration on paragraphs related to task.

Two types of cognitive resource allocation strategies, question-oriented (QO) and navigation-assistant (NA) were identified according to the differences in FDP and FCP. In FF task, although QO strategy was applied by the two groups, AR group was significantly more effective and efficient. In CU task, although the two groups were similar in effectiveness and efficiency, AR group promoted their strategies to NA while IAR group sticked to applying QO strategy. Furthermore, an interesting phenomenon “win by uncertainty”, which implies IAR group may get correct answer through uncertain means, such as clue, domain knowledge or guess, rather than task-related information, was observed.

This study takes a deep insight into cognition from the prospect of attentive and inattentive to task-related information. Identifying indicators about cognition helps to distinguish attentive and inattentive readers in various tasks automatically. The cognitive resource allocation strategy applied by readers sheds new light on reading skill training. A typical reading phenomenon “win by uncertainty” was found and defined. Understanding the phenomenon is of great value for satisfying reader information need and enhancing their deep learning.

The purpose of this study is to investigate the impact of user-driven innovation (UDI) and employee intrapreneurship (EI) on the innovation performance of platform enterprises through the mediating role of market intelligence responsiveness (MIR) and the moderating role of knowledge and information resource acquisition (KRA and IRA, respectively) between MIR and innovation performance.

Data were collected from 167 platform enterprises in northern, eastern and southern China with survey questionnaires. Participants were mainly middle and senior managers with a comprehensive grasp of the enterprises' information.

The results indicated that both UDI and EI, particularly synergy, positively influenced the innovation performance of platform enterprises. Furthermore, higher innovation performance resulted from high congruence between UDI and EI, and the innovation performance of enterprises increased when UDI and EI shifted from being incongruent to congruent. Lastly, MIR played a mediating role in this relationship, and both KRA and IRA played a positive moderating role between MIR and innovation performance.

Platform enterprises should pay attention to external users and internal employees to achieve their development goals and establish tripartite cooperative relationships involving firms, employees and users. Enabling platform enterprises to develop continually and in a healthy way requires the integration and utilization of all types of resources.

This was an empirical study on the impact mechanism of employees and users on the innovation performance of platform enterprises in China.

The purpose of this paper is to explore the effect of ZnO on the structure and properties of micro-arc oxidation (MAO) coating on rare earth magnesium alloy under large concentration gradient.

The macroscopic and microscopic morphology, thickness, surface roughness, chemical composition and structure of the coating were characterized by different characterization methods. The corrosion resistance of the film was studied by electrochemical and scanning Kelvin probe force microscopy. The results show that the addition of ZnO can significantly improve the compactness and corrosion resistance of the MAO coating, but the high concentration of ZnO will cause microcracks, which will reduce the corrosion resistance to a certain extent.

When the concentration of zinc oxide is 8 g/L, the compactness and corrosion resistance of the coating are the best, and the thickness of the coating is positively correlated with the concentration of ZnO.

Too high concentration of ZnO reduces the performance of MAO coating.

The MAO coating prepared by adding ZnO has good corrosion resistance. Combined with organic coatings, it can be applied in corrosive marine environments, such as ship parts and hulls. To a certain extent, it can reduce the economic loss caused by corrosion.

The effect of ZnO on the corrosion resistance of MAO coating in electrolyte solution was studied systematically, and the conclusion was new to the common knowledge.

This paper aims to document the adaptation strategies developed by local farmers to adjust to climate change and related hazards in Lijiang Prefecture in Southwest China, and quantify the determinants of the adaptation measures.

The study conducted a household survey with 433 respondents in Lijiang to documents adaptation measures. The authors used a multivariate probit model to quantify five categories of adaptation measures against a set of household features, extension and information, resources, social network, financial assets and perception variables.

The most significant determinants consisted of information on early climate warnings and impending hazards, ownership to land and livestock, irrigation membership in community-based organisations, household savings, cash crop farming and perceptions of climate change and its related hazards. Adaptation strategies and policies highlighting these determinants could help to improve climate change adaptation in the region.

This study quantified the determinants of adaptive strategies and mapped important determinants for the region that will provide farmers with the appropriate resources and information to implement the best practices for adapting to climatic changes. The method and findings could be useful and easily replicable for future agriculture policies.

How to improve the resilience of service firms in the crisis, such as the COVID-19 epidemic, to maintain a sustainable competitive advantage becomes a growing concern worldwide. Digital platform capability (DPC) provides a series of opportunities and advantages for service firms to shape resilience in the crisis. This study aims to clarify the effect and mechanism of DPC on service firms’ resilience, and provides a new mediator (strategic learning [SL]), as well as two boundary conditions (legal inefficiency [LIE] and legal incompleteness [LIC]).

Questionnaires were used to obtain firm data, and executives answered these key questions. Data from 293 service firms during the COVID-19 period were used for hypothesis testing.

DPC was positively related to the adaptive capacity (AC) and planning capacity (PC) of service firms. SL mediated the positive effect of DPC on the AC and PC of service firms. The positive effect between DPC and SL was weakened when LIE and LIC were high.

This study suggests that it is a very desirable measure to improve DPC to gain organizational resilience (OR) in the crisis. In addition, a SL process in the crisis is crucial, because service firms need to absorb key strategic information from digital platforms to cope with uncertainty. The services firms need to realize that the benefits of DPC will be weakened in the dysfunctional institutional environment of LIE and LIC.

To the best of the authors’ knowledge, this study is the first to link the DPC with the resilience of service firms, and provides a new explanation mechanism and some boundary conditions for this important relationship. Furthermore, this study takes a step forward, because these efforts respond to the widespread call of the literature on digitalization and OR, and provide new insights for understanding digital resilience.

The purpose of this paper is to review the operation and maintenance practices within wind power applications and to clarify practical needs as gaps between researchers and practitioners.

The paper collects, categorizes, and analyzes the published literature of both researchers and practitioners systematically.

The paper defines significant issues in operation and maintenance of wind energy related to: site and seasonal asset disturbances; stakeholders’ requirements trade‐off; dependability and asset deterioration challenges; diagnostic, prognostic and information and communication technologies (ICTs) applications; and maintenance optimization models. Within each category, the gaps and further research needs have been extracted with respect to both an academic and industrial perspective.

The use of wind energy is growing rapidly and the associated practices related to maintenance and asset management are still lacking. Therefore, the literature review of operation and maintenance is a necessity to uncover the holistic issues and interrelationships of what has so far been published as detailed and fragmented topics to specific issues. Wind energy assets represent modern renewable energy assets which are affected by environmental disturbances, rapid technological development, rapid scaling‐up processes, the stochastic and dynamic nature of operations and degradation, the integrity and interoperability of system‐to‐support.

The paper provides a comprehensive review of research contributions and industrial development efforts. That will be useful to the life cycle stakeholders in both academia and industry in understanding the maintenance problem and solution space within the wind energy context.