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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 streamline and enhance the assembly defect inspection process in diesel engine production. Traditional manual inspection methods are labor-intensive and time-consuming because of the complex structures of the engines and the noisy workshop environment. This study’s robotic system aims to alleviate these challenges by automating the inspection process and enabling easy remote inspection, thereby freeing workers from heavy fieldwork.

This study’s system uses a robotic arm to traverse and capture images of key components of the engine. This study uses anomaly detection algorithms to automatically identify defects in the captured images. Additionally, this system is enhanced by digital twin technology, which provides inspectors with various tools to designate components of interest in the engine and assist in defect checking and annotation. This integration facilitates smooth transitions from manual to automatic inspection within a short period.

Through evaluations and user studies conducted over a relatively long period, the authors found that the system accelerates and improves the accuracy of engine inspections. The results indicate that the system significantly enhances the efficiency of production processes for manufacturers.

The system represents a novel approach to engine inspection, leveraging robotic technology and digital twin enhancements to address the limitations of traditional manual inspection methods. By automating and enhancing the inspection process, the system offers manufacturers the opportunity to improve production efficiency and ensure the quality of diesel engines.

The study aims to examine diabetic patients’ switching intentions toward self-monitoring blood glucose devices, incorporating perceived usefulness and perceived ease of use, with switching cost as a moderator.

A self-administered questionnaire was developed using established measuring scales. Data from 321 respondents was collected and analyzed using the partial least squares structural equation modeling approach.

Results indicate that perceived usefulness and perceived ease of use influence switching intention. Switching cost does not moderate the perceived usefulness, perceived ease of use and switching intention. This study reveals important information for healthcare practitioners and device manufacturers.

The significance and originality of this study stem from its pioneering investigation into the switching intentions of diabetic patients regarding self-monitoring glucose devices through the application of the technology acceptance model, thereby addressing a notable gap in the existing literature on diabetes management and technology adoption, which has lacked comprehensive examination of patients’ transition behaviors in this specific context.

This study aims to shed light on the under-researched relationship between government–public relationship and tourism ethnocentrism via patriotism in emerging tourism destinations. The study empirically test the determinant role of government–public relationship and patriotism on tourism ethnocentrism within the theoretical lens of social exchange theory.

The idea is to develop a condition-based maintenance (CBM) model for continuously monitored degrading systems under imperfect maintenance. The system is subjected to random shocks, inspection, corrective maintenance (CM) and preventive maintenance (PM); respective thresholds are set to make decisions.

The generalized renewal process is considered for degradation modeling, and the maximum likelihood estimation method is used for parameter estimation. Optimum replacement time is derived by minimizing downtime per unit time (DT).

Optimum replacement time is derived by minimizing DT. The paper provides insight into the virtual age model’s applicability and efficacy in CBM policy-based decision-making.

This paper assesses the CBM policy for continuously degrading systems under random shocks and imperfect maintenance. An operating system faces five events, i.e. CM, PM, inspection, random shock and sudden failure, during its lifetime. The combination and timing of these mutually exclusive events decide the degradation path in addition to the system's natural degradation (wear-out) dynamics when it is not tampered with in any way. Sequential modeling of such events for a degradation dataset will provide maintenance estimation and prediction parameters.

In general, CBM models do not consider CM to be part of the maintenance policy. It is debatable whether to include CM as part of a CBM policy. In our case, we consider CM in CBM policy formulation, assuming: (1) fail-repair: the system is restored to its operating state after failure with repair; (2) salvage: disposal of non-repairable part or material from the system, i.e. CM actions are a result of minor component-level failures. System failure is referred to as a case involving rebuild/complete system replacement. We assume CM for minor failures and acknowledge that failure can be delayed using CBM but cannot be avoided entirely. Therefore, the consideration of CM in the CBM model will make the model more generic and comprehensive.

As China is on an inevitable march into the digital era, firms have accumulated abundant digital assets, such as algorithms and data. Facing the possibility of using digital assets as a new type input, besides traditional inputs such as capital and labor, would powerful managers perform better? Would managerial power help managers increase the efficiency of how a firm combines traditional and digital inputs and converts them into outputs? Thus, the purpose of this study is to investigate whether powerful managers promotes corporate productivity by using digital assets as a new input.

Using data from listed Chinese firms between 2008 and 2020, the authors constructed panel regressions with three-way fixed effects to examine whether and how managerial power influences corporate productivity in the current digital context, particularly under market uncertainty.

The findings reveal no consistent relationship between managerial power and corporate productivity. The results explain this from two contrasting effects: while managerial power promotes technological change it hinders technical efficiency – two components of total productivity. Moreover, this study identifies market uncertainty as a significant external contingency. In uncertain markets, strong managerial power positively impacts corporate productivity.

The results extend extant theoretical insights in the literature on how managerial power might influence corporate productivity.

This paper considers an e-tailer planning to distribute a product under one direct sales channel and multiple asymmetric agency platforms. Based on the multinomial logit (MNL) choice model, this study optimizes the pricing strategy and channel selection strategy to maximize the e-tailer’s profit.

A two-stage channel selection and pricing problem is formulated, where the profit-maximizing e-tailer first optimally selects a specified number of agency platforms from a set of alternatives to distribute the product and then determines the optimal prices in those channels.

An optimal pricing strategy is proposed to maximize the e-tailer’s total profit on multiple asymmetric channels. The results show that the e-tailer can obtain a higher profit by selling products on more asymmetric agency platforms. Moreover, an effective channel selection algorithm is provided to help the e-tailer optimally select the M agency platforms from N alternatives.

This study enriches the relevant research on multichannel selection and pricing by proposing an optimal pricing strategy and an effective channel selection algorithm. Evaluation results based on real-world industrial data show that the proposed optimal multichannel pricing strategy in this paper can significantly improve the profit of a real-world e-tailer compared to the e-tailer’s actual profit.

This study aims to investigate the different effects of physical and social servicescapes on brand love for internet-famous restaurants, focusing on their pathways and strengths of influence.

Structural equation modeling was applied to analyze data from 387 online questionnaires in China.

Results indicate that social servicescape directly influences brand love for internet-famous restaurants, while physical servicescape does not. The effect of physical servicescape on brand love for internet-famous restaurants is mediated by perceived coolness and perceived enjoyment, whereas social servicescape’s influence is mediated solely by perceived enjoyment. Overall, physical servicescape has a stronger impact on brand love for internet-famous restaurants compared to social servicescape.

The findings help internet-famous restaurants create effective physical and social servicescapes to enhance brand love, underscoring that physical servicescape is more crucial than social servicescape for cultivating this love.

This study contributes to the literature by analyzing the heterogeneous pathways and strengths of physical and social servicescapes influencing brand love for internet-famous restaurants, while highlighting the mediating role of perceived coolness and expanding the application scope of cognitive appraisal theory.

The current study aims to investigate the impact of perceived blockchain-related information transparency on consumers’ intention to purchase organic food. This study examines how perceived blockchain- related information transparency, directly and indirectly, affects purchase intentions through attitudes, perceived behavioural control and subjective norms. Additionally, the study explores how blockchain-based trust moderates the influence of perceived blockchain-related information transparency on these factors and the intention to purchase organic food.

Based on the theory of planned behaviour framework and a sample of 5,326 consumers, this study uses partial least squares structural equation modelling to test the research model.

This study finds that perceived blockchain-related information transparency directly enhances consumers’ attitudes towards organic food purchase, perceived behavioural control, subjective norms and intention to purchase organic food. Additionally, perceived blockchain-related information transparency indirectly affects consumers’ intention to buy organic food through three antecedents of the theory of planned behaviour model. Notably, these indirect effects were moderated by consumers’ blockchain-based trust.

This study provides recommendations for leveraging blockchain to enhance transparency and build trust, which could boost consumer engagement and organic food purchases.

This research contributes to blockchain literature by empirically examining the role of perceived blockchain-related transparency and blockchain-based trust in consumers’ purchasing decisions regarding organic food. It provides valuable insights into the consumer-centric benefits of blockchain technology. Furthermore, this study also contributes to the literature on organic food, particularly its promotion through blockchain technology.

Information transparency is an important factor in enhancing trust and promoting interfirm cooperation. By combining transaction cost theory and institutional theory, this study aims to examines whether host-country firms’ information transparency prompt multinational enterprises’ (MNEs) to choose the joint venture entry mode for outward foreign direct investment (OFDI).

Using Heckman two-stage estimation method, this study examines Chinese listed manufacturing firms for the period 2014–2019.

The findings indicate that the higher the information transparency of host-country firms, the higher the possibility of MNEs choosing the joint venture entry mode for OFDI. This study further finds that the positive relationship between host country firms’ information transparency and the possibility of choosing the joint venture entry mode is enhanced by institutional distance, but weakened by MNEs’ host-country experience.

How to choose the appropriate entry mode of OFDI in the internationalization strategy is an important issue for MNEs to consider. As the postpandemic world is characterized by increased global risks, decoupling of economies, disruption of global value chains and the retreat of globalization (Contractor and Cantwell, 2022), how to further strengthen cooperation, reduce the cost and risk of MNEs and truly realize common construction and sharing is one of the hot issues in both practice and research.