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Based on the micro role transition theory (MRTT), the present study aims to explore how leader–follower congruence in psychological capital (PsyCap) affects followers' task performance and voice behavior, in which we uncover the mediating role of organizational embeddedness.

A survey was conducted in South China through a three-stage procedure, and finally, a dyad-structured sample of 62 leaders and 218 employees was matched. The polynomial regression method, response surface analysis and structural equation modeling were employed to test the effects of leader–follower PsyCap congruence.

(1) Followers' organizational embeddedness will be higher when leaders' and followers' PsyCap are more aligned; (2) followers' organizational embeddedness will be higher when leaders' and followers' PsyCap are aligned at a high level rather than when they are aligned at a low level; (3) followers' organizational embeddedness will be higher when followers' PsyCap is higher than leaders', compared to when followers' PsyCap is lower than leaders'; (4) organizational embeddedness mediates the relationship between leader–follower PsyCap congruence and followers' (a) task performance and (b) voice behavior.

This study emphasizes leaders' pivotal role in a process where followers' PsyCap affects task performance and voice behavior, and further extends MRTT through introducing organizational embeddedness as a mediator in such a mechanism.

This study explores whether media coverage of Chinese food safety guide consumer behaviour and determines its impact.

Using data from the China Family Panel Studies, this study implements unsupervised machine learning methods to quantitatively identify themes in news media coverage of food safety across various provinces and regions. Based on these findings, this study examines the impact of coverage of food safety on consumer behaviour related to FAFH.

We find that media coverage of food safety in the restaurant sector significantly decreases household expenditure on FAFH relative to total expenditure. While negative coverage substantially decreases expenditure on FAFH, non-negative coverage significantly increases it. Reports of food safety incidents outside consumers’ province are negatively correlated with expenditure on FAFH, whereas reports within province significantly increases such spending. Further, the negative impact of media coverage on FAFH spending is less pronounced among higher-income families, households headed by individuals with high educational levels and those with low sensitivity to newspaper information. A robust government information infrastructure also mitigates this negative impact.

The findings have important policy reference value for promoting the healthy development of catering and other life services by improving news reporting and the regulatory system.

This article employs machine learning methods to identify news reports related to food safety in the catering industry quantitatively and incorporates them into the study of household consumption in China. Consequently, this not only fills a gap in the existing literature but also provides a new perspective for interdisciplinary research in economics, sociology and computer science.

To fabricate high quality parts, and to make the development generic yet compatible with the in‐house hardware, a virtual simulation system has been developed, and an in‐house intelligent multi‐material toolpath generation system has been under development. This new development includes the issues such as multiple fill‐toolpaths for the same material, interface mismatch between adjacent materials and the intelligent toolpath features for machine control. After the multi‐material toolpath file generated by the in‐house software, the existing virtual graphical simulation as well as well selected part fabrication experiments were used to validate it. Based on the authors’ ongoing research about multi‐material layered manufacturing, it was determined that the build characteristic was heavily dependent on the material being used. Therefore, it was important to develop the hardware/software that will accommodate this requirement.

The purpose of this paper is to evaluate the salt spray corrosion (SSC) and electrochemical corrosion performances of CrNi, TiAlN/NiCr and CrNi–Al₂O₃–TiO₂ coatings on H13 steel, which improved the corrosion resistance of H13 hot work mold.

CrNi, TiAlN/NiCr and CrNi–Al₂O₃–TiO₂ coatings were fabricated on H13 hot work mold steel using a laser cladding and cathodic arc ion plating. The SSC and electrochemical performances of obtained coatings were investigated using a corrosion test chamber and electrochemical workstation, respectively. The corrosion morphologies, microstructure and phases were analyzed using an electron scanning microscope, optical microscope and X-ray diffraction, respectively, and the mechanisms of corrosion resistance were also discussed.

The CrNi coating is penetrated by corrosion media, producing the oxide of Fe₃O₄ on the coating surface; and the TiAlN coating is corroded to enter into the CrNi coating, forming the oxides of TiO and NiO, the mechanism is pitting corrosion, whereas the CrNi–Al₂O₃–TiO₂ coating is not penetrated, with no oxides, showing the highest SSC resistance among the three kinds of coatings. The corrosion potential of CrNi coating, TiAlN/CrNi and CrNi–Al₂O₃–TiO₂ coatings was –0.444, –0.481 and –0.334 V, respectively, and the corresponding polarization resistances were 3,074, 2,425 and 86,648 cm², respectively. The electrochemical corrosion resistance of CrNi–Al₂O₃–TiO₂ coating is the highest, which is enhanced by the additions of Al₂O₃ and TiO₂.

The CrNi, TiAlN/CrNi and CrNi–Al₂O₃–TiO₂ coatings on H13 hot work mold were firstly evaluated by the SSC and electrochemical performances.

Canada has lagged in access to capital for high-potential, growth-oriented new ventures, but has made considerable strides in the past decade. This study aims to examine the evolving state of the market for risk capital in Canada during the COVID-19 pandemic, providing a critical assessment of government policy from the perspective of angel investors and diverse communities of entrepreneurs.

A thematic analysis was conducted of seven COVID-19 roundtable discussions hosted by the National Angel Capital Organization that included 51 global and national-level business and political leaders. The analysis extracted the most salient details from the discussions, distilling them into timely and actionable insights for policymakers.

The analysis suggests that the government’s economic policy response to the COVID-19 crisis fails to address the sudden liquidity problems faced by new ventures. Entrepreneurs and angel investors have remained resilient, rallied as a community and demonstrated an extraordinary level of trust. Traditionally under-represented communities of entrepreneurs are more affected by the crisis than others.

The findings and recommendations are of relevance to policymakers interested in post-COVID-19 economic policies to address the unique challenges faced by start-ups and ensure their full contribution to economic recovery.

The paper presents several policy recommendations and proposes a novel framework to describe the impacts of the pandemic on different categories of start-ups.

Ant colony algorithm is widely used in recent years as a heuristic algorithm. It provides a new way to solve complicated combinatorial optimization problems. Having been enlightened by the behavior of ant colony's searching for food, positive feedback construction and distributed computing combined with certain heuristics are adopted in the algorithm, which makes it easier to find better solution. This paper introduces a series of ant colony algorithm and its improved algorithm of the basic principle, and discusses the ant colony algorithm application situation. Finally, several problems existing in the research and the development prospect of ACO are reviewed.

This paper aims to research, identify and discuss the benefits and overall role of big data and artificial intelligence (BDAI) in the tourism sector, as this is depicted in recent literature.

A systematic literature review was conducted under the McKinsey’s Global Institute (Talwar and Koury, 2017) methodological perspective that identifies the four ways (i.e. project, produce, promote and provide) in which BDAI creates value. The authors enhanced this analysis methodology by depicting relevant challenges as well.

The findings imply that BDAI create value for the tourism sector through appropriately identified disseminations. The benefits of adopting BDAI strategies include increased efficiency, productivity and profitability for tourism suppliers combined with an extremely rich and personalized experience for travellers. The authors conclude that challenges can be bypassed by adopting a BDAI strategy. Such an adoption will stand critical for the competitiveness and resilience of existing established and new players in the tourism sector.

Besides identifying the benefits that BDAI brings in the tourism sector, the research proposes a guidebook to overcome challenges when introducing such new technologies. The exploration of the BDAI literature brings important implication for managers, academicians and consumers. This is the first systematic review in an area and contributes to the broader e-commerce marketing, retailing and e-tourism research.

本论文旨在研究、指出、和讨论大数据和人工智能（BDAI）在旅游业中的优势和整体作用。这些方面也在近文献中有所提到。

本论文采用系统综述方式, 在McKinsey’s Global Institute方法论的指导下, 确认BDAI可以在四种方面（预测、产出、提高、以及提供）创造价值。我们也通过阐述相关挑战来增强这个分析方法。

本论文结果显示BDAI通过适当的传播方式来为旅游业中创造价值。采用BDAI战略的好处包括：对旅游提供商带来高效、多产、盈利, 以及对旅游者们带来极度丰富和个性化的旅游体验。我们还总结了采取BDAI战略带来的诸多挑战。采用BDAI战略对旅游业中现有和新参与者的竞争力和弹性起到至关重要的作用。

除了指出了旅游业中BDAI带来的优势, 本论文还提出了一个指南, 来指导当新科技被引进时如何克服挑战。本论文通过对BDAI文献的梳理, 其文献综述结果对经理、学者、和消费者都有重要的启示作用。本论文是首篇在BDAI领域的系统综述, 对拓展电子商务营销、零售、和电子旅游科研有着重大贡献。

This study aims to address the challenge of the real-time state of charge (SOC) estimation for lithium-ion batteries in robotic systems, which is critical for monitoring remaining battery power, planning task execution, conserving energy and extending battery lifespan.

The authors introduced an optimal observer based on adaptive dynamic programming for online SOC estimation, leveraging a second-order resistor–capacitor model for the battery. The model parameters were determined by fitting an exponential function to the voltage response from pulse current discharges, and the observer's effectiveness was verified through extensive experimentation.

The proposed optimal observer demonstrated significant improvements in SOC estimation accuracy, robustness and real-time performance, outperforming traditional methods by minimizing estimation errors and eliminating the need for iterative steps in the adaptive critic and actor updates.

This study contributes a novel approach to SOC estimation using an optimal observer that optimizes the observer design by minimizing estimation errors. This method enhances the robustness of SOC estimation against observation errors and uncertainties in battery behavior, representing a significant advancement in battery management technology for robotic applications.