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This paper investigates the spillover effect of firms’ social media engagement with investors on consumption market performance and examines the impact of balanced/imbalanced social media stakeholder engagement strategies on firms’ consumption market performance.

The study employs multi-source secondary data covering 3,856 quarterly observations of 188 firms in the Chinese retail industry over six years (2015–2020). Polynomial regression analysis and response surface methodology are used to test the hypotheses.

The study reveals that firms’ social media engagement with investors has a positive spillover effect on consumption market performance. Additionally, the authors find that a balanced social media engagement strategy, which allocates resources evenly between consumers and investors, is more likely to optimize firm performance than an imbalanced strategy.

The research reveals cross-stakeholder spillover effects of social media engagement, introduces balanced/imbalanced engagement strategy concepts and extends the balanced marketing perspective to the social media context, providing guidance for firms to optimize their social media strategies.

This study aims to understand how Gen Z consumers perceive fashion brands’ corporate social responsibility (CSR) communication through emotional appeals on Instagram and how such perception affects their overall behaviour towards the brand.

The study adopts a qualitative research approach through photo-elicitation and 14 semi-structured in-depth interviews with members of Gen Z, using one of the world’s largest fast fashion brands, H&M, as the study context.

It is increasingly difficult to capture the attention of Gen Z as they have become immune to the typical CSR messages despite attempting to appeal to their emotions. This makes CSR communication alone challenging in influencing brand perception. However, behaviour towards the brand, such as purchase intention, is not necessarily dependent on whether consumers are convinced of the brand’s CSR activities, as greater value is placed on fast fashion’s price and availability. For Gen Z, such elements surpass their concern for sustainable fashion. Since more emphasis is placed on neutral endorsers due to their trustworthiness, CSR efforts may be disseminated through such third parties to achieve desired outcomes.

Understanding consumers’ perceptions of the current CSR effort allows brand managers to reevaluate their CSR communication strategies to appeal to Gen Z and encourage positive brand behaviour.

Contrary to previous studies, which have focused on organisational outcomes, the study has in-depth explored consumers’ perception of CSR efforts on Instagram and the implications of such perceptions for long-term brand building.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

The purpose of this paper is to examine the influence of intelligent manufacturing on audit quality and its underlying mechanism as well as the variation in this influence across different types of organizations.

This research utilizes a difference-in-differences (DID) method to examine how enterprises that apply intelligent manufacturing choose auditors and impact their audit work. The study is based on 15,228 observations of Chinese-listed A-shares from 2011 to 2020.

(1) There is a strong correlation between intelligent manufacturing and audit quality. (2) This positive correlation is statistically significant only in state-owned enterprises (SOEs), those that have steady institutional investors and where the roles of the CEO and chairman are distinct. (3) Enterprises that have implemented intelligent manufacturing are more inclined to employ auditors who possess extensive industry expertise. The auditor's industry expertise plays a crucial role in ensuring audit quality. (4) The adoption of intelligent manufacturing also leads to higher audit fees and longer audit delay periods.

This paper validates the beneficial impact of intelligent manufacturing on improving corporate governance. In addition, it is recommended that managers prioritize the involvement of skilled auditors with specialized knowledge in the industry to ensure the high audit quality and the transparency of information in intelligent manufacturing enterprises.

This study builds upon previous research that has shown the importance of artificial intelligence in enhancing audit procedures. It contributes to the existing body of knowledge by examining how enterprise intelligent manufacturing systems (IMS) enhance audit quality. Additionally, this study provides valuable information on how to improve audit quality in the field of intelligent manufacturing by strategically selecting auditors based on resource dependency theory.

This study aims to tackle the primary challenges in human–robot–environment interaction (HREI) within unknown environments. The key issues include recognizing human motion intention and managing force impacts during transitions from free space to constrained space. Addressing these challenges is critical for improving compliance, enhancing force control accuracy, and ensuring the safety and performance of HREI systems.

First, the energy equation of the second-order system is presented, and variable admittance control laws are designed for both free space and constraint space based on the energy equation. Then, a smooth switching method based on selection matrix is developed. Subsequently, the admittance-based overall control system is discussed. Finally, comparative simulations and experiments are conducted to verify the efficacy of the variable admittance control method using the 7-degree-of-freedom (7-DOF) manipulator Panda arm.

The simulation and experiment results demonstrate that the proposed variable admittance control method outperforms the traditional method in terms of force overshoot and accuracy.

This study does not account for the shape of unknown surfaces in the formulation of the variable admittance control law.

This paper proposes an energy-based variable admittance control method that uses energy considerations and uses a smooth switching technique to deduce human intentions and mitigate the effects of impact force.

Dark triad (DT) personality traits, that is, Machiavellianism, narcissism and psychopathy, are socially unenthusiastic and predict a range of antisocial behaviors. Academic entitlement, similarly, demonstrates the students’ rising temptation of higher grades without putting corresponding efforts. Based on coercion theory, this research investigated power distance as mediator between DT and academic entitlement (externalized responsibility and entitled expectations). Further, this study examined DT model of personality as a predictor of academic entitlement in Chinese higher education institutions (HEIs).

Chinese HEIs were ascertained for data collection. Students (with bachelor’s, master’s and Ph.D. degrees) responded to 719 questionnaires for data analysis. Hypothesized relationships were examined through partial least squares structural equation model (PLS-SEM).

This study established positive and significant direct link between DT and academic entitlement. The indirect effect through power distance was found insignificant between the relationship of DT and academic entitlement.

Based on coercion theory, this study extends the prevailing literature through unexplored effects of DT on academic entitlement and role of power distance in Chinese HEIs. This study validated the effect of DT on academic entitlement; however, direct-only no-mediation of power distance between the relationships is novel in Chinese HEIs. Moreover, power distance as mediator is novel between the relationships. Hence, this study provides an understanding of mentioned associations and contributes to the literature.

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.

Inspired by the internationalisation paths to prosperity of small and medium-sized enterprises (SMEs), where narcissistic leaders are diligent about organisations but also pursue their dark goals, this study aims to concurrently examine two avenues for the internationalisation of narcissistic leaders in SMEs concerning the function of team organisational citizenship behaviours (OCB): corporate social irresponsibility (CSI) and digital business model innovation (BMI).

This study utilised a quantitative design emphasising mature theory research, and data was analysed using multiple regression analysis and Hayes' process model. The data for this study was collected via surveys from 270 SMEs in Vietnam.

The study showed that narcissistic Chief Executive Officers (CEOs) can penetrate the global market profoundly by utilising both the righteous path, which is based on the power of the times via BMI, and the unethical path, CSI. However, team devotion via OCB can mitigate the unethical conduct of narcissistic CEOs.

The study endeavoured to find a path to internationalisation for SMEs in emerging markets with high economic openness and increasingly close connections with international markets, via two strategies for SMEs to conquer the international market more successfully, and with utilising the foundations of CEO narcissism and team citizenship behaviour.

This study contributed to the theory of SME internationalisation by employing the resource-based view and upper-echelon theory, with the updated Uppsala model as its foundation.

This paper aims to offer a comprehensive review and categorization of production optimization throughout the additive manufacturing lifecycle in a cloud environment. It aims to provide a structured approach to identifying and addressing issues.

This paper systematically reviews 75 technical papers on cloud manufacturing, nesting, scheduling and postprocessing in additive manufacturing. This includes a detailed discussion of the key issues.

This paper introduces a production framework for the entire lifecycle of additive manufacturing in a cloud environment. This framework aids in problem identification and decision-making based on the process flow. It provides an integrated view from cloud to postprocessing, examining decision interdependencies and enhancing problem identification and organization.

To the best of the authors’ knowledge, this paper is the first to review the complete lifecycle of additive manufacturing, emphasizing the often-overlooked aspects of postprocessing and cloud manufacturing. It offers a comprehensive study of lifecycle optimization challenges and suggests ways to streamline the production process.

This paper aims to address the issue of privacy leakage indirectly caused by non-private data shared by travellers on location-based social media (LBSM) in data mining.

This paper proposes a privacy-preserving location data collection approach based on local differential privacy (LDP) and validates the feasibility of the approach through experiments on three real-world public check-in datasets.

The experimental results demonstrate the effectiveness of our proposed approach, which preserves privacy while retaining over 90% of the data utility.

This research has the potential to assist tourism practitioners in establishing improved collaborations with trusted third parties, enabling the exploration of user location data insights without undue concerns regarding indirect privacy breaches during data mining, thereby enhancing travellers’ experience and aiding businesses’ decision-making.

This paper is likely to be the first to represent a promising solution for addressing privacy leakage concerns related to non-sensitive data in data mining. It provides a location data collection technology that strikes a balance between user privacy and data utility for tourism practitioners.