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This study aims to crystallize the research landscape of corporate social responsibility (CSR) authenticity by systematically analyzing CSR scholarships published in peer-reviewed journals from 2007 to 2021.

Quantitative content analysis was used to systematically analyze 52 peer-reviewed articles on CSR authenticity. In particular, this study coded the conceptualizations and operationalizations of CSR authenticity, research contexts, applied theoretical frameworks and constructs associated with authenticity in the CSR scholarships.

This study’s analysis revealed that CSR authenticity is a multifaceted and multidimensional concept researched in various contexts. Yet, it still lacks clear and consistent conceptualization and theorization. Methodologically, qualitative and quantitative methods have equally contributed to the investigation of CSR authenticity. However, scale development and validation still need to improve.

The sample of this research is limited by the searching method and language restriction. This research contributes to CSR scholarships by describing the growing landscape of CSR authenticity research, identifying key research gaps and offering suggestions for future research.

Practitioners can use the findings as references to develop more authentic CSR activities.

This study is an early attempt to examine the research on CSR authenticity, which has been inconclusive and disorganized, despite the rapid growth of publications in recent years.

A total of 478 Americans participated in an online survey. Each participant was asked to answer questions about a company randomly assigned from one of 36 companies representing six industries.

This study aims to explain how corporate social responsibility (CSR) and negative corporate ability (CA) associations lead to negative word-of-mouth (WOM) intentions in non-crisis situations. Specifically, this study investigates the mediating roles of revenge and avoidance motives in the relationship between negative CSR and CA associations and the intention to generate negative WOM.

The findings indicate that negative CSR associations have a greater effect on WOM than negative CA associations. Moreover, negative CSR associations stimulate the revenge motive, resulting in stronger intentions to spread negative information, while negative CA associations lead to the avoidance motive, resulting in weaker intentions to spread negative information.

Unlike most previous studies that focused on crises, this study examines how negative CA and CSR associations influence negative WOM in non-crisis situations, shedding light on the roles of motives including the revenge and avoidance. The research fills a gap in the existing literature by demonstrating that negative CSR associations have a greater impact on negative WOM intentions than negative CA associations in non-crisis situations.

This study aims to represent a novel closed-form solutions method based on the product of the exponential model to solve the inverse kinematics of a robotic manipulator. In addition, this method is applied to master–slave control of the minimally invasive surgical (MIS) robot.

For MIS robotic inverse kinematics, the closed-form solutions based on the product of the exponential model of manipulators are divided into the RRR and RRT subproblems. Geometric and algebraic constraints are used as preconditions to solve two subproblems. In addition, several important coordinate systems are established on the surgical robot and master–slave mapping strategies are illustrated in detail. Finally, the MIS robot can realize master–slave control by combining closed-form solutions and master–slave mapping strategy.

The simulation of the instrument manipulator based on the RRR and RRT subproblems is executed to verify the correctness of the proposed closed-form solutions. The fact that the accuracy of the closed-form solutions is better than that of the compensation method is validated by the contrastive linear trajectory experiment, and the average and the maximum tracking errors are 0.1388 mm and 0.3047 mm, respectively. In the animal experiment, the average and maximum tracking error of the left instrument manipulator are 0.2192 mm and 0.4987 mm, whereas the average and maximum tracking error of the right instrument manipulator are 0.1885 mm and 0.6933 mm. The successful completion of the animal experiment comprehensively demonstrated the feasibility and reliability of the master–slave control strategy based on the novel closed-form solutions.

The proposed closed-form solutions are error-free in theory. The master–slave control strategy is not affected by calculation error when the closed-form solutions are used in the surgical robot. And the accuracy and reliability of the master–slave control strategy are greatly improved.

Purpose: The primary purpose is to discuss the productivity and digitalisation interaction at the theoretical level, analyse the productivity and digitalisation differences between the European Union (EU)-14 and EU-13 countries, and evaluate the digitalisation impact on the manufacturing sector labour productivity of the EU countries.

Need for study: The average added value created per capita in new EU countries (EU-13) is one-third lower than in old EU countries (EU-14). To increase productivity, manufacturing companies must adapt to modern trends and take advantage of industrial digitisation opportunities. Digitisation can improve production efficiency, reduce costs, and improve product quality, allowing continuous monitoring and analysis of production data, enabling informed decisions and faster problem-solving.

Methodology: Analysis of scientific literature, comparing viewpoints, insights, and conclusions. The empirical study includes calculating rates of change of indicators, differences between EU-14 and EU-13, and structural analysis. The impact of digitisation on the productivity of EU countries is studied by creating a correlation matrix and using regression analysis: ordinary least square models.

Findings: EU-13 countries are behind EU-14 in labour productivity and manufacturing digitalisation. Digitalisation positively impacts productivity per employee. A faster increase in digitisation, industrial robot use, and e-commerce sales could significantly increase productivity in EU-13, reducing productivity differences between countries.

Practical implications: This study highlights the need for policy promoting digitisation innovation, particularly in EU-13 countries, to be implemented by both national and EU-based economic development and regional and cohesion institutions.

This paper aims to study the effect of ultraviolet (UV) light on the corrosion behavior of BC550 weathering steel in simulated marine atmospheric environment.

The effect of UV light on the corrosion behavior of BC550 weathering steel in simulated marine atmospheric environments were investigated by the corrosion weight gain experiment, in situ electrochemical noise, scanning electron microscope and X-ray diffraction.

UV light accelerated the corrosion process of BC550 weathering steel in the simulated marine atmospheric environment during the first 168 h. The maximum influence factor of UV light was 0.32, and it was only 0.08 after 168 h of corrosion process.

As the extension of corrosion time, the thickness and density of the corrosion product layer increased, which weakened the acceleration effect of UV light.

The purpose of this paper is to investigate the relationship between the keyhole geometry and acoustic signatures from the backside of a workpiece. It lays a solid foundation for monitoring the penetration state in variable polarity keyhole plasma arc welding.

The experiment system is conducted on 6-mm-thick aluminum alloy plates based on a dual-sensor system including a sound sensor and a charge coupled device (CCD) camera. The first step is to extract the keyhole boundary from the acquired keyhole images based on median filtering and edge extraction. The second step is to process the acquired acoustic signal to obtain some typical time domain features. Finally, a prediction model based on the extreme learning machine (ELM) technique is built to recognize different keyhole geometries through the acoustic signatures and then identify the welding penetration status according to the recognition results.

The keyhole geometry and acoustic features after processing can be closely related to dynamic change information of keyhole. These acoustic features can predict the keyhole geometry accurately based on the ELM model. Meanwhile, the predict results also can identify different welding penetration status.

This paper tries to make a foundation work to achieve the monitoring of keyhole condition and penetration status through image and acoustic signals. A useful model, ELM, is built based on these features for predicting the keyhole geometry. Compared with back-propagating neural network and support vector machine, this proposed model is faster and has better generalization performance in the case studied in this paper.

Spatial integration and industrial clustering have become an important feature of the culture tourism business. When the core elements in both the culture industry and tourism industry are integrated, a model based on system science is constructed that combines the resources and capacity of the two entities to envisage the ways of creating integrated products and services from the two sectors. Guided by the system science, this study proposes a culture tourism system revealing the clustering and hierarchical structure of the industrial elements. The system contains two subsystems: internal system and external system. The agglomeration model of the system includes 26 indices and the PEF methods, which involved the Parallelogram Law, Entropy-weight Method, and Fuzzy Membership Function. Finally, this study deploys an empirical study involving all provincial territories (N=31) in mainland China. It analyzes the variability and degree of balanced development of the system. In addition, through the resultant data this research adds a typology of culture tourism system along with policy recommendations.

From an internal perspective, the purpose of this study is to understand employees' responses to chief executive officer (CEO) activism, a phenomenon wherein a company's CEO expresses his/her own opinions and ideas on controversial sociopolitical issues. Integrating corporate social responsibility (CSR), public relations and leadership literature, this study examines the effects of employees' expectations toward CEOs and transformational CEO leadership on the perceived morality of CEO activism and its attitudinal and behavioral outcomes.

An online survey was conducted with 417 full-time employees in the US whose CEO has been engaging in sociopolitical issues.

The results showed that employees' ethical expectations toward their CEOs and transformational CEO leadership were positively associated with perceived morality of CEO activism, whereas economic expectations toward CEOs had no significant relationship with it. In turn, perceived morality of CEO activism contributed to employees' positive attitudes and supportive behaviors for their CEOs and their companies.

This study is among the first attempts to examine the effectiveness of CEO activism from an internal perspective, drawing from CSR, public relations and leadership literature.

This paper aims to quantify atmospheric corrosion by image analyses. The corrosion extent, form and distribution of corrosion product on Q235B and T91 steels exposed to a Zhoushan marine atmosphere over one year are characterized by image analysis.

Image analysis of corrosion images were achieved using the gray value, wavelet analysis and fuzzy Kolmogorov–Sinai (K–S) entropy.

As corrosion becomes extensive, the gray value of corrosion images decreases, and the energy value of nine subimages after wavelength decomposition decreases. Fuzzy K–S entropy increases as localized corrosion propagates but decreases as uniform corrosion spreads.

The methods proposed in this work open a new way for fast corrosion evaluation of metallic materials exposed to atmospheric conditions.