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Corrosion of steel in marine environments poses a significant economic and environmental challenge because of its detrimental effects on marine structures and equipment. Traditional chemical inhibitors that mitigate corrosion often introduce harmful substances into the environment. As a result, there is a growing interest in exploring eco-friendly alternatives, such as plant-derived inhibitors, to reduce the environmental impact of corrosion protection strategies. The purpose of this study is to investigate the effectiveness of Phyllanthus urinaria extract as a green anti-corrosion additive for rebar steel in marine conditions.

Phyllanthus urinaria extract was prepared in the ethanol solution with the assistance of a sonicator. The steel’s surface upon addition of the extract was characterized using SEM, EDX and FTIR analysis. The electrochemical corrosion characteristics, including potentiodynamic polarization and electrochemical impedance spectroscopy, were used to evaluate the inhibitory performance of the extract on steel under simulated marine conditions (3.5% NaCl solutions).

The results of this study showed that with Phyllanthus urinaria extract’s content of 0.02% in NaCl solution of 3.5%, the corrosion rate decreased to about 30% compared to the controlled sample. Measurements of the inhibitory mechanism analysis study for all solutions from 0 mg/L to 1.114 mg/L of polyphenol from Phyllanthus urinaria extract showed a significant reduction in rebar corrosion rate, especially with 0.2228 mg/L polyphenol. Reinforcement can increase corrosion inhibition by up to 30% compared to the control sample.

To the best of the authors’ knowledge, this is the first study of using Phyllanthus urinaria extract as green inhibitor for protection of steel from the corrosion in the simulated marine solution. The protective mechanism for steel using Phyllanthus urinaria extract was investigated using the FTIR, SEM, EDX and electrochemical analysis. The results indicated that the polyphenols in the extract showed inhibition that could minimize the corrosion of reinforcement in marine environments.

Spirituality serves as an ethical benchmark for shaping human and brand identity. Only a few studies have recently attempted to examine the impact of spiritual attributes on customer behavior. This study extends the current literature and aims to develop a research model to investigate spiritual brand attributes toward customers’ behavior. The study employs the stimulus–organism–response (SOR) model as a theoretical signpost to construct the research model. Driven by this chapter, future research opportunities are presented, and the opportunity for empirical research is also illustrated.

This study empirically tests the influence of key elements on intent to use electronic (E)-ticket through the “Stimulus–Organism–Response (SOR)” framework and structural equation model. Results highlight factors such as E-trust Technology, Ease of Use, E-satisfaction, Intention to Purchase E-ticket, Price Perception, and Usefulness; the study comprehensively analyzes the factors influencing the decision-making process of consumers when it comes to purchasing E-tickets. The research employs a hypothesis-driven approach and gathers survey results from 408 observants to find out the intention of consumers to use E-tickets for using transportation services, which help transportation providers understand the importance of its platform to benefit customers who are willing to change their perceptions from paper tickets to E-tickets, the reason customers buying E-ticket rather than paper ticket while using digitalization to help firms control their cost and building internal legitimacy by better managing their internal stakeholder.

This study aims to explore the relationship between artificial intelligence (AI) awareness and physical and psychological withdrawal behaviors of enterprises employees through the mediating roles of job security and emotional exhaustion as well as the moderating role of emotional intelligence.

Data were collected through a self-administered questionnaire from six fields with the highest level of AI application with a sample of 1,129 Vietnamese enterprises employees. Data were analyzed using SmartPLS, a bootstrapping technique was used to analyze the data. The mediating effect of job security and emotional exhaustion and the moderating effect of emotional intelligence were performed.

The research showed that the proposed moderated mediation model was accepted because the relationships between the constructs were statistically significant. The results of the data analysis supported a positive relationship between AI awareness and physical and psychological withdrawal behaviors, as well as a mediating effect of job security and emotional exhaustion. The findings also confirmed that there is a moderating effect of emotional intelligence between AI awareness and job security, emotional exhaustion, physical and psychological withdrawal behaviors.

Sample data was only collected at a few Vietnamese enterprises in six fields with the highest level of AI application which are e-commerce, transportation and logistics, education, real estate, finance and agriculture, which may be limiting generalizability of research results.

This study offers several practical and useful management implications, such as anticipating negative attitudes, feelings and behaviors of employees to prepare a response plan; conducting interviews, investigate employees’ AI awareness and do their best to minimize its negative effects on employees’ psychological states and behaviors; and paying attention to recruiting and selecting employees with good emotional intelligence.

This study contributes to the growing literature on AI by elucidating the mediating roles of job insecurity and emotional exhaustion in the relationship between AI awareness and physical and psychological withdrawal behavior. This study also makes a significant step forward in examining the moderating mechanisms of emotional intelligence in attenuating the effects of AI awareness on job insecurity, emotional exhaustion, physical and psychological withdrawal behavior.

This paper aims to investigate logistics operators’ acceptance of robots by adopting an integrated perspective of trust and technology acceptance.

A survey instrument was developed for data collection, targeting employees from Vietnam’s manufacturing or logistics sectors. A total of 401 valid responses were collected; the data were analysed using structural equation modelling.

Dispositional and situational trust positively influenced perceived usefulness and ease of use. Furthermore, dispositional and situational trust, perceived ease of use, and perceived usefulness collectively influenced trust in logistics robots. In addition, we found that trust in logistics robots positively affected operators’ acceptance intentions. Thus, the integrated perspectives of trust and technology acceptance were supported.

By focusing on the interaction between operators and logistics robots, this paper’s findings extend the technology acceptance model (TAM) and enrich the theory of trust.

The study has significant implications for factories integrating logistics robots into production processes by elucidating the relationship between operators and logistics robots.

Previous research has repeatedly identified trust considerations as a critical factor influencing individuals’ automated technology usage. However, the micro-level trust formation process has received limited attention. This study explains the relationship between perspectives on trust and technology acceptance.

Currently, innovation performance (IP) and innovation quality (IQ) are essential intertwined constructs that help small- and medium-sized enterprises (SMEs) thrive in a competitive business environment and achieve long-term success and sustainability. This paper aims to examine the effect of top management knowledge values (TMKVs), knowledge-oriented culture (KOC) and rewards on IP and IQ through knowledge sharing.

The authors used a deductive cross-sectional data approach and a standardized questionnaire adopted from the literature to obtain responses from the employees of Egyptian manufacturing SMEs. The authors based this study’s findings on 316 usable samples by applying the purposive sampling technique.

Using structural equation modeling (SEM) with path analysis using SmartPLS4, the findings of this study demonstrate that TMKV positively affects IP but not IQ. On the one hand, the KOC and knowledge-sharing process (KSP) are positive enablers of IP and IQ. On the other hand, knowledge-based reward (KBR) has an insignificant effect on IP and IQ. Moreover, while KSP mediates TMKV’s and KOC’s connections with IP and IQ, it does not mediate KBR’s relationship with IP and IQ.

This study’s findings will help policymakers and planners create strategies through knowledge management to improve employees’ vision, commitment and dedication, culminating in a favourable impact on IP and IQ. These findings highlight the need to foster a knowledge-based culture that promotes communication networks, establishes trust and enables individuals to make decisions to enhance organizational success, IP and IQ.

In the case of a developing country, this study helps to fill the gaps by offering an integrated framework that simultaneously explores knowledge management enablers, IP and IQ.

This study examines the efficiency dynamics of public health service providers in Colombia between 2010 and 2021. In order to achieve this objective, a data panel is utilized to assess the effectiveness of 841 institutions across three levels of complexity (1, 2 and 3) in providing patient care, taking into account user satisfaction from 2010 to 2021.

By employing growth mixture analysis (GMA) and other statistical techniques, we may identify unique efficiency profiles among hospitals with different levels of complexity.

The results demonstrate varied efficiency patterns, with certain profiles generally retaining or improving efficiency over time, while others observe fluctuations or reductions. Efficiency outcomes are significantly impacted by factors such as capital investment, operational costs and workforce mix. Efficiency levels can be improved by making strategic investments in capital infrastructure and implementing effective operational cost management.

Changes in the healthcare market conditions in recent years in Colombia have compelled healthcare providers (IPS) to transform themselves into sustainable organizations.

The study aims to investigate the implementation of green supply chain management (GSCM) in the footwear industry. It focuses on identifying key factors (dimensions and corresponding sub-dimensions) that promote GSCM and examines the importance and relevance of these factors in improving sustainability and competitive advantage within the footwear manufacturing supply chain.

A literature review and expert interviews were conducted to identify the factors for GSCM in the footwear industry. The DEMATEL-based ANP (DANP) method was used to analyze the importance and interrelationships of the identified dimensions and sub-dimensions. The data were collected through questionnaires and analyzed across different levels of the supply chain to compare the significant factors affecting GSCM implementation.

The study reveals that green purchasing is the core dimension, playing a critical role in the footwear industry. Organizational and environmental management emerges as the most influential causal factors, strongly correlated with other factors. However, as to sub-dimensions, different level of supply chain members should focus on different sub-dimensions.

This research provides valuable insights into the key dimensions and sub-dimensions and their causal relationships in the footwear industry. It offers practical suggestions for manufacturers to prioritize organizational and environmental management as a strategic approach to maximize the benefits of GSCM.