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The importance of service firms cooperating with digital platforms is widely acknowledged. The authors study three contractual relationships (fixed-cost, cost-sharing, and profit-sharing) between service firms (specifically hotels) and digital platforms in a highly fragmented service supply chain to examine which of these contract types optimizes profits.

The authors extend prior models analyzing the optimal expected total profit from the travel service firm (hotel)–digital platform relationship, providing new insights into each contract type’s ability to coordinate decentralized systems and optimize profits for both parties.

This study finds that fixed cost contracts cannot coordinate the decentralized system. Cost-sharing contracts can coordinate the decentralized system but only allow one channel profit split. In contrast, profit-sharing contracts may not always perfectly coordinate the decentralized system but support alternative profit allocations. Practically, both profit-sharing and cost-sharing contracts are preferable to fixed-cost contracts.

The paper includes implications for travel service firm managers to consider when structuring contracts with digital platforms to focus on profit optimization. Profit-sharing contracts are most preferable when cost and revenue data are fully shared between parties, while cost-sharing contracts are preferable over fixed-cost contracts.

This study extends prior investigations into the utility of different contract types on the optimal profit of a travel service firm (hotel)-digital platform provider relationship. The research fills a gap in the literature concerning the contracts used in these relationship types.

This research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.

A total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.

The People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.

This study helps librarians, scientists and funders understand smart library trends.

There are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.

Aluminum foam-filled thin-walled unit structures have received much attention for their excellent energy absorption properties. To improve the energy absorption effect of car energy absorption box under axial compression, this paper optimizes the fiber lay-up sequence, fiber angle and aluminum foam density of aluminum foam filled carbon fiber reinforced plastic (CFRP) thin-walled square tubes.

Design of sample points required to construct the proxy model using design of experiments (DOE) method, and the data sample points of different models are obtained through Abaqus simulation and test. A double high-precision proxy model with the maximum specific energy absorption (SEA) and the minimum initial peak crash force (PCF) as the evaluation index is constructed based on the response surface function method. The NSGA-II multi-objective genetic algorithm was used to optimize the design parameters and obtain the optimal solution for the Pareto front, and the results were verified by using the multi-objective optimization toolbox in design-expert.

The results show that the optimal solution to the multi-objective optimization problem with the inclusion of the lay-up sequence is ρ = 0.5g/cm3 for a fiber lay-up angle varying in the range ±15–90° and an aluminum foam density varying in the range 0.2g/cm3-0.5g/cm3, with a lay-up method of [±87°/±16°/±15°/±89°]. The two optimization methods correspond to SEA and PCF errors of 2.109% and 4.1828%, respectively. The optimized SEA value is 18.2 J/g and the PCF value is 18,230 N. The optimized design reduces the peak impact force and increases the specific energy absorption, which improves the energy absorption effect of thin-walled energy-absorbing boxes for automobiles.

In this paper, the impact resistance of CFRP thin-walled square tubes filled with aluminum foam is optimized. Based on numerical simulations and experiments to obtain the sample point data for constructing the dual-agent model, we investigate the effect of filling with different densities of aluminum foam under the simultaneous change of fiber lay-up angle and order on its mechanical properties in this process, and carry out the multi-objective optimization design with NSGA-II algorithm.

The purpose of this study is to explore the interfacial adhesion between superhydrophobic coatings FC-X (X = 1%, 2%, 3%, 4% and 5%) and the concrete substrate, along with the impact of FC-X on the water repellency characteristics of the concrete substrate.

One synthetic step was adopted to prepare novel F-SiO₂ NP hybrid fluororesin coating. The impact of varying mass fractions of F-SiO₂ NPs on the superhydrophobicity of FC-X was analyzed and subsequently confirmed through water contact angle (WCA) measurements. Superhydrophobic coatings were simply applied to the concrete substrate using a one-step spraying method. The interfacial adhesion between FC-X and the concrete substrate was analyzed using tape pasting tests and abrasion resistance measurements. The influence of FC-X on the water repellency of the concrete substrate was investigated through measurements of water absorption, impermeability and electric flux.

FC-4% exhibits excellent superhydrophobicity, with a WCA of 157.5° and a sliding angle of 2.3°. Compared to control sample, FC-X exhibits better properties, including chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

This study offers a thorough investigation into the practical implications of enhancing the durability and water repellency of concrete substrates by using superhydrophobic coatings, particularly FC-4%, which demonstrates exceptional superhydrophobicity alongside remarkable chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

Through the examination of the interfacial adhesion between FC-X and the concrete substrate, along with an assessment of FC-X’s impact on the water repellency of the concrete, this paper provides valuable insights into the practical application of superhydrophobic coatings in enhancing the durability and performance of concrete materials.

With the development of Web information systems, steel e-commerce platforms have accumulated a large number of quality objection texts. These texts reflect consumer dissatisfaction with the dimensions, appearance and performance of steel products, providing valuable insights for product improvement and consumer decision-making. Currently, mainstream solutions rely on pre-trained models, but their performance on domain-specific data sets and few-shot data sets is not satisfactory. This paper aims to address these challenges by proposing more effective methods for improving model performance on these specialized data sets.

This paper presents a method on the basis of in-domain pre-training, bidirectional encoder representation from Transformers (BERT) and prompt learning. Specifically, a domain-specific unsupervised data set is introduced into the BERT model for in-domain pre-training, enabling the model to better understand specific language patterns in the steel e-commerce industry, enhancing the model’s generalization capability; the incorporation of prompt learning into the BERT model enhances attention to sentence context, improving classification performance on few-shot data sets.

Through experimental evaluation, this method demonstrates superior performance on the quality objection data set, achieving a Macro-F1 score of 93.32%. Additionally, ablation experiments further validate the significant advantages of in-domain pre-training and prompt learning in enhancing model performance.

This study clearly demonstrates the value of the new method in improving the classification of quality objection texts for steel products. The findings of this study offer practical insights for product improvement in the steel industry and provide new directions for future research on few-shot learning and domain-specific models, with potential applications in other fields.

This study aims to examine millennial consumers’ intentions towards purchasing eco-friendly products in the emerging Arab nation of Oman, focusing on the moderating role of eco-labelling (EL).

Environmental knowledge (EK) and environmental concern (EC) are integrated into the theory of planned behaviour (TPB) framework as independent variables, along with EL as a moderating variable. The data was collected through a self-administered survey and consisted of 705 random responses that was tabulated and analysed through the structural equation modelling technique.

ECs, subjective norms (SNs) and perceived behavioural control (PBC) significantly influence consumer attitudes towards green eco-friendly products. Consumers’ EK and attitudes positively influence the purchase intention (PI) to make green purchases. SNs and PBC substantially influence consumer attitudes towards adopting green products. However, the findings reveal a non-significant moderating influence of EL on the relationship between EC and PI for millennial Omani consumers.

The findings are limited to only one Arab country, Oman, which limits the scope of the study. This study contributes to the TPB by using additional dimensions to examine the green purchasing behaviour of millennials.

Marketers can use these insights to develop strategies that emphasise the environmental benefits of products, leverage social influences and empower consumers to make environmentally conscious choices. Incorporating EL and green packaging can enhance the visibility and attractiveness of green products.

Promoting environmental education, awareness campaigns and policy interventions that highlight the importance of eco-friendly product choices can foster more sustainable consumption patterns among Arab consumers.

To the best of the authors’ knowledge, this is the first study to examine the green PIs of millennials in an Arab context, specifically focusing on the moderating role of EL.

This study aims to study the formation mechanism of micro-arc oxidation (MAO) coating on AZ31 magnesium alloy and how the annealing process affects its corrosion resistance.

This study involved immersion experiments, electrochemical experiments and slow strain rate tensile experiments, along with scanning electron microscopy, optical microscopy observation and X-ray diffraction analysis.

The findings suggest that annealing treatment can refine the grain size of AZ31 magnesium alloy to an average of 6.9 µm at 300°C. The change in grain size leads to a change in conductivity, which affects the performance of MAO coatings. The MAO coating obtained by annealing the substrate at 300°C has smaller pores and porosity, resulting in better adhesion and wear resistance.

The coating acts as a barrier to prevent corrosive substances from entering the substrate. However, the smaller pores and porosity reduce the channels for the corrosive solution to pass through the coating. When the coating cracks or falls off, the corrosive medium and substrate come into direct contact. Smaller and uniform grains have better corrosion resistance.

The research analyzes the influence of three environmental triggers, i.e. awareness, concern and knowledge on environmental attachment and green motivation that affect tourists' pro-environmental behavior in the Pakistan’s tourism industry. Furthermore, this study has analyzed the moderating role of moral obligation concerning environmental attachment and green motivation on tourists' pro-environmental behavior.

Data were gathered via a structured questionnaire by 237 local (domestic) tourists of Pakistan. Furthermore, the data were examined by employing SmartPLS.

Findings demonstrate that all three environmental triggers have a positive and significant relationship with environmental attachment and green motivation. Accordingly, environmental attachment and green motivation promote tourists' pro-environmental behavior. Furthermore, the moderating role of moral obligations has also been incorporated in the study. The finding reveals a strong and positive relationship among environmental attachment and tourists' pro-environmental behaviors during high moral obligations. In contrast, moral obligations do not moderate association between green motivation and tourists' pro-environmental behavior. Therefore, competent authorities should facilitate tourists to adopt environmentally friendly practices; which will ultimately promote pro-environmental behavior.

This study provides useful insights regarding the role of tourism in fostering environmental attachment and green motivation that sequentially influence tourist pro-environmental behavior. Secondly, this research has employed moral obligations as a moderator to identify the changes in tourists’ pro-environmental behavior based on individuals' ethical considerations. Hence, the study provides an in-depth insight into tourists' behavior. Lastly, the present research offers effective strategies for the tourism sector and other competent authorities to increase green activities that can embed the importance of the environment among individuals.