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The purpose of this study is to explore the coopetition relationships between platform owners and complementors in complementary product markets. Drawing on the coopetition theory, the authors examined the evolutionary trends of the coopetition relationships between platform owners and complementors and explore the main influence factors.

The authors used Lotka–Volterra model to analyze the coopetition relationship between platform owners and complementors, including the evolutionary trends as well as the results. Considering the feasibility of sample data collection, simulation is used to verify the effects of different factors on the evolution of coopetition relationships.

The results show that there are four possible results of the competition in the complementary products market. That comprises “winner-take-all for platform owners,” “winner-take-all for complementors,” “stable competitive coexistence” and “unstable competitive coexistence,” where “stable competitive coexistence” is the optimal evolutionary state. Moreover, the results of competitive evolution are determined by innovation subjects’ interaction parameters. However, the natural growth rate, the initial market benefits of the two innovators and the overall benefits of the complementary product markets influence the time to reach a steady state.

The study provides new insights into the entry of platform owners into complementary markets, and the findings highlight the fact that in complementary product markets, platform owners and complementors should seek “competitive coexistence” rather than “winner-takes-all.” Moreover, the authors also enrich the coopetition theory by revealing the core factors that influence the evolution of coopetition relationships, which further enhance the analysis of the evolutionary process of coopetition relationships.

Grounded in upper echelon (UE) theory, this study aims to examine the role of managerial competencies (business experience, financial literacy and digital literacy) in sustainable development strategy, with resource management as a mediator.

The empirical data collection is conducted through a survey completed by 297 top management teams of small and medium-sized enterprises (SMEs) operating in Pakistan. Structural equation modelling in Smart PLS is used to substantiate the hypotheses.

The findings reveal that financially and digitally literate managers significantly contribute to the sustainable development strategies of SMEs. However, experienced managers do not focus significantly on sustainable development strategies. Resource management partially mediates the nexus between financial literacy and sustainable development strategy, as well as between digital literacy and sustainable development strategy. In contrast, resource management does not mediate the nexus between business experience and sustainable development strategy.

This study recommends that SMEs should prioritize managers with digital and financial literacy over those with experience. SMEs led by a management team with digital and financial literacy are more effective in resource management for sustainable development practices, whereas experienced managers may not significantly prioritize managing resources for sustainability.

While research based on the UE theory significantly contributes to the body of knowledge on sustainable development, the role of managerial competencies, particularly business experience, financial literacy and digital literacy, in sustainable development strategy via resource management is neglected. This research fills this gap in the context of UE theory and thereby enriches the literature.

Express freight transportation is in rapid development currently. Owing to the higher speed of express freight train, the deformation of the bridge deck worsens the railway line condition under the action of wind and train moving load when the train runs over a long-span bridge. Besides, the blunt car body of vehicle has poor aerodynamic characteristics, bringing a greater challenge on the running stability in the crosswind.

In this study, the aerodynamic force coefficients of express freight vehicles on the bridge are measured by scale model wind tunnel test. The dynamic model of the train-long-span steel truss bridge coupling system is established, and the dynamic response as well as the running safety of vehicle are evaluated.

The results show that wind speed has a significant influence on running safety, which is mainly reflected in the over-limitation of wheel unloading rate. The wind speed limit decreases with train speed, and it reduces to 18.83 m/s when the train speed is 160 km/h.

This study deepens the theoretical understanding of the interaction between vehicles and bridges and proposes new methods for analyzing similar engineering problems. It also provides a new theoretical basis for the safety assessment of express freight trains.

Testing several approaches for implied volatility modeling and forecasting.

Comparative empirical study with four traded options.

Non-parametric higher-order spline is better than parametric stochastic volatility inspired (SVI) in China.

Our results imply that even though popular on Wall Street, SVI seems not to be utilized by traders and market-makers in China.

Traders may consider higher-order spline as a better method for implied volatility modeling and forecasting.

Propose to model and forecast implied volatility via the fifth-order spline interpolation as a first; initiates studies of the empirical performance of SVI and the fifth-order spline models in implied volatility modeling and forecasting.

Given the current friction and wear challenges faced by automobile parts and bearings, this study aims to identify a novel texture for creating anti-friction and wear-resistant surfaces. This includes detailing the preparation process with the objective of mitigating friction and wear in working conditions.

Femtosecond laser technology was used to create a mango-shaped texture on the surface of GCr15 bearing steel. The optimized processing technology of the texture surface was obtained through adjusting the laser scanning speed. The tribological behavior of the laser-textured surface was investigated using a reciprocating tribometer.

The friction coefficient of the mango-shaped texture surface is 25% lower than that of the conventional surface, this can be attributed to the reduced contact area between the friction ball and the micro-textured surface, leading to stress concentration at the extrusion edge and a larger stress distribution area on the contact part of the ball and disk compared to the conventional surface and the function of the micro-texture in storing wear chips during the sliding process, thereby reducing secondary wear.

The mango-shaped textured surface in this study demonstrates effective solutions for some of the friction and wear issues, offering significant benefits for equipment operation under light load conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0127/

The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.

This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.

The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.

Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/

The purpose of this study is to evaluate the tannase-assisted extraction of tea stem pigment from waste tea stem, after which the stability of the purified pigment was determined and analyzed.

The extracting process was optimized using the response surface methodology (RSM) approach. Material-liquid ratio, temperature and time were chosen as variables and the absorbance as a response. The stability of the tea stem pigment at the different conditions was tested and analyzed.

The optimized extraction technology was as follows: material-liquid ratio 1:20 g/ml, temperature 50°C and time 60 min. The stability test results showed that tea stem pigment was sensitive to oxidants, but the reducing agents did not affect it. The tea stem pigment was unstable under strong acid and strong alkali and was most stable at pH 6. The light stability was poor. Tea stem pigment would form flocculent precipitation under the action of Fe²⁺ or Fe³⁺ and be relatively stable in Cu²⁺ and Na²⁺ solutions. The tea stem pigment was relatively stable at 60°C and below.

No comprehensive and systematic study reports have been conducted on the extraction of pigment from discarded tea stem, and researchers have not used statistical analysis to optimize the process of tannase-assisted tea stem pigment extraction using RSM. Additionally, there is a lack of special reports on the systematic study of the stability of pigment extracted from tea stem.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

The study aims to synthesize existing knowledge and proposes a research framework for building a resilient supply chain (SC) through artificial intelligence (AI) technology. It also identifies existing literature gaps and paves the way for a future research agenda.

A systematic literature review has been carried out to identify the peer-reviewed articles from Scopus and Web of Science databases. Then, the selected articles published between 2012 and 2023 are analyzed using descriptive and thematic analysis methods to unearth research gaps and offer new research directions.

Descriptive and thematic analysis reveals the overall development of literature on the role of AI for supply chain resilience (SCR). Based on the findings of the thematic analysis, the motivation, application, capability and outcome (MACO) framework has been developed and propositions have been proposed. Several future research directions have also been suggested in terms of theory, context and methodology (TCM).

The study provides a fresh perspective on the integration of AI technology within the realm of SCR. The developed MACO framework serves as a practical tool for supply chain management (SCM) professionals, offering a nuanced understanding of AI's applications across various functional areas to streamline operations, minimize waste and optimize resource utilization, thereby helping them in strategic planning.

This study contributes to the literature on the role of AI for building SCR by uncovering gaps, offering research directions and developing propositions for future research directions.

Polyaniline (PANI) has garnered attention for its potential applications in anticorrosion fields because of its unique properties. Satisfactory outcomes have been achieved when using PANI as a functional filler in organic coatings. More recently, research has extensively explored PANI-based organic coatings with self-healing properties. The purpose of this paper is to provide a summary of the active agents, methods and mechanisms involved in the self-healing of organic coatings.

This study uses specific doped acids and metal corrosion inhibitors as active and self-healing agents to modify PANI using the methods of oxidation polymerization, template synthesis, nanosheet carrier and nanocontainer loading methods. The anticorrosion performance of the coatings is evaluated using EIS, LEIS and salt spray tests.

Specific doped acids and metal corrosion inhibitors are used as active agents to modify PANI and confer self-healing properties to the coatings. The coatings’ active protection mechanism encompasses PANI’s own passivation ability, the adsorption of active agents and the creation of insoluble compounds or complexes.

This paper summarizes the active agents used to modify PANI, the procedures used for modification and the self-healing mechanism of the composite coatings. It also proposes future directions for developing PANI organic coatings with self-healing capabilities. The summaries and proposals presented may facilitate large-scale production of the PANI organic coatings, which exhibit outstanding anticorrosion competence and self-healing properties.