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To reduce the wheel maintenance costs caused by wheel wear and to transition from traditional periodic maintenance to condition-based maintenance for railway freight wagons, it is necessary to investigate the prediction of wheel wear and understand the evolution rule of wheel profile wear.

This paper established a wheel wear prediction model for railway freight wagons based on Archard’s wear theory and proposed a prediction method that combines vehicle system dynamic, interpolation iteration and intelligent simulation. The wear coefficients in the model were obtained through wheel wear tests by using the roller rig. The model’s effectiveness was further verified through line testing and simulation models, and the corrected wear coefficient can be used for wear prediction of heavy-haul freight wagons in China.

The wheel wear prediction showed that the results of the wheel wear prediction model by adopting the wear coefficients obtained from the roller rig tests are close to the actual wheel wear, with the difference of the maximum in wear depth at the nominal rolling circle being within 7%.

This paper proposed a method that can establish a database of wheel wear coefficients for predicting wheel wear of railway freight wagons under similar operating conditions. The revised wear coefficient can be used for wear prediction of heavy-haul freight wagons in China.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0329/

This study investigates the factors affecting the performance of smallholder oil palm farmers in Indonesia, with an emphasis on sustainable productivity.

The study involved interviews with regulators, practitioners and experienced farmers in Riau, West Kalimantan, Central Kalimantan and the Bangka Belitung Islands, Indonesia. A confirmatory and explanatory approach was used to explore the relationships among farmer competency, social capital, institutional support, sustainable productivity and overall performance. Data from 757 farmers were analyzed using partial least squares structural equation modeling (PLS-SEM), while the analytical network process (ANP) method identified strategic priorities.

The results indicate that the sustainability of oil palm farming was low. Social capital, institutional support and sustainable productivity are the key performance factors. Sustainable productivity mediates these relationships. Farmers’ competence indirectly affects performance through sustainable productivity, social capital and institutions. Institutional support needs to be improved.

This study suggests expanding sustainability indicators by following the latest standards of RSPO principles and criteria, simplifying language for better farmer understanding and assessing sustainability before and after policy implementation.

The proposed policy framework emphasizes social capital, institutional support and sustainable productivity to improve sustainability and effectiveness.

This study highlights the critical role of social capital, institutional support and sustainable productivity in enhancing Indonesian palm oil farmers’ sustainability and performance.

This unique integrated approach combining PLS-SEM and ANP methodologies provides a comprehensive understanding of the factors affecting smallholder performance and data-driven strategic priorities for policy interventions.

The impact of FinTech in sub-Saharan Africa has primarily been limited to financial inclusion. Contrarily, this study aims to deviate from this norm to estimate how FinTech affects carbon emissions in the subregion. This provides policy recommendations for FinTech regulators, service providers and practitioners to consider optimal products and services that reduce carbon emissions.

A balanced panel data set from 2009 to 2020 is used and estimated with the fully modified ordinary least squares estimator after checking for cross-sectional dependence, unit root, stationarity and cointegration.

Results from the estimation suggest a negatively significant relationship between financial technology and carbon emissions in these countries. However, domestic credit to the private sector revealed a statistically insignificant relationship with carbon emissions for the same period. Further, foreign direct investment reduces carbon emissions but gross domestic product and trade openness increase carbon emissions in these countries.

The impact of FinTech in sub-Saharan Africa has primarily been limited to financial inclusion. Contrarily, this study deviates from this norm and estimates how FinTech affects carbon emissions in the subregion.

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.