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This work intends to evaluate experimentally the ratcheting behaviour of AM MS300. Furthermore, cyclic plasticity modelling (modified Abdel-Karim and Ohno model) is examined as a means of predicting ratcheting.

Uniaxial stress-controlled cyclic loading histories were utilised to evaluate ratcheting for Maraging Steel 300 (MS300) fabricated via laser powder bed fusion (LPBF) additive manufacturing (AM). Heat-treated and as-built AM and conventionally manufactured (CM) MS300 coupons were tested at room temperature, under constant and incrementally variable stress amplitude and mean stress. Two sets of AM test coupons were used, printed at horizontal and vertical built orientation. The AM material ratcheting was predicted via constitutive modelling and numerical simulation. The Abdel-Karim and Ohno cyclic plasticity model was modified by introducing a memory surface, to improve ratcheting prediction.

The hysteresis stress–strain response and low cycle fatigue (LCF) life were obtained from the different loading histories. Both the AM and CM MS300 exhibited an accumulation of axial strain (ratcheting) for all tests, attributed to the application of non-zero mean stress. The AM MS300 has demonstrated a higher ratcheting accumulation rate than the CM material. The achieved agreement between the numerical results of the new model and the experimental data offers an indication on the suitability and the robustness of this model.

The ratcheting behaviour of the AM MS300 material has been characterised for the first time in the published literature, for a variety of loading histories selected. A modified Abdel-Karim and Ohno plasticity model has been developed to account for the ratcheting performance of this material.

This study explores the antecedent configurations shaping ambidextrous environmental strategy (AES) and the subsequent performance outcomes. The lack of literature from the configurational perspective and inconsistent performance results suggest that this study has significant implications for practitioners, policymakers and the public. Therefore, this study aims to investigate how different antecedent conditions interact to shape AES and subsequent performance outcomes.

To achieve the research aims, the current research utilize research techniques based on technology–organization–environment framework and configurational perspective. This study collects data from 317 Chinese manufacturing enterprises and tests the theoretical framework using fuzzy set qualitative comparative analysis and propensity score matching.

Perceived institutional pressure, green supply chain integration and digital technology adoption form four paths that lead to the existence of AES. There are four sets of replaceable conditions between distinct paths. In addition, except for configuration P3, all other configurations promote environmental, operational and financial performance.

Our results provide new insights for enterprises to shape AES and achieve multiple performances, and new ideas for promoting environmental policies and public environmental awareness.

This study adds literature on AES and confirms multiple drivers, revealing their interaction mechanisms and key antecedent conditions. In addition, this study promotes the performance practice of AES by examining different AES configurations that achieve triple performance and insignificant operational performance.

This article examines the relationships between objective overqualification, volunteering as an extra-work activity and job satisfaction.

The study draws on a vast secondary sample of 20,686 British employees across four waves covering the period 2009–2017. The bivariate ordered probit estimate was used to test the study hypotheses in the bioprobit procedure in STATA.

Our study unravels compelling insights. Overqualified employees experience lower job satisfaction and engage more in volunteering activities. The results emphasised that voluntary work allows the utilisation of skills and fulfils basic psychological needs, leading to enhanced general well-being and higher job satisfaction.

Overqualified employees, by actively engaging in volunteering, not only make valuable contributions to society but also experience positive spillover effects that significantly influence their workplace attitudes and behaviours. This underscores the potential for promoting volunteering as an effective means to mitigate the private and social overqualification.

This study provides valuable insights into the role of overqualification as well as resulting job dissatisfaction, in shaping volunteering decisions. This insight contributes to the overqualification literature and strengthens our understanding of volunteering as an important mechanism in the relationship between overqualification and job satisfaction.

Machinery operating in a sand-dust environment is more susceptible to sand particles. The purpose of this paper is to investigate the impact of sand particle deposition rate, surface hardness and normal load on the tribological performance.

A predictive model to approximate the number of sand particles within the pin-on-disc contact surface is proposed. The efficacy of the model is validated through experimental method, which replicates a sand environment with two distinct particle deposition rates. Dry sliding friction experiments are also conducted using 45 carbon steel and H90 brass pins against GCr15 bearing steel discs.

When at high particle deposition rate [6.89 × 10^–5 g/(s·mm²)], the contact surfaces are separated by particles, resulting in an indirect metal contact. While at low deposition rate [6.08 × 10^–8 g/(s·mm²)], there is an alternating occurrence of direct and indirect metal contacts. In sand environment, the specific wear rate of 45 and H90 decreases by 50% and 33%, respectively, compared to non-sand environment when the applied load is 2.45 N. However, it is only 0.18% for 45 but remains significant at 25% for H90 at load of 9.8 N.

The predictive model and experimental method used in this paper are helpful for understanding the interaction between particles and sliding surfaces, thereby providing a solid foundation for material selection and load optimization of friction pairs influenced by sand-dust environments.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0155/

The present study aims to inform the requirements for developing a sustainable rating tool for small-scale infrastructure projects (SSIPs) through research findings.

A review-based comparative study of existing infrastructure sustainability (IS) rating tools for assessment of SSIPs is presented. Key stakeholder participants of the existing IS rating tools, are interviewed to identify existing barriers and requirements for sustainability rating. The study further presents possible rating tool options to optimise the sustainable performance evaluation of SSIPs.

Findings of this study indicated that prevalent IS rating tools are majorly applied to large-scale infrastructure projects and sustainability of SSIPs are seldom assessed. Based on a literature review and series of interviews, it was found that user friendliness, efficient structure, training and technical support, cost effectiveness and stakeholder recognition are the five key requirements of a sustainability rating tool for SSIPs. Additionally, six sustainability assessment options were proposed for SSIPs which range from pathways for existing tools through to new, customisable tools. Upon comparison, a new modified tool with verification process and revised tool with defined grouping of sustainable criteria was more effective for evaluation of SSIPs.

Use of case specific information for validation and framework development may lack generalisation. However, methodology can be used for future decision-making by making necessary adjustments to suit different local regional requirements.

Despite lack of generalisation, the findings can lead to future general studies on sustainability of SSIPs. Findings of the study provide foundation knowledge and awareness for sustainability evaluation of SSIPs.

This paper examines how soft skills training for owner-managers affects the financial performance of exporting small and medium-sized enterprises (SMEs). Furthermore, the authors examine the differential influence of specific owner-manager skills, such as “team working skills”, “technical skills” and “leadership skills”, on performance.

The paper utilises the Longitudinal Small Business Survey, which is a nationally representative employer dataset of UK SMEs with up to 249 employees, including those with no employees. The dataset contains information on firms' turnover, export status of goods or services and training provision for employees or owner-managers.

The results suggest that owner-manager's training has a positive effect on turnover in non-exporting firms. Moreover, a combination of soft and hard skills is associated with higher turnover in exporting firms. Amongst the specific skills of owner-managers, training on “team working” has the most significant impact on exporting SMEs' performance.

The authors' findings imply that managerial training to develop soft skills such as leadership, decision-making and communication is a worthwhile investment. The knowledge that owner-managers acquire through soft and hard skills training enables them to develop essential internationalisation competencies. Moreover, the authors demonstrate that teamwork is a significant predictor of performance.

The authors contribute to the literature by examining the role of owner-managers' training in shaping internal systems, structure, processes and internationalisation strategies, thus affecting SMEs performance. The authors' also provide a nuanced analysis of how various types of soft and hard skills underpin the successful implementation of internationalisation initiatives.

The purpose of the present study was to investigate the interrelationships among the dimensions of sport event experience, event satisfaction and event behavioral intentions.

The sample was comprised of 186 individuals who actively participated in a mass participation sport event. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the relationships among the latent constructs.

The results indicated that the dimensions of sport event experience predicted 55% of the variance of event satisfaction and 63% of the variance of event behavioral intentions was predicted by sport event experience dimensions and event satisfaction. Specifically, the sensory, affective and relational dimensions of experience sought to have a statistically significant and positive association with event satisfaction, while event satisfaction and the relational dimension of experience were found to have a statistically significant and positive correlation with event behavioral intentions. In addition, event satisfaction was found to mediate the relationships between sensory, affective and relational experiences and event behavioral intentions.

The present study is one of the first that explores the relationships among sport event experience’s dimensions, event satisfaction and positive behavioral intentions in the context of sport event participation.

Significant developments in the service sector have been brought about by Industry 4.0. Automated digital technologies make it possible to upgrade existing services and develop modern industrial services. This study prioritizes critical factors for adopting Industry 4.0 in the Indian service industries.

The author identified four criteria and fifteen significant factors from the relevant literature that have been corroborated by industry experts. Models are then developed by the analytical hierarchy process (AHP) and analytical network process (ANP) approach to ascertain the significant factors for adopting Industry 4.0 in service industries. Further, sensitivity analysis has been conducted to determine the sensitivities of the rank of criteria and sub-factors to corroborate the results.

The outcome reveals the top significant criteria as organizational criteria (0.5019) and innovation criteria (0.3081). This study prioritizes six significant factors information technology (IT) specialization, digital decentralization of all departments, organizational size, smart services through customer data, top management support and Industry 4.0 infrastructure in the transition toward Industry 4.0 in the service industries.

The potential factors identified in this study will assist managers in determining strategies to effectively manage the Industry 4.0 transition by concentrating on top priorities when leveraging Industry 4.0. The significance of organizational and innovation criteria given more weight will lay the groundwork for future Industry 4.0 implementation guidelines in service industries.

Our research is novel since, to our knowledge, no previous study has investigated the potential critical factors from organizational, environmental, innovation and cost dimensions. Thus, the potential critical factors identified are the contributions of this study.

This study explores the impact mechanism of corporate digital transformation (CDT) on the quality of accounting information.

Samples of A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2007 to 2020 are used as a research sample. The empirical analysis is based on the ordinary least squares regression model, and mediation and moderation effect models were used in further analysis.

This study finds that CDT enhances accounting information quality by alleviating the agency problem. This positive effect is more significant among firms that exhibit less media coverage, have low industry competition and are not subject to cyber-attack.

This study extends the economic consequences of CDT and enriches the literature on the factors that affect accounting information quality. Further, this study's findings guide the government to actively promote CDT, facilitate the digital upgrading of industries and improve accounting information quality and efficiency in capital markets.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.