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Drawing upon strengths-based inclusive work theory, this study explores how strengths-based leadership promotes employee career sustainability, particularly in the absence of protean career orientation (PCO), with career adaptability as a mediator.

A three-wave survey of 329 Chinese employees tested the moderated mediation model. Hypotheses were assessed using SPSS 26.0 and Mplus 8.3.

Strengths-based leadership positively influences career adaptability, leading to greater career sustainability. The effect is stronger when PCO is low, highlighting the compensatory role of strengths-based leadership.

The present paper extends the existing literature on strengths-based leadership and unveils that strength-based leadership can compensate for a lack of PCO. Also, it augments strengths-based inclusive work theory and provides meaningful insights to cultivate employee career sustainability.

The cross-sectional design and self-reported data limit causal conclusions. Future research should use longitudinal methods and diverse cultural contexts to improve generalizability.

This paper aims to study the problem of starvation lubrication of high-speed ball bearings due to temperature rise during operation and to avoid thermal failure of bearing lubrication.

Under the quasi-statics model of grease lubrication, both the oil film dragging force and the rolling friction between the balls and raceways collectively counteract the gyroscopic torque. Initially, the static model for grease lubrication is solved, followed by calculating the generated heat using the local heat generation method and ultimately the multinodal thermal network model is solved, and the solved results of the quasi-statics are updated by the temperatures of the grease nodes based on the relationship of the grease temperature and viscosity, as well as the relationship of the viscosity and the film thickness.

By comparing the numerical calculation results of bearings under different working conditions, the influence of starvation lubrication on the oil film thickness, oil film drag force and rolling friction of bearings is discussed, and it is found that the numerical calculation results of the outer ring temperature of bearings under the starvation lubrication due to the consideration of temperature rise are closer to the experimental values.

This study reveals the dynamic characteristics of bearings under starvation lubrication, which is more practical and engineering guiding significance for the design of bearings, and introduces a new method and basis for the calculation of temperature rise of rolling bearings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0208/

Despite the continuous development and application of new digital technologies in the construction industry, there has been little research on digital technology trajectories in the construction industry. The study addresses the issue faced by the construction industry in exploring digital technology trajectories: how to comprehensively identify and analyse digital technology pathways across multiple technology fields in the construction industry.

Firstly, the digital technology patent identification and classification method based on text mining is used to identify digital technology patents and construct a digital technology innovation network. Second, the main path of the digital technology innovation network is identified with the help of SPNP. Then, the subpaths of the digital technology innovation network are identified with the help of the Louvain algorithm and SPNP. Finally, starting from the technology nodes where the main path and subpaths intersect, the technological similarity of the paths is analysed to explore the evolutionary characteristics of the technology trajectories. In light of this, the developed method is applied to the global construction industry patent dataset to analyse the trajectories of digital technologies.

The technological innovation path in the construction industry starts with construction materials and gradually expands to intelligence, automation and digital data processing technology. Equipment and devices with electronic digital data processing capabilities as well as improvements in green building technologies and user experience-enhancing technologies, may be the future of the construction industry. With the increasing demand for green buildings and intelligent buildings, the direction of digital technology innovation in the construction industry is gradually tilted towards these areas. In addition, influenced by geographic and economic factors, there is a spatial clustering effect of digital technology innovation in the construction industry.

Future research should analyse in depth the performance of different countries and regions in digital technology innovation and explore the root causes, motivations and influencing factors behind it, such as the policy environment, the level of the economy and the investment in research and development. Exploring the reasons affecting digital technology innovation can help formulate more targeted policies and promote cooperation and exchange of digital technology innovation in the global construction industry. Meanwhile, to solve the problems of overly broad IPC categorization and the difficulty of accurately describing cross-field innovations, combining IPC co-occurrence networks with patent citation networks is an effective strategy. This strategy can track technologically interrelated patents and provide more specific contents to know the advantages and challenges of the construction industry in the field of digital technology innovation.

The study has practical implications for the construction industry. The identification of digital technology innovation trajectories provides valuable insights for industry firms and research institutes. It helps them understand the current and future directions of digital technology in construction, enabling them to stay at the forefront of technological advancements. The findings highlight the importance of focusing on areas such as solar energy utilisation, green energy, intelligence, automation and data applications. This knowledge can guide firms in developing new building materials, incorporating digital information technologies and enhancing user experiences. The study’s results can inform strategic decision-making, technology adoption and innovation management in the construction sector.

The social implications of this study are significant for various stakeholders. The identification of digital technology innovation trajectories in the construction industry highlights the potential benefits for society. The focus on green energy, intelligent buildings and enhanced user experiences aligns with the increasing demand for sustainability, energy efficiency and comfortable living environments. These technological advancements can contribute to reducing environmental impact, improving quality of life and promoting sustainable development. The findings can inform policymakers, urban planners and architects in shaping regulations, designing sustainable cities and creating buildings that prioritize energy efficiency and user well-being. Ultimately, the study’s social implications aim to foster a more sustainable and livable built environment.

An identification method integrated with SPNP and the Louvain algorithm is developed to map digital technology innovation trajectories in the construction industry. This study helps to reveal the trajectories of digital technology innovation, provides new perspectives, insight and ideas for research in related fields and has great potential for applications in practice to promote the innovation and development of the construction industry.

Exponential organizations (ExOs) are purpose-driven companies that leverage exponential technologies and exponential business practices to grow and scale rapidly, transform industries and create massive value and impact. In contrast, non-ExOs follow a linear approach to business and organizational strategy design and execution. This study aims to validate the hypothesis, based on financial metrics, that ExOs outperform their competitors and linear counterparts. Furthermore, it also brings a new understanding of the gap raised in the past eight years about how ExOs can achieve significantly better performance, measured with financial metrics.

For measuring how exponential an organization is, this study elaborated a completely new assessment tool called Exponential Quotient (ExQ). This study applied ExQ to the 100 largest US headquartered companies as ranked by Fortune magazine in 2014. Calculating the ExQ enabled this study to rank these Fortune 100 companies and identify the most and the least exponential firms. This study tracked these companies as to how they performed on different financial metrics over the eight years of 2014–2021 and analyzed the results.

Through the analysis, this study revealed that the top 10 ExOs have significantly outperformed their bottom 10 non-exponential peers, delivering 40x higher shareholder returns, 2.6x better revenue growth, 6.8x higher profitability and 11.7x better asset turnover. Furthermore, this study could identify commonalities and similarities between the two groups. This means that ExOs can thrive even in tough times and that accelerating technologies unlock abundance and allow every organization to become a disruptive innovator and stay ahead of the competition. These are novel results in the research focusing on the gap between exponential and traditional organizations.

Using the ExQ diagnostics tool, every organization can see how flexible, scalable and agile they are, which is the starting point for an exponential transformation program. Although this approach has already found its way into practice and is applied globally by thousands of organizations (startups, scaleups and incumbents), so far, the academic establishment is in its nascent phase. With this research, the authors wanted to extend this field of science. On the other hand, because of its novelty, no appropriate previous studies existed to compare the results.

The possible implications showed that there is a plannable way for significantly increasing an organization’s ExQ and advance it from a linear toward an exponential organizational model.

The results validated the robustness of the ExO framework and philosophy and shed light on the importance of exponential transformation – a proven method to increase an organization’s ExQ. This framework is not a “how to be successful” guide. Instead, it uncovered some of the previously unknown and universal mechanisms of scalability – which, in turbulent times, make companies successful (based on financial metrics). To the best of the authors’ knowledge, this study was among the first kind of in-depth analyses to validate the whole ExO model.

A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the interaction among evaluators and improve the credibility of evaluation results.

This paper proposes a multi-stage approach for design concept evaluation based on complex network and bounded confidence. First, a network is constructed according to the evaluation data. Depending on the consensus degree of evaluation opinions, the number of evaluation rounds is determined. Then, bounded confidence rules are applied for the modification of preference information. Last, a planning function is constructed to calculate the weight of each stage and aggregate information at multiple evaluation stages.

The results indicate that the opinions of the evaluators tend to be consistent after multiple stages of interactive adjustment, and the ordering of design concept alternatives tends to be stable with the progress of the evaluation.

Updating preferences according to the bounded confidence rules, only the opinions within the trust threshold are considered. The attribute information of the node itself is inadequately considered.

This method addresses the need for considering the evaluation information at each stage and minimizes the impact of disagreements within the evaluation group on the evaluation results.

This study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) and provide the knowledge graph (KG) comprehensively and systematically. By presenting the relationship among content, discipline, and author, this study focuses on providing services for knowledge discovery of ancient Chinese scientific and technological documents.

This study compiles ancient Chinese STDBS and designs a knowledge mining and graph visualization framework. The authors define the summaries' entities, attributes, and relationships for knowledge representation, use deep learning techniques such as BERT-BiLSTM-CRF models and rules for knowledge extraction, unify the representation of entities for knowledge fusion, and use Neo4j and other visualization techniques for KG construction and application. This study presents the generation, distribution, and evolution of ancient Chinese agricultural scientific and technological knowledge in visualization graphs.

The knowledge mining and graph visualization framework is feasible and effective. The BERT-BiLSTM-CRF model has domain adaptability and accuracy. The knowledge generation of ancient Chinese agricultural scientific and technological documents has distinctive time features. The knowledge distribution is uneven and concentrated, mainly concentrated on C1-Planting and cultivation, C2-Silkworm, and C3-Mulberry and water conservancy. The knowledge evolution is apparent, and differentiation and integration coexist.

This study is the first to visually present the knowledge connotation and association of ancient Chinese STDBS. It solves the problems of the lack of in-depth knowledge mining and connotation visualization of ancient Chinese STDBS.

This study aims to investigate the acoustic roughness of rails on China’s high-speed railways, with a focus on short-wavelength irregularities (less than 80 cm), which are known to significantly contribute to noise. The goal is to develop a specific acoustic roughness spectrum tailored for China’s high-speed railway system, as no such spectrum currently exists.

A long-term tracking study was conducted on major railway lines in China, monitoring rail roughness throughout the initial operational period and the rails’ service life. Data preprocessing techniques such as peak removal and curvature correction were applied for acoustic adjustments. A spatial-wavelength domain transformation was performed, providing the distribution patterns and statistical characteristics of acoustic roughness on China’s high-speed rails. Based on these analyses, a model for constructing the acoustic roughness spectrum was developed.

The study found that the acoustic roughness of China’s high-speed railway rails follows a χ² distribution with six degrees of freedom. For wavelengths greater than 8 cm, the acoustic roughness spectrum remains below the ISO specified limits. In the wavelength range of 3.2 cm to 6.3 cm, the roughness is comparable to or within the limits specified by ISO 3095:2005 and ISO 3095:2013. However, for wavelengths shorter than 2.5 cm, the roughness exceeds ISO limits.

This research fills the gap in the lack of a specific acoustic roughness spectrum for China’s high-speed railways. By establishing a tailored spectrum based on long-term data analysis, the findings provide valuable insights for noise control and rail maintenance in the context of China’s high-speed rail system.

This study aims to investigate the impact of emotional perceived value on hotel guests’ satisfaction, affective commitment and loyalty.

Data were collected from 348 respondents living in the United Arab Emirates, and hypotheses were tested using AMOS 28 and structural equation modeling.

This study’s unique contribution lies in its revelation that emotional perceived value directly impacts guests’ satisfaction, affective commitment and loyalty. Furthermore, it uncovers that emotional-perceived value indirectly influences loyalty through satisfaction and affective commitment.

This research underscores the importance of hotel managers prioritizing guests’ emotional perceived value in their offerings. Managers can significantly enhance guests’ satisfaction, affective commitment and loyalty by highlighting self-gratification, aesthetics, prestige, transaction and hedonics.

This study brings a fresh perspective to understanding customer perceived value (CPV). It argues that the mere emphasis on the functional aspect of CPV would likely fall short of fully comprehending specific outcomes of their experience (e.g. satisfaction-dissatisfaction, loyalty, etc.). Assessing the emotional aspect of CPV, known as emotional customer perceived value (ECPV), adds further explanations and sheds light on the understanding of the CPV concept and its impacts on consumers’ experience. Furthermore, this study emphasizes that emotional perceived value is better comprehended as a multidimensional rather than a unidimensional construct. It adds that the concept of customer value as a multidimensional concept is context-specific (i.e. dimensions vary from one service sector to another), providing a unique and valuable perspective for the luxury hotel industry.

The purpose of this study is to investigate the influence of ambidextrous strategy on supply chain resilience and its impact on firm performance, employing the Dynamic Capabilities View.

Through a survey of 215 supply chain professionals, the research employs a structural equation modeling analysis to examine the relationships between ambidexterity, agile operations, resilience, and performance.

The findings demonstrate that the ambidextrous strategy significantly enhances both agile operations and supply chain resilience. In turn, agile operations and resilience positively impact firm performance. The study also reveals that agile operations and supply chain resilience partially mediate the relationship between ambidextrous strategy and firm performance.

This research contributes to the supply chain management literature by highlighting the importance of an ambidextrous approach in fostering agile operations and resilience, thereby improving firm performance. It extends the dynamic capabilities view framework by elucidating how ambidexterity acts as a pivotal mechanism for adapting to disruptions and securing competitive advantage in volatile markets. Finally, measurements of ambidextrous strategy and resilience are provided to further enhance practitioners’ understanding of building these important components in networks.

The purpose of this study is to examine the influence of ESG practices on green innovation with the moderating effect of innovation orientation in Malaysian manufacturing listed companies.

This study employed a quantitative research approach by using a well-structured questionnaire for data collection. The questionnaire was distributed to 204 Malaysian manufacturing listed companies in consumer products and services sector. Finally, partial least square-structural equation modeling (PLS-SEM) was utilized to examine the relationship between constructs.

Based on stakeholder theory, results indicated that environmental, social and governance (ESG) practices significantly improve green innovation. The insignificant moderating effect of innovation orientation was identified between the relationship of environmental and social practices and green innovation. Interestingly, results affirmed the negative moderating effect between the relationship of governance practices and green innovation.

This study is limited to Malaysian manufacturing companies of consumer products and services sector in Bursa Malaysia. Hence, the findings of this study cannot be generalized to manufacturing companies of other geographical contexts.

This work provides constructive implications to management and policymakers of Malaysian manufacturing companies in strategic planning toward enhancing green innovation and developing business competitiveness to achieve sustainable business performance.

This research magnifies valuable insights into the literature through a comprehensive model that simultaneously investigates the relationships between ESG practices, innovation orientation and green innovation. In addition, this is the first attempt to investigate the influence of ESG practices on green innovation with a moderating effect of innovation orientation, which indeed strengthens the originality of this study.