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This paper aims to further our understanding of policy–practice gaps in organizations from an organizational learning perspective. The authors conceptualize and analyze policy–practice gaps in terms of what they label the dual challenge of organizational learning, i.e. the organizational tasks of both adapting ongoing practices to prescribed policy demands and adapting the policy itself to the needs of practice. Specifically, the authors address how this dual challenge can be understood in terms of organizational learning and how an organization can be managed to successfully resolve the dual learning challenge and, thereby, bridge policy–practice gaps in organizations.

This paper draws on existing literature to explore the gap between policy and practice. Through a synthesis of theories and an illustrative practical example, this paper highlights key conceptual underpinnings.

In the analysis of the dual challenge of organizational learning, this study provides a conceptual framework that emphasizes the important role of tensions and contradictions between policy and practice and their role as drivers of organizational learning. To bridge policy–practice gaps in organizations, this paper proposes five key principles that aim to resolve the dual challenge and accommodate both deployment and discovery in organizations.

Because this is a conceptual study, empirical research is called for to explore further and test the findings and conclusions of the study. Several avenues of possible future research are proposed.

This paper primarily contributes by introducing and elaborating on a conceptual framework that offers novel perspectives on the dual challenges of facilitating both discovery and deployment processes within organizations.

A novel type of heat transfer fluid known as hybrid nanofluids is used to improve the efficiency of heat exchangers. It is observed from literature evidence that hybrid nanofluids outperform single nanofluids in terms of thermal performance. This study aims to address the stagnation point flow induced by Williamson hybrid nanofluids across a vertical plate. This fluid is drenched under the influence of mixed convection in a Darcy–Forchheimer porous medium with heat source/sink and entropy generation.

By applying the proper similarity transformation, the partial differential equations that represent the leading model of the flow problem are reduced to ordinary differential equations. For the boundary value problem of the fourth-order code (bvp4c), a built-in MATLAB finite difference code is used to tackle the flow problem and carry out the dual numerical solutions.

The shear stress decreases, but the rate of heat transfer increases because of their greater influence on the permeability parameter and Weissenberg number for both solutions. The ability of hybrid nanofluids to strengthen heat transfer with the incorporation of a porous medium is demonstrated in this study.

The findings may be highly beneficial in raising the energy efficiency of thermal systems.

The originality of the research lies in the investigation of the Darcy–Forchheimer stagnation point flow of a Williamson hybrid nanofluid across a vertical plate, considering buoyancy forces, which introduces another layer of complexity to the flow problem. This aspect has not been extensively studied before. The results are verified and offer a very favorable balance with the acknowledged papers.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

This study aims to investigate the fabrication of solid ankle foot orthoses (SAFOs) using fused deposition modeling (FDM) printing technology. It emphasizes cost-effective 3D scanning with the Kinect sensor and conducts a comparative analysis of SAFO durability with varying thicknesses and materials, including polylactic acid (PLA) and carbon fiber-reinforced (PLA-C), to address research gaps from prior studies.

In this study, the methodology comprises key components: data capture using a cost-effective Microsoft Kinect® Xbox 360 scanner to obtain precise leg dimensions for SAFOs. SAFOs are designed using CAD tools with varying thicknesses (3, 4, and 5 mm) while maintaining consistent geometry, allowing controlled thickness impact investigation. Fabrication uses PLA and PLA-C materials via FDM 3D printing, providing insights into material suitability. Mechanical analysis uses dual finite element analysis to assess force–displacement curves and fracture behavior, which were validated through experimental testing.

The results indicate that the precision of the scanned leg dimensions, compared to actual anthropometric data, exhibits a deviation of less than 5%, confirming the accuracy of the cost-effective scanning approach. Additionally, the research identifies optimal thicknesses for SAFOs, recommending a 4 and 5 mm thickness for PLA-C-based SAFOs and an only 5 mm thickness for PLA-based SAFOs. This optimization enhances the overall performance and effectiveness of these orthotic solutions.

This study’s innovation lies in its holistic approach, combining low-cost 3D scanning, 3D printing and computational simulations to optimize SAFO materials and thickness. These findings advance the creation of cost-effective and efficient orthotic solutions.

The integration of industry 4.0 has become a priority for many organizations. However, not all organizations are suitable and capable of implementing industry 4.0 because it requires a dynamic and flexible implementation strategy. The implementation of industry 4.0 often involves overcoming several tensions between internal and external stakeholders. This paper aims to explore the paradoxical tensions that arise for health-care organizations when integrating industry 4.0. Moreover, it discusses how a paradox lens can support the conceptualization and proposes techniques for handling tensions during the integration of industry 4.0.

This qualitative and in-depth study draws upon 32 semi-structured interviews. The empirical case concerns how two health-care organizations handle paradoxical tensions during the integration of industry 4.0.

The exploration resulted in six recurring technology tensions: technology invention (modularized design vs. flexible design), technology collaboration (automation vs. human augmentation), technology-driven patient experience (control vs. autonomy), technology uncertainty (short-term experimentation vs. long-term planning), technology invention and diffusion through collaborative efforts among stakeholders (selective vs. intensive collaboration) and technological innovation (market maintenance vs. disruption).

A paradox theory-informed conceptual model is proposed for how to handle tensions during the integration of industry 4.0. To the best of the authors’ knowledge, this is the first paper to introduce paradox theory for quality management, including lean and Six Sigma.

The purpose of this paper aims to investigate the adaptive impedance control and its optimized PSO algorithm for force tracking of a dual-arm cooperative robot. Because the dual-arm robot is directly in contact with external environment, controlling the mutual force between robot and external environment is of great importance. Besides, a high compliance of the robot should be guaranteed.

An impedance control based on Particle Swarm Optimization (PSO) algorithm is designed to track the mutual force and achieve compliance control of the robot end.

The experimental results show that the impedance control coefficients can be automatically tuned converged by PSO algorithm.

The system can reach a steady state within 0.03 s with overshoot convergence, and the force fluctuation range at the steady state decreases to about ±0.08 N even under the force mutation condition.

In most economies, there are rules from the market regulators or government to sell at an equal wholesale price (EWP). But when one upstream channel is facing a negative demand disruption and another positive, EWP can create extra pressure on the disadvantageous supply chain partner, which faces negative disruption. The purpose of this study is to analyse the impact of EWP and the scope of the discriminatory wholesale price (DWP) during disruptions.

For the study, the authors used a dual-channel supply chain consisting of a manufacturer, online retailer (OR) and traditional brick-and-mortar (BM) retailer. Stackelberg game is used to model the interaction between the upstream and downstream channel partners, and the horizontal Nash game to analyse the interaction within downstream channel partners. For modelling asymmetric disruption, the authors took instances from the lock-down and post-lock-down periods of the COVID-19 pandemic, where consumers flow from BM retailer to OR store.

By analysing the disruption period, the authors found that this asymmetric disruption is detrimental to the BM channel, favourable to OR and has no impact on the manufacturer. But with DWP, the authors found that the profit of the BM channel and manufacturer can be increased during disruption. Though the profit of the OR decreased, it was found to be higher than in the pre-disruption period. Under DWP, the consumer surplus increased during disruption, making it favourable for the customers also. Thus, DWP can aid in creating a win-win strategy for all the supply chain partners during asymmetric disruption. Later as an extension to the study, the authors analysed the impact of the consumer transfer factor and found that it plays a crucial role in the optimal decisions of the channel partner during DWP.

Very scant literature analyses the intersection of DWP and disruptions. To the best of the authors’ knowledge, this study, for the first time uses DWP as a tool to help the disadvantageous supply chain partner during asymmetric disruptions. The study findings will assist the government, market regulators and manufacturers in revamping the wholesale pricing policies and strategies to help the disadvantageous supply chain partner during asymmetric disruption.

Stewardship behavior is an important embodiment of the spirit of employee ownership, which is critical to the sustainability of companies, especially under the influence of the COVID-19 epidemic. Most previous studies have focused on how to motivate employees’ stewardship behavior, but little is known about how stewardship behavior affects employees themselves. The purpose of this study is to explore how employee stewardship behavior affects their work-family interface based on the conservation of resources (COR) theory.

In this study, structural equation modeling was conducted using two-wave survey data from 323 employees through three internet companies in Southern China.

Results reveal that engaging in stewardship behavior is positively correlated with both positive emotion and emotional exhaustion. Positive emotion and emotional exhaustion, in turn, mediate the effects of stewardship behavior on work–home interface. Family motivation influences the strength of the relationships between positive emotion or emotional exhaustion and work–family interface, that is, high family motivation strengthens the positive association between positive emotion and work–family enrichment and weakens the positive association between emotional exhaustion and work–family conflict.

This study suggests that managers should give employees more support and care to ease the worries of engaging in stewardship behavior. Also, organizations should recruit employees with high family motivation, which can reduce the negative effects of stewardship behavior on work–-family interface.

Based on an actor’s perspective, this study examines both the positive and negative effects of stewardship behavior on employees themselves, thereby increasing understanding of the dual effect of stewardship behavior. In addition, this study further elucidates the mechanisms that moderate the positive and negative effects of individual family motivation on their engagement in stewardship behavior within the COR theory.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.