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The purpose of this study is to improve the thermal management of lithium-ion batteries. The phase change material (PCM) cooling does not require additional equipment to consume energy. To improve the heat dissipation capacity of batteries, fins are added in the PCM to enhance the heat transfer process.

Computational fluid dynamics method is used to study the influence of number of vertical fins and ring fins (i.e. 2, 4, 6 and 8 vertical fins, and 2, 3, 4 and 5 ring fins) and the combination of them on the cooling performance.

The battery maximum temperature can be decreased by the PCM with vertical or ring fins, and it can be further decreased by the combination of them. The PCM with eight vertical fins and five ring fins reduces the battery maximum temperature by 5.21 K. In addition, the temperature and liquid-phase distributions of the battery and PCM are affected by the design of the cooling system.

This work can provide guidelines for the development of new and efficient PCM cooling systems for lithium-ion batteries.

The combination of PCM and fins can be used to reduce the battery maximum temperature and temperature difference.

Hexahedral meshing is one of the most important steps in performing an accurate simulation using the finite element analysis (FEA). However, the current hexahedral meshing method in the industry is a nonautomatic and inefficient method, i.e. manually decomposing the model into suitable blocks and obtaining the hexahedral mesh from these blocks by mapping or sweeping algorithms. The purpose of this paper is to propose an almost automatic decomposition algorithm based on the 3D frame field and model features to replace the traditional time-consuming and laborious manual decomposition method.

The proposed algorithm is based on the 3D frame field and features, where features are used to construct feature-cutting surfaces and the 3D frame field is used to construct singular-cutting surfaces. The feature-cutting surfaces constructed from concave features first reduce the complexity of the model and decompose it into some coarse blocks. Then, an improved 3D frame field algorithm is performed on these coarse blocks to extract the singular structure and construct singular-cutting surfaces to further decompose the coarse blocks. In most modeling examples, the proposed algorithm uses both types of cutting surfaces to decompose models fully automatically. In a few examples with special requirements for hexahedral meshes, the algorithm requires manual input of some user-defined cutting surfaces and constructs different singular-cutting surfaces to ensure the effectiveness of the decomposition.

Benefiting from the feature decomposition and the 3D frame field algorithm, the output blocks of the proposed algorithm have no inner singular structure and are suitable for the mapping or sweeping algorithm. The introduction of internal constraints makes 3D frame field generation more robust in this paper, and it can automatically correct some invalid 3–5 singular structures. In a few examples with special requirements, the proposed algorithm successfully generates valid blocks even though the singular structure of the model is modified by user-defined cutting surfaces.

The proposed algorithm takes the advantage of feature decomposition and the 3D frame field to generate suitable blocks for a mapping or sweeping algorithm, which saves a lot of simulation time and requires less experience. The user-defined cutting surfaces enable the creation of special hexahedral meshes, which was difficult with previous algorithms. An improved 3D frame field generation method is proposed to correct some invalid singular structures and improve the robustness of the previous methods.

This paper aims to understand how cultural and creative industries (CCIs) contribute to regional innovation.

This paper explores the process of CCIs contributing to regional innovation and assesses the accumulated outcome of this process.

The authors conclude that CCIs contribute to a city’s innovation involving five dimensions (time, space, tangible, intangible and division) and four phases (people, tool, collaboration and brokerage) and the contributions are accumulated into positive innovation outcome; however, a highly developed economy is relatively unsupportive of CCIs contributing to regional innovation.

The main contributions are that the authors configured the detailed process of CCIs contributing to regional innovation and the authors quantitatively measured the impact of CCIs on regional innovation, using the Porter diamond model and Shannon entropy to construct the CCI index.

Based on the dynamic capability theory, the purpose of this study is to examine the mediating role of the adaptive capability of small- and medium-sized enterprises (SMEs) on the relationship between business ties and firm performance. This study also investigates the moderating role of technological turbulence in those relationships.

Data were collected from 1,265 SME managers in Turkey. Partial least squares analysis, a variance-based structural equation modelling, was applied to examine a mediated moderation model.

The results support the proposed framework illustrating that business ties are positively related to adaptive capability and firm performance. Moreover, adaptive capability mediates the relationship between business ties and firm performance. The results also indicate that the indirect effect of business ties on firm performance through adaptive capability was moderated by technological turbulence.

SMEs in emerging economies need to enhance their business ties and invest in their adaptive capabilities to increase their performances. This relation becomes more strategic under technologically turbulent environments.

By introducing empirical data from the Turkish emerging context, this paper contributes to our understanding of how SMEs’ relational networks contribute to firm performance. From the dynamic capability perspective, it shows how SMEs use their adaptive capabilities to environmental challenges. It also fills an important gap by showing that environmental uncertainties (specifically technological turbulence) moderate the adaptive capability’s mediating impact on the relationship between business ties and firm performance. The results also provide potential future directions for dynamic capabilities research in emerging contexts.

Drawing on institutional theory, this study investigates the role of individual cultural values on the adoption of socially sustainable supply chain management (socially SSCM) for Chinese suppliers facing the normative institutional pressures of guanxi (interpersonal relationships).

Using empirical data collected in three waves from 205 Chinese manufacturers supplying international markets, the proposed theoretical model is tested through partial least squares structural equation modeling (PLS-SEM).

The results indicate that guanxi has a positive impact on socially SSCM, and this positive effect is strengthened when the individual cultural values of the supplier's representative embody high collectivism and low uncertainty avoidance.

This study highlights the leading role of guanxi in improving socially SSCM practices due to its normative institutional force. In addition, the findings suggest that future studies should consider individual differences in supply chain partners, which may lead to distinct reactions when facing normative institutional pressures.

This study suggests international buyers should adopt guanxi management with their Chinese suppliers to encourage them to adopt socially SSCM. In addition, managers should note that the guanxi strategy is more effective when the supplier's representative collectivism is high and uncertainty avoidance is low.

This study contributes to socially SSCM research in emerging economies by unveiling the role of guanxi as a key driver of socially SSCM in the Chinese market and providing empirical evidence of the moderating effect of individual culture on the guanxi normative institutionalization process.

Research on the relationship between customer bargaining power and supplier performance in supplier–customer relationships has flourished in recent decades. This study aims to empirically investigate whether product market overlap (PMO) in a supply chain moderates the effect of customer bargaining power on supplier profitability.

This study uses large-scale secondary data from multiple databases. Econometric panel data techniques are used to test the hypotheses.

The results show that PMO in a supplier–customer relationship and PMO in supplier–supplier relationships both exacerbate the negative effect of the bargaining power of customers on supplier profitability.

This study contributes to the field of supply chain management. This study brings new insights into the ongoing debate surrounding the relationship between customer bargaining power and supplier profitability. The study also contributes to the literature on supply chain networks by showing the impact of indirect supply chain relationships.

This paper contributes to studies on the relationship between dynamic capabilities (DCs) and performance by showing how domain-specific DCs – international dynamic marketing capabilities (IDMCs) – affect the international performance of exporting firms in the context of extreme environmental dynamism – during the COVID-19 pandemic.

The authors focus on a sample of 277 exporting manufacturers from the post-transition economy of Poland. The authors use hierarchical multiple regression analysis to test this study's hypotheses.

This study's findings show that deployment of IDMCs by export manufacturers in the context of environmental jolts contributes to better performance, and this relationship is mediated by adaptation to foreign markets and product development capability. Additionally, this study's results reveal that the significant and positive indirect effect of IDMCs on international performance (through mediators) is, however, weakened under conditions of extreme environmental dynamism.

The limitations pertain to the cross-sectional nature of this study and the research sample, characterised by the dominance of export manufacturers of final products, the dominance of manufacturers operating in the business-to-business sector, or in the business-to-business and business-to-customer sectors simultaneously.

The study provides suggestions to managers on how to build resilience in international markets during turbulent times. These activities involve investments in IDMCs that support activities centred around product development and adaptation to foreign markets.

The novel construct of IDMCs is introduced and operationalized. The study empirically tests the direct and indirect relationship between IDMCs and performance contingent upon extreme environmental dynamism. The results demonstrate the boundary conditions for the effectiveness of these domain-specific DCs in such a research setting.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

This study aims to investigate the rising trend of virtual influencers – digitally created characters with human-like attributes. It aims to evaluate and compare their effectiveness with human influencers in terms of brand attitudes and purchase intentions. It uncovers the mechanisms underlying the differences in effectiveness observed between virtual influencers and their human counterparts.

The research uses a 2 (influencer type: human vs virtual) × 3 (product type: functional vs symbolic vs experiential) between-subjects design. Through a pilot study (n = 334) and a main study (n = 352), the research examines the interactive effects of influencer and product type on brand attitude and purchase intentions. Hypotheses were developed and tested using moderating mediation models centered on authenticity and product–endorser fit.

Virtual influencers are perceived as less authentic than human influencers across all product types, negatively influencing brand attitude and purchase intention. However, the extent to which influencer type affects brand attitudes and purchase intentions, mediated by product–endorser fit, varies based on the product type.

This research emphasizes two key mechanisms – authenticity and product–endorser fit – influencing the effectiveness of virtual influencers. It suggests that aligning virtual influencers with suitable product types can offset their perceived authenticity deficit, significantly affecting their endorsement effectiveness.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.