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Flow induced by rotating disks is of great practical importance in several engineering applications such as rotating heat exchangers, turbine disks, pumps and many more. The present research has been freshly displayed regarding the implementation of an engine oil-based Casson tri-hybrid nanofluid across a rotating disk in mass and heat transferal developments. The purpose of this study is to contemplate the attributes of the flowing tri-hybrid nanofluid by incorporating porosity effects and magnetization and velocity slip effects, viscous dissipation, radiating flux, temperature slip, chemical reaction and activation energy.

The articulated fluid flow is described by a set of partial differential equations which are converted into one set of higher-order ordinary differential equations (ODEs) by using convenient conversions. The numerical solution of this transformed set of ODEs has been spearheaded by using the effectual bvp4c scheme.

The acquired results show that the heat transmission rate for the Casson tri-hybrid nanofluid is intensified by, respectively, 9.54% and 11.93% when compared to the Casson hybrid nanofluid and Casson nanofluid. Also, the mass transmission rate for the Casson tri-hybrid nanofluid is augmented by 1.09% and 2.14%, respectively, when compared to the Casson hybrid nanofluid and Casson nanofluid.

The current investigation presents an educative response on how the flow profiles vary with changes in the inevitable flow parameters. As per authors’ knowledge, no such scrutinization has been carried out previously; therefore, our results are novel and unique.

The objective of this study was to develop wearable suit platforms with various anchoring structure designs with the intention of improving wearability and enhancing user satisfaction.

This study selected fabrics and materials for the suit platform through material performance tests. Two anchoring structure designs, 11-type and X-type are compared with regular clothing under control conditions. To evaluate the comfort level of the wearable suit platform, a satisfaction survey and electroencephalogram (EEG) measurements are conducted to triangulate the findings.

The 11-type exhibited higher values in comfort indicators such as α, θ, α/High-β and lower values in concentration or stress indicators such as β, ϒ, sensorimotor rhythm (SMR)+Mid-β/θ, and a spectral edge frequency of 95% compared to the X-type while walking. The 11-type offers greater comfort and satisfaction compared to the X-type when lifting based on the EEG measurements and the participants survey.

It is recommended to implement the 11-type when designing wearable suit platforms. These findings offer essential data on wearability, which can guide the development of soft wearable robots.

This study aims to examine the effects of cross-flow and multiple jet impingement on conductive panel cooling performance when subjected to uniform magnetic field effects. The cooling system has double rotating cylinders.

Cross-flow ratios (CFR) ranging from 0.1 to 1, magnetic field strength (Ha) ranging from 0 to 50 and cylinder rotation speed (Rew) ranging from −5,000 to 5,000 are the relevant parameters that are included in the numerical analysis. Finite element method is used as solution technique. Radial basis networks are used for the prediction of average Nusselt number (Nu), average surface temperature of the panel and temperature uniformity effects when varying the impacts of cross-flow, magnetic field and rotations of the double cylinder in the cooling channel.

The effect of CFR on cooling efficiency and temperature uniformity is favorable. By raising the CFR to the highest value under the magnetic field, the average Nu can rise by up to 18.6%, while the temperature drop and temperature difference are obtained as 1.87°C and 3.72°C. Without cylinders, magnetic field improves the cooling performance, while average Nu increases to 4.5% and 8.8% at CR = 0.1 and CR = 1, respectively. When the magnetic field is the strongest with cylinders in channel at CFR = 1, temperature difference (ΔT) is obtained as 2.5 °C. The rotational impacts on thermal performance are more significant when the cross-flow effects are weak (CFR = 0.1) compared to when they are substantial (CFR = 1). Cases without a cylinder have the worst performance for both weak and severe cross-flow effects, whereas using two rotating cylinders increases cooling performance and temperature uniformity for the conductive panel. The average surface temperature lowers by 1.2°C at CFR = 0.1 and 0.5°C at CFR = 1 when the worst and best situations are compared.

The outcomes are relevant in the design and optimization-based studies for electric cooling, photo-voltaic cooling and battery thermal management.

The lightweight design of aircraft seats can significantly improve fuel efficiency and reduce greenhouse gas emissions. Metal additive manufacturing (MAM) can produce lightweight topology-optimized designs with improved performance, but limited build volume restricts the printing of large components. The purpose of this paper is to design a lightweight aircraft seat leg structure using topology optimization (TO) and MAM with build volume restrictions, while satisfying structural airworthiness certification requirements.

TO was used to determine a lightweight conceptual design for the seat leg structure. The conceptual design was decomposed to meet the machine build volume, a detailed CAD assembly was designed and print orientation was selected for each component. Static and dynamic verification was performed, the design was updated to meet the structural requirements and a prototype was manufactured.

The final topology-optimized seat leg structure was decomposed into three parts, yielding a 57% reduction in the number of parts compared to a reference design. In addition, the design achieved an 8.5% mass reduction while satisfying structural requirements for airworthiness certification.

To the best of the authors’ knowledge, this study is the first paper to design an aircraft seat leg structure manufactured with MAM using a rigorous TO approach. The resultant design reduces mass and part count compared to a reference design and is verified with respect to real-world aircraft certification requirements.

Sailing toward sustainability is becoming the strategic focus of shipping firms. Drawing on organizational information processing theory (OIPT) and the theory of planned behavior (TPB), we investigated the impact of digital transformation (DT) on shipping firms’ sustainable management performance and the boundary conditions guiding this relationship.

The authors examined the hypotheses by employing hierarchical linear modeling on two-wave time-lagged data from 189 shipping firm employees in China.

The results suggest that a shipping firm’s DT is positively associated with its sustainable management performance and that the relationship is strengthened by having better cross-functional and customer coordination mechanisms. Furthermore, our three-way interaction analyses show that while injunctive norms in a shipping firm’s networks can strengthen the contingency roles of both cross-functional and customer coordination mechanisms, descriptive norms alone significantly influence customer coordination.

Drawing on organizational information processing and planned behavior theories, the present research provides new insights into leveraging DT for sailing toward sustainable success. Moreover, this study extends the current understandings of the boundary conditions of the relationship between DT and sustainable management performance by showing the two-way and three-way interaction effects of coordination mechanisms and subjective norms. The findings of the present research can be utilized as effective strategies for promoting sustainable management performance.

This study aims to explore the role of frontline service employees’ (FSEs) awareness that their job can be substituted by smart technology, artificial intelligence, robotics and algorithms (STARA) in their job autonomy and proactive service performance and when these relationships can be buffered. Drawing on the cognitive appraisal theory of stress, the study examined the mediating relationship between FSEs’ STARA awareness, job autonomy and proactive service performance and the moderating effects of self-efficacy and resilience on this relationship.

The authors administered two-wave online surveys to 301 South Korean FSEs working in various service sectors (e.g. retailing, food/beverage, hospitality/tourism and banking). The Time 1 survey measured respondents’ STARA awareness, self-efficacy, resilience and job autonomy, and the Time 2 survey assessed their proactive service performance.

FSEs’ STARA awareness negatively affected their subsequent proactive service performance through decreased job autonomy. The negative association between STARA awareness and job autonomy was weaker when FSEs’ self-efficacy was high than when it was low. While the authors observed no significant moderation of resilience, the author found a marginally significant three-way interaction between STARA awareness, self-efficacy and resilience. Specifically, STARA awareness was negatively related to job autonomy only when both self-efficacy and resilience were low. When either self-efficacy or resilience was high, the association between STARA awareness and job autonomy became nonsignificant, suggesting the buffering roles of the two personal resources.

Given that the measurement of variables relied on self-reported data, rater biases might have affected the findings of the study. Moreover, the simultaneous measurement of STARA awareness, self-efficacy, resilience and job autonomy could preclude causal inferences between these variables. The authors encourage future studies to use a more rigorous methodology to reduce rater biases and establish stronger causality between the variables.

Service firms can decrease FSEs’ STARA awareness through training in the knowledge and skills necessary to work with these technologies. To promote FSEs’ proactive service performance in this context, service firms need to involve them in decisions related to STARA adoption and allow them to craft their jobs. Service managers should provide FSEs with social support and exercise empowering and supportive leadership to help them view STARA as a challenge rather than a threat.

Distinct from prior research on STARA awareness and employee outcomes, the study identified proactive service performance as a key outcome in the STARA context. By presenting self-efficacy and resilience as crucial personal resources that buffer FSEs from the deleterious impact of STARA awareness, the study provides practitioners with insights that can help FSEs maintain their job autonomy and proactive service performance in times of digitalization and automation.

In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.

The determinants that contribute to reducing stock price crash risk have garnered attention from scholars and practitioners. However, our understanding of the relationship between board diversity and stock crash risk, as well as the contextual factors that influence this relationship, remains limited. To address this gap, this study aims to investigate how different attributes of board diversity affect stock price crash risk, particularly under conditions of higher performance hazard and ownership concentration.

Using a two-stage least squares fixed-effects estimator, the authors analyze a panel data set of 1,792 firm-year observations across 282 firms listed on the KOSPI200 from 2010 to 2019.

Relation-oriented diversity reduces future stock price crash risk, particularly when firms experience performance shortfalls and have concentrated ownership structures, but task-oriented diversity has no significant effects. The results imply that only relation-oriented diversity strengthens governance mechanisms by curtailing managerial bad news withholding behaviors, and the role of relation-oriented diversity in reducing stock crash risk becomes more crucial when firms have higher performance hazard and concentrated ownership.

This study makes crucial contributions as follows: the authors contribute to the stock crash risk literature by shifting the focus from how to when board diversity matters in assessing stock crash risk; the authors extend the board diversity research and enhance scholarly understanding of the effects of board diversity on corporate governance by highlighting that not all aspects of board diversity improve firm governance mechanisms; and the authors widen the lens from a single attribute to multiple attributes of diversity to reveal the effects of diversity on boards in assessing future crash risk.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

The purpose of this study is to analyze the nonlinear effects of corporate philanthropy on the responses of both internal and external stakeholders as well as its impact on corporate financial performance.

Based on the stakeholder theory, the authors developed a conceptual model to examine the nonlinear effects of corporate philanthropy on company performance. For the empirical analysis, data from 397 company-years was analyzed using a using a Heckman two-stage model. The robustness of the findings was also confirmed through panel regression analysis.

The study revealed a linear relationship between corporate reputation and corporate philanthropy, whereas job satisfaction exhibited a nonlinear relationship with corporate philanthropy.

This research bridges the gap in extant literature by scrutinizing the nonlinear associations between corporate philanthropy and financial performance. Additionally, it addresses an emerging scholarly demand to uncover the “dark side” of corporate philanthropy through an investigation into its adverse impacts on employee satisfaction. Moreover, the study augments existing understandings of stakeholder theory and corporate philanthropy, positing that the influence of corporate philanthropy, as conceptualized through stakeholder theory, hinges on perceived fairness in multilateral relationships.