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Digital technology (DT) is a massive and robust tool for organizational success. This paper aims to examine the roles of digitalization and digital innovation (DI) in developing the capability of a digital economy.

The authors used a cross-sectional study to collect the data from the managers of Egyptian SME manufacturing firms. This study utilized 322 samples.

From applying the structural equation model (SEM), this study’s findings show that digital capability (DC) and digital orientation (DO) exert a positive effect on the firm’s digital economy capability (DEC). In addition, DC has a positive impact on DI. In contrast, digital technology self-efficacy (DTSE) negatively predicts DEC. This study’s results also confirm DO’s negative effect on DI. The DTSE is a positive enabler of DI that has also positively affected the DEC. The mediating results demonstrate that DI reinforces the positive connection between DO and DEC. On the other hand, DI does not mediate the connection between DO and DEC and between DTSE and DEC.

This study’s outcomes support policymakers and manufacturing organizations in employing DT to improve DEC and, thereby, develop firm performance and success. The study’s findings also encourage organizations to invest in bringing about a digital culture within them. Finally, by developing DT and DI, firms can nurture a conducive culture of creativity and forward-thinking.

This study directly overcomes the need for an integrated framework of all DI, DTSE, DO, DC and DEC. Furthermore, DI’s mediating contribution between DC and DEC, between DO and DEC and between DTSE and DEC adds fresh insights to the existing literature.

Accounting scandals and earnings management problems at large firms such as Global Crossing and Enron have resulted in lots of wealth loss not only to corporate investors but also led tremendous damage to societies. Hence, policymakers and academic researchers have started to explore mechanisms to prevent improprieties in financial reporting and further enhance firm value. Using data from United States (US)-listed companies between 2000 and 2018, this article explores the effect of ex-military executives on earnings quality, the role of financial analysts in their interplay and the firm value implication of earnings quality driven by ex-military executives.

This study employs a firm fixed-effects model to validate the main conjecture and adopts the weighted least squares, Granger causality analysis, instrumental variable approach, propensity score matching, entropy balancing approach and dynamic system Generalized Method of Moments (GMM) estimator to address robustness and endogeneity issues.

Authors reveal that companies run by ex-military senior executives exhibit lower levels of accruals-based and real earnings management than those without. The effect of management military leadership on constraining earnings management is more prominent for companies with low analyst coverage, suggesting that the military experience of executives could be a substitute for external monitoring. Authors also find that these ethical managers alleviate the negative impact of earnings management on firm value and that companies managed by these managers exhibit higher firm performance.

This study highlights the importance of the intrinsic motivation behind the effect of military experience on senior managers' personalities and offers essential stakeholder-related implications regarding the effect of military experience. The military experience of senior managers helps facilitate the attainment of broader corporate governance and economic objectives.

This article adds new insights to the literature on the role of managerial military experience in decision-making processes, financial reporting outcomes and firm performance by employing the upper echelons and imprinting theoretical perspectives.

Electromagnetic shielding (EMS) fabrics composed of cotton, polyester and other high-polymer short-staple fibers are widely utilized in various fields. However, the inevitable pores in these fabrics lead to the leakage of electromagnetic waves, which severely diminishes the fabric’s shielding effectiveness (SE). To address this issue, this paper proposes the implantation of a metamaterial structure known as the “split ring resonator (SRR)” into the fabric.

Firstly, the types and principles of SRRs are analyzed. Through electromagnetic simulation and emulation, the effectiveness of SRRs in dissipating electromagnetic waves is confirmed. By selecting different embroidery methods, various shapes of SRRs are implanted into the fabric. Subsequently, through testing and analysis of sample fabrics embroidered with SRRs, it is concluded that implanting appropriate SRRs into pure cotton fabrics and cotton/polyester/stainless steel-blended EMS fabrics can effectively impart or enhance the SE of these fabrics.

For pure cotton fabric without inherent SE, the peak SE value can reach over 30 dB within the 6.57 GHz–7 GHz frequency band, and the minimum SE is greater than 10 dB in the 7 GHz–9.99 GHz frequency band. For the cotton/polyester/stainless steel-blended EMS fabric, the improvement in SE across all frequency bands exceeds 10 dB, averaging around 15.6 dB. The circular type SRR demonstrates the most significant improvement in fabric SE. When the substrate is composed of pure cotton or a cotton/polyester/stainless steel blend, the circular SRRs provide an average enhancement of more than 4 dB and 6 dB, respectively, than other shapes. The fewer the holes created by the implantation method, the higher the SE of the fabric after SRR implantation, with the invisible embroidery technique being the most effective. It improves the fabric’s SE by an average of about 2 dB more than flat embroidery and can be up to an average of around 6 dB higher than the backstitch embroidery technique. For every 0.2 cm increase in the size of the SRRs, the average SE increases by about 4 dB, and for every 0.5 cm increase in the spacing between them, the fabric’s SE decreases by an average of more than 2.7 dB.

This paper offers a novel approach to counteract the issue of pores reducing the SE of EMS fabrics and provides a new method for developing lightweight, thin, low-cost and high-performance EMS fabric composite materials.

Depression has become one of the most serious and prevalent mental health problems worldwide. The rise and popularity of social networks such as microblogs provides a wealth of psychological data for early depression detection. Language use patterns reflect emotional states and psychological traits. Differences in language use between depressed and general users may help predict and diagnose early depression. Existing work focuses on depression detection using users' social textual emotion expressions, with less psychology-related knowledge.

In this paper, we propose an RNN-capsule-based depression detection method for microblog users that improves depression detection accuracy in social texts by combining textual emotional information with knowledge related to depression pathology. Specifically, we design a multi-classification RNN capsule that enhances emotion expression features in utterances and improves classification performance of depression-related emotional features. Based on user emotion annotations over time, we use integrated learning to detect depression in a user’s social text by combining the analysis results with components such as emotion change vector, emotion causality analysis, depression lexicon and the presence of surprising emotions.

In our experiments, we test the accuracy of RNN capsules for emotion classification tasks and then validate the effectiveness of different depression detection components. Finally, we achieved 83% depression detection accuracy on real datasets.

The paper overcomes the limitations of social text-based depression detection by incorporating more psychological background knowledge to enhance the early detection success rate of depression.

According to reputation theory, enterprises that adopt a proactive approach to corporate social responsibility (CSR) are known to actively invest in corporate innovation. However, this theory does not fully explain the mechanisms through which CSR influences corporate innovation, nor does it address how to effectively amplify CSR’s positive impact on innovation. To overcome these limitations, this research aims to incorporate the theories of innovation investment and dynamic capabilities. Innovation investment theory elucidates how CSR can attract additional financing, which can be directed toward innovation activities. Meanwhile, dynamic capabilities theory highlights how digital transformation in enterprises can enhance the positive effects of CSR on innovation, providing insights from both theoretical and empirical perspectives.

To demonstrate the mediating role of debt financing costs and the moderating role of enterprise digital transformation in the mechanism of CSR on corporate innovation, this research conducts fixes effects models by collecting 27,912 data points from 3,775A-share China-listed enterprises, ranging in period from 2010 to 2020. Empirical research once again proves that the theories of innovation investment and dynamic capabilities effectively compensates for the shortcomings of reputation theory. These three theories effectively explain that what is the effect of CSR on enterprise innovation? How does CSR influence corporate innovation? And through what mechanisms can CSR better enhance corporate innovation?

According to innovation investment theory, the cost of debt financing mediates the positive relationship between CSR and corporate innovation. This occurs because enterprises with robust CSR practices are more likely to secure external funding, thereby reducing their costs associated with external debt financing. Lower debt financing costs provide a stable source of funds for corporate innovation. Additionally, dynamic capability theory suggests that enterprise digital transformation moderates the positive relationship between CSR and corporate innovation. Building on these insights, it is recommended that enterprises, especially state-owned ones, should prioritize technological innovation to enhance their competitiveness.

This research aims to address and narrow the knowledge gap regarding the relation between CSR and corporate innovation through theoretical and empirical analyses. With respect to the influence mechanism, this research solely based on innovation investment theory and dynamic capabilities theory, focuses on the influence mechanism of CSR on corporate innovation, with the debt financing costs as the mediating variable and digital transformation as the moderating variable. However, the influence mechanism turns out to be complicated and there is room for further exploring numerous mechanisms. For example, future research can focus on identifying additional channels through which CSR exerts an influence on corporate innovation based on TOE theoretical framework.

This research presents several strategies to enhance corporate innovation based on its conclusions: First, enterprises should promptly publish social responsibility reports to build a positive industry reputation. Moreover, by actively participating in CSR activities, they can strengthen their networks and enhance their industry standing. Second, the significant mediating role of debt financing costs should not be ignored. Enterprises are encouraged to seek diverse financing channels to reduce financial pressures, address financing challenges and facilitate the coordinated development of CSR and innovation. Third, enterprise digital transformation significantly affects the impact of CSR on innovation. Therefore, enterprises should advance digital transformation initiatives that incorporate technological innovation, organizational improvements and integration with supply chain partners. Finally, it has been noted that state-owned enterprises are often less responsive to technological innovation than their non-state counterparts. SOEs could redefine the scope and priorities of their social responsibilities to prevent excessive resource consumption that could hinder innovation. For instance, integrating some of their social responsibilities with innovation projects could promote both social and technological innovation objectives. Additionally, the government could ensure fair resource distribution among different types of enterprises and provide an equitable financing platform to mitigate financial challenges for both state-owned and non-state-owned enterprises.

Reputation theory does not fully elucidate the mechanisms by which CSR influences corporate innovation or how to effectively enhance CSR’s positive impact on innovation. This research integrates the theories of innovation investment and dynamic capabilities to address these gaps. According to innovation investment theory, debt financing costs mediate the positive relationship between CSR and corporate innovation. Meanwhile, dynamic capabilities theory posits that enterprise digital transformation moderates this positive relationship, further strengthening the impact of CSR on innovation.

Stainless-steel electromagnetic shielding (EMS) fabrics are widely applied as protective materials against electromagnetic interference (EMI). However, these fabrics primarily shield electromagnetic waves through reflection, which can lead to the formation of resonance effects that severely compromise their protective capabilities and potentially cause secondary electromagnetic pollution in the external environment.

In this paper, carbon nanotube fibers are added via spacing method to replace some stainless-steel fibers to impart absorbing properties to stainless-steel EMS fabric. The shielding effectiveness (SE) of the EMS fabrics across various polarization directions is analyzed. Additionally, a spacing arrangement for the carbon nanotube fibers is designed. The EMS fabric with carbon nanotube fibers is manufactured using a semi-automatic sample loom, and its SE is tested using a small window method test box in both vertical and horizontal polarization directions.

According to the experimental data and electromagnetic theory analysis, it is determined that when the spacing between the carbon nanotube fibers is less than a specific distance, the SE of the stainless-steel EMS fabric significantly improves. The fabric exhibits stable absorbing properties within the tested frequency range, effectively addressing the issue of secondary damage that arises from relying solely on reflective shielding. Conversely, as the spacing between the carbon nanotube fibers exceeds this distance, the SE diminishes. Notably, the SE in the vertical polarization direction is substantially higher than that in the horizontal polarization direction at the same frequency.

This study provides a new path for the development of high-performance EMS fabrics with good wave-absorption characteristics and SE.

The 6D pose estimation is a crucial branch of robot vision. However, the authors find that due to the failure to make full use of the complementarity of the appearance and geometry information of the object, the failure to deeply explore the contributions of the features from different regions to the pose estimation, and the failure to take advantage of the invariance of the geometric structure of keypoints, the performances of the most existing methods are not satisfactory. This paper aims to design a high-precision 6D pose estimation method based on above insights.

First, a multi-scale cross-attention-based feature fusion module (MCFF) is designed to aggregate the appearance and geometry information by exploring the correlations between appearance features and geometry features in the various regions. Second, the authors build a multi-query regional-attention-based feature differentiation module (MRFD) to learn the contribution of each region to each keypoint. Finally, a geometric enhancement mechanism (GEM) is designed to use structure information to predict keypoints and optimize both pose and keypoints in the inference phase.

Experiments on several benchmarks and real robot show that the proposed method performs better than existing methods. Ablation studies illustrate the effectiveness of each module of the authors’ method.

A high-precision 6D pose estimation method is proposed by studying the relationship between the appearance and geometry from different object parts and the geometric invariance of the keypoints, which is of great significance for various robot applications.

This study aims to provide data references for deposit cleaning, fuel formulation and lubricant formulation.

The engine disassembly procedure was carried out based on the IO540 operation manual part number 60297-10-1-7 document. Except for the normal disassembly and assembly of the engine and the measurement of parts, the main test contents included break-in run operation, cylinder pressure test, oil consumption run, pretest calibration run, post-test calibration test and the most critical endurance test. The Lycoming IO-540-V4V5 engine and the customized Hartzell CK319 propeller were selected for the test run.

The deposits were mainly composed of C, O, B, Al, Br and Pb, which were mainly sourced from fuel, lubricating oil and body materials. XPS analysis showed that the presence of O determined the richness of the deposit components, giving the deposit structure with organic and inorganic components.

This work provides certain data support and reference for subsequent aircraft maintenance, fuel formula and lubricating oil formula. The long-term stability and safety of the aircraft run can be ensured through continuous research, improvement and optimizing the operating of the engine.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2024-0300/

The affordable loss (AL) heuristic, as one crucial sub-dimension of effectuation, delineates the maximum level of investment entrepreneurs are ready to lose in a worst-case scenario. Conflicting conceptualizations remain regarding whether entrepreneurs’ psychological traits matter for AL. Based on the narcissistic admiration and narcissistic rivalry perspective, this study investigates the relationship between chief executive officer (CEO) narcissism and AL behaviors.

Using data collected from the CEOs and paired vice presidents at 122 small and medium enterprises (SMEs) in mainland China, the authors intend to further explore the association between psychological traits, especially CEO narcissism and AL behaviors under environment and resource constraints (e.g. perceived uncertainty and slack resources).

The findings show that CEO admiration-based narcissism is positively related to AL behaviors in the firm. Furthermore, when firms hold more slack resources, narcissistic admiration has a stronger positive association with AL; while when the environment becomes more uncertain, narcissistic admiration has a weaker positive association with AL. In contrast, CEO rivalry-based narcissism is negatively related to AL behaviors in the firm. When the environment becomes more uncertain, narcissistic rivalry has a stronger negative association with AL.

This article contributes to trait-based effectuation research and suggests that individual psychological traits affect AL behaviors at the firm level, though the patterns of the relationship vary with both the type of narcissism and contexts.

This study aimed to explore the spatial accessibility dynamics of urban parks and their driving forces from 1901 to 2010 in terms of the dynamic relationships between spatial morphology and road networks, taking Nanjing City as an example.

This study mapped and examined the spatiotemporal distribution of urban parks and road networks in four time points at Nanjing: the 1910s, 1930s, 1960s and 2010s, using the analysis methodology of spatial design network analysis, kernel density estimation and buffer analysis. Two approaches of spatial overlaying and data analysis were adopted to investigate the accessibility dynamics. The spatial overlaying compared the parks' layout and the road networks' core, subcore and noncore accessible areas; the data analysis clarified the average data on the city-wide and local scales of the road networks within the park buffer zone.

The analysis of the changing relationships between urban parks and the spatial morphology of road networks showed that the accessibility of urban parks has generally improved. This was influenced by six main factors: planning implementation, political policies, natural resources, historical heritage and cultural and economic levels.

The results provide a reference for achieving spatial equity, improving urban park accessibility and supporting sustainable urban park planning.

An increasing number of studies have explored the spatial accessibility of urban parks through the relationships between their spatial distribution and road networks. However, few studies have investigated the dynamic changes in accessibility over time. Discussing parks' accessibility over relatively long-time scales has practical, innovative and theoretical values; because it can reveal correlational laws and internal influences not apparent in short term and provide reference and implications for parks' spatial equity.