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The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.

Drawing upon resource dependence theory, this study aims to examine how a firm’s information technology (IT) capabilities (i.e. IT integration and IT reconfiguration) influence its responses to disruptions – bridging with a current supplier and buffering with an alternative supplier. We further examine how such relationships are moderated by the firm–supplier relative dependence (i.e. firm dependence advantage and supplier dependence advantage).

Based on data from 141 match-paired surveys of firms in China, we test our model.

Our study finds that IT integration positively influences bridging and IT reconfiguration positively influences buffering. Furthermore, our findings indicate that the positive impact of IT integration on bridging is negatively influenced by the firm’s dependence (FD) advantage but positively moderated by the supplier’s dependence advantage. By contrast, the positive impact of IT reconfiguration on buffering is negatively influenced by the FD advantage.

Our study provides a more nuanced insight into the effects of IT capabilities on disruption responses and a better understanding of the buyer–supplier dependence boundary conditions under which these effects vary.

Scholars and practitioners have long debated carbon dioxide (CO2) emissions reduction via setting double-carbon goals of peak emissions and carbon neutrality in China. Our study, based on dynamic capability and resource dependence theory (RDT), explores whether digital transformation (DT) affects carbon emissions reduction (CER), and the role of operations and supply chain management (OSCM) factors in this relationship.

The samples are constructed with 454 A-shared listed manufacturing firms with complete financial data from 2010–2021. Regression models with fixed effects are applied to estimate the potential parameters.

We find that DT promotes CER. The performance output of CER is strengthened when supplier concentration and customer concentration are high. In contrast, the performance output of CER is weaker when environmental uncertainty is high.

The findings of our study enrich the literature on CER in Chinese manufacturing firms and highlight DT and OSCM factors as important drivers influencing CER practices.

The purpose of this study is to evaluate service robots as an alternative service provider that can reduce customers’ social discomfort in hospitality service encounters. Specifically, the authors discuss when and in what scenarios service robots can alleviate such social discomfort and explain this effect from the perspective of dehumanization.

Following a social constructivist paradigm, the authors adopt a qualitative research design, gathering data through 21 semistructured interviews to explore why the presence of service employees causes customers’ social discomfort in hospitality service encounters and how service robots alleviate such discomfort.

This study’s results suggest that both the active and passive engagement of service employees are sources of customers’ social discomfort in hospitality service encounters; thus, adopting service robots can help reduce such discomfort in some scenarios. Customers’ differentiating behaviors, a downstream effect of social discomfort, are also addressed.

Service robots can reduce customers’ social discomfort in certain scenarios and influence their consumption behaviors. This finding offers actionable insights regarding the adoption of service robots in hospitality service encounters.

This research enhances the understanding of social discomfort in hospitality service encounters and expands the research on service robots. To the best of the authors’ knowledge, it is the first attempt to reveal the bright side of robots in service encounters from a dehumanization perspective.

This study assesses how relational factors and buyer-supplier relationship commitment (BSRC) influence supply chain integration (SCI) and firm performance in Bangladesh's apparel manufacturing sector. Firm performance includes operational performance and innovation performance.

Grounded in the social exchange theory, a survey data-based structural equation modeling (SEM) approach is applied. Based on two experts and four executives' opinions and an in-depth literature review, 28 measurement items were identified in the close-ended questionnaire design. Further, 144 valid questionnaires from the manufacturer-supplier dyads in Bangladesh were collected and used for SEM analysis.

Our study reveals that relational factors positively influence BSRC. BSRC directly impacts SCI, operational, and innovation performance, whereas SCI is significantly related to operational and innovation performance. Besides, SCI mediates the two relationships: BSRC and operational performance; and BSRC and innovation performance.

Our results contribute to the literature and offer a new way to understand relationships that connect relational factors of BSRC, BSRC, and outcomes not only by examining the focal firm but also by examining its dyadic supplier partner separately. Separate assessment in the dyad displays some similar and dissimilar results. Moreover, we suggest practical implications for managers to enhance firm performance by focusing on the significance of linking relational factors, BSRC, and SCI.

Based on resource dependence theory (RDT) and transaction cost theory (TCT), we aim to investigate the relationship between supply chain concentration and firm performance. Based on the resource-based perspective, we further investigate the moderating effect of marketing and operational capabilities on the relationship between supply chain concentration and firm performance.

Based on data from 2,082 firms with 8,371 observations from 2008 to 2020 in China, we use stochastic frontier analysis to calculate marketing capability and operational capability and use multinational regressions to test our research model.

We find a U-shaped relationship between supplier concentration and firm performance; there is also a U-shaped relationship between customer concentration and firm performance. In addition, the relationship between supplier concentration and firm financial performance is strengthened by the firm’s marketing capability, and the relationship between customer concentration and firm financial performance is weakened by the firm’s operational capability.

Drawing from RDT and TCT, this study extends the research on the impact of supply chain concentration on firm performance. The study finds that supply chain concentration and firm performance have a nonlinear relationship, and it is further moderated by marketing capability and operational capability, providing insights for managers.

This paper aims to obtain a calculation method by hand without iteration.

This paper adopts strains as known quantities to solve the internal forces and deformations of the section, simplifies the deflection curve of the column and obtains nomograms that can calculate the bearing capacity and reinforcement of circular reinforced concrete (RC) columns by hand.

Nomograms include five variables: mechanical reinforcement ratio, relative normal force, dimensionless bending moment, slenderness ratio and ultimate dimensionless curvature. Nomograms corresponding to all classes of concrete have been drawn, and their dimensionless form makes them widely applicable. The calculation results of nomograms are compared and analysed with numerical calculation results, and the difference is within 5%, meeting the engineering requirements.

Calculating the bearing capacity of compression bending components requires considering second-order effects. Therefore, the calculation of the bearing capacity of circular RC columns requires iterative calculation, as it includes dual nonlinearity of material and geometry, and the two are coupled with each other. To calculate the bearing capacity of the section adopting ordinary concrete, it is necessary to solve the transcendental equation iteratively. For high-strength concrete, it can only be solved by numerical integration. A fast calculation method by hand is proposed in this paper.

Findings in the literature indicate leading financial analysts attract high levels of market attention and provide more accurate earnings forecasts prior to becoming all-star analysts. Furthermore, these analysts significantly impact the investment decisions of other market participants and thus the market price of assets. Therefore, this study examines the information role of leading financial analysts and identifies two significant conclusions. First, the positive outcomes of these analyst leaders are more informative and attract more followers. Second, informational herding by followers of these analysts is not as naïve as suggested in previous studies, as followers who smartly use information from analyst leaders tend to perform better. We also find that analysts who practice smart learning by studying and selectively employing analyst-leader decisions achieve better career outcomes.

Positive-framed and negative-framed messages were delivered to examine the effect of framing on intertemporal decisions through lab experiments while holding the level of financial literacy constant. The three big questions adopted by Lusardi and Mitchell were utilized to assess the financial literacy of our subjects before they were asked to complete 20 incentivized intertemporal decisions. A small, delayed reward and a slightly bigger one were incorporated into the intertemporal decisions with a delay of 30 days. The ordinary least square (OLS) shows that the negative relationship between financial literacy and discount rates was held when the delayed reward was small. Interestingly, when the delayed reward became slightly bigger, their discount rates were reduced significantly with the negatively framed message. These findings suggest that the negatively framed message can motivate individuals to save for a greater return in the real world. Lastly, subjects with the highest level of financial literacy were not responsive to the magnitude effect, proving that a financial literacy program is essential to strengthen the individual's financial plan and reduce their discount rates in the developing country context.

We form portfolios based on return and liquidity and examine the effects of liquidity and other risk factors on asset pricing in the Chinese stock market. Our results show that the past loser-and-illiquid stock portfolios tend to outperform the past winner-and-liquid stock portfolios in the 1–12 months holding period. The excess return is significantly associated with the market-wide liquidity factor even when we control the three Fama-French and momentum factors. Cross-sectionally, the liquidity beta significantly affects the excess return even with control of other risk betas and other traditional liquidity proxies.