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Since the inception of aircraft, the phenomenon of spin has persistently accompanied aircraft, and research into spin has been ongoing. This paper aims to introduce an optimization technique to enhance the traditional geometric method for predicting steady spin, aiming to achieve more precise predictive outcomes.

To begin with, the force and moment equations used for motion analysis are initially presented, followed by the establishment of the motion model. Subsequently, the forward problem is set up, and the equilibrium solutions for the left and right spins of the aircraft are determined using the geometric method under the basic and wingtip configurations, thus solving the forward problem. In the final stage, nonlinear inversion is applied, and the inversion objective function is formulated based on the least squares approach. Through iterative processes, the measured data are interpolated, leading to the acquisition of the accurate equilibrium solution.

The findings indicate that the utilization of the nonlinear iterative inversion algorithm has effectively optimized the geometric method, yielding favorable outcomes. Postoptimization, the prediction accuracy has been enhanced, and the error has significantly diminished when compared to the preoptimization results.

The nonlinear inversion algorithm is used to refine the steady spin prediction for general aviation aircraft. This approach significantly mitigates the precision issues inherent in the forward problem. As demonstrated through the simulations provided, the application of the nonlinear iterative algorithm to resolve the inversion function yields promising optimization outcomes.

Robots are widely used in industrial manufacturing and service industries around the world. However, most of the previous studies on industrial robots use data at the national or industry level in the context of developed countries. This study examines the impact of imported industrial robots on firm innovation at the firm level in China.

Drawing on a large dataset of more than three million records in China, including non-publicly traded small and medium firms, the authors adopt a difference-in-differences method to investigate the impact and channels of industrial robots on firm innovation.

The authors find that the application of industrial robots increases firm innovation. Two possible channels are identified through which robots promote innovation: alleviation of financial constraints and the improvement of human capital. Further analysis shows that the effect of robots on innovation is more pronounced for firms that are highly dependent on external financing, belong to high-tech industries, import high-end robots, have insufficient supply of skilled labor and private firms (non-SOEs). The authors also find that industrial robots increase the firms' innovation quality and the marginal contribution of innovation to firms' total factor productivity.

This study provides big data evidence of the unintended positive consequences of industrial robots on firm innovation. The results are helpful to clarify the controversy of industrial robots. It also has important implications for government industrial policy making, firm innovation and human resource management.

The purpose of this paper is to explore the effects of competitive pressure on financial statements’ comparability (comparability) by analyzing various dimensions of competition.

The authors study the effect of competition on comparability using the comparability measure of De Franco et al. (2011) and various proxies for competition, competition from existing/potential rivals and non-price competition (NPC).

This study documents that competition is positively associated with comparability, and this effect is more (less) pronounced for industry followers (leaders). The authors also document that competition from existing rivals enhances comparability, but competition from potential entrants does not. Moreover, NPC is also a significant determinant of comparability. Furthermore, the competition from existing/potential rivals plays no significant role in the production of comparable financial statements in state-owned enterprises. The results are robust to alternative measures of comparability and methodological approaches.

This study is the first empirical study that documents a new channel (comparability) through which competition affects financial statements. The findings support the argument that competitive pressure acts as a governance mechanism, disciplines management and increases comparability leading to lower information asymmetry (governance view). However, the findings contest the argument that higher competition motivates managers to withhold information (proprietary cost hypothesis). By examining the effect of state ownership, this study might also help to characterize the effects of changes in corporate objectives on managerial decisions related to financial reporting.

The conventional textile dyeing process requires various operational characteristics, and determining the most reliable factor in dyeing performance has always been a challenge for the textile industry. Thus, the present paper aimed to evaluate the process sensitivity of C. I. Reactive Blue 194 dyeing of cotton fabric using a statistical technique.

An L₂₇ orthogonal array-based Taguchi's methodology was used with six parameters and three levels of each parameter. The signal-to-noise (S/N) ratio and analysis of variance were studied using total fixation efficiency (T%) as the response of the process sensitivity.

Results showed that dyebath pH was the most influential factor on the process and total fixation efficiency (p-value = 0.00 and contribution percentage 45.03%), followed by dye-fixing temperature, dye mass, electrolyte concentration, dye-fixing time and material to liquor ratio.

Overall this study provides a foundation for the determination of dyeing process sensitivity that will be useful in textile industries toward further development.

This study searches for sentimental herding in Borsa Istanbul (BIST) during the last decade using a state-space model employing cross-section standard deviations of systematic risk (Beta). It has been found that herding toward the market in the BIST-100 is both statistically significant and persistent independently from market fundamentals such as the volatility of returns and the levels of market returns. Herding trends over the sample period indicate that the financial crisis in 2000–2001 appeared to bring about sentimental herding in BIST which was followed by a calm period during which investors turned to fundamentals. Thereafter, we observe a volatile adverse herding pattern till the end of 2011 due to the confusing environment caused by the internal and external events.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

Smartphone demand has been driving people towards refurbished electronic products. However, a lack of transparency in refurbished product pricing makes purchases time-consuming and reduces customer trust. Thus, our research aims to help practitioners and researchers understand how product life and usage characteristics, technical attributes and crowdsourced product reviews and sentiments affect exchange prices for refurbished/remanufactured smartphones.

Our five-stage exchange price predictive framework begins with data gathering and predictor variable identification. Thereafter, customer review data were scraped to populate both customer ratings and textual content, enabling sentiment analysis for the various smartphone configurations. Stepwise regression was used to find statistically significant factors and validate the predictive model. Testing for nonlinear effects, normality, outliers and homoskedasticity warrants power transformation of the target variable. The analysis used data from GSMArena.com and Amazon.com.

Our study validates extant findings and provides several novel insights for functional yet hedonistic products like smartphones. Unlike other pure hedonistic products, refurbished phone buyers care more about usage duration than life. Besides having a strong affinity for the sleekness of the phone, such customers are strongly dissuaded by the presence of negative textual content in the customer reviews.

Our study augments the current understanding of exchange price modelling by bringing in perspectives from life cycle characteristics, technical attributes and product reviews.

The primary aim of this study is to examine the decision-making process of a reverse supply chain within a cooperative-competitive environment, with a particular emphasis on the incorporation of Internet of Things (IoT) technology in the recycling process.

The impact of IoT on recycling effectiveness, RF (refurbished) product demand and remanufacturing expenses is analyzed. The game-theoretic models are constructed to incorporate the co-competitive relationship between a IR (Internet Recycler) and a remanufacturer, with specific attention paid to the IR's application of IoT technology.

The results indicate that the use of IoT reduces the costs associated with remanufacturing, leading to an increase in the transfer price of pre-owned items procured from IRs. The efficacy of the reverse supply chain depends not only on its cost-saving capabilities but also on consumer preferences toward RF and remanufactured (RM) items.

IoT technology can benefit Internet recycling and remanufacturing by enhancing transparency, quality monitoring and automation of processes. It can also help reduce operating costs, improve customer engagement and incentivize cooperation between organizations.

This study examined the strategic decision-making processes in the context of cooperation and competition between IR and remanufacturers. In addition, this research makes a valuable contribution to the literature by elucidating the optimal conditions for the effective implementation of Internet of Things (IoT) technology in recycling operations.

The blade profile and its geometrical features play an important role in the separation of the boundary layer on the blade. Modifying the blade geometry, which might lead to the delay or elimination of the flow separation, can be considered as a passive flow control methodology. This study aims to find a novel and inexpensive way to reduce loss with appropriate modifications on the leading edge of the turbine blade.

Three types of wave leading edges were designed with different wavelengths and amplitudes. The selected numbers for the wave characteristics were based on the best results of previous studies. Models with appropriate and independent meshing have been simulated and studied by a commercial software. The distribution of the loss at different planes and mid-plane velocity vectors were shown. The mass flow average of loss at different incidence angles was calculated for the reference blade and modified ones for the sake of comparison.

The results show that in all three types of modified blades compared to the reference blade, the elimination of flow separation is observed and therefore the reduction of loss at the critical incidence angle of I = –15°. As the amplitude of the wave increased, the amount of loss growing up, while the increase in wavelength caused the loss to decrease.

The results of the present numerical analysis were validated by the laboratory results of the reference blade. The experimental study of modified blades can be used to quantify numerical solutions.

This paper examines how the level of low-carbon awareness (LCA) affects the remanufacturing strategy in a supply chain with an original equipment manufacturer (OEM) and an independent remanufacturer (IR) competing with each other.

Game theory and operations optimization.

The studies analytically characterize the threshold levels of the LCA in response to which the OEM and the IR will change their remanufacturing strategies from no remanufacturing to partial remanufacturing and then to full remanufacturing. In addition, the studies reveal that as compared with the OEM, the IR has more flexibility in terms of the market entry to remanufacturing with the level of LCA increasing. With the extended studies, it is exhibited that the above findings are robust to a good extent.

It can provide decision support for remanufacturing enterprises.