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Previous studies have rarely integrated the financing modes of a capital-constrained manufacturer with the choices of online sales strategies. To address this gap, the authors study how a manufacturer selects optimal financing modes under different sales strategies in three dual-channel supply chains.

This paper considers three sales strategies, namely, combining a traditional retailer channel with one of the direct selling, reselling and agency selling channels, and two common financing modes, namely, bank financing and retailer financing. The authors obtain equilibrium outcomes of the manufacturer and traditional retailer and then provide the conditions for them to select optimal financing modes under three sales strategies.

The results indicate that the manufacturer’s financing decisions rely on the initial capital and interest rates, and the manufacturer selects retailer financing only if the initial capital is relatively larger. In terms of financing mode options, the retailer financing mode is more beneficial for the manufacturer under the three sales strategies. From the perspective of sales strategies, the direct selling model is more beneficial. In addition, the higher the consumer acceptance of the online channel, the more profits the manufacturer obtains.

This paper provides suggestions on how the capital-constrained manufacturer chooses financing modes and sales strategies.

This paper integrates the financing mode and different sales strategies to investigate the manufacturer’s optimal operational decisions. These sales strategies allow us to investigate the manufacturer’s optimal financing modes in the presence of both different financing modes and sales strategies.

The purpose of this study is to compare the properties and performance of ordinary Portland cement-based self-compacting concrete (OPC-SCC) and pozzolanic-based SCC (pozzolanic-SCC) in concrete applications. The research employs a comparative analysis to examine the workability and strength characteristics of these two types of SCC.

This study involves analyzing and comparing the properties and performance of OPC-SCC and pozzolanic-SCC through a literature review of relevant studies and experiments. The key findings indicate that the use of pozzolanic materials in SCC, such as fly ash, silica fume and metakaolin, can enhance the sustainability and durability of the concrete. The research also reveals that the choice of steel fibers and polypropylene fibers can impact the fire performance and mechanical properties of SCC.

The findings indicate that the inclusion of supplementary cementitious materials enhances the workability, strength and fire resistance of SCC to a greater extent compared to the addition of steel and polypropylene fibers.

The practical implications of this research are significant for selecting and utilizing SCC in concrete applications.

The originality of this research lies in the comparative analysis of OPC-SCC and pozzolanic-SCC, considering their properties, performance and practical implications. The study extends the existing knowledge on the use of SCC and provides insights into best practices for its application. The research contributes to the field of concrete technology and sustainable construction by highlighting the benefits and limitations of different types of SCC and their potential impact on concrete performance.

Building on the core concept of anthropomorphism and the empathy-helping theory, this research aims to examine how product anthropomorphism and buyer usage intentions affect sellers’ pricing in second-hand markets as well as explore the psychological dynamics underlying these effects.

To test the hypotheses, a series of four experiments were conducted. Studies 1a (n = 140) and 1b (n = 140) employed a one-factor (product anthropomorphism: yes vs no) between-subject design and used chi-square analysis. Study 2 (n = 145) and Study 3 (n = 162) employed a 2 (usage intention: protective vs destructive) × 2 (product anthropomorphism: yes vs no) between-subject design and used two-way ANOVA and moderated mediation analysis.

The study found that even when potential buyers with destructive (vs protective) usage intentions offer higher prices, sellers of anthropomorphized (vs non-anthropomorphized) products are less willing to choose them (Studies 1a and 1b). When potential buyers express destructive (vs protective) usage intentions, sellers of anthropomorphized (vs non-anthropomorphized) products are less willing to offer discounts (Study 2), and the lowest price they are willing to accept is higher (Study 3). The level of perceived capacity for pain mediates these effects (Study 3).

These findings offer insights into the application of product anthropomorphism strategies and the second-hand transactions of used anthropomorphized products.

Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes.

The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns.

The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%.

The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution.

Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland.

The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

The high-load operation of the engine crankshaft causes severe wear and fatigue. This study aims to prepare in situ textures with effective density and study their wear mechanism on the surface of ductile cast iron, which optimizes the tribological properties of engine crankshafts and reduces wear.

A new method was proposed based on the hardness difference in graphite removal to form an in situ texture. The friction performance was evaluated using a combination of computational fluid dynamics and tribological testings. The influence of the texture characteristic parameters on the bearing capacity of the oil film was analyzed. The surface wear morphology was studied by scanning electron microscopy.

The texture density significantly affected the oil film bearing capacity. The surface texture can reduce the average friction coefficient (COF) by more than 35% owing to the oil film bearing and storage capacity. Specifically, the 13% texture density exhibited the lowest wear rate and COF under all three experimental conditions. The reduction in abrasive particles in the wear area of the textured surface indicates that the surface texture can improve the lubrication mechanism.

This study systematically explored the influence of the weight of each model parameter on tribological properties. Subsequently, focusing on the critical parameter (texture density), detailed tribological testings were carried out to reveal the specific effect of texture density on the wear mechanism under different working conditions, and the optimal texture density to achieve the optimal tribological performance was determined accordingly.

This study proposes the novel construct of digital transformation anxiety and investigates its effect, which is mediated by absorptive capacity and dynamic capability, on digital innovation performance.

This study conducted a questionnaire survey among Taiwanese manufacturing and service companies to verify the research framework. A total of 130 valid responses were collected and analyzed using partial least squares structural equation modeling (PLS-SEM) and bootstrapping to test direct and mediation effects, respectively.

Digital transformation anxiety negatively affects absorptive capacity and dynamic capability, whereas absorptive capacity and dynamic capability positively affect digital innovation performance. Dynamic capability more strongly mediates the association between digital transformation anxiety and digital innovation performance than absorptive capacity. Additionally, digital transformation anxiety does not negatively affect digital innovation performance. Finally, manufacturing companies had significantly higher levels of digital transformation anxiety than service companies.

This study proposes the novel construct of digital transformation anxiety to address a gap in the literature. Digital transformation anxiety leads companies to adopt unnecessarily conservative practices, preventing them from flexibly responding to technological advances. This insight highlights the negative effect of such anxiety on absorptive capacity and dynamic capability, extending the application of path dependency theory to companies. The findings underscore the value of enhancing dynamic capability and reallocating resources to foster digital innovation. The study identified and explored the concept of digital transformation anxiety and extended the perspective of dynamic capability to include digital transformation and digital innovation.

The current findings indicate that digital transformation anxiety does not substantially affect digital innovation performance in Taiwanese companies. Consequently, Taiwanese companies should focus on developing their absorptive capacity and dynamic capability to enhance digital innovation.

The study proposes the novel construct of digital transformation anxiety and explores its effect on business units. It presents a pioneering framework derived from path dependence theory and the perspective of dynamic capability.

This study aims to explore the impact mechanism of social support on individual health knowledge creation among users in online patient communities, guide and promote the creation of health knowledge and provide insights into managing online patient communities.

A theoretical model was constructed by integrating social impact and social support theories. Data were collected through questionnaires, and 750 valid responses were analysed using a structural equation model.

This study found the following. (1) Social support influences individual health knowledge creation through the mediating effects of creative self-efficacy and positive emotions. (2) The general rule of the strength of the influencing factors on individual health knowledge creation is that creative self-efficacy > positive emotions. (3) The general pattern of the mediating effect of attitude factors between social support and health knowledge creation is that creative self-efficacy > positive emotions. (4) The key path for social support to influence individual health knowledge creation is “social support → creative self-efficacy → health knowledge creation”. (5) The dimensions of social support in online patient communities can be divided into information, emotional, respect and network support. Individual health knowledge creation can be divided into health knowledge externalisation, combination, socialisation and internalisation.

This study expands the application scope of social influence theory and opens up the “black box” of the impact of social support on individual health knowledge creation behaviour. Simultaneously, the dimensions of social support, individual health knowledge creation and the mediating role between social support and health knowledge creation are discussed.

This study aims to propose a calibration method to enhance the positioning accuracy in dual-robot collaborative operations, aiming to address the challenge of drilling hole spacing errors in spacecraft core cabin brackets that require an accuracy of less than 0.5 mm.

Initially, the cooperative error of dual robots is defined. Subsequently, an integrated model is constructed that encompasses the kinematic model errors of the dual robots, as well as the establishment errors of the base and tool frames. A calibration method for optimizing the cooperative accuracy of dual robots is proposed.

The application of the proposed method satisfies the collaborative drilling requirements for the spacecraft core cabin. The average cooperative positioning error of the dual robots was reduced from 0.507 to 0.156 mm, with the maximum value and standard deviation decreasing from 1.020 and 0.202 mm to 0.603 and 0.097 mm, respectively. Drilling experiments conducted on a core cabin simulator demonstrated that after calibration, the maximum hole spacing error was reduced from 1.219 to 0.403 mm, with all spacing errors falling below the 0.5 mm threshold, thus meeting the requirements.

This paper addresses the drilling accuracy requirements for spacecraft core cabins by using a calibration method to reduce the cooperative error of dual robots. The algorithm has been validated through experiments using ER 220 robots, confirming its effectiveness in fulfilling the drilling task requirements.

This study aims to provide a new perspective on the impact of mortality threats on consumer behavior through the lens of brand anthropomorphism. It examines the mediating effects of control and connectedness motives and the moderating effects of brand roles on the relationship between mediators and brand attitudes.

A preliminary study explored the relationship between pandemic-induced mortality threats and attitudes toward anthropomorphized brands. Study 1 investigated the underlying mechanism, and Study 2 examined the moderating effects of servant or partner roles. Study 3 confirmed the mortality threat effect on anthropomorphic brand attitudes in the absence of the pandemic.

The study revealed that mortality threats enhanced the desire for control and connectedness, which strengthened attitudes toward anthropomorphized brands. The results also indicated matching effects between the motivations for anthropomorphism and brand roles.

This research offers novel insights into the effects of pandemic-induced mortality threats and mortality threats in non-pandemic contexts on anthropomorphic motives. It highlights the influence of these psychological needs on consumer responses to brand roles and provides insights for brand management during a crisis.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.