Search Results (120)

This paper investigates the interactive effects of live streaming pre-sale modes and return policies within a manufacturer’s two-stage supply chain. On the one hand, in addition to traditional pre-sales, manufacturers can adopt merchant live streaming or commission influencer live streaming to stimulate demand, enhance consumer engagement, and generate social influence. On the other hand, a “Money-back guarantee (MBG)” policy can be implemented to mitigate consumers’ valuation uncertainty. Using a game-theoretic model, we examine the manufacturer’s optimal joint decisions across six scenarios, determining the optimal conditions for activating each pre-sale mode and the MBG policy. Our findings reveal that the effectiveness of an MBG in promoting pre-sales is not universal but highly contingent on factors such as return costs, product satisfaction, and the social influence generated through live streaming. Specifically, traditional pre-sales tend to adopt an MBG only when return costs are low, whereas merchant live streaming pre-sales consistently adopt it under weak social influence. In contrast, influencer live streaming pre-sales are more likely to adopt MBGs when return costs are low; however, with high return costs, the manufacturer’s profit may fall below that of not conducting pre-sales, leading to the abandonment of this mode. Regarding mode selection, under a no-return policy, manufacturers prefer influencer live streaming when social influence is weak but switch to merchant live streaming when it is strong. When offering an MBG, manufacturers tend to commission influencer live streaming when product satisfaction and return costs are low but revert to traditional pre-sales when satisfaction is high. Conversely, with high return costs, manufacturers prefer merchant live streaming under low satisfaction but favor influencer live streaming when satisfaction is high. These findings offer valuable theoretical insights and practical guidance for manufacturers to optimize their pre-sales and return strategies under diverse market conditions. Full article

This study proposes a structural method for analyzing Raphael Sanzio’s Sistine Madonna through the constructive modeling of visual impact. Such an approach makes it possible to connect the internal logic of the painting’s conception with the historical circumstances of its creation as a papal commission for Julius II, clarifying those compositional decisions that appear unique and uncharacteristic for Raphael’s usual manner. The term visual engineering is employed to designate a structural approach that shifts attention from traditional iconographic interpretation to the underlying constructive logic of the image—the principles by which Raphael organizes space, atmosphere, and light into a unified perceptual system. The aim of the study is to reveal how these interdependent mechanisms generate clarity of spatial hierarchy and integrate architectural, luminous, and symbolic functions within a coherent mode of perception. In this sense, the Sistine Madonna emerges as a deliberately constructed environment of vision, in which pictorial form and theological meaning operate as inseparable components of a single Renaissance act of artistic thought. Full article

Exemplified by EcoStruxure from Schneider and CASICloud, production-capacity-sharing platforms typically operate as two-sided platforms. These platforms contribute to carbon emission reductions while generating revenue through uniform membership fees, fixed service charges, or commission fees applied to one or both sides of the platform. As B2B platforms, however, they must determine whether to offer online payment options to participants on both sides of the market. We employ the theory of two-sided markets and the method of comparative analysis, developing a two-sided market model to investigate: (1) the platform’s optimal payment method selection strategies and (2) how same-side network externalities and user online search costs affect platform performance. We examine two payment modes: M mode (offline payments only) and F mode (combined offline/online payments). The F mode comprises two sub-modes—FF (two-sided users choose to pay offline) and FN (two-sided users choose to pay online)—determined by users’ payment preferences on each side. We conduct pairwise comparisons of the platform’s membership fee, fixed service fee, and online service level between: (i) FF and M modes and (ii) FN and M modes. Our results indicate that the optimal payment method selection varies across market conditions, with each mode demonstrating superior performance under specific market characteristics. The FF mode consistently yields higher profits compared to the M mode. When suppliers’ expected revenues fall below a certain threshold, the FN mode outperforms the M mode in terms of profit generation. Conversely, the M mode becomes preferable above this threshold. Furthermore, the effects of same-side network externalities and search costs vary significantly across different payment modes. Under the M mode and the FF₁ mode, the effects of the same-side network externality on the platform’s membership fee are associated with two-sided users’ online search costs, which are more monotonous. Under the FN₁ and FN₂ modes, both the same-side network externality and two-sided users’ online search costs impact the platform’s optimal strategies monotonously, but they are not always the same in these two modes. Full article

Modern power grids face increasing stress from volatile, high-dynamics loads, such as Electric Vehicle (EV) charging clusters and intermittent renewable energy sources. Accurate transformer thermal monitoring via the International Electrotechnical Commission (IEC) 60076-7 and the Institute of Electrical and Electronics Engineers (IEEE) C57.91 standards is crucial, yet their methodologies differ significantly. This study develops a comprehensive MATLAB simulation framework to quantify these differences. The analysis compares physical thermal models across multi-stage cooling—Oil Natural Air Natural (ONAN), Oil Natural Air Forced (ONAF), and Oil Forced Air Forced (OFAF)—and insulation aging models. It is demonstrated that divergence in transformer life estimation stems primarily from the physical thermal models. A ‘reversal of conservatism’ is identified, where ‘conservative’ is defined as predicting higher hot-spot temperatures and enforcing a larger safety margin. Results prove that while the IEC model is thermally more conservative during cooling failures (static mode), the IEEE model is consistently more conservative during normal active cooling. Additionally, 2D “heat maps” are presented to define safe operational zones, and the catastrophic impact of cooling system failures is quantified. These findings provide a quantitative outline for managing transformer state under increasingly demanding loading schemes. Full article

The unequal status between manufacturers and live-streamers often undermines supply chain profitability and social welfare. However, the “volume guarantee” commission mode, designed to mitigate this issue, has proven ineffective in practice. This paper adopts a Nash bargaining fairness framework to analyze this paradox, incorporating two defining features of live-streaming commerce: the social network effect and the streamer’s cost of purchasing public domain traffic. We develop a dynamic game model involving the platform, manufacturer, streamer, and consumers to examine commission mode selection and supply chain decision-making. Our analysis yields four key findings: (1) Under Nash bargaining fairness, the “volume guarantee” mode is invariably redundant, regardless of who sets the sales threshold. Bargaining power only influences profit distribution via commission rates without distorting optimal product pricing or traffic acquisition decisions. (2) The social network effect boosts product prices, traffic purchases, total profit, and social welfare, with its impact amplified by the streamer’s fanbase size. Thus, collaborating with top-streamers is advantageous for manufacturers. (3) While higher platform traffic costs do not affect the optimal product price, they reduce traffic purchase volume, thereby decreasing supply chain profits and social welfare. (4) To enhance social welfare, platforms can implement differentiated traffic pricing, offering discounts to top-streamers. This study provides critical managerial insights for designing fair contracts and fostering equitable cooperation in live-streaming ecosystems. Full article

Based on the perspective of multi-stage dynamic competition, this study constructs a discrete dynamic model of price competition between the “direct sales” and “resale” channels in cross-border e-commerce (CBEC) under three blockchain deployment modes. Drawing on nonlinear dynamics theory, the Nash equilibrium of the system and its stability conditions are examined. Using numerical simulations, the effects of factors such as the channel price adjustment speed, tariff rate, and commission ratio on the dynamic evolution, entropy, and stability of the system under the empowerment of blockchain technology are investigated. Furthermore, the impact of noise factors on system stability and the corresponding chaos control strategies are further analyzed. This study finds that a single-channel deployment tends to induce asymmetric system responses, whereas dual-channel collaborative deployment helps enhance strategic coordination. An increase in price adjustment speed, tariffs, and commission rates can drive the system’s pricing dynamics from a stable state into chaos, thereby raising its entropy, while the adoption of blockchain technology tends to weaken dynamic stability. Therefore, after deploying blockchain technology, each channel should make its pricing decisions more cautiously. Moderate noise can exert a stabilizing effect, whereas excessive disturbances may cause the system to diverge. Hence, enterprises should carefully assess the magnitude of disturbances and capitalize on the positive effects brought about by moderate fluctuations. In addition, the delayed feedback control method can effectively suppress chaotic fluctuations and enhance system stability, demonstrating strong adaptability across different blockchain deployment modes. Full article

The problem of the conversion of diesel buses to electric ones in connection with the inevitable introduction of the EURO 7 emission standards entails an automatic requirement to follow several additional United Nations Economic Commission for Europe rules, like R100 regulations. They regulate the preservation of battery units at longitudinal 12 g and transverse 10 g accelerations without penetrating into the elements of the bus body. Three models (12 modes in total) of battery units with frames made of S235 steel were analysed. The maximum stress value varies between 364.89 MPa and 439.08 MPa in 10 g and 12 g modes, respectively, which is beyond the tensile strength (360 MPa) and provokes plastic deformations. The max deformations were recorded in the models with the highest average stress: 63.04 mm in the 12 g mode with an average stress of 83.18 MPa. The minimum deformations of 6.95 and 7.95 mm were found in the 10 g modes (left and right acceleration direction, respectively), which meet the manufacturer’s requirements (45–50 mm maximum). The study’s primary contribution lies in developing a practical method for assessing battery unit integrity and structural behaviour during the conversion of diesel buses to electric propulsion, fully compliant with R100 regulations. By combining transient structural simulation, mathematical centre modelling of acceleration propagation, and centre of gravity prediction, the proposed approach enables engineers to evaluate electric conversions’ safety and certification feasibility without modifying the existing bus body. Full article

As environmental issues become increasingly prominent, the sustainable practices of enterprises, especially measures at the product level, have garnered widespread attention from scholars. Although numerous studies have explored suppliers’ sales strategies for green products, they often overlook the scenario where suppliers simultaneously sell both green and non-green products.This study focuses on the sales mode selection strategies of suppliers when providing green and non-green products through e-commerce platforms. Utilizing a game model, we analyze the equilibrium strategies between suppliers and e-commerce platforms, and conduct sensitivity analyses to evaluate the impact of key parameters on decision-making. The results reveal that there are significant differences in the strategic preferences of suppliers and e-commerce platforms. However, when commission rates are moderate and green products incur high production costs, these preferences tend to align, leading to Pareto optimal outcomes. Additionally, our findings demonstrate that adopting differentiated sales modes for the two product types can effectively mitigate the problem of double marginalization, thereby enhancing the efficiencyof supply chains. These insights provide valuable guidance for e-commerce platform managers and suppliers in making decisions on sales models for managing multiple types of products. Full article

Uncertainty in consumer purchasing behavior within online markets propels manufacturers to adopt blockchain for risk mitigation, reshaping supply chain operational dynamics. This study investigates the sales mode selection and blockchain adoption strategies of a risk-averse manufacturer in platform supply chain under uncertain market demand. By integrating Stackelberg game theory with mean-variance analysis, we analyze supply chain equilibrium across four scenarios: RN, RB, AN, and AB. Our findings highlight the significance of a critical commission rate threshold in the manufacturer’s sales mode choice, emphasizing that blockchain adoption enhances the preference for the agency mode. Importantly, highly risk-averse manufacturers are inclined to absorb higher costs associated with blockchain adoption, while those with lower risk aversion only consider it when costs are minimal. Notably, the “agency mode with blockchain adoption” (AB) creates mutual benefits under low adoption costs and risk aversion. When both parties exhibit risk aversion, the platform’s risk aversion significantly influences resale-mode decisions, leading to a transition from the scenario AN to the RB, thereby optimizing synchronized profits. Full article

This study estimated the density distribution of Antarctic krill inhabiting an area near the South Shetland Islands using two acoustic analysis methods recommended by the Commission for the Conservation of Antarctic Marine Living Resources, based on data collected using an echosounder installed on commercial fishing vessels. Mean Antarctic krill density for the entire survey area was estimated with two methods recommended by the Commission for the Conservation of Antarctic Marine Living Resources. The mean body length of krill collected using trawl gear was 49.06 ± 4.15 mm (range: 22.0–67.0 mm), with mode of krill observed at 50 mm body length. Using the swarm-based method and the frequency differences according to krill size, the mean densities of krill for stations and transects were 14.86 g/m² (CV = 47.09%) and 13.10 g/m² (CV = 41.16%), respectively. Furthermore, using the dB-difference method for the entire survey area, the average densities were 10.76 g/m² (CV = 43.83%) and 10.14 g/m² (CV = 53.48%), respectively, using the frequency difference based on krill size determined at all stations and per transect. Full article

With the rapid development of the digital economy and the evolving shopping preferences of consumers, e-commerce platforms have been enhancing their competitiveness by launching private label brands and optimizing their sales channel strategies. This study focuses on an online sales system comprising a strong brand and an e-commerce platform. Four game modes were constructed: agency selling only (NN), agency selling combined with reselling (NS), agency selling combined with private labels (IN), and reselling combined with agency selling under the introduction of private labels (IS). Under the coupon promotion strategy, this study focused on the introduction strategy for private labels (PLs) and the selection strategy for platform sales modes. Our research produced the following findings: (1) Regardless of whether the platform introduces its own brand, adopting a reselling mode can significantly enhance the profits of both the brand owner and platform. (2) Irrespective of whether the reselling mode is implemented, the platform’s profits are always increased when introducing its own brand. (3) When the coupon redemption rate is higher, the brand owner achieves greater profitability in the absence of PL introduction. Conversely, when the coupon redemption rate is low, an increase in the commission rate leads to reduced profit margins for the brand owner due to competition from a private label. (4) When the coupon redemption and commission rate are both high, the coupon face value without a PL is larger. Otherwise, when these rates are both low, the coupon face value is higher under the introduction of a PL. This study offers a theoretical foundation and decision-making support for e-commerce platforms to optimize sales mode selection, introduce private-label brands, and develop coupon strategies. Full article

Building shoreline position databases able to capture event- to centennial-scale coastal changes is critical for scientists to improve knowledge of past coastal dynamics and predict future changes. Thanks to the commissioning of several satellites acquiring recurrent high-resolution optical images over coastal areas, coastal scientists have developed methods for detecting the shoreline position from satellite images in most parts of the world. These methods use image band analyses to delineate the waterline and require post-processing to produce time-consistent satellite-derived shorelines. However, the detection accuracy generally decreases with increasing tidal range. This work investigates an alternative approach for meso- and macrotidal coasts, which relies on the delineation of the boundary between dry and wet sand surfaces. The method was applied to the high-energy meso-macrotidal km-scale Cap Ferret sand spit, SW France, which has undergone large and contrasted shoreline changes over the last decades. Comparisons with topographic surveys conducted at Cap Ferret between 2014 and 2020 have shown that the raw satellite-derived wet/dry line reproduces well the mean high water shoreline, with an overall bias of 1.7 m, RMSE of 20.2 m, and R2 of 0.86. Building on this, the shoreline variability at Cap Ferret was investigated over the 1984–2021 period. Results have evidenced an alongshore gradient in the dominant modes of variability in the last 2 km of the sand spit. Near the tip, the shoreline has chronically retreated on the decadal scale at about 8.4 m/year and has been strongly affected on the interannual scale by the onset and migration of shoreline undulations having a wavelength of 500–1200 m and a cross-shore amplitude of 100–200 m. Some 3 km away from the sand spit extremity, the shoreline has been relatively stable in the long term, with a dominance of seasonal and interannual variability. This work brings new arguments for using the wet/dry line to monitor shoreline changes from spatial imagery at meso- and macrotidal sandy coasts. Full article

Promoting alternative modes of transportation such as cycling represents a valuable strategy to minimize environmental impacts, as confirmed in the main targets set out by the European Commission. In this regard, in cities throughout the world, there has been a significant increase in the construction of bicycle paths in recent years, requiring effective maintenance strategies to preserve their service levels. The continuous monitoring of road networks is required to ensure the timely scheduling of optimal maintenance activities. This involves regular inspections of the road surface, but there are currently no automated systems for monitoring cycle paths. In this study, an integrated monitoring and assessment system for cycle paths was developed exploiting Raspberry Pi technologies. In more detail, a low-cost Inertial Measurement Unit (IMU), a Global Positioning System (GPS) module, a magnetic Hall Effect sensor, a camera module, and an ultrasonic distance sensor were connected to a Raspberry Pi 4 Model B. The novel system was mounted on a e-bike as a test vehicle to monitor the road conditions of various sections of cycle paths in Rome, characterized by different pavement types and decay levels as detected using the whole-body vibration $a_{wz}$ index (ISO 2631 standard). Repeated testing confirmed the system’s reliability by assigning the same vibration comfort class in 74% of the cases and an adjacent one in 26%, with an average difference of 0.25 m/s², underscoring its stability and reproducibility. Data post-processing was also focused on integrating user comfort perception with image data, and it revealed anomaly detections represented by numerical acceleration spikes. Additionally, data positioning was successfully implemented. Finally, $a_{wz}$ measurements with GPS coordinates and images were incorporated into a Geographic Information System (GIS) to develop a database that supports the efficient and comprehensive management of surface conditions. The proposed system can be considered as a valuable tool to assess the pavement conditions of cycle paths in order to implement preventive maintenance strategies within budget constraints. Full article

Woody debris (WD) is an important element in forest ecosystems. It provides critical habitats for plants, animals, and insects. It is also a source of fuel contributing to fire propagation and sometimes leads to catastrophic wildfires. WD inventory is usually conducted through field surveys using transects and sample plots. Light Detection and Ranging (LiDAR) point clouds are emerging as a valuable source for the development of comprehensive WD detection strategies. Results from previous LiDAR-based WD detection approaches are promising. However, there is no general strategy for handling point clouds acquired by different platforms with varying characteristics such as the pulse repetition rate and sensor-to-object distance in natural forests. This research proposes a general and adaptive morphological WD detection strategy that requires only a few intuitive thresholds, making it suitable for multi-platform LiDAR datasets in both plantation and natural forests. The conceptual basis of the strategy is that WD LiDAR points exhibit non-planar characteristics and a distinct intensity and comprise clusters that exceed a minimum size. The developed strategy was tested using leaf-off point clouds acquired by Geiger-mode airborne, uncrewed aerial vehicle (UAV), and backpack LiDAR systems. The results show that using the intensity data did not provide a noticeable improvement in the WD detection results. Quantitatively, the approach achieved an average recall of 0.83, indicating a low rate of omission errors. Datasets with a higher point density (i.e., from UAV and backpack LiDAR) showed better performance. As for the precision evaluation metric, it ranged from 0.40 to 0.85. The precision depends on commission errors introduced by bushes and undergrowth. Full article

Assessing people’s satisfaction with diverse modes of transportation is complex yet crucial. This paper delves into the pivotal outcomes derived from analyzing survey data. The surveys, conducted at Aristotle University of Thessaloniki (AUTH), gauged student satisfaction with the available transport options in the Thessaloniki Metropolitan Area during 2021 and 2022, thus providing insights into trends in satisfaction levels, allowing for a deeper understanding of evolving mobility preferences. Through a comparative analysis of the data, we discerned attributes influencing participants’ transportation choices. Our research contributes to the literature by applying a standardized methodology using an algorithm developed by the European Commission; the satisfaction levels among university students for private car and public transport in those years were determined. Notably, the findings underscore that, despite a marginally higher usage of public transport, university students exhibit a greater satisfaction level with private car transportation. This implies a nuanced preference for private car usage among students, as opposed to a mere emphasis on the higher popularity of public transport within this demographic. The findings aim to provide transport operators and policymakers with valuable information in terms of ways to enhance sustainable urban mobility and improve public transport services. Full article