Optimal Mode Research Articles

Optimal Nonlinear Robust Sliding Mode Control of an Excitation System Based on Mixed $\mathcal{H}_{2}/\mathcal{H}_{\infty}$ Linear Matrix Inequalities

Optimal Nonlinear Robust Sliding Mode Control of an Excitation System Based on Mixed $\mathcal{H}_{2}/\mathcal{H}_{\infty}$ Linear Matrix Inequalities

Techno-Economic Analysis of Clean Hydrogen Production Plants in Sicily: Comparison of Distributed and Centralized Production

This paper presents an assessment of the levelized cost of clean hydrogen produced in Sicily, a region in Southern Italy particularly rich in renewable energy and where nearly 50% of Italy’s refineries are located, making a comparison between on-site production, that is, near the end users who will use the hydrogen, and centralized production, comparing the costs obtained by employing the two types of electrolyzers already commercially available. In the study for centralized production, the scale factor method was applied on the costs of electrolyzers, and the optimal transport modes were considered based on the distance and amount of hydrogen to be transported. The results obtained indicate higher prices for hydrogen produced locally (from about 7 €/kg to 10 €/kg) and lower prices (from 2.66 €/kg to 5.80 €/kg) for hydrogen produced in centralized plants due to economies of scale and higher conversion efficiencies. How-ever, meeting the demand for clean hydrogen at minimal cost requires hydrogen distribution pipelines to transport it from centralized production sites to users, which currently do not exist in Sicily, as well as a significant amount of renewable energy ranging from 1.4 to 1.7 TWh per year to cover only 16% of refineries’ hydrogen needs.

Fast Depth Map Coding Algorithm for 3D-HEVC Based on Gradient Boosting Machine

Three-Dimensional High-Efficiency Video Coding (3D-HEVC) has been extensively researched due to its efficient compression and deep image representation, but encoding complexity continues to pose a difficulty. This is mainly attributed to redundancy in the coding unit (CU) recursive partitioning process and rate–distortion (RD) cost calculation, resulting in a complex encoding process. Therefore, enhancing encoding efficiency and reducing redundant computations are key objectives for optimizing 3D-HEVC. This paper introduces a fast-encoding method for 3D-HEVC, comprising an adaptive CU partitioning algorithm and a rapid rate–distortion-optimization (RDO) algorithm. Based on the ALV features extracted from each coding unit, a Gradient Boosting Machine (GBM) model is constructed to obtain the corresponding CU thresholds. These thresholds are compared with the ALV to further decide whether to continue dividing the coding unit. The RDO algorithm is used to optimize the RD cost calculation process, selecting the optimal prediction mode as much as possible. The simulation results show that this method saves 52.49% of complexity while ensuring good video quality.

Adaptively multi-scale microstructure characterization of cancellous bone via photoacoustic signal decomposition

Osteoporosis is a systemic disease with a high incidence in the elderly and seriously affects the quality of life of patients. Photoacoustic (PA) technology, which combines the advantages of light and ultrasound, can provide information about the physiological structure and chemical information of biological tissues in a non-invasive and non-radiative way. Due to the complex structural characteristics of bone tissue, PA signals generated by bone tissue are non-stationary and nonlinear. However, conventional PA signal processing methods are not effective for non-stationary signal processing. In this study, an empirical mode decomposition (EMD)-based Hilbert-Huang transform (HHT) PA signal analysis method, called HHT PA signal analysis (HPSA), was developed to assess the microstructure information of bone tissue, which is closely related to bone health. The feasibility of the HPSA method in bone health assessment was proven by numerical simulation and experimental studies on animal samples with different bone volume/total volume (BV/TV) and bone mineral densities. First, based on adaptive EMD, the different modes correlated with multi-scale information were mined from the PA signal, the correlations between different intrinsic mode function (IMF) modes and BV/TVs were analyzed, and the optimal mode for more efficient PA time–frequency analysis was selected. Second, multi-wavelength HPSA was used to assess the changes in the chemical components of the bone tissue. The results demonstrate that the HPSA method can distinguish bones with different BV/TVs and microstructure conditions adaptively with high efficiency. They further emphasize the potential of PA techniques in characterizing biological tissues in bones for early and rapid detection of bone diseases.

Selection of heat treatment and its impact on the structure and properties of AK10M2N–10%TiC composite material obtained via SHS method in the melt

The composite materials based on the Al–Si system alloys, strengthened with a highly dispersed titanium carbide phase, possess improved characteristics and belong to the group of promising structural materials. Currently, self-propagating high-temperature synthesis (SHS) based on the exothermic interaction, wherein titanium and carbon precursors directly involve in the melt, is the most accessible and effective method to obtain them. This paper proves the feasibility and demonstrates the successful synthesis of a 10 wt.% titanium carbide phase in the melt of the AK10M2N alloy, resulting in the AK10M2H-10% TiC composite material. Samples of the matrix alloy and the composite material were subjected to heat treatment according to the T6 mode, with various temperature-time parameters for hardening and aging operations. Based on the results, optimal heat treatment modes were selected to ensure maximum hardness. We studied the macroand microstructure of the obtained samples and performed micro X-ray spectral and X-ray diffraction phase analyses. Different groups of properties underwent comparative tests. It was established that the density of AK10M2N–10%TiC samples before and after heat treatment, according to optimal modes, is close to the calculated value. We showed that the combination of reinforcement and heat treatment significantly increases hardness, microhardness, and compressive strength, with a slight decrease in ductility. Additionally, it maintains the values of the coefficient of thermal linear expansion, high-temperature strength, and resistance to carbon dioxide and hydrogen sulfide corrosion at the level of the original alloy. The greatest effect was observed during the investigation of tribological characteristics: heat treatment of the composite material according to the recommended mode significantly reduces the wear rate and friction coefficient, eliminates seizure and tearing, and prevents temperature rise due to friction heating.

Simulation and analysis of optimal energy-saving mode in microfield of underground rail transit

Underground rail transit has become one of the most popular transportation modes because of its advantages such as fast running speed, large passenger flow and punctuality. This mode of transportation can alleviate urban traffic congestion to a certain extent, so underground rail transit has been vigorously developed, and the number of rail lines has increased exponentially. However, with the continuous development of underground rail transit, the energy consumption of train operation is also increasing, resulting in a waste of energy. To solve this problem, this paper proposes to improve the energy-saving technology of train operation by using train autopilot control strategy. Firstly, a train operation optimization model considering train position and speed limit is established by using automatic train driving strategy, and the nonlinear problem of the optimization model is solved by genetic algorithm. The micro-field theory is introduced into the control strategy of automatic train driving, and the energy-saving model of underground rail transit is established. The energy consumption is optimized from three aspects: train energy-saving technology, line planning and overall operation planning of rail transit. The simulation results show that the average impact rate and energy consumption of trains under the proposed energy-saving model are significantly reduced compared with the other two groups of trains, and the average impact rate and energy consumption are significantly reduced compared with the other two groups of trains. The running time and energy consumption of the energy-saving model are lower than those of the experimental group. To sum up, the energy-saving model of underground rail transit proposed in this paper not only reduces the operating energy consumption, but also improves the passenger comfort, which can provide low-cost energy-saving technology for underground transportation field, and has positive significance for urban low-carbon development.

The result of the investigation of a new micromodule gas burner with a sudden expansion at the outlet

The object of the study is a new micromodule gas burner for small hot water boilers, in which, to stabilize combustion, the phenomena of flow disruption due to sudden expansion at the outlet of the burner are used. Today, there is an urgent task related to the development of new technical solutions for the most efficient and environmentally pure combustion of fuel in power plants, particularly, it is necessary to pay special attention to the stabilization of the flare. The combustion characteristics in this burner have been studied experimentally and theoretically, calculations are given for modeling a micromodule gas burner with a sudden expansion at the outlet, in particular, the model of a burner device for burning natural gas (propane) was modeled in the Ansys Fluent 2021 R1 software package. As a result of the experiment, the length of the torch was reduced, as well as the concentrations of harmful NOx emissions were reduced with improved indicators of combustion completeness and temperature uniformity of the field. The results of experiments with different nozzles are presented, namely nozzles with slots at the outlet d1 – 0.12 m and d2 – 0.15 m. The number of modes in each experiment is 5. Mathematical modeling of this burner with the possibility of evaluating the effectiveness of these measures will allow us to develop optimal operating modes of power plants and develop new technical solutions to reduce the emission of pollutants. Based on the experimental data obtained, graphs were constructed (completeness of combustion, temperature unevenness, concentration of substances), and the results were summarized. In general, these characteristics will increase the efficiency of using this burner in hot water boilers

Energy management strategy for electro-hydraulic hybrid electric vehicles considering optimal mode switching: A soft actor-critic approach trained on a multi-modal driving cycle

Hybrid electric vehicles (HEVs) feature multiple working modes. Thoughtful selection of these modes can optimally balance driving performance, power demands, and energy consumption, thereby enhancing the overall efficiency of the vehicle. This paper presents a soft actor-critic (SAC) approach trained on a multi-modal driving cycle (MDC) for selecting operational modes of electro-hydraulic hybrid electric vehicle (EHHEV). Firstly, characteristic parameters are extracted and clustered for five typical driving cycles through principal component analysis and K-means clustering, creating a multi-modal driving cycle. Secondly, based on the operational characteristics of EHHEV, state variables, action variables, reward functions, learning rates, and other parameters are set for the SAC algorithm, and the EMS framework is built based on the electro-hydraulic hybrid electric power system. Subsequently, the SAC algorithm is trained using the MDC to construct the SAC-MDC EMS. Results demonstrate that compared to EV, RB EMS, and SAC EMS, IREC achieves maximum improvements of 22.38 %, 5.55 % and 0.80 %, respectively. The dynamic performance and the motor load optimization capability are also enhanced. To further validate the practicality and reliability of the SAC-MDC EMS, this paper validates it using actual driving data, revealing that it still exhibits outstanding performance.

Evaluating and optimizing of steam ejector performance considering heterogeneous condensation using machine learning framework

In the context of global warming and pollution concerns, refrigeration systems have become pivotal in energy conversion system. Within this realm, ejector types that harness renewable energy resources emerge as promising alternatives, offering a pathway towards environmentally conscious and resilient energy practices. Under specific conditions, condensation within the heat exchanger results in diverse droplet sizes at the ejector inlet, inducing homogeneous-heterogeneous condensation (HMTC) and heterogeneous condensation (HTC) phenomena. This study aims to evaluate and improve the performance of steam ejectors by investigating and optimizing the effects of homogeneous condensation (HMC), HTC, HMTC, and evaporation processes using a machine learning (ML) framework. The drone squadron optimization (DSO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) are chosen and used in the ML framework to find the optimal droplet radius and number. Findings predict that the presence of 1018 1/kg droplets with a radius of 0.02 μm (Optimal mode) at the inlet results in a 2.6 % increase in the entrainment ratio (Er) and a 6.9 % reduction in the entropy generation compared to the baseline mode. Generally, the research reveals that HTC exhibits superior performance compared to prevailing theories, leading to enhanced ejector performance.

Prediction of emergency-free operation of production wells with a horizontal termination under conditions of high removal of mechanical impurities on the example of the Severo-Komsomolskoe field

Relevance. As readily available oil reserves are developed and production technologies develop, oil and gas companies are gradually moving to the development of previously unprofitable assets. Over the past five years, several oil-and-gas condensate fields with oil rims have been put into operation in Western Siberia. Their development is further complicated by oil high viscosity and poor cementation of the reservoir rocks. Low values of critical drawdown do not allow oil to be produced without destruction of the productive formation, and mechanical impurities entering the well lead to spillage of perforation intervals and downhole equipment failures. The use of mathematical modeling in relation to the operation of wells in the conditions of the removal of mechanical impurities will make it possible to control production and select the optimal well operation mode. Aim. Forecasting the trouble-free operation of a production well under conditions of high removal of mechanical impurities. Objects. Producing oil wells; the subject of the study is the movement of solid particles in the wellbore of a production well, the relationship and dependence of formation of sand plugs on the operating parameters of the well. Methods. Theoretical research methods – analysis (analysis of models for calculating the critical flow velocity in a horizontal pipe (calculation of the critical velocity in a single-phase flow; calculation of the critical velocity in a multi-phase flow; calculation of the critical velocity based on the balance of forces)) and modeling (simulation of work wells with the removal of mechanical impurities). The totality and combination of these methods are adequate to the goals and objectives, the object and subject of the study of this work. Results. The problem of sand production is typical not only for fields that are in the late stages of development, but also for fields that have recently been put into operation. Sand shows up are a complicating factor in the operation of wells at the Severo-Komsomolskoe high-viscosity oil field located in Western Siberia. The main object of development of the studied field is a weakly cemented sandy layer. Oil production in such difficult areas requires a very careful approach to the choice of development system, to the selection of methods to deal with complications, including the choice of the right method to limit sanding. However, regardless of the approach taken to solve the problem of sand production, some rock will still flow into the well. To prevent the formation of sand plugs, it is necessary to understand the nature of the movement of solid particles along the wellbore. It is possible to assess whether a well is capable of carrying out solid particles from a horizontal section using modeling in specialized software products. Modeling of the well operation, taking into account the influence of mechanical impurities, made it possible to solve the following problems: 1) determine the fluid to carry rock particles out of the horizontal section; 2) identify the areas in which there is a risk of sand plugs; 3) present the dependence for calculating the critical speed for high-viscosity oil with different water cut; 4) assess how the water cut and gas factor affect well operation in conditions of high removal of mechanical impurities; 5) calculate the time of formation of sand plugs.

Analysis of the amount of latent carbon in the reconstruction of residential buildings with a multi-objective optimization approach

Purpose Due to the increase in energy demand and the effects of global warming, energy-efficient buildings have gained significant importance in the modern construction industry. To create a suitable framework with the aim of reducing energy consumption in the building sector, the external walls of a residential building were considered with two criteria of global warming potential and energy consumption. Design/methodology/approach In the first stage, to achieve a nearly zero-energy building, energy analysis was performed for 37 different states of thermal insulation. Then, the insulation materials’ life cycle assessment was performed. These results were used to find a set of optimal modes in the Pareto front by using non-dominated sorting genetic algorithm II multi-objective genetic algorithm. Thus, based on the data obtained from this method, it was possible to compare and choose different thermal insulation materials based on the distance from the Pareto front, reducing the environmental effects. Findings The results showed that replacing the windows was possible to save 3.24% in energy consumption. Also, selecting the proper insulation reduced energy consumption value by 63.13%. Finally, this building can save 69.31% of energy consumption compared to the base building by following the zero-energy building standard. As a result, the Pareto curve was introduced as a guide for the optimal design of the building’s wall insulation. Originality/value The proposed method provides designers with a framework for latent carbon analysis to access quickly and select optimal scenarios. It can also be used without restrictions for other decisions with different goals and criteria.

A health technology assessment of COVID-19 vaccination for Nigerian decision-makers: Identifying stakeholders and pathways to support evidence uptake

BackgroundNigeria commenced rollout of vaccination for coronavirus disease 2019 (COVID-19) in March 2021 as part of the national public health response to the pandemic. Findings from appropriately contextualized cost–effectiveness analyses (CEA) as part of a wider process involving health technology assessment (HTA) approaches have been important in informing decision-making in this area. In this paper we outline the processes that were followed to identify COVID-19 vaccine stakeholders involved in the selection, approval, funding, procurement and rollout of vaccines in Nigeria, and describe the process routes we identified to support uptake of HTA-related information for evidence-informed policy in Nigeria.MethodsOur approach to engaging with policy-makers and other stakeholders as part of an HTA of COVID vaccination in Nigeria consisted of three steps, namely: (i) informal discussions with key stakeholders; (ii) stakeholder mapping, analysis and engagement; and (iii) communication and dissemination strategies for the HTA-relevant evidence produced. The analysis of the stakeholder mapping uses the power/interest grid framework.ResultsThe informal discussion with key stakeholders generated six initial policy questions. Further discussions with policy-makers yielded three suitable policy questions for analysis: which COVID-19 vaccines should be bought; what is the optimal mode of delivery of these vaccines; and what are the cost and cost–effectiveness of vaccinating people highlighted in Nigeria’s phase 2 vaccine rollout prioritized by the government, especially the inclusion of those aged between 18 and 49 years. The stakeholder mapping exercise highlighted the range of organizations and groups within Nigeria that could use the information from this HTA to guide decision-making. These stakeholders included both public/government, private and international organizations The dissemination plan developed included disseminating the full HTA results to key stakeholders; production of policy briefs; and presentation at different national and international conferences and peer-reviewed publications.ConclusionsHTA processes that involve stakeholder engagement will help ensure important policy questions are taken into account when designing any HTA including any underpinning evidence generation. Further guidance about stakeholder engagement throughout HTA is required, especially for those with low interest in vaccine procurement and use.

УПРОЧНЕНИЕ МЕТАЛЛОРЕЖУЩЕГО ИНСТРУМЕНТА ЭЛЕКТРОИСКРОВОЙ ОБРАБОТКОЙ

Metal-cutting tools during the machining of parts by cutting experience high strength and thermal loads, causing wear of the cutting edges. Increasing the wear resistance of the cutting edges of a metal-cutting tool is an urgent task. (Research purpose) The research purpose is analyzing the causes of wear of end mills and drills and proposing the most rational method of hardening metal-cutting tools. (Materials and methods) End mills and drills were chosen as the object of research. The BIG-5 installation with the use of electrodes made of hard alloys VK8 and T15K6 was used to harden metal-cutting tools. It was pointed out that relatively mild electrical modes with pulse energy from 0.05 to 0.2 joules are used to harden drills and end mills, the thickness of the applied coating layer in such modes is 10-30 micrometers. (Results and discussion) It was noted that the performed analysis of the applied hardening methods confirmed the feasibility of using electric spark processing for these purposes. The optimal modes of electric spark processing were selected on the basis of previous studies. Comparative tests for wear resistance of samples from materials of end mills (P18) and drills (P6M5) were performed. It was shown that when using electrodes made of T15K6, the wear resistance of the samples increases by 1.85 times for P18 and by 8 times for P6M5. Comparative tests of hardened end mills and drills for wear resistance were carried out. The indicator was the number of processed parts. (Conclusions) The result of using the electric spark processing method to harden the cutting tool was an increase in the life of end mills by 3.8 times, drills by 2.25 times. The productivity of manufacturing parts has increased.

Dynamic Modelling and Optimal Sliding Mode Control of the Wearable Rehabilitative Bipedal Cable Robot with 7 Degrees of Freedom

Although robot-assisted physiotherapy has gained increasing attention in recent years, the use of wearable rehabilitation robots for lower limbs has shown reduced efficiency due to additional equipment and motors located at the center of the joint, increasing complexity and load on disabled patients. This paper proposes a novel rehabilitation approach by eliminating motors and equipment from the center of joints and placing them on a fixed platform using cable-based power transmission. A proposed model of a 14 cable-driven bipedal robot with 7 degrees of freedom has been used to model a lower limb rehabilitation robot corresponding to it. The dynamic equations of the robot are derived using the Euler-Lagrange method. The sliding mode control technique is utilized to offer accurate control for tracking desired trajectories, ensuring smoothness despite disturbances, and reducing tracking errors. This approach is employed to help prevent patients from falling and support them in maintaining balance during rehabilitative exercises. To ensure that cables exert positive tension, the sliding mode controller was combined with quadratic programming optimization, minimizing path error while constraining the controller input torque to be non-negative. The performance of the proposed controller was assessed by considering several control gains resulting in K = 10 identified as the most effective one. The feasibility of this approach to rehabilitation is demonstrated by the numerical results in MATLAB simulation, which show that the RMSE amount of the right and left hip and thigh angles are 0.29, 0.37, 0.31, and 0.44, respectively which verified an improved rehabilitation process. Also, the correlation coefficient between the Adams and MATLAB simulation results for motor torque was found to be 0.98, indicating a high degree of correlation between the two simulation results.

Multi-criteria decision-making for the selection of best airport ground access mode with a new fuzzy rough-entropy based method

In order to cope with the inherent complexities and uncertainties of settings such as transportation problems, the adoption of proper decision procedures becomes a pivotal issue. Particularly, multi-criteria group decision-making (MCGDM) uses multiple evaluations of the options based on several criteria to select the optimal choice and/or rank the alternatives. In this paper we are interested in the Entropy-REGIME method for MCGDM and its ability to handle uncertainty in the presence of fuzzy rough numbers (that allow the practitioner to represent and process imprecise data). To this end we propose a hybrid framework of the fuzzy rough-entropy based REGIME method that involves two main components: fuzzy rough-entropy for the evaluation of the objective weights of the decision criteria, and fuzzy rough-REGIME to rank the alternatives based on the weighted criteria. Its motivation is a case study that concerns the selection of the best transport mode to access Istanbul newly constructed airport. We consider four alternatives for ground access options, namely, underground metro, bus rapid transit, light rail transit, and premium bus services. Our findings show that an underground metro system is the optimal mode, followed by light rail transit, bus rapid transit, and premium bus services. Additionally, to demonstrate the superiority and effectiveness of the proposed technique, comparisons are made with existing methods.

System dynamics-multiple the objective optimization model for the coordinated development of urban economy-energy-carbon system

The deepening conflict between human societal progress and efforts to combat climate change necessitates immediate coordination among the Economy-Energy-Carbon (EEC) management. The study applies IPCC accounting methods to compute the historical carbon emissions in the Chengdu-Chongqing economic circle from 2005 to 2021. It assesses the developmental efficiency of various subsystems in the EEC system by employing the rank-sum ratio. Taking a typical city in the region (Chongqing) as a case study, this study integrates System Dynamics (SD) with NSGAIII to develop an EEC multi-objective optimization model. It utilizes the VIKOR model to select the optimal solution. Based on this, the analysis explores the coupled and coordinated state of the EEC system from 2022 to 2030 under the optimal solution mode. Research findings indicate that: (1) The overall carbon emissions exhibit a slight increase, where carbon sources surpass the carbon sink created by land use. (2) Compared to results from other preference-based scenarios, in the scenario where subsystem efficiencies are all optimal, the minimum cumulative carbon emissions amount to 1520.52 million tons, with the economy maintaining a favorable status. Moreover, the overall coupling coordination of the EEC is in a relatively favorable state, and it tends to improve annually. (3) To attain the coordinated development of the EEC system by 2030, the energy structure of the representative city must decrease coal consumption by 26.17%, maintain the construction land ratio below 3.7%, and guarantee forest coverage exceeds 57.77%. This study, utilizing complex system simulations and optimization analyses across various scenarios, offers pertinent recommendations for attaining urban low-carbon development while upholding societal advancement.

Research on performance seeking control of turbofan engine in minimum hot spot temperature mode

Abstract The uneven temperature distribution at the combustion chamber outlet seriously affects the working life of the engine. In order to reduce the heat spot temperature at the combustion chamber outlet, a performance optimization control method of the engine minimum heat spot temperature pattern is proposed. Firstly, based on CFD method, the temperature distribution characteristics of combustion chamber outlet under different working conditions were obtained, and a component-level model of turbofan engine was established to characterize the heat spot temperature at combustion chamber outlet. Secondly, the high precision and high real-time engine on-board model is established by deep neural network. Compared with the component-level model, the average relative error of each performance parameter is less than 0.3 %, and the real-time performance is improved by 12 times. Finally, based on the feasible sequential quadratic programming algorithm, the performance optimization control of the minimum hot spot temperature model in the typical flight envelope is simulated and verified. The simulation results show that under the condition of ensuring the safe and stable operation of the engine and constant thrust, the heat spot temperature at the combustion chamber outlet decreases by 21 K maximum. Compared with the conventional minimum turbine front temperature optimization mode, the minimum heat spot temperature mode significantly reduces the heat spot temperature at the combustion chamber outlet.

Exploiting exergy and exergoeconomic analysis as decisional tool for cogeneration plant optimal operating mode: A sugar factory case study

Due to the energy transition scenario, the efficient use of energy and operations flexibility to deal with the market volatility have become the major concerns of the industrial sector. In particular, in those contexts and countries where the grid supply cannot be continuously ensured, the selection of the best operation set up is of critical importance for both stability and profitability of the system. Based on the available data of the Wonji-Shoa sugar factory in Ethiopia, the digital twin of the related Combined Heat and Power generation plant was reproduced by means of ProSimPlus® process simulator. Thanks to the software dedicated tools, the exergy and exergoeconomic analysis were carried out to compare the performances of three possible functioning modes. The study revealed that the highest profitability for the power plant is achieved when it serves both the sugar factory and the electricity grid. With regard to the energy efficiency, the prevention of exergy losses up to 9.63 MW is possible and a 15% heat recovery potential could be viable by implementing a better integration between utility streams. Based on these results, the optimal combined scheduling of power plant and sugar factory will be the object of future studies.

Implementing operational strategy of closed-loop supply chain considering data intelligence level with an online platform

At present, the manufacturer collaborates on selling and recycling through an online platform. We explores the mode selection of closed-loop supply chain (CLSC) under the reselling or agency modes in forward SC and under the delegated-recycling mode or agency-recycling mode in reverse SC considering data intelligence level with an online platform. The results show that both the retail price of intelligent connected products (ICPs) and the demand of new ICPs are positively correlated with data intelligence level of new ICPs. The recycling price of old ICPs is negatively relevant to data intelligence level of old ICPs. However, the recycling quantity of old ICPs is positively related to data intelligence level of old ICPs. Increasing data intelligence level of new ICPs is benefit to enterprises. Moreover, it is very unconventional that the demand of new ICPs is increasing when the retail price of new ICPs increases. In addition, the manufacturer can choose the optimal selling mode and recycling mode by setting the selling commission rate and the recycling commission rate.

Strategic channel decisions for the supplier and specialized e‐retailer in the presence of a third‐party marketplace

AbstractWith the advancement of e‐commerce and the intensification of market competition, many suppliers have leveraged third‐party online marketplaces to expand their sales channels and bolster competitiveness. This poses potential threats to e‐retailers specializing in the core business of certain categories. This study examines a specialized e‐retailer's selling mode choice (reselling, in‐marketplace selling, or agency selling mode) and how this choice interacts with a supplier's channel strategy (marketplace, e‐retailer, or both/dual channels) in the presence of a third‐party marketplace. Our findings indicate that (1) the e‐retailer's optimal selling mode is contingent on the supplier's sales service quality and efficiency, and the e‐retailer's market occupation. Generally, when initially occupying a small market, the e‐retailer prefers selling in a third‐party marketplace, whereas when the initial market is relatively large, the e‐retailer is more inclined to opt for the reselling (agency selling) mode if the supplier's sales efficiency is low (high). Additionally, if the supplier's sales service quality is low, the e‐retailer will never choose the agency selling mode. (2) Exclusively introducing the marketplace channel is not the optimal choice for the supplier. Instead, adopting a dual channel is better when the direct selling cost is not too high. (3) Under certain scenarios, the supplier can manipulate the e‐retailer's channel by introducing the marketplace channel and offering a reference price without actually selling any products.