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By studying the competition between a B2C platform and a third-party seller, the purpose of this paper is to analyze and compare their optimal decisions and profits between cases with and without sales effort of the platform or third-party seller.

This paper studies the competition between a B2C platform and a third-party seller. The platform sells a product directly, and allows the third-party seller to sell a competing product on the platform. Based on whether the platform or the third-party seller makes sales effort, there are four scenarios. The paper analyzes the optimal decisions and profits of platform and third-party seller under each scenario, respectively.

The transaction fee has a negative effect on third-party seller’s sales effort level. What is more, the platform can take a free riding from the third-party seller’s sales effort, but the platform’s sales effort has a negative effect on the profit of third-party seller.

These results provide managerial insights for the platform and the third-party seller to make decisions.

This paper is among the first papers to study the competition between B2C platform and third-party seller.

This paper aims to study whether the recycling of a third party competes with the trade-in service of a manufacturer, and explores the optimal trade-in and third-party collection authorization strategies for the manufacturer.

According to whether to authorize a third party to collect its used products, the manufacturer has two choices: one is not authorization (NA); the other is authorization (A). This paper uses profit-maximization model to investigate the optimal decisions of the manufacturer and the third party under NA and A, respectively, and then explores which choice is better for the manufacturer.

It is observed that there is a competition between trade-in service and third-party recycling when the durability parameter of the used product is relatively small. Moreover, when the durability parameter of the used product is relatively large, A is always better choice for the manufacturer; otherwise, NA is a better choice except for the case that the unit trade-in subsidy is low and the salvage of the used product is high.

These results provide managerial insights for the manufacturer and the third party to make decisions in the field of recycling.

This paper is among the first papers to study the competition between trade-in program and third party’s collecting program under government’s trade-in subsidy policy. Moreover, this paper presents the conditions under which the manufacturer should authorize or not authorize the third party to collect its used products.

Experts may adjust their assessments through communication and mutual influence, and this dynamic evolution relies on the spread of internal trust relationships. Due to differences in educational backgrounds and knowledge experiences, trust relationships among experts are often incomplete. To address such issues and reduce decision biases, this paper proposes a probabilistic linguistic multi-attribute group decision consensus model based on an incomplete social trust network (InSTN).

In this paper, we first define the new trust propagation operators based on the operations of Probability Language Term Set (PLTS) with algebraic t-conorm and t-norm, which are combined with trust aggregation operators to estimate InSTN. The adjustment coefficients are then determined through trust relations to quantify their impact on expert evaluation. Finally, the particle swarm algorithm (PSO) is used to optimize the expert evaluation to meet the consensus threshold.

This study demonstrates the feasibility of the method through the selection of treatment plans for complex cases. The proposed consensus model exhibits greater robustness and effectiveness compared to traditional methods, mainly due to the effective regulation of trust relations in the decision-making process, which reduces decision bias and inconsistencies.

This paper introduces a novel probabilistic linguistic multi-attribute swarm decision consensus model based on an InSTN. It proposes a redefined trust propagation and aggregation approach to estimate the InSTN. Moreover, the computational efficiency and decision consensus accuracy of the proposed model are enhanced by using PSO optimization.

Examines the fifteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.