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Wireless network localization technology is very popular in recent years and has attracted worldwide attention. The purpose of this paper is to improve the localization accuracy of ultra-wideband (UWB) with lower localization error taking into consideration the special real environment with the closed long and narrow space.

The principle of multidimensional scaling (MDS), particle swarm optimization (PSO) and Taylor series expansion algorithm (Taylor-D) were introduced. A novel positioning algorithm, MDS-PSO-Taylor was proposed to minimize the localization error. MDS-PSO algorithm provided a more accurate preliminary coordinate by applying the PSO algorithm so that the Taylor-D was used for further enhancing the localization accuracy.

Experimental results manifested that the proposed algorithm, providing small localization error value and higher positioning accuracy, can effectively reduce errors and achieve better performance in terms of the considerable improvement of localization accuracy.

The presented study with the real environment test attempts to demonstrate the proposed algorithm is hopeful to be applied to the underground environment for in the future.

The purpose of this paper is to investigate the effect of hexagonal boron nitride (h-BN) and poly (phenyl p-hydroxybenzoate) (PHBA) on improving the torsional tribological behavior of polytetrafluoroethylene (PTFE).

This paper investigates the torsional tribological behavior of PTFE composites filled with h-BN and PHBA under different angular displacements with a plane-on-plane torsional friction tester. The worn surface of PTFE composites was investigated by using a scanning electron microscope.

The shape of T–Θ curves of PTFE composites was influenced by both content fillers and torsional angule. The material with a higher coefficient of sliding friction exhibited the larger torsional angle under which the torsional regime transited from a partial slip to a gross slip. PTFE composites filled with 20 weight per cent PHBA and 10 weight per cent h-BN showed the best anti-wear properties. The specific wear rate of composites exhibits a negative correlation with material hardness. The wear volume loss presents a positive correlation with friction dissipation energy. The specific wear rate of all composites decreased with increasing torsional angle. The dominant wear mechanism of pure PTFE was adhesive wear. The slight plastic flow and plowing occurred on the worn surfaces of PTFE composites because of the higher hardness of composites and the lubrication of h-BN particles with layer crystal structure.

This paper put forward a kind of PTFE composite with low torsional wear rate, which can be used in the sliding slewing bearing or the center plate of a bogie.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

The purpose of this study is to examine how use of agriculture information systems could impact farmers' intention to convert from traditional to organic agriculture production in the mountainous areas of Northern Vietnam, based on a research framework developed from integrating Diffusion of Innovation Theory and Theory of Planned Behavior. Specifically, the authors aim to test the direct impact of use of agriculture information systems on converting intention and the interaction between use of agriculture information systems and perceived economic benefits, perceived non-economic benefits of organic production and market access on the formation of converting intention.

Data were collected from a sample survey that included 634 agriculture-producing households in Thai Nguyen, Tuyen Quang and Cao Bang provinces of Northern Vietnam. The logistic regression was used for data analysis.

Research findings indicate that perceived economic benefits, non-economic benefits, market access and use of agriculture information systems positively support the converting intention. Moreover, the use of information systems strengthens the links between the converting intention and perceived economic benefits, perceived non-economic benefits and market access.

This research is innovative in incorporating the use of agriculture information systems as both direct contributor and moderator in converting decisions.

With the rapid development of the sharing economy in manufacturing industries, manufacturers and the equipment suppliers frequently share capacity through the third-party platform. This paper aims to study influences of manufacturers sharing capacity on the supplier and to analyze whether the supplier shares capacity as well as its influences.

This paper deals with conditions that the supplier and manufacturers share capacity through the third-party platform, and the third-party platform competes with the supplier in equipment sales. Considering the heterogeneity of the manufacturer's earning of unit capacity usage and the production efficiency of manufacturer's usage strategies, this paper constructs capacity sharing game models. Then, model equilibrium results under different sharing scenarios are compared.

The results show that when the production or maintenance cost is high, manufacturers sharing capacity simultaneously benefits the supplier, the third-party platform and manufacturers with high earnings of unit capacity usage. When both the rental efficiency and the production cost are low, or both the rental efficiency and the production cost are high, the supplier simultaneously sells equipment and shares capacity. The supplier only sells equipment in other cases. When both the rental efficiency and the production cost are low, the supplier’s sharing capacity realizes the win-win-win situation for the supplier, the third-party platform and manufacturers with moderate earnings of unit capacity usage.

This paper innovatively examines supplier's selling and sharing decisions considering manufacturers sharing capacity. It extends the research on capacity sharing and is important to supplier's operational decisions.

This paper investigates the dynamic pricing strategy of a firm for the successive-generation products under the conditions of the limited trade-in duration and strategic customers. Further, it explores the effect of a limited trade-in duration on the choice of the myopic and strategic customers, besides the optimal dynamic pricing and trade-in strategy of the firm.

Based on the choice behavior of the myopic and strategic customers, the authors have developed a two-period game-theoretic analytical model to decide the optimal retail prices of the successive-generation products and the optimal trade-in rebate when the firm adopts a dynamic pricing strategy and then investigate three extensions of the basic model to discuss the change in the results owing to the relaxation of certain conditions.

The authors find from the results that, in terms of profit maximization, it is better to extend the limited trade-in duration, and hence, the firm should implement a dynamic pricing strategy. However, in the situation of using a static pricing strategy, the firm should extend the limited trade-in duration only if the incremental value of the new generation products is below a certain threshold. Moreover, the firm should use a dual rollover strategy instead of a single rollover one. If all customers in the market are myopic, then the firm should also extend the limited trade-in duration.

This study mainly discusses the impact of limited trade-in duration on the firm's dynamic pricing strategy when facing strategic customers, which provides several directions for future research. First, if the government offers subsidies to consumers, how will strategic consumers make purchase decisions? How would the enterprise make its pricing decision? Second, when asymmetric information exists between consumers and firms, how will it affect consumers' choice behavior and firms' pricing decisions? All these issues are worth exploring in the future.

These results offer certain managerial insights for the firm in the decision making on pricing within the trade-in program.

This is the first work to study the dynamic pricing strategy of the firm for the successive-generation products under the conditions of the limited trade-in duration and strategic customers. Further, this work discusses the changes in results owing to the relaxation of certain conditions.

The management issues of this article, and the author is attempting to address these issues, are as follows: What is the optimal decision of each entity in the closed-loop supply chain for the cascading utilization of power batteries under three government measures: no subsidies, subsidies and rewards and punishments? How do different measures affect the process of cascading the utilization of power batteries? Which measures will help incentivize cascading utilization and battery recycling efforts?

The paper uses game analysis methods to study the optimal decisions of various stakeholders in the supply chain under the conditions of subsidies, non-subsidies and reward and punishment policies. The impact of various parameters on the returns of game entities is tested through Matlab numerical simulation.

The analysis discovered that each party in the supply chain will see an increase in earnings if the government boosts trade-in subsidies, which means that the degree of recycling efforts of each entity will also increase; under the condition with subsidies, the recycling efforts and echelon utilization rates of each stakeholder are higher than those under the incentive and punishment measure. In terms of the power battery echelon’s closed-loop supply chain incentive, the subsidy policy exceeds the reward and punishment policy.

The article takes the perspective of differential games and considers the dynamic process of exchanging old for new, providing important value for the practice of using old for new behavior in the closed-loop supply chain of power battery cascading utilization.

This paper aims to develop an optimal buyback promotion strategy for enterprises, including multibuyback strategy and self-buyback strategy, taking both the consumer's multichannel psychological acquisition attributes and remaining market into account.

Based on the game theory and Hotelling model, the authors formulate a new model to study the equilibrium of different buyback models, given the utility maximization of the consumers, the profit maximization and the constraint on nondecreasing market share of the enterprises, and the authors conduct comparative analysis.

Intuitively, enterprises buying back products of other brands would appeal to some consumers. However, the authors find that after implementing the multibuyback scheme, enterprises may not be able to seize competitors' markets or even lose their original customer base in the context considered in this article counterintuitive. In addition, the size of remaining market share and the consumer's multichannel psychological acquisition affect the choice of buyback promotion strategies. Moreover, after implementing multibuyback scheme, customers with old products subsidize those who receive additional discounts. Finally, the authors point out that the buyback strategy choices of companies with different goal-oriented are diverse.

This study has a very solid realistic background and provides guidance for enterprises to implement buyback promotion strategies. In addition, the authors unearth new influencing factors to provide a reasonable explanation for different buyback strategies in reality.

To the best of the authors’ knowledge, this study is one of the first to explore the multibuyback promotion strategy as a new buyback method, where the two influencing factors the authors have not been proposed so far.

The confirmation of receipt of orders by consumers means that the online retailer actually receives the payments on many retail platforms (e.g. Taobao). In order to recoup funds as soon as possible, the retailer will take steps (e.g. improving the level of delivery and adopting a rebate policy) to encourage consumers to confirm receipt earlier. It is significant for the retailer to identify an appropriate strategy and determine the optimal product price. To address the above issues, this paper examines and compares the pricing strategies and profits under different strategies to show some managerial insights for the retailer's decision-making.

In this paper, the authors discuss four models, i.e. adopting common delivery and offering consumers no rebates, adopting common delivery and offering rebates, adopting fast delivery and offering no rebates and adopting fast delivery and offering rebates, which the retailer may consider. Under different models, consumer utility and firm's profit structure are disparate. After comparing the retailer's profits under four models, the optimal strategy, profit and product price are obtained.

Some interesting results are as follows. When the cost of fast delivery is not very high, improving the level of delivery would bring more profit to the retailer and create a positive impact on consumers. Interestingly, our results also show that offering proper rebates to stimulate consumers to confirm receipt early only serves to improve the profit only when the motivation of consumers to confirm the receipt is very low. Moreover, the authors find that a higher level of delivery services can promote the implementation of the rebate policy to improve the retailer's earnings.

This paper is the first study on the transaction mode of retail platforms and the problem of confirming receipt by a model-based method.

Environmental crises and resource shortage have been matters of concern worldwide particularly, as the beginning of the twenty-first century. Remanufacturing can be one of the best approaches to promoting the development of circular economy and realizing the efficient use of resources. However, research studies indicate that the general public still remains unaware of the merits of remanufactured products. Hence, investigating main motivations of consumers to purchase remanufactured products is certainly worth exploring. The purpose of this paper is to find out consumers’ key motivations to purchase remanufactured products. A new multi-attributes decision-making method based on prospect theory (PT) is conducted.

Firstly, according to the prior literature, 12 main factors that influence consumers to purchase a remanufactured product are selected. Then, the single valued triangular neutrosophic numbers and triangular neutrosophic weighted geometric averaging operator are applied to rank them. Secondly, a multi-attribute decision-making method with PT is used to evaluate the utilities of new and remanufactured products, respectively. Based on the utilities, consumers’ preferred choice between the new and remanufactured products can be elicited.

The proposed method has been applied to a real survey. The results demonstrate that the proposed method is not only capable of recognizing the consumers’ key motivations for purchasing a remanufactured product but also able to deal with the ranking of the new and remanufactured products.

The contributions of this paper are threefold. Firstly, this paper attempts to explore the main motivations that encourage consumers to purchase a remanufactured product, instead of a new one. Secondly, the proposed method is established based on PT, taking consumers’ psychological behavior into consideration, which can obtain a relatively reasonable result. Thirdly, it can enrich the remanufacturing literature, serving as a guideline for consumers when purchasing a remanufactured product. In addition, this paper can help the remanufacturers make pricing and production decisions where necessary.