Qinyi Zhang, Wen Cao and Zhichao Zhang
With the rapid growth of the economy, people have increasingly higher living standards, and although people simply pursued material wealth in the past, they now pay more attention…
Abstract
Purpose
With the rapid growth of the economy, people have increasingly higher living standards, and although people simply pursued material wealth in the past, they now pay more attention to material quality and safety and environmental protection. This paper discusses the lack of motivation for investing in fresh-keeping technology for agricultural products by individual members of an agricultural supply chain composed of a supplier and a retailer by means of mathematical models and data simulations and discuss the optimal price-invest strategies under different sales models.
Design/methodology/approach
First, based on the model of no investment by both sides (NN), this paper considers three models: supplier only (MN), retailer only (NR) and cooperative investment (MR). Then, the authors analyze the influence of consumer price sensitivity and freshness sensitivity on the investment motivation of agricultural products under four models. Subsequently, the paper makes a sensitivity analysis of the optimal strategies under several models, and makes a game analysis of the suppliers and retailers of agricultural products. Finally, we conduct an empirical analysis through specific values.
Findings
The results show that (a) when the two sides cooperate, the amount of investment is largest, the freshness of the agricultural products is highest, and the sales volume is greatest; however, when both sides do not invest, the freshness of agricultural products and sales volume are lowest. (b) The price and freshness sensitivity of the consumer have an impact on investment decisions. Greater freshness sensitivity corresponds to a higher investment, higher agricultural product price, greater sales volume, and greater supply chain member income and overall income; however, greater price sensitivity corresponds to a lower investment, lower agricultural product price, lower sales volume, fewer supply chain members and lower overall income. (c) The investment game between the supplier and retailer is not only related to the sensitivity to price and freshness but also to the coordination coefficients of interest. At the same time, the market position of agricultural products should be considered when making decisions. The market share of agricultural products will affect the final game equilibrium and then affect the final benefit of the supply chain and individual members.
Practical implications
These results provide managerial insights for enterprises preparing to invest in agricultural products preservation technology.
Originality/value
At present, the main problem is that member enterprises of agricultural supply chains operate based on their own benefits and are resistant to investing alone to improve the freshness of agricultural products. Instead, they would prefer that other members invest so that they may reap the benefits at no cost. Therefore, the enterprises in each node of the agricultural product supply chain are not motivated enough to invest, and competition and game states are observed among them, and such behavior is definitely not conducive to improving the freshness of agricultural products. However, the current research on agricultural products is more about price, quality and greenness, etc., and there are few studies on agricultural investment. Through the establishment of the model, this paper is expected to provide theoretical suggestions for the supply chain enterprises that plan to invest in agricultural products preservation technology.
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Qinyi Zhang, Wen Cao, Yongmei Liu and Zhichao Zhang
As one of the omnichannel sales models, “buy online and pick up in store” (BOPS) not only is used in the commercial field but also has gradually attracted many scholars’…
Abstract
Purpose
As one of the omnichannel sales models, “buy online and pick up in store” (BOPS) not only is used in the commercial field but also has gradually attracted many scholars’ interests. However, although there are numerous research ideas, most of the current work is still limited to theoretical and empirical research, and few scholars study BOPS through models. This paper aims to discuss the best market conditions and opportunities for the implementation of BOPS against the backdrop of omnichannel by means of mathematical models and data simulations and discuss the optimal price–service strategies under different sales models.
Design/methodology/approach
First, from the perspective of different consumer shopping types, this paper separately divides consumers into different groups in traditional “dual channel” and BOPS models. Then, the authors analyze the impact of company market size, consumer service sensitivity and the scale of BOPS on companies’ strategies and the profit of the supply chain. Subsequently, they conduct an empirical analysis through specific values. Finally, the authors further expand the model on the basis of the original research, and discuss the retailer’s fairness concerns and unit compensation strategy to ensure that the research content is more rigorous.
Findings
It is observed that whether companies adopt BOPS depends on consumers’ service sensitivity degree and the scale of BOPS consumers and online retailers: when the sensitivity and the proportion of online consumers are high or the number of BOPS consumers is large, it is more advantageous for companies to implement BOPS. Moreover, companies should not only consider the market scale and production cost but also have a precise orientation of consumers’ experience sensitivity and willingness to engage in extra consumption when making price and service strategies. At the same time, the compensation strategy of companies and the peer-regarding fairness concern behavior of offline retailers will affect the optimal price and service strategy in the BOPS model.
Social implications
These results provide managerial insights for companies preparing to implement BOPS and promote the development of relevant theories in the channel field.
Originality/value
At present, most of the research on BOPS is based on empirical reviews. However, this paper analyzes the applicability and feasibility of implementing BOPS by using specific models, and it will provide some reference for companies preparing to implement BOPS. In addition, this paper also discusses the unit compensation strategy and peer-regarding fairness concern behavior in the BOPS model, which have not been studied by relevant scholars.
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Xiaogang Cao, Boning Xiao, Hui Wen and Mingzhe Fu
This paper explores how the existence of a second-hand market can affect remanufacturing decisions for durable goods in the presence of patent protection.
Abstract
Purpose
This paper explores how the existence of a second-hand market can affect remanufacturing decisions for durable goods in the presence of patent protection.
Design/methodology/approach
The authors construct a dynamic decision model between a durable goods original manufacturer and a durable goods remanufacturer considering the characteristics of the multi-cycle uses of new durable goods and remanufactured durable goods.
Findings
The results show that (1) the second-hand market compresses the cost space of a durable goods original manufacturer and a remanufacturer; (2) when the second-hand market exists, the optimal pricing of new durable goods is reduced, the optimal pricing of remanufactured durable goods is increased and the patent cost of each unit of durable goods increases and (3) the presence of the second-hand market will increase the original manufacturer's and remanufacturer's profits.
Originality/value
The research conclusion has certain reference value for the production strategy selection of each enterprise in the process of patented product remanufacturing and the government's fiscal policy formulation at each stage of the remanufacturing industry's development.
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Junjie Cao, Nannan Wang, Jie Zhang, Zhijie Wen, Bo Li and Xiuping Liu
– The purpose of this paper is to present a novel method for fabric defect detection.
Abstract
Purpose
The purpose of this paper is to present a novel method for fabric defect detection.
Design/methodology/approach
The method based on joint low-rank and spare matrix recovery, since patterned fabric is manufactured by a set of predefined symmetry rules, and it can be seen as the superposition of sparse defective regions and low-rank defect-free regions. A robust principal component analysis model with a noise term is designed to handle fabric images with diverse patterns robustly. The authors also estimate a defect prior and use it to guide the matrix recovery process for accurate extraction of various fabric defects.
Findings
Experiments on plain and twill, dot-, box- and star-patterned fabric images with various defects demonstrate that the method is more efficient and robust than previous methods.
Originality/value
The authors present a RPCA-based model for fabric defects detection, and show how to incorporate defect prior to improve the detection results. The authors also show that more robust detection and less running time can be obtained by introducing a noise term into the model.
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Zhenya Tang, Zhongyun Zhou, Feng Xu and Merrill Warkentin
The WeChat mini-program is a new channel for the delivery of online and mobile services, including electronic government services. Given the distinguishing characteristics and new…
Abstract
Purpose
The WeChat mini-program is a new channel for the delivery of online and mobile services, including electronic government services. Given the distinguishing characteristics and new business model of WeChat mini-programs, additional studies of mini-program-based government services are warranted. The purpose of this paper is to identify the factors that determine user adoption and usage of government WeChat mini-programs (GWMPs).
Design/methodology/approach
An empirical study was conducted through an online survey of Chinese GWMPs users. The proposed model was tested by analyzing the collected data using the covariance-based structural equation modeling approach.
Findings
The findings show that trust in government, trust in WeChat, trust in GWMPs and perceived convenience have significant effects on the usage of GWMPs.
Originality/value
This study contributes to the understanding of the GWMPs and mini-program-based government phenomenon. Theoretical implications for future e-government research as well as practical suggestions for GWMPs operators are also discussed.
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Yanchuang Cao, Junjie Rong, Lihua Wen and Jinyou Xiao
The purpose of this paper is to develop an easy-to-implement and accurate fast boundary element method (BEM) for solving large-scale elastodynamic problems in frequency and time…
Abstract
Purpose
The purpose of this paper is to develop an easy-to-implement and accurate fast boundary element method (BEM) for solving large-scale elastodynamic problems in frequency and time domains.
Design/methodology/approach
A newly developed kernel-independent fast multipole method (KIFMM) is applied to accelerating the evaluation of displacements, strains and stresses in frequency domain elastodynamic BEM analysis, in which the far-field interactions are evaluated efficiently utilizing equivalent densities and check potentials. Although there are six boundary integrals with unique kernel functions, by using the elastic theory, the authors managed to accelerate these six boundary integrals by KIFMM with the same kind of equivalent densities and check potentials. The boundary integral equations are discretized by Nyström method with curved quadratic elements. The method is further used to conduct the time-domain analysis by using the frequency-domain approach.
Findings
Numerical results show that by the fast BEM, high accuracy can be achieved and the computational complexity is brought down to linear. The performance of the present method is further demonstrated by large-scale simulations with more than two millions of unknowns in the frequency domain and one million of unknowns in the time domain. Besides, the method is applied to the topological derivatives for solving elastodynamic inverse problems.
Originality/value
An efficient KIFMM is implemented in the acceleration of the elastodynamic BEM. Combining with the Nyström discretization based on quadratic elements and the frequency-domain approach, an accurate and highly efficient fast BEM is achieved for large-scale elastodynamic frequency domain analysis and time-domain analysis.
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Chunlei Li, Chaodie Liu, Zhoufeng Liu, Ruimin Yang and Yun Huang
The purpose of this paper is to focus on the design of automated fabric defect detection based on cascaded low-rank decomposition and to maintain high quality control in textile…
Abstract
Purpose
The purpose of this paper is to focus on the design of automated fabric defect detection based on cascaded low-rank decomposition and to maintain high quality control in textile manufacturing.
Design/methodology/approach
This paper proposed a fabric defect detection algorithm based on cascaded low-rank decomposition. First, the constructed Gabor feature matrix is divided into a low-rank matrix and sparse matrix using low-rank decomposition technique, and the sparse matrix is used as priori matrix where higher values indicate a higher probability of abnormality. Second, we conducted the second low-rank decomposition for the constructed texton feature matrix under the guidance of the priori matrix. Finally, an improved adaptive threshold segmentation algorithm was adopted to segment the saliency map generated by the final sparse matrix to locate the defect regions.
Findings
The proposed method was evaluated on the public fabric image databases. By comparing with the ground-truth, the average detection rate of 98.26% was obtained and is superior to the state-of-the-art.
Originality/value
The cascaded low-rank decomposition was first proposed and applied into the fabric defect detection. The quantitative value shows the effectiveness of the detection method. Hence, the proposed method can be used for accurate defect detection and automated analysis system.
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Abstract
Purpose
This study aims to examine whether and when real-time updated online search engine data such as the daily Baidu Index can be useful for improving the accuracy of tourism demand nowcasting once monthly official statistical data, including historical visitor arrival data and macroeconomic variables, become available.
Design/methodology/approach
This study is the first attempt to use the LASSO-MIDAS model proposed by Marsilli (2014) to field of the tourism demand forecasting to deal with the inconsistency in the frequency of data and the curse problem caused by the high dimensionality of search engine data.
Findings
The empirical results in the context of visitor arrivals in Hong Kong show that the application of a combination of daily Baidu Index data and monthly official statistical data produces more accurate nowcasting results when MIDAS-type models are used. The effectiveness of the LASSO-MIDAS model for tourism demand nowcasting indicates that such penalty-based MIDAS model is a useful option when using high-dimensional mixed-frequency data.
Originality/value
This study represents the first attempt to progressively compare whether there are any differences between using daily search engine data, monthly official statistical data and a combination of the aforementioned two types of data with different frequencies to nowcast tourism demand. This study also contributes to the tourism forecasting literature by presenting the first attempt to evaluate the applicability and effectiveness of the LASSO-MIDAS model in tourism demand nowcasting.
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Zhijie Wen, Qikun Zhao and Lining Tong
The purpose of this paper is to present a novel method for minor fabric defects detection.
Abstract
Purpose
The purpose of this paper is to present a novel method for minor fabric defects detection.
Design/methodology/approach
This paper proposes a PETM-CNN algorithm. PETM-CNN is designed based on self-similar estimation algorithm and Convolutional Neural Network. The PE (Patches Extractor) algorithm extracts patches that are possible to be defective patches to preprocess the fabric image. Then a TM-CNN (Triplet Metric CNN) method is designed to predict labels of the patches and the final label of the image. The TM-CNN can perform better than normal CNN.
Findings
This algorithm is superior to other algorithms on the data set of fabric images with minor defects. The proposed method achieves accurate classification of fabric images whether it has minor defects or not. The experimental results show that the approach is effective.
Originality/value
Traditional fabric defects detection is not effective as minor defects detection, so this paper develops a method of minor fabric images classification based on self-similar estimation and CNN. This paper offers the first investigation of minor fabric defects.
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Xiu Jin, Jinming Yu, Yueli Liu and Na Chen
Previous research has predominantly concentrated on examining risk spillovers through single-layer networks, neglecting the multi-related and multilayer network characteristics of…
Abstract
Purpose
Previous research has predominantly concentrated on examining risk spillovers through single-layer networks, neglecting the multi-related and multilayer network characteristics of the economic system. This study constructs multilayer connectedness networks, including return, volatility and extreme risk layers, to systematically analyze the risk spillovers across Chinese industries at the system and industry levels.
Design/methodology/approach
Previous studies have constructed multilayer networks using Diebold and Yilmaz’s (2012) approach or the time-varying parameter vector autoregressive (TVP-VAR) connectedness model. In this study, we employ the TVP-VAR-extended joint connectedness approach, which improves these methods and captures risk spillovers more accurately.
Findings
At the system level, the risk spillover across industries exhibits distinct network structures and dynamic evolution behaviors across different layers. During extreme events, the intensity, scope and speed of risk spillovers increase markedly across all layers, with volatility and extreme risk layers demonstrating greater sensitivity to crises. At the industry level, industrial and optional consumption typically serve as risk transmitters, while medicine and health, as well as financial real estate, tend to be risk receivers across three layers. Moreover, industrial, optional consumption and materials exhibit significant systemic importance.
Originality/value
To the best of our knowledge, this is the first study to apply multilayer networks with return, volatility and extreme risk layers to systematically examine risk spillovers between Chinese industries.