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Article
Publication date: 11 July 2008

Ning Cao, Zhiming Zhang, Kin Man To and Keng Po Ng

The purpose of this paper is to reveal the empirical issues of the implementation of coordination for textile‐apparel supply chains.

6253

Abstract

Purpose

The purpose of this paper is to reveal the empirical issues of the implementation of coordination for textile‐apparel supply chains.

Design/methodology/approach

Employing case study, the paper examines three different types of coordination practice in three different structures of textile‐apparel supply chains: vertical integration chain, efficiency oriented chain and 3P‐hub chain. The coordinators are three leading Hong Kong based international textiles and apparel companies in these cases. The case sources are published articles, company web sites and some open seminars offered by the case companies.

Findings

In textile and apparel industries, brand owners generally coordinate the supply chain. There are also other coordination practices in industries. Through the research observations and analyses in the cases it is found that the integrated company, powerful garment manufacturer and trade agent play the role of coordinators in vertical integration chain, efficiency oriented chain and 3P‐hub chain, respectively. No matter what type of coordination practice, information sharing and product flow coordination should be comprehensive. Coordinators are the information centers of the whole supply chain. They should have power to manage the supply chain. They should actively integrate the whole chain for maximum total profitability.

Research limitations/implications

This paper is just an overview of coordination practice in textile‐apparel supply chains. The case sources are published articles, company web sites and some open seminars made by the case companies. The methodology should be more systematic.

Originality/value

Coordination in textile‐apparel supply chains is still an unresolved question both from the theoretic and practical points of view. This paper fills in some of the gaps.

Details

Journal of Fashion Marketing and Management: An International Journal, vol. 12 no. 3
Type: Research Article
ISSN: 1361-2026

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Article
Publication date: 9 November 2021

Shilpa B L and Shambhavi B R

Stock market forecasters are focusing to create a positive approach for predicting the stock price. The fundamental principle of an effective stock market prediction is not only…

916

Abstract

Purpose

Stock market forecasters are focusing to create a positive approach for predicting the stock price. The fundamental principle of an effective stock market prediction is not only to produce the maximum outcomes but also to reduce the unreliable stock price estimate. In the stock market, sentiment analysis enables people for making educated decisions regarding the investment in a business. Moreover, the stock analysis identifies the business of an organization or a company. In fact, the prediction of stock prices is more complex due to high volatile nature that varies a large range of investor sentiment, economic and political factors, changes in leadership and other factors. This prediction often becomes ineffective, while considering only the historical data or textural information. Attempts are made to make the prediction more precise with the news sentiment along with the stock price information.

Design/methodology/approach

This paper introduces a prediction framework via sentiment analysis. Thereby, the stock data and news sentiment data are also considered. From the stock data, technical indicator-based features like moving average convergence divergence (MACD), relative strength index (RSI) and moving average (MA) are extracted. At the same time, the news data are processed to determine the sentiments by certain processes like (1) pre-processing, where keyword extraction and sentiment categorization process takes place; (2) keyword extraction, where WordNet and sentiment categorization process is done; (3) feature extraction, where Proposed holoentropy based features is extracted. (4) Classification, deep neural network is used that returns the sentiment output. To make the system more accurate on predicting the sentiment, the training of NN is carried out by self-improved whale optimization algorithm (SIWOA). Finally, optimized deep belief network (DBN) is used to predict the stock that considers the features of stock data and sentiment results from news data. Here, the weights of DBN are tuned by the new SIWOA.

Findings

The performance of the adopted scheme is computed over the existing models in terms of certain measures. The stock dataset includes two companies such as Reliance Communications and Relaxo Footwear. In addition, each company consists of three datasets (a) in daily option, set start day 1-1-2019 and end day 1-12-2020, (b) in monthly option, set start Jan 2000 and end Dec 2020 and (c) in yearly option, set year 2000. Moreover, the adopted NN + DBN + SIWOA model was computed over the traditional classifiers like LSTM, NN + RF, NN + MLP and NN + SVM; also, it was compared over the existing optimization algorithms like NN + DBN + MFO, NN + DBN + CSA, NN + DBN + WOA and NN + DBN + PSO, correspondingly. Further, the performance was calculated based on the learning percentage that ranges from 60, 70, 80 and 90 in terms of certain measures like MAE, MSE and RMSE for six datasets. On observing the graph, the MAE of the adopted NN + DBN + SIWOA model was 91.67, 80, 91.11 and 93.33% superior to the existing classifiers like LSTM, NN + RF, NN + MLP and NN + SVM, respectively for dataset 1. The proposed NN + DBN + SIWOA method holds minimum MAE value of (∼0.21) at learning percentage 80 for dataset 1; whereas, the traditional models holds the value for NN + DBN + CSA (∼1.20), NN + DBN + MFO (∼1.21), NN + DBN + PSO (∼0.23) and NN + DBN + WOA (∼0.25), respectively. From the table, it was clear that the RMSRE of the proposed NN + DBN + SIWOA model was 3.14, 1.08, 1.38 and 15.28% better than the existing classifiers like LSTM, NN + RF, NN + MLP and NN + SVM, respectively, for dataset 6. In addition, he MSE of the adopted NN + DBN + SIWOA method attain lower values (∼54944.41) for dataset 2 than other existing schemes like NN + DBN + CSA(∼9.43), NN + DBN + MFO (∼56728.68), NN + DBN + PSO (∼2.95) and NN + DBN + WOA (∼56767.88), respectively.

Originality/value

This paper has introduced a prediction framework via sentiment analysis. Thereby, along with the stock data and news sentiment data were also considered. From the stock data, technical indicator based features like MACD, RSI and MA are extracted. Therefore, the proposed work was said to be much appropriate for stock market prediction.

Details

Kybernetes, vol. 52 no. 3
Type: Research Article
ISSN: 0368-492X

Keywords

Available. Content available
Article
Publication date: 9 May 2008

62

Abstract

Details

Journal of Fashion Marketing and Management: An International Journal, vol. 12 no. 2
Type: Research Article
ISSN: 1361-2026

Available. Open Access. Open Access
Article
Publication date: 1 April 2019

Peide Liu, Xiaoxiao Liu and Hongyu Yang

Accurately judging the quality of marine economic development is the premise of grasping the level and status of marine economic development. In order to scientifically evaluate…

775

Abstract

Purpose

Accurately judging the quality of marine economic development is the premise of grasping the level and status of marine economic development. In order to scientifically evaluate the development quality of regional marine economy, the purpose of this paper is to select the marine area of Qingdao as the research object, and construct a marine economic development quality evaluation index system with 16 indicators.

Design/methodology/approach

The raw data is normalized by the range conversion method, and the weight of the index is determined by the information entropy model. Further, the grey relational analysis (GRA) method is used to evaluate the quality of marine economic development of Qingdao from 2012 to 2017.

Findings

The results show that the marine economic development capacity of Qingdao is with the generally increasing trend, the total marine economy is with on the rising trend, the marine storage and transportation capacity, and marine ecological environment are first decreased, and then increased. The utilization of marine resources is generally decreasing, and the comprehensive management of oceans varies with the changes of environment and economy. Therefore, in view of the development capacity of marine economy, the coordinated development of economy and environment should be carried out.

Originality/value

This paper uses the GRA to evaluate the quality of marine economic development and provides a reference for the development of marine economy in Qingdao.

Details

Marine Economics and Management, vol. 2 no. 1
Type: Research Article
ISSN: 2516-158X

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Article
Publication date: 9 July 2024

Yidong Zhang

The purpose of this study is to adjust the electronic transport performance of zinc oxide–silicon dioxide (ZnO-SiO2) film by the construction of a grain boundary barrier.

33

Abstract

Purpose

The purpose of this study is to adjust the electronic transport performance of zinc oxide–silicon dioxide (ZnO-SiO2) film by the construction of a grain boundary barrier.

Design/methodology/approach

ZnO-SiO2 thin films were prepared on glass substrates by a simple sol-gel method. The crystal structure of ZnO and ZnO-SiO2 powders were tested by X-ray diffraction with copper (Cu) Kα radiation. The absorption spectra of ZnO and ZnO-SiO2 films were recorded by a ultraviolet-visible spectrophotometer. The micro electrical transport performance of ZnO-SiO2 thin films were investigated by conductive atomic force microscope and electrostatic force microscope.

Findings

The results show that the current of ZnO-SiO2 film decrease, indicating that the mobility of ZnO-SiO2 film is greatly decreased, owing to the formation of the grain boundary barrier between ZnO and SiO2. The phase variation of ZnO-SiO2 film increases due to the electron accumulation at grain boundaries.

Originality/value

ZnO and ZnO-5SiO2 thin films prepared on glass substrates by a simple sol-gel method were first studied by CAFM and EFM. The band gaps of ZnO and ZnO-5SiO2 is ∼3.05 eV and 3.15 eV, respectively. The barrier height of ZnO-5SiO2 film increased by ∼0.015 eV after introducing SiO2. The phase variation intensity increased to a certain extent after doping SiO2, due to the increased GB barrier. ZnO-5SiO2 film will be a promising ETL candidate in the application of QLEDs field.

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Article
Publication date: 25 June 2024

Ranran Yang, Zhaojun Liu, Jingjing Li and Jianling Jiao

Waste classification plays an important role in reducing pollution, promoting waste recycling and resource utilization. This paper aims to explore the multiple reasons that affect…

90

Abstract

Purpose

Waste classification plays an important role in reducing pollution, promoting waste recycling and resource utilization. This paper aims to explore the multiple reasons that affect the performance of waste classification governance.

Design/methodology/approach

Content analysis of the existing waste classification policies is conducted using the Latent Dirichlet Allocation (LDA) model. Based on this analysis, influencing factors are identified through the technology-organization-environment (TOE) research framework. The condition configurations and action paths that cause differences in governance performance are derived using the fuzzy-set qualitative comparative analysis method (fsQCA).

Findings

The results show that there are spatial and temporal disparities in waste classification policies among different provinces/cities. In most situations, the implementation effect of policy combinations is better than that of a single type of policy, with mandatory policies playing a key role. Additionally, a single influencing factor cannot constitute the bottleneck of high governance performance. Policy topics coordinate with environmental and technical factors to influence governance performance. Finally, in light of China's actual governance situation, several targeted implications are proposed for the practical optimization of local government waste classification governance.

Originality/value

This paper presents a novel approach by integrating multiple heterogeneous data sources from both online and offline channels, adopting a public-government perspective and applying the fsQCA method to investigate the combined effects of technical, organizational and environmental factors on waste classification governance performance across 31 provinces and cities in China.

Details

Management of Environmental Quality: An International Journal, vol. 35 no. 7
Type: Research Article
ISSN: 1477-7835

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Article
Publication date: 6 July 2023

Mengda Xing, Weilong Ding, Tianpu Zhang and Han Li

Remaining useful life (RUL) prediction for power transformer maintenance is a challenging task on heterogeneous data. Monitoring data of power transformers are not always…

249

Abstract

Purpose

Remaining useful life (RUL) prediction for power transformer maintenance is a challenging task on heterogeneous data. Monitoring data of power transformers are not always compatible or in an identical format; therefore, RUL predictions traditionally work separately on different data. Moreover, chemical molecules used in RUL prediction can be transformed into each other under different conditions, thus forming a complete graph with uncertain adjacency matrix (UAM). This study aims to find and evaluate a new model to achieve better results of RUL prediction than the other baselines.

Design/methodology/approach

In this work, the authors propose a spatiotemporal complete graph convolutional network (STCGCN) for RUL prediction in two branches, in which daily and hourly features are extracted from correlated heterogeneous data separately. This study provides a thorough evaluation of the proposed model on real-world data and compare the proposed model with state-of-the-art RUL prediction models.

Findings

By using the multibranch structure and EucCos similarity aggregation, STCGCN was able to capture the dynamic spatiotemporal patterns on a variety of heterogeneous data and obtain more accurate prediction results, compared to other time series prediction methods.

Originality/value

In this work, the authors propose a novel multibranch structure to compute feature maps from two heterogeneous data sources efficiently and a novel similarity aggregation method to compute the spatial UAM within the complete graph. Compared with traditional time series prediction models, the model pays attention to the spatial relationships in time series data.

Details

International Journal of Web Information Systems, vol. 19 no. 2
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 6 July 2020

Pooja Arora and Anurag Dixit

The advancements in the cloud computing has gained the attention of several researchers to provide on-demand network access to users with shared resources. Cloud computing is…

90

Abstract

Purpose

The advancements in the cloud computing has gained the attention of several researchers to provide on-demand network access to users with shared resources. Cloud computing is important a research direction that can provide platforms and softwares to clients using internet. However, handling huge number of tasks in cloud infrastructure is a complicated task. Thus, it needs a load balancing (LB) method for allocating tasks to virtual machines (VMs) without influencing system performance. This paper aims to develop a technique for LB in cloud using optimization algorithms.

Design/methodology/approach

This paper proposes a hybrid optimization technique, named elephant herding-based grey wolf optimizer (EHGWO), in the cloud computing model for LB by determining the optimal VMs for executing the reallocated tasks. The proposed EHGWO is derived by incorporating elephant herding optimization (EHO) in grey wolf optimizer (GWO) such that the tasks are allocated to the VM by eliminating the tasks from overloaded VM by maintaining the system performance. Here, the load of physical machine (PM), capacity and load of VM is computed for deciding whether the LB has to be done or not. Moreover, two pick factors, namely, task pick factor (TPF) and VM pick factor (VPF), are considered for choosing the tasks for reallocating them from overloaded VM to underloaded VM. The proposed EHGWO decides the task to be allocated in the VM based on the newly derived fitness functions.

Findings

The minimum load and makespan obtained in the existing methods, constraint measure based LB (CMLB), fractional dragonfly based LB algorithm (FDLA), EHO, GWO and proposed EHGWO for the maximum number of VMs is illustrated. The proposed EHGWO attained minimum makespan with value 814,264 ns and minimum load with value 0.0221, respectively. Meanwhile, the makespan values attained by existing CMLB, FDLA, EHO, GWO, are 318,6896 ns, 230,9140 ns, 1,804,851 ns and 1,073,863 ns, respectively. The minimum load values computed by existing methods, CMLB, FDLA, EHO, GWO, are 0.0587, 0.026, 0.0248 and 0.0234. On the other hand, the proposed EHGWO with minimum load value is 0.0221. Hence, the proposed EHGWO attains maximum performance as compared to the existing technique.

Originality/value

This paper illustrates the proposed LB algorithm using EHGWO in a cloud computing model using two pitch factors, named TPF and VPF. For initiating LB, the tasks assigned to the overloaded VM are reallocated to under loaded VMs. Here, the proposed LB algorithm adapts capacity and loads for the reallocation. Based on TPF and VPF, the tasks are reallocated from VMs using the proposed EHGWO. The proposed EHGWO is developed by integrating EHO and GWO algorithm using a new fitness function formulated by load of VM, migration cost, load of VM, capacity of VM and makespan. The proposed EHGWO is analyzed based on load and makespan.

Details

International Journal of Pervasive Computing and Communications, vol. 16 no. 3
Type: Research Article
ISSN: 1742-7371

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Article
Publication date: 28 December 2023

Ankang Ji, Xiaolong Xue, Limao Zhang, Xiaowei Luo and Qingpeng Man

Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack…

247

Abstract

Purpose

Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack contributes to establishing an appropriate road maintenance and repair strategy from the promptly informed managers but still remaining a significant challenge. This research seeks to propose practical solutions for targeting the automatic crack detection from images with efficient productivity and cost-effectiveness, thereby improving the pavement performance.

Design/methodology/approach

This research applies a novel deep learning method named TransUnet for crack detection, which is structured based on Transformer, combined with convolutional neural networks as encoder by leveraging a global self-attention mechanism to better extract features for enhancing automatic identification. Afterward, the detected cracks are used to quantify morphological features from five indicators, such as length, mean width, maximum width, area and ratio. Those analyses can provide valuable information for engineers to assess the pavement condition with efficient productivity.

Findings

In the training process, the TransUnet is fed by a crack dataset generated by the data augmentation with a resolution of 224 × 224 pixels. Subsequently, a test set containing 80 new images is used for crack detection task based on the best selected TransUnet with a learning rate of 0.01 and a batch size of 1, achieving an accuracy of 0.8927, a precision of 0.8813, a recall of 0.8904, an F1-measure and dice of 0.8813, and a Mean Intersection over Union of 0.8082, respectively. Comparisons with several state-of-the-art methods indicate that the developed approach in this research outperforms with greater efficiency and higher reliability.

Originality/value

The developed approach combines TransUnet with an integrated quantification algorithm for crack detection and quantification, performing excellently in terms of comparisons and evaluation metrics, which can provide solutions with potentially serving as the basis for an automated, cost-effective pavement condition assessment scheme.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 10 July 2023

Ning Li, Chao Hu and Li Zhang

According to governance theory, choosing an effective supply chain (SC) governance mechanism can balance the interests and conflicts between enterprises and help them achieve…

422

Abstract

Purpose

According to governance theory, choosing an effective supply chain (SC) governance mechanism can balance the interests and conflicts between enterprises and help them achieve their performance goals. However, incentive and relational governance have not been fully studied in improving enterprise cooperative performance (ECP). This study aims to examine the relationship between incentive and relational governance in general, the direct effects of combined governance strategy (CGS; the combination dimension of the above two governance mechanisms) on ECP and the mediating effects of SC ambidexterity on CGS and ECP in particular.

Design/methodology/approach

To test the hypotheses, this study implements hierarchical linear regression and bootstrap with a survey data set of Chinese manufacturing enterprises.

Findings

Results demonstrate that incentive and relational governance can generate complementary effects through enabling and compensating mechanisms, and their combination, that is, CGS, can promote ECP more than a single governance approach; CGS is conducive to solving the SC ambidexterity dilemma and can simultaneously enhance SC alignment and adaptability, thus further improving ECP; and SC ambidexterity plays an intermediary role between CGS and ECP.

Originality/value

The present study examines the complex interaction between incentive governance, relational governance, SC ambidexterity, and ECP. Implications for theory and practice are that formulating appropriate CGS can develop SC ambidexterity and improve ECP.

Details

Journal of Business & Industrial Marketing, vol. 39 no. 2
Type: Research Article
ISSN: 0885-8624

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