Xuejun Shen, Minghui Yue, Pengfei Duan, Guihai Wu and Xuerui Tan
Based on the prediction of the consumption of medical materials, the purpose of this paper is to study the applicability of the grey model method to the field and its predicted…
Abstract
Purpose
Based on the prediction of the consumption of medical materials, the purpose of this paper is to study the applicability of the grey model method to the field and its predicted accuracy.
Design/methodology/approach
The ABC classification method is used to classify medical consumables and select the analysis objects. The GM (1,1) model predicts the annual consumption of medical materials. The GM (1,1) modeling of the consumption of the selected medical materials in 2006~2017 was carried out by using the metabolite sequence and the sequence topology subsequence, respectively. The average rolling error and the average rolling accuracy are calculated to evaluate the prediction accuracy of the model.
Findings
The ABC classification results show that Class A projects, which account for only 9.79 percent of the total inventory items, occupy most of the inventory funds. Eight varieties with varying purchases and usages and complete historical data were selected for further analysis. The subsequence GM(1,1) model group constructed by two different methods predicts and scans the annual consumption of eight kinds of medical materials, and the rolling precision can reach more than 90 percent.
Originality/value
The metabolic GM (1,1) model is an ideal predictive model that can meet the requirements for a short-term prediction of medical material consumption (Zhang et al., 2014). The GM (1,1) model is more suitable for a short-term prediction of medical material consumption with less data modeling.
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Xuejun Fan and De Du
Focusing on the spillover effects between the CSI 500 stock index futures market and its underlying spot market during April to September 2015, the purpose of this paper is to…
Abstract
Purpose
Focusing on the spillover effects between the CSI 500 stock index futures market and its underlying spot market during April to September 2015, the purpose of this paper is to explore whether Chinese stock index futures should be responsible for the 2015 stock market crash.
Design/methodology/approach
Using both linear and non-linear econometric models, this paper empirically examines the mean spillover and the volatility spillover between the CSI 500 stock index futures market and the underlying spot market.
Findings
The results showed the following: the CSI 500 stock index futures market has significant one-way mean spillover effect on its spot market. The volatility in CSI 500 stock index futures market also has a significant positive spillover effect on its spot stock market, and the mean value of dynamic correlation coefficient between the two market volatility is 0.4848. The spillover effect of the CSI 500 stock index futures market on the underlying spot market is significantly asymmetric, characterized by relatively moderate and slow during the period of the markets rising, yet violent and rapid during the period of the markets falling. The findings suggest that although the stock index futures itself was not the “culprit” of Chinese stock market crash in 2015, its existence indeed accelerated and exacerbated the stock market’s decline under the imperfect trading system.
Originality/value
Different from the existing literature mainly focusing on CSI 300 stock index futures, this paper empirically examines the impact of the introduction of CSI 500 stock index futures on 2015 Chinese stock market crash for the first time.
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Xuejun Zhao, Yong Qin, Hailing Fu, Limin Jia and Xinning Zhang
Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the…
Abstract
Purpose
Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the actual signal acquisition is usually hindered by certain restrictions, such as the limited number of signal channels. The purpose of this study is to fulfill the weakness of the existed BSS method.
Design/methodology/approach
To deal with this problem, this paper proposes a blind source extraction (BSE) method for bearing fault diagnosis based on empirical mode decomposition (EMD) and temporal correlation. First, a single-channel undetermined BSS problem is transformed into a determined BSS problem using the EMD algorithm. Then, the desired fault signal is extracted from selected intrinsic mode functions with a multi-shift correlation method.
Findings
Experimental results prove the extracted fault signal can be easily identified through the envelope spectrum. The application of the proposed method is validated using simulated signals and rolling element bearing signals of the train axle.
Originality/value
This paper proposes an underdetermined BSE method based on the EMD and the temporal correlation method for rolling element bearings. A simulated signal and two bearing fault signal from the train rolling element bearings show that the proposed method can well extract the bearing fault signal. Note that the proposed method can extract the periodic fault signal for bearing fault diagnosis. Thus, it should be helpful in the diagnosis of other rotating machinery, such as gears or blades.
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Chongli Di, Xiaohua Yang, Xuejun Zhang, Jun He and Ying Mei
The purpose of this paper is to simulate and analyze accurately the multi-scale characteristics, variation periods and trends of the annual streamflow series in the Haihe River…
Abstract
Purpose
The purpose of this paper is to simulate and analyze accurately the multi-scale characteristics, variation periods and trends of the annual streamflow series in the Haihe River Basin (HRB) using the Hilbert-Huang Transform (HHT).
Design/methodology/approach
The Empirical Mode Decomposition (EMD) approach is adopted to decompose the original signal into intrinsic mode functions (IMFs) in multi-scales. The Hilbert spectrum is applied to each IMF component and the localized time-frequency-energy distribution. The monotonic residues obtained by EMD can be treated as the trend of the original sequence.
Findings
The authors apply HHT to 14 hydrological stations in the HRB. The annual streamflow series are decomposed into four IMFs and a residual component, which exhibits the multi-scale characteristics. After the Hilbert transform, the instantaneous frequency, center frequency and mean period of the IMFs are obtained. Common multi-scale periods of the 14 series exist, e.g. 3.3a, 4∼7a, 8∼10a, 11-14a, 24∼25a and 43∼45a. The residues indicate that the annual streamflow series has exhibited a decreasing trend over the past 50 years.
Research limitations/implications
The HHT method is still in its early stages of application in hydrology and needs to be further tested.
Practical implications
It is helpful for the study of the complex features of streamflow.
Social implications
This paper will contribute to the sustainable utilization of water resources.
Originality/value
This study represents the first use of the HHT method to analyze the multi-scale characteristics of the streamflow series in the HRB. This paper provides an important theoretical support for water resources management.
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Lianhua Cheng, Huina Ren, Huimin Guo and Dongqiang Cao
Safety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of…
Abstract
Purpose
Safety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of factors influencing safety cognition and lack a quantitative evaluation system of safety cognitive ability. The purpose of this paper is to find out the deficiencies in the safety cognition of workers in high-risk construction positions and to provide practical suggestions for improving their safety cognitive ability and reducing unsafe behavior.
Design/methodology/approach
Based on the iceberg model, the factors influencing the safety cognitive ability of workers in high-risk construction positions and their hierarchical relationship were determined, and an evaluation index system consisting of four primary indicators and 20 secondary indicators was constructed. The game theory algorithm was used to optimize the subjective and objective weights of the indicators calculated by the sequential analysis method (G1) and the entropy weighting method (EWM) to obtain the optimal combination weight value. The Matlab software was used for cloud mapping and similarity calculation to determine the safety cognitive ability level of the object to be evaluated.
Findings
The research results indicate that the comprehensive level of safety cognitive ability of scaffolders in this construction project is at “Level III”, the fundamental factors and compliance factors are at “Level IV”, the auxiliary factors and driving factors are at “Level III”. This conclusion aligns with the situation learned from the previous field investigation, which validates the feasibility and scientificity of the proposed evaluation method.
Research limitations/implications
Considering that the safety cognitive ability of construction workers is constantly changing, this study has not yet delved into the specific impacts of various influencing factors on the level of safety cognitive ability. Future research can utilize simulation software, such as MATLAB and Vensim, to construct dynamic simulation models that accurately simulate the changing rules of construction workers’ safety cognitive ability under the influence of different factors.
Practical implications
This research broadens the application scope of the iceberg model, enriches the analysis model of the factors influencing the safety cognitive ability of workers in high-risk construction positions and provides a novel perspective for similar research. The safety cognitive ability evaluation method proposed in this paper can not only accurately evaluate the safety cognitive ability level of workers in high-risk positions such as scaffolders but also provide practical suggestions for improving the safety cognitive ability of workers, which is of great significance to improve the safety management level and reduce unsafe behavior in the construction field.
Originality/value
This research fills the research gap of workers in high-risk construction positions and the quantification of safety cognitive ability. The iceberg model is used to realize the hierarchical division of the factors influencing safety cognitive ability. Additionally, an evaluation method for the safety cognitive ability of workers in high-risk construction positions based on the game theory combination weighting method and cloud model is proposed, which realizes the quantitative evaluation of safety cognitive ability.
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Guojun Wang and Xing Su
During the early 1970s, faced with the serious demographic situation, China began to fully implement the policy of family planning in urban and rural regions. Nowadays, the…
Abstract
Purpose
During the early 1970s, faced with the serious demographic situation, China began to fully implement the policy of family planning in urban and rural regions. Nowadays, the problems of pension and medical care for aged parents confronted by the first generation of the one‐child family have begun to gradually appear. Meanwhile, China's population and the family planning are also faced with some problems that are difficult to solve, including unbalanced fertility rate of urban and rural population, the gender imbalance, the difficulty of the risk diversification in a one‐child family, as well as the profound contradiction between the stability of the family planning policy and the drive of administrative measures. Therefore, it is necessary to establish the integrated‐scheduled life security system of the one‐child family in urban and rural areas, in order to overcome the problems and to promote the transformation of the family planning policy. The purpose of this paper is to discuss the life security system for China's one‐child families.
Design/methodology/approach
The life security system for the one‐child family proposed by this paper consists of three issues: the basic security based on the level of social security, the additional security of the policy insurance and the supplementary security of the commercial insurance. The paper begins with the history of the family planning policy in the first section and then go through some relevant articles regarding complementary measures such as maternity insurance, rural endowment insurance that only focused on one aspect of issues associated with the family planning. In section three, four typical problems are listed for the purpose of following discussion of corresponding solutions which are full of deficiency in section four. In part five, the integrated planning of the life security system for Chinese one‐child family is elaborated with risk and fund management. In the last part, we conclude that the family planning policy maintains stable, whereas measures to be taken are adjusted along with changeable new problems.
Findings
The policy insurance plays an increasingly important role in dealing with the life security of older people in one‐child families. It may be better to promote the kind of insurance.
Originality/value
The paper comprehensively discusses the life security system for Chinese families in compliance with the family planning policy.
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Shrawan Kumar Trivedi and Amrinder Singh
There is a strong need for companies to monitor customer-generated content of social media, not only about themselves but also about competitors, to deal with competition and to…
Abstract
Purpose
There is a strong need for companies to monitor customer-generated content of social media, not only about themselves but also about competitors, to deal with competition and to assess competitive environment of the business. The purpose of this paper is to help companies with social media competitive analysis and transformation of social media data into knowledge creation for decision-makers, specifically for app-based food delivery companies.
Design/methodology/approach
Three online app-based food delivery companies, i.e. Swiggy, Zomato and UberEats, were considered in this study. Twitter was used as the data collection platform where customer’s tweets related to all three companies are fetched using R-Studio and Lexicon-based sentiment analysis method is applied on the tweets fetched for the companies. A descriptive analytical method is used to compute the score of different sentiments. A negative and positive sentiment word list is created to match the word present on the tweets and based on the matching positive, negative and neutral sentiments score are decided. The sentiment analysis is a best method to analyze consumer’s text sentiment. Lexicon-based sentiment classification is always preferable than machine learning or other model because it gives flexibility to make your own sentiment dictionary to classify emotions. To perform tweets sentiment analysis, lexicon-based classification method and text mining were performed on R-Studio platform.
Findings
Results suggest that Zomato (26% positive sentiments) has received more positive sentiments as compared to the other two companies (25% positive sentiments for Swiggy and 24% positive sentiments for UberEats). Negative sentiments for the Zomato was also low (12% negative sentiments) compared to Swiggy and UberEats (13% negative sentiments for both). Further, based on negative sentiments concerning all the three food delivery companies, tweets were analyzed and recommendations for business provided.
Research limitations/implications
The results of this study reveal the value of social media competitive analysis and show the power of text mining and sentiment analysis in extracting business value and competitive advantage. Suggestions, business and research implications are also provided to help companies in developing a social media competitive analysis strategy.
Originality/value
Twitter analysis of food-based companies has been performed.
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Octaviano Rojas Luiz, Fernando Bernardi de Souza, João Victor Rojas Luiz and Daniel Jugend
The purpose of this paper is to analyze the state of the art in Critical Chain Project Management (CCPM), outlining the CCPM literature to date, in an effort to guide future…
Abstract
Purpose
The purpose of this paper is to analyze the state of the art in Critical Chain Project Management (CCPM), outlining the CCPM literature to date, in an effort to guide future studies.
Design/methodology/approach
The paper is based on a bibliometric analysis using Scopus and Web of Science databases. The authors identified the principal journals, articles and authors regarding the research theme, as well as the authors elaborated co-citation and co-occurrence network maps to support the analysis.
Findings
The authors described five co-citation clusters: Fundamentals of Critical Chain, Scheduling, Operations Research, Multi-project and Network, and General Project Management. The most frequently occurring keywords were: “project management,” “critical chain,” “scheduling” and “theory of constraints.” Observing the distribution, the expression “project management” occupied a central position, connecting two other clusters, represented by the keywords “scheduling” and “critical chain.” The authors proposed an evolutive framework for the CCPM state of the art in three stages, according to the most frequent topics identified: Conceptual, Deepening of Applications and Methodological Maturity.
Originality/value
This research adopts a systematic approach based on bibliometric tools, which allows a more rigorous organization of the literature. Co-citation and keyword co-occurrence maps provide evidence of how the main themes in CCPM relate. Besides, the presented historical framework allows new research in CCPM to be directed to the most recent topics of interest that have gaps to be explored.
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Gionata Carmignani and Francesco Zammori
The capability to overcome tradeoffs among costs, quality and time has become a must in high-margin businesses too. Lean thinking may be a solution, but applications in the…
Abstract
Purpose
The capability to overcome tradeoffs among costs, quality and time has become a must in high-margin businesses too. Lean thinking may be a solution, but applications in the luxury-fashion market are still rare. In order to shed light on this apparent contradiction, the purpose of this paper is to identify the key features of the luxury-fashion market that may act as barriers for the adoption of lean principles. Next, based on the results of this preliminary analysis, the paper tries to verify, if and how, lean principles can be properly reinterpreted, so as to properly fit the requirements of this market.
Design/methodology/approach
Due to the operating nature of lean, an empiric approach was followed. From the evidences gathered during a lean project of a world-wide company, critical elements of the luxury-fashion market were identified and used as criteria to select, among lean tools, the most appropriate ones. Lastly, selected tools were integrated in a structured framework (for lean implementation) that was used to analyze and to improve many logistics and manufacturing processes.
Findings
Developed solutions were implemented as pilot projects, with outstanding preliminary result. Results are case specific and trying to infer general considerations may be hazardous. Nonetheless, due to the relevant dimension of the project, they can be considered more than a clue concerning the robustness of the framework and, most of all, concerning the real potentialities of lean in the luxury-fashion market.
Practical implications
The framework is extremely operational and, together with the proposed industrial cases, can be used as a guideline to support practitioners during the implementation of similar projects.
Originality/value
Lean thinking is relatively new in the luxury-fashion market, where the focus on operational costs has been traditionally considered as a marginal issue. Thus, the application of lean principles in this market is the innovative element of the paper.
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Yuxiang Shan, Qin Ren, Gang Yu, Tiantian Li and Bin Cao
Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards…
Abstract
Purpose
Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards illegally, which leads to increased cost of enterprises and reduced effect of marketing. Therefore, this paper aims to construct a user risk assessment model to identify potential underground industry users to protect the interests of real consumers and reduce the marketing costs of enterprises.
Design/methodology/approach
Method feature extraction is based on two aspects. The first aspect is based on traditional statistical characteristics, using density-based spatial clustering of applications with noise clustering method to obtain user-dense regions. According to the total number of users in the region, the corresponding risk level of the receiving address is assigned. So that high-quality address information can be extracted. The second aspect is based on the time period during which users participate in activities, using frequent item set mining to find multiple users with similar operations within the same time period. Extract the behavior flow chart according to the user participation, so that the model can mine the deep relationship between the participating behavior and the underground industry users.
Findings
Based on the real underground industry user data set, the features of the data set are extracted by the proposed method. The features are experimentally verified by different models such as random forest, fully-connected layer network, SVM and XGBOST, and the proposed method is comprehensively evaluated. Experimental results show that in the best case, our method can improve the F1-score of traditional models by 55.37%.
Originality/value
This paper investigates the relative importance of static information and dynamic behavior characteristics of users in predicting underground industry users, and whether the absence of features of these categories affects the prediction results. This investigation can go a long way in aiding further research on this subject and found the features which improved the accuracy of predicting underground industry users.