A new grey prediction model considering the data gap compensation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Che-Jung Chang ◽  
Chien-Chih Chen ◽  
Wen-Li Dai ◽  
Guiping Li
Keyword(s):  
Experimental Results ◽  
Small Data ◽  
Grey Prediction ◽  
Data Set ◽  
Forecasting Accuracy ◽  
Content Type ◽  
Background Values ◽  
Managerial Decisions ◽  
Modeling Process ◽  
Grey Models

PurposeThe purpose of this paper is to develop a small data set forecasting method to improve the effectiveness when making managerial decisions.Design/methodology/approachIn the grey modeling process, appropriate background values are one of the key factors in determining forecasting accuracy. In this paper, grey compensation terms are developed to make more appropriate background values to further improve the forecasting accuracy of grey models.FindingsIn the experiment, three real cases were used to validate the effectiveness of the proposed method. The experimental results show that the proposed method can improve the accuracy of grey predictions. The results further indicate that background values determined by the proposed compensation terms can improve the accuracy of grey model in the three cases.Originality/valuePrevious studies determine appropriate background values within the limitation of traditional grey modeling process, while this study makes new background values without the limitation. The experimental results would encourage researchers to develop more accuracy grey models without the limitation when determining background values.

Predicting product demand from small-sized data: grey models

2017 ◽  
Vol 7 (1) ◽  
pp. 80-96 ◽  
Author(s):  
Asli Özdemir ◽  
Güzin Özdagoglu
Keyword(s):  
Markov Model ◽  
Prediction Models ◽  
Markov Models ◽  
Small Data ◽  
Grey Prediction ◽  
Prediction Problem ◽  
Content Type ◽  
Demand Prediction ◽  
Grey Models ◽  
Prediction Problems

Purpose Prediction problems raised in uncertain environments require different solution approaches such as grey prediction models, which consider uncertainty in information and also enable the use of small data sets. The purpose of this paper is to investigate the comparative performances of grey prediction models (GM) and Markov chain integrated grey models in a demand prediction problem. Design/methodology/approach The modeling process of grey models is initially described, and then an integrated model called the Grey-Markov model is presented for the convenience of applications. The analyses are conducted on a monthly demand prediction problem to demonstrate the modeling accuracies of the GM (1,1), GM (2,1), GM (1,1)-Markov, and GM (2,1)-Markov models. Findings Numerical results reveal that the Grey-Markov model based on GM (2,1) achieves better prediction performance than the other models. Practical implications It is thought that the methodology and the findings of the study will be a significant reference for both academics and executives who struggle with similar demand prediction problems in their fields of interest. Originality/value The novelty of this study comes from the fact that the GM (2,1)-Markov model has been first used for demand prediction. Furthermore, the GM (2,1)-Markov model represents a relatively new approach, and this is the second paper that addresses the GM (2,1)-Markov model in any area.

In vitro effectiveness of biapenem against IMP-producing Enterobacteriaceae

2021 ◽  
Vol 70 (10) ◽  
Author(s):  
Kazuyoshi Gotoh ◽  
Makoto Miyoshi ◽  
I Putu Bayu Mayura ◽  
Koji Iio ◽  
Osamu Matsushita ◽  
...  
Keyword(s):  
Therapeutic Option ◽  
Small Data ◽  
Limited Data ◽  
Data Set ◽  
Content Type ◽  
Link Type ◽  
Almost All ◽  
New Treatments ◽  
Time Kill

The options available for treating infections with carbapenemase-producing Enterobacteriaceae (CPE) are limited; with the increasing threat of these infections, new treatments are urgently needed. Biapenem (BIPM) is a carbapenem, and limited data confirming its in vitro killing effect against CPE are available. In this study, we examined the minimum inhibitory concentrations (MICs) and minimum bactericidal concentrations (MBCs) of BIPM for 14 IMP-1-producing Enterobacteriaceae strains isolated from the Okayama region in Japan. The MICs against almost all the isolates were lower than 0.5 µg ml−1, indicating susceptibility to BIPM, while approximately half of the isolates were confirmed to be bacteriostatic to BIPM. However, initial killing to a 99.9 % reduction was observed in seven out of eight strains in a time–kill assay. Despite the small data set, we concluded that the in vitro efficacy of BIPM suggests that the drug could be a new therapeutic option against infection with IMP-producing CPE.

Causal ascription of rework in building and civil engineering projects

2014 ◽  
Vol 21 (1) ◽  
pp. 111-126 ◽  
Author(s):  
Palaneeswaran Ekambaram ◽  
Peter E.D. Love ◽  
Mohan M. Kumaraswamy ◽  
Thomas S.T. Ng
Keyword(s):  
Construction Projects ◽  
Civil Engineering ◽  
Small Data ◽  
Data Set ◽  
Content Type ◽  
Management Measures ◽  
Significant Difference ◽  
Quantitative Impact ◽  
Engineering Projects

Purpose – Rework is an endemic problem in construction projects and has been identified as being a significant factor contributing cost and schedule overruns. Causal ascription is necessary to obtain knowledge about the underlying nature of rework so that appropriate prevention mechanisms can be put in place. The paper aims to discuss these issues. Design/methodology/approach – Using a supervised questionnaire survey and case-study interviews, data from 112 building and engineering projects about the sources and causes of rework in projects were obtained. A multivariate exploration was conducted to examine the underlying relationships between rework variables. Findings – The analysis revealed that there was a significant difference between rework causes for building and civil engineering projects. The set of associations explored in the analyses will be useful to develop a generic causal model to examine the quantitative impact of rework on project performance so that appropriate prevention strategies can be identified and developed. Research limitations/implications – The limitations include: small data set (112 projects), which include 75 from building and 37 from civil engineering projects. Practical implications – Meaningful insights into the rework occurrences in construction projects will pave pathways for rational mitigation and effective management measures. Originality/value – To date there has been limited empirical research that has sought to determine the causal ascription of rework, particularly in Hong Kong.

Skills and knowledge management in higher education: how service learning can contribute to social entrepreneurial competence development

2019 ◽  
Vol 23 (10) ◽  
pp. 1925-1948 ◽  
Author(s):  
Jantje Halberstadt ◽  
Jana-Michaela Timm ◽  
Sascha Kraus ◽  
Katherine Gundolf
Keyword(s):  
Service Learning ◽  
Social Entrepreneurship ◽  
Qualitative Content Analysis ◽  
Educational Practice ◽  
Future Research ◽  
Small Data ◽  
Learning Approaches ◽  
Structured Interviews ◽  
Data Set ◽  
Content Type

Purpose The purpose of this paper is to elaborate on how service learning approaches are able to foster social entrepreneurship competences. The aim of the paper is to formulate a framework of key competences for social entrepreneurship and to give first insights in how service learning actually has an impact on change in students’ set of competences. Design/methodology/approach This paper uses a mixed-methods approach combining qualitative data collectionmethods of learning diaries of the students and semi-structured interviews, including 40 master’s students studying at a German university in interdisciplinary learning settings and five instructors from the same universities. Analysis was carried out by means of qualitative content analysis. Findings This paper provides empirical insights about the competences that are being fostered by service learning. From these, a framework for social entrepreneurship competences is being derived. Research limitations/implications The set of competences should be further investigated, as it was derived out of a small data set. Therefore, researchers are encouraged to use the set of competences for social entrepreneurship as a basis for future research and on a longer-term perspective, which lead to substantial implications for educational practice. Practical implications This paper includes implications for new perspectives on service learning in the light of the development of a relevant framework for social entrepreneurship competence, having significant implications for educational practice in social entrepreneurship education. Originality/value With this paper, the authors fulfill the need of a framework of social entrepreneurship competences that serves as a foundation for educational practice and further research in the context of service learning and beyond.

Energy-related CO2 emission forecast for Turkey and Europe and Eurasia

2017 ◽  
Vol 7 (3) ◽  
pp. 436-452 ◽  
Author(s):  
Berk Ayvaz ◽  
Ali Osman Kusakci ◽  
Gül T. Temur
Keyword(s):  
Global Warming ◽  
Design Methodology ◽  
Political Leaders ◽  
Emission Data ◽  
Data Set ◽  
Content Type ◽  
Root Cause ◽  
Second Stage ◽  
Grey Models ◽  
Using Data

Purpose The global warming, caused by the anthropogenic greenhouse gases, has been one of the major worldwide issues over the last decades. Among them, carbon dioxide (CO2) is the most important one and is responsible for more than the two-third of the greenhouse effect. Currently, greenhouse gas emissions and CO2 emissions – the root cause of the global warming – in particular are being examined closely in the fields of science and they also have been put on the agenda of the political leaders. The purpose of this paper is to predict the energy-related CO2 emissions through using different discrete grey models (DGMs) in Turkey and total Europe and Eurasia region. Design/methodology/approach The proposed DGMs will be applied to predict CO2 emissions in Turkey and total Europe and Eurasia region from 2015 to 2030 using data set between 1965 and 2014. In the first stage of the study, DGMs without rolling mechanism (RM) will be used. In the second stage, DGMs with RM are constructed where the length of the rolling horizons of the respected models is optimised. Findings In the first stage, estimated values show that non-homogeneous DGM is the best method to predict Turkey’s energy-related CO2 emissions whereas DGM is the best method to predict the energy-related CO2 emissions for total Europe and Eurasia region. According to the results in the second stage, NDGM with RM (k=26) is the best method for Turkey while optimised DGM with RM (k=4) delivers most reliable estimates for total Europe and Eurasia region. Originality/value This study illustrates the effect of different DGM approaches on the estimation performance for the Turkish energy-related CO2 emission data.

Educational tourism and experiential learning: students’ perceptions of field trips

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Charles Arcodia ◽  
Margarida Abreu Novais ◽  
Nevenka Cavlek ◽  
Andreas Humpe
Keyword(s):  
Experiential Learning ◽  
Principal Component ◽  
Field Trips ◽  
Small Data ◽  
Key Factors ◽  
Data Set ◽  
Content Type ◽  
Future Studies ◽  
Paired Samples ◽  
Educational Tourism

Purpose This paper aims to investigate participants’ motivations and perceptions of a field trip. Specifically, this paper examines if and how students’ perceptions change with time and it explores the main factors for ensuring success in an experiential learning tourism program. Design/methodology/approach The study gathered and compared data collected in two points in time – immediately at the end of the experience and two months afterward. T-tests for paired samples were used to examine potential differences in perceptions and principal component analysis was used to identify the key factors determining the success of the experience. Findings The findings indicate that there are various motivations behind participation and that time barely affects perceptions of the experience. Furthermore, three factors emerged as important for meeting expectations, namely, social and professional connections, learning and traditional yet engaging teaching. Research limitations/implications While the outcomes are useful, they need to be thoughtfully applied because of the small data set. It is important to repeat similar investigations to allow more certainty in the propositions formulated. Furthermore, future studies should evaluate a broader variety of outcomes to determine whether perceptions remain constant. The implications are that educators and destination managers can easily apply these conclusions for the benefit and the findings can inform other field trips and broader experiential initiatives. Originality/value Despite research on learning outcomes and perceptions of experiential learning having expanded considerably, a fundamental question that remains unanswered is how perceptions of such experiences change and, consequently, when the most appropriate time is to assess participant perceptions.

The exponential grey forecasting model for CO2 emissions in Taiwan

2015 ◽  
Vol 5 (3) ◽  
pp. 354-366 ◽  
Author(s):  
Chen-Fang Tsai ◽  
Shin-Li Lu
Keyword(s):  
Moving Average ◽  
Grey Model ◽  
Model Optimization ◽  
Content Type ◽  
Background Values ◽  
Optimal Weights ◽  
Grey Forecasting ◽  
Grey Models ◽  
Forecast Models ◽  
Weighted Moving Average

Purpose – The purpose of this paper is to improve the forecasting efficiency of a grey model. Design/methodology/approach – The exponentially weighted moving average (EWMA) algorithm is proposed to modify background values for a new grey model optimization. Findings – The experimental results reveal that the proposed models (EGM, REGM) outperform traditional grey models. Originality/value – A genetic algorithm (GA) optimizer is used to select the optimal weights for the background values of the EGM(1,1) and REGM(1,1) forecast models. The results of the current study are very encouraging, as the empirical results show that the REGM(1,1) and EGM(1,1) models reduce the MAPE rates over the traditional GM(1,1) and RGM(1,1) models.

Social media in the airline industry: acceptance of social seating

2017 ◽  
Vol 8 (2) ◽  
pp. 256-279 ◽  
Author(s):  
Stefan Koch ◽  
Franziska Tritscher
Keyword(s):  
Social Networking ◽  
Technology Acceptance ◽  
Airline Industry ◽  
Survey Methodology ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Small Data ◽  
Perceived Ease Of Use ◽  
Data Set ◽  
Content Type

Purpose This paper aims to analyze influences on the adoption of an application launched by some airlines and independent providers, called “social seating”, which is based on user profiles from or similar to social networks. These applications have not been widely successful, and therefore constitute an interesting exception within the area of social networking, warranting further investigation. Design/methodology/approach An empirical study based on the technology acceptance model and using survey methodology has been undertaken to understand antecedents of adoption and use of such applications. Findings Results show a consistent influence of perceived ease of use on perceived usefulness, as well as a strong role of privacy and data security. Research limitations/implications Due to the limited adoption, the actual use could only be investigated using a small data set, while the majority of results rely on stated intentions. Originality/value This is one of a few studies that focuses on a social networking application that both crosses into the physical world, and that has been very limited in adoption and success.

Online investigation of users’ attitudes using automatic question answering

2018 ◽  
Vol 42 (3) ◽  
pp. 419-435 ◽  
Author(s):  
Chengzhi Zhang ◽  
Qingqing Zhou
Keyword(s):  
Experimental Data ◽  
Question Answering ◽  
Online Reviews ◽  
Experimental Results ◽  
Question Generation ◽  
Data Set ◽  
Content Type ◽  
Internet Users ◽  
Tourism Services ◽  
Sentiment Computing

Purpose With the development of the internet, huge numbers of reviews are generated, disseminated, and shared on e-commerce and social media websites by internet users. These reviews usually indicate users’ opinions about products or services directly, and are thus valuable for efficient marketing. The purpose of this paper is to mine online users’ attitudes from a huge pool of reviews via automatic question answering. Design/methodology/approach The authors make use of online reviews to complete an online investigation via automatic question answering (AQA). In the process of AQA, question generation and extraction of corresponding answers are conducted via sentiment computing. In order to verify the performance of AQA for online investigation, online reviews from a well-known travel website, namely Tuniu.com, are used as the experimental data set. Finally, the experimental results from AQA vs a traditional questionnaire are compared. Findings The experimental results show that results between the AQA-based automatic questionnaire and the traditional questionnaire are consistent. Hence, the AQA method is reliable in identifying users’ attitudes. Although this paper takes Chinese tourism reviews as the experimental data, the method is domain and language independent. Originality/value To the best of the authors’ knowledge, this is the first study to use the AQA method to mine users’ attitudes towards tourism services. Using online reviews may overcome problems with using traditional questionnaires, such as high costs and long cycle for questionnaire design and answering.

Path-based keyword search over XML streams

2015 ◽  
Vol 11 (3) ◽  
pp. 347-369 ◽  
Author(s):  
Savong Bou ◽  
Toshiyuki Amagasa ◽  
Hiroyuki Kitagawa
Keyword(s):  
Keyword Search ◽  
Real Data ◽  
Experimental Results ◽  
Data Set ◽  
Content Type ◽  
Finite Automation ◽  
Powerful Means ◽  
Extensible Markup ◽  
Xml Streams ◽  
Better Than

Purpose – In purpose of this paper is to propose a novel scheme to process XPath-based keyword search over Extensible Markup Language (XML) streams, where one can specify query keywords and XPath-based filtering conditions at the same time. Experimental results prove that our proposed scheme can efficiently and practically process XPath-based keyword search over XML streams. Design/methodology/approach – To allow XPath-based keyword search over XML streams, it was attempted to integrate YFilter (Diao et al., 2003) with CKStream (Hummel et al., 2011). More precisely, the nondeterministic finite automation (NFA) of YFilter is extended so that keyword matching at text nodes is supported. Next, the stack data structure is modified by integrating set of NFA states in YFilter with bitmaps generated from set of keyword queries in CKStream. Findings – Extensive experiments were conducted using both synthetic and real data set to show the effectiveness of the proposed method. The experimental results showed that the accuracy of the proposed method was better than the baseline method (CKStream), while it consumed less memory. Moreover, the proposed scheme showed good scalability with respect to the number of queries. Originality/value – Due to the rapid diffusion of XML streams, the demand for querying such information is also growing. In such a situation, the ability to query by combining XPath and keyword search is important, because it is easy to use, but powerful means to query XML streams. However, none of existing works has addressed this issue. This work is to cope with this problem by combining an existing XPath-based YFilter and a keyword-search-based CKStream for XML streams to enable XPath-based keyword search.

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