Using the GM(1,1) model cluster to forecast global oil consumption

2017 ◽  
Vol 7 (2) ◽  
pp. 286-296 ◽  
Author(s):  
Chaoqing Yuan ◽  
Yuxin Zhu ◽  
Ding Chen ◽  
Sifeng Liu ◽  
Zhigeng Fang
Keyword(s):  
Growth Rate ◽  
Model Selection ◽  
Design Methodology ◽  
Oil Consumption ◽  
Medium Term ◽  
Model Cluster ◽  
Content Type ◽  
Forecasting Models ◽  
Grey Forecasting ◽  
Term Prediction

Purpose The purpose of this paper is to compare GM(1,1) model, rolling GM(1,1) model and metabolism GM(1,1) model included in the GM(1,1) model cluster and use these models to forecast global oil consumption. Design/methodology/approach Simulated sequences will be generated randomly, and used to test the models included in the GM(1,1) model cluster; and these grey forecasting models are applied to forecast global oil consumption. Findings Effectiveness of these grey forecasting models is proved by random experiments, which explains the model adaptability. Global oil consumption is predicted, and it shows that global oil consumption will increase at a rather big growth rate in the next years. Originality/value The effectiveness of medium-term prediction of these grey forecasting models is analyzed by random experiments. These models are compared, and some basis for model selection is obtained.

Forecasting cocoa production of six major producers through ARIMA and grey models

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tawiah Kwatekwei Quartey-Papafio ◽  
Saad Ahmed Javed ◽  
Sifeng Liu
Keyword(s):  
Growth Rate ◽  
Prediction Models ◽  
Small Sample ◽  
Cocoa Bean ◽  
Production Forecast ◽  
Content Type ◽  
Forecasting Models ◽  
Grey Forecasting ◽  
Grey Models ◽  
Cocoa Production

PurposeIn the current study, two grey prediction models, Even GM (1, 1) and Non-homogeneous discrete grey model (NDGM), and ARIMA models are deployed to forecast cocoa bean production of the six major cocoa-producing countries. Furthermore, relying on Relative Growth Rate (RGR) and Doubling Time (Dt), production growth is analyzed.Design/methodology/approachThe secondary data were extracted from the United Nations Food and Agricultural Organization (FAO) database. Grey forecasting models are applied using the data covering 2008 to 2017 as their performance on the small sample size is well-recognized. The models' performance was estimated through MAPE, MAE and RMSE.FindingsResults show the two grey models fell below 10% of MAPE confirming their high accuracy and forecasting performance against that of the ARIMA. Therefore, the suitability of grey models for the cocoa production forecast is established. Findings also revealed that cocoa production in Côte d'Ivoire, Cameroon, Ghana and Brazil is likely to experience a rise with a growth rate of 2.52, 2.49, 2.45 and 2.72% by 2030, respectively. However, Nigeria and Indonesia are likely to experience a decrease with a growth rate of 2.25 and 2.21%, respectively.Practical implicationsFor a sustainable cocoa industry, stakeholders should investigate the decline in production despite the implementation of advanced agricultural mechanization in cocoa farming, which goes further to put food security at risk.Originality/valueThe study presents a pioneering attempt of using grey forecasting models to predict cocoa production.

scholarly journals Explanation of terms of grey forecasting models

2017 ◽  
Vol 7 (1) ◽  
pp. 123-128 ◽  
Author(s):  
Sifeng Liu ◽  
Yingjie Yang
Keyword(s):  
System Theory ◽  
Design Methodology ◽  
Grey System Theory ◽  
Grey System ◽  
Content Type ◽  
Forecasting Models ◽  
Grey Forecasting ◽  
Key Terms ◽  
Practical Implications

Purpose The purpose of this paper is to present the terms of grey forecasting models and techniques. Design/methodology/approach The definitions of basic terms about grey forecasting models and techniques are presented one by one. Findings The reader could know the basic explanation about the important terms about various grey forecasting models and techniques from this paper. Practical implications Many of the authors’ colleagues thought that unified definitions of key terms would be beneficial for both the readers and the authors. Originality/value It is a fundamental work to standardise all the definitions of terms for a new discipline. It is also propitious to spread and universal of grey system theory.

The impact of blacklists on external deposits: one size does not fit all

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Michael Jonsson ◽  
Jan Pettersson ◽  
Christian Nils Larson ◽  
Nir Artzi
Keyword(s):  
Growth Rate ◽  
Design Methodology ◽  
Descriptive Statistics ◽  
Comparable Data ◽  
Patriot Act ◽  
Content Type ◽  
Probable Impact ◽  
The Impact ◽  
Practical Implications ◽  
Country Specific

Purpose This study aims to measure the impact of the Non-Cooperative Countries and Territories, Organization for Economic Cooperation and Development and US PATRIOT Act Section 311 blacklists on external deposits from blacklisted jurisdictions into BIS reporting countries in 1996–2008, a period when anti-money laundering-related actions were consistently less stringent than post-2010, to see whether they had an effect even absent the threat of sizable financial fines. Design/methodology/approach The study uses descriptive statistics and bivariate and multivariate regressions to analyze the probable impact from blacklists on non-bank external deposits. The country sample is divided into offshore financial centers (OFCs) and non-OFCs and includes 158 non-listed countries. The impact of the blacklists is tested both jointly and individually for the respective blacklists. Findings The authors find mixed impact from jurisdictions being blacklisted on the growth rate of stocks of deposits into BIS reporting countries. Effects are often zero, negative in several cases and positive in some cases. This is consistent with the “stigma effect” and the “stigma paradox” in the literature. An overall impact from blacklisting is difficult to discern. Different blacklists had different effects, and the same blacklist impacted countries differently, illustrating the importance of disaggregating the analysis by individual countries. Research limitations/implications Interpretation of these data is limited by the absence of comparable data on non-resident deposits in blacklisted jurisdictions. Practical implications The impact of a blacklist depends in part on the structure of the listed jurisdictions’ economies, implying that country-specific sanctions may be more effective than blacklists. Originality/value This is one of the very few papers to date to rigorously test the impact of blacklists on external deposits.

Study on the second grey relational grade and its properties

Kybernetes ◽  
2010 ◽  
Vol 39 (8) ◽  
pp. 1330-1335 ◽  
Author(s):  
Yan Ma
Keyword(s):  
System Theory ◽  
Design Methodology ◽  
Grey System Theory ◽  
Forecasting Model ◽  
Grey System ◽  
Content Type ◽  
Grey Forecasting ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Practical Implications

PurposeThe purpose of this paper is to propose a second relational grade based on the general grey relational grade and analyze several of its properties.Design/methodology/approachGrey system theory. The paper proposes and studies second grey relational grade, establishes second grey relational formula, and studies several characteristics of second grey relational formula.FindingsProposing a second relational grade proved it could solve the problem of the parallelism partly and weaken relativity of space position.Research limitations/implicationsUntil now, the problem of the consistency could not be solved, nor could the problem of the effect which keeps the sequence the same.Practical implicationsThe precision of the grey forecasting model could be strengthened if used in the forecasting model.Originality/valueThe general relational grade only thinks over the relation between two sequences but does not involve the relation in one sequence. The second relational grade considers these two, so if the forecasting model is established with it, the model should be more exact.

Demand prediction in health sector using fuzzy grey forecasting

2018 ◽  
Vol 31 (6) ◽  
pp. 937-949 ◽  
Author(s):  
Ceyda Zor ◽  
Ferhan Çebi
Keyword(s):  
Relevant Literature ◽  
Health Sector ◽  
Healthcare Sector ◽  
Content Type ◽  
Demand Prediction ◽  
Forecasting Models ◽  
Grey Forecasting ◽  
Forecasting Performance ◽  
Grey Models ◽  
Health Demand

Purpose The purpose of this paper is to apply GM (1, 1) and TFGM (1, 1) models on the healthcare sector, which is a new area, and to show TFGM (1, 1) forecasting accuracy on this sector. Design/methodology/approach GM (1, 1) and TFGM (1, 1) models are presented. A hospital’s nine months (monthly) demand data is used for forecasting. Models are applied to the data, and the results are evaluated with MAPE, MSE and MAD metrics. The results for GM (1, 1) and TFGM (1, 1) are compared to show the accuracy of forecasting models. The grey models are also compared with Holt–Winters method, which is a traditional forecasting approach and performs well. Findings The results of this study indicate that TFGM (1, 1) has better forecasting performance than GM (1, 1) and Holt–Winters. GM (1, 1) has 8.01 per cent and TFGM (1, 1) 7.64 per cent MAPE, which means excellent forecasting power. So, TFGM (1, 1) is also an applicable forecasting method for the healthcare sector. Research limitations/implications Future studies may focus on developed grey models for health sector demand. To perform better results, parameter optimisation may be integrated to GM (1, 1) and TFGM (1, 1). The demand may be predicted not only for the total demand on hospital, but also for the demand of hospital departments. Originality/value This study contributes to relevant literature by proposing fuzzy grey forecasting, which is used to predict the health demand. Therefore, the new application area as the health sector is handled with the grey model.

Human capital analytics: the winding road

2017 ◽  
Vol 4 (2) ◽  
pp. 133-136 ◽  
Author(s):  
Morten Kamp Andersen
Keyword(s):  
Human Capital ◽  
Design Methodology ◽  
Full Potential ◽  
Medium Term ◽  
Content Type ◽  
Current State ◽  
A Value ◽  
Being There ◽  
Practical Implications

Purpose The purpose of this paper is to explore the question: human capital analytics (HR analytics) – are we there yet? It will seek to clarify what is meant by “being there yet” and it will argue that the most positive proponents for this field are way too optimistic about the current state and what impact it will have on HR in the short-to-medium term but that the long-term outlook remain positive for the field. Design/methodology/approach This is a viewpoint paper and the conclusions draw upon the author’s experience in the field. Findings It has been widely acknowledged that HR analytics is still a fairly immature field and has not yet reached its full potential. In this viewpoint, the author argues that the most positive proponents for this field are way too optimistic about the current state and what impact it will have on HR in the short-to-medium term but that the long-term outlook remains positive for the field. The author names four main reasons why HR analytics is still in its infancy: maturity, mindset, organization and competencies. Practical implications If these four aspects are addressed, the HR analytics function will be able to contribute much more to HR’s role as a value generator. Originality/value Focusing on these aspects will set HR analytics up for success and will lead to potentially large shareholder value creation.

A synthetic indicator of market leaders in the crowdlending sector

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Samuel Ribeiro-Navarrete ◽  
Daniel Palacios-Marqués ◽  
José María Martín Martín ◽  
José Manuel Guaita Martínez
Keyword(s):  
Performance Indicators ◽  
Design Methodology ◽  
Key Factors ◽  
Medium Term ◽  
Moderate Amount ◽  
Content Type ◽  
Synthetic Indicator ◽  
Key Variables ◽  
Market Leadership ◽  
Practical Implications

PurposeThis study contributes to the limited literature on crowdlending by providing a data-driven analysis of the sector. A synthetic DP2 indicator is proposed to identify the leaders of the crowdlending market, the key factors behind their success and the medium-term competitive implications.Design/methodology/approachThe study examines 17 crowdlending platforms and eight performance indicators. The information provided by these indicators is aggregated using a synthetic indicator based on the P2 Distance (DP2) method.FindingsMintos, Evoestate, Peerberry, Bondster and Fellow Finance are the leading platforms. This method reveals the key variables in the identification of market leaders, namely year-on-year variation in the number of investors and year-on-year variation in lending per investor. The leaders in terms of lending volumes should not take their current situation for granted. Small and medium-sized platforms are pushing hard and may overtake the incumbents as market leaders.Practical implicationsFinancial intermediation through crowdlending is becoming an increasingly popular alternative to traditional models. Changes in the sector are expected in the coming years due to the rise of platforms with a moderate amount of lending and solid year-on-year improvement. To become leaders and to attract both lenders and borrowers, platforms are encouraged to improve the information that they provide.Originality/valueThis paper offers the first analysis of market leadership in the crowdlending sector. It analyses the competitive market of the crowdlending sector based on its actors and key factors. These factors explain the differences in the market position of different platforms. Based on this analysis, the trends in this sector can be identified. This study is exploratory, so it offers empirical data that can be useful in the development of theories that apply to the sector.

The art of designing early exits

2018 ◽  
Vol 34 (8) ◽  
pp. 36-38
Keyword(s):  
Case Studies ◽  
Design Methodology ◽  
Reading Time ◽  
Research Paper ◽  
Cutting Edge ◽  
Medium Term ◽  
Content Type ◽  
Strategic Plans ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings This research paper concentrates on comparing startup acquisition trends concerning US and European companies, as well as the strategic plans founding entrepreneurs can make to maximise their chance of a profitable short to medium term exit from their startup. Acquiring companies find tech startups less than five years old to be desirable target for M&A purposes, and US companies are expanding the volume of their zealous M&A activity into Europe. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

New insights into consumer confidence in financial services

2011 ◽  
Vol 29 (2) ◽  
pp. 90-106 ◽  
Author(s):  
Adèle Gritten
Keyword(s):  
Financial Services ◽  
Paradigm Shift ◽  
Quantitative Research ◽  
Design Methodology ◽  
Consumer Behaviour ◽  
Consumer Confidence ◽  
Way Of Life ◽  
Medium Term ◽  
Content Type ◽  
Household Finances

PurposeA paradigm shift in consumer confidence has taken place with the worst recession on record forcing people to evaluate their personal and household finances. This paper seeks to explore the extent to which consumer confidence has been tarnished, and how it has evolved post‐recession. It aims to take both retrospective and prospective views on what has changed in the British psyche since the credit crunch, looking at where new confidences have been found and where old confidences have been lost, and hypothesising about the extent to which consumer behaviour will remain constant or further change against a likely backdrop of continuing financial instability.Design/methodology/approachThis paper is based on a variety of proprietary quantitative research surveys conducted by YouGov plc.FindingsThis paper provides new insights into consumer confidence, including, but not limited to: demonstrating the harsh realities of more people being in financial difficulty now than 18 months ago, and its impact on confidence; looking at which aspects of household expenditure and budgets have been hardest squeezed, and what that means for short‐ and medium‐term futures; analysing the extent to which the generally lower level of available credit makes consumers more or less reliant on borrowing as a way of life, and the associated impact on confidence and decision making/financial planning prioritisation; exploring the real fears and concerns people have about their future finances; and exploring consumer financial hopes and aspirations in a post‐recessionary climate.Originality/valueFindings from bespoke research offer hitherto unpublished and statistically valid results on the extent to which consumers have coped with and embraced the aftermath of the recession, and, moreover, how that might manifest itself in terms of future consumer confidence in financial services.

Beyond the causes

2017 ◽  
Vol 17 (3) ◽  
pp. 363-380 ◽  
Author(s):  
Richard Ohene Asiedu ◽  
Ebenezer Adaku ◽  
De-Graft Owusu-Manu
Keyword(s):  
Construction Industry ◽  
Design Methodology ◽  
Group Discussion ◽  
Good Practice ◽  
Sampling Technique ◽  
Schedule Control ◽  
Medium Term ◽  
Content Type ◽  
Scientific Approach ◽  
Unique Approach

Purpose This paper aims to contend that the circle of investigation into overruns cannot be complete unless the established critical failure factors are matched against their respective mitigating measures to avert the overruns. Extant literature is replete with factors that engender cost and time overruns within the design and construction phase. The constraint is the lack of a scientific approach in establishing a tackling mechanism to address the root causes and stakeholder responsibilities. Design/methodology/approach The research is based on nine unique grand factors previously established and reported in literature about the Ghanaian Construction Industry. A focus group discussion convened through a purposive sampling technique led to the establishment of a list of mitigating measures and strategies. Findings The paper established a checklist of 114 mitigating measures categorised into preventive, predictive and corrective approaches. Additionally, several short to medium term key strategies have been recommended to avert the occurrence of cost and time overruns. Originality/value The mitigating measures can be adopted as a checklist of good practice to help practitioners enhance the effectiveness of project budget and schedule control. It is also supposed to serve as a guide to practitioners in averting overruns through predictive, preventive and/or corrective causes. A unique approach in averting the occurrence of cost and time overruns.

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