scholarly journals Global money laundering appeal index: application of principal component analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Milind Tiwari ◽  
Adrian Gepp ◽  
Kuldeep Kumar
Keyword(s):  
Principal Component Analysis ◽  
Money Laundering ◽  
Principal Component ◽  
Component Analysis ◽  
Economic Feasibility ◽  
Ranking System ◽  
Single Measure ◽  
Financial Flows ◽  
Content Type ◽  
To Come

Purpose The paper aims at developing a global ranking system determining a country's appeal as a destination for money laundering. Design/methodology/approach This paper uses principal component analysis (PCA), with a mix of standardised and unstandardised components relating to attractiveness, economic freedom and money laundering risk to come up with an index of money laundering appeal. Findings Four components relating to economic feasibility, financial liberty, government spending and tax regime are critical in influencing a country's money laundering appeal. Research limitations/implications This paper attempts to use a standardised and replicable methodology to condense into a single measure the complex and multifaceted phenomenon of a country's appeal as a destination for money laundering, thus avoiding the difficulty associated with precisely calculating illicit financial flows. Practical implications The ranking system could be used to determine the destinations attractive for laundering money. Such information can be used to come up with more effective preventative strategies to combat phenomena responsible for the stagnation of economic growth through tax evasion, corruption and creation of non-competitive markets. Originality/value It is the first attempt to use a statistical technique to understand the underlying components of a country's money laundering appeal.

A principal component analysis of the determinants of spatial disparity between rural and urban localities of Ghana

2017 ◽  
Vol 44 (6) ◽  
pp. 715-731 ◽  
Author(s):  
Ivy Drafor
Keyword(s):  
Principal Component Analysis ◽  
Rural Areas ◽  
Urban Areas ◽  
Principal Component ◽  
Component Analysis ◽  
Spatial Inequality ◽  
Necessary Condition ◽  
Spatial Disparity ◽  
Content Type ◽  
Rural And Urban

Purpose The purpose of this paper is to analyse the spatial disparity between rural and urban areas in Ghana using the Ghana Living Standards Survey’s (GLSS) rounds 5 and 6 data to advance the assertion that an endowed rural sector is necessary to promote agricultural development in Ghana. This analysis helps us to know the factors that contribute to the depravity of the rural sectors to inform policy towards development targeting. Design/methodology/approach A multivariate principal component analysis (PCA) and hierarchical cluster analysis were applied to data from the GLSS-5 and GLSS-6 to determine the characteristics of the rural-urban divide in Ghana. Findings The findings reveal that the rural poor also spend 60.3 per cent of their income on food, while the urban dwellers spend 49 per cent, which is an indication of food production capacity. They have low access to information technology facilities, have larger household sizes and lower levels of education. Rural areas depend a lot on firewood for cooking and use solar/dry cell energies and kerosene for lighting which have implications for conserving the environment. Practical implications Developing the rural areas to strengthen agricultural growth and productivity is a necessary condition for eliminating spatial disparities and promoting overall economic development in Ghana. Addressing rural deprivation is important for conserving the environment due to its increased use of fuelwood for cooking. Absence of alternatives to the use of fuelwood weakens the efforts to reduce deforestation. Originality/value The application of PCA to show the factors that contribute to spatial inequality in Ghana using the GLSS-5 and GLSS-6 data is unique. The study provides insights into redefining the framework for national poverty reduction efforts.

Factorial analysis of stress factors among the sample of Lebanese police officers

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fadi Afif Fayyad ◽  
Filip Vladimir Kukić ◽  
Nemanja Ćopić ◽  
Nenad Koropanovski ◽  
Milivoj Dopsaj
Keyword(s):  
Principal Component Analysis ◽  
Police Officers ◽  
Psychological Health ◽  
Social Life ◽  
Principal Component ◽  
Component Analysis ◽  
Stress Factors ◽  
Research Approach ◽  
Content Type ◽  
Stress Management Training

PurposeThe purpose of the study is to determine the prevalence of stress and to identify the occupational stressors among Lebanese police officers.Design/methodology/approachOperational Police Stress Questionnaire (PSQ-op) was addressed to 100 randomly selected male Lebanese Police officers. Twenty items from the PSQ-op were run through the principal component analysis to determine the most significant factors of stress and loading within each of the factors.FindingsThe results indicated that 59% of officers reported moderate stress level and 41% reported strenuous stress. Principal component analysis identified six independent factors or stress among Lebanese police officers explaining in total 72.1% of the total variance: excessive workload (30.6%), social-life time management (12.8%), occupational fitness (9.1%), success-related stress (8.6%), physical and psychological health (5.8%), and working alone at night (5.2%).Research limitations/implicationsThis research approach encountered some limitations so further research must: use a larger sample size, include female gender and identify other sources of stressors mainly organizational or job context stressors.Originality/valueAddressing and understanding stress factors among Lebanese police officers helps improving awareness and developing individualized treatment strategies leading police officers to engage in stress-management training to learn coping strategies and use effective tools for preventing stress before it becomes chronic.

Sociodemographic characteristics and dietary patterns in cardiometabolic risk subjects

2019 ◽  
Vol 121 (11) ◽  
pp. 2780-2790 ◽  
Author(s):  
Brenda Kelly Souza Silveira ◽  
Juliana Farias de Novaes ◽  
Sarah Aparecida Vieira ◽  
Daniela Mayumi Usuda Prado Rocha ◽  
Arieta Carla Gualandi Leal ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Dietary Patterns ◽  
Cardiovascular Health ◽  
Cardiometabolic Risk ◽  
Principal Component ◽  
Component Analysis ◽  
Unhealthy Lifestyle ◽  
Cross Sectional ◽  
Content Type ◽  
Traditional Pattern

Purpose The purpose of this paper is to examine the associations of dietary patterns with sociodemographic and lifestyle characteristics in a cardiometabolic risk population. Design/methodology/approach In this cross-sectional study data from 295 (n=123 men/172 women, 42±16 years) participants in a Cardiovascular Health Care Program were included. After a 24-hour recall interview the dietary patterns were determined using principal component analysis. Sociodemographic, clinical and lifestyle data were collected by medical records. Findings Subjects with diabetes and hypertension had a higher adherence in the “traditional” pattern (rice, beans, tubers, oils and meats). Poisson regression models showed that male subjects with low schooling and smokers had greater adherence to the “traditional” pattern. Also, students, women, and those with higher schooling and sleeping =7 h/night showed higher adherence to healthy patterns (whole grains, nuts, fruits and dairy). Women, young adults and those with higher schooling and fewer sleep hours had greater adherence to healthy dietary patterns. Those with low schooling and unhealthy lifestyle showed more adherence to the “traditional” pattern. Social implications The results indicate the importance to personalized nutritional therapy and education against cardiometabolic risk, considering the dietary patterns specific to each population. Originality/value Socioeconomic and lifestyle characteristics can influence dietary patterns and this is one of the few studies that investigated this relationship performing principal component analysis.

scholarly journals Characterising 3D spherical packings by principal component analysis

2019 ◽  
Vol 37 (3) ◽  
pp. 1023-1041 ◽  
Author(s):  
Tingting Zhao ◽  
Y.T. Feng ◽  
Yuanqiang Tan
Keyword(s):  
Principal Component Analysis ◽  
Gaussian Quadrature ◽  
Three Dimensional ◽  
Principal Component ◽  
Component Analysis ◽  
Particle Packing ◽  
Cross Sectional ◽  
Content Type ◽  
Computer Methods ◽  
Novel Approach

Purpose The purpose of this paper is to extend the previous study [Computer Methods in Applied Mechanics and Engineering 340: 70-89, 2018] on the development of a novel packing characterising system based on principal component analysis (PCA) to quantitatively reveal some fundamental features of spherical particle packings in three-dimensional. Design/methodology/approach Gaussian quadrature is adopted to obtain the volume matrix representation of a particle packing. Then, the digitalised image of the packing is obtained by converting cross-sectional images along one direction to column vectors of the packing image. Both a principal variance (PV) function and a dissimilarity coefficient (DC) are proposed to characterise differences between different packings (or images). Findings Differences between two packings with different packing features can be revealed by the PVs and DC. Furthermore, the values of PV and DC can indicate different levels of effects on packing caused by configuration randomness, particle distribution, packing density and particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach. Originality/value Develop an alternative novel approach to quantitatively characterise sphere packings, particularly their differences.

The long-run effects of energy use, urbanization and financial development on carbon dioxide emissions

2020 ◽  
Vol 14 (6) ◽  
pp. 1405-1424
Author(s):  
Paul Adjei Kwakwa
Keyword(s):  
Carbon Dioxide ◽  
Principal Component Analysis ◽  
Financial Development ◽  
Carbon Emission ◽  
Energy Use ◽  
Principal Component ◽  
Component Analysis ◽  
Content Type ◽  
Long Run ◽  
Emission Effect

Purpose This study aims to fill the gap in existing studies that have analyzed the drivers of carbon dioxide (CO2) emissions. The author investigate the long-run effects of energy types, urbanization, financial development and, the interaction between urbanization and financial development on CO2 emissions. Design/methodology/approach Stochastic impacts by regression on population, affluence and technology model served as the framework for empirical modeling. Using annual time-series data for Tunisia, autoregressive distributed lag bounds test was used to examine the cointegration of the variables. Also, the fully modified ordinary least squares was used to estimate the emission effect of the explanatory variables. Further investigations were done using the principal component analysis and variance decomposition analysis. Findings Income, urbanization, trade and financial development exert upward pressure on CO2 emissions. However, the interaction between urbanization and financial development reduces the emission of CO2. Furthermore, primary energy use, energy intensity, electricity consumption and fossil fuel consumption have positive effects on carbon emission, while combustible renewables and waste, and electricity production from natural gas have negative effects on carbon emission. Practical implications The policy implication/recommendation indicates that the financial sector’s authorities can combat carbon emission by properly regulating the development and activities of the financial sector in urban areas in Tunisia. The promotion of the development and usage of cleaner energy is recommended to help reduce carbon emission. Policymakers need to promote environmentally friendly economic growth and development agenda. Originality/value The contribution of this study to the environmental degradation literature is that it offers evidence from Tunisia, which has not received much empirical attention. It also examines the effect of various forms of energy usage on carbon emission. To the best of the author’s knowledge, this is the first study to examine the interaction effect between urbanization and financial development on carbon emission. Also, if not the first, this study is among the earliest to use the principal component analysis as a part of the prediction of the carbon emission effect of energy variables.

Customers’ quality demands as directions to the cold chicken supply chain management

2018 ◽  
Vol 24 (3) ◽  
pp. 771-785 ◽  
Author(s):  
Gustavo Schiavo ◽  
Andre Luis Korzenowski ◽  
Eduardo Roberto Soares Batista ◽  
Davenilcio Luiz de Souza ◽  
Annibal Scavarda
Keyword(s):  
Principal Component Analysis ◽  
Supply Chain ◽  
Quality Function Deployment ◽  
Principal Component ◽  
Component Analysis ◽  
Content Type ◽  
Product Specificity ◽  
Product Availability ◽  
Product Assortment ◽  
Quality Aspects

PurposeThe purpose of this paper is to analyze the perception of the cold chicken meat value in its supply chain and how to manage the influence of quality demands in this supply chain. It is based on the views that retails and restaurants have about the main quality aspects required to meet their end customers.Design/methodology/approachThis paper surveyed 135 respondents from restaurants, butcheries, supermarkets, and convenience stores located in the Southern Brazilian metropolitan area. Principal component analysis followed by quality function deployment was performed to analyze the data.FindingsThe principal component analysis results in seven factors: product quality and flexibility of delivery; supply flexibility; responsiveness to market changes and product assortment; measurements of the inventory and competitiveness; product specificity; product availability and specificity cost; and delivery frequency. The comparative study on the steps of the process between restaurants and retailers shows that distribution, cutting and packaging are the key process steps in this chain.Practical implicationsThe results show what process steps must be prioritized to comply with the customers’ quality requirements. Since the most important process steps are different for different customers, companies may elect what steps require more attention to satisfy the most profitable customer types.Originality/valueSeveral studies are found in the literature that present a theoretical discussion on the quality demands of perishable products. The management of factors related to the process steps can help members of the supply chain in their decision-making processes. The contribution of this research is to identify, by an applied study, how the demanded quality aspects should be considered by the poultry industry to satisfy customers in different market segments.

Branding efforts and SME performance – an empirical investigation of variations across firm sizes and business sectors

2017 ◽  
Vol 19 (1) ◽  
pp. 59-76 ◽  
Author(s):  
Raphael Odoom ◽  
Priscilla Mensah ◽  
George Asamoah
Keyword(s):  
Principal Component Analysis ◽  
Emerging Market ◽  
Pearson Correlation ◽  
Principal Component ◽  
Component Analysis ◽  
Content Type ◽  
Brand Building ◽  
Brand Marketing ◽  
And Performance ◽  
Stage Analysis

Purpose This paper aims to draw on the organizational ecology theory to examine variations in branding efforts and performance of small and medium-sized enterprises (SMEs) across enterprises sizes and business operating sectors. Design/methodology/approach A four-stage analysis involving principal component analysis, Pearson correlation, ANOVA and logistic regressions was used on a sample of 430 SMEs within an emerging market. Findings Principal component analysis identified four brand marketing efforts relevant to the SMEs. These efforts were used in fluctuating extents among small-sized versus medium-sized enterprises, as well as manufacturing versus services SMEs. Additionally, proportionate levels of performance corollaries were found to be accruable across the enterprise sizes and operating sectors. Originality/value The paper first identifies four brand-building efforts germane to SMEs within an emerging market and examines their precise contributions to firm performance within enterprise sizes and business operating sectors. It further reinforces the relevance of brand marketing programs to the growth of SMEs by establishing the likelihood and extent to which brand-building efforts impact on SME performance across enterprise sizes, as well as operating sectors. The study also presents issues of potential research and managerial interest from an emerging market, offering insightful implications to researchers and SME managers.

Assessment of antioxidant activity, minerals and chemical constituents of edible mahua (Madhuca longifolia) flower and fruit of using principal component analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vinti Singh ◽  
Jyotsana Singh ◽  
Radha Kushwaha ◽  
Monika Singh ◽  
Sandeep Kumar ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Antioxidant Activity ◽  
Mineral Content ◽  
Principal Component ◽  
Component Analysis ◽  
Total Phenolic ◽  
Ripe Fruit ◽  
Unripe Fruit ◽  
Content Type ◽  
Madhuca Longifolia

Purpose Flowers and fruits of Madhuca longifolia (Koenig) (mahua) tree are edible and used as traditional Indian medicines. The physicochemical properties of different parts of mahua are investigated. This study aims to estimate the different mineral contents, polyphenols compounds and antioxidant activities by 2,2-diphenyl-1-picrylhydrazyl inhibition, reducing power, free radical scavenging activity using 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) and ferric reducing antioxidant power assays of mahua flower, ripe and unripe fruit. Design/methodology/approach Flavonoids were identified and quantified in yellow flowers and fruits of M. longifolia tree by high-performance liquid chromatography with diode array detector. Low molecular weight carbohydrates were determined by the ICBio scan, a specific method for determining of carbohydrates. Mineral content is determined by laser-induced breakdown spectroscopy (LIBS) and atomic absorption spectroscopy. Physicochemical, nutritional and mineral properties of mahua flower, ripe and unripe fruit were investigated by the statistical approach of principal component analysis (PCA). Findings Ascorbic acid, gallic acid (GA), quercetin and myrcetin were the phenolic compounds identified and quantified in mahua flower and fruit extracts. Sugar profiling of mahua flowers and fruits confirmed the presence of inositol, sorbitol, mannitol, dextrose, fructose, sucrose, raffinose and maltose. The mineral content of Na, K, Mg and Ca was present in quite a good amount in all samples. Total phenolic content (TPC) was significantly high in mahua flower (25.3 ± 1.0 mg GA equivalent/g FW) followed by mahua unripe (15.8 ± 1.0 mg GA equivalent/g FW) and ripe fruit (14.3 ± 1.0 mg GA equivalent/g FW) at p = 5%. In contrast, total flavonoid contents (TFCs) were highest in ripe fruit, then mahua flower and unripe fruit. Positive correlations were predicted by PCA for mahua flower with TPC, antioxidant activity assays and minerals except for Na; ripe fruit with TFC and Na; and unripe fruit with maltose and sorbitol. Originality/value This study demonstrates the application of LIBS for the determination of elements present in the mahua flowers and fruits and reveals that mahua can be a good source of nutrients. Sugar profiling of mahua flower showed that it is a rich source of reducing and non-reducing sugar, proving that mahua flower juice can be used as a natural sweetener in the development of different food products, namely, biscuits, cookies, cake, jam, jelly, juice and squash.

scholarly journals The Quality Assessment of Commercial Lycium Berries Using LC-ESI-MS/MS and Chemometrics

Plants ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 604 ◽  
Author(s):  
Jarouche ◽  
Suresh ◽  
Hennell ◽  
Sullivan ◽  
Lee ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Blood Glucose Control ◽  
Principal Component ◽  
Component Analysis ◽  
Resolving Power ◽  
Qualitative Assessment ◽  
Ranking System ◽  
Esi Ms ◽  
Method Optimization ◽  
Validation Procedure

Lycium (also known as Goji berry) is used in traditional Chinese medicine (TCM) with claimed benefits, including eye and liver protection, immune system fortification and blood glucose control. The commercially available product comes from either the L. barbarum or L. chinense species, with the former dominating the marketplace due to its better taste profile. The main objective of this study was to develop a validated LC-ESI-MS/MS method to quantify multiple key bio-active analytes in commercially available Lycium berries and to qualitatively assess these samples using a principal component analysis (PCA). A LC-ESI-MS/MS method for the quantitation of seven analytes selected using the Herbal Chemical Marker Ranking System (Herb MaRS) was developed. The Herb MaRS ranking system considered bioavailability, bioactivity and physiological action of each target analyte, its intended use and the commercial availability of an analytical standard. After method optimization combining high resolving power with selective detection, seven analytes were quantified and the Lycium samples were quantitatively profiled. Chromatographic spectra were also obtained using longer run-time LC-UV and GC-MS methods in order to qualitatively assess the samples using a principal component analysis (PCA). The result of the method validation procedure was a 15.5 min LC-ESI-MS/MS method developed for the quantification of seven analytes in commercial Lycium samples. Wide variation in analyte concentration was observed with the following results (analyte range in mg/g): rutin, 16.1–49.2; narcissin, 0.37–1.65; nictoflorin, 0.26–0.78; coumaric acid, 6.84–12.2; scopoletin, 0.33–2.61; caffeic acid, 0.08–0.32; chlorogenic acid, 1.1–9.12. The quantitative results for the L. barbarum and L. chinense species samples indicate that they cannot be differentiated based on the bio-actives tested. A qualitative assessment using PCA generated from un-targeted LC-UV and GC-MS phytochemical spectra led to the same conclusion. The un-targeted quantitative and qualitative phytochemical profiling indicates that commercial L. barbarum and L. chinense cannot be distinguished using chemical analytical methods. Genetic fingerprinting and pharmacological testing may be needed to ensure the efficacy of commercial Lycium in order to validate label claims.

Quantitative assessment of spiritual capital in changing organizations by principal component analysis and fuzzy clustering

2015 ◽  
Vol 28 (3) ◽  
pp. 469-485 ◽  
Author(s):  
Mohammad Reza Taghizadeh Yazdi
Keyword(s):  
Principal Component Analysis ◽  
Fuzzy Clustering ◽  
Questionnaire Survey ◽  
Quantitative Assessment ◽  
Principal Component ◽  
Component Analysis ◽  
Second Phase ◽  
Two Phase ◽  
Content Type ◽  
Spiritual Capital

Purpose – The purpose of this paper is to illustrate the application of statistical tools and techniques for quantitative assessment of spiritual capital (SC) based on a questionnaire survey in the organizations which undergo large-scale organizational change projects. Design/methodology/approach – A sample of 65 individuals from three organizations were interviewed. The paper uses the 12 principles of transformation available to spiritual intelligence (referred to as SQ characteristics) to assess SC in a two-phase integrated algorithm of principal component analysis (PCA) and fuzzy clustering. Findings – The paper proposes a two-phase integrated algorithm. In the first phase, PCA is used to reduce the scores of items related to each of SQ characteristics and aggregate them into a single and unique measure. In the second phase, PCA is applied for total SQ quantification. For verification and validation, fuzzy clustering is employed along with PCA to cluster the people in the survey into different classes, which may possess different stocks of SC and rank them based on their level of SQ. The results of PCA are verified and validated by fuzzy clustering revealing the applicability and usefulness of PCA for SC quantification. Research limitations/implications – The paper is based on individual judgments about their own SQ characteristics hence the results of questionnaire survey may be biased by individual personal characteristics. Future research can apply the proposed algorithm and check for its reliability using other psychometric instruments available in the field. Originality/value – The paper contributes by filling a gap in the quantitative management tools literature, in which empirical studies on validated multivariate analysis of spirituality have been scarce until now.

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