Customer insurance frauds: the influence of fraud type, moral intensity and fairness perception

2019 ◽  
Vol 45 (3) ◽  
pp. 452-467 ◽  
Author(s):  
Lu-Ming Tseng
Keyword(s):  
Least Squares ◽  
Design Methodology ◽  
Partial Least Squares Regression ◽  
Empirical Investigation ◽  
Moral Intensity ◽  
Demographic Variables ◽  
Insurance Fraud ◽  
Least Squares Regression ◽  
Content Type ◽  
Fairness Perception

Purpose The purpose of this paper is to examine customers’ ethical attitudes (EA) and intentions toward two types of insurance frauds. This study proposes that the factors, such as fraud types (i.e. opportunistic and planned insurance fraud), moral intensity and fairness perception (FP), can affect the customers’ acceptance of the insurance frauds. Design/methodology/approach To test the research hypotheses of this study, Taiwanese insurance customers are invited in the empirical investigation, and a scenario-based questionnaire is used to collect the data. The hypotheses of this study are tested by using a partial least squares regression. Findings The results show that moral intensity constructs and FP significantly relate to the respondents’ acceptance of insurance frauds, while fraud types also have significant impacts on the respondents’ perceptions of moral intensity and fairness. Originality/value There is no research which has examined the relationships among fraud types, moral intensity, FP, demographic variables and customers’ EA and intentions toward insurance frauds. Understanding the relationships among these variables could provide implications for those involved in the practice of anti-fraud programs.

Empirical investigation of SMEs’ perceptions towards PLS financing in Morocco

2018 ◽  
Vol 11 (2) ◽  
pp. 250-273 ◽  
Author(s):  
Fairouz Badaj ◽  
Bouchra Radi
Keyword(s):  
Theory Of Planned Behaviour ◽  
Partial Least Squares Regression ◽  
Empirical Investigation ◽  
Research Model ◽  
Least Squares Regression ◽  
Policy Makers ◽  
Content Type ◽  
Intention To Adopt ◽  
Stage Of Development ◽  
The Family

PurposeThe main purpose of the study is to examine the willingness of Moroccan small- and medium-sized enterprises (SMEs) to adopt profit and loss sharing (PLS) method of finance and the factors that may influence their decision.Design/methodology/approachThe research model is based on the decomposed theory of planned behaviour (DTPB). A total of 340 questionnaires were randomly distributed to SMEs’ owner-managers, out of which 177 were collected and only 153 were valid for analysis. Factor analysis and partial least squares regression were subsequently applied.FindingsThe results showed that cost, loss of control, constrained access to conventional debt, financial suitability, stage of development as well as religious beliefs have a significant impact on the SMEs’ attitude towards PLS modes. Likewise, normative belief was also found to have a significant influence on subjective norm, by particular reference to the family, financial external consultants and internal managers, as the main referent groups. In addition, finally, attitude and perceived behavioural control were found to have a significant impact on the intention to adopt PLS financing by Moroccan SMEs.Research limitations/implicationsThe sample is not representative; hence, the findings cannot be generalized to all Moroccan SMEs. Furthermore, the variables and dimensions used are not exhaustive. With regard to implications, the study confirms the applicability of the DTPB to SME financing questions. Moreover, this study provides great indications to the practitioners, investors, policy makers and regulators on the perception of the Moroccan entrepreneurs, which should be taken into consideration to establish the necessary strategies to attract them.Originality/valueThis paper verifies the applicability of the DTPB in another area, that is, adoption of PLS instruments and contributes to explain the entrepreneurs’ perceptions towards theses modes of financing.

Continuous disclosure and information asymmetry

2015 ◽  
Vol 28 (2) ◽  
pp. 195-224 ◽  
Author(s):  
Mark Russell
Keyword(s):  
Information Asymmetry ◽  
Least Squares ◽  
Design Methodology ◽  
Ordinary Least Squares ◽  
Bad News ◽  
Least Squares Regression ◽  
Two Stage ◽  
Ordinary Least Squares Regression ◽  
Content Type ◽  
High Information

Purpose – This paper aims to examine whether firms with high information asymmetry disclose more information under a continuous disclosure regime, and, second, the paper examines whether continuous disclosures reduce information asymmetry. Design/methodology/approach – The study models relations between continuous disclosures and information asymmetry using ordinary least squares regression and two-stage least squares regression. Findings – The study finds firms with high information asymmetry disclose more information. Further, the study finds that disclosure in the presence of high information asymmetry increases asymmetry. Finally, while bad news increases information asymmetry, the disclosure of firm-specific good and bad news is associated with reduced information asymmetry. Originality/value – The paper identifies conditions under which Continuous Disclosure Regime increases information in markets and influences information asymmetry.

Effect of inter-organizational systems appropriation in agility and resilience development: an empirical investigation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Santanu Mandal ◽  
Ritesh Kumar Dubey
Keyword(s):  
Least Squares ◽  
Design Methodology ◽  
Dynamic Capabilities ◽  
Empirical Investigation ◽  
Organizational Systems ◽  
Content Type ◽  
Tourism Sector ◽  
Hotel Managers ◽  
The Impact

PurposeThis study explored the role of inter-organizational systems (IOS) appropriation in the form of five key IOS usage-based capabilities, namely, IOS use for communication, intelligence, integration, collaboration and coordination in the development of tourism SC agility and resilience. Furthermore, the inter-relationship among these IOS usage-based capabilities were explored.Design/methodology/approachThe study collected perceptual measures from hotel managers and tour managers having sufficient experience in the tourism sector. With 209 completed responses, the data were analyzed using partial least squares.FindingsThe study found IOS use of communication and intelligence as prominent enablers of IOS use for integration, collaboration and coordination. Furthermore, IOS use for integration, collaboration and coordination was found to have a prominent influence in the development of tourism SC agility and resilience. However, the influence of IOS use for communication on collaboration was not supported. Also, the impact of IOS use for collaboration in tourism resilience development was not supported.Originality/valueThe study is the foremost to explore the role of IOS appropriation in the development of dynamic capabilities like agility and resilience in tourism. Furthermore, the study also contributed to extant literature on IOS appropriation through suggesting two additional factors, namely, IOS use for collaboration and coordination to the existing IOS usage-based capabilities.

Use of reflectance spectroscopy to estimate the organic carbon and CaCO3 contents of soils

2012 ◽  
Vol 61 (2) ◽  
pp. 277-290 ◽  
Author(s):  
Ádám Csorba ◽  
Vince Láng ◽  
László Fenyvesi ◽  
Erika Michéli
Keyword(s):  
Organic Carbon ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Mean Squared Error ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Root Mean Squared Error ◽  
Squared Error

Napjainkban egyre nagyobb igény mutatkozik olyan technológiák és módszerek kidolgozására és alkalmazására, melyek lehetővé teszik a gyors, költséghatékony és környezetbarát talajadat-felvételezést és kiértékelést. Ezeknek az igényeknek felel meg a reflektancia spektroszkópia, mely az elektromágneses spektrum látható (VIS) és közeli infravörös (NIR) tartományában (350–2500 nm) végzett reflektancia-mérésekre épül. Figyelembe véve, hogy a talajokról felvett reflektancia spektrum információban nagyon gazdag, és a vizsgált tartományban számos talajalkotó rendelkezik karakterisztikus spektrális „ujjlenyomattal”, egyetlen görbéből lehetővé válik nagyszámú, kulcsfontosságú talajparaméter egyidejű meghatározása. Dolgozatunkban, a reflektancia spektroszkópia alapjaira helyezett, a talajok ösz-szetételének meghatározását célzó módszertani fejlesztés első lépéseit mutatjuk be. Munkánk során talajok szervesszén- és CaCO3-tartalmának megbecslését lehetővé tévő többváltozós matematikai-statisztikai módszerekre (részleges legkisebb négyzetek módszere, partial least squares regression – PLSR) épülő prediktív modellek létrehozását és tesztelését végeztük el. A létrehozott modellek tesztelése során megállapítottuk, hogy az eljárás mindkét talajparaméter esetében magas R2értéket [R2(szerves szén) = 0,815; R2(CaCO3) = 0,907] adott. A becslés pontosságát jelző közepes négyzetes eltérés (root mean squared error – RMSE) érték mindkét paraméter esetében közepesnek mondható [RMSE (szerves szén) = 0,467; RMSE (CaCO3) = 3,508], mely a reflektancia mérési előírások standardizálásával jelentősen javítható. Vizsgálataink alapján arra a következtetésre jutottunk, hogy a reflektancia spektroszkópia és a többváltozós kemometriai eljárások együttes alkalmazásával, gyors és költséghatékony adatfelvételezési és -értékelési módszerhez juthatunk.

Speech Emotion Recognition Based on Sparse Representation

2013 ◽  
Vol 38 (4) ◽  
pp. 465-470 ◽  
Author(s):  
Jingjie Yan ◽  
Xiaolan Wang ◽  
Weiyi Gu ◽  
LiLi Ma
Keyword(s):  
Dimensionality Reduction ◽  
Emotion Recognition ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Speech Emotion Recognition ◽  
Least Squares Regression ◽  
Computer Science Pedagogy ◽  
Reduction Methods ◽  
Analysis Computer

Abstract Speech emotion recognition is deemed to be a meaningful and intractable issue among a number of do- mains comprising sentiment analysis, computer science, pedagogy, and so on. In this study, we investigate speech emotion recognition based on sparse partial least squares regression (SPLSR) approach in depth. We make use of the sparse partial least squares regression method to implement the feature selection and dimensionality reduction on the whole acquired speech emotion features. By the means of exploiting the SPLSR method, the component parts of those redundant and meaningless speech emotion features are lessened to zero while those serviceable and informative speech emotion features are maintained and selected to the following classification step. A number of tests on Berlin database reveal that the recogni- tion rate of the SPLSR method can reach up to 79.23% and is superior to other compared dimensionality reduction methods.

scholarly journals Rapid tannin profiling of tree fodders using untargeted mid-infrared spectroscopy and partial least squares regression

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jordi Ortuño ◽  
Sokratis Stergiadis ◽  
Anastasios Koidis ◽  
Jo Smith ◽  
Chris Humphrey ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Multivariate Calibration ◽  
Plant Ecology ◽  
Coefficient Of Determination ◽  
Least Squares Regression ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

Abstract Background The presence of condensed tannins (CT) in tree fodders entails a series of productive, health and ecological benefits for ruminant nutrition. Current wet analytical methods employed for full CT characterisation are time and resource-consuming, thus limiting its applicability for silvopastoral systems. The development of quick, safe and robust analytical techniques to monitor CT’s full profile is crucial to suitably understand CT variability and biological activity, which would help to develop efficient evidence-based decision-making to maximise CT-derived benefits. The present study investigates the suitability of Fourier-transformed mid-infrared spectroscopy (MIR: 4000–550 cm−1) combined with multivariate analysis to determine CT concentration and structure (mean degree of polymerization—mDP, procyanidins:prodelphidins ratio—PC:PD and cis:trans ratio) in oak, field maple and goat willow foliage, using HCl:Butanol:Acetone:Iron (HBAI) and thiolysis-HPLC as reference methods. Results The MIR spectra obtained were explored firstly using Principal Component Analysis, whereas multivariate calibration models were developed based on partial least-squares regression. MIR showed an excellent prediction capacity for the determination of PC:PD [coefficient of determination for prediction (R2P) = 0.96; ratio of prediction to deviation (RPD) = 5.26, range error ratio (RER) = 14.1] and cis:trans ratio (R2P = 0.95; RPD = 4.24; RER = 13.3); modest for CT quantification (HBAI: R2P = 0.92; RPD = 3.71; RER = 13.1; Thiolysis: R2P = 0.88; RPD = 2.80; RER = 11.5); and weak for mDP (R2P = 0.66; RPD = 1.86; RER = 7.16). Conclusions MIR combined with chemometrics allowed to characterize the full CT profile of tree foliage rapidly, which would help to assess better plant ecology variability and to improve the nutritional management of ruminant livestock.

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