scholarly journals Is Gastronomy A Relevant Factor for Sustainable Tourism? An Empirical Analysis of Spain Country Brand

2019 ◽  
Vol 11 (9) ◽  
pp. 2696 ◽  
Author(s):  
Ulpiano J. Vázquez-Martinez ◽  
Carlos Sanchís-Pedregosa ◽  
Antonio L. Leal-Rodríguez
Keyword(s):  
Economic Growth ◽  
Least Squares ◽  
Partial Least Squares ◽  
Place Branding ◽  
Structural Equations ◽  
Relevant Factor ◽  
Key Factors ◽  
Data Set ◽  
It Impacts ◽  
Country Brand

Tourism has become a fundamental industry for the economic growth of many countries. Due to this, there is growing competitiveness among the different destinations to attract as many tourists as possible. As a result, disciplines such as marketing have developed tools to differentiate some destinations from others and concepts such as place branding and country brand have emerged. One of the key factors forming the country brand is gastronomy, as food tourism is one way to reduce the growing problem of sustainability in tourism, as it impacts different aspects of the country’s environment. However, there is a great lack of scientific works that relate both variables. In this paper, we propose to establish that, in the case of Spain, tourists’ perception of Spanish gastronomy is a key element of its country brand. To do that, this study relies on the use of Partial Least Squares Structural Equations Modeling (PLS-SEM) using a 496 cases data set.

scholarly journals Do Innovation and Cooperation Influence SMEs’ Competitiveness? Evidence From the Andalusian Metal-Mechanic Sector

Innovar ◽  
2015 ◽  
Vol 25 (55) ◽  
pp. 101-115
Author(s):  
Juan A. Tamayo ◽  
José E. Romero ◽  
Javier Gamero ◽  
Juan A. Martínez-Román
Keyword(s):  
Quality Management ◽  
Least Squares ◽  
Partial Least Squares ◽  
Positive Influence ◽  
Structural Equations ◽  
Financial Resources ◽  
Management Knowledge

This study's main objective is to determine the influence of innovation and cooperation on the competitiveness of SMEs in the metal-mechanic sector of Andalusia (Spain). Using information obtained by interviewing managers of a sample of 80 firms, we proposed a model of structural equations based on the Partial Least Squares (PLS) technique. This model, which explained 37% of the variability of competitiveness, also allowed us to test hypotheses about the positive influence of quality management, knowledge, financial resources and cooperation on innovative outcomes. Along with the contrasted hypotheses, the most noteworthy finding was that cooperation does not significantly influence the innovative outcomes of firms in this sector.

scholarly journals Structural equation models - PLS in engineering sciences: a brief guide for researchers through a case applied to the industry

Athenea ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 5-18
Author(s):  
Juan Enrique Villalva A.
Keyword(s):  
Structural Equation Modeling ◽  
Least Squares ◽  
Partial Least Squares ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Structural Equations ◽  
Partial Least Square ◽  
Equation Modeling ◽  
Engineering Sciences ◽  
The Impact

Modeling using structural equations, is a second generation statistical data analysis technique, it has been positioned as the methodological options most used by researchers in various fields of science. The best known method is the covariance-based approach, but it presents some limitations for its application in certain cases. Another alternative method is based on the variance structure, through the analysis of partial least squares, which is an appropriate option when the research involves the use of latent variables (for example, composite indicators) prepared by the researcher, and where it is necessary to explain and predict complex models. This article presents a brief summary of the structural equation modeling technique, with an example on the relationship of constructs, sustainability and competitiveness in iron mining, and is intended to be a brief guide for future researchers in the engineering sciences. Keywords: Competitiveness, Structural equations, Iron mining, Sustainability. References [1]J. Hair, G. Hult, C. Ringle and M. Sarstedt. A Primer on Partial Least Square Structural Equation Modeling (PLS-SEM). California: United States. Sage, 2017. [2]H. Wold. Model Construction and Evaluation when Theoretical Knowledge Is Scarce: An Example of the Use of Partial Least Squares. Genève. Faculté des Sciences Économiques et Sociales, Université de Genève. 1979. [3]J. Henseler, G. Hubona & P. Ray. “Using PLS path modeling new technology research: updated guidelines”. Industrial Management & Data Systems, 116(1), 2-20. 2016. [4]G. Cepeda and Roldán J. “Aplicando en la Práctica la Técnica PLS en la Administración de Empresas”. Congreso de la ACEDE, Murcia, España, 2004. [5]D. Garson. Partial Least Squares. Regresión and Structural Equation Models. USA. Statistical Associates Publishing: 2016. [6]D. Barclay, C. Higgins & R. Thompson. “The Partial Least Squares (PLS) Approach to Causal Modeling: Personal Computer Adoption and Use as an Illustration”. Technology Studies. Special Issue on Research Methodology. (2:2), pp. 285-309. 1995. [7]J. Medina, N. Pedraza & M. Guerrero. “Modelado de Ecuaciones Estructurales. Un Enfoque de Partial Least Square Aplicado en las Ciencias Sociales y Administrativas”. XIV Congreso Internacional de la Academia de Ciencias Administrativas A.C. (ACACIA). EGADE – ITESM. Monterrey, México, 2010. [8]J. Medina & J. Chaparro. “The Impact of the Human Element in the Information Systems Quality for Decision Making and User Satisfaction”. Journal of Computer Information Systems. (48:2), pp. 44-52. 2008. [9]D. Leidner, S. Carlsson, J. Elam & M. Corrales. “Mexican and Swedish Managers’ Perceptions of the Impact of EIS on Organizational Intelligence, Decisión Making, and Structure”. Decision Science. (30:3), pp. 633-658. 1999.[10]W. Chin. “The partial least squares approach for structural equation modeling”. Chapter Ten, pp. 295-336 in Modern methods for business research. Edited by Macoulides, G. A., New Jersey: Lawrence Erlbaum Associates, 1998. [11]M. Höck & C. Ringle M. “Strategic networks in the software industry: An empirical analysis of the value continuum”. IFSAM VIIIth World Congress, Berlin 2006. [12]J. Henseler, Ch. Ringle & M. Sarstedt. Handbook of partial least squares: Concepts, methods and applications in marketing and related fields. Berlin: Springer, 2012. [13]S. Daskalakis & J. Mantas. “Evaluating the impact of a service-oriented framework for healthcare interoperability”. Studies in Health Technology and Informatics. pp. 285-290. 2008. [14]C. Fornell & D. Larcker: “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error”, Journal of Marketing Research, vol. 18, pp. 39-50. Februay 1981. [15]C. Fornell. A Second Generation of Multivariate Analysis: An Overview. Vol. 1. New York, U.S.A. Praeger Publishers: 1982. [16]R. Falk and N. Miller. A Primer for Soft Modeling. Ohio: The University of Akron. 1992. [17]M. Martínez. Aplicación de la técnica PLS-SEM en la gestión del conocimiento: un enfoque técnico práctico. Revista Iberoamericana para Investigación y el Desarrollo Educativo. Vol. 8, Núm. 16. 2018. [18]S. Geisser. “A predictive approach to the random effects model”. Biometrika, Vol. 61(1), pp. 101-107. 1974. [19]J. Cohen. Statistical power analysis for the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum, 1988. [20]GRI (2013). G4 Sustainability Reporting Guidelines. Global Reporting Initiative. Available: www.globalreporting.org

scholarly journals Analysing the effects of strategic assets on company success : an evidence in manufacturing company

2018 ◽  
Vol 7 (2.10) ◽  
pp. 102
Author(s):  
Sarminah Samad ◽  
Hazaz Abdullah Alsolami
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Significant Role ◽  
Manufacturing Industry ◽  
Future Research ◽  
Manufacturing Companies ◽  
Key Factors ◽  
Factors Influencing ◽  
Strategic Assets ◽  
The Relationship

Manufacturing industry plays a significant role in the development of a nation. Thus, analyzing the factors influencing its success is profoundly needed. Scholars have identified strategic assets as a key factors that influence the success of manufacturing companies. This study examined the relationship between strategic assets on company success. 400 manufacturing companies in Malaysia have participated in the survey.  A total of 299 usable questionnaires were analyzed using Smart Partial Least Squares (PLS). The results revealed that manufacturing companies should consider increasing their strategic assets to achieve superior success. This suggests that strategic assets are crucial towards improving company success. The results found that intangible assets have emerged as the most significant predictor that affect company success. The implications of this study and recommendations for future research are also discussed.  

Characterization and analysis of soils using mid-infrared partial least-squares .2. Correlations with some laboratory data

Soil Research ◽  
1995 ◽  
Vol 33 (4) ◽  
pp. 637 ◽  
Author(s):  
LJ Janik ◽  
JO Skjemstad
Keyword(s):  
Soil Properties ◽  
Least Squares ◽  
Partial Least Squares ◽  
Analytical Data ◽  
Quantitative Information ◽  
Data Set ◽  
Qualitative And Quantitative ◽  
Organic Components ◽  
Pls Analysis ◽  
Pls Method

Infrared partial least squares (PLS) analysis is shown to provide a simple, rapid chemometric technique for the simultaneous analysis of soil properties. The method is capable of extracting both qualitative and quantitative information from soil spectra. A number of the mineral and organic components which are responsible for certain soil properties have been identified and the prediction of these properties assessed. Diffuse reflectance infrared Fourier-transform (DRIFT) spectra of whole soils were recorded to form a large training data set. The spectral information from this set was compressed into a small number of subspectra (called weight loadings) which contained positive and negative peaks reflecting correlations between the soil mineral and organic components and corresponding analytical data. Positive peaks in the weight loadings corresponding to organic components including alkyl, carboxylic and amide species were highly correlated with OC and N. Likewise, smectite, kaolinite and gibbsite clay minerals, together with organic alkyl and carboxylic species, contributed either positively or negatively to pH, sum of cations and clay content. Positive peaks due to calcite were well resolved in the first carbonate weight loading. Quartz was identified as an 'interference' for all analyses, with a series of negative peaks in the weight loadings. Implications were that quartz exerted a strong spectral signal for the majority of soil spectra, although it was not directly related to particular analyses. The usual PLS method, in which there is assumed to be a linear relationship between the loading intensities and soil property values, was found to give nonlinear prediction regression. The nonlinearity was assumed to be due to the effects of nonlinear response of the DRIFT signal and to significant compositional variability between calibration samples with high and low analyte concentrations. An alternative strategy of using a locally linear PLS model was tested, where small subsets of the total span of analytical values were independently used for PLS analysis. This approach improved prediction linearity and precision improved significantly for most analyses. The PLS method was thus shown to provide a useful surrogate technique for the study of soils, with which the PLS analysis of a single spectrum could provide simultaneous qualitative and quantitative information on a number of widely different soil analyses.

scholarly journals Corticomuscular Activity Modeling by Combining Partial Least Squares and Canonical Correlation Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Xun Chen ◽  
Aiping Liu ◽  
Z. Jane Wang ◽  
Hu Peng
Keyword(s):  
Correlation Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Medical Knowledge ◽  
Data Sets ◽  
Data Set ◽  
Activity Modeling ◽  
Multiple Data Sets

Corticomuscular activity modeling based on multiple data sets such as electroencephalography (EEG) and electromyography (EMG) signals provides a useful tool for understanding human motor control systems. In this paper, we propose modeling corticomuscular activity by combining partial least squares (PLS) and canonical correlation analysis (CCA). The proposed method takes advantage of both PLS and CCA to ensure that the extracted components are maximally correlated across two data sets and meanwhile can well explain the information within each data set. This complementary combination generalizes the statistical assumptions beyond both PLS and CCA methods. Simulations were performed to illustrate the performance of the proposed method. We also applied the proposed method to concurrent EEG and EMG data collected in a Parkinson’s disease (PD) study. The results reveal several highly correlated temporal patterns between EEG and EMG signals and indicate meaningful corresponding spatial activation patterns. In PD subjects, enhanced connections between occipital region and other regions are noted, which is consistent with previous medical knowledge. The proposed framework is a promising technique for performing multisubject and bimodal data analysis.

scholarly journals Wine aging authentication through Near Infrared Spectroscopy: a feasibility study on chips and barrel aged wines

OENO One ◽  
2020 ◽  
Vol 54 (1) ◽  
pp. 165-173
Author(s):  
Tiziana Nardi ◽  
Maurizio Petrozziello ◽  
Raffaele Girotto ◽  
Michele Fugaro ◽  
Raffaele Antonio Mazzei ◽  
...  
Keyword(s):  
Data Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Aging Process ◽  
Near Infrared ◽  
Research Centre ◽  
Electromagnetic Spectrum ◽  
Method Performance ◽  
Data Set ◽  
Wine Aging

Aim: This research primarily focuses on exploring the suitability of near infrared (NIR) spectroscopy with multivariate data analysis as a tool to classify commercial wines depending on the aging process. It is aimed at discriminating between wines aged in barrels and those obtained using alternative products (chips).Methods and Results: Around 75 commercial barrel-aged red wines issued from the appellation “Valpolicella” (Italy) were analyzed. Moreover, 15 wines were aged at the experimental winery of the Research Centre of Viticulture and Enology in Asti using different types of commercial oak chips. Wines were analyzed in transmittance using NIR regions of the electromagnetic spectrum. Principal component analysis (PCA) and partial least squares (PLS) analyses were used to classify wines: a preliminary step was carried out using PCA that showed interesting groups in the whole data set. Next, in order to test if combined explanatory variables made it possible to discriminate treatments and how they are useful to predict which group a new observation will belong to, an orthogonal partial least squares discriminant analysis (OPLS-DA) was carried out. Several wine groups were considered, defined by factors including the aging process, the type of oak used for aging (wood barriques, barrels or chips) and the wine typologies (differing for some enological parameters).Conclusions: Overall, OPLS-DA models correctly classified >90 % of the wines. These results demonstrate the potential of combining spectroscopy with chemometric data analysis as a rapid method to classify wines according to their aging process. Nevertheless, the development of a mathematical model for predictive purposes is a complex task: indeed, large databases for different wines should be constructed, and other spectral IR zones might be evaluated for improving the method performance in determining wine aging process.Significance and impact of the study: This study contributes to the development of an easy-to-use and easily applicable NIR method for correlating the infrared “fingerprint” spectrum with the aging process in wines, aimed at implementing a technique able to discriminate wines aged with different wood types, that can be progressively used in the laboratory for routine fraud inspection.

scholarly journals Gestión equitativa, fuente de empoderamiento personal y compromiso afectivo

2019 ◽  
Vol 17 (3) ◽  
Author(s):  
Alberto Díaz Rosillo ◽  
Arístides Alfredo Vara Horna ◽  
Zaida Asencios González ◽  
Raquel Chafloque Céspedes ◽  
Inés Santi Huaranca
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Structural Equations ◽  
Work Life ◽  
Personal Life ◽  
Research Article ◽  
Working Groups ◽  
The Relationship

This research article aims to establish whether equitable management by managers improves the personal role of their employees thanks to the skills acquired in the work and if this improvement of the personal role could mediate the relationship between equitable management and identification with the company. The method used was a self-reported questionnaire to 19 working groups led by a manager, 398 women and 413 men. Structural equations by partial least squares (SEM-PLS) are applied. Results: the equitable behavior of the managers favors the personal life of the employees although the relationship and its intensity are not high. The models with a mediating variable of work-life enrichment explain the relationship between an equitable management with the identification with the company. Other results and differences between sexes and the gender of the manager are discussed.RESUMENEste artículo de investigación pretende establecer si la gestión equitativa por parte de los gerentes mejora el rol personal de sus empleados gracias a las habilidades adquiridas en el trabajo y si esta mejora del rol personal pudiera mediar la relación entre la gestión equitativa y la identificación con la empresa. El método empleado fue un cuestionario auto-informado a 19 grupos de trabajo dirigidos por un gerente/a, 398 trabajadoras y 413 trabajadores. Se aplican ecuaciones estructurales por mínimos cuadrados parciales (SEM-PLS). Resultados: la conducta equitativa de los gerentes favorece la vida personal de los/las empleados, aunque la relación y su intensidad no son elevados. Los modelos con variable mediadora de enriquecimiento laboral – vida personal explican en mayor medida la relación entre una gestión equitativa con la identificación con la empresa. Se discuten otros resultados y las diferencias entre sexos y el sexo del gerente.RESUMOEste artigo de pesquisa visa estabelecer se a gestão eqüitativamente pelos gerentes melhora o papel pessoal de seus trabalhadores graças às habilidades adquiridas no trabalho e se essa melhoria do papel pessoal poderia mediar a relação entre gestão equitativa e identificação com a empresa. Método: questionário auto-relatado para 19 grupos de trabalho liderados por um gestor, 398 trabalhadores homens e 413 trabalhadores mulheres. Equações estruturais são aplicadas por mínimos quadrados parciais (SEM-PLS). Resultados: o comportamento equitativo dos gerentes favorece a vida pessoal dos trabalhadores, embora o relacionamento e sua intensidade não sejam altos. Modelos com uma variável mediadora de enriquecimento do trabalho - vida pessoal explicam em maior grau a relação entre a gestão equitativa e a identificação com a empresa. Outros resultados e diferenças entre os sexos e o gênero do gerente são discutidos.

A Calibration Tutorial for Spectral Data. Part 2. Partial Least Squares Regression Using Matlab and Some Neural Network Results

1996 ◽  
Vol 4 (1) ◽  
pp. 243-255 ◽  
Author(s):  
Paul Geladi ◽  
Harald Martens ◽  
Lubomir Hadjiiski ◽  
Philip Hopke
Keyword(s):  
Neural Network ◽  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variable ◽  
Degree Of Approximation ◽  
Successive Approximations ◽  
Data Set ◽  
Calibration Methods ◽  
Data Pretreatment ◽  
Latent Variable Regression

Part 1 explained multiplicative scatter correction (MSC), the building of a principal component regression (PCR) model and how the test data can be used in prediction. Emphasis was on data pretreatment for linearistion and on spectral/chemical interpretation of the results. Part 2 discusses partial least squares (PLS or PLSR) regression. The data set prepared in Part 1 is also used here. Details on data pretreatment are, therefore, not repeated. Some details of PLS modeling are explained using the calculations of the example. Also, the interpretation of the PLS model gets some attention. Neural network calculation results are included for comparison. Artifical neural networks (ANN) are non-linear, so linearisation is not considered necessary. Latent variable regression methods such as PLS and PCR and ANNs are all successive approximations to the unknown function y = f(x) that forms the basis of all calibration methods. In latent variable regression, the rank of the model determines the degree of approximation. In ANNs, the number of hidden nodes and the number of iterations determine the degree of approximation.

scholarly journals Predicting and Explaining the Acceptance of Social Video Platforms for Learning: The Case of Brazilian YouTube Users

2019 ◽  
Vol 11 (24) ◽  
pp. 7115
Author(s):  
Patricio Ramírez-Correa ◽  
Ari Mariano-Melo ◽  
Jorge Alfaro-Pérez
Keyword(s):  
Developing Countries ◽  
Social Influence ◽  
Least Squares ◽  
Partial Least Squares ◽  
Predictive Power ◽  
Structural Equations ◽  
Research Model ◽  
Structural Equations Modeling ◽  
Perception Of Performance

This study aims to predict and explain the acceptance of social video platforms for learning. A research model is proposed that explains that the intention of using these platforms is based on the perception of performance, social influence, and hedonic motivation. To validate the model, 568 Brazilian YouTube users were surveyed. The data were analyzed with partial least squares structural equations modeling (PLS-SEM). In particular, the predictive power of the model was assessed using the PLSpredict procedure. The results of this study can help to understand and forecast the use of these platforms for learning in developing countries.

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