Essays 2018: Multivariate Analysis with a Dependent Focus in Management Sciences as a Basis for Innovation

The present work, "Essays 2018: Multivariate Analysis with a Dependent Approach in the Management Sciences as a Basis for Innovation," aims to bring together a series of essays written by students of the Doctorate in Management Sciences (DCA) at the University Center for Economic and Administrative Sciences (CUCEA) of the University of Guadalajara (UdeG), based on what they have learned in the Quantitative Research I course.

These essays are initially aimed at conducting a dissertation exercise that reinforces either their thesis or serves as a contribution to the subject, highlighting the relevance of their writing, conceptualizing, and proposing the reviewed models as a development of their dissertation. This serves as a basis for conducting discussions that clarify the expected contribution and, ultimately, concluding on essential points that serve both the reader and the presenter for further studies.

Thus, this work is divided into ten essays. The first essay, "Predictive Multivariate Analysis Tools and Data Mining with SPSS Modeler and Statistic: A Comparative Study," represents an excellent opportunity for the reader to become familiar with the SPSS software, the most widely used tool in social and health sciences regarding inferential statistical tools, with its contribution being very valuable in terms of the specific scope of each version of SPSS.

The second contribution, "The Importance of Simple Linear Regression Technique in the Field of Economic-Administrative Sciences," is a great reference to the utility represented by parametric projection techniques based on linear regression, demonstrating its current use through extensive bibliometric study and its opportunity for use in economic-administrative sciences.

The third essay, "Software as Tools for Strategic Prospective Methods: MICMAC," presents valuable justifications and relevant bases on how to conduct prospective studies with this software, clarifying the scope of additional computer tools that allow specifying possible, probable, and desirable future scenarios through: MACTOR, MORPHOL, MULTIPOLAR, and SMIC.

Regarding the fourth work, "Comparative Analysis between Multiple Linear Regression and Partial Least Squares and its Application in Economic-Administrative Sciences," its value in making comparative analyses that allow readers to understand the scope and impacts of both techniques when determining usage recommendations in the field is highlighted, with partial least squares technique gaining sustained importance.

The fifth essay, "Applied Linear Regression: Analysis of Corporate Social Responsibility," shows its relevance by conducting a broad and in-depth bibliometric analysis of the contributions of linear regression technique in the field of corporate social responsibility, comparing four related models and discussing the impact of the discovered variables.

The sixth work, "Multivariate Analysis Techniques for Validating a Conceptual Model of Transformation from Linear to Exponential Organization," reveals the importance of its contribution by verifying previous exponential organization models in which the variables discussed so far are exposed to make an original proposal for a new model based on constructs resulting from the review of the state of the art.

The seventh work, "Correlation of Competitiveness Variables through the Application of Dependent Multivariable Analysis Techniques (Multiple Linear Regression)," makes a dissertation on the various models that address competitiveness through a broad and in-depth bibliometric analysis that allows comparing six models with their corresponding variables and discussing the proposal of an original model as a result.

The eighth essay, "Multivariate Analysis as a Tool for Measuring Human Resources Management Processes and Knowledge Management and its Relationship with Innovation," is based on extensive and in-depth bibliometric analysis showing the opportunity to contribute to the relationships between various human resources management processes and knowledge management in innovation through an original proposal based on previously published models in this regard.

The ninth work, "The Use of Multivariate Statistical Techniques through Discriminant Analysis, Applied in Business, Companies, and Organizations in General," meets the challenge of discussing models and variables that explain the relationships present in businesses, companies, and organizations from a financial point of view, hence the value represented by the proposal of this essay.

The tenth essay, "Scientific Research in HR: The Challenge Professionals Must Face," informs about the opportunity in the field of human resources to propose models that allow discovering the main determinants explaining the various relationships to which individuals are subjected, based on multivariate analysis.

It is the desire of the coordination of this work that it contributes to the reader's enthusiasm for knowing the projects being developed and informing about the opportunities presented, with the aim of monitoring their evolution during their stay in the postgraduate program.