Management Sciences and Multivariate Analysis: Research Projects, Analysis, and Discussion of Results Volume II: Interdependent Techniques

Authors

Juan Mejía-Trejo
Universidad de Guadalajara, Jalisco, México
https://orcid.org/0000-0003-0558-1943

Keywords:

Administración, Análisis Multivariante, Técnicas interdependientes

Synopsis

With greater capabilities and availability of computing resources today, multivariate analysis is now featured in various software applications, increasing its use across multiple disciplines such as Administrative Sciences. Some of the most widely used models in academic and professional fields worldwide include Statistical Package for the Social Sciences (SPSS, by IBM), Analytics, Business Intelligence and Data Management (SAS, by SAS Institute and/or World Programming), Statistica (by STATISTICA), and the R language (open-source software), to name a few. It is not surprising that Administrative Sciences support academic development in various postgraduate programs as well as in the professional realm related to Social Sciences. Consequently, there is a growing trend in the presentation of reports, articles, book chapters, or books that discuss various theoretical-empirical aspects and their interpretation based on these software applications. In our case, we have adopted IBM's SPSS 20 for developing the topics in this book.

Based on the above, we present the work: Administrative Sciences and Multivariate Analysis under the approach of Interdependent Techniques. Research Projects, Analysis, and Discussion of Results. Volume II, with the recommendation to have previously read the first three chapters of Volume I. The main objectives are:

  1. To present a document that serves both those familiar and unfamiliar with the topic, who need to understand the concepts discussed in this volume and manipulate the various commands offered by IBM's SPSS 20 regarding the problem cases presented as examples.

  2. For better comprehension of the treatment of cases, the sequence proposed by Hair et al. (1999) of the six steps: objectives, design, assumptions, execution, interpretation, and validation, is used as the framework for presenting and solving these cases.

  3. As the Coordinator of the Doctorate in Administrative Sciences at the Centro Universitario de Ciencias Económico Administrativas (CUCEA) of the University of Guadalajara (UdG), to present the base book for the course Quantitative Methods I and II.

The author hopes to contribute to the reader's acquisition of knowledge that can be applied in the practical world and aid in its theoretical interpretation. If not, it is hoped that at least it serves as another useful step towards achieving their academic and/or professional formation.

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Author Biography

Juan Mejía-Trejo, Universidad de Guadalajara, Jalisco, México

Dr. Juan Mejía Trejo
He is born in 1964 in CDMX, México.
As professional experience:
1986-1987. Quality Department Control in KOKAI Electrónica S.A.
1987-2008. Former Internal Plant Exploitation Manager at Teléfonos de México S.A.B. Western Division.
As academic experience :
1987. He earned his degree in Communications and Electronics Engineering from the Escuela Superior de Ingeniería Mecánica y Eléctrica, Instituto Politécnico Nacional (ESIME at the IPN)
2004. He earned his master’s in Telecommunications Business Administration from INTTELMEX and France Telecom.
2010. He earned his doctorate in Administrative Sciences from the Escuela Superior de Comercio y Administración (ESCA at the IPN)
2011.He is a member of the Sistema Nacional de Investigadores (SNI) Level I of the Consejo Nacional de Ciencia y Tecnología (CONACYT) , México.
2010 to the present, he is Titular Research Professor B at the Department of Marketing and International Business at the Universidad de Guadalajara, México.
2018-2020. He earned his master’s in Valuing Business in the Centro de Valores S.C. México.
2019.He earned Level II of the SNI/CONACYT
2015-2022.He earned the Coordination of the Doctorate in Management Sciences at the Universidad de Guadalajara.

Currently, he is the founder of the AMIDI (Academia Mexicana de Investigacion y Docencia en Innovación SC) (https://amidi.mx/) as well as founder and editor-in-chief of the scientific journal Scientia et PRAXIS (https://scientiaetpraxis .amidi.mx/index.php/sp)
https://orcid.org/0000-0003-0558-1943

His line of research is Innovation Management, publishing articles and books that can be found on the Internet.
Email: jmejia@cucea.udg.mx

References

Anderson, J. C., Gerbing, D. W. y Hunter J. E. (1987), On the Assessment of Unidimensional Measurement: Internal and External Consistency and Overall Consistency Criteria. Journal of Marketing Research 24 (November): 432-37.

American Psychological Association (1985), Standards for Educational and Psychological Tests. Washington, D.C.: APA.

Bearden, W. 0., Netemeyer, R. G. y Mobic M. ( 1993), Handbook of Marketing Sea!es: Multi-ltem Measures for Marketing and Consumer Behavior. Newbury Park, Calif.: Sage.

Bentler, Peter M. (1992), EQS Structural EquationsProgram Manual. Los Angeles: BMDP Statistica1Software.

BMDP Statistical Software, Inc. ( 1992), BMDP Statistical Software Manual, Release 7, vols. 1 and 2,Los Angeles: BMDP Statistical Software.

Borgatta, E. F., Kercher, K. y Stull D. E. ( 1986), A Cautionary Note on the Use of Principal Components Analysis. Sociological Methods and Research 15:160- 68.

Bruner, G. C., y Hensel P. J. (1993). Marketing Scales Handbook, A Compilation of Multi- ltem Measures. Chicago: American Marketing Association.

Campbell, D. T., y Fiske D. W. (1959). Convergentand Discriminant Validity by the Multitrait Multimethod Matrix. Psychological Bulletin 56 (March): 81-105.

Cattell, R. B. (1966), The Scree Test for the Number of Factors. Multivariate Behavioral Research 1 (April): 245-76.

Cattell, R. B., Balear, K. R. Horn, J. L. y Nesselroade, J. R. ( 1969), Factor Matching Procedures: An Improvement of the s index; with tables. Educational and Psychological Measurement 29: 781-92.

Chatterjee, S., Jamieson, L. y Wiseman F. (1991), ldentifying Most Influential Observations in Factor Analysis. Marketing Science 10 (Spring): 145-60.

Churchill, G. A. (1979), A Paradigm for Developing Better Measures of Marketing Constructs. Journal of Marketing Research 16 (February): 64-73.

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Published

December 30, 2017

Details about this monograph

ISBN-13 (15)

978-607-742-774-2

doi

10.55965/abib.9786077427742.2017b