Efficient model of cluster analysis as a segmentation strategy: inductive social responsibility of technological innovation in MYPES

Abstract

The present research aims to develop a rationalized framework for the analysis of conglomerates as a segmentation strategy of inductive social responsibility of technological innovation of the mypes of San Juan del Río-Querétaro. Mexico. A quantitative research method was used through surveys addressed to the directors or managers of the selected companies, accompanied by a qualitative approach by virtue of the nature of the survey. 11 items were considered, 5 were contemplated for Social Responsibility variable and 6 for Technological Innovation variable In stage 1 normality was assessed with Shapiro-Wilk, Anderson-Darling, Lilliefors and Jarque-Bera methods declaring non normality proceeding to develop the analysis of conglomerates. The stage 2 of the scale analysis which exhibited an elevated reliability level of 0.796 subsequently in stage 3 the conglomerate analysis was run with the Kaiser-Meyer- Olkin KMO and Bartlett tests of sampling adequacy with 0, 844 confirming that the adequacy of the sample for the investigation is very good and three conglomerates were determined. In stage 4 of dynamic analysis the forecast of the regression auto-econometric model with statistically significant parameters and the equation: Technological Innovation= 2.2470 - 0.0009 Anti discrimination policy + 0.6739 Reuse +0.4687 Listening needs +0.6576 Impact on customers - 2.0653 Confidentiality - 0.7829 Volunteering: According to Akaike's information criterion (AIC) = 2, 4232 this model has a good fit to the data, although the search can be continued of better models in subsequent research. Such as A. Hartono and R. Kusumawardhani confirm that the importance in innovation facing manufacturing firms is assessed the impact of barriers, when these are identified by factor process and conglomerates, it is possible to contribute to Mypes reducing uncertainty and the risks