Consumption Patterns in the Relationship of Work Climate in Customer Service Considering Data Science Techniques (CPRWCCDST)

This multidisciplinary research project focuses on applying advanced data science techniques to examine the critical interconnection between consumption patterns, internal work climate, and customer service quality within Ecuadorian organizations. The central problem addressed is the lack of quantitative understanding of how these variables interact, which limits business capacity for trend anticipation and operational improvement. The methodological approach will be mixed, combining data collection via structured surveys (using QuestionPro) and semi-structured interviews, supplemented by automated data extraction (web scraping/APIs). Data will undergo rigorous preprocessing, including cleaning, qualitative coding (NLP/sentiment analysis), and normalization. Analysis will involve descriptive statistics, inferential statistics (regression, ANOVA), and the development of machine learning predictive models to assess the impact of work climate on satisfaction and consumption. The expected outcomes are practical recommendations for optimizing internal and external strategies, thereby improving operational efficiency and competitiveness. The central hypothesis posits that a positive work climate significantly impacts service quality, which in turn influences consumption patterns. The findings aim to contribute to Ecuador's economic and social development by providing actionable insights for businesses.<br/><br/><b>Goal</b>: <br/>To analyze the relationship between consumption patterns, work climate, and customer service in Ecuadorian organizations by applying data science techniques to identify patterns, trends, and correlations that impact business performance and social well-being.<br/><br/><b>Research lines</b>: <br/>Data science