Do Patterns of Levels of Faculty Effort Affect Overall Business School Performance? An Application of Profile Deviation Analysis

This paper aims to analyze the student dropout from a higher education course, in the city of Guarapari, Espírito Santo, Brazil, through the use of the computational tool known as data mining. The objective was to investigate the possible scenarios for the early identification of students with higher risk of dropping out by analyzing socioeconomic data from business school graduates between 2014 and 2018 with the use of information extracted from the academic system. The methodology used was the experimental research, from a quantitative approach through a comparative analysis of data resulting from the processing of computational algorithms. After the analysis, it was concluded that computational techniques can be used to help administrators to plan pedagogical and administrative actions and that the combination of socioeconomic data with school performance information, using the tool, can yield advantageous results, allowing the fight against evasion to be seen as an early and continuous practice.

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Customer satisfaction and corporate culture: A profile deviation analysis of a relationship marketing outcome

Psychology and Marketing ◽

10.1002/(sici)1520-6793(199710)14:7<663::aid-mar2>3.0.co;2-e ◽

1997 ◽

Vol 14 (7) ◽

pp. 663-674 ◽

Cited By ~ 17

Author(s):

Craig A. Conrad ◽

Gene Brown ◽

Harry A. Harmon

Keyword(s):

Customer Satisfaction ◽

Relationship Marketing ◽

Corporate Culture ◽

Deviation Analysis ◽

Profile Deviation

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University strategic marketing activities and business school performance

Marketing Intelligence & Planning ◽

10.1108/02634500410568565 ◽

2004 ◽

Vol 22 (7) ◽

pp. 732-741 ◽

Cited By ~ 5

Author(s):

Kevin Hammond ◽

Harry Harmon ◽

Robert Webster ◽

Mike Rayburn

Keyword(s):

School Performance ◽

Business School ◽

Strategic Marketing ◽

Marketing Activities

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Examining the relationship between patient experience and readmission rates: A profile deviation analysis

Health Services Management Research ◽

10.1177/0951484820987499 ◽

2021 ◽

pp. 095148482098749

Author(s):

Sidney Anderson

Keyword(s):

Patient Experience ◽

Hospital Readmissions ◽

Empirical Support ◽

Hospital Performance ◽

Central Component ◽

Readmission Rates ◽

Deviation Analysis ◽

Profile Deviation ◽

Significant Difference ◽

The Relationship

The purpose of this study is to examine the relationship between patient experience and readmissions by exploring whether the deviation from an ideal patient-experience profile is linked to higher readmissions. Using patient experience scores, hospitals were assigned to one of four groups based on their deviation from an ideal profile. The readmission rates for the four groups were analyzed using Profile Deviation, ANOVA, and Least Significant Difference. Patient experience is a central component of hospital performance, specifically, readmission rates. Findings indicate as patient experience scores decrease, profile deviation increases, with a corresponding increase in readmission rate. This study provides empirical support for administrators focusing on patient experience as part of an overall strategy for reducing hospital readmissions. The key feature of this research is the use of a profile deviation methodology to examine the relationship between patient experience and readmission rates.

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