Generating Insight into Optimizing the Interaction between Employees and Decision-Support Systems for Planning Related Activities (AI Planner of The Future Project 2) – Dow Inc.



Company Name / Department Dow Inc.
Contact Person Aram de Ruiter, Bao Lin, Kees Maton
Capacity Group (TU/e) IE&IS, Human Performance Management Group
Location Terneuzen, The Netherlands
Optional remote work TBD
Housing arranged by company TBD
Internship compensation  TBD
Study program Operations Management
ESCF community Full member
Start date February 2024

Company Description

Dow Inc.’s ambition is to become the most innovative, customer-centric, inclusive and sustainable materials science company. Our goal is to deliver value growth and best-in-class performance. The Company’s portfolio comprised of six global business units, organized into three operating segments: Performance Materials & Coatings, Industrial Intermediates & Infrastructure and Packaging & Specialty Plastics. Its products serve different applications, including coatings, home and personal care, durable goods, adhesives and sealants, and food and specialty packaging.


Project Description

Project description:

In order to improve operational performance, through innovation, DOW makes use of decision-support systems, that assist employees with decision-making for planning related activities. In this project, you will be analyzing user log-data (i.e., employees’ objective behaviors when interacting with these systems in a digital environment). Specifically, you will be interviewing managers, to make a classification of employee behaviors (e.g., favorable/unfavorable) when using these systems. Next you will be relating survey data (e.g., individual, technological, and organizational characteristics variables) of employees to these behaviors to objectively identify factors (e.g., employee profiles, contextual features) that improve adoption and righteous usage of decision-support systems at DOW.

Goals of the project:

Relevant insights into how, individual, technological, and organizational characteristics relate to more favorable (adoption) behaviors of employees, and practical recommendations that may increase the added-value of these systems at DOW.


    • An overview of how the abovementioned factors interact to predict adoption and performance when using these systems to;
    • Develop applicable recommendations for DOW as to improve adoption and performance of employees that can be implemented;
    • to be included in a Thesis Report.

    Essential student knowledge:

    • Analyzing of Big Data (user-logs) in Statistical Software, such as R, Python or MATLAB.
    • Some behavioral operations management, or work- and organizational psychology knowledge is a pre.
    • Some knowledge on, or willingness to learn social science analyses techniques is a pre as well.




    More information:  


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