Interactive Management App

The Interactive Management App project will design and build an open source tool for conducting Interpretive Structural Modeling (ISM) research with participants

Table of Contents

• Background
• Install
• Research
• Requirements
• Core Action

Background

This is an Open Community Research Accelerator (ORCA) project at the University of Vermont. The objective of this project is to design and build an open source browser-based tool for conducting Interpretive Structural Modeling (ISM) research with participants. It includes a series of questions about pairs of variables (called "factors") and whether or not those factors are related to one another. The software will produce a flow diagram of the relationships between factors as identified by the participant, and provide the researchers with one flow diagram that averages the data across all participants in a particular study. The flow diagram will suggest factors that are likely more effective to address first, and factors that are likely to follow or become easier to address as a result of addressing earlier factors.

ISM is one of a number of core methodologies that groups and teams can benefit from when working to address complex problems. The hope is that a web-based version can increase accessibility for communities and organizations to use ISM in fostering collective intelligence for informing social transformation.

Interpretive Structural Modeling (ISM) is a method for representing and analyzing complex systems. It was developed by J. Warfield in 1973 and has been used in a variety of fields, including business, engineering, education, and healthcare.

The method builds a flowchart of the relationships between variables that influence a desired outcome for a system, like “a sustainable environment” or “an inclusive workplace.” It does this by creating a network that represents the relationships between the variables that affect a system. The nodes in the network represent factors, and the arrows (called “directed ties” or “directed edges” in network terminology) represent the relationships between the factors. The direction of the edge indicates the direction of the influence.

ISM uses a four-step process to develop a model of a system:

• Identify the factors that affect the system. This step uses a survey of participants to gather a list of factors that affect a specified outcome for the system.
• Ranking the factors. In this step, a researcher groups factors from the surveys that are similar. Then, they pick the most important factors mentioned by the participants for the participants to keep working with.
• Determine the relationships between the factors. This step involves asking one participant or a group of participants the question "Does factor A influence factor B?" for each possible relationship and recording the answer as a directed edge in the network.
• Construct the flowchart. This step uses a network node ordering algorithm to identify factors (the nodes) that come before each other in solving the problem. It then displays the ordered network as a flowchart with factors that come first farthest to the left.

Here are some of the benefits of using ISM:

• It is a visual method that is easy to understand and communicate.
• It can be used to model complex systems.
• It can be used to identify the key elements of a system and the relationships between them.
• It can be used to identify potential problems in the system and to develop strategies for improving the system.

Here are some of the limitations of ISM:

• It is a subjective method that depends on the judgment of the people involved in the modeling process.
• It can be time-consuming and labor-intensive to develop an ISM model.
• It can be difficult to validate the results of an ISM model.

UVM

Install

Running locally

These instructions are designed for MacOS & GNU/Linux users.
Windows users: Using WSL (Windows Subsystem for Linux) is recommended.

Requirements

Install the following tools using their instructions:

• pyenv- Python version manager
• nvm - Node version manager

Running locally

Email Recovery For email recovery please create an email account and fill out the required fields on the .env file

Setup pyenv & nvm

# Python
pyenv install # If the version already exists, no need to re-install
# Node.js
nvm install

Install dependencies

# Python
pip install -r requirements.txt
# Node.js
corepack install # Sets up npm
npm install

Run the app

python wsgi.py --port=5001 --host=localhost --debug

Then visit http://localhost:5001

Python Anywhere

To access this app from the web, visit https://interactivemanagement.pythonanywhere.com/

Future documentation/updating the app on pythonyanywhere:

• Ensure the main branch on the repo has the latest changes that you want.
• Go to the Consoles tab on pythonanywhere and start a new bash console. Navigate to the "Interactive-Management-App" directory.
• run "git pull origin main"
• Update .env file with password email credentials if needed. Gmail account must have 2 factor authentication enabled and an app specific password.
• Exit the bash console and go to the Web tab. Click the green reload button at the top.
• Good to go!

Research

Relevent Research

Razzante, R. J., Hogan, M., Broome, B., Tracy, S. J., Chawla, D., & Skurzak, D. M. (2023). Interactive Management Research in Organizational Communication. Management Communication Quarterly, 0(0). https://doi.org/10.1177/08933189231159386

Existing Projects

• https://github.com/jjs0sbw/bsmp
• https://github.com/varchasvshri/ISM_Analysis
• https://github.com/cran/ISM
• https://github.com/Dr-Eti/ISMiR-ISM_in_R

Contributors

• Alyssa Maguire (Team Lead)
• Fernanda De Oliveira Girelli (Team Lead)
• Tushar Asthana (Team Lead)
• Grace Kinney
• James Catanzaro
• Sebastian Thomas
• Adrien Monks
• James Catanzaro
• Jason Lobell
• John Meluso