Resistant to Change: How Declined Expectations Affect Public Appreciation Despite an Electric Approach

Resistant to Change: How Declined Expectations Affect Public Appreciation Despite an Electric Approach


Download Paper
Download Bibtex


Authors

  • Krishan Ayyub

Associated

Looking back, peering forward: our 2025 journey

As 2025 draws to a close, we’d like to take a moment to pause

Job Opportunity: Director at the Africa Evidence Network (AEN)

More than a decade ago, a group of people passionate about generating and using

What role for research when ordinary life is put on hold?

Today, November 29th, is the UN International Day of Solidarity with the Palestinian People.

Africa’s use of evidence: challenges and opportunities

Africa Evidence Week 2024 got off to an exciting start! I had the pleasure

Nothing about us without us

“If you’re going to come up with solutions to the problems of Africa don’t


Related Links

Abstract

This study explores the phenomenon of resistance to change within the context of public appreciation. Specifically, it investigates how declined expectations can negatively impact public appreciation despite the implementation of an electric approach. A mixed-methods approach was used, consisting of a survey and interviews with members of the public who had experienced a change in a service or product. Results indicate that declined expectations were associated with a decrease in public appreciation, even when an electric approach was implemented. Furthermore, the study found that resistance to change was driven by a variety of factors, including fear of the unknown, perceived loss of control, and lack of trust in the change process. These findings have important implications for organizations seeking to implement change and highlights the need for effective communication and engagement strategies to mitigate resistance to change and maintain public appreciation.

Citation

Krishan Ayyub "Resistant to Change: How Declined Expectations Affect Public Appreciation Despite an Electric Approach".  IEEE Exploration in Machine Learning, 2022.

Supplemental Material

Preview

Note: This file is about ~5-30 MB in size.

This paper appears in:
Date of Release: 2022
Author(s): Krishan Ayyub.
IEEE Exploration in Machine Learning
Page(s): 8
Product Type: Conference/Journal Publications

 


The roots of AI fear in the West are cultural, not technological

Popular conceptions of AI differ drastically between the US and...

Are we about to solve the greatest mystery of the neutrino?

We have long had a seemingly simple question about neutrinos:...

It’s about to get a lot harder to keep countries honest about climate change

A row over when to publish crucial climate change assessments risks letting countries...

Bottlenose whales may look after each other when they’re sick

Northern bottlenose whales are more likely to stick together when...

Discovery of T. rex’s cousin upends our understanding of tyrannosaur evolution

A dinosaur that is new to science has features of...