Techno Blender
Digitally Yours.

Examining gender mismatch and bias in people‐centric operations

0 25


Credit: CC0 Public Domain

Considerable research has been devoted to studying gender bias in the physical workplace, especially in the fields of management and economics.

Within online platforms, however, gender biases and how they manifest have received far less attention. There are some exceptions, including operational outcomes such as hiring, performance and compensation. Largely ignored, though, is how the design of operational processes lessens or increases gender bias.

A new study from the University of Notre Dame examines how gender bias influences people-centric operations in online platforms.

“Gender Mismatch and Bias in People-Centric Operations: Evidence from a Randomized Field Experiment” is published in the Journal of Operations Management from lead author Yoonseock Son, assistant professor of information technology, analytics and operations in Notre Dame’s Mendoza College of Business.

For seven months, the team collaborated with an online weight management platform in Asia that provides programs, products and consulting services for healthy living.

The researchers created an experimental design that linked clients and consultants in different gender combinations, and then examined how gender biases differed during their exchanges.

Clients could ask questions on the website’s chat feature and within 24 hours, a consultant would respond and then recommend a product. The clients would then rate their experience.

“Surprisingly, we found that clients have a better experience and spend more on products and services when there are gender mismatches,” Son said. “In other words, this happens when female clients are paired with male consultants and male clients with females.”

The team also found the effects of gender mismatches differ depending on the customer’s actions, whether they are leaving ratings, purchasing recommended products or simply browsing.

Knowing a consultant’s gender led customers to leave more and higher ratings, click on recommended products and then make purchases.

If the consultant was of the opposite gender, ratings were even higher—much more so from female clients with male consultants.

Female customers had a higher click-through rate when gender was reported, regardless of which it was, but the men only clicked more on the products if their consultants were women.

Purchase rates increased only for products recommended by the female consultants, and in these cases, the men bought significantly more than the women.

“Past research suggests that women’s performance may suffer with a male consultant,” Son said, “but we find women may actually outperform their male counterparts.”

The study states, “The design—or redesign—of operational processes with consideration to gender bias is important across sectors, but is particularly important in the service industry as services are people-centric and increasingly shifting toward online platforms where face-to-face interactions are largely eliminated.”

The findings, which apply to any circumstance with no face-to-face interaction, provide a new tool for managers of platform businesses such as TripAdvisor, Yelp, Uber and Lyft. With ride-hailing services, the decision to ride is made before the customer and driver meet.

Better understanding how a client’s gender influences biases toward a company’s employees can help improve customer service as well as firm performance.

Firms can look at a customer’s name and browsing history to help deduce gender, and then design more effective customer-employee matching algorithms and training programs.

“Our study can help firms to get the most from matches or leverage mismatches and maximize overall effectiveness,” Son said. “It’s a win-win situation for both the customer and the firm.”

Co-authors include Kaitlin Wowak, the Robert and Sara Lumpkins Associate Professor of Business Analytics, and Corey Angst, the Jack and Joan McGraw Family Collegiate Professor of IT, Analytics and Operations, both at Notre Dame, along with Angela Choi from SungKyunKwan University in South Korea.

More information:
Yoonseock Son et al, Gender mismatch and bias in people‐centric operations: Evidence from a randomized field experiment, Journal of Operations Management (2023). DOI: 10.1002/joom.1249

Provided by
University of Notre Dame


Citation:
Examining gender mismatch and bias in people‐centric operations (2024, February 14)
retrieved 14 February 2024
from https://phys.org/news/2024-02-gender-mismatch-bias-peoplecentric.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.




gender
Credit: CC0 Public Domain

Considerable research has been devoted to studying gender bias in the physical workplace, especially in the fields of management and economics.

Within online platforms, however, gender biases and how they manifest have received far less attention. There are some exceptions, including operational outcomes such as hiring, performance and compensation. Largely ignored, though, is how the design of operational processes lessens or increases gender bias.

A new study from the University of Notre Dame examines how gender bias influences people-centric operations in online platforms.

“Gender Mismatch and Bias in People-Centric Operations: Evidence from a Randomized Field Experiment” is published in the Journal of Operations Management from lead author Yoonseock Son, assistant professor of information technology, analytics and operations in Notre Dame’s Mendoza College of Business.

For seven months, the team collaborated with an online weight management platform in Asia that provides programs, products and consulting services for healthy living.

The researchers created an experimental design that linked clients and consultants in different gender combinations, and then examined how gender biases differed during their exchanges.

Clients could ask questions on the website’s chat feature and within 24 hours, a consultant would respond and then recommend a product. The clients would then rate their experience.

“Surprisingly, we found that clients have a better experience and spend more on products and services when there are gender mismatches,” Son said. “In other words, this happens when female clients are paired with male consultants and male clients with females.”

The team also found the effects of gender mismatches differ depending on the customer’s actions, whether they are leaving ratings, purchasing recommended products or simply browsing.

Knowing a consultant’s gender led customers to leave more and higher ratings, click on recommended products and then make purchases.

If the consultant was of the opposite gender, ratings were even higher—much more so from female clients with male consultants.

Female customers had a higher click-through rate when gender was reported, regardless of which it was, but the men only clicked more on the products if their consultants were women.

Purchase rates increased only for products recommended by the female consultants, and in these cases, the men bought significantly more than the women.

“Past research suggests that women’s performance may suffer with a male consultant,” Son said, “but we find women may actually outperform their male counterparts.”

The study states, “The design—or redesign—of operational processes with consideration to gender bias is important across sectors, but is particularly important in the service industry as services are people-centric and increasingly shifting toward online platforms where face-to-face interactions are largely eliminated.”

The findings, which apply to any circumstance with no face-to-face interaction, provide a new tool for managers of platform businesses such as TripAdvisor, Yelp, Uber and Lyft. With ride-hailing services, the decision to ride is made before the customer and driver meet.

Better understanding how a client’s gender influences biases toward a company’s employees can help improve customer service as well as firm performance.

Firms can look at a customer’s name and browsing history to help deduce gender, and then design more effective customer-employee matching algorithms and training programs.

“Our study can help firms to get the most from matches or leverage mismatches and maximize overall effectiveness,” Son said. “It’s a win-win situation for both the customer and the firm.”

Co-authors include Kaitlin Wowak, the Robert and Sara Lumpkins Associate Professor of Business Analytics, and Corey Angst, the Jack and Joan McGraw Family Collegiate Professor of IT, Analytics and Operations, both at Notre Dame, along with Angela Choi from SungKyunKwan University in South Korea.

More information:
Yoonseock Son et al, Gender mismatch and bias in people‐centric operations: Evidence from a randomized field experiment, Journal of Operations Management (2023). DOI: 10.1002/joom.1249

Provided by
University of Notre Dame


Citation:
Examining gender mismatch and bias in people‐centric operations (2024, February 14)
retrieved 14 February 2024
from https://phys.org/news/2024-02-gender-mismatch-bias-peoplecentric.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.

FOLLOW US ON GOOGLE NEWS

Read original article here

Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials to their authors. If you are the owner of the content and do not want us to publish your materials, please contact us by email – [email protected]. The content will be deleted within 24 hours.

Leave a comment