MbrlCatalogueTitleDetail

Do you wish to reserve the book?
Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion
Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion
Hey, we have placed the reservation for you!
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Title added to your shelf!
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion
Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion

Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
How would you like to get it?
We have requested the book for you! Sorry the robot delivery is not available at the moment
We have requested the book for you!
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion
Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion
Journal Article

Consensus-Based Sub-Indicator Weighting Approach: Constructing Composite Indicators Compatible with Expert Opinion

2022
Request Book From Autostore and Choose the Collection Method
Overview
The weighting of sub-indicators is a relevant problem in the composite indicators literature and impacts several fields of science. None of the existing weighting approaches, Equal-Weights, Data-Driven, and Participatory, is exempt from criticism. Specifically, weights obtained by the Participatory approach are associated with two frequent problems: assessments errors and international comparisons. Mainly, the assessments errors occur when the number of sub-indicators to be assessed is high, as it requires more cognitive effort from decision-makers. The problem of international comparison occurs because the weights of the sub-indicators reflect the specific characteristics of the countries and are not necessarily the same. Selecting experts who know the countries involved increases the impact of expert assessments on the results as the number of experts qualified to carry out the assessments decreases. These are common problems in composite indicators such as the Global Innovation Index, Multidimensional Poverty Index, Sustainable Development Goals Index, and Ease of Doing Business Index. This research presents solutions to these two problems. First, experts ordered seventeen sub-indicators by importance, decreasing the cognitive effort of the experts and the assessment errors that occur when the sub-indicators are assessed directly or compared in pairs. Second, the order of importance is converted into weights through six assessment format transformation functions. The deviant assessments are identified by the Concordance Correlation Coefficient and Intraclass Correlation Coefficient and excluded. Sub-indicators are weighted with a twenty-nine percent higher consensus degree, allowing the construction of composite indicators compatible with collective opinion.