Development of an Index in Social Science: A Systematic Literature Review
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.3.09Keywords:
Social sciences, Analytic hierarchy process, Principal component analysisDimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
In the social sciences, indices are vital tools for summarizing and interpreting complex social phenomena by aggregating various indicators into a composite measure. This systematic literature review explores the methodologies employed in developing such indices, emphasizing the challenges of operationalizing abstract social concepts like well-being and inequality. The review identifies common practices in selecting and weighting indicators, with methodologies ranging from simple equal weighting to advanced statistical techniques like Principal Component Analysis (PCA) and the Analytic Hierarchy Process (AHP). Despite the widespread use of these indices, academic literature on their development remains sparse, with much of the existing work carried out by agencies rather than academic researchers. This review fills this gap by analyzing diverse studies across different social science domains, offering insights into best practices for future research. The findings underscore the importance of methodological rigor in ensuring the validity and reliability of indices, which are increasingly relied upon to inform policy and guide social interventions.Abstract
How to Cite
Downloads
Similar Articles
- Shefali Bahadur, Rohit Kushwaha, M. Venkatesan, Ramya Singh, Manish Mishra, Strategic alignment in multispecialty hospitals: Implementing a balanced scorecard approach for optimal performance , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Sharayu Mirasdar, Mangesh Bedekar, Knowledge graphs for NLP: A comprehensive analysis , The Scientific Temper: Vol. 16 No. Spl-1 (2025): The Scientific Temper
- Shamba Gowda, AR Chethan Kumar, S. Srinivasaragavan, Scholarly communication behavior in forestry research: A bibliometric analysis of global publications , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Vaishali Yeole, Rushikesh Yeole, Pradheep Manisekaran, Analysis and prediction of stomach cancer using machine learning , The Scientific Temper: Vol. 16 No. Spl-1 (2025): The Scientific Temper
- M. Iniyan, A. Banumathi, Brower blowfish nash secured stochastic neural network based disease diagnosis for medical WBAN in cloud environment , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Raghvendra, Tulika Saxena, Saurabh Verma, Rashi Saxena, Smita Dron, Shilpi Singh, Combination of financial literacy, strategic marketing and effective human resource for sustainable household wealth development , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Ayesha Shakith, L. Arockiam, EMSMOTE: Ensemble multiclass synthetic minority oversampling technique to improve accuracy of multilingual sentiment analysis on imbalance data , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- SHILPENDRA KOUR, REKHA KHANDAL, RASHMI TRIPATHI, EVALUATION OF LEAF EXTRACTS OF DIFFERENT MEDICINAL PLANTS FOR POTENTIAL ANTIBACTERIAL ACTIVITY AND PRELIMINARY PHYTOCHEMICAL ANALYSIS , The Scientific Temper: Vol. 3 No. 1&2 (2012): The Scientific Temper
- Anjali Thapa, Yunus Ali, Sanjay Madan, Pragya Verma, Prajwal Verma, Naveen Gaurav, An Assessment of in vitro Propagation and Medicinal Properties of Datura stramonium (Dhatura) , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- S ChandraPrabha, S. Kantha Lakshmi, P. Sivaraaj, Data analysis and machine learning-based modeling for real-time production , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
<< < 12 13 14 15 16 17 18 19 20 21 > >>
You may also start an advanced similarity search for this article.

