Sustainability Indicators and Product Diversification: An Exploratory Predictive Assessment

ABSTRACT This study examines whether carbon footprint, eco‐friendly manufacturing and recycling programmes help predict recorded product‐line count, used as a limited indicator of product diversification. Using the records from a sustainability dataset, we apply exploratory predictive modelling with linear regression, random forest and gradient boosting. We evaluate sustainability‐only, context‐only and combined models against a training‐mean benchmark using a held‐out sample and fivefold cross‐validation. Adding sustainability information improves some predictions beyond price, country, year and market trend but offers little consistent advantage over simply predicting the average product‐line count. The study contributes by showing the difference between improving a model and providing useful predictions of product‐range size. Uncertain corporate provenance and undocumented product‐line definitions prevent broader conclusions about sustainability's effects on strategic diversification or stakeholder value.

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Publication Details

Journal
Business Strategy and the Environment
Published
2026-10-27
DOI
https://doi.org/10.1002/bse.71791
Primary Topic
Environmental Sustainability in Business
Type
article
Field-Weighted Citation Impact
0.00
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article

Sustainability Indicators and Product Diversification: An Exploratory Predictive Assessment

Tomáš Kincl, Nick Hajli, Tahir M. Nisar, Guangming Cao et al.
3 links
Business Strategy and the Environment
Environmental Sustainability in Business
article

Sustainability Indicators and Product Diversification: An Exploratory Predictive Assessment

Tomáš Kincl, Nick Hajli, Tahir M. Nisar, Guangming Cao, Narges Siamian
article en

Abstract

ABSTRACT This study examines whether carbon footprint, eco‐friendly manufacturing and recycling programmes help predict recorded product‐line count, used as a limited indicator of product diversification. Using the records from a sustainability dataset, we apply exploratory predictive modelling with linear regression, random forest and gradient boosting. We evaluate sustainability‐only, context‐only and combined models against a training‐mean benchmark using a held‐out sample and fivefold cross‐validation. Adding sustainability information improves some predictions beyond price, country, year and market trend but offers little consistent advantage over simply predicting the average product‐line count. The study contributes by showing the difference between improving a model and providing useful predictions of product‐range size. Uncertain corporate provenance and undocumented product‐line definitions prevent broader conclusions about sustainability's effects on strategic diversification or stakeholder value.

Business Strategy and the Environment
Loughborough University (GB), Ajman University (AE), Czech University of Life Sciences Prague (CZ), Prague University of Economics and Business (CZ), AVE (Czechia) (CZ), Nemocnice Jindřichův Hradec (CZ), University of Southampton (GB)
Responsible consumption and production
Openalex Percentile: Top 6%
Environmental Sustainability in Business
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Sustainability Indicators and Product Diversification: An Exploratory Predictive Assessment — Tomáš Kincl, Nick Hajli, et al. · Business Strategy and the Environment (2026) | TGRS Research Map | TGRS