Exploring the sustainable packaging sector through European companies' LinkedIn profiles with unsupervised machine...

Area of Science:

• Environmental Science
• Business Strategy
• Data Science

Background:

• Growing demand for goods increases packaging use, impacting environmental factors like waste and emissions.
• Sustainable production and consumption are vital for environmental preservation.
• The sustainable packaging sector is a key area for environmental and business strategy research.

Purpose of the Study:

• To analyze how European companies in the sustainable packaging sector describe their operations and brand strategies.
• To identify key themes and approaches within the sustainable packaging industry using data mining techniques.

Main Methods:

• Investigated 516 LinkedIn profiles of companies mentioning 'Sustainable Packaging' in Europe.
• Applied two unsupervised machine learning methods: HDBSCAN and Latent Dirichlet Allocation (LDA) to company descriptions.
• Analyzed textual data to uncover thematic patterns in corporate communication regarding sustainable packaging.

Main Results:

• Identified two main thematic clusters in company descriptions.
• The first theme highlights the integration of sustainability across business operations and product development.
• The second theme emphasizes the strategic use of sustainability for brand identity, particularly in the cosmetics and organic product markets.

Conclusions:

• Companies in the sustainable packaging sector in Europe emphasize operational sustainability and brand differentiation.
• Sustainability is leveraged as a core element of corporate identity, especially in consumer-facing markets.
• Machine learning effectively identified distinct strategic approaches within the sustainable packaging industry.