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This study investigates how the consumption of sugar products and non-alcoholic beverages has changed across birth cohorts. In addition, this study examines how the socio-economic gaps in the consumption of said products have evolved across birth cohorts.

The research data are drawn from the Finnish household expenditure surveys covering the period 1985–2016 (n = 44,286). An age-period-cohort methodology is utilised through the age-period-cohort-trended lag model. The model assumes that the linear long-term component of change is caused by generations replacing one-another, and that the age effect is similar across cohorts.

Sugar products and non-alcoholic beverages occupied a larger portion of more recent birth cohorts' food baskets. Cohort differences were larger in beverage consumption. Lower income was associated with a higher food expenditure share of sugar products in several cohorts. A higher education level was linked to a higher food expenditure share of sugar products in more cohorts than a lower education level. In cohorts born before the 1950s, non-alcoholic beverages occupied a larger portion of the food baskets of the high socio-economic status groups. This gap reversed over time, leading to larger food expenditure shares of non-alcoholic beverages in low socio-economic status groups.

This study assessed how the consumption of sugar products and non-alcoholic beverages has changed across birth cohorts. In addition, this study assessed how socio-economic differences in the consumption of said products have changed. The results highlight that sugar products and non-alcoholic beverages occupy larger portions of more recent birth cohorts’ food baskets. The results also highlight a reversal of socioeconomic differences in non-alcoholic beverage consumption.

Responding to calls for deeper analysis of the conceptual foundations of service infusion in manufacturing, this paper examines the underlying assumptions that: (i) manufacturing firms incorporating services follow a pathway, moving from pure-product to pure-service offerings, and (ii) profits increase linearly with this process. We propose that these assumptions are inconsistent with the premises of behavioural and learning theories.

Machine learning algorithms are applied to test whether a successive process, from a basic to a more advanced offering, creates optimal performance. The data were gathered through two surveys administered to USA manufacturing firms in 2021 and 2023. The first included a training sample comprising 225 firms, whilst the second encompassed a testing sample of 105 firms.

Analysis shows that following the base-intermediate-advanced services pathway is not the best predictor of optimal performance. Developing advanced services and then later adding less complex offerings supports better performance.

Manufacturing firms follow heterogeneous pathways in their service development journey. Non-servitised firms need to carefully consider their contextual conditions when selecting their initial service offering. Starting with a single service offering appears to be a superior strategy over providing multiple services.

The machine learning approach is novel to the field and captures the key conditions for manufacturers to successfully servitise. Insight is derived from the adoption and implementation year datasets for 17 types of services described in previous qualitative studies. The methods proposed can be extended to assess other process-based models in related management fields (e.g., sand cone).