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Purpose – The purpose of this study is to explore the concept of spatial modeling in adolescent and under-five children’s nutritional status.

Design/Methodology/Approach – The indicator used to identify spatial autocorrelation is the Local Indicator of Spatial Association (LISA). LISA is a method of exploratory analysis of spatial data capable of detecting spatial relationships at the local level and its effects globally. Aplication of stochastic modeling in spatial nutrition identification mapping can be categorized into two cases based on spatial autocorrelation and non-spatial autocorrelation.

Findings – This results of this study indicate that there is no spatial autocorrelation in the adolescent nutritional dataset. The thematic map for anemia showed that that the highest number of anemia in adolescents was in KutaAlam sub-districts (48 people). Sub-districts that were second most common were Meuraxa, Jaya Baru, and Baiturrahman sub-districts. The fewest cases were found in Lueng Bata sub-district (12 people). There were no sub-districts affected by neighboring areas, in the case of adolescents’ anemia in Banda Aceh. For the under-five nutritional data set, it shows that there are four factors that significantly affect spatial influence, which are malnutrition, chronic energy deficiency, woman of child-bearing age, proportion of family planning, percentage of households with PHBS and coverage of access to clean water.

Research Limitations/Implications – Anemia data were obtained with a school-based survey. Household survey would be better to implement in spatial analysis.

Practical Implications – The comparison of the dataset with the two methods provides a simple example to implement special autocorrelation in practice.

Social Implications – The results contribute to a much better comparison in many cases in the nutritional field.

Originality/Value – This is the initial nutritional status of adolescents in Banda Aceh.

Introduction: Regional economies are significantly shaped by the new developments in technology, digital transformations, as well as by the demographic processes (the ageing population and international migration), all of these being amplified by the Covid-19 pandemics and requiring tailored strategies to bridge regional welfare gaps and enhance sustainable economic development.

Aim: This research provides a review of the interplay between the regional economic welfare and digitalisation, with a keen focus on digital transformations, education, digital skills and risk management strategies in filling development gaps and enhancing regional economic growth in a sustainable development framework, with a keen focus on Romania. In this approach, the study undertakes several essential research questions and designs an advanced theoretical and empirical research to inforce the knowledge in this scientific field.

Method: The methodological framework consists of robust regression models and spatial analysis with two types of spatial models, namely spatial lag-autoregressive and spatial error. National data compiled for Romania during the 2010–2019 lapse of time were exploited.

Findings: Main results encompass that digitalisation coordinates, education and digital skills are essential for enhancing the economic development and labour market performance of various regions in Romania, with beneficial spill-overs on sustainable economic welfare and poverty reduction. These advances bring to the fore important shifts in both demand and supply sides across regional economies that affect the equilibrium and overall performance, while public discourse, regulatory authorities, policy-makers and business representatives render global the keen need to strengthen the understandings in this scientific field.