Pattern Identification by Factor Analysis for Regions with Similar Economic Activity Based on Mobile Communication Data

Arhipova, Irina; Berzins, Gundars; Brekis, Edgars; Opmanis, Mārtiņš; Binde, Juris; Kravcova, Jevgenija; Šteinbuka, Inna

doi:10.1007/978-3-030-03402-3_39

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…The data analysis shows differences in the intensity of call activity between workdays and weekends/holidays, characterizing the economic activity of the area (Arhipova et al, ). At the same time, the peak of the call activity was observed at noon on all days (Arhipova et al, ), as well the seasonality effect in summer and winter holidays.…”

Section: Methodsmentioning

confidence: 88%

“…In the first time period, 67.6% of the total variance is described by the first two principal components (PC), and the KMO value equals 0.990, where the first PC has high values on workdays for municipalities with higher economic activity, but the second PC has high values during weekends/holidays for municipalities with lower economic activity (Arhipova et al, ).…”

Section: Methodsmentioning

confidence: 99%

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Mobile phone data statistics as a dynamic proxy indicator in assessing regional economic activity and human commuting patterns

et al. 2020

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Various studies demonstrate that data on mobile phone use are useful when analysing problems in the fields of human activity or population dynamics, including tourism, transportation planning, public administration, etc. However, one of the biggest challenges is related to the restrictions contained in the General Data Protection Regulation that force the use of statistics about mobile operator client activities instead of allowing the analysis of mobile operator data. Therefore, a data analytics approach that does not involve information on the mobility of particular persons was developed, providing economically relevant data on aggregate mobility while protecting personal data. The activity data aggregation was conducted at 15-min intervals in the area of each cellular base station; "activity" is defined as the number of outgoing and incoming calls and sent and received text messages (short message service or SMS) and, in some instances, as the count of unique users. The case study examines all of Latvia's municipalities, analysing the economic activity level in each municipality in comparison to the mobile phone activity

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Section: Methodsmentioning

confidence: 88%

Section: Methodsmentioning

confidence: 99%

Mobile phone data statistics as a dynamic proxy indicator in assessing regional economic activity and human commuting patterns

et al. 2020

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Development of Waste Collection Model Using Mobile Phone Data: A Case Study in Latvia

Arhipova

Berzins

Erglis

et al. 2020

Advances in Intelligent Systems and Computing

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Smart and sustainable local communities in global Covid-19 pandemic conditions

Edgars

Una

Sanda

et al. 2021

LAA

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The COVID-19 pandemic has brought many changes in everyone’s life. Villages and rural areas are among the places where people have sought refuge in order to stay away from others and to be able to comply with government regulations during an emergency. Crisis conditions require the choice of means of communication, remote employment and self-help and self-support. Smart and strong communities or villages – this means more than only technologically and economically advanced communities – can be more successful in overcoming the crisis. This study analyses the characteristics of smart communities, the external factors influencing the functioning of these communities, as well as the specific circumstances caused by the first wave period of the Covid-19 pandemic (from March 2020 till June 2020). Collecting basic information on smart communities, external factors and special circumstances, and using the methods of analysis, comparison and drawing conclusions, the most important factors that have positively affected communities in the pandemic conditions have been taken into account within the framework of this study, clearly indicating the sustainability and development advantages of smart communities in Latvia. Nobody knows what will be “new normal” after COVID-19, but some benefits of smart thinking are noticed

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Pattern Identification by Factor Analysis for Regions with Similar Economic Activity Based on Mobile Communication Data

Cited by 3 publications

References 6 publications

Mobile phone data statistics as a dynamic proxy indicator in assessing regional economic activity and human commuting patterns

Mobile phone data statistics as a dynamic proxy indicator in assessing regional economic activity and human commuting patterns

Development of Waste Collection Model Using Mobile Phone Data: A Case Study in Latvia

Smart and sustainable local communities in global Covid-19 pandemic conditions

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