scholarly journals City consumption profile: a city perspective on the spending behavior of citizens

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Alessia Galdeman ◽  
Cheick T. Ba ◽  
Matteo Zignani ◽  
Christian Quadri ◽  
Sabrina Gaito

AbstractIn designing the city of the future, city managers and urban planners are driven by specific citizens’ behaviors. In fact, economic and financial behaviors, and specifically, which goods and services citizens purchase and how they allocate their spending, are playing a central role in planning targeted services. In this context, cashless payments provide an invaluable data source to identify such spending behaviors. In this work, we propose a methodology to extract the consumption behaviors of a large sample of customers through credit card transaction data. The main outcome of the methodology is a concise representation of the economic behavior of people residing in a city, the so-called city consumption profile. We inferred the city consumption profile from a network-based representation of the similarity among the customers in terms of purchase allocation; on top of which we applied a community detection algorithm to identify the representative consumption profiles. By applying the above methodology to a set of credit card transactions of an Italian financial group, we showed that cities, even geographically close, exhibit different profiles which makes them unique. Specifically, usage patterns focused on a single type of good/service—mono-categorical consumption profile—are the main factors leading to the differences in the city profiles. Our analysis also showed that there is a group of consumption profiles common to all cities, made up by purchases of primary goods/services, such as food or clothing. In general, the city consumption profile represents a tool for understanding the economic behaviors of the citizens and for comparing different cities. Moreover, city planners and managers may use it in the outline of city services tailored to the citizens’ needs.

Contexto ◽  
2020 ◽  
Vol 14 (20) ◽  
Author(s):  
María Erándi Flores Romero ◽  
Irving Omar Morales Agiss ◽  
Liliana Beatriz Sosa Compean

The following article proposes a method to identify structures inside a road network with a flow-base community detection algorithm implemented on a graph representing the city road network. According to the results obtained in the cities of Mexico and Monterrey, the method effectively divides road infrastructure into several communities and preserves geographical neighboring. The frontiers of communities match administrative divisions along with other frontiers inside the city. The identification of communities could be useful to study the heterogeneity of street connectivity inside the city which could lead to improvements in urban mobility or even the application of public policies.


Author(s):  
Mohammed Hamad Almannaa ◽  
Huthaifa I. Ashqar ◽  
Mohammed Elhenawy ◽  
Mahmoud Masoud ◽  
Andry Rakotonirainy ◽  
...  

Climate ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 34
Author(s):  
Catarina C. Rolim ◽  
Patrícia Baptista

Several solutions and city planning policies have emerged to promote climate change and sustainable cities. The Sharing Cities program has the ambition of contributing to climate change mitigation by improving urban mobility, energy efficiency in buildings and reducing carbon emissions by successfully engaging citizens and fostering local-level innovation. A Digital Social Market (DSM), named Sharing Lisboa, was developed in Lisbon, Portugal, supported by an application (APP), enabling the exchange of goods and services bringing citizens together to support a common cause: three schools competing during one academic year (2018/2019) to win a final prize with the engagement of school community and surrounding community. Sharing Lisboa aimed to promote behaviour change and the adoption of energy-saving behaviours such as cycling and walking with the support of local businesses. Participants earned points that reverted to the cause (school) they supported. A total of 1260 users was registered in the APP, collecting more than 850,000 points through approximately 17,000 transactions. This paper explores how the DSM has the potential to become a new city service promoting its sustainable development. Furthermore, it is crucial for this concept to reach economic viability through a business model that is both profitable and useful for the city, businesses and citizens, since investment will be required for infrastructure and management of such a market.


Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 680
Author(s):  
Hanyang Lin ◽  
Yongzhao Zhan ◽  
Zizheng Zhao ◽  
Yuzhong Chen ◽  
Chen Dong

There is a wealth of information in real-world social networks. In addition to the topology information, the vertices or edges of a social network often have attributes, with many of the overlapping vertices belonging to several communities simultaneously. It is challenging to fully utilize the additional attribute information to detect overlapping communities. In this paper, we first propose an overlapping community detection algorithm based on an augmented attribute graph. An improved weight adjustment strategy for attributes is embedded in the algorithm to help detect overlapping communities more accurately. Second, we enhance the algorithm to automatically determine the number of communities by a node-density-based fuzzy k-medoids process. Extensive experiments on both synthetic and real-world datasets demonstrate that the proposed algorithms can effectively detect overlapping communities with fewer parameters compared to the baseline methods.


2021 ◽  
Vol 13 (14) ◽  
pp. 8035
Author(s):  
Ayman Nagi ◽  
Meike Schroeder ◽  
Wolfgang Kersten

The aim of this work is to detect communities of stakeholders at the port of Hamburg regarding their communication intensity in activities related to risk management. An exploratory mixed-method design is chosen as a methodology based on a compact survey and semi-structured interviews, as well as secondary data. A compact survey at the port of Hamburg is utilized to address the communication intensity values among stakeholders. Based on 28 full responses, the data is extracted, cleansed, and prepared for the network analysis using the software “Gephi”. Thereafter, the Louvain community detection algorithm is used to extract the communities from the network. A plausibility check is carried out using 15 semi-structured interviews and secondary data to verify and refine the results of the community analysis. The results have revealed different communities for the following risk categories: (a) natural disasters and (b) operational and safety risks. The focus of cooperation is on the reactive process and emergency plans. For instance, emergency plans play an important role in the handling of natural disasters such as floods or extreme winds.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Abhishek Uday Patil ◽  
Sejal Ghate ◽  
Deepa Madathil ◽  
Ovid J. L. Tzeng ◽  
Hsu-Wen Huang ◽  
...  

AbstractCreative cognition is recognized to involve the integration of multiple spontaneous cognitive processes and is manifested as complex networks within and between the distributed brain regions. We propose that the processing of creative cognition involves the static and dynamic re-configuration of brain networks associated with complex cognitive processes. We applied the sliding-window approach followed by a community detection algorithm and novel measures of network flexibility on the blood-oxygen level dependent (BOLD) signal of 8 major functional brain networks to reveal static and dynamic alterations in the network reconfiguration during creative cognition using functional magnetic resonance imaging (fMRI). Our results demonstrate the temporal connectivity of the dynamic large-scale creative networks between default mode network (DMN), salience network, and cerebellar network during creative cognition, and advance our understanding of the network neuroscience of creative cognition.


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