Business location planning based on a novel geo-social influence diffusion model

Zeng, Qian; Zhong, Ming; Zhu, Yuanyuan; Qian, Tieyun; Li, Jianxin

doi:10.1016/j.ins.2021.01.047

Cited by 11 publications

(3 citation statements)

References 15 publications

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“…The study of BLP (business location planning) problems has been widely analyzed from different angles over the years. These analyzes more often concern geographic locations, qualities (stars and prices), and social influence [5] or the behavior of social network users [6].…”

Section: Business Location Planning Methodsmentioning

confidence: 99%

“…The limitation of the work of Hung et al [10] is that the RNN users may have a weak influence and may not be willing to promote the location. Thus, Zeng et al (2020) [5] addressed the BLP problem by exploiting influence maximization techniques to promote each candidate location actively, thereby guaranteeing the achievement of the maximum spread of influence for each candidate location [6].…”

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confidence: 99%

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Mechanism for the Optimal Location of a Business as a Lever for the Development of the Economic Strength and Resilience of a City

2021

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Today, the location of a business is more important than ever, as it contributes to its consolidation in the market and, in parallel, to the economic development of a city. Over the years, the theories about the optimal location of a business have undergone various changes, both financial and spatial. On the other hand, economic geography, as a discipline that studies the distribution of economic activities as well as the interactions between them, is also an important tool for the analysis of urban/spatial and business processes. This paper finds the optimal locations of economic activities through the combination of theories of economic geography and spatial analysis, for the sake of reducing urban shrinkage and increasing the resilience of businesses and cities. The analysis of this paper proved that the areas that are most exposed to urban shrinkage are the least central areas. Urban shopping centers, despite the large percentage of closed stores, continue due to their centrality to attracting more new businesses. The calculation of the optimal location of the economic activity showed that the optimal location depends on the financial sector itself but also on the economic activities that open or close over time in this region. In this way, an answer is sought regarding the way in which each region and its economic identity can influence a city’s future development and resilience. Thus, through this analysis, cities are able to control and strengthen their economic landscapes, vulnerable as they are in difficult times, and to implement policies in specific urban units, with a view to the prosperity of their economic activities.

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Section: Business Location Planning Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Mechanism for the Optimal Location of a Business as a Lever for the Development of the Economic Strength and Resilience of a City

2021

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“…Chen and Chen [29] propose a relaxationbased algorithm for solving both the conditional discrete and continuous l-center problem. More recently, Zeng et al [30] propose a novel business location planning approach for the emerging online-to-offline businesses. In the approach, online social network marketing is defined as an influence maximization process based on a particular diffusion model that is aware of offline factors such as competitive locations, target users, and geographic distance.…”

Section: Conditional Facility Location Problemmentioning

confidence: 99%

Efficient Sample Location Selection for Query Zone in Geo‐Social Networks

Tang

Zhan

et al. 2021

Complexity

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While promoting a business or activity in geo-social networks, the geographical distance between its location and users is critical. Therefore, the problem of Distance-Aware Influence Maximization (DAIM) has been investigated recently. The efficiency of DAIM heavily relies on the sample location selection. Specifically, the online seeding performance is sensitive to the distance between the promoted location and its nearest sample location, and the offline precomputation performance is sensitive to the number of sample locations. However, there is no work to fully study the problem of sample location selection for DAIM in geo-social networks. To do this, we first formalize the problem under a reasonable assumption that a promoted location always adheres to the distribution of users (query zone). Then, we propose two efficient location sampling approaches based on facility location analysis, which is one of the most well-studied areas of operations research, and these two approaches are denoted by Facility Location based Sampling (FLS) and Conditional Facility Location Based Sampling (CFLS), respectively. FLS conducts one-time sample location selection, and CFLS extends the one-time sample location selection to a continuous process, so that an online advertising service can be started immediately without sampling a lot of locations. Our experimental results on two real datasets demonstrate the effectiveness and efficiency of the proposed methods. Specifically, both FLS and CFLS can achieve better performance than the existing sampling methods for the DAIM problem, and CFLS can initialize the online advertising service in a matter of seconds and achieve better objective distance than FLS after sampling a large number of sample locations.

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Influence Maximization in Attributed Social Network Based on Susceptibility Cascade Model

Chen,

Xin,

Lei

et al. 2024

Lecture Notes in Computer Science

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Business location planning based on a novel geo-social influence diffusion model

Cited by 11 publications

References 15 publications

Mechanism for the Optimal Location of a Business as a Lever for the Development of the Economic Strength and Resilience of a City

Mechanism for the Optimal Location of a Business as a Lever for the Development of the Economic Strength and Resilience of a City

Efficient Sample Location Selection for Query Zone in Geo‐Social Networks

Influence Maximization in Attributed Social Network Based on Susceptibility Cascade Model

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