ARTICLE INFO

Article Type

Original Research

Authors

Fazel Torshizi   D. (1)
Naji-Azimi   Z. (*1)
Kazemi   M. (1)






(1) Department of Management, Faculty of Economics and Business Administration, Ferdowsi University of Mashhad, Mashhad, Iran

Correspondence

Address: Department of Management, Faculty of Economics and Business Administration, Ferdowsi University of Mashhad, Azadi Square, Mashhad, Iran. Postal Code: 9177948951.
Phone: +98 (51) 38805352
Fax: +98 (51) 38811243
znajiazimi@um.ac.ir

Article History

Received:  June  27, 2020
Accepted:  September 2, 2020
ePublished:  December 12, 2020

BRIEF TEXT


The improvement of the spatial access to the public services, can increase the economic and social efficacy in various fields.

Revelle & Swain (1970) were the first who evaluated the importance of the public facilities location. The purpose in private sector is to achieve the maximum profit and the minimum cost, while the purpose in public sector is to maximize the service provision and show a better picture of the organization provides the service. Public sector tends to decrease the clients' dissatisfaction by decreasing the commuting costs and waiting time [Marianov & Serra, 2011]. Antunes & Peeters (2011) worked on the dynamic locating of the facilities for planning the schools network. Considering the abundance and the location of the bicycle stands and the bicycle lanes, Lin et al. (2013) evaluated the available facilities to share the bicycles. Taghipourian et al. (2013) proposed a fuzzy planning approach about the dynamic locating in public transport so as to reduce the transport costs. Djeni'c et al. (2017) evaluated the feasibility of locating the health centers to minimize the number of the patients in each center.

This study aimed to use the dynamic locating of the public service centers in urban management long-term planning.

This is an empirical study in terms of the purpose and descriptive-quantitative in terms of the methodology.

The current research is carried out for planning for a period of 20 years including four periods of five years in12 districts of Mashhad

The research is done in all 12 districts of Mashhad.

Used devices and material are not reported.

The planning period in this research is 20 years including four periods, with 160 candidate areas and 33 areas with equal number of clients.According to the elites' opinion, other parameters such as the coverage radius (Ɛ) 2500m, the coefficient of determining the maximum facility (λ) 0.00001 of the population, and the allowed percentage to increase each facility's capacity (α) 0.1 were included considering the supportive situation of the organizations. The results of the population estimation in Mashhad using the census of 2016 (Table 3). Model's parameters are extracted using the available databases in relevant organizations and the elites' opinion in registry office, Mashhad union bus company, and Mashhad municipality (Table 4). The information about 160 areas with active counter offices of civil registration organization in Mashhad were extracted using GIS maps. Some other potential areas for establishing new offices were detected using the elites' opinions and geographical information layers. Geographical coordinates of the clients' center and location of the offices were determined using GIS maps (Table 5). According to the results of the model in four periods, the optimum number of the centers was such that the maximum coverage was provide in terms of the population and urban areas. Changes in the components of the objective function shows the improvement of the desirability from stakeholders' perspective [Table 6]. Locating selected places for the offices at the end of the planning period was done, as well. The best places were selected from the candidate places according to their better coverage and geographical distribution, leading to the optimum amount of the objective function and their maximum desirability (Figure 1).

Various methods for locating different places to provide service have been used during the recent years for example locating the health centers [Djeni'c et al., 2017; Basu et al., 2018, and Ljubi'c & Moreno, 2018], public transport stations [Sterle et al., 2016; Klier & Haase, 2015], and emergency management agencies [Jena et al., 2017]. However, there have not been any research working on the counter office of civil organizations as one of the most important centers with lots of clients. In developing the objective function, the current research is consistent with Lin & Yang (2011). Both studies considered all stakeholder's perspectives to achieve more accurate results.

There is no suggestions reported.

There is no limitations reported.

Using the dynamic locating model, the proper time to establish the offices and their optimum distribution were determined according to the coverage area, maximum population coverage, the ability to respond current and future demands, possibility to reopen the office in times of the demand increase, and considering the clients needs.

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TABLES and CHARTS

Show attach file


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