نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار گروه مهندسی شهرسازی، دانشکده هنر و معماری، دانشگاه سلمان فارسی کازرون

2 استادیار، گروه مهندسی شهرسازی، دانشکده فنی و مهندسی، دانشگاه لرستان، خرم آباد، ایران.

چکیده

در نظام برنامه­ریزی و مطالعات اقتصادشهری، شناسایی نحوه توزیع، الگوهای مکان­گزینی و پیکربندی فعالیت­های مختلف در بستر شهر و ساماندهی آنها از منظر اجتماعی- اقتصادی، ترافیکی، زیست محیطی و غیره از اهمیت زیادی برخوردار است. در این زمینه، پژوهش حاضر تلاش دارد با رویکردی کیفی نحوه مکان­گزینی فروشگاه­های خرده فروشی پوشاک در شهر کازرون را بررسی و تحلیل نماید. فروشگاه­های یادشده در شهر کازرون از دیرباز بر اساس صرفه­های ناشی از تجمع به صورت متمرکز در بازار و مراکز خرید متصل به آن مستقر بوده اند اما در سال های اخیر این فروشگاه ها به جای بازار و استفاده از مزایای ناشی از تجمع، خیابان را برای فعالیت انتخاب کرده­اند. با توجه به اهمیت و ابعاد تأثیرگذار این تغییر رفتار، هدف این پژوهش شناسایی دلایل دوری­گزینی فروشگاه های پوشاک از بازار، الگوی توزیع آنها و معیارهای مکانیابی در سطح شهر است. در این راستا، عوامل و جذابیت­های مکانی و غیرمکانی مؤثر بر استقرار فروشگاه­های پوشاک شهر کازرون در لبه خیابان تحلیل شده است. روش گردآوری داده ها، مصاحبه با فروشندگان و تحلیل آن با کمک نرم افزار مکس کیودا و روش تحلیل محتوا انجام شده است. نتایج پژوهش نشان می دهد که فروشگاه های خیابانی به دلیل محدودیت زمان فعالیت بازار، دسترسی آسان­تر، وجود پارکینگ در دسترس، تأثیر شبکه های اجتماعی، تأثیر حوادثی مانند ویروس کووید۱۹، مساحت و اندازه مغازه ها، جو و دلایل شخصی، وجود یا عدم مغازه خالی، فضا برای چیدمان و هزینه اجاره، خیابان را به جای بازار(تجمع فروشگاه های پوشاک) ترجیح داده­اند. از طرف دیگر معیارهای مکانیابی آنها در سطح خیابان به ترتیب شامل وجود جای پارک برای مشتری، خیابان پویا و فعال، دید مناسب، نزدیکی به مراکز جاذبه فعالیتی، ابعاد و اندازه مغازه، مالکیت و نحوه قرارداد، نزدیکی به رقبا، نزدیکی به فروشگاه های مکمل و هزینه است که با تحلیل فضایی ارائه شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Avoiding the Bazar: an analysis of spatial and non-spatial attractions affecting the establishment of activities on the edge of the street: clothing retailing activity in Kazeroon city

نویسندگان [English]

  • Gholamreza Moradi 1
  • Enayat Mirzaei 2

1 Department of Urban Planning, Faculty of Technology and Engineering, University of Salman Farsi of Kazerun, Kazerun, Iran.

2 Department of Urban Planning, Faculty of Engineering, University of Loreatan, Khorramabad, Iran.

چکیده [English]

Highlights

Location is a critical concept in retail, especially in the clothing sector.
Many clothing stores opt for street locations over the Bazaar (retail agglomeration).
Factors such as business hours, accessibility, parking availability, and social networks play a significant role in avoiding retail agglomerations (Bazaar and shopping centers).
Parking, street activity, visibility, and proximity to major urban centers are key reasons for establishing stores on the street.
Using MaxQDA software is highly effective for qualitative data analysis and interview coding.

1. Introduction
Location selection is vital in all types of businesses, including retail, wholesale, service, and manufacturing. This is particularly true for retail businesses, where location often plays a determining role in the success or failure of commercial activities. Agglomeration economies, where stores physically cluster together to gain mutual benefits, are common in retail. In Kazeroon City, many retail activities, especially clothing stores, have traditionally been located in the city center, within the Bazaar or nearby shopping centers. However, in recent years, a noticeable shift has occurred, with some stores opting for street locations instead. This research seeks to explore the reasons behind this trend of avoiding retail agglomeration and the criteria for selecting locations on the street.
2. Theoretical Framework
Retail agglomeration occurs when similar or complementary retailers cluster in or near a location, creating a pull factor for both retailers and customers. This concept is a foundational element in economic studies and urban planning. Retail patterns can be categorized hierarchically, from central business districts to isolated store clusters, and by their form into planned or unplanned, linear, or isolated clusters. Three types of retail agglomerations are commonly distinguished: evolved (such as central business districts), created (such as shopping malls), and hybrid (like retail parks). Furthermore, these agglomerations can be classified as planned or unplanned, depending on their level of management and organization. Various theories such as Central Place Theory, the Spatial Interaction Model, Bid Rent Theory, and the Principle of Minimum Differentiation provide insight into how retailers distribute themselves spatially within cities and why they form agglomerations.
3. Methodology
This research employs a qualitative approach to collect and analyze data. Kazeroon, a city in Iran's Fars Province, has over 4,877 active economic activities, 395 of which are clothing stores. Of these, 330 are located within the Bazaar or shopping centers (i.e., retail agglomerations), while 65 are located on the street. Data was gathered through face-to-face interviews with 24 street-based clothing vendors, and content was analyzed using MaxQDA software. Spatial analysis was conducted using GIS Pro software to map the spatial distribution and configuration of stores.
4. Results and Discussion
The primary reasons for retailers choosing street locations over the Bazaar included factors such as business hours, accessibility, parking availability, social networks, store atmosphere, the size of the shop, COVID-19 impacts, ownership, costs, and the unavailability of empty shops within the Bazaar. These factors can be divided into two categories: non-spatial factors (e.g., business hours, social networks, ownership) and spatial factors (e.g., accessibility, parking availability, store size). Interviews revealed that retailers were attracted to street locations because of convenient customer parking, high visibility, active streets, and proximity to major urban centers. These factors, as well as store size and ownership arrangements, were commonly cited as critical considerations in selecting a location.
The deductive approach based on theoretical foundations and past research revealed that parking availability, visibility, active street life, and proximity to major attractions were frequently mentioned by interviewees. Proximity to complementary stores, rental costs, and proximity to competitors were also noted but were not as prominent as in previous studies. The findings suggest that while proximity to complementary stores and cost considerations are significant in other research, in the case of Kazeroon, these factors were less influential. The unique conditions of the city, such as the lack of adequate parking near the Bazaar, shifted the emphasis towards street locations, where customer access is easier due to marginal parking availability. Active street life, visibility, and proximity to major land uses remain consistent with findings from other studies.
Notably, the influence of the COVID-19 pandemic, the growing role of social networks, and the atmospheric quality of street stores emerged as differentiating factors in this study, contrasting with findings from other research. Ownership arrangements and contract types also played a significant role in location decisions, providing an additional layer of complexity not often addressed in traditional retail studies. Moreover, it was discovered that some clothing stores are moving away from the city center and forming new retail clusters on the outskirts, creating new agglomerations.
5. Conclusion
The findings of this research underscore that store ownership is a significant factor in avoiding central city locations, as owning property eliminates the need to pay rent, reducing the perceived benefits of agglomeration. Additionally, the rise of social networks as a customer acquisition tool has decreased the reliance on physical proximity to the Bazaar. Limited business hours within the Bazaar, particularly closing on holidays and early evening closures, along with the confined atmosphere of shopping malls, have prompted retailers to establish street-based locations. Among the most critical factors influencing this decision is the ease of customer access, particularly due to the availability of marginal parking. Factors such as active street life, high visibility, and proximity to significant land uses are consistent with previous studies on retail location selection. However, the influence of proximity to competitors and complementary stores, which are frequently emphasized in the literature, were less significant in this study. The research also highlights that certain retailers, far from the city center, are forming new agglomerations in less central areas, indicating the emergence of new retail patterns in Kazeroon.
This research contributes to the understanding of retail location dynamics, particularly in smaller cities like Kazeroon. It suggests that retailers prioritize factors that facilitate customer convenience, such as parking and accessibility, over traditional agglomeration benefits. The findings have implications for urban planners and policymakers, particularly in addressing the infrastructural needs of non-central retail areas.

کلیدواژه‌ها [English]

  • Retail Agglomeration
  • Street Retailing
  • Clothing Stores
  • Location Selection
  • Kazeroon
Adeniyi, O., Brown, A., & Whysall, P. (2020). Retail location preferences: A comparative analysis. Journal of Retailing and Consumer services, 55, 102146 https://doi.org/10.1016/j.jretconser.2020.102146
Akalin, M., Turhan, G., & Sahin, A. (2013). The application of AHP approach for evaluating location selection elements for retail store: a case of clothing store. International Journal of Research in Business and Social Science (2147-4478), 2(4), 01-20.  DOI: https://doi.org/10.20525/ijrbs.v2i4.77
Araldi, A., & Fusco, G. (2019). Retail fabric assessment: Describing retail patterns within urban space. Cities, 85, 51-62.  https://doi.org/10.1016/j.cities.2018.11.025
Aithal, R. K., & Pradhan, D. (2022). Resilience of an evolved retail agglomeration: case of rural periodic markets in emerging economies. International Journal of Retail & Distribution Management, 50(11), 1395-1411. https://doi.org/10.1108/IJRDM-09-2021-0423
Baraklianos, I., Bouzouina, L., & Bonnel, P. (2018). The impact of accessibility on the location choices of the business services. Evidence from Lyon urban area. Reg. Dev, 48, 85-104.  https://econpapers.repec.org/RePEc:hal:journl:halshs-02114205
Chang, H.-J., & Hsieh, C.-M. (2018). A new model for selecting sites for chain stores in China. International Journal of Industrial and Systems Engineering, 28(3), 346-359.  https://doi.org/10.1504/IJISE.2018.089744
Damavandi, H., Abdolvand, N., & Karimipour, F. (2018). The computational techniques for optimal store placement: A review. Paper presented at the Computational Science and Its Applications–ICCSA 2018: 18th International Conference, Melbourne, VIC, Australia, July 2-5, 2018, Proceedings, Part II 18. https://doi.org/10.1007/978-3-319-95165-2_31
Damavandi, H., Abdolvand, N., & Karimipour, F. (2019). Utilizing location-based social network data for optimal retail store placement. Earth Observation and Geomatics Engineering3(2), 77-91.‏https://ssrn.com/abstract=3926534
Erbıyık, H., Özcan, S., & Karaboğa, K. (2012). Retail store location selection problem with multiple analytical hierarchy process of decision making an application in Turkey. Procedia-Social and Behavioral Sciences, 58, 1405-1414.  https://doi.org/10.1016/j.sbspro.2012.09.1125
Farahani, R. Z., SteadieSeifi, M., & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied mathematical modelling, 34(7), 1689-1709.  https://doi.org/10.1016/j.apm.2009.10.005
Hao, F., Yang, Y., & Wang, S. (2021). Patterns of location and other determinants of retail stores in urban commercial districts in Changchun, China. Complexity, 2021, 1-14.  https://doi.org/10.1155/2021/8873374
Hameli, Kujtim. (2018). A literature review of retailing sector and business retailing types. ILIRIA International Review8، (1)، 67-87.
Kickert, C., & Vom Hofe, R. (2018). Critical mass matters: The long-term benefits of retail agglomeration for establishment survival in downtown Detroit and The Hague. Urban Studies, 55(5), 1033-105 https://doi.org/10.1177/0042098017694131.
Knežević, B., Delić, M., & Ptić, K. (2016). Clothing Buying Motives And Store Selection Criteria–The Case Of Croatian Adolescents. Ekonomski vjesnik/Econviews-Review of Contemporary Business, Entrepreneurship and Economic Issues, 29, 105-116.  https://hrcak.srce.hr/ojs/index.php/ekonomski-vjesnik/article/view/4707
Larsson, J. P., & Öner, Ö. (2014). Location and co-location in retail: a probabilistic approach using geo-coded data for metropolitan retail markets. The Annals of Regional Science, 52, 385-408.  https://doi.org/10.1007/s00168-014-0591-7
Legros, D., Dubé, J., Brunelle, C., & Legros, D. (2016). Location Theories and Business Location Decision: A Micro-Spatial Investigation of a Nonmetropolitan Area in Canada (No. hal-01338639). ‏doi: 10.52324/001c.8039
Lin, S.-H., Hsu, C.-C., Zhong, T., He, X., Li, J.-H., Tzeng, G.-H., & Hsieh, J.-C. (2021). Exploring location determinants of Asia’s unique beverage shops based on a hybrid MADM model. International Journal of Strategic Property Management, 25(4), 291-315.  https://doi.org/10.3846/ijspm.2021.14796
Kabamba, L. (2018, July). THE IMPACT OF LOCATION DECISION ON SMALL, MEDIUM, AND MICRO-ENTERPRISES (SMMEs) PERFORMANCE IN JOHANNESBURG. In 2nd European International Conference on Industrial Engineering and Operations Management, https://doi.org/10.46254/EU02.20180219.
Lu, C., Yu, C., Xin, Y., & Zhang, W. (2023). Spatial Distribution Characteristics and Influencing Factors on the Retail Industry in the Central Urban Area of Lanzhou City at the Scale of Daily Living Circles. ISPRS International Journal of Geo-Information, 12(8), 344. https://doi.org/10.3390/ijgi12080344
Mazhi, K. Z., Suryana, L. E., Davi, A., & Dewi, W. R. (2020). Site selection of retail shop based on spatial analysis and machine learning. Paper presented at the 2020 international conference on advanced computer science and information systems (icacsis). https://doi.org/10.1109/ICACSIS51025.2020.9263156
Paroli, E., & Maraschin, C. (2018). Locational attractiveness modelling of retail in santa maria, Brazil. Urban Science2(4), 105.‏ https://doi.org/10.3390/urbansci2040105
Pope, J. A., Lane, W. R., & Stein, J. (2012). A multiple-attribute decision model for retail store location. Southern Business Review, 37(2), 15-25.
Reigadinha, T., Godinho, P., & Dias, J. (2017). Portuguese food retailers–Exploring three classic theories of retail location. Journal of Retailing and Consumer services, 34, 102-116. https://doi.org/10.1016/j.jretconser.2016.09.015
Rosenthal, S. S., & Strange, W. C. (2020). How close is close? The spatial reach of agglomeration economies. Journal of economic perspectives, 34(3), 27-49.  DOI: 10.1257/jep.34.3.27
Sabzali Yamaqani, K., Ahmadi, M., Gharibnavaz, N., & keshtkar haranaki, M. (2021). Identify and Prioritize the Factors Affecting the Optimal Location Selection of Retail Chain Stores Using Geomarketing. New Marketing Research Journal11(1), 111-142. doi: 10.22108/nmrj.2020.123853.2178 [in Persian]
Sabzali Yamaqani, K., Ahmadi, M., Gharibnavaz, N., & Sabzali Yameqani, A. (2022). Optimal Location of New Chain Retail Stores Based on Geomarketing (Location-Based Marketing) with a Combined Approach of TOPSIS and GIS. Iranian Journal of Trade Studies27(105), 53-90. doi: 10.22034/ijts.2022.561536.3710 [in Persian]
salehnia, N., & Maghsoudpour, M. (2022). The Effect of Accumulation and Urbanization Savings on the Economic Growth of Food and Beverage Industries. Geography and Urban Space Development8(2), 161-177. doi: 10.22067/jgusd.2021.70681.1051 [in Persian]
Sarmento Silva, R., Donaire, D., & Gaspar, M. A. (2021). ANALYSIS OF THE COMPETITION, COOPERATION, AND COOPETITION: A COMPARISON BETWEEN PLANNED AND UNPLANNED RETAILER CLUSTERS. Brazilian Journal of Management/Revista de Administração da UFSM, 14(4). doi: 10.5902/1983465963708
Sanchez-Saiz, R. M., Ahedo, V., Santos, J. I., Gomez, S., & Galan, J. M. (2022). Identification of robust retailing location patterns with complex network approaches. Complex & Intelligent Systems, 8(1), 83-106.  https://doi.org/10.1007/s40747-021-00335-8
Saraiva, M., & Pinho, P. (2017). Spatial modelling of commercial spaces in medium-sized cities. GeoJournal, 82(3), 433-454. https://doi.org/10.1007/s10708-015-9694-7
Shahbazi, K., & salimian, S. (2018). Firms Location Choice in the Case of Presence of a Variety of Consumers (Experienced and Inexperienced). Journal of Economic Research (Tahghighat- E- Eghtesadi)53(1), 45-68. doi: 10.22059/jte.2018.65070 [in Persian]
Sevtsuk, A. (2014). Location and agglomeration: The distribution of retail and food businesses in dense urban environments. Journal of Planning Education and Research34(4), 374-393.‏ https://doi.org/10.1177/0739456X14550401
Singla, V., & Rai, H. (2016). Investigating the effects of retail agglomeration choice behavior on store attractiveness. Journal of Marketing Analytics4, 108-124.‏ https://doi.org/10.1057/s41270-016-0004-0
Sokol, V., & Jordanov, K. (2020). Site selection for small retail stores using sustainable and location-driven indicators: Case study: Starbucks coffee shops in Los Angeles.
Tănase, G. C. (2010). Trading Area Analysis and the importance of location to Retail Companies.
Teller, C. (2008). Shopping streets versus shopping malls–determinants of agglomeration format attractiveness from the consumers' point of view. The International Review of Retail, Distribution and Consumer Research, 18(4), 381-403.  https://doi.org/10.1080/09593960802299452
Teller, C., Alexander, A., & Floh, A. (2016). The impact of competition and cooperation on the performance of a retail agglomeration and its stores. Industrial Marketing Management, 52, 6-17.  https://doi.org/10.1016/j.indmarman.2015.07.010
Teller, C., Wood, S., & Floh, A. (2016). Adaptive resilience and the competition between retail and service agglomeration formats: an international perspective. Journal of Marketing Management, 32(17-18), 1537-1561. https://doi.org/10.1080/0267257X.2016.1240705
Turhan, G., Akalın, M., & Zehir, C. (2013). Literature review on selection criteria of store location based on performance measures. Procedia-Social and Behavioral Sciences, 99, 391-402.  https://doi.org/10.1016/j.sbspro.2013.10.507
Yoon, H. (2018). Interrelationships between retail clusters in different hierarchies, land value and property development: A panel VAR approach. Land Use Policy, 78, 245-257.  https://doi.org/10.1016/j.landusepol.2018.06.032
Wieland, T. (2023). A micro‐econometric store choice model incorporating multi‐and omni‐channel shopping: The case of furniture retailing in Germany. Geographical Analysis, 55(1), 3-30. https://doi.org/10.1111/gean.12308
Zheng, B., Lin, X., Yin, D., & Qi, X. (2023). Does Tobler’s first law of geography apply to internet attention? A case study of the Asian elephant northern migration event. Plos one, 18(3), e0282474. https://doi.org/10.1371/journal.pone.0282474