نوع مقاله : مقاله پژوهشی (آمیخته )

نویسندگان

• محمدمهدی رضوانی ¹
• میثم کشاورز ²
• محمد هادی عسگری ^{3، 4}

¹ دکترای سنجش از دور و سیستم اطلاعات مکانی، رئیس کمیته ژئومارکتنیگ انجمن مدیریت کسب و کار ایران.

² دانش آموخته دوره دکترای مدیریت جامع کسب‌وکار، رئیس کمیته نگارندگان و مترجمان انجمن مدیریت کسب و کار ایران.

³ استادیار، گروه مدیریت بازرگانی،واحد تنکابن ، دانشگاه آزاد اسلامی ، تنکابن ،ایران .

⁴ رئیس انجمن مدیریت کسب و کار ایران.

چکیده

هدف از این مقاله بررسی دقیقتر قابلیت‌های توسعه عنصر مکان بر بستر راهبرد ژئومارکتینگ در ارتباط با هریک از عناصر آمیخته بازاریابی (قیمت و محصول و ترویج) است که با ارائه تعریفی نوین از این سرفصل به‌همراه تبیین اصولی، مراحل پیاده‌سازی یک پروژه ‌استاندارد ژئومارکتینگ با استناد به داده‌های واقعی شهر تهران در نحوه هدایت و راهبری سیاست‌گذاری‌های یک کسب‌وکار آمده ‌است. در این مقاله با جمع‌آوری اطلاعات و فراوری آنها در 6 مولفه کسب‌وکاری نسبت به ‌استخراج پتانسیل‌های مغفول در توسعه شعبات یک برند پوشاک با پیاده‌سازی تحلیل‌های تصمیم‌گیری چندمعیاره و میانگین وزنی حاصل جمع‌آوری حاصل نظر 11 خبره حوزه پوشاک بر بستر نرم افزار ArcGIS اقدام شد. در انتها با سه محدوده بلوار ارتش، آبشناسان و میدان شهدا بعنوان محدوده‌های پرپتانسیل با پیاده مشخص گردید و به تفسیر گذاشته شد.

کلیدواژه‌ها

• ژئومارکتینگ
• بازاریابی مکان محور
• آمیخته بازاریابی
• سیستم اطلاعات جغرافیایی
• تحلیل های تصمیم گیری چندمعیاره
• پلن توسعه فروشگاهی

20.1001.1.00000000.1402.3.3.2.8

موضوعات

• مدیریت کسب و کار

عنوان مقاله [English]

Geomarketing, the superiority of the place element from the marketing mix, case study: the expansion plan of the garment stores in districts of Tehran

نویسندگان [English]

• Mohammad Mahdi Rezvani ¹
• meisam Keshavarz ²
• Mohammad Hadi Asgari ^{3 4}

¹ PhD of Remote Sensing and Geopatial Information System, Chairman of GeoMarketing Committee of Iran Business Management Association.

² Graduated from the comprehensive business management doctoral course, Chairman of Writers and Translators Committee of Iran Business Management Association,. The head of the committee of writers and

³ Assistant Professor, Department of Business Management, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran.

⁴ President of Iran Business Management Association.

چکیده [English]

Abstract
Geomarketing is a new interdisciplinary knowledge that has been increasingly used with the development of technology and tools for collecting location data, especially in organizations developed in the geographical area. In fact, GeoMarketing should be considered as a kind of engineering of the neglected element of location in minimizing the uncertainties of marketing policies, so that it has the ability to challenge the traditional models of developing marketing strategies. GeoMarketing should be considered as a scientific and operational strategy in measuring the spatial acceptability of policy feedback before adopting them on the basis of smart maps. The purpose of this article is to examine more closely the capabilities of the development of the Place element on the basis of the GeoMarketing strategy in relation to each elements of marketing mix (price, product and promotion). which by providing a new definition of this topic along with the basic explanation, Implementation steps of Tehran's standard geomarketing project to guide the policies of a business..
In this article, by collecting information and processing them in 7 business components, in relation to the extraction of neglected potentials in the development of the branches of a clothing brand, by implementing multi-criteria decision analysis and the weighted average result of collecting the opinions of 11 experts in the field of clothing on the software platform ArcGIS was implemented. In the end, the three areas of Artesh Boulevard, Abshenasan and Shohada Square were identified as areas of potential with pedestrians and left for interpretation. It is obvious that this new topic is in the early stages of its maturity and it is suggested to discover its practical capabilities in other business topics.
Extended Abstract
Introduction
Geomarketing was first proposed as a new marketing method in 1990, and research-oriented articles mention the advantages of including geographic information in marketing methods (Shweta & Rohit, 2023). This method was used over time with the development of technologies related to location calculation, such as the Global Positioning System (GPS), even for the banking industry and the development of urban tourism (Sabet et al., 2021). In general, geomarketing is the set of activities in which location information is used to improve the accuracy and efficiency of marketing programs. It is worth noting that this information are extracted from various sources such as GPS; field observations; aerial and satellite images; digital maps; local data; etc. (Shweta & Rohit, 2023).
Choosing optimal locations in a store development program is one of the main conditions for the success rate of a store. The problem that was tried to be answered in this research with a scientific and operational solution by the basic implementation of the geomarketing strategy in the branch development program of one of the clothing brands in Tehran. In line with the basic explanation of geomarketing services, the superiority of the element of place for each and every elements of the marketing mix has been elaborated; and then the implementation steps of a geomarketing project were presented in order to find the most productive locations in a store branch development program in Tehran's clothing field. For this purpose, by considering 6 main components in the optimal location selection of store locations in the clothing field, in relation to the collection of spatial data and their processing, a multi-criteria decision-making model was implemented. Then, the processed components were weighted based on the opinion of active experts in this field, and the most potential locations were extracted in the developed model.
Research literature
The main goal in the new geomarketing strategy is to scientifically consider the neglected element of location in business decisions. Philip Kotler, the father of modern marketing science, was the first to codify the marketing mix concept as it is today under the title of 4P (Perreault & McCarthy 2002); and 7P, 15P, and 44P models were also developed later. Meanwhile, the combination of four elements including location, promotion, price, and product is the main reference of researchers in this field such as Singh (2012).
Understanding that every customer is located in a geographical point of the earth having the nature of location is the main key in defining and explaining geomarketing services in each and every elements of marketing mix. In fact, geomarketing should be called the engineering science of location, the result of the intersection of marketing science and geographic information science (GIS). It is obvious that explaining the concept of geomarketing requires examining the services and capabilities that can be provided in each and every marketing mix elements (García et al., 2022). In the following, considering the research articles of Ramadan et al., (2017); Farmanesh et al., (2017); Cliquet & Baray (2020); and Baray & Pelé (2020) to derive a standard mechanism in how to define, collect and process business indicators in a geomarketing project was discussed with a case study on the optimal location of new branches of a clothing brand in Tehran, considering 6 components including household density; financial ability; foot traffic; away from competitors; micro business density; and the accesses were investigated.
Research methodology
The present research was carried out by implementing the practical steps of geomarketing with the sample of Tehran. After defining the project and assessing the need, determining the information layers determined in the previous stage and taking action to collect and update of the available data was performed by using different tools from different sources. In the preparation phase, the spatial data that was collected from different sources in the previous phase; sometimes in different formats, was integrated; and after cleaning, necessary measures were taken to prepare them in order to implement advanced spatial analysis, which is known as data cleaning and GeoData preparing. GIS Ready, GeoData Referencing, and GeoDatabase Implementation can be mentioned among the measures taken in this stage. In the processing phase, the raw data collected and prepared with the processes required by a project and explained and defined in the analysis phase of the need and definition of the project are upgraded to the maturity level of information. Thermal maps or heatmaps are among the most widely used outputs at this level, which are referred to under the Spatial Analyst analysis collection in the user space of spatial data science software (DANIELE, 2019). In the conducted research, a number of outputs derived from the above analysis on the data collected in Tehran city were mentioned. The household density component taken from the latest census of the Statistics Center, Financial ability component derived from the average rental price of the neighborhoods of Tehran, foot traffic component derived from the implementation of proximity analysis on the data of commercial centers and shopping centers in Tehran, and the distance component from competitors through the collection of the location of more than 1000 store locations of garment area in Tehran city from Google Map data, micro business density component based on more than 36,000 micro businesses registered in Google Map and accesses including the integration of parameters of main roads with maximum impact, secondary roads at the second level of importance, taxi stations, buses, subway and parking lots at the third level of importance, were collected with weights of 40, 35 and 25, respectively. In order to process the six data mentioned in the extraction of high-yield points in the aforementioned store development planning, a specific placement model based on the multi-criteria decision-making algorithm or MCDM was developed based on the Raster Calculator analysis of the Spatial Analyst analysis package in the ArcGIS software space with the obtained weights. In the special integrated model developed in the processing of components in order to implement multi-criteria decision analysis, the blue circles represent the variables (six components and their subsets), and the yellow rectangles represent the processing steps in the data processing, which is implemented in the last part of the decision analysis.
Research findings
The results of the weights assigned to each of the 6 components acquired from the average expert opinion of 11 people active in the field of clothing were presented in a table. Also, the results of the output in the integrated model indicate the existence of three areas full of neglected potential in the field of clothing in Tehran, including the first area (Artesh Blvd.) between Sohanak and Oshan Boulevard; the second area (Abshenasan highway) between Ashrafi Esfahani and Bakeri highways; and the third area (Shohada Square to Imam Hossein Square). All the above three cases were located in the commercial centers of Tehran city, while in the field surveys, the accumulation of the presence of medium and large shopping centers including Parnian Center, Mahtab, Nakhl, Morvarid and Shemiran Center was only within the determined potential range of the first range. The occurrence of the same issue in the second area, including Qaim, Maryam, Ghadir shopping centers, as well as Goldis, Bahar and Zomorrod shopping centers in the third area shows the high potentials of the clothing field in the proposed areas.
Conclusion
Managers of any business always make strategic decisions to determine the survival and success of that business. Ignoring each of the different success parameters makes decisions' success faced with challenge. Decision-making algorithms and analyzes in GIS not only consider all the influential parameters in the form of information layers, but also determine and define the impact of each one by the ability to weight each one (Tu Le et al., 2023). In practice, at this level, the intra-organizational, peripheral, and extra-organizational information layers that were prepared and processed in the previous stages were modeled in different scenarios and weight combinations using advanced spatial data science analyzes so that the feedback measurement and spatial acceptability measurement of decisions and policies makes it possible on the basis of the map. In this strategy, it is important to minimize uncertainties by optimally allocating resources to the most productive points in the geography of the market. The uniqueness of geomarketing evolves by integrating functions and spatial analysis in order to solve problems related to the development of local, regional and extra-regional markets with different social, economic and political approaches as the driving force of modern marketing knowledge (Tkhorikov et al., 2020).
Marketing mix elements are one of the main topics that are always cited and evaluated in the formulation of marketing strategies (Thabit & Manaf 2018). Location is one of these pillars that, due to the development of information infrastructure and software based on GIS knowledge, is able to provide unique capabilities along with the development of businesses and brands in global markets (Matheus et al., 2020).
The authors of the article believe that the absence or lack of standard location data has made it difficult to refer to the achievements and outputs of geomarketing in practice. In this article, by explaining a comprehensive definition, it was tried to investigate the geomarketing solutions that can be presented in each of the elements of the marketing mix, and its applications were introduced by determining the implementation steps with reference to Tehran's business data.
It is suggested that case studies on the implementation of the services of this strategy to be implemented in other business areas such as restaurants, banking industry and broadcasting industry by the researchers of this field, and geomarketing services investigated specifically for each of the elements of the marketing mix based on real business data.
 

کلیدواژه‌ها [English]

• Geomarketing
• location-based marketing
• marketing mix
• geographic information system
• multi-criteria decision making
• store expansion plan