Geographic Analytics and Visualization for Decision Making: An Application for Online Food Delivery Platform
Karan George1, Sreejith R2, Senthil S3
1Karan George, Rajagiri Business School, Kochi, India.
2Sreejith R, Asst. Professor, Rajagiri College of Social Sciences, Kochi, India.
3Senthil S, Director, School of CSA, REVA University, Bangalore India.
Manuscript received on 06 March 2019 | Revised Manuscript received on 11 March 2019 | Manuscript published on 30 July 2019 | PP: 6453-6458 | Volume-8 Issue-2, July 2019 | Retrieval Number: B220678219/2019©BEIESP | DOI: 10.35940/ijrte.B2206.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Promoting organizers such as marketing planners frequently utilize geographical information systems to single out appropriate retail stores, setting up advertising campaigns based on regions, and target direct showcasing exercises. Geographical information systems topical maps encourage the visual evaluation of regions. A wide arrangement of elective symbolization, for example, circles, bars, or shading, can be utilized to represent quantitative geospatial data on such maps. In any case, there is little learning on which sort of symbolization is most viable for each case. In a huge scale exploratory study, the creators demonstrate that the symbolization firmly impacts choice execution. GIS-based representations encourage the evaluation of store areas and help organizers to choose the most encouraging options. The choice of the best option requires a visual streamlining which is supported by GIS topical maps. In this study, the manner in which how various GIS-based information portrayals impact advertising analyst’s decision making for online food delivery platforms is explored. The outcomes demonstrate that GIS maps are an important piece of work and that sort of guided representation impacts the initiated decision-making process.
Keywords: Geographical Visualization; Food Delivery Platform; Online Food Ordering
Scope of the Article: Big Data Analytics Application Systems