CLOUD COMPUTING AND BIG DATA AS CONVERGENT TECHNOLOGIES FOR RETAIL PRICING STRATEGIES OF SMEs
Most retailers know that technology has played an increasingly important role in helping retailers set prices. Online business decision systems are at the core point of an SMEs management and reporting activities. But, until recently, these efforts have been rooted in advances in computing technolog...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nicolae Titulescu University Publishing House
2014-05-01
|
| Series: | Challenges of the Knowledge Society |
| Subjects: | |
| Online Access: | http://cks.univnt.ro/uploads/cks_2014_articles/index.php?dir=12_IT_in_social_sciences%2F&download=CKS+2014_IT_in_social_sciences_art.106.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846146719266373632 |
|---|---|
| author | George SUCIU Gyorgy TODORAN Adelina OCHIAN Victor SUCIU Janna CROPOTOVA |
| author_facet | George SUCIU Gyorgy TODORAN Adelina OCHIAN Victor SUCIU Janna CROPOTOVA |
| author_sort | George SUCIU |
| collection | DOAJ |
| description | Most retailers know that technology has played an increasingly important role in helping retailers set prices. Online business decision systems are at the core point of an SMEs management and reporting activities. But, until recently, these efforts have been rooted in advances in computing technology, such as cloud computing and big data mining, rather than in newfound applications of scientific principles. In addition, in previous approaches big data mining solutions were implemented locally on private clouds and no SME could aggregate and analyze the information that consumers are exchanging with each other. Real science is a powerful, pervasive force in retail today, particularly so for addressing the complex challenge of retail pricing. Cloud Computing comes in to provide access to entirely new business capabilities through sharing resources and services and managing and assigning resources effectively. Done right, the application of scientific principles to the creation of a true price optimization strategy can lead to significant sales, margin, and profit lift for retailers. In this paper we describe a method to provide the mobile retail consumers with reviews, brand ratings and detailed product information at the point of sale. Furthermore, we present how we use Exalead CloudView platform to search for weak signals in big data by analyzing multimedia data (text, voice, picture, video) and mining online social networks. The analysis makes not only customer profiling possible, but also brand promotion in the form of coupons, discounts or upselling to generate more sales, thus providing the opportunity for retailer SMEs to connect directly to its customers in real time. The paper explains why retailers can no longer thrive without a science-based pricing system, defines and illustrates the right science-based approach, and calls out the key features and functionalities of leading science-based price optimization systems. In particular, given a cloud application, we propose to leverage trivial and non-trivial connections between different sensor signals and data from online social networks, in order to find patterns that are likely to provide innovative solutions to existing retail problems. The aggregation of such weak signals will provide evidence of connections between environment and consumer related behavior faster and better than trivial mining of sensor data. As a consequence, the software has a significant potential for matching environmental applications and business challenges that are related in non-obvious ways. |
| format | Article |
| id | doaj-art-fdae2a60530c4acda76bb3e911041afa |
| institution | Kabale University |
| issn | 2068-7796 2068-7796 |
| language | English |
| publishDate | 2014-05-01 |
| publisher | Nicolae Titulescu University Publishing House |
| record_format | Article |
| series | Challenges of the Knowledge Society |
| spelling | doaj-art-fdae2a60530c4acda76bb3e911041afa2024-12-02T01:33:44ZengNicolae Titulescu University Publishing HouseChallenges of the Knowledge Society2068-77962068-77962014-05-014110441052CLOUD COMPUTING AND BIG DATA AS CONVERGENT TECHNOLOGIES FOR RETAIL PRICING STRATEGIES OF SMEsGeorge SUCIU0Gyorgy TODORAN1Adelina OCHIAN2Victor SUCIU3Janna CROPOTOVA4PhD candidate, Dipl. Eng, Faculty of Electronics, Telecommunications and Information Technology, 3CPS Department, University POLITEHNICA of Bucharest (e-mail: george@beia.ro).PhD candidate, Dipl. Eng, Faculty of Electronics, Telecommunications and Information Technology, TEF Department, University POLITEHNICA of Bucharest (e-mail: todoran.gyorgy@gmail.com).Dipl. Eng, Faculty of Electronics, Telecommunications and Information Technology, University POLITEHNICA of Bucharest (e-mail: adelina@beia.ro)PhD Student, Dipl. Eng, BEIA Consult International, Bucharest (e-mail: victor.suciu@beia.ro).PhD Student, Researcher, Practical Scientific Institute of Horticulture and Food Technology of Chisinau (jcropotova@gmail.com).Most retailers know that technology has played an increasingly important role in helping retailers set prices. Online business decision systems are at the core point of an SMEs management and reporting activities. But, until recently, these efforts have been rooted in advances in computing technology, such as cloud computing and big data mining, rather than in newfound applications of scientific principles. In addition, in previous approaches big data mining solutions were implemented locally on private clouds and no SME could aggregate and analyze the information that consumers are exchanging with each other. Real science is a powerful, pervasive force in retail today, particularly so for addressing the complex challenge of retail pricing. Cloud Computing comes in to provide access to entirely new business capabilities through sharing resources and services and managing and assigning resources effectively. Done right, the application of scientific principles to the creation of a true price optimization strategy can lead to significant sales, margin, and profit lift for retailers. In this paper we describe a method to provide the mobile retail consumers with reviews, brand ratings and detailed product information at the point of sale. Furthermore, we present how we use Exalead CloudView platform to search for weak signals in big data by analyzing multimedia data (text, voice, picture, video) and mining online social networks. The analysis makes not only customer profiling possible, but also brand promotion in the form of coupons, discounts or upselling to generate more sales, thus providing the opportunity for retailer SMEs to connect directly to its customers in real time. The paper explains why retailers can no longer thrive without a science-based pricing system, defines and illustrates the right science-based approach, and calls out the key features and functionalities of leading science-based price optimization systems. In particular, given a cloud application, we propose to leverage trivial and non-trivial connections between different sensor signals and data from online social networks, in order to find patterns that are likely to provide innovative solutions to existing retail problems. The aggregation of such weak signals will provide evidence of connections between environment and consumer related behavior faster and better than trivial mining of sensor data. As a consequence, the software has a significant potential for matching environmental applications and business challenges that are related in non-obvious ways.http://cks.univnt.ro/uploads/cks_2014_articles/index.php?dir=12_IT_in_social_sciences%2F&download=CKS+2014_IT_in_social_sciences_art.106.pdfCloud ComputingBig DataRetail Pricing StrategiesSmall and Medium Enterprise; |
| spellingShingle | George SUCIU Gyorgy TODORAN Adelina OCHIAN Victor SUCIU Janna CROPOTOVA CLOUD COMPUTING AND BIG DATA AS CONVERGENT TECHNOLOGIES FOR RETAIL PRICING STRATEGIES OF SMEs Challenges of the Knowledge Society Cloud Computing Big Data Retail Pricing Strategies Small and Medium Enterprise; |
| title | CLOUD COMPUTING AND BIG DATA AS CONVERGENT TECHNOLOGIES FOR RETAIL PRICING STRATEGIES OF SMEs |
| title_full | CLOUD COMPUTING AND BIG DATA AS CONVERGENT TECHNOLOGIES FOR RETAIL PRICING STRATEGIES OF SMEs |
| title_fullStr | CLOUD COMPUTING AND BIG DATA AS CONVERGENT TECHNOLOGIES FOR RETAIL PRICING STRATEGIES OF SMEs |
| title_full_unstemmed | CLOUD COMPUTING AND BIG DATA AS CONVERGENT TECHNOLOGIES FOR RETAIL PRICING STRATEGIES OF SMEs |
| title_short | CLOUD COMPUTING AND BIG DATA AS CONVERGENT TECHNOLOGIES FOR RETAIL PRICING STRATEGIES OF SMEs |
| title_sort | cloud computing and big data as convergent technologies for retail pricing strategies of smes |
| topic | Cloud Computing Big Data Retail Pricing Strategies Small and Medium Enterprise; |
| url | http://cks.univnt.ro/uploads/cks_2014_articles/index.php?dir=12_IT_in_social_sciences%2F&download=CKS+2014_IT_in_social_sciences_art.106.pdf |
| work_keys_str_mv | AT georgesuciu cloudcomputingandbigdataasconvergenttechnologiesforretailpricingstrategiesofsmes AT gyorgytodoran cloudcomputingandbigdataasconvergenttechnologiesforretailpricingstrategiesofsmes AT adelinaochian cloudcomputingandbigdataasconvergenttechnologiesforretailpricingstrategiesofsmes AT victorsuciu cloudcomputingandbigdataasconvergenttechnologiesforretailpricingstrategiesofsmes AT jannacropotova cloudcomputingandbigdataasconvergenttechnologiesforretailpricingstrategiesofsmes |