Determining the mobile device offering at a large SA retailer
| dc.contributor.advisor | Nieuwoudt, Isabelle | en_ZA |
| dc.contributor.author | Dagnin, Monique | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics. | en_ZA |
| dc.date.accessioned | 2023-03-06T08:50:50Z | |
| dc.date.accessioned | 2023-05-18T07:19:59Z | |
| dc.date.available | 2023-03-06T08:50:50Z | |
| dc.date.available | 2023-05-18T07:19:59Z | |
| dc.date.issued | 2023-03 | |
| dc.description | Thesis (MCom)--Stellenbosch University, 2023. | en_ZA |
| dc.description.abstract | ENGLISH SUMMARY: The retail industry is one of the biggest industries in the world and an important factor in the success of retailers, is carrying the correct products for their customers. The Retailer in this study, like many other retailers, provides a range of financial services and products to their customers to add value and improve the customers’ experience in their stores. Therefore, the aim of this study is to assist The Retailer in determining the best range of mobile devices to keep in stock in their stores. The Retailer has over 1 280 stores and was seeking device ranges for store groups, rather than a unique range for each individual store. Therefore, stores with similar characteristics are grouped based on several external factors that were identified. Hierarchical clustering is used to group similar stores within each supermarket type based on the number of landlines, rate of population change, population age and population income. Six clusters, two per supermarket type, are found with this method. For each group of stores, the range of mobile devices to keep in stock is determined using three performance measures, namely rate of sale, total units sold and average units in stock. These measures are calculated to evaluate the performance of mobile devices and rank the devices according to their performance. Two iterative approaches are followed to determine whether a device should be ranged in any of the six clusters. For mobile devices that have not been ranged in a particular store, but should be ranged according to their performance, the required stock level in these stores is determined by estimating the rate of sale per store using a regression tree for each mobile device. To build the regression trees, population age, rate of population change, population income, number of landlines, store size, province in which a store is located, adapted mobile device category rate of sale, average sales amount per store and total number of mobile devices sold in a store are used as independent variables. The methodology is illustrated using a selection of The Retailer’s devices currently in stock. Eleven of these 30 sampled mobile devices are ranged using this methodology, suggesting that this methodology succeeds in reducing the variety of mobile devices ranged by The Retailer by removing under performing devices. | en_ZA |
| dc.description.abstract | AFRIKAANSE OPSOMMING: Die kleinhandelbedryf is een van die grootste nywerhede ter wereld en om die regte produkte aan te hou, is ’n belangrike faktor in die sukses van kleinhandelaars. Die Kleinhandelaar in hierdie studie verskaf, soos baie ander kleinhandelaars, finansiele produkte en dienste aan hul kliente om waarde toe te voeg en die kliente se ervaring in hul winkels te verbeter. Dus is die doelwit van hierdie studie om Die Kleinhandelaar te help om die beste reeks selfone te bepaal om in hul winkels in voorraad te hou. Die Kleinhandelaar het meer as 1 280 winkels en was op soek na ’n reeks selfone vir winkelgroepe, eerder as ’n reeks per individuele winkel. Dus word winkels met soortgelyke eienskappe word dan op grond van verskeie eksterne faktore gegroepeer. Hierargiese groepering word gebruik om soortgelyke winkels binne elke supermarktipe op grond van die aantal landlyne, bevolkingsveranderingskoers, bevolkingsouderdom en bevolkingsinkomste te groepeer. Ses groepe, twee per supermarktipe, word met hierdie metode gevind. Vir elke groep winkels, word die reeks selfone wat in voorraad gehou moet word, met behulp van ’n drie prestasiemaatstawwe, naamlik die verkoopskoers, die totale eenhede verkoop en die gemiddelde eenhede in voorraad, bepaal. Die prestasiemaatstawwe word bereken om die prestasie van selfone te evalueer en daarvolgens te rangskik. Twee benaderings word gevolg om te bepaal of ’n selfoon in enige van die ses winkelgroepe aangehou moet word. Vir selfone wat nie in ’n spesifieke winkel aangehou word nie, maar volgend hul prestasie aangehou behoort te word, word die vereiste voorraadvlak in hierdie winkel bepaal deur die verkoopkoers, deur middel van ’n regressieboom, te benader. Om die regressiebome te bou, word die bevolkingsouderdom, bevolkingsveranderingskoers, bevolkingsinkomste, aantal landlyne, winkelgrootte, provinsie waarin ’n winkel gelee is, aangepaste verkoopkoers vir die selfoonkategorie, gemiddelde verkoopsprys per winkel en die totale aantal toestelle wat in ’n winkel aangehou word, as onafhanklike veranderlikes gebruik. Die metodologie word deur ’n steekproef van Die Kleinhandelaar se huidige selfone geillustreer. Elf van die 30 selfone in die steekproef word steeds volgens hierdie metodologie aangehou, wat daarop dui dat hierdie metodologie daarin slaag om die verskeidenheid selfone wat deur Die Kleinhandelaar aangehou word, te verminder deur onderpresterende toestelle te verwyder. | af_ZA |
| dc.description.version | Masters | |
| dc.format.extent | 119 pages : illustrations (some color), maps, includes annexures | |
| dc.identifier.uri | http://hdl.handle.net/10019.1/127395 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | |
| dc.rights.holder | Stellenbosch University | |
| dc.subject.lcsh | Cell phones -- Selling -- South Africa | en_ZA |
| dc.subject.lcsh | Cell phones -- Sales promotion -- South Africa | en_ZA |
| dc.subject.lcsh | Business -- Communication systems -- South Africa | en_ZA |
| dc.subject.name | UCTD | |
| dc.title | Determining the mobile device offering at a large SA retailer | en_ZA |
| dc.type | Thesis | en_ZA |
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