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DTSTAMP:20240503T120024Z
SUMMARY:Yasamin Salmani\, PhD Candidate at Drexel University
DESCRIPTION: \n\nTitle: Investment Decision Making in Improving Multiple Sa
 les Channels\n\nAbstract: A supply chain\, employing multiple sales channe
 ls\, needs to\ncontinually enhance these channels for achieving competitiv
 e\nadvantage. The purpose of this dissertation is to provide a systematic\
 nprocedure for optimal investment decisions towards improving existing\nsa
 les channels in a multi-channel multi-product setting. The research\nprovi
 des a channel-level benefit-cost analysis\, rather than the common\nproduc
 t-level profitability\, through the integration of operations and\nmarketi
 ng perspectives. The motivation to undertake this problem is\nthe critical
  decision for investment\, on the part of many established\nfirms that typ
 ically utilize multiple channel structures. This\nultimately helps the fir
 ms to enhance their competitive position\nthrough improvements in the perf
 ormance of sales channels. In pursuing\nour objective\, initially\, we inv
 estigate the customers’ criteria in\nchoosing sales channels in a so-cal
 led omnichannel setting. Then\, we\nsuggest an analytic model that conside
 rs both customer priorities and\ndemand correlations among channels\, for 
 quantifying customer input. We\nexplicitly resolve the major issue of chan
 nel demand correlation that\nmost manufacturers encounter in multichannel 
 retailing. This model is\ntested and verified utilizing an experimental st
 udy in an omnichannel\nretailing environment. Next\, we develop a mathemat
 ical model for\nanalyzing benefits and relevant operational costs associat
 ed with each\nspecific channel. Accordingly\, we propose a novel measureme
 nt for\nbudget allocation decision among already established\, alternate s
 ales\nchannels. We further provide a comprehensive analysis of the effect 
 of\nthe firm’s “cycle service level” and “demand uncertainty” on
 \nthe improvement investment decisions. Later\, we implement the model\nus
 ing a company’s data and demonstrate the practicability of the\nproposed
  methodology.\n 
DTSTART:20190524T180000Z
DTEND:20190524T193000Z
LOCATION:Gerri C. LeBow Hall\, 3220 Market Street\, 408\, Philadelphia\, PA
  19104
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