Optimal pricing strategies for online auction entrepreneurs
- Authors: Knox, Ian , Lynch, David
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at 30th Institute for Small Business & Entrepreneurship Conference, Glasgow, Scotland : 7th-9th November 2007
- Full Text:
- Description: Objectives: Online auctions have emerged as a major opportunity for individuals to start businesses or for established businesses to diversify and grow their markets. To-date, research interest has focused largely on the technological entrepreneur rather than the Internet based (cyber) entrepreneur. The aim of this study was to examine the behaviour of participants in online auctions, in order to predict optimal selling strategies. Prior work: While auction pricing has been the subject of theoretical research (Budish and Takeyama, 2001; Maskin and Riley, 1985) little empirical data has been collected. Pricing decisions are largely unresolved in the marketing literature despite the importance for consumer perceptions of value. The implication is that managing the price (expectation) for a product in an online auction is important and may be achieved by reference price management. Nagle and Hogan (2006) allude to the distinction between price management and reference price management but suggest that they are clearly interlinked. Approach: A response to changed independent variables under actual market conditions was measured. 1,000 books were offered for sale on eBay. To test the study’s hypotheses, a one way ANOVA was initially undertaken to separately examine differences in the % of recommended retail price (RRP) for each of the study’s independent variables – postage, starting price and length of auction. A factorial ANOVA was completed and an OLS regression analysis was undertaken to assess the effects of selling strategies on the % of RRP obtained. Results: A high start price was found to significantly increase the average percentage of RRP received, contrary to popular belief that favours low start prices. Free postage, was not found to be significant except when combined with a low % of RRP achieved. The optimal auction duration was five days, suggesting, 10 day auctions provide no additional benefits and may in fact result in a lower %RRP achieved. Implications: Early online auction research consistently highlighted the opinion that Internet auctions were primarily concerned with the sale of collectable goods. An examination of 2007 auction data clearly illustrates that this is no longer the case, and in fact the sale of non-collectable goods now dominates, indicating a need for alternative selling strategies, for common value items. Value: No previous work to date has manipulated auction start prices to assess potential profitability. These findings are particularly significant to assist online auction entrepreneurs to develop optimal selling strategies.
- Description: 2003005204
- Authors: Knox, Ian , Lynch, David
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at 30th Institute for Small Business & Entrepreneurship Conference, Glasgow, Scotland : 7th-9th November 2007
- Full Text:
- Description: Objectives: Online auctions have emerged as a major opportunity for individuals to start businesses or for established businesses to diversify and grow their markets. To-date, research interest has focused largely on the technological entrepreneur rather than the Internet based (cyber) entrepreneur. The aim of this study was to examine the behaviour of participants in online auctions, in order to predict optimal selling strategies. Prior work: While auction pricing has been the subject of theoretical research (Budish and Takeyama, 2001; Maskin and Riley, 1985) little empirical data has been collected. Pricing decisions are largely unresolved in the marketing literature despite the importance for consumer perceptions of value. The implication is that managing the price (expectation) for a product in an online auction is important and may be achieved by reference price management. Nagle and Hogan (2006) allude to the distinction between price management and reference price management but suggest that they are clearly interlinked. Approach: A response to changed independent variables under actual market conditions was measured. 1,000 books were offered for sale on eBay. To test the study’s hypotheses, a one way ANOVA was initially undertaken to separately examine differences in the % of recommended retail price (RRP) for each of the study’s independent variables – postage, starting price and length of auction. A factorial ANOVA was completed and an OLS regression analysis was undertaken to assess the effects of selling strategies on the % of RRP obtained. Results: A high start price was found to significantly increase the average percentage of RRP received, contrary to popular belief that favours low start prices. Free postage, was not found to be significant except when combined with a low % of RRP achieved. The optimal auction duration was five days, suggesting, 10 day auctions provide no additional benefits and may in fact result in a lower %RRP achieved. Implications: Early online auction research consistently highlighted the opinion that Internet auctions were primarily concerned with the sale of collectable goods. An examination of 2007 auction data clearly illustrates that this is no longer the case, and in fact the sale of non-collectable goods now dominates, indicating a need for alternative selling strategies, for common value items. Value: No previous work to date has manipulated auction start prices to assess potential profitability. These findings are particularly significant to assist online auction entrepreneurs to develop optimal selling strategies.
- Description: 2003005204
A comparison of bidding strategies for online auctions using fuzzy reasoning and negotiation decision functions
- Kaur, Preetinder, Goyal, Madhu, Lu, Jie
- Authors: Kaur, Preetinder , Goyal, Madhu , Lu, Jie
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Transactions on Fuzzy Systems Vol. 25, no. 2 (2017), p. 425-438
- Full Text:
- Reviewed:
- Description: Bidders often feel challenged when looking for the best bidding strategies to excel in the competitive environment of multiple and simultaneous online auctions for same or similar items. Bidders face complicated issues for deciding which auction to participate in, whether to bid early or late, and how much to bid. In this paper, we present the design of bidding strategies, which aim to forecast the bid amounts for buyers at a particular moment in time based on their bidding behavior and their valuation of an auctioned item. The agent develops a comprehensive methodology for final price estimation, which designs bidding strategies to address buyers' different bidding behaviors using two approaches: Mamdani method with regression analysis and negotiation decision functions. The experimental results show that the agents who follow fuzzy reasoning with a regression approach outperform other existing agents in most settings in terms of their success rate and expected utility.
- Authors: Kaur, Preetinder , Goyal, Madhu , Lu, Jie
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Transactions on Fuzzy Systems Vol. 25, no. 2 (2017), p. 425-438
- Full Text:
- Reviewed:
- Description: Bidders often feel challenged when looking for the best bidding strategies to excel in the competitive environment of multiple and simultaneous online auctions for same or similar items. Bidders face complicated issues for deciding which auction to participate in, whether to bid early or late, and how much to bid. In this paper, we present the design of bidding strategies, which aim to forecast the bid amounts for buyers at a particular moment in time based on their bidding behavior and their valuation of an auctioned item. The agent develops a comprehensive methodology for final price estimation, which designs bidding strategies to address buyers' different bidding behaviors using two approaches: Mamdani method with regression analysis and negotiation decision functions. The experimental results show that the agents who follow fuzzy reasoning with a regression approach outperform other existing agents in most settings in terms of their success rate and expected utility.
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