東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Integrating social network effects in product design and diffusion.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Integrating social network effects in product design and diffusion./
Author:	Gunnec, Dilek.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2012,
Description:	159 p.
Notes:	Source: Dissertations Abstracts International, Volume: 74-06, Section: A.
Contained By:	Dissertations Abstracts International74-06A.
Subject:	Operations research. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3543285
ISBN:	9781267720344

Integrating social network effects in product design and diffusion.
Gunnec, Dilek.

Integrating social network effects in product design and diffusion. - Ann Arbor : ProQuest Dissertations & Theses, 2012 - 159 p.

Source: Dissertations Abstracts International, Volume: 74-06, Section: A.

Thesis (Ph.D.)--University of Maryland, College Park, 2012.

This item is not available from ProQuest Dissertations & Theses.

Connectivities among people are amplified with recent advancements in internet technology increasing the number of communication channels. Information spread over these networks strengthen the social influence among individuals and affect their purchasing decisions. In this thesis, we study three problems in the product design and diffusion context by integrating such social network effects where influence takes place over neighborhood relationship ties among the users of the product. We consider the setting where peer influence plays a significant role in a consumer's product choice or there is a tangible benefit from using the same product as the rest of one's social network. Building upon the well-known Share-of-Choice problem, we model an influence structure and define the Share-of-Choice problem with Network Effects. It is an NP-Hard combinatorial optimization problem which we solve using a Genetic Algorithm. Using simulated data we show that ignoring social network effects in the design phase of a product results in a significantly lower market share for a product. Our genetic algorithm obtains near-optimal solutions and is very robust in terms of its running time, scalability, and ability to adapt to additional constraints/variations of the model. In this setting, we introduce a product diffusion problem, the Least Cost Influence Problem, which increases the market share of a product by intervening the natural diffusion of it over the social network. This intervention is in the form of incentive supply to a group of people in a least costly way while maximizing the spread of the product. We generalize the Least Cost Influence Problem by moving away from the marketing setting and by treating the previous product as any piece of "information" that can spread over a social network by adoption. We show that this problem is polynomially solvable over tree networks under some conditions. We provide a Dynamic Programming algorithm to solve this problem and show that it can be interpreted as a greedy algorithm that gives incentives starting with the people that are least influenced by their neighbors, albeit the definition of susceptibility to influence from neighbors is updated throughout the algorithm. We introduce a two dimensional influence model and extend our modeling and solution methods for the product line design problem which involves designing multiple products within the same product line with the objective of appealing to the heterogeneous structure of the market. The first dimension of influence is the affection of individuals from using the same product, and the second dimension is the influence of using a similar product from the same product line which has a lower intensity of influence. We reexamine the Least Cost Influence Problem in the product line setting.

ISBN: 9781267720344Subjects--Topical Terms:

547123
Operations research.
Subjects--Index Terms:

Diffusion

Integrating social network effects in product design and diffusion.
LDR:04186nmm a2200397 4500 001 2343420
005 20220502104250.5
008 241004s2012 ||||||||||||||||| ||eng d
020 $a 9781267720344
035 $a (MiAaPQ)AAI3543285
035 $a (MiAaPQ)umd:13604
035 $a AAI3543285
040 $a MiAaPQ $c MiAaPQ
100 1 $a Gunnec, Dilek. $3 3681981
245 1 0 $a Integrating social network effects in product design and diffusion.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2012
300 $a 159 p.
500 $a Source: Dissertations Abstracts International, Volume: 74-06, Section: A.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Raghavan, Subramanian.
502 $a Thesis (Ph.D.)--University of Maryland, College Park, 2012.
506 $a This item is not available from ProQuest Dissertations & Theses.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a Connectivities among people are amplified with recent advancements in internet technology increasing the number of communication channels. Information spread over these networks strengthen the social influence among individuals and affect their purchasing decisions. In this thesis, we study three problems in the product design and diffusion context by integrating such social network effects where influence takes place over neighborhood relationship ties among the users of the product. We consider the setting where peer influence plays a significant role in a consumer's product choice or there is a tangible benefit from using the same product as the rest of one's social network. Building upon the well-known Share-of-Choice problem, we model an influence structure and define the Share-of-Choice problem with Network Effects. It is an NP-Hard combinatorial optimization problem which we solve using a Genetic Algorithm. Using simulated data we show that ignoring social network effects in the design phase of a product results in a significantly lower market share for a product. Our genetic algorithm obtains near-optimal solutions and is very robust in terms of its running time, scalability, and ability to adapt to additional constraints/variations of the model. In this setting, we introduce a product diffusion problem, the Least Cost Influence Problem, which increases the market share of a product by intervening the natural diffusion of it over the social network. This intervention is in the form of incentive supply to a group of people in a least costly way while maximizing the spread of the product. We generalize the Least Cost Influence Problem by moving away from the marketing setting and by treating the previous product as any piece of "information" that can spread over a social network by adoption. We show that this problem is polynomially solvable over tree networks under some conditions. We provide a Dynamic Programming algorithm to solve this problem and show that it can be interpreted as a greedy algorithm that gives incentives starting with the people that are least influenced by their neighbors, albeit the definition of susceptibility to influence from neighbors is updated throughout the algorithm. We introduce a two dimensional influence model and extend our modeling and solution methods for the product line design problem which involves designing multiple products within the same product line with the objective of appealing to the heterogeneous structure of the market. The first dimension of influence is the affection of individuals from using the same product, and the second dimension is the influence of using a similar product from the same product line which has a lower intensity of influence. We reexamine the Least Cost Influence Problem in the product line setting.
590 $a School code: 0117.
650 4 $a Operations research. $3 547123
650 4 $a Studies. $3 3433795
650 4 $a Influence. $3 1973172
650 4 $a Peer relationships. $3 3435318
650 4 $a Innovations. $3 754112
650 4 $a Purchasing. $3 652497
653 $a Diffusion
653 $a Product design
653 $a Social network effects
690 $a 0338
690 $a 0454
690 $a 0796
710 2 $a University of Maryland, College Park. $b Business and Management: Decision & Information Technologies. $3 1678266
773 0 $t Dissertations Abstracts International $g 74-06A.
790 $a 0117
791 $a Ph.D.
792 $a 2012
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3543285