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The effectiveness of business-to-bus...

Purdue University., Agricultural Economics.

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The effectiveness of business-to-business word-of-mouth marketing strategies.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The effectiveness of business-to-business word-of-mouth marketing strategies./
Author:	Xu, Pei.
Description:	217 p.
Notes:	Advisers: Jay T. Akridge; Joan Fulton.
Contained By:	Dissertation Abstracts International69-05B.
Subject:	Agriculture, Agronomy. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3307385
ISBN:	9780549562863

The effectiveness of business-to-business word-of-mouth marketing strategies.
Xu, Pei.

The effectiveness of business-to-business word-of-mouth marketing strategies. - 217 p.

Advisers: Jay T. Akridge; Joan Fulton.

Thesis (Ph.D.)--Purdue University, 2007.

Facilitated business-to-business (B2B) word-of-mouth (WOM) is becoming an important marketing tactic. A paucity of academic research has measured the effectiveness of facilitated B2B WOM. Previous research has also failed to adequately measure its effectiveness on target audiences' purchase decisions, information sharing decisions and its reinforcement effect on manufacturer advertising.

ISBN: 9780549562863Subjects--Topical Terms:

1018679
Agriculture, Agronomy.

The effectiveness of business-to-business word-of-mouth marketing strategies.
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035 $a (UMI)AAI3307385
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040 $a UMI $c UMI
100 1 $a Xu, Pei. $3 1057558
245 1 4 $a The effectiveness of business-to-business word-of-mouth marketing strategies.
300 $a 217 p.
500 $a Advisers: Jay T. Akridge; Joan Fulton.
500 $a Source: Dissertation Abstracts International, Volume: 69-05, Section: B, page: 2679.
502 $a Thesis (Ph.D.)--Purdue University, 2007.
520 $a Facilitated business-to-business (B2B) word-of-mouth (WOM) is becoming an important marketing tactic. A paucity of academic research has measured the effectiveness of facilitated B2B WOM. Previous research has also failed to adequately measure its effectiveness on target audiences' purchase decisions, information sharing decisions and its reinforcement effect on manufacturer advertising.
520 $a A conceptual framework was employed to model the effectiveness of facilitated B2B WOM on target audiences' purchase volume, the time of first adoption, information sharing decisions, and recall of product benefits as signaled by manufacturer advertising. Other factors that affect purchase decisions were also considered including product characteristics, audience characteristics, and manufacturer influences. These factors interact with facilitated B2B WOM to shape target audiences' purchase decisions.
520 $a Four products were selected to conduct this study including two crop expendable inputs, a livestock expendable input and a companion animal product. Data were collected through telephone surveys with initiative participants and non-participants. Both linear regression estimation and Logit estimation procedures were employed to test hypotheses about the effectiveness of facilitated B2B WOM.
520 $a Results suggest that the interaction between facilitated B2B WOM and a respondent's previous experiences with the product affects the quantity purchased. A direct effect of B2B WOM on purchase behavior was not measured at standard levels of statistical significance. Participation in a facilitated B2B WOM initiative did not have a statistically significant impact on the time of first adoption of the two crop expendable inputs. Facilitated B2B WOM was reported to have some impact on a respondent's recall of benefits about a Canadian crop expendable input as signaled by manufacturer advertising messages. In addition, participants in B2B WOM initiatives clearly shared information with peers/clients and characteristics of initiative participants who shared information with larger numbers of peers/clients were identified.
520 $a Future research should expand sample size, use actual purchase quantities instead of respondent estimates, and consider the lag between respondent participation in the initiative and the assessment of benefits to improve the ability to measure the impact of facilitated B2B WOM initiatives. Also, exploring the return on investment (ROI), including all behavioral impacts of the B2B WOM initiative, would be productive.
590 $a School code: 0183.
650 4 $a Agriculture, Agronomy. $3 1018679
650 4 $a Business Administration, Marketing. $3 1017573
690 $a 0285
690 $a 0338
710 2 0 $a Purdue University. $b Agricultural Economics. $3 1020282
773 0 $t Dissertation Abstracts International $g 69-05B.
790 $a 0183
790 1 0 $a Akridge, Jay T., $e advisor
790 1 0 $a Alexander, Corinne $e committee member
790 1 0 $a Fulton, Joan, $e advisor
790 1 0 $a Tang, Jen $e committee member
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3307385