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  • 1
    Online Resource
    Online Resource
    SAGE Publications ; 2009
    In:  Journal of Service Research Vol. 12, No. 1 ( 2009-08), p. 73-86
    In: Journal of Service Research, SAGE Publications, Vol. 12, No. 1 ( 2009-08), p. 73-86
    Abstract: This article focuses on the empirical modeling of advance purchasing and the effects of price on purchasing behavior. Because pricing strategies are typically more complex than simply setting a single price point, the authors consider multiple aspects of price: (a) use of multiple price tiers, (b) face value of tickets, and (c) discounts resulting in week-to-week variations in price. They show that failure to account for price tiers can lead to exaggerated inferences about the role of price over time. Findings reflect substantial differences across tiers. Purchasers in the high-priced tier tend to buy earlier in the selling period and are influenced by price discounts and premiums in the spot market. Purchasers in the low- and mid-priced tiers tend to delay purchasing and are influenced only by face value prices in the spot market. The authors discuss the implications of these empirical observations for future researchers and marketing managers.
    Type of Medium: Online Resource
    ISSN: 1094-6705 , 1552-7379
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2009
    detail.hit.zdb_id: 2020788-8
    SSG: 3,2
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  • 2
    Online Resource
    Online Resource
    Wiley ; 2003
    In:  Journal of Consumer Psychology Vol. 13, No. 1-2 ( 2003-1), p. 29-39
    In: Journal of Consumer Psychology, Wiley, Vol. 13, No. 1-2 ( 2003-1), p. 29-39
    Type of Medium: Online Resource
    ISSN: 1057-7408
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2003
    detail.hit.zdb_id: 2021876-X
    detail.hit.zdb_id: 1109529-5
    SSG: 3,2
    SSG: 5,2
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  • 3
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2004
    In:  Management Science Vol. 50, No. 3 ( 2004-03), p. 299-308
    In: Management Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 50, No. 3 ( 2004-03), p. 299-308
    Abstract: This paper examines search across competing e-commerce sites. By analyzing panel data from over 10,000 Internet households and three commodity-like products (books, compact discs (CDs), and air travel services), we show that the amount of online search is actually quite limited. On average, households visit only 1.2 book sites, 1.3 CD sites, and 1.8 travel sites during a typical active month in each category. Using probabilistic models, we characterize search behavior at the individual level in terms of (1) depth of search, (2) dynamics of search, and (3) activity of search. We model an individual's tendency to search as a logarithmic process, finding that shoppers search across very few sites in a given shopping month. We extend the logarithmic model of search to allow for time-varying dynamics that may cause the consumer to evolve and, perhaps, learn to search over time. We find that for two of the three product categories studied, search propensity does not change from month to month. However, in the third product category we find mild evidence of time-varying dynamics, where search decreases over time from already low levels. Finally, we model the level of a household's shopping activity and integrate it into our model of search. The results suggest that more-active online shoppers tend also to search across more sites. This consumer characteristic largely drives the dynamics of search that can easily be mistaken as increases from experience at the individual level.
    Type of Medium: Online Resource
    ISSN: 0025-1909 , 1526-5501
    RVK:
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2004
    detail.hit.zdb_id: 206345-1
    detail.hit.zdb_id: 2023019-9
    SSG: 3,2
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  • 4
    Online Resource
    Online Resource
    Wiley ; 2017
    In:  Journal of Product Innovation Management Vol. 34, No. 5 ( 2017-09), p. 697-702
    In: Journal of Product Innovation Management, Wiley, Vol. 34, No. 5 ( 2017-09), p. 697-702
    Abstract: While the data from social media platforms are abundant, social media has primarily been viewed as a channel through which marketers can reach consumers. While its use as a promotional channel is important, this perspective ignores the potential value of social media data. From social media data, much can be learned about individual consumers and more broadly networks of consumers. Viewed in this way, social media data can be an important source of insights into consumers that can be used to support marketing decisions. In contrast to more traditional means of gathering insights, social media data are freely provided by the consumers themselves, allowing marketers to hear the “voice of the consumer” directly. In this paper, the authors introduce a framework that views social media data as a source of marketing insights. They then discuss the characteristics of social data that have required innovation in the analytic approaches used to derive actionable marketing insights. The authors identify and elaborate on specific topics in which they believe that social media analytics can serve as a valuable tool for marketers, as well as discuss areas of opportunity for future research.
    Type of Medium: Online Resource
    ISSN: 0737-6782 , 1540-5885
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2012544-6
    detail.hit.zdb_id: 722136-8
    SSG: 3,2
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  • 5
    Online Resource
    Online Resource
    Elsevier BV ; 2012
    In:  SSRN Electronic Journal
    In: SSRN Electronic Journal, Elsevier BV
    Type of Medium: Online Resource
    ISSN: 1556-5068
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2012
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  • 6
    Online Resource
    Online Resource
    Elsevier BV ; 2017
    In:  International Journal of Research in Marketing Vol. 34, No. 1 ( 2017-03), p. 100-119
    In: International Journal of Research in Marketing, Elsevier BV, Vol. 34, No. 1 ( 2017-03), p. 100-119
    Type of Medium: Online Resource
    ISSN: 0167-8116
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2017
    detail.hit.zdb_id: 2014002-2
    detail.hit.zdb_id: 622691-7
    SSG: 3,2
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  • 7
    Online Resource
    Online Resource
    SAGE Publications ; 2014
    In:  Journal of Marketing Research Vol. 51, No. 4 ( 2014-08), p. 387-402
    In: Journal of Marketing Research, SAGE Publications, Vol. 51, No. 4 ( 2014-08), p. 387-402
    Abstract: In this research, the authors jointly model the sentiment expressed in social media posts and the venue format to which it was posted as two interrelated processes in an effort to provide a measure of underlying brand sentiment. Using social media data from firms in two distinct industries, they allow the content of the post and the underlying sentiment toward the brand to affect both processes. The results show that the inferences marketing researchers obtain from monitoring social media are dependent on where they “listen” and that common approaches that either focus on a single social media venue or ignore differences across venues in aggregated data can lead to misleading brand sentiment metrics. The authors validate the approach by comparing their model-based measure of brand sentiment with performance measures obtained from external data sets (stock prices for both brands and an offline brand-tracking study for one brand). They find that their measure of sentiment serves as a leading indicator of the changes observed in these external data sources and outperforms other social media metrics currently used.
    Type of Medium: Online Resource
    ISSN: 0022-2437 , 1547-7193
    RVK:
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2014
    detail.hit.zdb_id: 2066604-4
    detail.hit.zdb_id: 218319-5
    SSG: 3,2
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  • 8
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2002
    In:  Marketing Science Vol. 21, No. 3 ( 2002-08), p. 347-364
    In: Marketing Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 21, No. 3 ( 2002-08), p. 347-364
    Abstract: Marketers have long struggled with developing forecasts for new products before their launch. We focus on one data source—advance purchase orders—that has been available to retailers for many years but has rarely been tied together with postlaunch sales data. We put forth a duration model that incorporates the basic concepts of new product diffusion, using a mixture of two distributions: one representing the behavior of innovators (i.e., those who place advance orders) and one representing the behavior of followers (i.e., those who wait for the mass market to emerge). The resulting mixed-Weibull model specification can accommodate a wide variety of possible sales patterns. This flexibility is what makes the model well-suited for an experiential product category (e.g., movies, music, etc.) in which we frequently observe very different sales diffusion patterns, ranging from a rapid exponential decline (which is most typical) to a gradual buildup characteristic of “sleeper” products. We incorporate product-specific covariates and use hierarchical Bayes methods to link the two customer segments together while accommodating heterogeneity across products. We find that this model fits a variety of sales patterns far better than do a pair of benchmark models. More importantly, we demonstrate the ability to forecast new album sales before the actual launch of the album, based only on the pattern of advance orders.
    Type of Medium: Online Resource
    ISSN: 0732-2399 , 1526-548X
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2002
    detail.hit.zdb_id: 2023536-7
    detail.hit.zdb_id: 883054-X
    SSG: 3,2
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  • 9
    Online Resource
    Online Resource
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2013
    In:  Marketing Science Vol. 32, No. 5 ( 2013-09), p. 753-767
    In: Marketing Science, Institute for Operations Research and the Management Sciences (INFORMS), Vol. 32, No. 5 ( 2013-09), p. 753-767
    Abstract: Online advertising campaigns often consist of multiple ads, each with different creative content. We consider how various creatives in a campaign differentially affect behavior given the targeted individual's ad impression history, as characterized by the timing and mix of previously seen ad creatives. Specifically, we examine the impact that each ad impression has on visiting and conversion behavior at the advertised brand's website. We accommodate both observed and unobserved individual heterogeneity and take into account correlations among the rates of ad impressions, website visits, and conversions. We also allow for the accumulation and decay of advertising effects, as well as ad wearout and restoration effects. Our results highlight the importance of accommodating both the existence of multiple ad creatives in an ad campaign and the impact of an individual's ad impression history. Simulation results suggest that online advertisers can increase the number of website visits and conversions by varying the creative content shown to an individual according to that person's history of previous ad impressions. For our data, we show a 12.7% increase in the expected number of visits and a 13.8% increase in the expected number of conversions.
    Type of Medium: Online Resource
    ISSN: 0732-2399 , 1526-548X
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2013
    detail.hit.zdb_id: 2023536-7
    detail.hit.zdb_id: 883054-X
    SSG: 3,2
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  • 10
    Online Resource
    Online Resource
    SAGE Publications ; 2018
    In:  Journal of Interactive Marketing Vol. 42 ( 2018-05), p. A1-A2
    In: Journal of Interactive Marketing, SAGE Publications, Vol. 42 ( 2018-05), p. A1-A2
    Type of Medium: Online Resource
    ISSN: 1094-9968
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
    detail.hit.zdb_id: 1501741-2
    SSG: 3,2
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