Customized Bundling and Consumption Variety of Digital Information Goods

Bockstedt, Jesse; Goh, Kim Huat

doi:10.2139/ssrn.2470799

Cited by 6 publications

(7 citation statements)

References 40 publications

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“…After eliminating less frequent items we were finally left with 29 categories. These items were then sorted into categories using card-sorting procedure Author(s) Success factors Methodology Bundling strategy Prasad et al (2015) Price discrimination Modeling Mix bundling de Miranda et al (2006) Pricing Modeling Service bundling Koukova et al (2008) Complementarity, product type Experiment Product bundling, Agarwal and Chatterjee (2003) Complexity, uniqueness, similarity Survey Product bundling Avenali et al (2013) Price, quality investment Modeling Product bundling Lee and Kwon (2011) Complementarity Modeling Service bundling Sett (2014) Complementarity, reference framing, price framing Experiment Product bundling, price bundling Bouwman et al (2007) Price, bundle size Survey Service bundling Sheng et al (2007) Price, perceived quality, complementarity Experiment Product bundling de Pechpeyrou (2013) Perceived unit cost, product attractiveness Experiment Virtual bundling Chung et al (2013) Brand, consumer surplus, social welfare Modeling Product bundling Bockstedt and Goh (2014) (Moore and Benbasat, 1991) to verify the construct, face, and discriminant validity (Khalifa and Liu, 2002). Each item was printed on a card and these cards were then shuffled before they were handed over to the judges.…”

Section: Unique Characteristics Of App-bundlesmentioning

confidence: 99%

Evaluating app bundling strategy for selling mobile apps: an ambivalent perspective

Wan

Zhao

et al. 2017

ITP

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Purpose Mobile appstores have fast sprung up during the last few years. The large number of apps in these appstores results in increased search effort for the customer as well as fierce competition leading to poorer revenues for both appstores as well as developers. Therefore, appstores allow developers to resort to bundling apps so as to increase the revenues and improve customer loyalty. Since an app-bundle is a mix of two or more apps, it may induce both positive and negative emotions simultaneously in the consumer. The purpose of this paper is to examine the effectiveness of app-bundling strategy from consumers’ perspective, and help developers design app-bundles. Design/methodology/approach Based on ambivalence theories, this research investigate different antecedents and influence of positive attitude and negative attitude on purchase behavior, and derives seven key app-bundles attributes through an exploratory study. The data were collected from 930 consumers of app-bundles in China and analyzed using SEM approach. Findings The findings indicate that positive attitude and negative attitude are two separate concepts and the identified seven app-bundling attributes have distinct effect on shaping consumers’ positive and negative attitude. Originality/value This study makes three key contributions to theory and practice. First, this study identifies the specific attributes of app-bundles using exploratory study. Second, this study addresses the challenges involved in examining bundles using ambivalence theory. In doing so, it characterizes attitude as positive and negative and treats them as separate constructs. Third, as called forth by previous studies, this study establishes the co-existence of positive attitude and negative attitude.

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Section: Unique Characteristics Of App-bundlesmentioning

confidence: 99%

Evaluating app bundling strategy for selling mobile apps: an ambivalent perspective

Wan

Zhao

et al. 2017

ITP

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“…As an intuitive choice, most of the respondents in this survey preferred statin B, which has a ‘milder’ risk‐benefit contrast than statin A. In cognitive sciences, people's aversion to extreme choices has been observed in many fields, and this pattern of preference was highly expected . However, MCDA seems to suffer from some technical obstacles concerning eliciting and expressing such preferences.…”

Section: Discussionmentioning

confidence: 99%

Discrepancies between multicriteria decision analysis-based ranking and intuitive ranking for pharmaceutical benefit-risk profiles in a hypothetical setting

Hoshikawa

Ono

2016

J Clin Pharm Ther

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Observed discrepancies between the rankings seemed to be primarily attributed to the structural characteristics of MCDA, which assumes that evaluation on each benefit and risk component should have monotonic impact on final scores. It would be difficult for MCDA to reflect commonly observed non-monotonic preferences for risk and benefit profiles. Possible drawbacks of MCDA should be further investigated prior to the real-world application of its benefit-risk assessment.

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“…Randall et al (2007) found that users who have high expertize will feel that parameter-based systems are comfortable and more suitable for them, whereas needs-based systems are more apt for novices. Bockstedt and Goh (2014) found that, compared with traditional sales, in the context of bundling customized sales, consumers buy fewer types of goods and have a stronger tendency to buy popular products. Dellaert and Dabholkar (2009) found that supporting services such as visualization, salesperson interaction and post-purchase product adaptation in the customization system will increase consumers’ perception of online mass customization product results, control and enjoyment and reduce the perception of complexity.…”

Section: Literature Reviewmentioning

confidence: 99%

“…With the popularization of internet technologies and the rapid development of e-commerce, online customization (OC), as an important means for vendors to improve their competitiveness, has been applied to broad areas (Bockstedt and Goh, 2014; Dellaert and Dabholkar, 2009; Pallant et al , 2020b; Wang and Benbasat, 2009; Westphal et al , 1997). Many vendors (e.g.…”

Section: Introductionmentioning

confidence: 99%

Overt or covert? Effect of different digital nudging on consumers’ customization choices

Chen

Wang

2020

NBRI

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Purpose This study aims to explore the effect of two digital nudging technologies that is overt digital nudging (ODN) and covert digital nudging (CDN), on consumers’ choices of nudged options in the context of online customization systems (OCS). Design/methodology/approach This paper designed a 2 (ODN: yes/no) by 2 (CDN: yes/no) full factor between-subject lab experiment in the context of online travel package customization. This paper collected and analyzed the number of nudged options (the intermediate options) of choices among consumers in these four scenarios. Findings ODN and CDN have positive effects on consumers’ choices of nudged options in online customization (OC). In addition, mixed nudge (a combination of ODN and CDN) has a more significant effect on consumers’ choices of nudged options in OC than using CDN only. Research limitations/implications This study focused only on the choice behavior of consumers in the customization context and did not analyze their attitude change. The present study used vendor recommendation as the proxy variable of ODN and default option as the proxy variable of CDN. A future study could explore other instances of ODN and CDN. Practical implications This study explores the effects of digital nudging technologies in the context of OCS. The study provides clear guidance for customization vendors on whether to use digital nudging tools and their combinations, and which tools should be preferred. Social implications Vendors can adopt digital nudging technology to persuade consumers to choose nudged options. This nudging effect can make consumers’ choices predictable and less uncertain, thus adding profits for vendors. Originality/value First, the study focuses on the impact of digital nudging on consumers’ choices and enriches the understanding of the impact of customization system design on consumers’ choices. Second, this paper put forward a new classification method for digital nudging and proposed, respectively, the effect mechanisms on consumers’ customization choices. Third, this study explores the effect of combining multiple nudging tools in OC context on consumers’ choices, which deepens the understanding of the interactive effects of different types of nudging tools.

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Customized Bundling and Consumption Variety of Digital Information Goods

Cited by 6 publications

References 40 publications

Evaluating app bundling strategy for selling mobile apps: an ambivalent perspective

Evaluating app bundling strategy for selling mobile apps: an ambivalent perspective

Discrepancies between multicriteria decision analysis-based ranking and intuitive ranking for pharmaceutical benefit-risk profiles in a hypothetical setting

Overt or covert? Effect of different digital nudging on consumers’ customization choices

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