A Penny for Your Thoughts: Referral Reward Programs and Referral Likelihood

Ryu, Gangseog; Feick, Lawrence

doi:10.1509/jmkg.71.1.84

Cited by 225 publications

(260 citation statements)

References 28 publications

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“…Customers of strong brands usually do not need huge incentives to participate in loyalty programs. In contrast, customers have to be rewarded more heavily in the case of weaker brands because customers are less confident about recommending the brand and are therefore less motivated to perform such an action (Ryu and Feick, 2007).…”

Section: Antecedents Of Cebmentioning

confidence: 99%

Exploring customer engagement behavior: construct proposal and its antecedents

Romero¹,

Okazaki²

2015

Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users

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Customer engagement behavior (CEB) receives increasing attention from both academics and practitioners, as it represents one of the key customer profitability determinants. This study attempts to provide a holistic view of CEB by (1) proposing an instrument to measure CEB, and (2) its antecedents. Based on the existent literature, we conceptualize CEB as a formative construct consisting of word-of-mouth (WOM), loyalty program participation, customer interaction, and co-creation, which are determined by relationship quality, rewards, selfenhancement, learning, social integration, and company identification. In attempt to test these propositions, an online survey is conducted with 466 respondents. Our results provide empirical support for our proposed CEB construct, while corroborating five out of the six hypothesized antecedents. In closing, theoretical as well as managerial implications are discussed, while important limitations are recognized and future research directions are proposed.

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Section: Antecedents Of Cebmentioning

confidence: 99%

Exploring customer engagement behavior: construct proposal and its antecedents

Romero¹,

Okazaki²

2015

Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users

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“…Research shows that such programs can achieve up to 16% better results [29]. Referrals are often more personal than normal advertisements or SLAs and, therefore, show a high impact on user behavior as showed in [30]. Similar impact is possible with our approach because engaging options from coworkers are more trustworthy than SLAs from Cloud providers.…”

Section: Related Workmentioning

confidence: 66%

An architecture to stimulate behavioral development of academic cloud users

Kecskeméti

Ostermann

Prodan

2014

Sustainable Computing: Informatics and Systems

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Academic cloud infrastructures are constructed and maintained so they minimally constrain their users. Since they are free and do not limit usage patterns, academics developed such behavior that jeopardizes fair and flexible resource provisioning. For efficiency, related work either explicitly limits user access to resources, or introduce automatic rationing techniques. Surprisingly, the root cause (i.e., the user behavior) is disregarded by these approaches. This article compares academic cloud user behavior to its commercial equivalent. We deduce, that academics should behave like commercial cloud users to relieve resource provisioning. To encourage commercial like behavior, we propose an architectural extension to existing academic infrastructure clouds. First, every user's energy consumption and efficiency is monitored. Then, energy efficiency based leader boards are used to ignite competition between academics and reveal their worst practices. Leader boards are not sufficient to completely change user behavior. Thus, we introduce engaging options that encourage academics to delay resource requests and prefer resources more suitable for the infrastructure's internal provisioning. Finally, we evaluate our extensions via a simulation using real life academic resource request traces. We show a potential resource utilization reduction (by the factor of at most 2.6) while maintaining the unlimited nature of academic clouds.

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“…The goal is thus to build referral equity through referral rewards with minimum increases in marketing costs. Ryu and Feick (2007) show that referral rewards increase the likelihood that customers give positive referrals to potential customers, which should increase the number of positive referrals for the supplier firm. However, they also note that referral rewards are irrelevant when strong ties exist between referrers and potential customers (e.g., family members).…”

Section: Monetary Incentivesmentioning

confidence: 98%

“…As with all referrals, the referrer provides information about the supplier firm to the potential customer. However, if this referral causes the potential customer to purchase from the supplier firm, the supplier firm rewards the referrer, such that the referrer receives a benefit from the supplier firm (the reward), and from the potential customer (indirectly) (Ryu & Feick, 2007). Supplier firms are unlikely to offer monetary incentives to referrers in supplier-initiated referrals because the effectiveness of the referral depends on the referrer's reputation.…”

Section: Monetary Incentivesmentioning

confidence: 99%

“…However, they also note that referral rewards are irrelevant when strong ties exist between referrers and potential customers (e.g., family members). Because referrers tend to offer recommendations to potential customers with whom they have strong ties first, Ryu and Feick (2007) suggest increasing the referral reward as the number of referrals from a referrer increases.…”

Section: Monetary Incentivesmentioning

confidence: 99%

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Referral equity and referral management: the supplier firm's perspective

Hada¹,

Grewal²,

Lilien³

2010

Review of Marketing Research

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From the supplier firm's perspective, a referral is a recommendation from A (the referrer) to B (the potential customer) that B should, or should not, purchase from C (the supplier firm). Thus, as referrals are for a specific supplier firm, they should be viewed as part of the supplier firm's marketing and sales activities. We recognize three types of referralscustomer-to-potential customer referrals, horizontal referrals, and supplier-initiated referrals -that have critical roles in a potential customer's purchase decision. We develop the concept of referral equity to capture the net effect of all referrals for a supplier firm in the market. We argue that supplier firms should view referral equity as a resource that has financial value to the firm as it affects the firm's cash flows and profits. We offer strategies firms can use to manage referrals and build their referral equity and suggest a research agenda.

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A Penny for Your Thoughts: Referral Reward Programs and Referral Likelihood

Cited by 225 publications

References 28 publications

Exploring customer engagement behavior: construct proposal and its antecedents

Exploring customer engagement behavior: construct proposal and its antecedents

An architecture to stimulate behavioral development of academic cloud users

Referral equity and referral management: the supplier firm's perspective

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