Crowd vs. crowd

Park, Cheong Ha; Son, KyoungHee; Lee, Joon Hyub; Bae, Seok-Hyung

doi:10.1145/2441776.2441920

Cited by 25 publications

(5 citation statements)

References 24 publications

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“…Their study showed that their system resulted in better performance over pre-authored tutorials by improving learner performance, increasing motivation, and stimulating knowledge transfer. Park et al [34] presented a novel crowdsourcing method, where several design teams made up of designers and crowd compete with each other. They observed that the elements of competition and collaboration helped to sustain the crowd's motivation to participate, and that quality design outcomes were produced with a higher level of satisfaction for the stakeholders.…”

Section: Social Incentivesmentioning

confidence: 99%

Integrating Gamification and Social Interaction into an AR-Based Gamified Point System

Liu

Tanaka

2020

MTI

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A loyalty program is an important link between consumers and merchants in daily consumption. While new technologies (e.g. gamification, social networks, augmented reality, and so on) make it possible to strengthen this bond, their potential has not yet been fully exploited. In our research, we explore a novel approach to integrate gamification and social interaction into a loyalty program based on augmented reality (AR). We propose an AR-based gamified point system which supports users in obtaining pet-based dynamic feedback on mobile devices and provides a multi-user environment for social interaction. Compared to traditional point systems, pet-based designs help to establish an emotional connection between users and the system. The multi-user environment is designed to increase the user’s motivation through the positive effects of social interactions. Our system provides interpersonal communication channels between users, including competitive and non-competitive interactions. We performed an evaluation consisting of two experiments to examine the effects of game elements (mission and feedback) and social cues (competitive and non-competitive interactions). In the first experiment, we analyze the change in online shopping behavior before and after adding game elements. The results show that gamification can increase user participation in online shopping. In the second experiment, we study the effects of social cues. The results show that social cues can motivate users to participate in the use of a gamified point system.

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Section: Social Incentivesmentioning

confidence: 99%

Integrating Gamification and Social Interaction into an AR-Based Gamified Point System

Liu

Tanaka

2020

MTI

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“…Crowd vs. Crowd (CvC) [31] used competitions between crowd teams, led by a designer, to crowdsource the entire design process. One limitation of these systems was that they focused on asynchronous interactions and highly structured, iterative, tasks.…”

Section: Crowdsourcing In the Design Processmentioning

confidence: 99%

Crowdboard

Andolina

Schneider

Chan

et al. 2017

Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition

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Online crowds can help infuse creativity into the design process, but traditional strategies for leveraging them, such as large-scale ideation platforms, require time and organizational effort in order to obtain results. We propose a new method for crowd-based ideation that simplifies the process by having smaller crowds join in-person ideators during synchronous creative sessions. Our system Crowdboard allows online crowds to provide real-time creative input during early-stage design activities, such as brainstorming or concept mapping. The system enables in-person ideators to develop ideas on a physical or digital whiteboard which is augmented with real-time creative input from online participants who see and hear a live broadcast of the meeting. We validate Crowdboard via two user studies in which dyads of in-person ideators brainstormed with the help of crowd ideators. Our studies suggest that Crowdboard can effectively enhance ongoing brainstorming sessions, but also revealed key challenges for how to better facilitate interactions among in-person and crowd ideators.

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“…Readers are referred to Park et al. (2013) and Schmidt (2017) for a review of recent development of various crowdsourcing implementations in the corresponding industries.…”

Section: Introductionmentioning

confidence: 99%

“…These applications share a similar business principle where a firm or an individual fulfills his/her needs (for either goods or services) by tapping into a large and diverse crowd of potential contributors. Readers are referred to Park et al (2013) and Schmidt (2017) for a review of recent development of various crowdsourcing implementations in the corresponding industries.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Sequential Allocations for Creative Crowdsourcing

Tian

Shi

2022

Production and Operations Management

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C reative crowdsourcing is an innovative online business model in which a platform marshals independent professionals (e.g., designers) to conduct creative work projects. Typically, clients submit project requests stochastically to a platform which possesses a pool of registered designers. For each submitted project, designers decide whether to participate and attempt to submit a design, and the client either chooses a winner among all submissions, or rejects them all, based on subjective criteria. In general, platforms cannot control individual designers directly because of the nature of the freelance market, incurring possible mismatches between designers and arriving projects. To tackle the problem, we present a dynamic control policy applied to the maximum number of participants for each arrived project. Our study reveals that the optimal policy follows an inverted-U-shaped function of the project value, highlighting the importance of applying a stronger restriction on the number of participants for some sufficiently high-valued projects. In addition, the optimal policy we have developed allows the platform to gain higher rewards judiciously even when the market is more volatile. Furthermore, extensive numerical studies have been conducted to glean managerial insights. Specifically, the optimal policy becomes more beneficial even when more designers are available, which is counter-intuitive to the common-sense notion that control should be more valuable when designers are scarcer; and the optimal policy is further shown to be robust when the objective is changed from maximizing the total reward to maximizing the total number of successful projects.

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Crowd vs. crowd

Cited by 25 publications

References 24 publications

Integrating Gamification and Social Interaction into an AR-Based Gamified Point System

Integrating Gamification and Social Interaction into an AR-Based Gamified Point System

Crowdboard

Stochastic Sequential Allocations for Creative Crowdsourcing

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