Crowd Feedback Research Articles

Crowdsourcing Properties and Mechanisms of Mega Hackathons: The Case of Junction

Hackathons are time-bounded crowdsourcing events, which have recently prospered in many technology and science domains across the globe. We study Europe’s largest hackathon, Junction, to better understand the distinct crowdsourcing properties and mechanisms of this type of hackathon as a form of tournament-based crowdsourcing. Moreover, we determined how they add value to attending companies and participants. In this regard, six qualitative and quantitative datasets from participants, companies, and the organizer were collected and analyzed. Our findings revealed five distinct crowdsourcing properties and mechanisms of mega hackathons, including intricate crowd selection, strong crowd vibe, instant crowd feedback, versatile crowd potential, and pervasive information technology. Based on our findings, we argue that these properties and mechanisms increase the possibility of finding innovative solutions to companies’ problems in Junction-like mega hackathons. This article concludes with managerial implications for companies to consciously plan and prepare while knowing what to expect during the hackathon.

Aligning Crowdworker Perspectives and Feedback Outcomes in Crowd-Feedback System Design

Leveraging crowdsourcing in software development has received growing attention in research and practice. Crowd feedback offers a scalable and flexible way to evaluate software design solutions and the potential of crowd-feedback systems has been demonstrated in different contexts by existing research studies. However, previous research lacks a deep understanding of the effects of individual design features of crowd-feedback systems on feedback quality and quantity. Additionally, existing studies primarily focused on understanding the requirements of feedback requesters but have not fully explored the qualitative perspectives of crowd-based feedback providers. In this paper, we address these research gaps with two research studies. In study 1, we conducted a feature analysis (N=10) and concluded that from a user perspective, a crowd-feedback system should have five core features (scenario, speech-to-text, markers, categories, and star rating). In the second study, we analyzed the effects of the design features on crowdworkers' perceptions and feedback outcomes (N=210). We learned that offering feedback providers scenarios as the context of use is perceived as most important. Regarding the resulting feedback quality, we discovered that more features are not always better as overwhelming feedback providers might decrease feedback quality. Offering feedback providers categories as inspiration can increase the feedback quantity. With our work, we contribute to research on crowd-feedback systems by aligning crowdworker perspectives and feedback outcomes and thereby making the software evaluation not only more scalable but also more human-centered.

CrowdFolio

Freelancers increasingly earn their livelihood through online marketplaces. To attract new clients, freelancers continuously curate their online portfolios to convey their unique skills and style. However, many lack access to rapid, regular, and inexpensive feedback needed to improve their portfolios. Existing crowd feedback systems, which collect feedback on individual creative projects (i.e., decomposed approach), could fill this need, but it is unclear how they might support feedback on multiple projects (i.e., holistic approach). In a between-subjects study with 30 freelancers, we compared decomposed and holistic feedback collection approaches using CrowdFolio, a crowd feedback system for portfolios. The holistic approach helped freelancers discover new ways to describe their work, while the decomposed approach provided detailed insight about the visual attractiveness of projects. This study contributes evidence that portfolio feedback systems, regardless of collection approach, can positively support professional development by impacting how freelancers portray themselves online and reflect on their identity.

Modeling user concerns in Sharing Economy: the case of food delivery apps.

Sharing Economy apps, such as Uber, Airbnb, and TaskRabbit, have generated a substantial consumer interest over the past decade. The unique form of peer-to-peer business exchange these apps have enabled has been linked to significant levels of economic growth, helping people in resource-constrained communities to build social capital and move up the economic ladder. However, due to the multidimensional nature of their operational environments, and the lack of effective methods for capturing and describing their end-users’ concerns, Sharing Economy apps often struggle to survive. To address these challenges, in this paper, we examine crowd feedback in ecosystems of Sharing Economy apps. Specifically, we present a case study targeting the ecosystem of food delivery apps. Using qualitative analysis methods, we synthesize important user concerns present in the Twitter feeds and app store reviews of these apps. We further propose and intrinsically evaluate an automated procedure for generating a succinct model of these concerns. Our work provides a first step toward building a full understanding of user needs in ecosystems of Sharing Economy apps. Our objective is to provide Sharing Economy app developers with systematic guidelines to help them maximize their market fitness and mitigate their end-users’ concerns and optimize their experience.

The Development of Learning Mobile Application of Latin-to-Balinese Script Transliteration

Balinese script writing allegedly towards extinction. general objective of this research is to preserve this Balinese culture aspect through a technology approach. specific objective is to develop learning mobile application of Latin-To-Balinese script transliteration, as one of the innovative technology products of the Universitas Pendidikan Ganesha – Bali, and to analyze crowd feedback of that application to know the user acceptance and to obtain feedback for future improvement. This android-based application can be used as a learning media at mandatory local content subject Balinese Language in elementary and secondary schools in Province Bali since so far, it could handle the transliteration complex behaviors based on document The Balinese Alphabet with about 98% accuracy level (148 right of 151 test case). development of this application was based on Model-View-Controller design pattern and use dictionary data structure to hold special words. Crowd feedback data was obtained through Google Play Console in five months since the application release. There are more than 32 thousand installations and 152 ratings (63 ratings with reviews). Average rating score of 4.2 (from the maximum best score of 5) and positive general comments (57% from total review) reflects relatively good of the user acceptance to the application. Further improvement priority of the application based on top three feedback category, i.e. addition of: 1) copy-paste-share feature (18% of reviews total); 2) compatibility to the old version of android (5% of reviews total); and 3) character “ě” insertion feature for generating sign pepet of Aksara Bali (3% of reviews total).

Identifying New Product Ideas: Waiting for the Wisdom of the Crowd or Screening Ideas in Real Time

Crowdsourcing ideas from consumers can enrich idea input in new product development. After a decade of initiatives (e.g., Starbucks’ MyStarbucksIdea, Dell's IdeaStorm), the implications of crowdsourcing for idea generation are well understood, but challenges remain in dealing with the large volume of rapidly generated ideas produced in crowdsourcing communities. This study proposes a model that can assist managers in efficiently processing crowdsourced ideas by identifying the aspects of ideas that are most predictive of future implementation and identifies three sources of information available for an idea: its content, the contributor proposing it, and the crowd's feedback on the idea (the “3Cs”). These information sources differ in their time of availability (content/contributor information is available immediately; crowd feedback accumulates over time) and in the extent to which they comprise structured or unstructured data. This study draws from prior research to operationalize variables corresponding to the 3Cs and develops a new measure to quantify an idea's distinctiveness. Applying automated information retrieval methods (latent semantic indexing) and testing several linear methods (linear discriminant analysis, regularized logistic regression) and nonlinear machine‐learning algorithms (stochastic adaptive boosting, random forests), this article identifies the variables that are most useful towards predicting idea implementation in a crowdsourcing community for an IT product (Mendeley). Our results indicate that consideration of content and contributor information improves ranking performance between 22.6 and 26.0% over random idea selection, and that adding crowd‐related information further improves performance by up to 48.1%. Crowd feedback is the best predictor of idea implementation, followed by idea content and distinctiveness, and the contributor's past idea‐generation experience. Firms are advised to implement two idea selection support systems: one to rank new ideas in real time based on content and contributor experience, and another that integrates the crowd's idea evaluation after it has had sufficient time to provide feedback.

Optimization strategy of mobile data transmission based on optimal crowd feedback

In order to eliminate the factors that restrict the performance of wireless network data transmission, we proposed the optimal control mechanism of wireless network data transmission. The proposed mechanism solves the intelligence problem of the feedback loop, the mobility of relay nodes, and the feedback of the receiving end. On the one hand, to eliminate the external interference factors, we established an optimal feedback loop control system between the sender and the receiver. On the other hand, in the time linear region, the crowd feedback module is added to the optimal feedback closed-loop control system based on the linear weight. On the basis of the above schemes, we proposed an adaptive optimization model of mobile data transmission. The experiments compared the proposed optimal crowd feedback optimal control scheme with the optimization strategy of the data transmission. From the results of system efficiency and system throughput performance, the proposed optimal crowd feedback optimal control scheme has an obvious advantage.

Information problems, crowdfunding and debt decision for business start-upsLes problémes informationnels, financement participatif et décision d'endettement pour la création d'entreprise

The recent rise of crowdfunding begs the question of what unique value the crowd brings to entrepreneurs. This paper proposes an answer to this question by focusing on the informational role of crowdfunding in resolving financial constraints. I argue that a distinct role of crowdfunding is the provision of early feedback to entrepreneurs that resolve the moral hazard problem and lead to more bank debt funding. As traditional funding (bank debt), crowdfunding may be directed under specific characteristics of business start-up as information problems (i.e. information opacity and asymmetry). The study aims at comparing the decisive weight of information opacity and moral hazard problem on traditional funding (as bank debts) and crowdfunding of business start-ups. The study uses the panel study of entrepreneurial dynamics and a sample of 1014 business start-ups. The results show that the crowd's feedback affects entrepreneurs’ access to traditional funding. The results confirm that crowdfunding as a screening tool improves the information environment of the entrepreneur and limits the moral hazard problem. Crowdfunding is not just promoted to raise funds, but also for collecting information, and it is a complement rather than a substitute traditional entrepreneurial bank funding.