Crowdsourcing

About: Crowdsourcing is a research topic. Over the lifetime, 12889 publications have been published within this topic receiving 230638 citations.

Crowdsourcing: a comprehensive literature review

Abstract: – The purpose of this paper is to explore the development of crowdsourcing literature. , – This study is a comprehensive review of 346 articles on crowdsourcing. Both statistical and contents analyses were conducted in this paper. , – ISI listed journal articles, non-ISI listed journal articles and conference articles have had nearly the same contribution in crowdsourcing literature. Articles published in non-ISI listed journals have had an essential role in the initial theory development related to crowdsourcing. Scholars from the USA have authored approximately the same number of articles as scholars from all the European countries combined. Scholars from developing countries have been more relatively active in authoring conference articles than journal articles. Only very recently, top-tier journals have engaged in publishing on crowdsourcing. Crowdsourcing has proven to be beneficial in many tasks, but the extant literature does not give much help to practitioners in capturing value from crowdsourcing. Despite understanding that the motivations of crowds are crucial when planning crowdsourcing activities, the various motivations in different contexts have not been explored sufficiently. A major concern has been the quality and accuracy of information that has been gathered through crowdsourcing. Crowdsourcing bears a lot of unused potential. For example, it can increase employment opportunities to low-income people in developing countries. On the other hand, more should be known of fair ways to organize crowdsourcing so that solution seekers do not get a chance to exploit individuals committing to provide solutions. , – The literature included in the study is extensive, but an all-inclusive search for articles was limited to only nine selected publishers. However, in addition to the articles retrieved from the nine selected publishers, 52 highly cited articles were also included from other publishers. , – Crowdsourcing has much unused potential, and the use of crowdsourcing is increasing rapidly. The study provides a thematic review of various applications of crowdsourcing. , – The study is the first of its kind to explore the development of crowdsourcing literature, discussing the loci and foci of extant articles and listing applications of crowdsourcing. Successful applications of crowdsourcing include idea generation, microtasking, citizen science, public participation, wikies, open source software and citizen journalism.

Mitigating Herding in Hierarchical Crowdsourcing Networks.

Abstract: Hierarchical crowdsourcing networks (HCNs) provide a useful mechanism for social mobilization. However, spontaneous evolution of the complex resource allocation dynamics can lead to undesirable herding behaviours in which a small group of reputable workers are overloaded while leaving other workers idle. Existing herding control mechanisms designed for typical crowdsourcing systems are not effective in HCNs. In order to bridge this gap, we investigate the herding dynamics in HCNs and propose a Lyapunov optimization based decision support approach - the Reputation-aware Task Sub-delegation approach with dynamic worker effort Pricing (RTS-P) - with objective functions aiming to achieve superlinear time-averaged collective productivity in an HCN. By considering the workers’ current reputation, workload, eagerness to work, and trust relationships, RTS-P provides a systematic approach to mitigate herding by helping workers make joint decisions on task sub-delegation, task acceptance, and effort pricing in a distributed manner. It is an individual-level decision support approach which results in the emergence of productive and robust collective patterns in HCNs. High resolution simulations demonstrate that RTS-P mitigates herding more effectively than state-of-the-art approaches.

Deep Questions without Deep Understanding

Abstract: We develop an approach for generating deep (i.e, high-level) comprehension questions from novel text that bypasses the myriad challenges of creating a full semantic representation. We do this by decomposing the task into an ontologycrowd-relevance workflow, consisting of first representing the original text in a low-dimensional ontology, then crowdsourcing candidate question templates aligned with that space, and finally ranking potentially relevant templates for a novel region of text. If ontological labels are not available, we infer them from the text. We demonstrate the effectiveness of this method on a corpus of articles from Wikipedia alongside human judgments, and find that we can generate relevant deep questions with a precision of over 85% while maintaining a recall of 70%.

Avoiding the South Side and the Suburbs: The Geography of Mobile Crowdsourcing Markets

Abstract: Mobile crowdsourcing markets (e.g., Gigwalk and TaskRabbit) offer crowdworkers tasks situated in the physical world (e.g., checking street signs, running household errands). The geographic nature of these tasks distinguishes these markets from online crowdsourcing markets and raises new, fundamental questions. We carried out a controlled study in the Chicago metropolitan area aimed at addressing two key questions: (1) What geographic factors influence whether a crowdworker will be willing to do a task? (2) What geographic factors influence how much compensation a crowdworker will demand in order to do a task? Quantitative modeling shows that travel distance to the location of the task and the socioeconomic status (SES) of the task area are important factors. Qualitative analysis enriches our modeling, with workers mentioning safety and difficulties getting to a location as key considerations. Our results suggest that low-SES areas are currently less able to take advantage of the benefits of mobile crowdsourcing markets. We discuss the implications of our study for these markets, as well as for "sharing economy" phenomena like UberX, which have many properties in common with mobile crowdsourcing markets.

Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review

Abstract: The purpose of this paper is twofold: first, to review and classify scientific publications dealing with those innovative solutions aimed at increasing the efficiency of last-mile delivery in business to consumer (B2C) e-commerce; and, second, to outline directions for future research in this field.,The review is based on 75 papers published between 2001 and 2019 in international peer-reviewed journals or proceedings of conferences, retrieved from bibliographic databases and science search engines.,Due to its importance in affecting the overall logistics costs and, as a consequence, the economic sustainability of a B2C e-commerce initiative, last-mile delivery process deserves particular attention in order to be optimised. The review highlights that, among the main factors affecting its cost, there are the probability to have failed deliveries, the customer density in the delivery areas and the degree of automation of the process. Innovative and viable last-mile delivery solutions – which may impact the mentioned drivers – include parcel lockers, crowdsourcing logistics, mapping the consumer presence at home and dynamic pricing policies. Eventually, some gaps and areas for further research activities have been identified (e.g. mapping customer behaviour, crowdsourcing logistics).,This review offers interesting insights to both academics and practitioners. On the academic side, it analyses and classifies relevant literature about innovative and efficiency-oriented last-mile delivery solutions, proposing directions for future research efforts. On the managerial side, it presents a holistic framework of the main factors affecting last-mile delivery cost and of viable innovative solutions that may be implemented to increase efficiency.