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Crowd-Powered e-Services

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 17852

Special Issue Editors

Dr. Ioanna Lykourentzou

E-Mail Website
Guest Editor
Department of Information and Computing Sciences, Utrecht University, Domplein 29, 3512 JE Utrecht, Netherlands
Interests: Computer-supported cooperative work; Crowd computing; Online communities
Dr. Angeliki Antoniou

E-Mail Website
Guest Editor
Department of Informatics and Telecommunications, University of Peloponnese, Terma Karaiskaki, 22100 Tripolis, Greece
Interests: technologies and applications for cultural heritage; educational games (formal, non-formal and informal learning); augmented reality; user profiling; personalization; group adaptation; social networks; crowdsourcing
Special Issues, Collections and Topics in MDPI journals
Dr. Martín López-Nores

E-Mail Website
Guest Editor
atlanTTic Research Center, Department of Telematics Engineering, University of Vigo, 36310 Vigo, Spain
Interests: applied artificial intelligence; knowledge modeling; semantic reasoning; interactive storytelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Crowdsourcing is a model in which individuals or organizations obtain goods and services from a large, open and rapidly-evolving group of Internet users. The idea of dividing work between participants to achieve a cumulative result has been applied successfully in many areas, from biology and linguistics to engineering and cultural heritage. As a particular branch of crowdsourcing, crowd computing (also known as “human computation” or “human-centered AI”) systematizes the intertwining of human intelligence with artificial intelligence, aiming to solve tasks that are hard for individuals or computers to do alone. The key principles include (i) automation: machines do non-creative and repetitive work, providing a cascade of knowledge for humans to evaluate; (ii) micro-tasking: work is broken into small tasks that are easier to complete by humans chosen specifically on the grounds of their expertise; and (iii) mixed crowd: a greater volume of work, and of greater value, can be completed when specialists and open communities work together.

This Special Issue seeks to become a forum to publish broad, interdisciplinary research about human-in-the-loop intelligent e-services, human-AI interaction, and techniques for augmenting the abilities of individuals and communities to perform whichever tasks. We thereby solicit papers presenting theoretical contributions or practical uses of crowdsourcing and crowd computing models in any domains of application. Topics of interest include, but are not limited to, the following:

  • Crowdsourcing/crowd computing case studies:
    • digital humanities,
    • economy,
    • education,
    • health,
    • journalism,
    • software engineering,
    • tourism,
    • urban data collection,
    • …
  • Crowdsourcing/crowd computing theory and techniques:
    • algorithm design,
    • collective knowledge,
    • human-AI interaction,
    • incentives to collaboration,
    • intellectual property,
    • macro- and micro-tasking,
    • mixed crowd,
    • psychological and emotional aspects of crowd involvement,
    • quality control,
    • task assignment,
    • …
  • Uses of crowdsourcing/crowd computing:
    • games,
    • knowledge bases,
    • fact verification,
    • information retrieval,
    • machine learning,
    • optimization,
    • virtual labor markets,
    • …

Dr. Ioanna Lykourentzou
Dr. Angeliki Antoniou
Prof. Dr. Martín López-Nores
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • crowdsourcing
  • crowd computing
  • human computation
  • human-centered AI
  • IT-mediated crowds

Published Papers (5 papers)

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Research

23 pages, 3039 KiB  
Article
The Effectiveness of Centralized Payment Network Advertisements on Digital Branding during the COVID-19 Crisis
by Damianos P. Sakas, Ioannis Dimitrios G. Kamperos, Dimitrios P. Reklitis, Nikolaos T. Giannakopoulos, Dimitrios K. Nasiopoulos, Marina C. Terzi and Nikos Kanellos
Sustainability 2022, 14(6), 3616; https://0-doi-org.brum.beds.ac.uk/10.3390/su14063616 - 19 Mar 2022
Cited by 36 | Viewed by 3217
Abstract
Crises are always challenging for banking systems. In the case of COVID-19, centralized payment networks and FinTech companies’ websites have been affected by user behavior globally. As a result, there is ample opportunity for marketing managers and professionals to focus on big data [...] Read more.
Crises are always challenging for banking systems. In the case of COVID-19, centralized payment networks and FinTech companies’ websites have been affected by user behavior globally. As a result, there is ample opportunity for marketing managers and professionals to focus on big data from FinTech websites. This can contribute to a better understanding of the variables impacting their brand name and how to manage risk during crisis periods. This research is divided into three stages. The first stage presents the web analytics and the data retrieved from the FinTech platforms. The second stage illustrates the statistical analysis and the fuzzy cognitive mapping (FCM) performed. In the final stage, an agent-based model is outlined in order to simulate and forecast a company’s brand name visibility and user behavior. The results of this study suggest that, during crises, centralized payment networks (CPNs) and FinTech companies with high organic traffic tend to convert new visitors to actual “customers”. Full article
(This article belongs to the Special Issue Crowd-Powered e-Services)
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13 pages, 3265 KiB  
Article
A Framework for Crowd Management during COVID-19 with Artificial Intelligence
by Mishaal M. Almutairi, Mohammad Yamin, George Halikias and Adnan Ahmed Abi Sen
Sustainability 2022, 14(1), 303; https://0-doi-org.brum.beds.ac.uk/10.3390/su14010303 - 28 Dec 2021
Cited by 23 | Viewed by 3313
Abstract
COVID-19 requires crowded events to enforce restrictions, aimed to contain the spread of the virus. However, we have seen numerous events not observing these restrictions, thus becoming super spreader events. In order to contain the spread of a human to human communicable disease, [...] Read more.
COVID-19 requires crowded events to enforce restrictions, aimed to contain the spread of the virus. However, we have seen numerous events not observing these restrictions, thus becoming super spreader events. In order to contain the spread of a human to human communicable disease, a number of restrictions, including wearing face masks, maintaining social distancing, and adhering to regular cleaning and sanitization, are critical. These restrictions are absolutely essential for crowded events. Some crowded events can take place spontaneously, such as a political rally or a protest march or a funeral procession. Controlling spontaneous crowded events, like a protest march, political rally, celebration after a sporting event, or concert, can be quite difficult, especially during a crisis like the COVID-19 pandemic. In this article, we review some well-known crowded events that have taken place during the ongoing pandemic. Guided by our review, we provide a framework using machine learning to effectively organize crowded events during the ongoing and for future crises. We also provide details of metrics for the validation of some components in the proposed framework, and an extensive algorithm. Finally, we offer explanations of its various functions of the algorithm. The proposed framework can also be adapted in other crises. Full article
(This article belongs to the Special Issue Crowd-Powered e-Services)
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26 pages, 4643 KiB  
Article
Estimating Risk Perception Effects on Courier Companies’ Online Customer Behavior during a Crisis, Using Crowdsourced Data
by Damianos P. Sakas, Ioannis Dimitrios G. Kamperos and Panagiotis Reklitis
Sustainability 2021, 13(22), 12725; https://0-doi-org.brum.beds.ac.uk/10.3390/su132212725 - 17 Nov 2021
Cited by 15 | Viewed by 2946
Abstract
The ongoing COVID-19 pandemic has proven to be a real challenge for courier companies on a global scale and has affected customer behavior worldwide. This paper attempts to propound a new methodology in order to predict the effect of courier companies’ e-commerce on [...] Read more.
The ongoing COVID-19 pandemic has proven to be a real challenge for courier companies on a global scale and has affected customer behavior worldwide. This paper attempts to propound a new methodology in order to predict the effect of courier companies’ e-commerce on customers’ risk perception regarding their online behavior after the outbreak, and the final effect of their behavior on the global ranking of the company’s website, utilizing passive crowdsourcing data from five world-leading courier companies as representative examples of their respective business sectors. The results will allow supply chain risk management (SCRM) managers to make effective strategic decisions regarding the efficient allocation of resources to mitigate the corporate risk to their organization during a novel crisis. In our paper, we monitored five key performance indicators (KPIs) over a 24-month period (March 2019–February 2021) as the first of a suggested three-level analysis process using statistical analysis and fuzzy cognitive mapping techniques. We propose that courier service companies should manage the risk of a potential novel crisis by improving the reputation and brand name of the company, since customers tend to trust an established brand. Full article
(This article belongs to the Special Issue Crowd-Powered e-Services)
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22 pages, 5626 KiB  
Article
The Impact of Organic Traffic of Crowdsourcing Platforms on Airlines’ Website Traffic and User Engagement
by Damianos P. Sakas and Dimitrios P. Reklitis
Sustainability 2021, 13(16), 8850; https://0-doi-org.brum.beds.ac.uk/10.3390/su13168850 - 07 Aug 2021
Cited by 27 | Viewed by 3732
Abstract
With airline companies increasingly relying on crowdsourcing websites to deploy their digital marketing strategies, marketeers and strategists seek to acquire an understanding of the factors affecting airlines’ organic traffic and user engagement. Such an understanding is acquired through the consideration of variables that [...] Read more.
With airline companies increasingly relying on crowdsourcing websites to deploy their digital marketing strategies, marketeers and strategists seek to acquire an understanding of the factors affecting airlines’ organic traffic and user engagement. Such an understanding is acquired through the consideration of variables that influence a company’s organic traffic and user engagement and their correlation to each other. A three-stage data-driven analysis is used to examine the correlation between the foregoing variables and to consider strategies that can be implemented to optimize organic traffic and user engagement. The first section gathers data from five airline companies’ websites and five crowdsourcing websites over an interval of 180 days. The second stage creates an exploratory diagnostic model, through Fuzzy Cognitive Mapping, to visually illustrate the cause-and-effect correlations between the examined metrics. Finally, a predictive micro-level agent-based model simulates optimization strategies that can be used to improve organic traffic and user engagement. The results of this study, reveal that crowdsourcing organic traffic increases airline websites’ user engagement through paid campaigns, while a limited correlation was found to exist between the average duration of a user to organic traffic. The results of this study provide tangible digital marketing strategies which can be used by airline companies to improve the influence of their digital marketing strategies on their users. Full article
(This article belongs to the Special Issue Crowd-Powered e-Services)
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25 pages, 2513 KiB  
Article
Harvesting Crowdsourcing Platforms’ Traffic in Favour of Air Forwarders’ Brand Name and Sustainability
by Damianos P. Sakas and Nikolaos Th. Giannakopoulos
Sustainability 2021, 13(15), 8222; https://0-doi-org.brum.beds.ac.uk/10.3390/su13158222 - 23 Jul 2021
Cited by 26 | Viewed by 2935
Abstract
In the modern digitalised era, the total number of businesses and organisations utilising crowdsourcing services has risen, leading to an increase of their website traffic. In this way, there is plenty of space for marketers and strategists to capitalise big data from both [...] Read more.
In the modern digitalised era, the total number of businesses and organisations utilising crowdsourcing services has risen, leading to an increase of their website traffic. In this way, there is plenty of space for marketers and strategists to capitalise big data from both their own and the crowdsourcer’s websites. This can lead to a comprehension of factors affecting their brand name, sustainability (gross profit) and consequently visitor influence. The first of the three staged contexts, based on web data, includes the retrieval of web data analytics and metrics from five air forwarding and five crowdsourcing websites in 210 observation days. At stage two, we deployed a diagnostic-exploratory model, through Fuzzy Cognitive Mapping (FCM), and in the last stage, an Agent-Based Model is deployed for data prediction and simulation. We concluded that crowdsourcing referral traffic increases air forwarders’ top 3 keywords volume, and decreases social traffic and total keywords volume, which then boosts their global web rank and gross profit. The exact opposite results occur with crowdsourcing search traffic. To sum up, the contribution of this paper is to offer realistic and well-informed insights to marketers about SEO and SEM strategies for brand name and profit enhancement, based on harvesting crowdsourcing platform traffic. Full article
(This article belongs to the Special Issue Crowd-Powered e-Services)
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