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In recent years, crowdsourcing – an open and innovative model for outsourcing tasks to a crowd – has become popular for production processes, allowing organizations and firms in different industries to access external skills and expertise efficiently. Companies have opened their innovation processes to crowds outside their boundaries, and users and customers are often involved in developing products in line with market needs. This work aims to investigate the link between crowdsourcing, production and quality to better understand this new interesting phenomenon.

An explicit and systematic method for reviewing the literature was used. Through the selection and analysis of the relevant articles in the field, this paper presents a comprehensive overview of the pros and cons, risks and opportunities, disadvantages, or concerns, as addressed in the literature, for the adoption of crowdsourcing in the production processes.

It identifies where, how and to what extent crowdsourcing can be applied profitably within the production of products and services, highlighting how crowdsourcing could affect product and process quality. Finally, some directions for future research are outlined from the analysis conducted.

This work applied the systematic literature review to investigate and evaluate the actual use and impact of crowdsourcing on the production process, focusing on quality enhancement contribution.

The literature on entrepreneurial ecosystems is fragmented, and yet, no studies have paid attention to integrating the available studies. The purpose of this study is to provide a systematic review of contributions related to entrepreneurial ecosystems.

This literature review evaluates studies that are covered in the Web of Science index.

In addition to the recent state of research (covering industries, geographical scopes, methodologies, etc.), this study provides an extension of Isenberg’s (2011) model of entrepreneurial ecosystems.

A new avenue arises for both conceptual and empirical research by emphasizing crowdsourcing as a contributing element for the entrepreneurial ecosystem. Future studies can evaluate the effectiveness of different types of crowdsourcing profoundly to make sure whether creating a promising ecosystem all types of crowdsourcing have a similar value or impact.

For public policy and local decision-makers, both collaboration opportunities and interaction interfaces between the stakeholders of the entrepreneurial need to be reconsidered in the design of entrepreneurial ecosystems.

Higher degrees of collaboration, information exchange and innovation are likely to yield favorable entrepreneurship environments.

Novelty of this study arises from integrating crowdsourcing theory in the systematic review of entrepreneurial ecosystems.

This paper aims to support small mobile application development teams or companies performing testing on a large variety of operating systems versions and mobile devices to ensure their seamless working.

This paper proposes a “hybrid crowdsourcing” method that leverages the power of public crowd testers. This leads to generating a novel crowdtesting workflow Developer/Tester- Crowdtesting (DT-CT) that focuses on developers and crowd testers as key elements in the testing process without the need for intermediate as managers or leaders. This workflow has been used in a novel crowdtesting platform (AskCrowd2Test). This platform enables testing the compatibility of mobile devices and applications at two different levels, high-level (device characteristics) or low-level (code). Additionally, a “crowd-powered knowledge base” has been developed that stores testing results, relevant issues and their solutions.

The comparison of the presented DT-CT workflow with the common and most recent crowdtesting workflows showed that DT-CT may positively impact the testing process by reducing time-consuming and budget spend because of the direct interaction of developers and crowd testers.

To authors’ knowledge, this paper is the first to propose crowdtesting workflow based on developers and public crowd testers without crowd managers or leaders, which light the beacon for the future research in this field. Additionally, this work is the first that authorizes crowd testers with a limited level of experience to participate in the testing process, which helps in studying the behaviors and interaction of end-users with apps and obtains more concrete results.

The purpose of this paper is to propose an in-depth analysis of online communities of practice that support the innovative development of web applications. The analysis is aimed at understanding the preeminent characteristics of communities of practice that can favour the process of innovation (conceptualisation and realization of a web application) and if these characteristics differ in the diverse phases of a software development project (requirement specification, design, implementation and verification).

The authors adopted a multiple case study research design, selected 29 communities of practice related to the development of web applications and classified them recognizing the different practices that refer to the different phases of the innovation process of web-applications software development. Finally, the authors focussed on seven communities comparing five important dimensions for each one.

The results of the empirical analysis show that the best practices are different, considering the different phases of the project, and that these practices can be strategies directed at members to attract them and also, strategies directed at the community to permit collaboration.

The paper proposes an important and new insight into the management of virtual communities of practice (VCoP). The authors supposed that the ways to manage a VCoP could depend on project phases. In particular, the management practices of community should differ according to the different project phases, i.e. requirements specification, design, implementation and verification of the software. Literature in this sense presented only research focussed on the different effects of virtualness on teams depending on the length of team duration and on communication efforts.

The purpose of this paper is to illustrate and conceptualize how crowdsourcing can be implemented as a potential means to address gaps in service quality within service networks and to provide guidance to marketing practitioners on the use of crowdsourcing within service networks.

This paper conceptualizes how crowdsourcing can be used to address service quality gaps in service networks and provides propositions regarding the effects of crowdsourcing on service quality gaps.

Conceptual paper with a literature review, suggested a model for service quality gaps in service networks and propositions regarding the effects of crowdsourcing to manage service quality gaps.

This research contributes to the literature on crowdsourcing by theorizing how crowdsourcing impacts service quality in service networks.

Considerations for managers implementing crowdsourcing strategies and activities within service networks are provided. In particular, implications with regard to forming the crowd, developing the most appropriate approach and integrating value into the firm are discussed.

This paper offers an original contribution linking crowdsourcing to service quality.

With the development of social media and Internet technology, many firms have started to use various crowdsourcing innovation platforms to operate their open innovation business modes. The purpose of this study is to explore how such platforms' assurance mechanisms enhance the effectiveness of crowdsourcing innovations and how to apply assurance mechanisms to handle different innovation tasks, thereby motivating more seekers to use crowdsourcing innovations.

The authors use a Python-based technology to collect the research data comprising 2,302 solvers and 8,390 trade records from zbj.com and apply statistical methods to test the postulated hypotheses.

The effectiveness of assurance mechanism is confirmed by its positive relationship with solver's behaviour, thereby improving seeker's retention behaviour. However, task complexity, task novelty and task professionalization have different moderating effects on the relationships among assurance mechanism, solver's (innovator's) behaviour and seeker's behaviour.

This study enriches the literature on crowdsourcing innovations and extends the application of uncertainty reduction theory to innovation research. It also makes the theoretical contribution that the assurance mechanism adopted by the platform has different impacts on user's behaviour depending on the task characteristics.

The findings provide guidance to the platform operator on how to design the assurance mechanism to match the innovation task and innovator's behaviour to reduce seeker's uncertainty, thereby facilitating the seeker's decision-making.

A particular value of this study lies in exploring the impact of the platform assurance mechanism of social media-based crowdsourcing innovations on innovator's behaviour, which may further improve seeker's behaviour, based on uncertainty reduction theory.

The purpose of this paper is to study the decision-making behavior of the initiator and the participant under innovative and project-based tasks, respectively. It further explores the impact of the participant’s loss aversion and the initiator’s incentive level on the participant’s optimal effort level to reveal the implicit managerial mechanism.

This paper uses the Principal-agent Theory, Prospect Theory and Game Theory to study the decision-making behavior in crowdsourcing tasks. First, according to the return at the reference point, it establishes the utility function models of the participant and the initiator. Second, based on diverse loss aversion coefficient and incentive coefficient, it constructs the decision-making models of two types of task respectively. Third, it verifies the validity of models through simulation analysis.

For innovative task, the participant’s optimal effort level increases with the increment of loss aversion and incentive level, but decreases with the increase of his effort cost. For project-based task, the participant’s optimal effort level rises with the decrease of loss aversion; if the initiator does not take appropriate incentives, information asymmetry will lead to the task becoming a low-level innovation approach. Moreover, under innovative task, when the participant has loss aversion (or loss aversion reversal), his optimal effort level is higher (or lower) than that with no loss aversion, while the result under project-based task is just the opposite.

This paper characterizes two types of crowdsourcing task. Based on the prospect theory, it develops the decision-making models of the participant and the initiator under innovative and project-based tasks, thus exploring the impact of loss aversion and incentive level on their decision-making behavior. According to the findings in this paper, the initiator may effectively speculate the participant’s effort level and adopt reasonable monetary incentive measures to optimize the crowdsourcing return. In addition, this study can provide some reference for the design of incentive mechanism in crowdsourcing tasks and improve the relevant research of crowdsourcing.

Academics and practitioners are increasingly discussing the role of crowdsourcing initiatives in dealing with the challenges imposed by the COVID-19 pandemic, along with their role in an emergency context in general. However, empirical evidence about the role of crowdsourcing initiatives in an emergency context is still scarce. This paper aims to address this gap in knowledge.

The authors adopted an inductive approach to investigate how companies leveraged crowdsourcing initiatives to address the issues posed by COVID-19. Data were collected through semi-structured interviews. The selection of the interviewees was based on a purposive sampling strategy. Data were analysed through thematic analysis.

The analysis led to the identification and examination of drivers (e.g. preserving relationships with customers), advantages (e.g. increased demand for services) and disadvantages (e.g. increased platform cost) of implementing crowdsourcing initiatives during COVID-19. By leveraging the findings, this paper suggests future research opportunities. Relevant future research opportunities include: (1) quantitatively evaluating the economic impact of crowdsourcing initiatives during a disruptive event and (2) examining how the sector in which the company operates influences the beneficial and detrimental effects of crowdsourcing initiatives on company performance.

The involvement of crowds as innovation partners has provided unique opportunities for companies to innovate and address the challenging scenario. The scientific literature about the role of crowdsourcing during COVID-19 is growing. However, there is still a scarcity of empirical evidence about the mechanisms underpinning the use of crowdsourcing during the pandemic. By leveraging semi-structured interviews, this paper addresses this relevant gap in knowledge.

The purpose of this research is to investigate the use of Twitter in business as a medium for knowledge sharing and to crowdsource information to support innovation and enhance business relationships in the context of business-to-business (B2B) marketing.

This study uses a combination of methodologies for gathering data in 52 face-to-face interviews across five countries and the downloaded posts from each of the interviewees' Twitter accounts. The tweets were analysed using structural topic modelling (STM), and then compared to the interview data. This method enabled triangulation between stated use of Twitter and respondent's actual tweets.

The research confirmed that individuals used Twitter as a source of information, ideas, promotion and innovation within their industry. Twitter facilitates building relevant business relationships through the exchange of new, expert and high-quality information within like-minded communities in real time, between companies and with their suppliers, customers and also their peers.

As this study covered five countries, further comparative research on the use of Twitter in the B2B context is called for. Further investigation of the formalisation of social media strategies and return on investment for social media marketing efforts is also warranted.

This research highlights the business relationship building capacity of Twitter as it enables customer and peer conversations that eventually support the development of product and service innovations. Twitter has the capacity for marketers to inform and engage customers and peers in their networks on wider topics thereby building the brand of the individual users and their companies simultaneously.

This study focuses on interactions at the individual level illustrating that Twitter is used for both customer and peer interactions that can lead to the sourcing of ideas, knowledge and ultimately innovation. The study is novel in its methodological approach of combining structured interviews and text mining that found the topics of the interviewees' tweets aligned with their interview responses.

As the number of joined service providers (SPs) in knowledge-intensive crowdsourcing (KI-C) continues to rise, there is an information overload problem for KI-C platforms and consumers to identify qualified SPs to complete tasks. To this end, this paper aims to propose a quality of service (QoS) evaluation framework for SPs in KI-C to effectively and comprehensively characterize the QoS of SPs, which can aid the efficient selection of qualified SPs.

By literature summary and discussion with the expert team, a QoS evaluation indicator system for SPs in KI-C based on the SERVQUAL model is constructed. In addition, the Decision Making Trial and Evaluation Laboratory (DEMATEL) method is used to obtain evaluation indicators' weights. The SPs are evaluated and graded by the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and rank–sum ratio (RSR), respectively.

A QoS evaluation indicator system for SPs in KI-C incorporating 13 indicators based on SERVQUAL has been constructed, and a hybrid methodology combining DEMATEL, TOPSIS and RSR is applied to quantify and visualize the QoS of SPs.

The QoS evaluation framework for SPs in KI-C proposed in this paper can quantify and visualize the QoS of SPs, which can help the crowdsourcing platform to realize differentiated management for SPs and assist SPs to improve their shortcomings in a targeted manner. And this is the first paper to evaluate SPs in KI-C from the prospect of QoS.