Stefan Kleinschmidt, Christoph Peters and Jan Marco Leimeister
While scaling is a viable approach to respond to growing demand, service providers in contact-intensive services (CIS) – such as education, healthcare and social services �…
Abstract
Purpose
While scaling is a viable approach to respond to growing demand, service providers in contact-intensive services (CIS) – such as education, healthcare and social services – struggle to innovate their offerings. The reason is that the scaling of CIS – unlike purely digital settings – has resource limitations. To help ease the situation, the purpose of this paper is to identify and describe the practices used in scaling CIS to support ICT-enabled service innovation.
Design/methodology/approach
The research draws on an in-depth analysis of three CIS to examine service innovation practices. The analysis informs model development for service scaling.
Findings
The analysis uncovers three practices for service scaling – service interaction analysis, service pivoting and service validation – and their related activities that are applied in a cyclic and iterative logic.
Research limitations/implications
While the findings reveal that the scalability of CIS is limited and determined by the formative characteristic of personal interaction, this study and its findings describe how to leverage scalability in CIS.
Practical implications
The insights into the practices enable service providers of CIS to iteratively revise their service offerings and the logic of creating value with the service.
Originality/value
This research identifies and describes for the first time the practices for the scaling of CIS as an operationalisation of ICT-enabled service innovation.
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Jan Marco Leimeister, Karin Schweizer, Stefanie Leimeister and Helmut Krcmar
The purpose of this paper is to explore whether online communities meet their potential of providing environments in which social relationships can be readily established to help…
Abstract
Purpose
The purpose of this paper is to explore whether online communities meet their potential of providing environments in which social relationships can be readily established to help patients cope with their disease through social support. The paper aims to develop and test a model to examine antecedents of the formation of virtual relationships of cancer patients within virtual communities (VCs) as well as their effects in the form of social assistance.
Design/methodology/research
Data were collected from members of virtual patient communities in the German‐speaking internet through an online survey to which 301 cancer patients responded. The data were analyzed with partial least square (PLS) structural equation modeling.
Findings
Virtual relationships for patients are established in VCs and play an important role in meeting patients' social needs. Important determinants for the formation of virtual relationships within virtual communities for patients are general internet usage intensity (active posting vs lurking) and the perceived disadvantages of CMC. The paper also found that virtual relationships have a strong effect on virtual support of patients; more than 61 per cent of the variance of perceived social assistance of cancer patients was explained by cancer‐related VCs. Emotional support and information exchange delivered through these virtual relationships may help patients to better cope with their illness.
Research limitations/implications
In contrast to prior research, known determinants for the formation of virtual relationships (i.e. marital status, educational status, gender, and disease‐related factors such as the type of cancer as control variables, as well as general internet usage motives, and perceived advantages of CMC as direct determinants) played a weak role in this study of German cancer patients. Studies on other patient populations (i.e. patients with other acute illnesses in other cultures) are needed to see if results remain consistent.
Practical implications
Participants and administrators of patient VCs have different design criteria for the improvement of VCs for patients (e.g. concerning community management, personal behaviour and the usage of information in online communities). Once the social mechanisms taking place in online communities are better understood, the systematic redesign of online communities according to the needs of their users should be given priority.
Originality/value
Little research has been conducted examining the role of VCs for social relationships and social networks in general and for patients in particular. Antecedents and effects of virtual social relationships of patients have not been sufficiently theoretically or empirically researched to be better understood. This research combines various determinants and effects of virtual relationships from prior related research. These are integrated into a conceptual model and applied empirically to a new target group, i.e. VCs for patients.
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Chao Yu, Yueting Chai and Yi Liu
Collective intelligence has drawn many scientists’ attention in many centuries. This paper shows the collective intelligence study process in a perspective of crowd science.
Abstract
Purpose
Collective intelligence has drawn many scientists’ attention in many centuries. This paper shows the collective intelligence study process in a perspective of crowd science.
Design/methodology/approach
After summarizing the time-order process of related researches, different points of views on collective intelligence’s measurement and their modeling methods were outlined.
Findings
The authors show the recent research focusing on collective intelligence optimization. The studies on application of collective intelligence and its future potential are also discussed.
Originality/value
This paper will help researchers in crowd science have a better picture of this highly related frontier interdiscipline.
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Hanieh Javadi Khasraghi, Xuan Wang, Jun Sun and Bahar Javadi Khasraghi
To obtain optimal deliverables, more and more crowdsourcing platforms allow contest teams to submit tentative solutions and update scores/rankings on public leaderboards. Such…
Abstract
Purpose
To obtain optimal deliverables, more and more crowdsourcing platforms allow contest teams to submit tentative solutions and update scores/rankings on public leaderboards. Such feedback-seeking behavior for progress benchmarking pertains to the team representation activity of boundary spanning. The literature on virtual team performance primarily focuses on team characteristics, among which network closure is generally considered a positive factor. This study further examines how boundary spanning helps mitigate the negative impact of network closure.
Design/methodology/approach
This study collected data of 9,793 teams in 246 contests from Kaggle.com. Negative binomial regression modeling and linear regression modeling are employed to investigate the relationships among network closure, boundary spanning and team performance in crowdsourcing contests.
Findings
Whereas network closure turns out to be a negative asset for virtual teams to seek platform feedback, boundary spanning mitigates its impact on team performance. On top of such a partial mediation, boundary spanning experience and previous contest performance serve as potential moderators.
Practical implications
The findings offer helpful implications for researchers and practitioners on how to break network closure and encourage boundary spanning with the establishment of facilitating structures in crowdsourcing contests.
Originality/value
The study advances the understanding of theoretical relationships among network closure, boundary spanning and team performance in crowdsourcing contests.
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Dianwen Wang, Yupeng Mou, Zhihua Ding and Xuehui Jiang
Crowdsourcing refers to a new business model in which enterprises or individuals publish tasks or problems, attracting freelancers or contributors to participate in solving tasks…
Abstract
Purpose
Crowdsourcing refers to a new business model in which enterprises or individuals publish tasks or problems, attracting freelancers or contributors to participate in solving tasks, submitting bids and allowing task seekers to choose the final solution. How to attract more quantity and quality of contributors to submit their solutions through a crowdsourcing platform has become a vital question.
Design/methodology/approach
In this study, the authors use web crawling to obtain 43,265 effective tasks in EPWK website (www.epwk.com) to probe how to elevate the quantity and quality of contributors via task reward design. This study uses the hierarchical linear model to probe the research questions.
Findings
Results show that, with the increase of task reward, the quantity of contributors goes up first and then goes down (inverted U shape), whereas the quality of contributors goes down first and then goes up (U sharp). Moreover, the authors investigate the moderating effects of another task design attribute, task duration. This study finds that task duration weakens the effect of task reward on the quantity of contributors while strengthening the effects of task reward on the quality of contributors.
Originality/value
First, this study theoretically probes two key aspects of task performance, namely, the quantity and quality of contributors, which expand the scope of task performance evaluation. Second, this study reconciles previous concern about the relationship of task reward and performance, which is different from previous studies that have paid more attention to the single perspective of their relationship. Finally, the authors investigate the moderating effects of task duration, which further uncover the mechanism behind task reward and performance, that is, the quantity and quality of task contributors.
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Transformative generative artificial intelligence (AI) tools, such as ChatGPT, have revolutionized various sectors, including higher education. Since its release in November 2022…
Abstract
Purpose
Transformative generative artificial intelligence (AI) tools, such as ChatGPT, have revolutionized various sectors, including higher education. Since its release in November 2022, it has gathered attention from academia, scholars, students, regulators and education policymakers. Opinions diverge on whether ChatGPT’s use in academia should be circumscribed or regulated. To offer insights into some of these, this study synthesizes 139 contributions (articles and blogs) authored by instructors, publishers, professors, editors and education journalists in the education domain.
Design/methodology/approach
The study uses sentiment analysis and topic modelling to examine the 139 articles and blogs. Drawing on their insights, it firstly explores emotional dimensions of the content. Subsequently, using critical discourse analysis, it integrates them with emerging concerns (what and why), and explicates key processes (how) to inform academia, research, practice and policy.
Findings
Drawing on the results obtained from sentiment analysis, the study identifies that the overall sentiments surrounding generative AI tools such as ChatGPT in higher education are more positive (33%) than negative (11%). Using topic modelling, the study further highlights four thematic areas to explore benefits and challenges: perceptions and biases, pedagogical impact, ethical considerations and implementation and adoption.
Research limitations/implications
Limitations include the absence of student perspectives, which may offer deeper insights into perception, pedagogical impacts, and integrity-related issues. Additionally, while findings are applicable across various domains, specialized areas may present differing insights that could refine the conclusions.
Originality/value
Overall, contributors acknowledge the capabilities of generative AI tools like ChatGPT in enhancing students’ productivity. The findings suggest that it is likely to offer significant gains in the education domain, providing several benefits to both teachers and students. Nevertheless, they also consider its limitations, discrimination and bias, copyright infringement, plagiarism, fabricated unauthentic textual content and assessment bias.