Understanding user behavioral patterns in open knowledge communities

Yang, Xinrong; Song, Shuqiang; Zhao, Xinshuo; Yu, Shengquan

doi:10.1080/10494820.2017.1303518

Cited by 12 publications

(5 citation statements)

References 29 publications

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Section: Research Resultsmentioning

confidence: 99%

“…Science is also mentioned as a part of it. By applying text mining and intelligent agent technology, guidance and feedback are established to guide behaviours of users regarding knowledge evolution and in-depth interaction (Yang et al, 2018). On the other hand, the impact and application in the environment that people live in are explored, such as city, community and smart city.…”

Section: Topical Analysis Of Literaturementioning

confidence: 99%

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Bibliometrics-based visualization analysis of knowledge-based economy and implications to environmental, social and governance (ESG)

Chankoson

Dong

et al. 2022

LHT

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PurposeThis study brings knowledge economy and sharing to advance environmental, social and governance (ESG). Nevertheless, knowledge economy is a broad research field and dynamic phenomenon. To fill this lacuna, the purpose of this study is to build a link between the literature field of knowledge economy and sharing to advance each ESG limitation. To achieve this aim, the authors have (1) presented the prevailing state of research on the literature field of knowledge economy and sharing and (2) provided future research avenues for understanding the ESG.Design/methodology/approachTherefore, this study has conducted a bibliometrics-based visualization analysis of literature data of 169 publications in knowledge economy field from 2010 to 2020. The authors classify findings into five clusters mapping the evolution of knowledge economy.FindingsThe analytical findings indicate the linkages between these clusters with ESG, as well as the application of knowledge economy to advance ESG limitations. This study offers future research implications for knowledge management scholars and managerial suggestions to ESG practitioners.Originality/valueESG is a newly emerging investment concept and corporate evaluation standard aiming at exploring a sustainable development path and striking a balance between commercial value and corporate social responsibility. But the status quo indicates identical ESG limitations due to the board of directors’ limited knowledge capacity, inconsistent and ununified ESG measurement and a lack of ESG information. In parallel, knowledge economy has increasingly created a huge higher rate of return and benefits towards this disruptive society. This study brings knowledge economy and sharing to advance ESG. Nevertheless, knowledge economy is a broad research field and dynamic phenomenon.

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Section: Research Resultsmentioning

confidence: 99%

Section: Topical Analysis Of Literaturementioning

confidence: 99%

Bibliometrics-based visualization analysis of knowledge-based economy and implications to environmental, social and governance (ESG)

Chankoson

Dong

et al. 2022

LHT

View full text Add to dashboard Cite

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“…User groups usually include individuals with the intention of providing different levels of contributions [59], which increases the possibility of the market success of innovation [56]. The literature states that the continuous contribution of creative ideas by users has a positive impact on innovation performance, which, in turn, affects user behavior [60].…”

Section: Causal Relationship Of User Behavior Subsystemmentioning

confidence: 99%

“…Research shows that, in the Starbuck OIC, only one of the 500 user-submitted ideas was chosen for implementation, and whether an idea can be implemented depends largely on the degree of attention that the idea generates [61]. Therefore, interaction behavior helps improve the ideas in posts and reduce the uncertainty in decision making by facilitating better understanding [60]. Posts receiving high attention include more users demanding information and having higher innovative quality; thus, they are more easily adopted by enterprises.…”

Section: Causal Relationship Of User Behavior Subsystemmentioning

confidence: 99%

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

Gong

2019

Sustainability

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Open innovation communities (OICs) can help enterprises make full use of external knowledge resources from users, but problems such as low user participation and low conversion rate of creative ideas impact the efficiency of OICs. Most studies on this topic employ qualitative or empirical methods from a static perspective, but ignore the effect of interaction between enterprises and users as well as the cumulative effect of time. A discussion on the dynamic evolution process of open innovation is lacking. Based on a review of the literature on OICs, innovation performance, and system dynamics, this study proposes a conceptual model of innovation performance impact, which comprises the knowledge management, governance mechanism, and user behavior subsystems. Xiaomi’s OIC in China was selected as the research object, and relevant data were collected through a web spider. According to the system dynamics modeling method, a causal relationship analysis was carried out on the three aforementioned interrelated subsystems. Then, a stock flow chart with 32 variables was constructed to determine the initial values and calculation equations for each variable. Finally, the model was constructed and verified using Vensim PLE software. The simulation results were as follows. (1) The number of product releases in the Xiaomi OIC was positively correlated with the number of posts, comments, and views. Compared with user interaction behavior (i.e., commenting and viewing), the impact of user innovation behavior (i.e., posting) on enterprise innovation performance (i.e., number of patents) is clearer. Specifically, regarding interaction behavior, the impact of the users’ commenting behavior on innovation performance (i.e., number of product releases) was relatively clearer than that of their viewing behavior. (2) Governance mechanism (i.e., R&D investment and management expense), which comprises technical and organizational mechanisms, positively affected the innovation performance of enterprises. Compared with the organizational mechanism (i.e., management expense), the impact of the technical mechanism (i.e., R&D investment) on the innovation performance was clearer. (3) Governance mechanism helped to increase the number of users in the OIC, and, in turn, affected the user innovation and interaction behavior. (4) The technical mechanism positively affected knowledge application capability, which, in turn, had a positive impact on the innovation performance of enterprises. Based on these findings, management strategies are proposed for the establishment and development of OICs.

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“…In OKC, this shared and used information reflects the contributors' knowledge opinion. Knowledge opinion refers to the understanding and cognitive results of OKC's content posted by contributors (Yang et al , 2018). On the basis of OKC's distributed cognition context (Hinds and Mortensen, 2005), group knowledge heterogeneity determines the depth and breadth of the knowledge opinion shared.…”

Section: Introductionmentioning

confidence: 99%

OKC-enabled online knowledge integration: role of group heterogeneity and group interaction process

Qiu

Zuo

et al. 2020

ITP

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PurposeOnline knowledge integration has been an important concern of the online knowledge community as it can lead to various positive outcomes of online knowledge coproduction. This paper identifies online knowledge integration factors by considering group heterogeneity and group interaction process.Design/methodology/approachBased on the categorization-elaboration model (CEM) and interactive team cognition (ITC) theory, a research model that reflects the antecedent's factors and mediating factors of online knowledge integration was developed and empirically examined based on data collected from 2,339,836 data extracted from Wikipedia.FindingsGroup interaction process plays an essential mediator role in online knowledge integration. Group knowledge heterogeneity negatively influences online knowledge integration and group experience heterogeneity positively, and they both positively promote online knowledge integration through group interaction process with different paths.Research limitationsOur research concerns the OKC context in one setting (Wikipedia). We expect that the results will generalize to other OKC platforms.Practical implicationsThe findings of the study could assist the online knowledge community's organizers to understand the motivational mechanisms of online knowledge integration. Group interaction process could be regarded as the key role to promote group wisdom and maintain group independence.Social implicationsWe advance the understanding of the online knowledge integration and gain a richer understanding of the importance of group interaction independence for online knowledge integration based on the agreement of group wisdom. It suggested keeping group interaction independence is an important aspect for highly online knowledge integration among heterogeneity groups.Originality/valueThis study extends CEM and ITC theory to the domain of knowledge integration context and finds the mechanism between group heterogeneity and online knowledge integration by introducing the group interaction process.

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Understanding user behavioral patterns in open knowledge communities

Cited by 12 publications

References 29 publications

Bibliometrics-based visualization analysis of knowledge-based economy and implications to environmental, social and governance (ESG)

Bibliometrics-based visualization analysis of knowledge-based economy and implications to environmental, social and governance (ESG)

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

OKC-enabled online knowledge integration: role of group heterogeneity and group interaction process

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