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1 – 6 of 6Lijuan Luo, Yuwei Wang, Siqi Duan, Shanshan Shang, Baojun Ma and Xiaoli Zhou
Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations…
Abstract
Purpose
Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.
Design/methodology/approach
The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.
Findings
The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.
Originality/value
First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.
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Min Qin, Shuqin Li, Fangtong Cai, Wei Zhu and Shanshan Qiu
With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The…
Abstract
Purpose
With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas.
Design/methodology/approach
The authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process.
Findings
The empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF).
Originality/value
This empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities.
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Lifan Chen, Shanshan Zhang, Xiaoli Hu, Shengming Liu and Rujia Lan
As a counterproductive interpersonal work behavior, knowledge hiding inhibits team creativity, hampers collaboration and ultimately has a detrimental impact on organizational…
Abstract
Purpose
As a counterproductive interpersonal work behavior, knowledge hiding inhibits team creativity, hampers collaboration and ultimately has a detrimental impact on organizational performance. Drawing upon the impression management perspective. This study aims to investigate how and when employees’ political skill affects their knowledge-hiding behavior in real work contexts.
Design/methodology/approach
The authors tested the hypotheses using data gathered from 266 employees in China using a time-lagged research design.
Findings
The results indicate that political skill positively influences knowledge hiding through the supplication strategy. Moreover, the positive effect of political skill on this strategy is stronger under higher levels of competition.
Research limitations/implications
A cross-sectional design and the use of self-report questionnaires are the limitations of this study.
Originality/value
The authors contribute to the literature on the emergence of knowledge hiding by identifying an impression management perspective. The authors also contribute to the literature on political skill by exploring the potential negative effects of political skill in the interpersonal interaction. Moreover, the authors enrich the understanding of the literature in competitive climate by introducing the impression management theory and exploring its influence on knowledge floating.
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Shanshan Zhang, Fengchun Huang, Lingling Yu, Jeremy Fei Wang and Paul Benjamin Lowry
Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors'…
Abstract
Purpose
Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors' literature review indicates that uncertainty remains around the underlying mechanisms and factors involved in the self-disclosure process. The purpose of this research is to better understand the self-disclosure process from the lens of dual-process theory (DPT). The authors consider both the controlled factors (i.e. self-presentation and reciprocity) and an automatic factor (i.e. social influence to use an SNS) involved in self-disclosure and broaden The authors proposed a model to include the interactive facets of enjoyment.
Design/methodology/approach
The proposed model was empirically validated by conducting a survey among users of WeChat Moments in China.
Findings
As hypothesized, this research confirms that enjoyment and automatic processing (i.e. social influence to use an SNS) are complementary in the SNS self-disclosure process and enjoyment negatively moderates the positive relationship between controlled factor (i.e. self-presentation) and self-disclosure.
Originality/value
Theoretically, this study offers a new perspective on explaining SNS self-disclosure by adopting DPT. Specifically, this study contributes to the extant SNS research by applying DPT to examine how the controlled factors and the automatic factor shape self-disclosure processes and how enjoyment influences vary across these processes – enriching knowledge about SNS self-disclosure behaviors. Practically, the authors provide important design guidelines to practitioners concerning devising mechanisms to foster more automatic-enjoyable value-added functions to improve SNS users' participation and engagement.
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Gopi Battineni, Nalini Chintalapudi and Francesco Amenta
After the identification of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Wuhan, China, a pandemic was widely spread worldwide. In Italy, about 240,000…
Abstract
Purpose
After the identification of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at Wuhan, China, a pandemic was widely spread worldwide. In Italy, about 240,000 people were infected because of this virus including 34,721 deaths until the end of June 2020. To control this new pandemic, epidemiologists recommend the enforcement of serious mitigation measures like country lockdown, contact tracing or testing, social distancing and self-isolation.
Design/methodology/approach
This paper presents the most popular epidemic model of susceptible (S), exposed (E), infected (I) and recovered (R) collectively called SEIR to understand the virus spreading among the Italian population.
Findings
Developed SEIR model explains the infection growth across Italy and presents epidemic rates after and before country lockdown. The results demonstrated that follow-up of strict measures such that country lockdown along with high testing is making Italy practically a pandemic-free country.
Originality/value
These models largely help to estimate and understand how an infectious agent spreads in a particular country and how individual factors can affect the dynamics. Further studies like classical SEIR modeling can improve the quality of data and implementation of this modeling could represent a novelty of epidemic models.
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Zeinab Zaremohzzabieh and Roziah Mohd Rasdi
The existing literature on knowledge-sharing (KS) behavior in the organizational context demonstrates that there is diversity, if not divergence, in understanding KS. Thus, this…
Abstract
Purpose
The existing literature on knowledge-sharing (KS) behavior in the organizational context demonstrates that there is diversity, if not divergence, in understanding KS. Thus, this paper aims to integrate social cognitive theory and social exchange theory to construct a research model for determining the incentive for knowledge sharing among individuals in organizations based on past empirical results.
Design/methodology/approach
Accordingly, the methodology adopted in this study is the meta-analytic structural equation modeling based on the data gathered from 78 studies (80 samples, n = 29,318).
Findings
The most significant predictors of KSB were organizational support and social interaction ties, whereby KS intention and attitude were most optimally predicted by organizational commitment, knowledge self-efficacy, social interaction ties, organizational expectancy and reciprocal benefit. This study carried out a moderation analysis to look into potential causes of inconsistent results.
Originality/value
This meta-analysis shows the most influencing factors that trigger KSB in organizations. Moreover, this study clarifies the possible reasons for the inconsistent findings of the previous studies. Thus, it contributes to the KS literature.
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