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1 – 4 of 4Zhenxin Xiao, Maggie Chuoyan Dong and Xiaoxuan Zhu
Although supplier-initiated punishment is widely used to manage distributors’ opportunism, its spillover effect on unpunished distributors (i.e. observers) within the same…
Abstract
Purpose
Although supplier-initiated punishment is widely used to manage distributors’ opportunism, its spillover effect on unpunished distributors (i.e. observers) within the same distribution network remains under-researched. Specifically, this paper aims to investigate the curvilinear effect of punishment severity on an observer’s opportunism, and how such an effect is contingent on the observer’s network position.
Design/methodology/approach
This paper uses regression analysis with survey data gathered from 218 distributors in China’s automobile industry.
Findings
Punishment severity has an inverted U-shaped effect on the observers’ opportunism, and such effect is weakened by both the observers’ network centrality and their degree of dependence on the supplier.
Practical implications
The findings should encourage suppliers to focus more on the spillover effects of punishment on observers. To this end, the supplier must deliberately initiate the appropriate level of punishment severity against its distributors because an inappropriate level of punishment severity (e.g. too lenient) may unexpectedly raise the unpunished observers’ level of opportunism. Moreover, the supplier should be fully aware that observers’ specific network positions may produce varying spillover effects of the punishment.
Originality/value
This study enriches the literature on channel governance by revealing the curvilinear mechanism through which punishment severity influences observers’ opportunism. By applying social learning theory to channel punishment research, this study unveils both the inhibitive learning and the imitative learning forces inherent in a single punishment event, and it delineates their joint effect on an observer’s opportunism. In addition, this study outlines the observer’s vertical and horizontal relationships within the distribution network and explores their contingent roles in determining the spillover effects of punishment.
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Cuijuan Liu, Zhenxin Xiao, Yu Gao, Maggie Chuoyan Dong and Shanxing Gao
Although manufacturer-initiated rewards are widely used to secure distributors’ compliance, the spillover effect on unrewarded distributors (i.e. observers) in the same…
Abstract
Purpose
Although manufacturer-initiated rewards are widely used to secure distributors’ compliance, the spillover effect on unrewarded distributors (i.e. observers) in the same distribution channel is under-researched. Using insights from social learning theory, this paper aims to investigate how manufacturer-initiated rewards affect observers’ expectation of reward and shape observers’ compliance toward the manufacturer. Furthermore, this paper explores how such effects are contingent upon distributor relationship features.
Design/methodology/approach
To test the hypotheses, hierarchical multiple regression and bootstrapping analyses were performed using survey data from 280 Chinese distributors.
Findings
The magnitude of a manufacturer-initiated reward to a distributor stimulates expectation of reward among observers, which enhances compliance; observers’ expectation of reward mediates the impact of reward magnitude on compliance. Moreover, network centrality (of the rewarded peer) negatively moderates the positive impact of reward magnitude on observers’ expectation of reward, whereas observers’ dependence (on the manufacturer) positively moderates this dynamic.
Practical implications
Manufacturers should pay attention to the spillover effects of rewards. Overall, they should use rewards of appropriate magnitude to show willingness to recognize outstanding distributors. This will inspire unrewarded distributors, which will then be more compliant. Furthermore, manufacturers should know that specific types of distributor relationship features may significantly vary the spillover effects.
Originality/value
This study illuminates the spillover effects of manufacturer-initiated reward by opening the “black box” of the link between reward magnitude and observers’ compliance and by specifying the effects’ boundary conditions.
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Xiang Gong, Zhenxin Xiao, Xiaoxiao Liu and Matthew K.O. Lee
Active participation is critical to the survival and development of the multiplayer online battle arena (MOBA) game community. However, this issue has not received much attention…
Abstract
Purpose
Active participation is critical to the survival and development of the multiplayer online battle arena (MOBA) game community. However, this issue has not received much attention in the information systems literature. To address this issue, we develop a tripartite model that accounts for the roles of behavioral dedication, constraint, obligation mechanisms on active participation in the MOBA community.
Design/methodology/approach
The research model is empirically validated by online survey data among 971 users of a popular MOBA community.
Findings
The results show that perceived enjoyment, perceived escapism, and affective commitment are key behavioral dedication factors, which further promote active participation in the MOBA community. In addition, past investment, self-efficacy for change, and calculative commitment are important behavioral constraint factors, which ultimately influence active participation in the MOBA community. Finally, subjective norm, group norm, social identity, and normative commitment are influential behavioral obligation factors, which in turn facilitate active participation in the MOBA community.
Originality/value
This study contributes to the theoretical understanding of active participation in the MOBA community and offers practical guidance for promoting active participation in the community.
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This paper aims to analyze the impact of the relations between the US oil prices, carbon emissions and GDP through the analysis of data between 1987 and 2017.
Abstract
Purpose
This paper aims to analyze the impact of the relations between the US oil prices, carbon emissions and GDP through the analysis of data between 1987 and 2017.
Design/methodology/approach
ARIMA, VAR and VEC models are used to establish synthesis integration model. Furthermore, the stability test, cointegration test and Granger causality test of the model were carried out.
Findings
The results indicate that, in both short and long term, change in oil prices is the reason for change in carbon emissions, while GDP is not the reason for the growth of carbon emissions.
Originality/value
Increase of oil prices would have a negative impact on carbon emissions, and GDP growth does not lead to an increase in carbon emissions.
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