Customers have become co-creators of value in software development and improvement. The intensifying integration of social networks and online communities requires an understanding of social influence on user participation. Drawing upon social capital theory, we studied the influence of peers and network position on user participation in a firm-hosted software community. Based on an analysis of longitudinal data on the knowledge seeking and knowledge contribution behaviours of 2,192 users, we found that an individual’s quantity of friends’ participation is positively related to his or her participation. The source credibility from expert friends’ participation negatively affects user participation. We especially found that network centrality which depicts an individual’s relative position in the network significantly moderates the effects of peers. Interestingly, closeness centrality and betweenness centrality exert different moderating effects on the peer effects. Closeness centrality strengthens the influence of friends’ participation on knowledge seeking but has no effect on knowledge contribution. Betweenness centrality does not affect the effects of friends’ participation. The effects of source credibility from expert friends are weaker for users with lower closeness centrality and higher betweenness centrality. This study yields a better understanding of social influence on user participation and provides insights for software community managers.

Dempster's combination rule has been widely regarded and applied since it is an effective and rigorous method of synthesizing multisource information with its special information representation (ie, mass function or basic probability assignment). However, it has also been criticized and debated upon regarding some of its unreasonable behaviors and restrictive requirements, such as the counterintuitive results in some cases. To address these issues from different perspectives, in this study, an alternative fusion rule is developed under the framework of Dempster-Shafer evidence theory. A novel evidence combination rule called CR-SLF is proposed based on soft likelihood functions (SLF) considering the ordered weighted average aggregation operator. Some illustrative examples are shown, and the corresponding analyses demonstrate the good performance of CR-SLF to fuse multisource evidence. To extend CR-SLF further, the reliability of multisource evidence is considered from two aspects, subsequently two reliability-based combination rules are presented, including the discount-based rule and the SLF improvement-based rule. The simulation results show that the reliability-based CR-SLF has a better fusion effect than the rule without considering the reliability.

Multicriteria decision making (MCDM) is to select the optimal candidate which has the best quality from a finite set of alternatives with multiple criteria. One important component of MCDM is to express the evaluation information, and the other one is to aggregate the evaluation results associated with different criteria. For the former, Pythagorean fuzzy set (PFS) is employed to represent uncertain information in this paper, and for the latter, the soft likelihood function developed by Yager is used. To address MCDM issues from a new perspective, the likelihood function of PFS is first proposed in this study and, to improve some of its limitations, the ordered weighted averaging (OWA)-based soft likelihood function is defined, which introduces the attitudinal characteristic to identify decision makers' subjective preferences. In addition, the defined soft likelihood function of PFS is extended by weighted OWA operator considering the importance weight of the argument. Several illustrative cases are provided based on the presented (weighted) OWA-based soft likelihood functions in Pythagorean fuzzy environment for MCDM problem.

Inspired by Yager, in this paper, we present the concept of likelihood for intuitionistic fuzzy sets (IFSs), and propose an approach for flexible computation of likelihood functions of IFSs for multicriteria decision-making (MCDM). We employ ordered weighted average (OWA) aggregation method to soften the strong likelihood constraint condition. The OWA measure can be considered as the attitudinal character, which determines OWA weights, including optimistic or pessimistic likelihood values. Then the reliability-based soft likelihood function is developed by considering the reliability of intuitionistic fuzzy information. Some examples are conducted by using the proposed (reliability-based) soft likelihood functions in intuitionistic fuzzy environment for MCDM problem, and the results are analyzed in detail.

Prior research on ERP assimilation has primarily focused on influential factors at the organizational level. In this study, the authors attempt to extend their understanding of individual level ERP assimilation from the perspective of social network theory. They designed a multi-case study to explore the relations between ERP users' social networks and their levels of ERP assimilation based on the three dimensions of the social networks. The authors gathered data through interviews with 26 ERP users at different levels in five companies. Qualitative analysis was used to understand the effects of social networks and interactive learning. They found that users' social networks play a significant role in individual level ERP assimilation through interactive learning among users. They also found five key factors that facilitate users' assimilation of ERP knowledge: homophily (age, position and rank), tie content (instrumental and expressive ties), tie strength, external ties, and centrality.

This study extends the enterprise resource planning (ERP) assimilation research from organizational level to individual level with the argument that it is the individual users who transform ERP systems’ capabilities into organizational performance. We employed a multi-case study method in this exploratory research with the objectives of defining individual level ERP assimilation and identifying key influential factors. Interviews with ERP users at all levels in five organizations revealed four key drivers: influence of supervisors, performance evaluation schemes, intrinsic motivation, and perceived usefulness, as well as two significant moderators: job specifications and individual absorptive capacity. Moreover, evidence suggests a potential relationship between individual level and organizational level ERP assimilations. Our findings highlight the importance of individual level assimilation within a firm in the post-implementation phase and provide managerial insights on how firms could improve ERP assimilation at the individual level that could impact the organizational level assimilation.