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In recent years, online public opinion reversal incidents have been occurring frequently, which has increased the complexity of the evolution of online public opinion, and they have become a difficult issue for public opinion management and control. It is of great significance to explore the regularity of online public opinion reversal.

Combined with the grey characteristics of online public opinion information, a grey graphical evaluation review technique (G-GERT) network model is constructed based on kernel and grey degree, and the frequency, probability and time of online public opinion reversal nodes are calculated using C-marking method and Z-marking method.

Throughout the online public opinion reversal events, there are all repeated outbreak nodes occurring, so the authors regard the repeated occurrence of outbreak nodes as reversal. According to the average frequency, probability and time of repeated outbreak nodes in the G-GERT network model, the authors predict the corresponding key information of reversal. It can simulate the evolution process of public opinion events accurately.

The G-GERT network model based on kernel and grey degree reveals the regulation of public opinion reversal, predicts the frequency, probability and time of reversal nodes, which are the most concerned and difficult issues for decision-makers. The model provides the decision basis and reference for government decision-making departments.

The incentive cost of enterprises increases significantly with the rapid growth of the social commerce (SC) market. In this context, enterprises need to develop the optimal strategy to improve incentive effectiveness and reduce cost. Different types of consumers’ responses to incentives bring different values to enterprises. Hence, this paper proposes the social commerce value network (SCVN) to help enterprises study the contributions of different types of consumers to the network.

Based on the graphical evaluation and review technique (GERT), the authors construct the social commerce value GERT (i.e. SCV-GERT) network and design three progressive experiments for estimating the value contributions of “network stage”, “consumer type”, and “resource type” to the SCVN under the same incentives. The authors initialize the SCV-GERT model with consumer data in SC and distinguish the most valuable consumers by adjusting the incentive parameters.

The results show that the SCV-GERT model can well describe the value flow of SCVN. The incentive on forwarding consumers brings the greatest value gain to the SCVN, and social trust contributes the most to forwarding consumers.

Under the guidance of the results, platforms and enterprises in SC can select the optimal type of consumers who bring the maximum network value so as to improve the effectiveness of incentive strategy and reduce marketing costs. A four-level incentive system should be established according to the ranking of the corresponding value gains: forwarding consumers > agent consumers > commenting consumers > potential consumers. Enterprises also need to find ways to improve the social resource investments of consumers participating in SC.

This paper investigates the incentive problem in SC grounded in the SCVN and uses the GERT method to construct the SCV-GERT model, which is the first attempt to introduce GERT into the SC context. This study also makes up for the lack of comparative research on different types of consumers in SC and can provide support for enterprises’ customer relationship management and marketing decisions.

Introduces a conditional repetitive group sampling plan. The OC and ASN functions are derived by GERT approach. The present development would be a valuable addition to the literature and a useful device to quality control practitioners and also to quality control engineers and plan designers in the development of further new plans.

This article presents a new chain sampling plan for three atttibute classes where items are classified into three categories namely good, marginal and bad. Various performance characteristics of interest to quality control engineers and plan designers are derived through GERT approach. In order to facilitate the operation and construction of the plan, Poisson unity values have been tabulated for a useful subset of the proposed plan.

Presents a repetitive group sampling plan for three‐attribute classes where items are classified into three categories, namely good, marginal and bad. Derives various performance characteristics of interest to quality control engineers and plan designers through the approach of the Graphic Evaluation and Review Technique (GERT). In order to facilitate the operation and construction of the plan, tabulates Poisson unity values for a useful subset of the proposed plan.

The purpose of this paper is to examine how internal locus of control (LOC) as a well-established entrepreneurial personality trait at team level impacts team performance (effectiveness and efficiency) in Austria. In addition, it investigates the interaction effects of LOC diversity and affective trust on the internal LOC-performance relationship.

Data originated from 44 entrepreneurial teams based in nine business incubators in Austria. Partial least squares (PLS) structural equation modelling was used to estimate the model.

Results indicate that higher internal LOC at team level promotes entrepreneurial team effectiveness and efficiency. However, team efficiency is increased when such teams possess a high internal LOC and low LOC diversity. Affective trust is identified as a crucial component in enhancing entrepreneurial team effectiveness, especially when the team has a high internal LOC.

This study extends research on internal LOC at team level by investigating it as a predictor of entrepreneurial team effectiveness and efficiency. Second, it systematically analyses if and how diversity in internal LOC affects team performance in an entrepreneurial team context. The paper takes a pioneering step by testing a key methodological contribution of addressing the inherent bias in measuring diversity of small teams. Finally, it is one of the first studies to show not only the importance of affect in general, but also the trust based on affect for entrepreneurial team dynamics.