The impact of factors on information sharing: An application of meta-analysis

Abstract

Background Information sharing plays a key role in supply chain performance. According to previous individual studies, technology, trust, commitment, and uncertainty are four potential factors affecting information sharing. However, most studies focus on testing a positive relationship between each factor and information sharing. Therefore, it is necessary to evaluate the effect of each factor on information sharing. Objective To determine the accurate effect of factors on sharing information and propose key factors to support decision-makers in improving their information sharing. Data Correlation coefficients between factors are collected from 41 individual studies with a total of 8,983 samples on Google Scholar Methods Using the rank correlation test and Egger’s regression test to test publication bias. The meta-analysis method is used to perform analysis models, including fixed-effect, random-effect, and Hunter and Schmidt methods Results Commitment plays the most important role in information sharing when compared to technology, trust, and uncertainty. Commitment accounts for 19% in the Hunter and Schmidt method and 22% in both fixed-effect and random-effect models. In addition, the result indicates that there are around 50% of other factors that affect the efficiency of sharing information besides four factors in our studies. Conclusion Technology, trust, and commitment significantly affect information sharing, of which the impact of commitment on information sharing is strongest and should be a priority in improving the effectiveness of information sharing. Our study contributes two findings to literature in the field of supply chain information sharing: 1) certain confirming the important role of commitment on sharing information, and 2) the necessity of considering other factors besides these four elements.

Supply chain visibility types and contextual characteristics: A literature‐based synthesis

“…Furthermore, while the foregoing reviews strictly address “supply chain visibility,” we followed a broader approach by including studies that address larger information sharing concepts, and we did not limit the review to empirical studies. We include math modeling, conceptual studies, and literature reviews that address information sharing across supply chain partners, as such studies provide additional insights for theory and hypothesis development (Jonsson & Myrelid, 2016; Kembro et al., 2014; Le et al., 2021; Leuschner et al., 2013; Maskey et al., 2019).…”

The Nexus of Big Data Analytics, Knowledge Sharing, and Product Innovation in Manufacturing

“…Several factors can influence the effectiveness of information sharing in product innovation. These include the technology used for information sharing, the level of trust and commitment among stakeholders, and the level of uncertainty in the information shared (Le et al, 2021). Additionally, factors such as culture (Maras, 2017), organizational structure (Cherian, 2007), and leadership (Hoch, 2014) can also play a role in determining the effectiveness of information sharing.…”

Isogency Hosmer–Lemeshow Logistic Regression-Based Secured Information Sharing for Pharma Supply Chain

“…A review and future perspective on supply chain interferences and resilience was discussed in detail in [22]. Positive and negative influences on information sharing in supply chain were investigated in [23].…”