Meta-analyze dichotomous data: Do the calculations with Log Odds Ratios and report Risk Ratios or Risk Differences

This paper describes a method to convert meta-analytic results in (log) Odds Ratio to either Risk Ratio or Risk Difference. It has been argued that odds ratios are mathematically superior for meta-analysis, but risk ratios and risk differences are shown to be easier to interpret. Therefore, the proposed method enables the calculation of meta-analytic results in (log) odds ratio and to transform them afterwards in risk ratio and risk difference. This transformation is based on the assumption of equal significance of the results. It is implemented Meta-Essentials: Workbooks for meta-analyses

Unraveling the dimensions of supplier involvement and their effects on NPD performance: a meta-analysis

We study the relationship between supplier involvement in New Product Development and performance. The current literature is scattered and fragmented with studies reporting mixed empirical evidence for a variety of concepts related to ‘Early Supplier Involvement’. We conduct a systematic review and meta‐analysis of the existing literature to reconcile conflicted findings, revise and refine theoretical perspectives, and provide evidence‐based scholarly and practical implications. To achieve these aims, we unravel the general relationship by considering three factors. First, we delineate different types of performance outcomes, mainly related to NPD efficiency (e.g., speed) and NPD effectiveness (e.g., product quality). Second, we distinguish between the moment and the extent of supplier involvement, related to different theoretical perspectives on external knowledge integration. Third, we disentangle multiple levels of analysis that are seemingly obscured in the literature, specifically the project and organizational levels. We find that extensive supplier involvement has positive effects on NPD efficiency and effectiveness, whereas earlier supplier involvement only to some degree affects NPD efficiency and not effectiveness. In conclusion, our meta‐analysis based on 11,420 observations from 51 studies provides strong theoretical and practical insights on the important phenomenon of supplier involvement

In Pursuit of Supplier Knowledge : Leveraging capabilities and dividing responsibilities in product and service contexts

In this dissertation, I study the integration of supplier knowledge through the lenses of dynamic capabilities and the division of responsibilities in the contexts of products and services. In Chapter 2, I provide a meta-analysis of the effects of supplier involvement on New Product Development performance, in order to resolve prior inconclusive and mixed findings. I therefore reconceptualize supplier involvement as two distinct practices to leverage absorptive and connective capacities for external knowledge integration and provide detailed results. I conduct further research on supplier knowledge integration in the context of business-to-business services. In Chapter 3, I develop a taxonomy of quality in outsourced business services based on a qualitative comparative analysis of outsource

Unraveling the Dimensions of Supplier Involvement and their Effects on NPD Performance: A Meta-Analysis

We study the relationship between supplier involvement in new product development and performance. The current literature is scattered and fragmented with studies reporting mixed empirical evidence for a variety of concepts related to “Early Supplier Involvement.” We conduct a systematic review and meta-analysis of the existing literature to reconcile conflicted findings, revise and refine theoretical perspectives, and provide evidence-based scholarly and practical implications. To achieve these aims, we unravel the general relationship by considering three factors. First, we delineate different types of performance outcomes, mainly related to NPD efficiency (e.g., speed) and NPD effectiveness (e.g., product quality). Second, we distinguish between the moment and the extent of supplier involvement, related to different theoretical perspectives on external knowledge integration. Third, we disentangle multiple levels of analysis that are seemingly obscured in the literature, specifically the project and organizational levels. We find that extensive supplier involvement has positive effects on NPD efficiency and effectiveness, whereas earlier supplier involvement only to some degree affects NPD efficiency and not effectiveness. In conclusion, our meta-analysis based on 11,420 observations from 51 studies provides strong theoretical and practical insights on the important phenomenon of supplier involvement

User manual for Meta-Essentials: Workbooks for meta-analyses (Version 1.3)

Meta-Essentials is a set of workbooks that facilitate the integration and synthesis of effect sizes from different studies and provide figures, tables, and statistics that might be helpful for interpreting them. Meta-Essentials generates (“overall” or “meta”) statistical information regarding a set of studies of the same phenomenon based on the statistical information from each separate study. The workbooks and a pdf-version of this user manual can be downloaded from [meta-essentials](http://www.erim.eur.nl/research-support/meta-essentials)

How to interpret results of meta-analysis (Version 1.3)

Meta-analysis is a systematic method for synthesizing quantitative results of different empirical studies regarding the effect of an independent variable (or determinant, or intervention, or treatment) on a defined outcome (or dependent variable). Mainly developed in medical and psychological research as a tool for synthesizing empirical information about the outcomes of a treatment, meta-analysis is now increasingly used in the social sciences as a tool for hypothesis testing. However, the assumptions underlying meta-analytic hypothesis testing in the social sciences will usually not be met under real-life conditions. This is the reason why meta-analysis is increasingly conducted with a different aim, based on more realistic assumptions. That aim is to explore the dispersion of effect sizes