Beyond Statistical Power and Significance in Entrepreneurship and Management Research

Findings in most empirical research on entrepreneurship and management focuses on a few things: statistical representativeness of the data, the methodological rigor used for arriving at the results, and the statistical power of the results. However, both results and data are far from being free of criticism. This chapter provides a way forward that uses the mixed-methods approach without falling into the common confusion of multiple methods used in one research. It looks back at the reliance of statistical testing, null-hypothesis, and testing the statistical significance as the criteria. It explores available alternatives that can offer to overcome the problem of non-significance, rather than rejecting it as is usually done. It acknowledges some quantitative solutions like replication, conjoint, and comparative analyses and extends the use of some qualitative methods like exploratory methods, case studies, and theory development studies that offer alternatives to treating the presence or absence of significance. It discusses the concepts used and gives the limitations of the study.

Subsampling of Regional-Scale Database for improving Multivariate Analysis Interpretation of Groundwater Chemical Evolution and Ion Sources

: Multivariate statistics are widely and routinely used in the field of hydrogeochemistry. Trace elements, for which numerous samples show concentrations below the detection limit (censored data from a truncated dataset), are removed from the dataset in the multivariate treatment. This study now proposes an approach that consists of avoiding the truncation of the dataset of some critical elements, such as those recognized as sensitive elements regarding human health (fluoride, iron, and manganese). The method aims to reduce the dataset to increase the statistical representativeness of critical elements. This method allows a robust statistical comparison between a regional comprehensive dataset and a subset of this regional database. The results from hierarchical Cluster analysis (HCA) and principal component analysis (PCA) were generated and compared with results from the whole dataset. The proposed approach allowed for improvement in the understanding of the chemical evolution pathways of groundwater. Samples from the subset belong to the same flow line from a statistical point of view, and other samples from the database can then be compared with the samples of the subset and discussed according to their stage of evolution. The results obtained after the introduction of fluoride in the multivariate treatment suggest that dissolved fluoride can be gained either from the interaction of groundwater with marine clays or from the interaction of groundwater with Precambrian bedrock aquifers. The results partly explain why the groundwater chemical background of the region is relatively high in fluoride contents, resulting in frequent excess in regards to drinking water standards.

Reduced Inequalities as Factor of Sustainable Development: The Analysis Under Econometric Models

The paper proposes a different approach for the analysis of the sustainable development in the context of 2030 Agenda. The authors defined and used a cumulative model. For the beginning, the authors compare the dependent variable with the regressors of the four reporting entities: EU28, Romania, Turkey and Switzerland. These entities cover EU, the country of the authors, a candidate country and non-EU country, as well. The analysis is focused on the Goal 10 from the 2030 Agenda Sustainable Development, covers 2000–2017 and is based on the latest official data from Eurostat. The model used by the authors generated high statistical representativeness. The statistical tests demonstrate the model’s homogeneity. A distinct part of the paper is focused on the risk analysis. The authors basically propose a distinct approach which is usefully for the central and regional decision makers. The statistical period took into consideration is good enough to support pertinent conclusions. The analysis leads to the conclusion that Romania can decrease the disparities regarding the sustainable development. On the other hand, the Romania’s progress in achieving sustainable development’s targets is lowest than the EU average. The model proposed in the paper supports the decision makers in achieving a more performant management regarding sustainable development goals. The paper represents a theoretical approach with great applicability to economic development.

Model of Modernization for Organizational Management Component Evaluation

The chapter proposes a simple—in light of previous evaluations of the instrument used in Excel in the MMGO model—methodology for each of the stages, giving particularly appropriate values for components that require statistical representativeness. In the end, the sum of the components analyzed and the comprehensive income of the company, which allows us to provide a proposal for adequate solution to establish reliable stadium set to support components of the company in order to improve the presentation of the results, is presented to facilitate an analysis of any organization. In this case, its implementation is presented in the medium enterprise Excellence located in Bogotá D.C.

A Comparative Study of Hydromechanical Properties in Saturated and Partially Saturated Conditions of Two Soils from the Runway of Oran Airport

This study concerns the ground soils of the second runway of the Es-Sénia airport in Oran (Algeria). This airport was built on a very complex hydro geotechnical site when underground cavities, following the dissolution of gypsum soil, were found during the before-construction geologic studies. Several, techniques are used in laboratory (Permeability, triaxial compression tests at various confining pressure, and hydric tests in saturated and unsaturated conditions) and for in situ it’s used the results of SPT and pressure-meter tests. A comparison of parameters of two soils identified in saturated and partially saturated conditions by in situ and laboratory tests was performed in order to respond to questions of the similarity of hydro mechanical properties of two soils as well as their statistical representativeness of the in-situ reality. It is found that, in respect to the studied parameters, laboratory results are statistically significant and reconstituted soils is statistically representative of natural soil reconstitution.

Non-executive director’s motivation to continue serving on boards: a self-determination theory perspective

Purpose This paper aims to identify distinct motivation profiles among non-executive directors and explores the reasons why non-executive directors continue to serve on boards of directors. Design/methodology/approach The analysis is based on a multiple case study in the context of German supervisory boards. The authors develop their primary insights from semi-structured interviews with 53 non-executive directors. Findings The findings indicate that non-executive director motivation revolves around material incentives, reputation, meaningfulness, congruence with firm goals and enjoyment. Three distinct motivation profiles emerge from the analysis, with each profile exhibiting a set of unique reasons to continue serving on boards. Research limitations/implications Future research needs to test for the statistical representativeness of the findings and their performance implications, preferably in a shareholder-oriented governance context. Originality/value The study introduces a psychological angle to the debate about non-executive director motivation. The contributions include going beyond a bi-polar distinction between intrinsic and extrinsic motivation and draw attention to how motivation profiles relate to non-executive director’s intention to continue serving on boards.

External Validity: The Next Step for Systematic Reviews?

Background: Systematic reviews—which identify, assess, and summarize existing research—are usually designed to determine whether research shows that an intervention has evidence of effectiveness, rather than whether an intervention will work under different circumstances. The reviews typically focus on the internal validity of the research and do not consistently incorporate information on external validity into their conclusions. Objectives: In this article, we focus on how systematic reviews address external validity. Methods: We conducted a brief scan of 19 systematic reviews and a more in-depth examination of information presented in a systematic review of home visiting research. Results: We found that many reviews do not provide information on generalizability, such as statistical representativeness, but focus on factors likely to increase heterogeneity (e.g., numbers of studies or settings) and report on context. The latter may help users decide whether the research characteristics—such as sample demographics or settings—are similar to their own. However, we found that differences in reporting, such as which variables are included and how they are measured, make it difficult to summarize across studies or make basic determinations of sample characteristics, such as whether the majority of a sample was unemployed or married. Conclusion: Evaluation research and systematic reviews would benefit from reporting guidelines for external validity to ensure that key information is reported across studies.

Improving the Reliability of EBSD-Based Texture Analysis by a New Large Area Mapping Technique

The relevance of EBSD-based investigations for statements on the macroscopic or mesoscopic behavior of materials is critically relying on the statistical representativeness of the data. Particularly, the statistical reliability of the EBSD-based results (e.g. texture, phase fraction or grain size) remains an open question since the areas observed by the EBSD technique are quite small compared to XRD techniques. It has already been shown that covering larger areas and probing more grains with the help of large step sizes is beneficial in terms of representativeness [1]. On the other hand, small step sizes are beneficial in terms of grain reconstruction and data clean-up. However, step sizes significantly smaller than the average grain size of the material lead to either covered areas or number of probed grains being too small to be representative or to very large datasets and correspondingly long measurement times. In this contribution, the benefits of a new mapping technique [1] that joins the advantages of large and small step size measurements will be demonstrated. The representativeness of the EBSD datasets obtained by classical and this new mapping techniques were compared by calculating the pole figure symmetries of a TRIP steel. The results show that the proposed mapping technique significantly improves the reliability and representativeness of EBSD-based texture measurements.