Introduction ixChapter 1. Modeling: The Explanatory Model and the Individual Predictive Model 11.1. Preliminary assumptions 11.1.1. Nature of uncertainty 11.1.2. Consequentialism 31.1.3. Rationality of the equity crowdfunding investor: a triptych of rationality 41.2. Explanatory model 81.2.1. Choice of model variables by the combined hypotheticodeductive and inductive/abductive approach 91.2.2. Confirmatory study of the variables of the model on qualitative material 211.2.3. Operationalization: development of the measurement model, choice, adaptation of scales and return to data 351.2.4. Other hypotheses of the model 731.2.5. Reading grids for the explanatory model 831.2.6. Conclusion 891.3. Individual predictive model 901.3.1. Presentation 901.3.2. Affective matching theory 931.3.3. Theoretical foundations 971.3.4. Definitions and operationalization 991.3.5. Concluding remarks 1071.4. Conclusion 108Chapter 2. Experimentation 1092.1. Experimental protocol 1092.1.1. Rationale and objectives 1112.1.2. Constitution, sample size and recruitment procedure 1142.1.3. Experimental protocol 1172.1.4. Experimental design 1212.1.5. Conclusion 1242.2. Carrying out the experimental procedure 1252.2.1. Conducting the experimental procedure 1252.2.2. Conclusion 1282.3. Validity and handling of biases 1282.3.1. Validity 1282.3.2. Handling biases 1292.3.3. Concluding remarks 1312.4. Conclusion 131Chapter 3. Hypotheses Testing, Results and Discussion 1333.1. Data prerequisites and the PLS approach 1333.1.1. Statistical data of the sample 1333.1.2. PLS-SEM 1343.1.3. Corrective reprocessing, transformation and adding control variables to the data file 1353.1.4. Sample size 1363.1.5. Data review: completeness and data quality 1363.1.6. Indicator measurement scales: symmetry and equidistance 1383.2. Preliminary validity of the measurement model 1383.2.1. Review of the measurement model 1383.2.2. Single-indicator variables 1423.2.3. Reflective variables 1433.2.4. Formative variables 1783.2.5. Conclusion 1913.3. Estimation of the explanatory model by structural equations 1933.3.1. PLS-SEM approach 1933.3.2. Revision of the structural model 1953.3.3. Structural model 1953.3.4. Mediators 2143.3.5. Invariance and moderators 2233.3.6. Control variables 2473.3.7. Conclusion 2503.4. Experimental design 2503.4.1. Impact of the Quality of the Business Plan on the Perceived Signal Quality 2513.4.2. Effect of the business plan on the parameters estimated by multigroup analysis 2553.4.3. Conclusion 2563.5. Results of the individual predictive model 2593.5.1. Reminder of the model 2593.5.2. Results of the individual predictive model 2703.5.3. Conclusion 2793.6. Conclusion 280Conclusion 283References 309Index 339
Christian Goglin is a Doctor of Management Sciences and a research associate at the CREGO Laboratory, part of the University of Burgundy ? France-Comte, France. His research and academic publications focus on behavioral finance and financerelated investor choice.