Emotional Decision-Making Biases Prediction in Cyber-Physical Systems
Abstract
:1. Introduction
2. Materials and Methods
2.1. About the Sample
- The budget that we have available for research.
- Experience in similar studies.
- The representation of each group considered: choose from each of them a sufficient number of respondents so that the results are indicative of the opinion of that group.
- Calculations for our study: Contrast the percentage of total active workers in a country with the people working in data center Management related activities. If the population of the country is 47 million people, and we find that 19,564,600 is the registered active workers, the number of them estimate that 5% of this population is related to this specialty (p = 0.05 and q = 0.95), we want a confidence of 95.5% that determines that k = 2 and we are willing to assume a sampling error of 5% (e) we would need a sample of at least 76 people to be representative. In our specific study:N: 19,564,600 (total active workers in Spain 19 March 2019)k: 2 (for 95.5% confidence level)e: 5%p: 0.05 (proportion of people that would match the desired profile)q: 0.95 (rest of the population proportion)Calculating the sample size:n: 76 is the minimum sample size for our study (we have 100).
2.2. About the Questionnaire
- Emotion A It is the initial emotion/mood recorded at the beginning of the experiment. It is indicated as a number from 1–5 that corresponds with the emotions above specified.
- Question 1A: When I make an important decision, for me, it is essential to overcome doubtful aspects. Questions with the suffix A indicate that no stimulus has been introduced. Every question is evaluated on a scale of 1 to 9 (being 1 the minimum score).
- Question 2A: When I make an important decision, for me, it is essential to organize the actions depending on the time.
- Question 3A: When I make an important decision, for me, it is essential to define the desired goals.
- Question 4A: When I make an important decision, for me, it is essential to accept responsibility for the decision.
- Question 5A: When I make an important decision, for me, it is essential to be motivated to make decision.
- Question 6A: When I make an important decision, for me, it is essential to generate emotions that will help me decide.
- Question 7A: When I make an important decision, for me, it is essential to reflect on the need to make the decision.
- Question 8A: When I make an important decision, for me, it is essential to plan the actions to be performed.
- Question 9A: When I make an important decision, for me, it is essential to make decisions without external pressure.
- Question 10A: When I make an important decision, for me, it is essential to take the goals of the business into account.
- Stimulus: Is the external news. it is a binary variable, as the news can be positive/good (0) or a negative/bad (1).
- Emotion B: After the news, the individuals are asked again to state the predominant emotion/mood they feel. Just like Emotion A, the emotion is indicated as a number from 1–5.
- Question 1B: When I make an important decision, for me, it is essential to overcome doubtful aspects. It is important to note that questions with the suffix B indicate that the stimulus (news) has been carried out.
- Question 2B: When I make an important decision, for me, it is essential to organize the actions depending on the time.
- Question 3B: When I make an important decision, for me, it is essential to define the desired goals.
- Question 4B: When I make an important decision, for me, it is essential to accept responsibility for the decision.
- Question 5B: When I make an important decision, for me, it is essential to be motivated to make decision.
- Question 6B: When I make an important decision, for me, it is essential to generate emotions that will help me decide.
- Question 7B: When I make an important decision, for me, it is essential to reflect on the need to make the decision.
- Question 8B: When I make an important decision, for me, it is essential to plan the actions to be performed.
- Question 9B: When I make an important decision, for me, it is essential to make decisions without external pressure.
- Question 10B: When I make an important decision, for me, it is essential to take the goals of the business into account.
- Decision: After the stimulus and the ten B questions, we ask the subjects about their willingness to act and raise the problem according to their situation. It is a binary variable, if they decide to act/raise the problem to the chain of command, the result is 1 and if they do not, it takes the 0 value.
2.3. Machine-Learning Techniques
3. Results
3.1. The Final Results
3.1.1. General Random Forest Model
3.1.2. Specific Random Forest Model
4. Discussion
Author Contributions
Acknowledgments
Conflicts of Interest
Appendix A. Machine-Learning Techniques Used in This Article
Appendix A.1. Random Forest
Appendix A.1.1. Bagged Trees
Appendix A.1.2. Random Forest
Appendix B. Weka Models
Appendix B.1. Trees J48
Appendix B.1.1. General Model
Appendix B.1.2. Specific Model
Appendix B.2. Random Forest
Appendix B.2.1. General Model
Appendix B.2.2. Specific Model
Appendix B.3. Random Tree
Appendix B.3.1. General Model
Appendix B.3.2. Specific Model
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k | 1.15 | 1.28 | 1.44 | 1.65 | 1.98 | 2 | 2.58 |
---|---|---|---|---|---|---|---|
Confidence level | 75% | 80% | 85% | 90% | 95% | 95.5% | 99% |
Metrics | Models | |
---|---|---|
General Random Forest | Specific Random Forest | |
Accuracy | 0.85 | 0.85 |
F1 | 0.84 | 0.87 |
Precision | 0.73 | 0.75 |
Recall | 0.80 | 1.00 |
Average Precision | 0.81 | 0.77 |
Area under the ROC curve | 0.91 | 0.98 |
Stimulus | Emotion B | Probability to Act |
---|---|---|
0 | 1 | 0.157 |
2 | 0.044 | |
3 | 0.434 | |
4 | 0.677 | |
5 | 0.850 | |
1 | 1 | 0.742 |
2 | 0.672 | |
3 | 0.906 | |
4 | 0.990 | |
5 | 0.990 |
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Corredera, A.; Romero, M.; Moya, J.M. Emotional Decision-Making Biases Prediction in Cyber-Physical Systems. Big Data Cogn. Comput. 2019, 3, 49. https://doi.org/10.3390/bdcc3030049
Corredera A, Romero M, Moya JM. Emotional Decision-Making Biases Prediction in Cyber-Physical Systems. Big Data and Cognitive Computing. 2019; 3(3):49. https://doi.org/10.3390/bdcc3030049
Chicago/Turabian StyleCorredera, Alberto, Marta Romero, and Jose M. Moya. 2019. "Emotional Decision-Making Biases Prediction in Cyber-Physical Systems" Big Data and Cognitive Computing 3, no. 3: 49. https://doi.org/10.3390/bdcc3030049