Building scenarios with Fuzzy Cognitive Maps: An exploratory study of solar energy

In scenario planning, causal mapping has long been used as a means to elicit the worldviews of multiple experts, facilitate discussion, and challenge and improve mental models. Large and complex causal maps, however, are difficult to analyze. This paper proposes a novel method for scenario building, based on Fuzzy Cognitive Maps, that combines intuitive, cognitive mapping techniques with formal, quantitative analysis. The proposed method helps scenario planners to integrate the qualitative and partial knowledge of multiple individuals and overcome information processing limitations. The feasibility of the proposed approach is investigated with two scenario studies on solar photovoltaic panels.     

Debt-for-nature swaps: Axing the debt instead of the forests

Combining debt reduction with halting deforestation seems to be an attractive way of solving two urgent global problems at the same time at hardly any cost. But this view may be overly optimistic. What are the advantages and the drawbacks of debt-for-nature swaps? Are there any better alternatives?     

Classification performance of mathematical programming techniques in discriminant analysis: Results for small and medium sample sizes

The performance on small and medium-size samples of several techniques to solve the classification problem in discriminant analysis is investigated. The techniques considered are two widely used parametric statistical techniques (Fisher's linear discriminant function and Smith's quadratic function), and a class of recently proposed nonparametric estimation techniques based on mathematical programming (linear and mixed-integer programming). A simulation study is performed, analyzing the relative performance of the above techniques in the two-group case, for various small sample sizes, moderate group overlap and across six different data conditions. Training samples as well as validation samples are used to assess the classificatory performance of the techniques. The degree of group overlap and sample sizes selected for analysis in this paper are of interest in practice because they closely reflect conditions of many real data sets. The results of the experiment show that Smith's nonlinear quadratic function tends to be superior on the training samples and validation samples when the variances–covariances across groups are heterogeneous, while the mixed-integer technique performs best on the training samples when the variances–covariances are equal, and on validation samples with equal variances and discrete uniform independent variables. The mixed-integer technique and the quadratic discriminant function are also found to be more sensitive than the other techniques to the sample size, giving disproportionally inaccurate results on small samples.     

Fair e-lottery system proposal based on anonymous signatures

The games in which large amount of money is involved are always called into question about the existence of the possibility to manipulate the game for an immediate benefit. Lottery system is not an exception in this regard; moreover, it is a subject of rumours that the game is not as fair as it is pretended to be. After studying the advantages and drawbacks of conventional lottery systems, the authors are proposing an e-lottery system based on anonymous signatures. Even though the proposal is using electronic signatures, which imply complex calculus and the possession of digital certificates for each player, the proposed system compensates these drawbacks by increasing trust and confidence of both the players and the lottery organizer. This will lead to more players participating in the lottery, which translates to more revenue for the lottery and larger prizes for the players.     

Full-Time and Part-Time Work and the Gender Wage Gap

Using hourly and weekly wages from the Canadian Labour Force Survey from 2000 until 2018, workers were separated into full-time and part-time and the following striking observation was documented. The overall gender wage gap is larger than either the full-time pay gap or the part-time pay gap, even after controlling for detailed personal and job characteristics. This result is a consequence of two findings: (i) part-time wages are lower than full-time wages, and (ii) the majority of part-time workers are women. In aggregation, this brings down the average female wage, leading to a larger aggregate gender wage gap. This was further linked to a differential selection by gender into full-time and part-time work, with women of higher earnings potential being overrepresented in the pool of part-time workers, resulting in no gender pay gap in the part-time worker category. Policies targeted at encouraging full-time employment for women should therefore reduce the gender wage gap.

     

Technology roadmap through fuzzy cognitive map-based scenarios: the case of wind energy sector of a developing country

In this research, a national-level wind energy roadmap is developed through scenario planning. Multiple future scenarios are developed using the fuzzy cognitive maps (FCM) approach. This research has extended technology roadmapping (TRM) through FCM-based scenario analysis. Building scenarios with FCM is a new approach, and for the first time, to the best of our knowledge, FCM-based scenarios are developed for the wind energy sector of a developing country. Based on these multiple scenarios, a TRM has been developed. Scenario planning and TRM techniques are combined in this study. This research approach is applied to the wind energy sector of Pakistan as a research case. The TRM has four layers: strategic objectives, targets, barriers, and action items. Expert judgement is used to develop scenarios and TRMs.