This article researches factors that influence price fairness judgments. The empirical literature suggests several factors: reference prices, the costs of the seller, a self-interest bias, and the perceived motive of sellers. Using a Dutch sample, we find empirical evidence that these factors significantly affect perceptions of fair prices. In addition, we find that the perceived fairness of prices is also influenced by other distributional concerns that are independent of the transaction. In particular, price increases are judged to be fairer if they benefit poor people or small organizations rather than rich people or big organizations.
This paper researches perceptions of the concept of price fairness in the Dutch coffee market. We distinguish four alternative standards of fair prices based on egalitarian, basic rights, capitalistic and libertarian approaches. We investigate which standards are guiding the perceptions of price fairness of citizens and coffee trade organizations. We find that there is a divergence in views between citizens and key players in the coffee market. Whereas citizens support the concept of fairness derived from the basic rights approach, holding that the price should provide coffee farmers with a minimum level of subsistence, representatives of Dutch coffee traders hold the capitalistic view that the free world market price is fair.
This research aims to find relevant evidence on whether there is a link between air capacity management (ACM) optimization and airline operations, also considering the airline business model perspective. The selected research strategy includes a case study based on Paris Charles de Gaulle Airport to measure the impact of ACM optimization variables on airline operations. For the analysis we use historical data which allows us to evaluate to what extent the new schedule obtained from the optimized scenario disrupts airline planned operations. The results of this study indicate that ACM optimization has a substantial impact on airline operations. Moreover, the airlines were categorized according to their business model, so that the results of this study revealed which category was the most affected. In detail, this study revealed that, on the one hand, Full-Service Cost Carriers (FSCCs) were the most impacted and the presented ACM optimization variables had a severe impact on slot allocation (approximately 50% of slots lost), fuel burn accounted as extra flight time in the airspace (approximately 12 min per aircraft) and disrupted operations (approximately between 31% and 39% of the preferred assigned runways were changed). On the other hand, the comparison shows that the implementation of an optimization model for managing the airport capacity, leads to a more balanced usage of runways and saves between 7% and 8% of taxi time (which decreases fuel emission).
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