Online Cashback Pricing: A New Affiliate Strategy for E-Business

This paper examines the impact of “cashback” mechanism on online merchants’ affiliate and pricing strategies. Through reimbursing a portion of the transactional amount to consumers in a form of cashback, merchants are able to practice second-degree price discrimination. We develop an analytical framework which explicitly considers the cost associated with the underlying promotional vehicle. We first identify the conditions under which affiliate strategy is profitable. Surprisingly, the promotional “low” price could be actually “high”, relative to the uniform price when cashback is absent. We also propose channel coordination as a remedy to mitigate market inefficiency caused by double marginalization. Finally, we extend our model to a duopoly setting and find that a merchant can benefit from its rival’s move into the cashback market. Interestingly, under certain conditions both merchants have no incentive to move alone but prefer its rival to do so

Bulk Glass Formation in Eutectic of La-Cu-Ni-Al Metallic Alloys

A eutectic in La-rich La-Cu₀.₅Ni₀.₅-Al alloys was determined by studying the melting behaviors and the microstructure observations. The microstructures of the La-Cu-Ni-Al alloys prepared by Bridgman Solidification and copper mould casting were studied by using scanning electron microscope (SEM). The results show that La₆₆[Cu₀.₅Ni₀.₅]₂₀Al₁₄ alloy is very near to a pseudo-ternary eutectic. When the cooling rate is higher than 450 K/s, fully amorphous can be formed; when the cooling rate is within 15 K/s to 450 K/s, the alloy has a microstructure of dendrite plus amorphous, when the cooling rate is within 12 K/s to 1.5 K/s, the microstructures of the alloy are dendrite plus eutectic, and when the cooling rate is lower than 0.12 K/s, the morphology of the alloy is eutectic microstructure. The off eutectic alloy has better glass forming ability, the best glass forming alloy obtained at La₆₂[Cu₀.₅Ni₀.₅>]₂₄Al₁₄ along the composition line of La₈₆₋x[Cu₀.₅Ni₀.₅]xAl₁₄. It has a potential to form bulk metallic glassy rod samples with diameter larger than 12 mm.Singapore-MIT Alliance (SMA

Metasurface-mediated anisotropic radiative heat transfer between nanoparticles

Metasurfaces, the two-dimensional (2D) counterpart of metamaterials, have recently attracted a great attention due to their amazing properties such as negative refraction, hyperbolic dispersion, manipulation of the evanescent spectrum. In this work, we propose a theory model for the near field radiative heat transfer (NFRHT) between two nanoparticles in the presence of an anisotropic metasurface. Specifically, we set the metasurface as an array of graphene strips (GS) since it is an ideal platform to implement any metasurface topology, ranging from isotropic to hyperbolic propagation. We show that the NFRHT between two nanoparticles can not only be significantly amplified when they are placed in proximity of the GS, but also be regulated over several orders of magnitude. In this configuration, the anisotropic surface plasmon polaritons (SPPs) supported by the GS are excited and provide a new channel for the near-field energy transport. We analyze how the conductance between two nanoparticles depends on the orientation, the structure parameters and the chemical potential of the GS, on the particle-surface or the particle-surface distances by clearly identifying the characteristics of the anisotropic SPPs such as dispersion relations, propagation length and decay length. Our findings provide a powerful way to regulate the energy transport in the particle systems, meanwhile in turn, open up a way to explore the anisotropic optical properties of the metasurface based on the measured heat transfer properties.Comment: 17 pages, 8figures, Journa

Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making

Scoring systems, as a type of predictive model, have significant advantages in interpretability and transparency and facilitate quick decision-making. As such, scoring systems have been extensively used in a wide variety of industries such as healthcare and criminal justice. However, the fairness issues in these models have long been criticized, and the use of big data and machine learning algorithms in the construction of scoring systems heightens this concern. In this paper, we propose a general framework to create fairness-aware, data-driven scoring systems. First, we develop a social welfare function that incorporates both efficiency and group fairness. Then, we transform the social welfare maximization problem into the risk minimization task in machine learning, and derive a fairness-aware scoring system with the help of mixed integer programming. Lastly, several theoretical bounds are derived for providing parameter selection suggestions. Our proposed framework provides a suitable solution to address group fairness concerns in the development of scoring systems. It enables policymakers to set and customize their desired fairness requirements as well as other application-specific constraints. We test the proposed algorithm with several empirical data sets. Experimental evidence supports the effectiveness of the proposed scoring system in achieving the optimal welfare of stakeholders and in balancing the needs for interpretability, fairness, and efficiency

The effects of adult ageing and culture on the tower of London task

This work was supported by Newton Fund Institutional Links grant ID: 331745333, under Newton-Ungku Omar Fund partnership to LP. The grant is funded by the United Kingdom Department for Business, Energy and Industrial Strategy and Malaysian Industry-Government Group for High Technology (MIGHT) and delivered by the British Council. For further information, please visit www.newtonfund.ac.uk. Data Availability Statement The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.Peer reviewedPublisher PD