Quality Choice, Competition and Vertical Relationship in a Market of Protected Designation of Origin

Protected Designation of Origin (PDO) is a public label that is used by the European Union as a tool to sustain the competitiveness and the profitability of agricultural sector and in particular to maintain rural activity in less favored areas. However, in PDO supply chain, many farmers deal with relatively few processing firms. In this framework, it is not clear that producers under such protective policy would have incentive to adopt costly measures to improve their product qualities and accept the restrictions on their production practices. Taking into account the vertical structure of the PDO supply chain, we develop a model of oligopoly and oligopsony competition to investigate the conditions under which PDO producers set high quality requirements on the production of the agricultural input. We find that even if raising quality does not imply additional willingness to pay from consumers, there is still scope for the PDO producers to choose a higher level of quality than the minimum quality standard. The outcome depends on the demand and technology characteristics, which will affect the oligopoly and oligopsony power of processors. In particular, farmers will prefer a higher quality standard than processors when the demand for PDO market is inelastic and the increase in quality generates an additional reduction in farmers’ return to scale.Marketing,

Economic Rationales of Exclusive Dealing ; Empirical Evidence from the French Distribution Networks

This paper investigates the rationales of exclusive dealing (ED), which is one of the most common forms of vertical restraint and attracts intense policy debates in anti-trust regulations. Based on a survey of the theoretical literature, we derive several hypotheses relative to the anti- and pro-competitive motivations of ED. These hypotheses are submitted to French data regarding several types of distribution networks in a wide range of sectors. Considering the industry features, our empirical analysis indicates that in the French distribution system, ED contracts tend to be procompetitive. The evidence suggests that the motivation of ED mainly lies in its positive role to foster the investment of upstream firms

Production Standards, Competition and Vertical Relationship

This paper investigates the collective choice of production standards by farmer and pro- cessor groups within a vertical food supply chain, taking into account their competition behaviors. In a context in which raising standards cannot translate into a direct price premium to consumers, we develop a general model to analyze the strategic motive of us- ing standards to limit supply and shift rents among farmers and processors in the vertical chain. We find that such a motive depends on farmers’ cost structure, final demand char- acteristics, and processors’ competition patterns. In particular, farmers prefer a stringent standard when the standard involves creating greater diseconomies of scale in production and when the demand for the final product is inelastic. However, processors only prefer a stringent standard in the presence of oligopsony competition

Production Standards, Competition and Vertical Relationship

This paper investigates the collective choice of production standards by farmer and pro- cessor groups within a vertical food supply chain, taking into account their competition behaviors. In a context in which raising standards cannot translate into a direct price premium to consumers, we develop a general model to analyze the strategic motive of us- ing standards to limit supply and shift rents among farmers and processors in the vertical chain. We find that such a motive depends on farmers’ cost structure, final demand char- acteristics, and processors’ competition patterns. In particular, farmers prefer a stringent standard when the standard involves creating greater diseconomies of scale in production and when the demand for the final product is inelastic. However, processors only prefer a stringent standard in the presence of oligopsony competition

What's in a Name? Information, Heterogeneity, and Quality in a Theory of Nested Names

Collective labels are widespread in food markets, either separated or nested with private brands; the latter known as nested names. We propose a model to explain the rationale of nested names, with collective labels being effective in reaching unaware consumers while individual brands help firms to reach aware consumers. We also incorporate the decision-making within the group of producers joining collective labels, taking into account their heterogeneity in providing quality. We show that nested names emerge when consumers become more aware of information on the label's quality and when producers become more heterogeneous. Welfare may decrease, however, when the group switches to nested names, because nested names may lead to lower quality incentives for the majority producers. The results also provide insights into the historical and recent trends in food industries, such as within-label differentiation and label fragmentation, and their welfare implications

Influences of human activity and climate change on growing-season soil moisture in the Qinghai–Tibet grasslands from 2000 to 2020

Soil moisture (SM) serves as a vital indicator reflecting environmental water conditions, but significant uncertainties still persist regarding how human activity and climate change affect SM. In this study, we quantified the influences of human activity and climate change on growing-season SM in the Qinghai–Tibet grasslands from 2000 to 2020. Climate change led to a decline in spatially mean SM at a rate of −0.01 and −0.06 g g−1 year−1 at 0–10 and 10–20 cm, respectively. Nonetheless, climate change caused the soil to become wetter in 39.97% and 22.29% areas at 0–10 and 10–20 cm, respectively. Human activity resulted in a decline in spatially mean SM by 36% and 21% at 0–10 and 10–20 cm, respectively. Nonetheless, human activity caused soil to become wetter in 2.82% areas at 0–10 cm and 30.03% areas at 10–20 cm. Therefore, both climate change and human activity have contributed to a pattern where the whole Qinghai–Tibet grasslands became drier while specific parts became wetter during the last 20 years. In addition to temperature and precipitation change, we should also pay attention to the response of SM to radiation change

Estradiol regulates miR-135b and mismatch repair gene expressions via estrogen receptor-β in colorectal cells.

Estrogen has anti-colorectal cancer effects which are thought to be mediated by mismatch repair gene (MMR) activity. Estrogen receptor (ER) expression is associated with microRNA (miRNA) expression in ER-positive tumors. However, studies of direct link between estrogen (especially estradiol E2), miRNA expression, and MMR in colorectal cancer (CRC) have not been done. In this study, we first evaluated the effects of estradiol (E2) and its antagonist ICI182,780 on the expression of miRNAs (miR-31, miR-155 and miR-135b) using COLO205, SW480 and MCF-7 cell lines, followed by examining the association of tissue miRNA expression and serum E2 levels using samples collected from 18 colorectal cancer patients. E2 inhibited the expressions of miRNAs in COLO205 cells, which could be reversed by E2 antagonist ICI 182.780. The expression of miR-135b was inversely correlated with serum E2 level and ER-β mRNA expression in CRC patients' cancer tissues. There were significant correlations between serum E2 level and expression of ER-β, miR-135b, and MMR in colon cancer tissue. This study suggests that the effects of estrogen on MMR function may be related to regulating miRNA expression via ER-β, which may be the basis for the anti-cancer effect in colorectal cells

Experimental and numerical simulation study of perforation effect of steel pipes subject to the impact loadings of ASC and LSC jets

The perforation effect of steel pipes subjected to the circular-shaped charge (ASC) and linear-shaped charge (LSC) jet were studied by experimental research, and the explicit nonlinear dynamic finite element computer code LS-DYNA was adapted to study the nonlinear responses of the steel pipes, which subjected to the impact of the two different jets, using Lagrangian-Eulerian coupling method. The deformation process and the stress of the steel pipes were described and analyzed, and the simulation results are in good agreement with the experiment data. The studies indicated that under the impact of ASC jet, the steel pipe got a circular incision and a deformation process of local perforation, flocculent shear lip forming and axial shock. Under the impact of LSC jet, the steel pipe got a ship-type incision and a deformation process of coupling of local perforation and dent, whole bending and radial shock. The formation of flocculent shear lip attributes to the radial stress concentration. Under the impact of LSC jet, the whole bending leads to the axial stretch and tearing of the cut tip, and there is a bigger radial plastic deformation area than the damage effect for the impact of ASC jet

Self-Reference Deep Adaptive Curve Estimation for Low-Light Image Enhancement

In this paper, we propose a 2-stage low-light image enhancement method called Self-Reference Deep Adaptive Curve Estimation (Self-DACE). In the first stage, we present an intuitive, lightweight, fast, and unsupervised luminance enhancement algorithm. The algorithm is based on a novel low-light enhancement curve that can be used to locally boost image brightness. We also propose a new loss function with a simplified physical model designed to preserve natural images' color, structure, and fidelity. We use a vanilla CNN to map each pixel through deep Adaptive Adjustment Curves (AAC) while preserving the local image structure. Secondly, we introduce the corresponding denoising scheme to remove the latent noise in the darkness. We approximately model the noise in the dark and deploy a Denoising-Net to estimate and remove the noise after the first stage. Exhaustive qualitative and quantitative analysis shows that our method outperforms existing state-of-the-art algorithms on multiple real-world datasets