Consumer Informedness and Diverse Consumer Purchasing Behaviors: Traditional Mass-Market, Trading Down, and Trading Out Into the Long Tail

As truly informed consumers are increasingly able to find exactly what they want and willing to pay premium prices to obtain products with perfect fit for them, companies have responded with new product portfolio strategies and new pricing strategies, based on the concepts of resonance marketing and hyperdifferentiation. This is not just consumers’ pursuit of products that are better, but rather better for them. It is not trading up, but rather trading out. In this paper we offer a more complete explanation of changes in consumer behavior, based on consumers’ new-found informedness, and an understanding of consumers’ pursuit of products that truly meet their individual wants and needs, cravings and longings. This paper also contributes to a deeper understanding of how online reviews are linked to sales. Recent empirical studies suggest that consumers use information in different ways in different shopping experiences, and that consumers’ purchasing behavior varies across different online shopping experiences; consequently, the best predictors of the success of different online products will therefore vary depending on what consumers are buying and why and how they are buying it

When Online Reviews Meet Hyperdifferentiation: A Study of the Craft Beer Industry

We analyze how online reviews are used to evaluate the effectiveness of product differentiation strategies based on the theories of hyperdifferentiation and resonance marketing. Hyperdifferentiation says that firms can now produce almost anything that appeals to consumers and they can manage the complexity of the increasingly diverse product portfolios that result. Resonance marketing says that informed consumers will purchase products that they actually truly want. When consumers become more informed, firms that provide highly differentiated products should experience higher growth rates than firms with less differentiated offerings. We construct measures of product positioning based on online ratings and find supportive evidence using sales data from the craft beer industry. In particular, we find that the variance of ratings and the strength of the most positive quartile of reviews play a significant role in determining which new products grow fastest in the market-place. This supports our expectations for resonance marketing

Modelling the Long-Term Impact on Herder Incomes and Environmental Services in an Uncertain World

Environmental, market and political influences affect herders’ livelihoods with the expectation that they maintain biologically and economically resilient systems. To balance these external influences and the trade-offs within a grassland system it involves the consideration of interactions between grassland ecology, technology use, environmental externalities, utilisation by grazing animals for food and fibre production, and the long-term profitability of the farming system. Many of these variables are slow-moving and are trade-offs are most efficiently studied with models. The StageTHREE Sustainable Grasslands Model, which utilizes the core functions and dynamics of more mechanistic tools, has been designed to minimize the skill and data required for parameterisation. It allows the key dynamics of the grassland systems to be incorporated along with the stochasticity of the system, in terms of both the uncertainty of the production and market environment. This enables an investigation into the sustainability and environmental impacts of alternative livestock management practices, so that these can be evaluated in relation to policy options. This paper presents an insight into the integration of herder level bioeconomic modelling for the analysis of grassland policy impacts in Mongolia and China. The research highlights that policy settings that reduce stocking rates can improve the environmental services from grasslands, and in most cases, also improve herder livelihoods and resilience

Management Changes and Strategies to Improve the Environmental Services from Grasslands in Northern China and Mongolia

The grasslands of Mongolia and northern China are part of the vast Eurasian grasslands that extend from east Asia to eastern Europe, with many common problems. Grassland degradation and herder livelihoods in the steppe regions of China and Mongolia are widely acknowledged as major issues that need to be improved. The core problem is too many animals are now grazing grasslands, initially driven by significant policy changes, and decisions that assumed more animals would lift herder incomes. Problems are accentuated by poorly defined property rights over the land. The effectiveness of current Government Programs aimed at reducing grazing pressures has been questioned, especially for their ability to deliver better environmental outcomes without impacting herder livelihoods. This panel session examines ways to understand the opportunities for improvement of grasslands. This first paper outlines some general aspects of the pastoral sectors, and management responses and strategies that can improve the services from grasslands

PGformer: Proxy-Bridged Game Transformer for Multi-Person Extremely Interactive Motion Prediction

Multi-person motion prediction is a challenging task, especially for real-world scenarios of densely interacted persons. Most previous works have been devoted to studying the case of weak interactions (e.g., hand-shaking), which typically forecast each human pose in isolation. In this paper, we focus on motion prediction for multiple persons with extreme collaborations and attempt to explore the relationships between the highly interactive persons' motion trajectories. Specifically, a novel cross-query attention (XQA) module is proposed to bilaterally learn the cross-dependencies between the two pose sequences tailored for this situation. Additionally, we introduce and build a proxy entity to bridge the involved persons, which cooperates with our proposed XQA module and subtly controls the bidirectional information flows, acting as a motion intermediary. We then adapt these designs to a Transformer-based architecture and devise a simple yet effective end-to-end framework called proxy-bridged game Transformer (PGformer) for multi-person interactive motion prediction. The effectiveness of our method has been evaluated on the challenging ExPI dataset, which involves highly interactive actions. We show that our PGformer consistently outperforms the state-of-the-art methods in both short- and long-term predictions by a large margin. Besides, our approach can also be compatible with the weakly interacted CMU-Mocap and MuPoTS-3D datasets and achieve encouraging results. Our code will become publicly available upon acceptance

Automated quantification of cartilage quality for hip treatment decision support

Purpose Preservation surgery can halt the progress of joint degradation, preserving the life of the hip; however, outcome depends on the existing cartilage quality. Biochemical analysis of the hip cartilage utilizing MRI sequences such as delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), in addition to morphological analysis, can be used to detect early signs of cartilage degradation. However, a complete, accurate 3D analysis of the cartilage regions and layers is currently not possible due to a lack of diagnostic tools. Methods A system for the efficient automatic parametrization of the 3D hip cartilage was developed. 2D U-nets were trained on manually annotated dual-flip angle (DFA) dGEMRIC for femoral head localization and cartilage segmentation. A fully automated cartilage sectioning pipeline for analysis of central and peripheral regions, femoral-acetabular layers, and a variable number of section slices, was developed along with functionality for the automatic calculation of dGEMRIC index, thickness, surface area, and volume. Results The trained networks locate the femoral head and segment the cartilage with a Dice similarity coefficient of 88 ± 3 and 83 ± 4% on DFA and magnetization-prepared 2 rapid gradient-echo (MP2RAGE) dGEMRIC, respectively. A completely automatic cartilage analysis was performed in 18s, and no significant difference for average dGEMRIC index, volume, surface area, and thickness calculated on manual and automatic segmentation was observed. Conclusion An application for the 3D analysis of hip cartilage was developed for the automated detection of subtle morphological and biochemical signs of cartilage degradation in prognostic studies and clinical diagnosis. The segmentation network achieved a 4-time increase in processing speed without loss of segmentation accuracy on both normal and deformed anatomy, enabling accurate parametrization. Retraining of the networks with the promising MP2RAGE protocol would enable analysis without the need for B1 inhomogeneity correction in the future