Degree of Instant Competition: Estimation of Market Power in India Instant Coffee Market

The new competition policy of the Government of India seeks to promote competition to protect consumer interests and increase market efficiency. In fact, the degree of price transmission between farmers and final consumers also depends on the degree of competition in the processing sector. Moreover, policy of trade liberalization too is expected to have impact on domestic markets. It becomes imperative, therefore, that one knows the degree of competition in various domestic industries. Instant coffee market in India is a duopoly of Nestl� and Hindustan Lever for decades. They also differentiate their products through branding. At the same time, however, incumbents might have perceived potential competition from another firm, Tata Coffee. In fact, instant coffee can be considered as a part of a larger beverage market with numerous competing products. With trade liberalization, imports have also started trickling in. Thus, circumstantial evidence regarding degree of competition or the market power in the instant coffee market is rather mixed one. By econometrically estimating the perceived first-order supply relation and the demand function, we calculate the market power parameter. Results indicate that the market is not characterized by collusive behaviour. It is quite close to perfectly competitive behaviour although we cannot reject the Cournot-Nash behaviour as well. The econometric study may be complemented by in-depth case study on coffee procurement, processing, and pricing by leading producers. Similar estimations of market power and case studies may be undertaken for other industries as well.

Social positioning matters: A socialized affordance perspective of mHealth in India

Existing research on technology affordance rarely considers the role of social structures in shaping the interaction between human actors and technology. In this paper, we draw upon the concept of social positioning to explore how socialized affordances of technology adoption, as well as their impact in work and social life, are shaped by the social positions that human actors occupy within multiple social structures. We do so by examining the adoption of mHealth devices by community health workers in India. The study generates theoretical implications for research on affordances of technology and social structures by integrating social positioning of actors in the analysis of a digital practice, and enriching IS research by incorporating the broader social arrangements and power relations

Ion thermal effects in oscillating multi-ion plasma sheath theory

The effects of ion temperature are discussed in a two-ion electron plasma and for a model applicable to the oscillating sheath theory that has recently been much in the focus of researchers. The differences between the fluid and kinetic models have been pointed out, as well as the differences between the approximative kinetic description (which involves the expansion of the plasma dispersion function), and the exact kinetic description. It is shown that the approximative kinetic description, first, can not describe the additional acoustic mode which naturally exists in the plasma with an additional ion population with a finite temperature, and, second, it yields an inaccurate Landau damping of the bulk ion acoustic mode. The reasons for these two failures are described. In addition to this, a fluid model is presented that is capable of capturing both of these features that are missing in the approximative kinetic description, i.e., two (fast and slow) ion acoustic modes, and the corresponding Landau damping of both modes

Nonlinear Volatility of River Flux Fluctuations

We study the spectral properties of the magnitudes of river flux increments, the volatility. The volatility series exhibits (i) strong seasonal periodicity and (ii) strongly power-law correlations for time scales less than one year. We test the nonlinear properties of the river flux increment series by randomizing its Fourier phases and find that the surrogate volatility series (i) has almost no seasonal periodicity and (ii) is weakly correlated for time scales less than one year. We quantify the degree of nonlinearity by measuring (i) the amplitude of the power spectrum at the seasonal peak and (ii) the correlation power-law exponent of the volatility series.Comment: 5 revtex pages, 6 page

HAPPI-2: a Comprehensive and High-quality Map of Human Annotated and Predicted Protein Interactions

BACKGROUND: Human protein-protein interaction (PPI) data is essential to network and systems biology studies. PPI data can help biochemists hypothesize how proteins form complexes by binding to each other, how extracellular signals propagate through post-translational modification of de-activated signaling molecules, and how chemical reactions are coupled by enzymes involved in a complex biological process. Our capability to develop good public database resources for human PPI data has a direct impact on the quality of future research on genome biology and medicine. RESULTS: The database of Human Annotated and Predicted Protein Interactions (HAPPI) version 2.0 is a major update to the original HAPPI 1.0 database. It contains 2,922,202 unique protein-protein interactions (PPI) linked by 23,060 human proteins, making it the most comprehensive database covering human PPI data today. These PPIs contain both physical/direct interactions and high-quality functional/indirect interactions. Compared with the HAPPI 1.0 database release, HAPPI database version 2.0 (HAPPI-2) represents a 485% of human PPI data coverage increase and a 73% protein coverage increase. The revamped HAPPI web portal provides users with a friendly search, curation, and data retrieval interface, allowing them to retrieve human PPIs and available annotation information on the interaction type, interaction quality, interacting partner drug targeting data, and disease information. The updated HAPPI-2 can be freely accessed by Academic users at http://discovery.informatics.uab.edu/HAPPI . CONCLUSIONS: While the underlying data for HAPPI-2 are integrated from a diverse data sources, the new HAPPI-2 release represents a good balance between data coverage and data quality of human PPIs, making it ideally suited for network biology