Exploring the role of market learning capability in competitive strategy

It has been argued that a firm's capacity to learn from its market is a source of both innovation and competitive advantage. However, past research has failed to conceptualize market-focused learning activity as a capability having the potential to contribute to competitive advantage. Prior innovation research has been biased toward technological innovation. However, there is evidence to suggest that both technological and non-technological innovations contribute to competitive advantage reflecting the need for a broader conceptualization of the innovation construct. Past research has also overlooked the critical role of entrepreneurship in the capability building process. Competitive advantage has been predominantly measured in terms of financial indicators of performance. In general, the literature reflects the need for comprehensive measures of organizational innovation and competitive advantage. This paper examines the role of market-focused learning capability in organizational innovation-based competitive strategy. The paper contributes to the strategic marketing theory by developing and refining measures of entrepreneurship, market-focused learning capability, organizational innovation and sustained competitive advantage, testing relationships among these constructs.

Quantitation of alternatively spliced NMDA receptor NR1 isoform mRNA transcripts in human brain by competitive RT-PCR

The N-methyl-D-aspartate (NMDA)-selective subtype of ionotropic glutamate receptor is of importance in neuronal differentiation and synapse consolidation, activity-dependent forms of synaptic plasticity, and excitatory amino acid-mediated neuronal toxicity [Neurosci. Res. Program, Bull. 19 (1981) 1; Lab. Invest. 68 (1993) 372]. NMDA receptors exist in vivo as tetrameric or pentameric complexes comprising proteins from two families of homologous subunits, designated NR1 and NR2(A-D) [Biochem. Biophys. Res. Commun. 185 (1992) 826]. The gene coding for the human NR1 subunit (hNR1) is composed of 21 exons, three of which (4, 20 and 21) can be differentially spliced to generate a total of eight distinct subunit variants. We detail here a competitive RT-PCR (cRT-PCR) protocol to quantify endogenous levels of hNR1 splice variants in autopsied human brain. Quantitation of each hNR1 splice variant is performed using standard curve methodology in which a known amount of synthetic ribonucleic acid competitor (internal standard) is co-amplified against total RNA. This method can be used for the quantitation of hNR1 mRNA levels in response to acute or chronic disease states, in particular in the glutamatergic-associated neuronal loss observed in Alzheimer's disease [J. Neurochem. 78 (2001) 175]. Furthermore, alterations in hNR1 mRNA expression may be reflected at the translational level, resulting in functional changes in the NMDA receptor. (C) 2003 Elsevier Science B.V. All rights reserved.

Quantitation of human brain GABAA receptor isoforms by competitive RT-PCR

We have developed a competitive RT-PCR assay, adapted from Lewohl et al. [Brain Res. Brain Res. Protoc. 1 (1997) 347]. for the quantitation of GABA, receptor beta isoforms in human brain using an internal standard that shares high sequence homology to the targets. The internal standard is identical to the beta(1) sequence except for a 61 bp deletion and the incorporation of a Hind III restriction enzyme site. Unlike traditional competitive RT-PCR, which requires a range of internal standard concentrations to be titrated against a constant amount of unknown, this method relies on a standard curve for quantitation of each sample and thus permits increased sample throughput. This method is suitable for the quantitation of beta(1), beta(2) and beta(3) isoforms of the GABA(A) receptor in human alcoholic and control brain. (C) 2003 Elsevier Science B.V. All rights reserved.

Designing competitive international compensation programs

Over the past 25 years, expatriate managers have voiced increased disenchantment with their compensation packages whíle abroad. This paper takes a prescriptive approach, outlíning severa I elements of a successful human resources strategy and stressing key ingredients of effective international compensation programs. Particular ettention is given to the adherence of cultural values and distrlbutive justice when working across nations and cultures.

Unit Commitment in a Competitive and Emission Constrained Environment

This paper is on the unit commitment problem, considering not only the economic perspective, but also the environmental perspective. We propose a bi-objective approach to handle the problem with conflicting profit and emission objectives. Numerical results based on the standard IEEE 30-bus test system illustrate the proficiency of the proposed approach.

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

A congestion management and transmission price simulator for competitive electricity markets

In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

VPPs information needs for effective operation in competitive electricity markets

The large increase of renewable energy sources and Distributed Generation (DG) of electricity gives place to the Virtual Power Producer (VPP) concept. VPPs may turn electricity generation by renewable sources valuable in electricity markets. Information availability and adequate decision-support tools are crucial for achieving VPPs’ goals. This involves information concerning associated producers and market operation. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, focusing mainly in the information requirements for adequate decision making.