Measuring economies of horizontal and vertical integration in the US electric power industry:how costly is unbundling?

This research employs econometric analysis on a cross section of American electricity companies in order to study the cost implications associated with unbundling the operations of integrated companies into vertically and/or horizontally separated companies. Focusing on the representative sample average firm, we find that complete horizontal and vertical disintegration resulting in the creation of separate nuclear, conventional, and hydro electric generation companies as well as a separate firm distributing power to final consumers, results in a statistically significant 13.5 percent increase in costs. Maintaining a horizontally integrated generator producing nuclear, conventional, and hydro electric generation while imposing vertical separation by creating a stand alone distribution company, results in a lower but still substantial and statistically significant cost penalty amounting to an 8.1 % increase in costs relative to a fully integrated structure. As these results imply that a vertically separated but horizontally integrated generation firm would need to reduce the costs of generation by 11% just to recoup the cost increases associated with vertical separation, even the costs associated with just vertical unbundling are quite substantial. Our paper is also the first academic paper we are aware of that systematically considers the impact of generation mix on vertical, horizontal, and overall scope economies. As a result, we are able to demonstrate that the estimated cost of unbundling in the electricity sector is substantially influenced by generation mix. Thus, for example, we find evidence of strong vertical integration economies between nuclear and conventional generation, but little evidence for vertical integration benefits between hydro generation and the distribution of power. In contrast, we find strong evidence suggesting the presence of substantial horizontal integration economies associated with the joint production of hydro generation with nuclear and/or conventional fossil fuel generation. These results are significant because they indicate that the cost of unbundling the electricity sector will differ substantially in different systems, meaning that a blanket regulatory policy with regard to the appropriateness of vertical and horizontal unbundling is likely to be inappropriate.

Supply chain integration framework using literature review

Definitions and measures of supply chain integration (SCI) are diverse. More empirical research, with clear definition and appropriate measures are needed. The purpose of this article is to identify dimensions and variables for SCI and develop an integrated framework to facilitate this. A literature review of the relevant academic papers in international journals in Logistics, Supply Chain Management and Operations Management for the period 1995-2009 has been undertaken. This study reveals that information integration, coordination and resource sharing and organisational relationship linkage are three major dimensions for SCI. The proposed framework helps integrate both upstream suppliers and downstream customers with the focal organisation. It also allows measuring SCI using both qualitative and quantitative approach. This study encourages researchers and practitioners to identify dimensions and variables for SCI and analyses how it affects the overall supply chain (SC) performance in terms of efficiency and responsiveness. Although there is extensive research in the area of SCI, a comprehensive and integrated approach is missing. This study bridges the gap by developing a framework for measuring SCI, which enables any organisation to identify critical success factors for integrating their SC, measures the degree of integration qualitatively and quantitatively and suggest improvement measures. © 2013 Copyright Taylor and Francis Group, LLC.

Discovering biomarkers for antidepressant response:protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. Trial registration: ClinicalTrials.gov identifier NCT01655706. Registered July 27, 2012.