Global marketing of industrial products:are interpersonal relationships always critical?

The present paper examines the issue of whether interpersonal relationships are critical for global marketing of industrial products. The fields of relationship marketing, IMP group research, sales research, and network theory have stressed the importance of interpersonal relationships in the business-to-business or industrial marketing context. In contrast to this emphasis on interpersonal relationships, we argue that industrial firms can both conceive and enhance marketing strategies based on developing high quality and consistent processes, products, services or outcomes (consistent processes and outcomes). Such strategies are especially important given the fact that developing interpersonal relationships is expensive due to their reliance on frequent and/or face-to-face communications. In this paper, we examine industry and country contexts that lead to the choice of alternative industrial product marketing strategies and highlight some future research directions and managerial implications.

Personal selling of high-technology products:the solutions-selling imperative

Traditional focus on the study of high-technology firms and products has practically ignored the importance and potential contributions of the sales force, especially in business-to-business marketing. This article suggests that traditional sales force strategies associated with high-technology products have been supply driven (i.e., driven by the strategies of the marketing firm). We suggest that in order to enhance the success of high-technology products and services, firms need to be more demand driven in their sales structures (i.e., driven by the strategies of the buying firm). We suggest that it is imperative that high-technology firms adopt “solution selling” to enhance high-technology adoption as well as enhance competitiveness. We describe this change in focus and draw out its various managerial and academic implications.

The variance in sales performance explained by the knowledge structures of salespeople

The last major study of sales performance variance explained by salespeople attributes was by Churchill et al. (1985). They examined the effect of role, skills, motivation, personal factors, aptitude, and organizational/environmental factors on sales performance—factors that have dominated the sales performance area. About the same time, Weitz, Sujan, and Sujan (1986) introduced the concepts of salespeople's knowledge structures. Considerable work on the relationship of the elements of knowledge structures and performance can be found in the literature. In this research note, we determine the degree to which sales performance can be explained by knowledge structure variables, a heretofore unexplored area. If knowledge structure variables explain more variance than traditional variables, then this paper would be a call to further research in this area. In examining this research question in a retail context, we find that knowledge structure variables explain 50.2 percent of the variance in sales performance. We also find that variance explained by knowledge structures is significantly different based on gender. The impact of knowledge structures on performance was higher for men than for women. The models using education demonstrated smaller differences.

The impact of transactional and relational strategies in business markets:an agenda for inquiry

The impetus for the special issue of Industrial Marketing Management is the importance of understanding the implications of transactional and relational strategies in business-to-business contexts. The objective of the special issue is to integrate conceptual and empirical research in this area. We highlight research that extends current thinking in the area to ensure that this special issue serves an impetus for future research on this important topic.

Investigating polymer-peptide conjugates and electrospinning for the production of advanced materials

This thesis describes the production of advanced materials comprising a wide array of polymer-based building blocks. These materials include bio-hybrid polymer-peptide conjugates, based on phenylalanine and poly(ethylene oxide), and polymers with intrinsic microporosity (PIMs). Polymer-peptides conjugates were previously synthesised using click chemistry. Due to the inherent disadvantages of the reported synthesis, a new, simpler, inexpensive protocol was sought. Three synthetic methods based on amidation chemistry were investigated for both oligopeptide and polymerpeptide coupling. The resulting conjugates produced were then assessed by various analytical techniques, and the new synthesis was compared with the established protocol. An investigation was also carried out focussing on polymer-peptide coupling via ester chemistry, involving deprotection of the carboxyl terminus of the peptide. Polymer-peptide conjugates were also assessed for their propensity to self-assemble into thixotropic gels in an array of solvent mixtures. Determination of the rules governing this particular self-assembly (gelation) was required. Initial work suggested that at least four phenylalanine peptide units were necessary for self-assembly, due to favourable hydrogen bond interactions. Quantitative analysis was carried out using three analytical techniques (namely rheology, FTIR, and confocal microscopy) to probe the microstructure of the material and provided further information on the conditions for self-assembly. Several polymers were electrospun in order to produce nanofibres. These included novel materials such as PIMs and the aforementioned bio-hybrid conjugates. An investigation of the parameters governing successful fibre production was carried out for PIMs, polymer-peptide conjugates, and for nanoparticle cages coupled to a polymer scaffold. SEM analysis was carried out on all material produced during these electrospinning experiments.

Facile synthesis of poly(3-hexylthiophene)-block-poly(ethylene oxide) copolymers via Steglich esterification

Poly(ethylene oxide) has been coupled to poly(3-hexylthiophene) using esterification to produce pure diblock copolymers, highly relevant for use in organic electronic devices. The new synthetic route described herein uses a metal-free coupling step, for the first time, to afford well-defined polymers in high yields following facile purification.

Identification and evaluation of agents isolated from traditionally used herbs against Ophiophagus hannah venom

The aim of this study was firstly to identify active molecules in herbs, that are traditionally used for the treatment of snake bite, such as Curcuma antinaia, Curcuma contravenenum, Andrographis paniculata, and Tanacetum parthenium; secondly to test similar structurally related molecules and finally to prepare and evaluate an efficient formulation against Ophiophagus hannah venom intoxification. Three labdane based compounds, including labdane dialdehyde, labdane lactone, and labdane trialdehyde and two lactones including 14-deoxy-11,12-didehydroandrographolide and parthenolide were isolated by column chromatography and characterised. Using the isolated rat phrenic nerve-hemidiaphragm preparation, the antagonistic effect of crude extracts, isolated compounds and prepared formulations were measured in vitro on the inhibition of the neuromuscular transmission. Inhibition on muscle contraction, produced by the 5 μg/mL venom, was reversed by test agents in organ bath preparations. A labdane trialdehyde, isolated from C. contravenenum, was identified as the best antagonising agent in the low micromolar range. Tests on formulations of the most potent C. contravenenum extract showed, that the suppository with witepsol H15 was an effective medicine against O. hannah venom. This study elucidated the active compounds, accounting for the antivenin activity of traditionally used herbs and suggested the most suitable formulation, which may help to develop potent medicines for the treatment of snake bite in the future.

Facile synthesis of polymer-peptide conjugates via direct amino acid coupling chemistry

Polymer-peptide conjugates (also known as biohy-brids) are attracting considerable attention as injectable materials owing to the self-assembling behavior of the peptide and the ability to control the material properties using the polymer component. To this end, a simple method for preparing poly(ethylene oxide)-oligophenylalanine polymer-peptide conjugates (mPEOm-F n-OEt) using isobutylchloroformate as the activating reagent has been identified and developed. The synthetic approach reported employs an industrially viable route to produce conjugates with high yield and purity. Moreover, the approach allows judicious selection of the precursor building blocks to produce libraries of polymer-peptide conjugates with complete control over the molecular composition. Control over the molecular make-up of the conjugates allows fine control of the physicochemical properties, which will be exploited in future studies into the prominent self-assembling behavior of such materials. © 2013 Wiley Periodicals, Inc.

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations.

Bagging model with cost sensitive analysis on diabetes data

Diabetes patients might suffer from an unhealthy life, long-term treatment and chronic complicated diseases. The decreasing hospitalization rate is a crucial problem for health care centers. This study combines the bagging method with base classifier decision tree and costs-sensitive analysis for diabetes patients' classification purpose. Real patients' data collected from a regional hospital in Thailand were analyzed. The relevance factors were selected and used to construct base classifier decision tree models to classify diabetes and non-diabetes patients. The bagging method was then applied to improve accuracy. Finally, asymmetric classification cost matrices were used to give more alternative models for diabetes data analysis.

Returns on key accounts:do the results justify the expenditures?

Purpose – The use of key accounts has become a mature trend and most industrial firms use this concept in some form. Selling firms establish key account teams to attend to important customers and consolidate their selling activities. Yet, despite such increased efforts on behalf of key accounts, sufficient research has not quantified the returns on key account strategy nor has it firmly established performance differences between key and non-key accounts within a firm. In response to this shortcoming, this study aims to examine returns on key accounts. Design Methodology/approach – Data were collected from a global consulting firm. The data collection started two years after the implementation of the key account program. Data were collected on recently acquired customers (within the previous year) at two time periods: year 1 and year 3 (based on company access of data). Findings – Initially, key accounts perform as well or better than other types of accounts. However, in the long term, key accounts are less satisfied, less profitable and less beneficial for a firm’s growth than other types of accounts. Because the returns to key account expenditures, thus, appear mixed, firms should be cautious in expanding their key account strategies. Research limitations implications – The study contributes to research in three areas. First, most research on the effectiveness of key accounts refers to the between-firm level, whereas this study examines the effect within a single firm. Second, this study examines the temporal aspects of key accounts, namely, what happens to key accounts over time, in comparison with other accounts in a fairly large sample. Third, it considers the survival rates of key accounts versus other types of accounts. Practical implications – The authors suggest that firms also need to track their key accounts better because the results show that key accounts are less satisfied, less profitable and less beneficial for a firm’s growth than other types of accounts. Originality/value – Extant research has not examined these issues.

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.

A Critical Review of the Implied Cost of Equity: A New Way to Estimate the Expected Return

For the last three decades, the Capital Asset Pricing Model (CAPM) has been a dominant model to calculate expected return. In early 1990% Fama and French (1992) developed the Fama and French Three Factor model by adding two additional factors to the CAPM. However even with these present models, it has been found that estimates of the expected return are not accurate (Elton, 1999; Fama &French, 1997). Botosan (1997) introduced a new approach to estimate the expected return. This approach employs an equity valuation model to calculate the internal rate of return (IRR) which is often called, 'implied cost of equity capital" as a proxy of the expected return. This approach has been gaining in popularity among researchers. A critical review of the literature will help inform hospitality researchers regarding the issue and encourage them to implement the new approach into their own studies.

(Table S1) Age determination of sediment cores SK99_17 and MD76-131

Productivity in the Arabian Sea is one of the highest in the world. It is controlled by seasonally reversing monsoonal wind-driven upwelling of nutrient-rich deeper waters which fuel phytoplankton growth. The detailed history of upwelling-induced productivity in the eastern Arabian Sea is unknown. Here we present paleoproductivity records from a composite sediment core at the millennial scale during the last 80 kyr B.P. These records are based on relative abundance counts of planktonic foraminifera and organic carbon contents, which are shown to mainly vary in concert. The eastern Arabian Sea upwelling-induced productivity was higher in the glacial period than in the Holocene, but it fell repeatedly on millennial timescales. These productivity declines occurred during cold events in the North Atlantic region, with the most pronounced changes prevailing during the Heinrich events. Hence, seasonal monsoon winds that drive upwelling-induced productivity in the east were weak when the North Atlantic was cold. These weak winds resulted in stratification of the water column, comparable to today's Arabian Sea stratification in the intermonsoonal period. Combining the new eastern with published western Arabian Sea results shows that the entire biological factory was severely diminished during the North Atlantic Heinrich events, and the seasonal productivity change in the Arabian Sea monsoon system was reduced with year-round low productivity.

Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus

BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk