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We solve a linear chance constrained portfolio optimization problem using Robust Optimization (RO) method wherein financial script/asset loss return distributions are considered as extreme valued. The objective function is a convex combination of portfolio’s CVaR and expected value of loss return, subject to a set of randomly perturbed chance constraints with specified probability values. The robust deterministic counterpart of the model takes the form of Second Order Cone Programming (SOCP) problem. Results from extensive simulation runs show the efficacy of our proposed models, as it helps the investor to (i) utilize extensive simulation studies to draw insights into the effect of randomness in portfolio decision making process, (ii) incorporate different risk appetite scenarios to find the optimal solutions for the financial portfolio allocation problem and (iii) compare the risk and return profiles of the investments made in both deterministic as well as in uncertain and highly volatile financial markets.

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Purpose The purpose of this paper is to highlight various aspects of business-to-business brand equity (B2BBE) and explain relative impact of marketing/advertising, research and development (R&D), human resource and distribution network to build compelling business brands that display better firm performance. Design/methodology/approach A total of 51 in-depth semi-structured interviews with distributors and industrial buyers revealed different facets of B2BBE. Generalized method of moments (GMM) was applied on a large-scale panel data set of industrial firms to estimate the effects of firms’ R&D, advertising/marketing, distribution and staff training (proxy to sources of B2BBE) on sales. Findings First, varying levels of product application criticality and end-customer brand stature reflect four distinct organizational purchase requirements, namely, assured performance, prestige, brand leaders and commodity. Second, a taxonomy of five sources of B2BBE (prominence, solutions, accessibility, relationships and network strength) manifests buyers’ interactive experience during the purchase cycle. Third, it illustrates the positive short-term effect of all explanatory variables coupled with the positive long-term impact of R&D on sales. Practical implications Features like B2C brand image, clear and precise product information, credit/flexible payment terms, distributor image, add-on services to the core product and upstream–downstream referrals characterize strong brands. GMM model results help managers, in budget allocation. Originality/value The originality of this paper lies in proposing a comprehensive B2BBE framework based on triangulation; deployment of a common structure to simultaneously investigate distributors and industrial buyers, to discover whether their philosophies reinforce/undermine industrial branding strategies; and suggesting the use of GMM model to arrive at actionable insights.