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Purpose This paper is about customer relationships from the perspective of small suppliers. More precisely, this paper aims to examine the relational implications through a product portfolio model with the main participants of the buying center (buyer/business manager). Design/methodology/approach The study first uses an in-depth qualitative data analysis to explore how elements of small suppliers’ relationship with such large customer’s main actors are affected by the nature of the product (categorized between strategic, bottleneck and non-critical items). From the results, an empirical model is drawn of small suppliers’ relational strategies in a product-centered and buyer/business manager relationship typology. To analyze the results of the empirical model, a quantitative analysis is performed, using the fuzzy set qualitative comparative analysis approach. Findings This study contributes to deepen the supplier–customer relationship analysis, from a product-centered and customer dyadic perspective (buyer and customer business manager). The findings highlight three different small suppliers’ relationship strategy with a different level of involvement of the different participants of the buying center. Originality/value Few studies so far analyze vertical asymmetric relationships from a triadic perspective composed of the small supplier, the buyer and the business manager – hence, this study contributes to unveiling some of the relationship complexity within a triad of actors and how small suppliers can navigate through this complexity according to their product or service positioning.

This paper analyzes the diversification benefits of adding alternative crypto-assets in a traditional portfolio, from the perspective of an investor who seeks to achieve multiple objectives. Our analysis is based on daily and weekly return data for eight different assets including Bitcoin, Ethereum, Ripple, for the crypto-assets and NASDAQ, S&P500, Dow-Jones, Crude-Oil, and Gold, for traditional assets. We use both in-sample and out-of-sample estimation procedures to analyze these data sets. We apply the weighted sum of deviations goal programming method to solve a bi-objective optimization problem where investors optimize simultaneously portfolio risk and return. For a variety of investor characteristics, ranging from risk-seeking to risk-averse, we show that augmenting portfolios with alternative crypto-currencies improves portfolio performance and the efficiency frontier, compared to standard portfolios. This improvement is even more observable for riskseeking investors, for both in-sample and out-of-sample estimation procedures.

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