Concerning trust and information

Communication and the associated information exchanges are key drivers of the development of relationships and of the trust embedded within them. This paper considers the development of business relationships in terms of the continuing co-evolution of trust and information exchange and the issues associated with researching these processes. The interconnections of trust and information exchange are examined in a survey of business relationships involving information exchange (n = 355). Analysis of variance shows few, if any, of the aspects of the standard conceptualizations of information exchange are associated with increased levels of trust. It is information exchange norms that have the greatest (positive) association with the level of trust. These norms emerge as part of the long term co-production of the relationship itself. This has important managerial implications. We conclude there are few managerial actions involving managing communication that can “manufacture” trust and improve or develop relationships in the short term. The paper concludes with a discussion of alternative ways of envisaging communication and relationship management and the nature and future of research into the evolution of business relationships.     

What's next in key account management research? Building the bridge between the academic literature and the practitioners' priorities

This research contrasts the academic literature on key account management (KAM) with the topics in this subject that are most critical to practitioners. Sixty four academic articles published in 17 journals, and ninety practitioners' articles appearing in the Velocity Magazine — published by the Strategic Account Management Association — were content analyzed and classified under ten ‘topic’ categories. Similarities and differences in the results for academics and practitioners are discussed. In addition, two specific topics were identified as being extremely important to managers but still under-researched by academics: the role of senior management in KAM, and the importance of internal alignment in determining KAM success.     

Selling and sales management: An introduction to the special section and recommendations on advancing the sales research agenda

Effectively managing the sales function is a prerequisite for success in business markets. Thus, practitioners are increasingly interested in improving the performance of their sales function. However, there is evidence pinpointing that academic research in the area may be experiencing a decline in its status among other subject areas in the marketing discipline. Fortunately, advances in the field of selling and sales management as reflected in the organization of specialized conferences/meetings and the development of special journal issues hold the promise of enhancing the status of sales within marketing academia. Following this stream of activities, this IMM special section on “Selling & Sales Management” aims at stimulating the level of discourse regarding how research in our field can be advanced. The present article introduces the special section; next, it summarizes the articles comprising the special section; and, finally, it concludes with some thoughts on fruitful research opportunities in the sales area.     

Quantiles as optimal point forecasts

Loss functions play a central role in the theory and practice of forecasting. If the loss function is quadratic, the mean of the predictive distribution is the unique optimal point predictor. If the loss is symmetric piecewise linear, any median is an optimal point forecast. Quantiles arise as optimal point forecasts under a general class of economically relevant loss functions, which nests the asymmetric piecewise linear loss, and which we refer to as generalized piecewise linear (GPL). The level of the quantile depends on a generic asymmetry parameter which reflects the possibly distinct costs of underprediction and overprediction. Conversely, a loss function for which quantiles are optimal point forecasts is necessarily GPL. We review characterizations of this type in the work of Thomson, Saerens and Komunjer, and relate to proper scoring rules, incentive-compatible compensation schemes and quantile regression. In the empirical part of the paper, the relevance of decision theoretic guidance in the transition from a predictive distribution to a point forecast is illustrated using the Bank of England’s density forecasts of United Kingdom inflation rates, and probabilistic predictions of wind energy resources in the Pacific Northwest.     

Implications of variant efficiency measures for policy evaluations in UK higher education

Policy goals in UK higher education encourage the publicly funded universities to become more-specialised and larger in size without compromising output quality. Efficiency gains are expected to flow from this increased specialisation in accordance with universities’ comparative research and teaching strengths. Mergers to reap further gains from economies of scale are also being actively encouraged. Given this scenario, the paper investigates whether best-practice efficiency measurement based on data envelopment analysis (DEA) provides empirical support for the current policy goals. It also assesses whether such support is dependent on the specific type of efficiency measure used in the DEA modelling. This assessment finds that a selection of (nine) commonly used, variant efficiency measures generally support the current policy goals. The paper also uses the principal-agent framework to explore the issues involved in using computed DEA-based efficiency scores for policy evaluations and possible funding guidance in UK higher education. This highlights empirically how policy-makers and universities can have very different preferences about which efficiency measure is to be used for policy evaluations and possible funding guidance.     

Spatial interaction modeling of interregional commodity flows

Drawing from both the spatial price equilibrium theoretical framework and the empirical literature on spatial interaction modeling, this paper expands models of interregional commodity flows (CFs) by incorporating new variables and using a flexible Box-Cox functional form. The 1993 US commodity flows survey provides the empirical basis for estimating state-to-state flow models for 16 commodity groups over the 48 continental US states. The optimized Box-Cox specification proves to be superior to the multiplicative one in all cases, while selected variables provide new insights into the determinants of state-to-state CFs.     

Firm heterogeneity, productivity and spatially bounded knowledge externalities

In this paper, we argue that conceptually disentangling the ‘context versus composition’ aspects of regional growth is a multilevel issue. By applying multilevel models (also called random-effects models), we show (1) the importance of considering firm-specific characteristics simultaneously with region-specific characteristics, as we find that a large part of what is traditionally assigned to the impact of the region should be assigned to firm-specific characteristics and (2) that existing single-level methodologies can be problematic, as they are vulnerable to the charge of estimating significance levels that are too liberally assigned and promote exaggerations. This is illustrated empirically by showing that single-level approaches would lead to the conclusion that innovation spillovers are highly significant in a setting of Dutch urban growth differentials, while multilevel analyses shows less liberally assigned significance levels. We conclude that multilevel-effect models better fit research questions that combine firm and spatial characteristics simultaneously, especially because they allow firm-specific characteristics to be differently linked to their regional contexts.