From academic research to marketing practice: Exploring the marketing science value chain

We aim to investigate the impact of marketing science articles and tools on the practice of marketing. This impact may be direct (e.g., an academic article may be adapted to solve a practical problem) or indirect (e.g., its contents may be incorporated into practitioners' tools, which then influence marketing decision making). We use the term "marketing science value chain" to describe these diffusion steps, and survey marketing managers, marketing science intermediaries (practicing marketing analysts), and marketing academics to calibrate the value chain.In our sample, we find that (1) the impact of marketing science is perceived to be largest on decisions such as the management of brands, pricing, new products, product portfolios, and customer/market selection, and (2) tools such as segmentation, survey-based choice models, marketing mix models, and pre-test market models have the largest impact on marketing decisions. Exemplary papers from 1982 to 2003 that achieved dual - academic and practice - impact are Guadagni and Little (1983) and Green and Srinivasan (1990). Overall, our results are encouraging. First, we find that the impact of marketing science has been largest on marketing decision areas that are important to practice. Second, we find moderate alignment between academic impact and practice impact. Third, we identify antecedents of practice impact among dual impact marketing science papers. Fourth, we discover more recent trends and initiatives in the period 2004-2012, such as the increased importance of big data and the rise of digital and mobile communication, using the marketing science value chain as an organizing framework

How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems

Marketing managers often provide much poorer evaluations of model-based marketing decision support systems (MDSSs) than are warranted by the objective performance of those systems. We show that a reason for this discrepant evaluation may be that MDSSs are often not designed to help users understand and internalize the underlying factors driving the MDSS results and related recommendations. Thus, there is likely to be a gap between a marketing manager’s mental model and the decision model embedded in the MDSS. We suggest that this gap is an important reason for the poor subjective evaluations of MDSSs, even when the MDSSs are of high objective quality, ultimately resulting in unreasonably low levels of MDSS adoption and use. We propose that to have impact, an MDSS should not only be of high objective quality, but should also help reduce any mental model-MDSS model gap. We evaluate two design characteristics that together lead model-users to update their mental models and reduce the mental model-MDSS gap, resulting in better MDSS evaluations: providing feedback on the upside potential for performance improvement and providing specific suggestions for corrective actions to better align the user's mental model with the MDSS. We hypothesize that, in tandem, these two types of MDSS feedback induce marketing managers to update their mental models, a process we call deep learning, whereas individually, these two types of feedback will have much smaller effects on deep learning. We validate our framework in an experimental setting, using a realistic MDSS in the context of a direct marketing decision problem. We then discuss how our findings can lead to design improvements and better returns on investments in MDSSs such as CRM systems, Revenue Management systems, pricing decision support systems, and the like

Business to Business Buying: Challenges and Opportunities

In this article, we lay out the challenges and research opportunities associated with business-to-business (B2B) buying. These challenges and opportunities reflect four aspects of B2B buying that the Institute for the Study of Business Markets (ISBM: www.isbm.org) has identified through a Delphi-like process: (1) the changing landscape of B2B buying, (2) the increasing sophistication of sellers, (3) the impact of technological changes, and (4) the increasing importance and growth of emerging markets. For each of these four areas, we identify the relevant background, key issues, and pertinent research agendas

Commentary on "Common Method Bias in Marketing:Causes, Mechanisms,and Procedural Remedies"

Common method bias is a potentially serious methodological problem in research in marketing. Several statistical remedies have been proposed in the literature, and used by academic researchers. MacKenzie and Podsakoff (2012) identify the causes of commo

Commentary on Common Method Bias: Nature, Causes, and Procedural Remedies

Common method bias is a potentially serious methodological problem in research in marketing. Several statistical remedies have been proposed in the literature, and used by academic researchers. MacKenzie and Podsakoff (2012) identify the causes of common method bias, and then provide a set of procedural remedies that might prevent the occurrence of the problem. In this commentary, we expand on their contribution by articulating the different types of measurement error that could occur in survey research, how a procedural remedy might simultaneously affect more than one type of error, and how common method bias might manifest itself in the domain of stimulus-centered measures

The Seeds of Dissolution: Discrepancy and Incoherence in Buyer–Supplier Exchange

In this research, we examine a novel mechanism of interorganizational relationship dissolution: incoherence in a partner’s behavior. We propose that the discrepancy between an exchange partner’s opportunistic behavior and the focal firm’s expectations may create a state of incoherence and uncertainty and that this effect can be damaging to the exchange even when the partner’s behavior is better than expected. Using nearly 500 longitudinal, confidential reports of industrial buyers and sellers, we find supportive evidence that (1) the net effect of the discrepancy is initially positive when behavior is better than expected but becomes rapidly negative thereafter, and (2) the net effect of the discrepancy is always negative when behavior is worse than expected. Thus, these effects will generally damage the exchange even as the partner tries to improve the relationship. This gives insight into why exchange relationships that hit a downward spiral can be difficult, if not impossible, to salvage. We also show that the dysfunctional consequences of discrepancy are mitigated through exchange structures such as the magnitude of dependence on an organizational partner, the development phase of the relationship, and the presence of bilateral idiosyncratic investments. Implications for theory and the management of interorganizational relationships are developed

The Seeds of Dissolution: Discrepancy and Incoherence in Buyer-Supplier Exchange

In this research, we examine a novel mechanism of interorganizational relationship dissolution: incoherence in a partner's behavior. We propose that the discrepancy between an exchange partner's opportunistic behavior and the focal firm's expectations may create a state of incoherence and uncertainty and that this effect can be damaging to the exchange even when the partner's behavior is better than expected. Using nearly 500 longitudinal, confidential reports of industrial buyers and sellers, we find supportive evidence that (1) the net effect of the discrepancy is initially positive when behavior is better than expected but becomes rapidly negative thereafter, and (2) the net effect of the discrepancy is always negative when behavior is worse than expected. Thus, these effects will generally damage the exchange even as the partner tries to improve the relationship. This gives insight into why exchange relationships that hit a downward spiral can be difficult, if not impossible, to salvage. We also show that the dysfunctional consequences of discrepancy are mitigated through exchange structures such as the magnitude of dependence on an organizational partner, the development phase of the relationship, and the presence of bilateral idiosyncratic investments. Implications for theory and the management of interorganizational relationships are developed.interorganizational relationship management and performance, belief discrepancy, incoherence, organizational sensemaking, opportunism, dependence, relationship phase, bilateral investments

Mapping the Bounds of Incoherence: How Far Can You Go and How Does It Affect Your Brand?

Consumers often have to evaluate products comprising a combination of attributes that is not expected by them, given their beliefs about how attributes normally co-vary in the product category. Such an attribute combination implies that the claimed level of a product attribute is then different from what the consumer might infer, given the level of another attribute, resulting in what we call product incoherence. We develop a model to calibrate the effect of incoherence on perceptions, uncertainty, preference, and ultimately purchase. Our model can allow managers to determine consumers’ acceptance for different positions in the multiattribute space, so they can optimize their product’s positioning. Our model implies that a product that combines positively valued attributes might increase some elements of preference for the product, but if those attributes occur in unexpected combinations, incoherence will also increase uncertainty which in turn might lower other elements of preference. The net risk-adjusted preference for a product in our model accommodates both the benefit from the expected attribute levels and the uncertainty associated with incoherence. We derive implications from the model and provide an empirical test that supports those implications