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.     

Network defense and behavioral biases: an experimental study

Experimental Economics - How do people distribute defenses over a directed network attack graph, where they must defend a critical node? This question is of interest to computer scientists,...     

An examination of temporal patterns in meta-analysis

Meta-analysis has become increasingly popular as a technique for generalizing and exploring the moderators of a relationship between variables. However, few meta-analyses have explored the possibility that the relationships being studied change over time. In this study, we explore the possible theoretical reasons to expect a temporal change in a relationship under study. In addition, some methodological issues related to detecting these effects are discussed and illustrated using a sample of past studies. The paper shows that the temporal effects are easy to incorporate in the analytical plan and can add to the overall utility of meta-analysis.The authors thank Dr. Robert Peterson, University of Texas at Austin, for providing data used in the study. Dr. Naveen Donthu, Georgia State University, the editor, Dr. Donald Lehmann, and two anonymous reviewers for helpful comments.     

From academic research to marketing practice: Some further thoughts

In this rejoinder, we share some further thoughts that were triggered by the insightful comments of Lehmann and Winer, and address some concerns expressed by them. We argue that our work can be interpreted using two different reference points, leading to an optimistic view or a more pessimistic one. We also advance a number of strategies for those in our field who aspire to influence the decisions that managers actually make.     

Scale modification: alternative approaches and their consequences

Important marketing scales such as SERVQUAL are often adapted for use in a particular applied/theory-testing context and/or refined using some statistical method, assuming the resultant scale will have improved psychometric properties for a particular application. However, little attention has been paid to the consequences of how scale modifications are made, the criteria that are used to assess how well a modified scale performs, and whether scale modification is in fact worthwhile. To investigate these issues, we review approaches to scale modification, select an influential marketing scale and use context, and then examine the effects of the different scale modification approaches on which items are included in the refined scale. We then cross-validate the psychometric performance of the resulting scales using criteria that reflect the multiple purposes to which a scale can be applied. The results show approaches that leads to a more reliable scale for one purpose (e.g., segmentation) can be far less adequate for another purpose (e.g., benchmarking).     

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 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.     

Market liquidity,closeout procedures and initial margin for CCPs*

ABSTRACT

Closeout procedures enable central counterparties (CCPs) to respond to events that challenge the continuity of their normal operations, most frequently triggered by the default of one or more clearing members. The procedures typically entail three main phases: splitting, hedging, and liquidation. Together, these ensure the regularity of the settlement process through the prudent and orderly liquidation of the defaulters’ portfolios. Traditional approaches to CCPs’ margin requirements typically assume a simple closeout profile, not accounting for the ‘real life’ constraints embedded in the management of a default. The paper proposes an approach to assess how distinct closeout strategies may expose a CCP to different sets of risks and costs taking into account real-life frictions. The proposed approach enables the evaluation of a full spectrum of hedging strategies and the assessment of the trade-offs between the risk-reducing benefits of hedging and the transaction costs associated with it. Using an unexplored set of transactional level data, the proposed framework is evaluated assuming the hypothetical default of a real CCP clearing member. We consider the worst-case loss of a large interest rate swap portfolio observed over the past 10 years (i.e. 2005–2015) and show that an efficient hedging strategy which minimises risk may not be optimal when transaction costs are taken into account. The empirical analysis suggests that transaction costs are a significant factor and should be accounted for when designing a hedging strategy. Specifically, it is shown that the risk-reducing benefits arising from more tailored hedging strategies may introduce higher transaction costs, and therefore may change the effectiveness of the strategies.