Ujwal Kayande

Original ArticlesUnmasking a phantom: a psychometric assessment of mystery shopping2

Because of increasing concern over whether they are really satisfying their customers, more retail and service firms are using mystery shoppers (sometimes also referred to as secret, phantom, or anonymous consumer shoppers) to monitor their frontline operations, to assess their customer service, and to benchmark their competitors’ performance. But virtually nothing is known about the psychometric quality of the data collected in mystery shopping studies, and how it compares with that of customer survey data. Yet such information is necessary for organizations to know when to use mystery shopping, how to design mystery shopping studies, and what weight to place on their results. Here we use a generalizability theory approach to assess the psychometric quality of mystery shopping data. First, we design a study to compare the use of mystery shopping and a traditional customer survey when collecting data to assess the service quality of competitive stores. Second, we evaluate the psychometric performance of a set of secondary mystery shopping data collected to evaluate and benchmark the performance of branches of a retail network. Finally, in a follow-up study, we examine whether mystery shopping data collected to scale the more objective store environment are more reliable than data for service quality.Abstract Because of increasing concern over whether they are really satisfying their customers, more retail and service firms are using mystery shoppers (sometimes also referred to as secret, phantom, or anonymous consumer shoppers) to monitor their frontline operations, to assess their customer service, and to benchmark their competitors’ performance. But virtually nothing is known about the psychometric quality of the data collected in mystery shopping studies, and how it compares with that of customer survey data. Yet such information is necessary for organizations to know when to use mystery shopping, how to design mystery shopping studies, and what weight to place on their results. Here we use a generalizability theory approach to assess the psychometric quality of mystery shopping data. First, we design a study to compare the use of mystery shopping and a traditional customer survey when collecting data to assess the service quality of competitive stores. Second, we evaluate the psychometric performance of a set of secondary mystery shopping data collected to evaluate and benchmark the performance of branches of a retail network. Finally, in a follow-up study, we examine whether mystery shopping data collected to scale the more objective store environment are more reliable than data for service quality.

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 partners behavior. We propose that the discrepancy between an exchange partners opportunistic behavior and the focal firms expectations may create a state of incoherence and uncertainty and that this effect can be damaging to the exchange even when the partners 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.

Attributing Conversion Credit in an Online Environment: An Analysis and Classification

In the context of marketing, attribution is the process of quantifying the value of marketing activities relative to the final outcome. It is a topic rapidly growing in importance as acknowledged by the industry. However, despite numerous tools and techniques designed for its measurement, the absence of a comprehensive assessment and classification scheme persists. Thus, we aim to bridge this gap by providing an academic review to accumulate and comprehend current knowledge in attribution modeling, leading to a road map to guide future research, expediting new knowledge creation.

Openness and Innovation Performance Revisited

Firms increasingly source new ideas and knowledge from alliances with external partners. Laursen and Salters (2006) seminal research shows that while such openness in innovation benefits firms, too much openness can have a negative effect on innovation performance. We provide a conceptual replication of this finding, relying on a unique longitudinal panel data set comprising three different innovation performance metrics: product and service innovations, process innovations, and marketing innovations.