The Effect of Single Rater Bias in Multi‐Stakeholder Research: A Methodological Evaluation of Buyer‐Supplier Relationships

As the global competitive landscape intensifies, firms have looked to their supply chain organizations to improve cost, visibility, and cycle time performance across functions, products, and markets. As a result, the scope of supply chain related operations have increasingly cut across organizational boundaries. To understand and capture such cross‐organizational activities, researchers have broadened the focus of their studies and included multiple stakeholders in their analysis (e.g., integration, sustainability, and buyer‐supplier relationships). However, multi‐stakeholder research has also increased the complexity and effort required to conduct studies across organizational boundaries. Unfortunately, many studies that use multi‐stakeholder constructs fail to fully address their multi‐sided nature during both construct conceptualization and data collection. Several studies suggest that neglecting the multi‐sided nature of certain constructs can affect the research validity and reliability and may invalidate research inferences and results, although such concerns have not been empirically demonstrated. The current study addresses this gap by performing a series of tests using data from 105 matched pairs of buyers and their suppliers to illustrate key methodological considerations for conducting multi‐stakeholder research. This study also offers practical guidance regarding assumptions routinely made in single rater research and proposes when single rater data may be appropriate for multi‐stakeholder research.     

First Step in Social Media: Measuring the Influence of Online Management Responses on Customer Satisfaction

With the growing influence of online social media, firms increasingly take an active role in interacting with consumers in social media. For many firms, their first step in online social media is management responses, where the management responds to customers' comments about the firm or its products and services. In this article, we measure the impact of management responses on customer satisfaction using data retrieved from a major online travel agency in China. Applying a panel data model that controls for regression toward the mean and heterogeneity in individual preference for hotels, we find that online management responses are highly effective among low satisfaction customers but have limited influence on other customers. Moreover, we show that the public nature of online management responses introduces a new dynamic among customers. Although online management responses increase future satisfaction of the complaining customers who receive the responses, they decrease future satisfaction of complaining customers who observe but do not receive management responses. The result is consistent with the peer‐induced fairness theory.