Deborah L. Kellogg and Lawrence F. Cunningham
International Journal of Information Systems and Social Change, Volume 5 Issue 3
This paper reports the results of a quasi-experiment designed to identify linkages between customer attributes and apology types in service recovery in informal resolution settings. Understanding these relationships is critical for enabling more effective and dynamic social relationships between the service provider and the customer/client with the use of technology, namely Customer Relationship Management Systems (CRM). The authors find that simple apologies decrease anger, restore distributive and interactional justice, and increase satisfaction. More importantly, the paper suggests that there are significant nuances in apology types and complex relationships between customer types and effective deployment of the apology in informal resolution settings. Further, the analysis suggests that apologies with explanations are more effective among customers with service experience and that apologies with compensation are most effective for all customers. When apologies are used with successive failures there is some evidence that the apology explanations are not equally effective for all customer types. The paper concludes with a discussion of the linkages between apology, service recovery and CRM systems in informal complaint resolution to improve senior level decision making, employee performance in service recovery, and customer satisfaction in for profit and non-profit organizations.
Steven Walczak, Deborah Kellogg and Dawn Gregg
International Journal of Information Systems in the Service Sector, Vol. 2 Issue 4, October 2010, pp. 39-56.
Today’s purchase processes often require complex decision-making and consumers frequently use Web information sources to support these decisions. Increasing amounts of information, however, can make finding appropriate information problematic. This information overload, coupled with decision complexity, can increase the time to make a decision and reduce decision quality. This creates a need for tools that support these decision-making processes. Online tools that bring together data and partial solutions are one option to improve decision-making in complex, multi-criteria environments. An experiment using a prototype mashup application indicates that these types of applications may significantly decrease the time spent and improve the overall quality of complex retail decisions.
Kellogg, Deborah L. and Smith, Marlene A.
Decision Sciences Journal of Innovative Education, Vol. 7 Issue 2, pp. 433-456
Faculty teaching in online environments are universally encouraged to incorporate a variety of student-to-student learning activities into their courses. Although there is a body of both theoretical and empirical work supporting this, adult professional students participating in an online MBA program at an urban business school reported being at best indifferent and often negative regarding these learning activities. A case study was performed to explore how pervasive this attitude was and the possible reasons for it. Through various sources of data and exploration, we discovered that common interactive modalities are not associated with either perceived learning or satisfaction. A content analysis of a data analysis course revealed that 64.5% of responses recalled student-to-student interactivities when responding to a “learned least from” query. We identified three possible reasons for these negative responses: time inefficiency, interaction dysfunction, and flexibility intrusion. We conclude that, although some working professional students probably do learn from student-to-student interactivity, the costs incurred may be too great. If working adult students present a different profile than those students typically represented in academic research and thus have different needs and expectations, we may need to rethink the design of online education delivered to them.
Kellogg, Deborah L. and Walczak, Steven
Interfaces Vol. 37, Issue 4, p. 355-369
The scheduling of nursing staff is a long-standing problem with myriads of research models published by academia. The exploratory research that we discuss examines the models that academia has produced and the models that hospitals have actually used. We use data from many sources, including research articles, e-mail and telephone surveys, an industry database, and a software source catalog. Only 30 percent of systems that research articles discuss are implemented, and there is very little academic involvement in systems that third-party vendors offer. We examine causes for the research-application gap and discuss directions for future academic research to make it more applicable.