Using clustering of rankings to explain brand preferences with personality and socio-demographic variables

The primary aim of market segmentation is to identify relevant groups of consumers that can be addressed efficiently by marketing or advertising campaigns. This paper addresses the issue whether consumer groups can be identified from background variables that are not brand-related, and how much personality vs. socio-demographic variables contribute to the identification of consumer clusters. This is done by clustering aggregated preferences for 25 brands across 5 different product categories, and by relating socio-demographic and personality variables to the clusters using logistic regression and random forests over a range of different numbers of clusters. Results indicate that some personality variables contribute significantly to the identification of consumer groups in one sample. However, these results were not replicated on a second sample that was more heterogeneous in terms of socio-demographic characteristics and not representative of the brands target audience

The Intentional Use of Service Recovery Strategies to Influence Consumer Emotion, Cognition and Behaviour

Service recovery strategies have been identified as a critical factor in the success of. service organizations. This study develops a conceptual frame work to investigate how specific service recovery strategies influence the emotional, cognitive and negative behavioural responses of . consumers., as well as how emotion and cognition influence negative behavior. Understanding the impact of specific service recovery strategies will allow service providers' to more deliberately and intentionally engage in strategies that result in positive organizational outcomes. This study was conducted using a 2 x 2 between-subjects quasi-experimental design. The results suggest that service recovery has a significant impact on emotion, cognition and negative behavior. Similarly, satisfaction, negative emotion and positive emotion all influence negative behavior but distributive justice has no effect

Understanding Customer Needs to Engineer Product-Service Systems

Part 2: Knowledge-Based ServicesInternational audienceStarting from the 90s, an increasing number of companies have been starting to move from a product-centric perspective towards Product-Service-System (PSS). In this context, suitable models, methods and tools to collect, engineer and embed in a single solution all the knowledge that meets or exceeds people’s emotional needs and expectations are required. Despite that, only few authors have proposed methodologies that can be easily adopted by industrial companies to design and engineer a product-service solution starting from the customer needs. Thus, this paper focuses on the customer needs analysis and aims at proposing a methodology to support companies in identifying customer needs, representing the starting point to the engineering and/or reengineering of PSS offering and the related delivery processes. An industrial case study in ABB S.p.A. has been carried out in order to test the methodology