Doctorate in Business and Socioeconomic Sciences

Research Profile Astrid Dickinger

Astrid Dickinger
Full Professor, Dearn of the MSc Study Programs, Department of Tourism and Service Management

Description of Research Profile
The following provides an account of the research streams developed and contributed to by Astrid Dickinger. The principal question of this research interest is, how firms can engage with customers through electronic channels and why do customers engage in these dialogues and use innovations. Furthermore, behavioral models such as satisfaction as well as dissatisfaction of customers, social norms as well as complaint handling are topics of interest. From a methodological perspective modeling and measurement are focal themes.

Understanding Customer Behavior and Innovative Services
The first area of research investigates various drivers of interaction with innovations. There is a vast body of knowledge in this field, however, yet inconclusive regarding the underlying dynamics. Therefore, this research builds on concepts from innovation management, technology acceptance and services marketing to gain further insight. The research contributes to literature on adoption, quality and trial of as well as satisfaction with a technology. Several articles contribute to theory in that they show how antecedents to satisfaction with a technology or acceptance of a technology differ when it comes to different online channels explored, competing systems evaluated and network externalities included (Dickinger, 2011; Dickinger, Arami, & Meyer, 2008; Dickinger & Stangl, 2012; Dickinger & Zins, 2008).

Heterogeneity in Customer Behavior due to Personality Traits
The vast majority of above mentioned models focus on the system performance irrespective of characteristics of an innovation’s users. Some researchers include demographic variables as moderators or as antecedents in models; however, evidence shows that these have only limited explanatory power. Traits considered in Astrid Dickinger’s research in addition to demographics are social norms, psychographics, experience, domain specific innovativeness, intrinsic motivation, knowledge about the product. Some articles tackle different types of traits with effects on behavior (Dickinger, 2007; Dickinger & Kleijnen, 2008; Stangl & Dickinger, 2010; Treiblmaier & Dickinger, 2006)

Context Factors
The third aspect of research, after insights into system factors and personality traits and their impact on users’ interaction with innovations, is to analyze the importance of the users’ context as trigger of usage. The articles Lengauer & Dickinger (2007) and Dickinger & Kleijnen (2012) investigate the relevance of context as influencing factors for mobile service consumption. While both academics and researchers have proclaimed this ubiquity as the most important relative advantage of mobile services there is still little insight into what this truly means in terms of consumers’ preferences and related behavior.

Companies’ Dialogue with Consumers
This stream of research shows how companies interact with customers through information and communication technologies (ICTs). Companies increasingly use ICTs to engage in dialogues with their customers. This leads to two sub-streams of research.
First, the efficient and high quality usage of e-mail for service recovery was investigated in two articles (Bauernfeind & Dickinger, 2009; Dickinger & Bauernfeind, 2009). Here ongoing projects by Astrid Dickinger contribute to research and practice in various ways: (a) it provides results on the quality of corporate e-mail replies to inquiries and complaints; (b) it extends research from traditional complaint handling to the online world; (c) it shows how service recovery strategies can be included in corporate communication; (d) it provides recommendations on how industry players can improve their e-mail customer interaction and gain insights into how to deal with complaints as opposed to inquiries.
Second, analyzing the utilization of mobile services for marketing purposes shows how the (mobile) Internet is used for interaction with customers. Mobile services offer companies powerful marketing potential via direct communication with consumers, anytime and anywhere. Two articles (Dickinger, Haghirian, Murphy, Scharl 2004; Scharl, Dickinger, & Murphy, 2005) give insights into the potential of mobile marketing, success factors and help gain and understanding of the diffusion of mobile marketing.

Measurement and Modeling
Formative vs. Reflective Measurement
In a methods focused research area Astrid Dickinger contributes to the debate on the appropriate conceptualization and operationalization of latent constructs. Depending on theoretical considerations certain constructs might be better represented by formative rather than by reflective indicators. Still reflective measurement is predominant in marketing and services literature. This stream of research contributes to the discussion of measurement in service and tourism and presents how formative measures are constructed and tested (Dickinger & Stangl, 2012).
Explicit and Implicit Measurement of Customer Perceptions
As the importance of the Internet as information source increases it is relevant for researchers in marketing and services to understand the customer created dialogue on the Internet. Ms. Dickinger’s research in this field focuses on identifying online representation of destinations in various sources. Furthermore, first results into measurement of image with a comparison between implicit measurement in the online world and explicit measurement from conventional studies were gained (Dickinger & Költringer, 2012; Scharl, Dickinger, & Weichselbraun, 2008). Ongoing research in this field focuses on product evaluations and forecasts of sales of products based on online word of mouth.

Modeling Unobserved Heterogeneit
From a methodological point of view, the assumption of homogeneity also has to be reconsidered. Heterogeneity can affect both, the measurement part and the structural part of behavioral models. Aggregate analysis can be seriously misleading when there are significant differences between segment-specific parameter estimates.
Therefore, Astrid Dickinger applies and compares different ways to approach heterogeneity. If the grouping criterion is clear then a (mean) split or predetermined split based on one variable could be performed (e.g. Dickinger (2009), Dickinger & Stangl (2012) and Dickinger & Zins (2008) for different systems and websites). Two articles (Dickinger & Kleijnen (2008) and Stangl & Dickinger (2010)) show how clustering of personality variables (not included in the SEM) can be used to arrive with user segments which in a second step are included as grouping variables for multiple group analysis. Dickinger (2007), however, compares the results of a-priori assumptions of heterogeneity and post hoc segmentation using latent class analysis. Treiblmaier & Dickinger (2006) take a different perspective by suggesting that relationships may not be linear. Departing from only investigating a model at an aggregate level we gain a deeper understanding of consumer behavior.

Selected Theses Supervised
1. Maria Razumova (external reviewer) Essays on Environmental Regulation, Environmental Innovation and Competitiveness in the Hotel Industry, 2010

2. Clemens Költringer, Evaluating Online Representation Measurement: Leveraging Online Media for Market Research, In progress