Julia Neidhardt

Future research issues in IT and tourism

The objective of this manifesto (as a result of the JITT workshop in June 2014) is to identify a list of pivotal research topics and issues in e-tourism. E-tourism can be seen as everything that happens electronically in the travel and tourism industry/experience; more formally it is defined as the design, implementation and application of IT and ecommerce solutions in the travel and tourism industry as well as the analysis of the impact of the respective technical and economic processes and market structures on all the involved actors and especially on the traveller’s experience. In tourism as an “information business”, Information Technology has always played an important role since the 1960s with the computerized reservation systems/global distribution systems; these were one of the first world-wide electronic networks. And since the beginning of the Web in the early 1990s, travel and tourism was and is a major application domain for Web-based services. As such, the domain is also a major driver of technological innovation. This manifesto provides guidelines on strategic research issues for the research community, but as such it is also conceived as a basis document for industry and policy makers.

On Successful Team Formation: Statistical Analysis of a Multiplayer Online Game

Teamwork plays an important role in many areas of todays society, such as business activities. Thus, the question of how to form an effective team is of increasing interest. In this paper we use the team-oriented multiplayer online game Dota 2 to study cooperation within teams and the success of teams. Making use of game log data, we choose a statistical approach to identify factors that increase the chance of a team to win. The factors that we analyze are related to the roles that players can take within the game, the experiences of the players and friendship ties within a team. Our results show that such data can be used to infer social behavior patterns.

Ranking factors of team success

As an increasing number of human activities are moving to the Web, more and more teams are predominantly virtual. Therefore, formation and success of virtual teams is an important issue in a wide range of fields. In this paper we model social behavior patterns of team work using data from virtual communities. In particular, we use data about the Web community of the multiplayer online game Dota 2 to study cooperation within teams. By applying statistical analysis we investigate how and to which extent different factors of the team in the game, such as role distribution, experience, number of friends and national diversity, have an influence on the teams success. In order to complete the picture we also rank the factors according to their influence. The results of our study imply that cooperation within the team is better than competition.

A picture-based approach to recommender systems

AbstractDue to their complexity, tourism products present major challenges to recommender techniques. Especially the assessment of customer preferences in order to get accurate user profiles is a non-trivial task for several reasons: (a) tourism is an “emotional” experience, which is typically hard to capture by using rational terms; (b) particularly in early phases of a travel decision process, users are not able to explicitly express their preferences; (c) and they are often lacking domain knowledge and thus have difficulties to use the right terminology. In this paper we introduce an alternative, i.e., a picture-based approach, as a new method to implicitly elicit user preferences for tourism products. We develop a model in which a user’s travel profile is composed of seven basic factors. The scores of these factors are determined by asking the user to select a number of pictures that are appealing to him or her. The model as well as its implementation into a recommender system are described in detail. First evaluations show that interactions with the system are perceived as inspiring and enjoyable.

Observing Group Decision Making Processes

Most research on group recommender systems relies on the assumption that individuals have conflicting preferences; in order to generate group recommendations the system should identify a fair way of aggregating these preferences. Both empirical studies and theoretical frameworks have tried to identify the most effective preference aggregation techniques without coming to definite conclusions. In this paper, we propose to approach group recommendation from the group dynamics perspective and analyze the group decision making process for a particular task (in the travel domain). We observe several individual and group properties and correlate them to choice satisfaction. Supported by these initial results we therefore advocate for the development of new group recommendation techniques that consider group dynamics and support the full group decision making process.

Eliciting the users' unknown preferences

Personalized recommendation strongly relies on an accurate model to capture user preferences; eliciting this information is, in general, a hard problem. In the field of tourism this initial profiling becomes even more challenging. It has been shown that particularly in the beginning of the travel decision making process, users themselves are often not conscious of their needs and are not able to express them. In this paper, the basics of a picture-based approach are introduced that aims at revealing implicitly given user preferences. Based on a set of travel related pictures selected by a user, an individual travel profile is deduced. This is accomplished by mapping those pictures onto seven basic factors that reflect different travel behavioral aspects. Also tourism products can be represented by this seven factor model. Thus, this model constitutes the basis of our recommendation algorithm. First tests show that this non-verbal way of interaction is experienced as exiting and inspiring.

Destinations and the web: a network analysis view.

network analysis methods have gained much attention in the last few years and have provided a wealth of insights into the structural and dynamic properties of many systems. here, we apply these methods to the study of tourism destinations’ Web spaces. this exploratory analysis aims at showing how these techniques can be used and what outcomes can be obtained. After a short introduction to network analysis and a brief review of the literature, two cases are presented, namely Austria as a whole country, and a smaller destination within Italy: the island of elba. for each case, data collection methods are described and the characteristic network parameters are calculated. the comparison between the two cases highlights both similarities and differences, which are described and interpreted. finally, the limitations of this approach are discussed.

Inter-organizational success factors: a cause and effect model

Inter-organizational systems form the basis for successful business collaboration in the Internet and B2B e-commerce era. To properly design and manage such systems one needs to understand the structure and dynamics of the relationships between organizations. The evaluation of such inter-organizational relationships (IORs) is normally conducted using “success factors”. These are often referred to as constructs, such as trust and information sharing. In strategic management and performance analysis, different methods are employed for evaluating business performance and strategies, such as the Balanced Scorecard (BSC) method. The BSC utilizes success factors for measuring and monitoring IORs against business strategies. For these reasons, a thorough understanding of success factors, the relationships between them, as well as their relationship to business strategies is required. In other words, understanding success factors allows strategists deriving measurements for success factors as well as aligning these success factors with business strategies. This underpins nowadays close relationship between business strategy, IORs and their realization by means of inter-organizational systems. In this paper, we present (1) a systematic literature review studying success factors and their impact on IORs as well as (2) an analysis of the results found. The review is based on 177 publications, published between 2000 and 2012, dealing with factors influencing IORs. The work presented provides an overview on success factors, influencing relationships between success factors, as well as their influence on the success of IORs. The work is somehow “meta-empirical” as it only looks at published studies and not on own cases. Consequently, it is based on the assumption that studies in scientific literature represent the real-world. The constructs and relationships found in the review are grouped based on their scope and summarized in a cause and effect model. The grouping of constructs results in five groups including Relationship Orientation, Relational Norm, Relational Capital, Atmosphere, and Others. Since the cause and effect model represents a directed graph, different network analysis methods may be applied for analyzing the model. In particular, an in- and out-degree analysis is applied on the cause and effect model for detecting the most influencing as well as the most influenced success factors.

RecTour 2016: Workshop on Recommenders in Tourism

In this paper, we summarize RecTour 2016 -- a workshop on recommenders in tourism co-located with RecSys 2016. There was a great variety of submissions, i.e., research papers, demo papers and position papers, addressing fundamental challenges of recommender systems in the tourism domain. The main topics included group recommendations, context-aware recommenders, choice-based recommenders and event recommendations.

Researching Individual Satisfaction with Group Decisions in Tourism: Experimental Evidence

The goal of the present study was to investigate how satisfied individuals are with the final outcome of a group decision-making process on a joint travel destination. Using an experimental paradigm (N total = 200, N groups = 55) it was obvious to hypothesize that individuals would especially be satisfied with the final group decision when it matched their own initial travel preference and that they would be dissatisfied in case it mismatched their initial preference. However, in addition the influence of personality and group dynamics differences (Thomas-Kilmann Conflict Mode Instrument, Five Factor Model) as well as travel types of the individual decision maker on the satisfaction level with the group decision outcome as the dependent variable were further researched. The paper concludes with implications for e-tourism, especially with regards to the development of interactive tools for group travel.