Christian Buchta

Making friends and communicating on Facebook: Implications for the access to social capital

Abstract In this paper, we explore the dynamics of access to social capital on Facebook. Existing approaches to network-based social capital measures are adapted to the case of Facebook and applied to the friendship and communication data of 438,851 users. These measures are correlated to user data in order to identify advantageous behavior for optimizing the possible access to social capital. We find that the access to social capital on Facebook is primarily based on a reasonable amount of active communication. Exaggerated friending and posting behavior can deteriorate the access to social capital. Furthermore, we investigate which kinds of posts are most advantageous as well as questions of homophily based on social capital.

A nonparametric approach to perceptions-based market segmentation : applications

How tourists perceive city destinations - a case for perceptions-based market segmentation and competition analysis (S. Dolnicar): The need for strategic marketing research Data Answer pattern compression Perceptual competition analysis Concentration analysis Segment formation Conclusions.- Segmentation and positioning analysis of competitive retail markets based on binary store image and preference data (C. Buchta, T. Reutterer): Introduction A stepwise segmentation procedure Standard market research data Compression of perceptual profiles Characterizing perceptual classes Formation of market segments Target marketing strategies Discussion.

Selective association rule generation

Mining association rules is a popular and well researched method for discovering interesting relations between variables in large databases. A practical problem is that at medium to low support values often a large number of frequent itemsets and an even larger number of association rules are found in a database. A widely used approach is to gradually increase minimum support and minimum confidence or to filter the found rules using increasingly strict constraints on additional measures of interestingness until the set of rules found is reduced to a manageable size. In this paper we describe a different approach which is based on the idea to first define a set of “interesting” itemsets (e.g., by a mixture of mining and expert knowledge) and then, in a second step to selectively generate rules for only these itemsets. The main advantage of this approach over increasing thresholds or filtering rules is that the number of rules found is significantly reduced while at the same time it is not necessary to increase the support and confidence thresholds which might lead to missing important information in the database.

Technological Efficiency and Organizational Inertia: A Model of the Emergence of Disruption

We study the influence of technological efficiency and organizational inertia on the emergence of competition when firms decide myopically. Using a multi-agent computer simulation model, we observe the competitive reaction of a former monopolist to the advent of a new competitor. While the entrant uses a new technology, the monopolist is free either to stick to his former technology or to switch to the new one. We find that—irrespective of details regarding the demand side—a change of industry leadership occurs only if the new (“disruptive”) technology is not too efficient and organizations are inert.

Learning by Simulation -Computer Simulations for Strategic Marketing Decision Support in Tourism

Abstract This paper describes the use of corporate decision and strategy simulations as a decision-support instrument under varying market conditions in the tourism industry. It goes on to illustrate this use of simulations with an experiment which investigates how successful different market segmentation approaches are in destination management. The experiment assumes a competitive environment and various cycle-length conditions with regard to budget and strategic planning. Computer simulations prove to be a useful management tool, allowing customized experiments which provide insight into the functioning of the market and therefore represent an interesting tool for managerial decision support. The main drawback is the initial setup of a customized computer simulation, which is time-consuming and involves defining parameters with great care in order to represent the actual market environment and to avoid excessive complexity in testing cause-effect-relationships.

Measuring the resemblance between pictorial and verbal city image spaces

Purpose – This study focuses on the emotional aspects of destinations and employs two different scales for capturing the affective component of city destination image. The aim of this paper is not only to measure the emotions assigned to different European cities, but also to compare these two instruments/scales by means of Procrustes analysis.Design/methodology/approach – The authors collected measurements on two different scales (verbal and pictorial) for capturing the emotional (affective) component of destination image – both based on Russells circumplex model of affect – in two independent surveys.Findings – Significant differences were found between the multidimensional scaling (MDS) results of both scales. Because the two samples match in terms of demographics and psychographics, the differences of the perceptual spaces are likely due to the form of stimuli (pictures compared to verbal items) presented. The results indicate that pictures are easy to use, but they also are subject to broader interp...

Improving the Probabilistic Modeling of Market Basket Data

Current approaches to market basket simulation neglect the fact that empty transactions are typically not recorded and therefore should not occur in simulated data. This paper suggest how the simulation framework without associations can be extended to avoid empty transactions and explores the possible consequences for several measures of interestingness used in association rule filtering.

A Guest Mix Approach to Analysing City Tourism Competition

Chapter 8 builds on previous results published in the first edition of this reader. Section 4.1, Part IV, of the first edition presented ‘A guest mix approach’ to assessing and visualising the competitive relationships among 16 European tourist cities as reflected in the guests’ distribution by nationalities. If two cities A and B exhibit very similar proportions of their guest nationalities it is likely that the CTO managers of A pay the same attention to each of these guest nations as the managers of B. In other words, the analysis rests on the assumption that the CTOs base their marketing effort on a geographical segmentation approach. This does not seem to be a severe restriction as it corresponds to customary strategy guidelines followed by many tourist organisations.

The Defense of Disruptive Technologies

We present an extension to an existing work that investigates conditions for “disruptive technologies” to cause the failure of a former monopolist (incumbent) to the advent of new firm (entrant). This paper shows that 1. the forecast of the positions of the entrant technology allows the incumbent to detect threatening entrant technologies, and 2. cloning the entrant firm allows the incumbent to participate in the new market and assures the survival of the incumbent firm group.

Disruptive Technologies: the Threat and its Defense

Based on extensive long-term studies of the disk drive and other industries, Christensen (1997) introduced the concept of “disruptive technology”. According to Christensen, initially such a technology is employed in a novel market segment, and, when judged according to the features most relevant to the incumbents’ current customers, is inferior to the technology used by the incumbents in the established market segment. Nevertheless, over time the firms using the disruptive technology are able to successfully invade the established market segment from the lower end of the market and industry leadership changes. Christensen’s finding provides empirical support to the resource-based and organizational learning perspective of the theory of the firm, whereas other approaches in general predict advantages for incumbents due to learning by doing, economies of scale and scope, network economies of scale, etc. (see, e.g., Klepper and Simons, 1997; Rumelt, 1981; Mas-Colell et al., 1995). Table 1 provides an example of a disruptive technology: 5.25 inch disk drives were used in the early eighties’ desktop computers and, initially, were inferior to the 8 inch drives used in minicomputers in terms of capacity, access time and cost/MB – the features most relevant to a minicomputer user. However, by 1986 industry leadership changed from CDC, the leading 8 inch vendor, to the new entrant Seagate, and most of the firms that were producing 8 inch drives vanished (see Christensen, 1993, p. 543). Christensen also demonstrates that it is the incumbents who are leading in “sustaining technologies”, i.e. innovations that follow the current trajectory of technological improvement, and are trying to find new technical solutions to tackle the flattening of the current technology’s S-curve. Thus, technological (in)competency cannot explain the failure of industry leaders, but this is rather done by factors rooted in the way new