Andreas Mild

An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data

Retail managers have been interested in learning about cross-category purchase behavior of their customers for a fairly long time. More recently, the task of inferring cross-category relationship patterns among retail assortments is gaining attraction due to its promotional potential within recommender systems used in online environments. Collaborative filtering algorithms are frequently used in such settings for the prediction of choices, preferences and/or ratings of online users. This paper investigates the suitability of such methods for situations when only binary pick-any customer information (i.e., choice/nonchoice of items, such as shopping basket data) is available. We present an extension of collaborative filtering algorithms for such data situations and apply it to a real-world retail transaction dataset. The new method is benchmarked against more conventional algorithms and can be shown to deliver superior results in terms of predictive accuracy. (authors abstract)

Open innovation modes and the role of internal R&D: An empirical study on open innovation adoption in Europe

Purpose – The purpose of this paper is to investigate how and how much open innovation is used across Europe. The goal of this study is therefore to provide comprehensive empirical evidence for the adoption of inbound and outbound open innovation activities in Europe.Design/methodology/approach – Data from 180 European companies were used to test three hypotheses on open innovation adoption and the role of internal R&D. Data were collected in 2009 and the sample comprises companies from different industries and 24 European countries.Findings – It is found that 30.3 per cent of European companies are very open to innovation and 38.7 per cent are semi‐open. The results show that inbound open innovation is more commonly used than outbound open innovation, which can be explained by insufficiencies of the market or the organization. Finally, it is found that the type of innovation strategy (vertically integrated, inbound, outbound, or mixed) is related to the R&D intensity.Originality/value – This paper provid...

Collaborative Filtering Methods for Binary Market Basket Data Analysis

Retail managers have been interested in learning about cross-category purchase behavior of their customers for a fairly long time. More recently, the task of inferring cross-category relationship patterns among retail assortments is gaining attraction due to its promotional potential within recommender systems used in online environments. Collaborative Filtering algorithms are frequently used in such settings for the prediction of choices, preferences and/or ratings of online users. The fundamental assumption of such algorithms resides in the available similarity information between a specific active user and a database of all other users. We study the effects of different similarity measures, available data points per user and the number of items to be recommended on the relative predictive performance in an experiment using market basket data collected from a grocery retailer. Using various measures for evaluation of the predictive ability, we derive some clues to the proper parameterization of such systems.

A hedonic wage model‐based methodology for evaluating the benefits of IT investments in public‐sector organisations

The economic justification of investments in information technology (IT) is a basic issue for IT management in private and in public‐sector organisations. Usually, the expenses made for any investment are compared to the cost saved. While the costs for implementing a new system are uncertain, only a small percentage of the benefits accrues as cost savings given the type of IT systems used today and the particularities of the public‐sector. In this paper, we present a methodology for the monetary quantification of the benefits resulting from the introduction of a modern IT application and demonstrate its use on the basis of a case of prison administration.

Bundling decisions in supply chains

Firms often sell products in bundles to extract consumer surplus. While most bundling decisions studied in the literature are geared to integrated firms, we examine a decentralized supply chain where the suppliers retain decision rights. Using a generic distribution of customers’ reservation price we establish equilibrium solutions for three different bundling scenarios in a supply chain, and generate interesting insights for distributions with specific forms. We find that (i) in supply chain bundling the retailer’s margin equals the margin of each independent supplier, and it equals the combined margin when the suppliers are in a coalition, (ii) when the suppliers form a coalition to bundle their products the bundling gain in the supply chain is higher and retail price is lower than when the retailer bundles the products, (iii) the supply chain has more to gain from bundling relative to an integrated firm, (iv) the first-best supply chain bundling remains viable over a larger set of parameter values than those in the case of the integrated firm, (v) supplier led bundling is preferable to separate sales over a wider range of parameter values than if the retailer led the bundling, and (vi) if the reservation prices are uniformly distributed bundling can be profitable when the variable costs are low and valuations of the products are not significantly different from one another. For normally distributed reservation prices, we show that the bundling set is larger and the bundling gain is higher than that for a uniform distribution.

Determinants of open innovation: an empirical study on organisational, market, and human drivers of open innovation adoption across Europe

Existing literature on open innovation shows the evolving diffusion of open innovation in certain industries and contexts. Also various case studies and theoretical work suggest that the open innovation adoption decision could be triggered by internal and external factors. The current study provides empirical evidence for a set of open innovation drivers. We use data from 180 European firms to link the adoption of open innovation with organisational capabilities, characteristics of the market environment, and human capabilities. The results indicate that open innovation adoption is strongly dependent on the level of technology and the level of hostility in an industry. We also find that organisational variables like the strategic breadth and human capabilities have significant influence on the adoption of open innovation strategies.

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.

Dynamic Pricing Support Systems for DIY Retailers – a Case Study from Austria

Abstract Merchandise managers have long dreamt of automated dynamic systems to help them make well-informed pricing decisions. However, such systems have proved as elusive as the Holy Grail - until now, that is. The story of an Austrian DIY retailer shows often undetected opportunities to use valuable information, hidden in retailers’ data warehouses, on consumer reactions to previous price changes in order to make automatic pricing and promotion decisions.

Ein sortimentsübergreifendes Entscheidungsunterstützungssystem für dynamische Preis- und Werbeplanung im DIY-Handel

Wir beschreiben ein Entscheidungsunterstutzungssystem zur dynamischen Preisund Werbeplanung. Das auf Wochendaten basierende Nachfragemodell berucksichtigt Preise, Referenzpreise, Saisonalitat, Artikelverfugbarkeit, Flugblatter und Rabatte. Wir quantifizieren Verbundeffekte und integrieren die daraus abgeleitete Gewinnsteigerung in das Preisoptimierungsmodell. Das Modell wurde bei einem osterreichischen Baumarkt entwickelt und implementiert. Aufgrund der praktischen Anforderungen wurde eine Zielfunktion verwendet, die die Strategie des Handelsunternehmens berucksichtigt. Acht Preisrunden mit Tausenden unterschiedlichen Artikeln wurden zur Evaluierung herangezogen. Unter Anwendung unterschiedlicher Vergleichswerte kann ein positiver Einfluss auf den Gewinn gezeigt werden. Das derzeit implementierte System steigerte den Bruttogewinn um durchschnittlich 8,1%, den Umsatz um 2,1%.

DELI: an interactive new product development and targeting tool

In this contribution, we present, DELI, a new interactive tool for supporting new product development decisions. In contrast to existing market research methodologies such as conjoint analysis, our approach is able to cope with a large number of potential product features and levels. Its main advantages lie in the integration of segmentation, visualization of competitive structures, the segment specific identification of new product functionality and several interactive features which support the search for new products. Furthermore, we introduce a novel conditional segmentation, mapping and positioning approach for an improved representation of products and customers within one map, supporting interpretation and segment specific new product development. An individual level scoring model supports the evaluation of new products.