Andreas Dypvik Landmark

Tracking customer behaviour in fashion retail using RFID

The purpose of this paper is to explore how tracking of products by the use of radio frequency identification (RFID) technology may describe customer behaviour in real-time.,The study was conducted as a field experiment, where a commercially available RFID platform was deployed in the fitting rooms of a fashion retail store.,The study demonstrates an application of in-store RFID tracking to describe customer behaviour, and some practical challenges of utilising such technology. An example typology of four fitting room traits was constructed based on the data collected.,Different customer types most likely require and respond differently to attention from the personnel operating the fitting room area. By identifying customer behaviour in real-time, it is possible to deliver “best practice” shop stewardship and create a more personalised retail experience.,The study is based on real-life retail settings, rather than anecdotal management observations or economic and demographic indicators. To the best of the authors’ knowledge, few contributions combine RFID and consumer behaviour outside conceptual work or laboratory experiments.

Use of mobile phone data for analysis of number of train travellers

Abstract Several studies have pointed to the difficulties of obtaining good data on train ridership. There are at least two challenges regarding these data. First, train operators consider such data confidential business information, especially in high resolution. Second, the data that actually are available vary in quality and coverage. This paper studies mobile phone data as an alternative measure to obtain data about train ridership. Handset counts were obtained from one telecom operator for selected mobile phone base stations and compared with timetable data and APC. The selected base stations are located so that it is likely that a large share of the mobile phone traffic is generated by train passengers. The number of units connected to a base station is found to correspond relatively well with the trains that pass close to the base stations. A ratio between the handset count and APC data appear as promising in utilizing handset count to calculate train ridership, with ratios around one in the rush hours. We discuss preliminary results as well as methodological and technical challenges. To make sure that we do not violate privacy concerns, the data used in the study have been approved by personal privacy representatives.

The Adaptive Fitting Room

In order to remain attractive and economically viable whilst supplementing online presence, physical stores need to play to their strengths and engage customers in novel ways. Stores have the possibility to act as experimental arenas, where customers can browse apparel through interactive installations and try on products in semi-realistic situations. For fashion retailers, however, the average fitting room experience is rarely representative of actual use. The product range is often diverse and varies with seasons, which makes it difficult to create a one-experience-fits-all fitting room. In this paper, we present a concept for a new customer experience. By exploiting automatic single item identification using RFID, we propose a fitting room that adapts to the products that enter the fitting room, using video projection mapping, magic mirrors and screens, lighting and sound. This allows different types of customer engagement prior to the point of purchase, opening up new possibilities for integrating product information, recommendations, clienteling and social media. Some expected benefits are illustrated through a set of user scenarios.

Managing Cost and Time in a Large Portfolio of Projects

Abstract If your business has a fixed yearly investment budget and you know that it is likely that your 300 projects will be delayed during the year, what is your strategy to meet your budget? This is a descriptive study on portfolio management across a multi-billion dollar business with more than 300 projects from a large Norwegian public entity. We have analyzed data over a five-year period (2008-2012). The data shows reoccurring delay trends year after year, trends which can be interpreted and used as information for governing the portfolio. The milestone delay curves from year to year are fascinatingly similar. Are these curves simply macro indicators of the phenomenon “planning fallacy” or are they the symptom of something more profound? We discuss the behaviouristics of this portfolio and the strategies used to be on budget despite delays. The dataare unique, but the problems global.