Jaap Boter

The Effect of Product Type on Consumer Preferences for Website Content Elements: An Empirical Study

This study attempts to demonstrate empirically how the importance of website content in online purchasing varies across 2 product categorizations: goods versus services and hedonic versus utilitarian products. We conducted an experiment that showed that when purchasing services, customers value evaluative elements and risk-reducing content, while consumers buying goods may be satisfied with fewer features. In addition, selling hedonic products could be more effective when focusing on large and unique assortment. Websites selling utilitarian products, on the other hand, may profit from investing in instrumental website content. The study validates the guiding role of product type in website design, and suggests that incorporating product tactics into design likely contributes to the development of websites tailored to specific consumer groups.

Assessing the Value of Museums with a Combined Discrete Choice / Count Data Model

This article assesses the value of Dutch museums using information about destination choice as well as about the number of trips undertaken by an actor. Destination choice is analysed by means of a mixed logit model, and a count data model is used to explain trip generation. We use a utility-consistent framework in which the discrete choice model for destination choice is linked to an indirect utility function. The results are used to compute the compensating variation of particular museums and of the total group of museums in the sample.

On Spatial Differences in the Attractiveness of Dutch Museums

Museums may serve as important amenities for inhabitants and act as magnets for attracting visitors to a city. For city planners it is important to understand what different types of museums there are in terms of attraction power, and how their attractiveness may depend on the presence of other museums. To this end, we propose a gravity model for all museums allowing for spatial dependence between museums to account for local competition or synergy effects. To address the likely heterogeneity in our sample of museums, we first adopt a spatial error component model. Thereafter, we model the variation between museums explicitly by segmenting the museums using a finite mixture approach. The application of this model uses a unique transaction database of the visiting behaviour of 80 821 persons to 108 Dutch museums. The results stress the large variation both in the spatial reach of museums and in their spatial context.

Time-restricted batching models and solution approaches for integrated forward and return product flow handling in warehouses

With the rise of Internet sales, retailers witness increases in returned products, generally because website pictures and specifications tend to be insufficient for customers to determine the right size, colour or suitability of a product. Efficient processing of the return flow can improve inventory management and increase the utilisation of warehouse capacities. Moreover, short response times to customer orders and on-time delivery are critical and shape warehouse operations. To address the problem of integrated order and return job batching, this article proposes two optimisation models with constraints on the delivery time. We propose different objectives in offline and online contexts which require unique solution approaches. Time constraints also need to be taken into account to exploit the different characteristics of order and return jobs, as well as to incorporate response time-oriented objectives. Computational examples confirm the effectiveness of included returns and the impact of consumer-oriented objectives. Finally, a comparison of the proposed solution approaches with batching procedures used by a library warehouse indicates significant savings in travel distance through integrated order and return job processing.

Risk control for staff planning in e-commerce warehouses

Internet sale supply chains often need to fulfil quickly small orders for many customers. The resulting high demand and planning uncertainties pose new challenges for e-commerce warehouse operations. Here, we develop a decision support tool to assist managers in selecting appropriate risk policies and making staff planning decisions in uncertain conditions. Multistage stochastic modelling has been used to analyse risk optimisation approaches and expected value-based optimisation. Exhaustive numerical and practical validations have been performed to test the tool’s applicability. We demonstrate, using a Dutch e-commerce warehouse, that the multi-period conditional value at risk appears to be most applicable.

Trade-offs in managing commercial consumer returns for online apparel retail

Purpose – The purpose of this paper is to investigate how online apparel retailers make trade-offs in achieving efficiency in handling consumer returns, attempting to reduce the number of consumer returns they are faced with and increasing sales through returns management. Design/methodology/approach – The authors use literature to develop propositions and employed a case study research design to understand how online apparel retailers make trade-offs in returns management practices in order to verify the propositions. Case study subjects have been anonimized. Findings – The authors have developed and verified five propositions with the aim to understand how retailers make trade-offs in reducing the number of online consumer returns, increasing the effectiveness of handling online consumer returns and increasing sales through returns management. Research limitations/implications – The research is limited by the use of interview data from cases, a focus on apparel retail only and by the use of companies lo...

Sales Forecasting as a Service

Data analysts are increasingly important for companies to extract critical information from their vast amount of data in order to be competitive. Data analytics specialists or data scientists develop statistical models and make use of dedicated software components for example to categorize products and forecast future sales. Their unique skill set is among the most sought after in the current job market. Cloud computing on the other hand helps companies to acquire services in the cloud and share the required expertise for delivery among service users. In this paper we take a cross disciplinary approach to develop a data analytics technique and a platform based IT architecture that allows to outsource sales forecasting analytics into the cloud.