Trust Building in Electronic Markets: Relative Importance and Interaction Effects of Trust Building Mechanisms

We examine the relative and complementary effectiveness of trust-building strategies in online environments. While prior research has examined various antecedents to trust, we investigated two trust-building mechanisms more in depth: Web site trust and vendor reputation. We tried to understand the relative effectiveness of these two important mechanisms to provide online businesses with a clear recommendation of how to establish trust in an effective and efficient manner. Drawing from the literature on trust, we proposed vendor reputation to be more effective than Web site trust. Moreover, we examined a potential complementary effect of these mechanisms so as to provide online businesses with a deeper understanding of how to derive superior trust. We hypothesize a small such effect. The study proposes a laboratory experiment to test the model

Multiple Category Decision Making: Review and Synthesis

In many purchase environments, consumers use information from a number of product categories prior to making a decision. These purchase situations create dependencies in choice outcomes across categories. As such, these decision problems cannot be easily modeled using the single-category, single-choice paradigm commonly used by researchers in marketing. We outline a conceptual framework for categorization, and then discuss three types of cross-category dependence: cross-category consideration cross-category learning, and product bundling. We argue that the key to modeling choice dependence across categories is knowledge of the goals driving consumer behavior

Approximating the Revenue Maximization Problem with Sharp Demands

Abstract. We consider the revenue maximization problem with sharp multi-demand, in which m indivisible items have to be sold to n potential buyers. Each buyer i is interested in getting exactly di items, and each item j gives a benefit vij to buyer i. We distinguish between unrelated and related valuations. In the former case, the benefit vij is completely arbitrary, while, in the latter, each item j has a quality qj, each buyer i has a value vi and the benefit vij is defined as the product viqj. The problem asks to determine a price for each item and an allocation of bundles of items to buyers with the aim of maximizing the total revenue, that is, the sum of the prices of all the sold items. The allocation must be envy-free, that is, each buyer must be happy with her assigned bundle and cannot improve her utility. We first prove that, for related valuations, the problem cannot be approximated to a factor O(m 1−ɛ), for any ɛ> 0, unless P = NP and that such result is asymptotically tight. In fact we provide a simple m-approximation algorithm even for unrelated valuations. We then focus on an interesting subclass of ”proper ” instances, that do not contain buyers a priori known not being able to receive any item. For such instances, we design an interesting 2-approximation algorithm and show that no (2 − ɛ)-approximation is possible for any 0 < ɛ ≤ 1, unless P = NP. We observe that it is possible to efficiently check if an instance is proper, and if discarding useless buyers is allowed, an instance can be made proper in polynomial time, without worsening the value of its optimal solution.