Optimal Goodwill Model with Consumer Recommendations and Market Segmentation

We propose a new dynamic model of product goodwill where a product is sold in many market segments, and where the segments are indicated by the usage experience of consumers. The dynamics of product goodwill is described by a partial di erential equation of the Lotka{Sharpe{ McKendrick type. The main novelty of this model is that the product goodwill in a segment of new consumers depends not only on advertising e ort, but also on consumer recommendations, for which we introduce a mathematical representation. We consider an optimal goodwill model where in each market segment the control variable is the company's advertising e orts in order to maximize its pro ts. Using the maximum principle, we numerically nd the optimal advertising strategies and corresponding optimal goodwill paths. The sensitivity of these solutions is analysed. We identify two types of optimal advertising campaign: `strengthening' and `supportive'. They may assume di erent shapes and levels depending on the market segment. These experiments highlight the need for both researchers and managers to consider a segmented advertising polic

Public Disclosure Programs vs. Traditional Approaches for Environmental Regulation: Green Goodwill and the Policies of the Firm

A Public Disclosure Program (PDP) is compared to a traditional environmental regulation (exemplified by a tax/subsidy) in a simple dynamic framework. A PDP aims at revealing the environmental record of firms to the public. This information affects its image (goodwill or brand equity), and ultimately its profit. In our model, this impact is endogenous, i.e., a firm polluting less than its prescribed target would win consumer's sympathy and raises its goodwill, whereas it is the other way around when the firm exceeds its emissions quota. The evolution of this goodwill is assumed to depend also on green activities or advertising expenditures. Within this framework, we analyse how a PDP affects the firm's optimal policies regarding emissions, pricing and advertising as compared to a traditional regulation. We show that advertising acts as a complementary device to pricing and that emissions are increasing in goodwill. We also conclude that the effects of a PDP are more pronounced than those of traditional instruments for firms with a high goodwill. Moreover, we study under which conditions a PDP may be profit improving and we connect this issue to the possibility that a PDP can induce firms to overcomply with the standard. The numerical value of the emission target is rather innocuous in a market-based setting but it turns to be a crucial variable in the presence of a PDP. The theoretical results are complemented with a numerical illustration.Market-based Environmental Regulation, Public Disclosure Program, Pricing, Advertising, Goodwill, Optimal Control.

Learning Adaptive Display Exposure for Real-Time Advertising

In E-commerce advertising, where product recommendations and product ads are presented to users simultaneously, the traditional setting is to display ads at fixed positions. However, under such a setting, the advertising system loses the flexibility to control the number and positions of ads, resulting in sub-optimal platform revenue and user experience. Consequently, major e-commerce platforms (e.g., Taobao.com) have begun to consider more flexible ways to display ads. In this paper, we investigate the problem of advertising with adaptive exposure: can we dynamically determine the number and positions of ads for each user visit under certain business constraints so that the platform revenue can be increased? More specifically, we consider two types of constraints: request-level constraint ensures user experience for each user visit, and platform-level constraint controls the overall platform monetization rate. We model this problem as a Constrained Markov Decision Process with per-state constraint (psCMDP) and propose a constrained two-level reinforcement learning approach to decompose the original problem into two relatively independent sub-problems. To accelerate policy learning, we also devise a constrained hindsight experience replay mechanism. Experimental evaluations on industry-scale real-world datasets demonstrate the merits of our approach in both obtaining higher revenue under the constraints and the effectiveness of the constrained hindsight experience replay mechanism.Comment: accepted by CIKM201

Pulsed Generic Advertising: The Case of Common Property

Regulation of fisheries production together with public promotion of fisheries products offer a potentially profitable environment for fishermen. Yet production restrictions are usually insufficient to prevent entry, causing depletion of the resource base and dissipation of long-run profits from promotion. Shorter run gains may be possible, providing producer response to advertising is not instantaneous. Lagged biological and economic responses appear to provide a rationale for pulsed advertising. Moreover, a pulsed advertising policy is shown to mitigate the adverse effects on the resource base which would normally accompany expansion of consumption without direct production control.generic promotion, oysters, common property, pulsed advertising, Environmental Economics and Policy, Resource /Energy Economics and Policy,

Optimizing Your Online-Advertisement Asynchronously

We consider the problem of designing optimal online-ad investment strategies for a single advertiser, who invests at multiple sponsored search sites simultaneously, with the objective of maximizing his average revenue subject to the advertising budget constraint. A greedy online investment scheme is developed to achieve an average revenue that can be pushed to within $O(\epsilon)$ of the optimal, for any $\epsilon>0$, with a tradeoff that the temporal budget violation is $O(1/\epsilon)$. Different from many existing algorithms, our scheme allows the advertiser to \emph{asynchronously} update his investments on each search engine site, hence applies to systems where the timescales of action update intervals are heterogeneous for different sites. We also quantify the impact of inaccurate estimation of the system dynamics and show that the algorithm is robust against imperfect system knowledge

Licensing radical product innovations to speed up the diffusion

Inventors can commercialize innovative products by themselves and simultaneously license the technology to other firms. The licensee may cannibalize sales of the licensor, but this can be compensated by gains from royalties. We show in this paper how licenses can be used strategically to speed up the new product diffusion process in two instances of markets: (i) a market with strong Intellectual Property Rights (IPR), and (ii) a market with weak IPR holder and pirate rivals. The main findings suggest that licensing is a beneficial strategy for a licensor in the context of strong IPR, because licensor benefits from the royalties, the advertising investment and positive word-of-mouth effects by licensees. We compare this result with a weak IPR context, where piracy speeds up the product diffusion but this does not compensate IPR holder for the sales loss effect who is willing to license to get some royalties. However, pirates do not generally find interesting the licensing agreement. We present a comparative statics analysis based on numerical simulation.Product diffusion models, Licensing, Optimal control and differential games

Strategic Interaction With Multiple Tools: A New Empirical Model

The Lanchester model of strategic interaction typically considers only two-firm rivalry and one strategic tool. This paper presents an alternative that considers rivalry among several firms using multiple tools. Marketing decisions are dynamically optimal and use equations of motion for market share that are consistent with optimal consumer choice. Using a single-market case study that consists of five years of monthly data on ready to eat cereal sales, advertising, product development investments and new product introductions, we test our model against a similar Lanchester specification. Non-nested specification tests fail to reject the proposed model, but reject the Lanchester alternative.advertising, brands, cereal, dynamic, Lanchester, oligopoly, strategic interaction., Marketing,