Interactive ads recommendation with contextual search on product topic space

The rapid popularization of various online media services have attracted large amounts of consumers and shown us a large potential market of video advertising. In this paper, we propose interactive service recommendation based on ad concept hierarchy and contextual search. Instead of traditional ODP (Open Directory Project) based approach, we built a ad domain based concept hierarchy to make the most of the product details over the e-commerce sites. Firstly, we capture the summarization images related to the advertising product in the video content and search visually similar product images from the built product image database. Then, we aggregate the visual tags and textual tags with K-line clustering. Finally, we map them to the product concept space and make keywords suggestion, and users can interactively select keyframes or keywords to personalize their intentions by textual re-search. Experiments and comparison show that the system can accurately provide effective advertising suggestions.     

Manufacturer defensive and offensive advertising in competing distribution channels

This paper investigates how two competing manufacturers should invest in defensive and offensive advertising in a two‐segment market and whether they should each adopt a decentralized or an integrated channel if their goal is to maximize total channel profits. We find that manufacturers in decentralized channels can exclusively undertake either of the two types of advertising or combine the two at the equilibrium. In integrated channels, they can either combine the two or exclusively undertake defensive advertising. When multiple equilibria exist, strategies that combine both types of advertising should be preferred to exclusive defensive advertising strategies, which are better than exclusive offensive advertising strategies. Also, total channel profits are higher in decentralized channels than in integrated channels when the brands are moderately or highly substitutable. Conversely, total channel profits of integrated channels are higher than those of decentralized channels in areas where the brands are relatively differentiated and the offensive advertising retaliatory capacity of the rival is stronger. Theoretical and managerial implications of these findings are discussed.     

Inferring contextual preferences using deep encoder-decoder learners

ABSTRACT

Context-aware systems enable the sensing and analysis of user context in order to provide personalised services. Our study is part of growing research efforts examining how high-dimensional data collected from mobile devices can be utilised to infer users’ dynamic preferences that are learned over time. We suggest novel methods for inferring the category of the item liked in a specific contextual situation, by applying encoder-decoder learners (long short-term memory networks and auto encoders) on mobile sensor data. In these approaches, the encoder-decoder learners reduce the dimensionality of the contextual features to a latent representation which is learned over time. Given new contextual sensor data from a user, the latent patterns discovered from each deep learner is used to predict the liked item’s category in the given context. This can greatly enhance a variety of services, such as mobile online advertising and context-aware recommender systems. We demonstrate our contribution with a point of interest (POI) recommender system in which we label contextual situations with the items’ categories. Empirical results utilising a real world data set of contextual situations derived from mobile phones sensors log show a significant improvement (up to 73% improvement) in prediction accuracy compared with state of the art classification methods.     

Sentiment-oriented contextual advertising

Web advertising (Online advertising), a form of advertising that uses the World Wide Web to attract customers, has become one of the world’s most important marketing channels. This paper addresses the mechanism of Content-based advertising (Contextual advertising), which refers to the assignment of relevant ads to a generic web page, e.g., a blog post. As blogs become a platform for expressing personal opinion, they naturally contain various kinds of expressions, including both facts and comments of both a positive and negative nature. Besides, in line with the major tenet of Web 2.0 (i.e., user-centric), we believe that the web-site owners would be willing to be in charge of the ads which are positively related to their contents. Hence, in this paper, we propose the utilization of sentiment detection to improve Web-based contextual advertising. The proposed sentiment-oriented contextual advertising (SOCA) framework aims to combine contextual advertising matching with sentiment analysis to select ads that are related to the positive (and neutral) aspects of a blog and rank them according to their relevance. We experimentally validate our approach using a set of data that includes both real ads and actual blog pages. The results indicate that our proposed method can effectively identify those ads that are positively correlated with the given blog pages.     

需求信息不对称下的双渠道供应链合作广告投资决策分析

研究制造商主导的Stackelberg 博弈下双渠道供应链的合作广告策略, 分析信息不对称及双渠道对供应链合作广告投资决策的影响. 研究表明, 零售商在具有需求信息优势时会谎报需求信息, 并且在一定条件下其谎报决策会降低制造商的利润, 但能提高供应链的利润, 这种情况下制造商无法通过激励合同促使零售商共享信息. 另外, 在最优合作广告策略下, 当直销渠道与分销渠道所占市场份额的分配比例小于一定值时, 制造商采取双渠道会使供应链参与者均受益.

     

Internet market strategies: Antecedents and implications

The Web is a new market channel that has become a serious alternative to traditional channels. At present, there is little strategy analysis available to guide a company's decision about its involvement in the internet market. In this paper, we differentiate between the internet and traditional market channels and define two fundamental strategies for operating on the internet as: pure and mixed. Based on models of competition in microeconomic theory and resource-based perspectives, we develop a conceptual model for channel selection. We discuss the results and their implications for companies operating on the internet.     

Vertical cooperative advertising in a retailer duopoly

This paper focuses on optimal pricing and advertising decisions within a two-echelon distribution channel, which consists of one manufacturer and two competing retailers. Assuming an inter-echelon Stackelberg equilibrium, where the manufacturer obtains channel leadership, we compare two different forms of retailer behavior: non-cooperative (Horizontal Nash) and cooperative (Cooperation). While the consumer demand depends both on retail price and advertising, the manufacturer can offer a vertical cooperative advertising program to increase the advertising efforts of his retailers. In order to derive a logically consistent price demand function, we deduce our demand function from the consumers’ utility function. Numerical examples lead to the following main findings: (i) consumers can benefit from retailer-competition, as it reduces retail price; (ii) the manufacturer’s participation in retailers’ advertising will be the highest when there is strong competition and no Cooperation; (iii) a Cooperation does not always yield higher profits for the retailers, but can also produce better results for the manufacturer.     

Performance analysis of keyword advertising campaign using gender-brand effect of search queries

In this research, we analyze the relationship among (1) the performance metrics of a sponsored search campaign, (2) the gender orientation of queries, and (3) the occurrence of branded terms in queries. The aim of this research is to investigate the effectiveness of increased personalization of search engine advertising in order to improve the consumer’s online experience. We segregate keyphrases from a dataset covering thirty-three consecutive months from a major US retailer consisting of 7 million daily records of a real time keyword advertising campaign into three gender categories (male, female and neutral) each with two groups (branded and unbranded) term usage. Using ANOVA, we analyze the effect of gender and brand keyphrases on critical sponsored search performance metrics of impressions, clicks, cost-per-clicks, sales revenue, orders, items purchased and return on advertising. Research findings show that the combination of brand focus with the gender-orientation of keyphrases is a significant factor in predicting sponsored search performance and behavior. There are statistically significant variations in consumer behavior as measured by sponsored search metrics among the gender categories. Specifically, females are more attracted to the use of branded terms than males, perhaps due to the trust and customer loyalty generated by brand image. Our results establishes that positive brand reputation creates dramatic influence on consumer’s loyalty over the brand and hence strongly affects their interests, activities and purchasing behavior in e-commerce environment.     

Blogger-Centric Contextual Advertising

Web advertising (online advertising), a form of advertising that uses the World Wide Web to attract customers, has become one of the most commonly-used marketing channels. This paper addresses the concept of Blogger-Centric Contextual Advertising, which refers to the assignment of personal ads to any blog page, chosen in according to bloggers’ interests. As blogs become a platform for expressing personal opinions, they naturally contain various kinds of statements, including facts, comments and statements about personal interests, of both a positive and negative nature. To extend the concept behind the Long Tail theory in contextual advertising, we argue that web bloggers, as the constant visitors of their own blog-sites, could be potential consumers who will respond to ads on their own blogs. Hence, in this paper, we propose using text mining techniques to discover bloggers’ immediate personal interests in order to improve online contextual advertising. The proposed Blogger-Centric Contextual Advertising (BCCA) framework aims to combine contextual advertising matching with text mining in order to select ads that are related to personal interests as revealed in a blog and rank them according to their relevance. We validate our approach experimentally using a set of data that includes both real ads and actual blog pages. The results indicate that our proposed method could effectively identify those ads that are positively-correlated with a blogger’s personal interests.     

The value of location in keyword auctions

Sponsored links on search engines are an emerging advertising tool, whereby a number of slots are put on sale through keyword auctions. This is also known as contextual advertising. Slot assignment and pricing in keyword auctions are then essential for the search engine’s management since provide the main stream of revenues, and are typically accomplished by the Generalized Second Price (GSP) mechanism. In GSP the price of slots is a monotone function of the slot location, being larger for the highest slots. Though a higher location is associated with larger revenues, the lower costs associated with the lowest slots may make them more attractive for the advertiser. The contribution of this research is to show, by analytical and simulation results based on the theory of order statistics, that advertisers may not get the optimal slot they aim at (the slot maximizing their expected profit) and that the GSP mechanism may be unfair to all the winning bidders but the one who submitted the lowest bid.     

Simulating Sequential Search Models with Genetic Algorithms: Analysis of Price Ceilings,Taxes, Advertising and Welfare

This paper studies advertising, price ceilings and taxes in a sequential search model with bilateral heterogeneities in production and search costs. We simulate equilibria using a genetic algorithm (GA) applied to over 100 market scenarios, each differing based on the number of firms, number of consumers, existence of price ceilings or taxes, costs of production, costs of advertising, consumers’ susceptibility to advertising and consumers’ search costs. We study the interaction of advertising and search and analyze the welfare effects of advertising, price ceilings and sales taxes. Despite advertising being uninformative, we find that firms charging lower prices tend to advertise more intensely and that price ceilings and advertising can improve welfare if search costs are high.     

Coordination of cooperative advertising models in a one-manufacturer two-retailer supply chain system

This paper considers cooperative advertising issues of a monopolistic manufacturer with competing duopolistic retailers. Four possible game structures (or power configurations), i.e., Stackelberg–Cournot, Stackelberg–Collusion, Nash–Cournot and Nash–Collusion, are discussed. Under each of four game structures, we develop a decision model for the three partners to design the optimal cooperative advertising policies. Through a comparison among the four models, we reveal how cooperative advertising policies and profits of all participants are affected by various competitive behaviors, and then determine whether the partners have any incentives to transit to a different structure. Also presented in the paper are a centralized decision model and a proposed cost-sharing contract, which is able to achieve perfect coordination of the considered channel, where the utility of risk preference is used to determine the fraction of local advertising costs shared by the manufacturer.     

The effects of product involvement and impulse buying on purchase intentions in mobile text advertising

While research in mobile advertising is abundant, limited attention has been paid to date to how consumers respond to mobile advertisements for different product categories and in which way impulsivity affects intentions to purchase. In this paper, we study the dimensionality of the product involvement construct and its effects on consumers’ purchase intentions via a simulated field experiment (N = 736). We show that the cognitive dimension of product involvement and impulsiveness significantly affect purchase intentions. We also present that the relationship between product involvement and purchase intention is moderated by the consumers’ impulse buying personality traits. These findings progress the current state-of-the-art in mobile advertising research, while also having significant practical consequences for the design of effective mobile SMS advertising campaigns.     

On Smoothed Analysis of?Quicksort?and?Hoare’s Find

We provide a smoothed analysis of Hoare’s find algorithm, and we revisit the smoothed analysis of quicksort. Hoare’s find algorithm—often called quickselect or one-sided quicksort—is an easy-to-implement algorithm for finding the k-th smallest element of a sequence. While the worst-case number of comparisons that Hoare’s find needs is Θ(n ²), the average-case number is Θ(n). We analyze what happens between these two extremes by providing a smoothed analysis. In the first perturbation model, an adversary specifies a sequence of n numbers of [0,1], and then, to each number of the sequence, we add a random number drawn independently from the interval [0,d]. We prove that Hoare’s find needs $\Theta(\frac{n}{d+1} \sqrt{n/d} + n)$ comparisons in expectation if the adversary may also specify the target element (even after seeing the perturbed sequence) and slightly fewer comparisons for finding the median. In the second perturbation model, each element is marked with a probability of p, and then a random permutation is applied to the marked elements. We prove that the expected number of comparisons to find the median is $\Omega((1-p) \frac{n}{p} \log n)$ . Finally, we provide lower bounds for the smoothed number of comparisons of quicksort and Hoare’s find for the median-of-three pivot rule, which usually yields faster algorithms than always selecting the first element: The pivot is the median of the first, middle, and last element of the sequence. We show that median-of-three does not yield a significant improvement over the classic rule.     

Advertising channel selection in a segmented market

We consider a market with a finite number of segments and assume that several advertising channels are available, with different diffusion spectra and efficiencies. The problem of the choice of an advertising channel to direct the pre-launch campaign for a new product is analyzed in two steps. First, an optimal control problem is solved explicitly in order to determine the optimal advertising policy for each channel. Then a maximum profit channel is chosen. In a simulation example we consider the choice of a newspaper among six available and analyze the relations among the firm target market and the advertising channels environment which induce the optimal decision.     

Strategic design of competing supply chain networks with foresight

We consider models for duopolistic competitive supply chain network designing with sequential acting and variable delivered prices. These models design a multi-tier chain operating in markets under deterministic price-depended demands and with a rival chain present. The existing rival chain tends to open some new retailers to recapture some income in a near future. These rival chains’ structures are assumed to be set “once and for all” in a sequential manner but further price adjustments are possible.This problem is modeled for each of the following two strategies: (1) the von Stackelberg strategy in which we assume the existing chain will choose its future entry sites in the way to optimize its market share. This problem is modeled by a linear binary bi-level program and solved by a combinatorial meta-heuristic. (2) the minimum regret strategy in which we assume the existing chain’s future entry sites are totally unpredic, it is playing a “game against nature”. This problem is modeled by linear binary programs.     

Digital new market creation by incumbent firms: A political lens on the effect of formalization on agility

Digital new market creation has several advantages for incumbent firms (hereafter referred to as ‘incumbents’) that they seek to exploit by using formalization and implementing agility in their new product development (NPD). We introduce the construct of NPD decision agility encompassing the dimensions of sensemaking, speed, and iteration. However, research reveals heterogeneous insights into formalization’s suitability for digital new market creation and NPD decision agility. In response to this research gap, we test our hypotheses by applying a behavioral lens to a sample of 129 incumbents. We reconcile these heterogeneous insights on innovation by showing that formalization increases digital new market creation, but has more fine-grained effects on NPD decision agility. Although improving sensemaking and reducing iteration, formalization has no effect on speed. Furthermore, political behavior increases formalization’s negative effect on iteration. We contribute to research digitalization and agility at the intersection of information systems and innovation management by reconciling these heterogeneous insights.     

A context-aware approach to automated negotiation using reinforcement learning

Agents negotiate depending on individual perceptions of facts, events, trends and special circumstances that define the negotiation context. The negotiation context affects in different ways each agent’s preferences, bargaining strategies and resulting benefits, given the possible negotiation outcomes. Despite the relevance of the context, the existing literature on automated negotiation is scarce about how to account for it in learning and adapting negotiation strategies. In this paper, a novel contextual representation of the negotiation setting is proposed, where an agent resorts to private and public data to negotiate using an individual perception of its necessity and risk. A context-aware negotiation agent that learns through Self-Play and Reinforcement Learning (RL) how to use key contextual information to gain a competitive edge over its opponents is discussed in two levels of temporal abstraction. Learning to negotiate in an Eco-Industrial Park (EIP) is presented as a case study. In the Peer-to-Peer (P2P) market of an EIP, two instances of context-aware agents, in the roles of a buyer and a seller, are set to bilaterally negotiate exchanges of electrical energy surpluses over a discrete timeline to demonstrate that they can profit from learning to choose a negotiation strategy while selfishly accounting for contextual information under different circumstances in a data-driven way. Furthermore, several negotiation episodes are conducted in the proposed EIP between a context-aware agent and other types of agents proposed in the existing literature. Results obtained highlight that context-aware agents do not only reap selfishly higher benefits, but also promote social welfare as they resort to contextual information while learning to negotiate.     

基于微分博弈的双渠道广告合作协调策略研究

研究在制造商开通网上和零售渠道的情形下, 供应链成员的广告合作和成本分担对双渠道协调的影响. 研究结果表明, 无论零售商的广告对品牌形象产生何种影响, 制造商分担零售商的部分广告费用均能使得双方的利润优于分散决策的情形, 但不能完全实现双渠道协调. 此外, 当零售商也分担制造商的部分广告费用时, 双方均可以实现完全的协调. 相比于零售商频繁促销产生负面影响的情形, 在不产生负面影响的情况下, 双方能够实现更多的价值.

     

Explorations in evolutionary design of online auction market mechanisms

This paper describes the use of a genetic algorithm (GA) to find optimal parameter-values for trading agents that operate in virtual online auction ‘e-marketplaces’, where the rules of those marketplaces are also under simultaneous control of the GA. The aim is to use the GA to automatically design new mechanisms for agent-based e-marketplaces that are more efficient than online markets designed by (or populated by) humans. The space of possible auction-types explored by the GA includes the continuous double auction (CDA) mechanism (as used in most of the world’s financial exchanges), and also two purely one-sided mechanisms. Surprisingly, the GA did not always settle on the CDA as an optimum. Instead, novel hybrid auction mechanisms were evolved, which are unlike any existing market mechanisms. In this paper we show that, when the market supply and demand schedules undergo sudden ‘shock’ changes partway through the evaluation process, two-sided hybrid market mechanisms can evolve which may be unlike any human-designed auction and yet may also be significantly more efficient than any human designed market mechanism.