Demand Estimation at Manufacturer-Retailer Duo: A Macro-Micro Approach

This dissertation is divided into two phases. The main objective of this phase is to use Bayesian MCMC technique, to attain (1) estimates, (2) predictions and (3) posterior probability of sales greater than certain amount for sampled regions and any random region selected from the population or sample. These regions are served by a single product manufacturer who is considered to be similar to newsvendor. The optimal estimates, predictions and posterior probabilities are obtained in presence of advertising expenditure set by the manufacturer, past historical sales data that contains both censored and exact observations and finally stochastic regional effects that cannot be quantified but are believed to strongly influence future demand. Knowledge of these optimal values is useful in eliminating stock-out and excess inventory holding situations while increasing the profitability across the entire supply chain. Subsequently, the second phase, examines the impact of Cournot and Stackelberg games in a supply-chain on shelf space allocation and pricing decisions. In particular, we consider two scenarios: (1) two manufacturers competing for shelf space allocation at a single retailer, and (2) two manufacturers competing for shelf space allocation at two competing retailers, whose pricing decisions influence their demand which in turn influences their shelf-space allocation. We obtain the optimal pricing and shelf-space allocation in these two scenarios by optimizing the profit functions for each of the players in the game. Our numerical results indicate that (1) Cournot games to be the most profitable along the whole supply chain whereas Stackelberg games and mixed games turn out to be least profitable, and (2) higher the shelf space elasticity, lower the wholesale price of the product; conversely, lower the retail price of the product, greater the shelf space allocated for that product

Keyword Targeting Optimization in Sponsored Search Advertising: Combining Selection and Matching

In sponsored search advertising (SSA), advertisers need to select keywords and determine matching types for selected keywords simultaneously, i.e., keyword targeting. An optimal keyword targeting strategy guarantees reaching the right population effectively. This paper aims to address the keyword targeting problem, which is a challenging task because of the incomplete information of historical advertising performance indices and the high uncertainty in SSA environments. First, we construct a data distribution estimation model and apply a Markov Chain Monte Carlo method to make inference about unobserved indices (i.e., impression and click-through rate) over three keyword matching types (i.e., broad, phrase and exact). Second, we formulate a stochastic keyword targeting model (BB-KSM) combining operations of keyword selection and keyword matching to maximize the expected profit under the chance constraint of the budget, and develop a branch-and-bound algorithm incorporating a stochastic simulation process for our keyword targeting model. Finally, based on a realworld dataset collected from field reports and logs of past SSA campaigns, computational experiments are conducted to evaluate the performance of our keyword targeting strategy. Experimental results show that, (a) BB-KSM outperforms seven baselines in terms of profit; (b) BB-KSM shows its superiority as the budget increases, especially in situations with more keywords and keyword combinations; (c) the proposed data distribution estimation approach can effectively address the problem of incomplete performance indices over the three matching types and in turn significantly promotes the performance of keyword targeting decisions. This research makes important contributions to the SSA literature and the results offer critical insights into keyword management for SSA advertisers.Comment: 38 pages, 4 figures, 5 table

Internet media planning : an optimization model

Of the various media vehicles available for advertising, the internet is the latest and the most rapidly growing, emerging as the ideal medium to promote products and services in the global market. In this article, the authors propose an internet media planning model whose main objective is to help advertisers determine the return they obtain from spending on internet advertising. Using available data such as internet page view and advertising performance data, the model contributes to attempts not only to optimize the internet advertising schedule but also to fix the right price for internet advertisements on the basis of the characteristics of the exposure distribution of sites. The authors test the model with data provided by KoreanClick, a Korean market research company that specializes in internet audience measurement. The optimal durations for the subject sites provide some useful insights. The findings contrast with current web media planning practices, and the authors demonstrate the potential savings that could be achieved if their approach were applied.media planning; optimization; advertising repeat exposure; probability distribution; internet

An Integrated Bargaining Solution Analysis For Vertical Cooperative Sales Promotion Campaigns Based On The Win-Win-Win Papakonstantinidis Model

Authors intention was to examine the possibility to investigate win-win-win papakonstantinidis model in order to develop an integrated bargaining solution analysis for vertical cooperative sales promotion campaigns. Based on previous theoretical extensions (Spais and Papakonstantinidis, 2011; Spais, Papakonstantinidis and Papakonstantinidis, 2009), this study presented an integrated bargaining solution analysis for cases of optimal allocation of a promotion budget in a cooperative sales promotion campaign in vertical marketing channels. This integrated bargaining solution analysis included: a) three (3) adjusted utility functions, considering the parameters of sales response budgeting method, the break-even sales analysis and the marketing channel members trade promotion goals; b) the referee solution, the optimal solution for the three players and the constraints; c) the definition of the third win in terms of a continuous sensitization process and perfect information; and d) the presentation of the potential outputs from a bargaining process regarding to the sharing of the cooperative sales promotion cost among A, B and C parties/players for different sales promotion offerings. Encouragingly, the review of the modern literature and the four (4) critical case studies of cooperative marketing programs confirmed the need for a win-win-win approach in cooperative sales promotion planning in vertical marketing channels

Portfolio Construction: The Efficient Diversification of Marketing Investments

Efforts in the marketing sciences can be distinguished between the analysis of individual customers and the examination of portfolios of customers, giving scarce theoretical guidance concerning the strategic allocation of promotional investments. Yet, strategic asset allocation is considered in financial economics theory to be the most important set of investment decisions. The problem addressed in this study was the application of strategic asset allocation theory from financial economics to marketing science with the aim of improving the financial results of investment in direct marketing promotions. This research investigated the components of efficient marketing portfolio construction which include multiattribute numerical optimization, stochastic Brownian motion, peer index tracking schemes, and data mining methods to formulate unique investable asset classes. Three outcomes resulted from this study on optimal diversification: (a) reduced saturative promotional activities balancing inefficient advertising cost and enterprise revenue objectives to achieve an investment equilibrium state; (b) the use of utility theory to assist in the lexicographic ordering of goal priorities; and (c) the solution approach to a multiperiod linear goal program with stochastic extensions. A performance test using a large archival set of customer data illustrated the benefits of efficient portfolio construction. The test asset allocation resulted in significantly more reward than that of the benchmark case. The results of this grounded theory study may be of interest to marketing researchers, operations research practitioners, and functional marketing executives. The social change implication is increased efficiency in allocation of large advertising budgets resulting in improved corporate performance

The Economics of Lotteries: An Annotated Bibliography

This paper presents an annotated bibliography of all papers relating to the economics of lotteries as of early to mid 2011. All published scholarly papers that could be identified by the authors are included along with the published abstract where available.lotto, lottery, public finance, gambling

Stockholding: Recent Lessons from Theory and Computations

Household-level portfolio data show a tendency of the majority of households in each country to hold no stocks despite a historical expected-return premium on equity relative to riskless assets. This paper first explains why such a tendency constitutes a puzzle in economic theory (the "stockholding puzzle"). It discusses why simple popular notions regarding the source of non-participation (risk aversion, risky labor income, and borrowing constraints) are not confirmed by careful analysis of portfolio models and presents recent conclusions on what causes non-participation. Based on this, it revisits the popular view on non-participation and shows how it can be qualified to be consistent with lessons from economic theory. It also explains how this view can be extended to account for exits from the stock market and for limited diversification. Then, the paper describes three unsolved empirical puzzles concerning the share of stocks in portfolios of households that do participate in the stock market. It points to basic underlying mechanisms producing these theoretical results and discusses briefly possible future directions for research that may help resolve the puzzles. Finally, the paper draws lessons for practitioners interested in expanding the stockholder base.

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment