Download or read book Modeling Consumer Choice Processes for High tech Durable Goods written by Judi Ella Strebel and published by . This book was released on 1997 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamics of consumer demand for new durable goods written by Gautam Gowrisankaran and published by . This book was released on 2009 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper specifies and estimates a dynamic model of consumer preferences for new durable goods with persistent heterogeneous consumer tastes, rational expectations about future products and repeat purchases over time. Most new consumer durable goods, particularly consumer electronics, are characterized by relatively high initial prices followed by rapid declines in prices and improvements in quality. The evolving nature of product attributes suggests the importance of modeling dynamics in estimating consumer preferences. We estimate the model on the digital camcorder industry using a panel data set on prices, sales and characteristics. We find that dynamics are a very important determinant of consumer preferences and that estimated coefficients are more plausible than with traditional static models. We use the estimates to evaluate cost-of-living indices for new consumer goods and dynamic demand elasticities.
Download or read book The Consumer s Decision to Replace Durable Goods written by Viviana Paulina Fernández and published by . This book was released on 1997 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Testing Stochastic Models of Consumer Choice Behavior written by R. Dale Wilson and published by . This book was released on 1977 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Innovation by Demand written by Andrew McMeekin and published by Manchester University Press. This book was released on 2002 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: The structure and regulation of consumption and demand has recently become of great interest to sociologists and economists alike, and at the same time there is growing interest in trying to understand the patterns and drivers of technological innovation. This book, newly available in paperback, brings together a range of sociologists and economists to study the role of demand and consumption in the innovative process.The book starts with a broad conceptual overview of ways that the sociological and economics literatures address issues of innovation, demand and consumption. It goes on to offer different approaches to the economics of demand and innovation through an evolutionary framework, before reviewing how consumption fits into evolutionary models of economic development. Food consumption is then looked at as an example of innovation by demand, including an examination of the dynamic nature of socially-constituted consumption routines.The book includes a number of illuminating case studies, including an analysis of how black Americans use consumption to express collective identity, and a number of demand-innovation relationships within matrices or chains of producers and users or other actors, including service industries such as security, and the environmental performance of companies. The involvement of consumers in innovation is looked at, including an analysis of how consumer needs may be incorporated in the design of high-tech products. The final chapter argues for the need to build an economic sociology of demand that goes from micro-individual through to macro-structural features.This book is relevant to United Nations Sustainable Development Goal 9, Industry, innovation and infrastructure
Download or read book Scalable Models of Consumer Demand with Large Choice Sets written by Robert Nathanael Donnelly and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three essays related to the analysis of heterogeneity in consumer preferences based on individual level data on historical choices. In particular, they are connected by their application of modern Bayesian approaches to model consumers who differ both in their preferences for observed characteristics as well as their preferences for characteristics that are unobserved by the econometrician, but can instead be inferred from the correlations in choice behavior across different subsets of the population of consumers. The three chapters of this dissertation are also connected by their focus on scalability (both in computation and statistical efficiency) to large choice sets. Large choice sets are all around us, and the rise of E-commerce is leading to even larger sets of products that consumers can choose between. The average grocery store has tens of thousands of unique SKUs. The South Bay region around Stanford University has thousands of restaurants to choose between when you decide to go out for lunch. Large web retailers like Amazon sell hundreds of millions of distinct items. Individual level data on choices in situations like these present both opportunities and challenges. While these data sources are often large and rich in information, it is almost always the case that the number of choice occasions that we observe for any single individual is very small relative to the number of possible items they could have chosen between. Some types of products are easily described as a bundle of characteristics that consumers have preferences over, for example cars (horsepower, number of doors, leather seats) or digital cameras (resolution, zoom, flash), however for many other product categories it is more difficult to find a ''feature representation'' of products that accurately captures the heterogeneity in preferences across consumers. What are the characteristics that differ between Coke and Pepsi that lead to such strong disagreements over which is best. My work builds on recently developed approaches from machine learning for estimating models with large numbers of latent variables. This allows us to infer latent ''characteristics'' of products that are not directly observed by the econometrician, but can be inferred based on similarities in choice patterns across a large set of consumers. This allows us to model consumer preferences with heterogeneity in preferences for both observed and unobserved product characteristics. The first chapter of this dissertation is a paper written together with Susan Athey, David Blei, Francisco Ruiz, and Tobias Schmidt which analyzes consumer choices over lunchtime restaurants using data from a sample of several thousand anonymous mobile phone users in the San Francisco Bay Area. The data is used to identify users' approximate typical morning location, as well as their choices of lunchtime restaurants. We build a model where restaurants have latent characteristics (whose distribution may depend on restaurant observables, such as star ratings, food category, and price range), each user has preferences for these latent characteristics, and these preferences are heterogeneous across users. Similarly, each restaurant has latent characteristics that describe users' willingness to travel to the restaurant, and each user has individual-specific preferences for those latent characteristics. Thus, both users' willingness to travel and their base utility for each restaurant vary across user-restaurant pairs. We use a Bayesian approach to estimation. To make the estimation computationally feasible, we rely on variational inference to approximate the posterior distribution, as well as stochastic gradient descent as a computational approach. Our model performs better than more standard competing models such as multinomial logit and nested logit models, in part due to the personalization of the estimates. We analyze how consumers re-allocate their demand after a restaurant opens or closes and compare our predictions to the actual realized outcomes. Finally, we show how the model can be used to analyze counterfactual questions such as what type of restaurant would attract the most consumers in a given location. The second chapter is a paper written together with Susan Athey, David Blei, and Francisco Ruiz applies a similar approach in the context of supermarket scanner data. This paper demonstrates a method for estimating consumer preferences among discrete choices, where the consumer makes choices from many different categories. The consumer's utility is additive in the different categories, and her preferences about product attributes as well as her price sensitivity vary across products. Her preferences are correlated across products. We build on techniques from the machine learning literature on probabilistic models of matrix factorization, extending the methods to account for time-varying product attributes, a more realistic functional form for price sensitivity, and products going out of stock. We incorporate the information about the product hierarchy, so that consumers are assumed to select at most one alternative within a category. We evaluate the performance of the model using held-out data from weeks with price changes. We show that our model improves over traditional modeling approaches that consider each category in isolation, when we evaluate the ability of the model to predict responsiveness to price changes (using held-out data from a large number of price changes that occurred in our sample). We show that one source of the improvement is the ability of the model to accurately estimate heterogeneity in preferences (by pooling information across categories); another source of improvement is its ability to estimate the preferences of consumers who have rarely or never made a purchase in a given category in the training data. We consider counterfactuals such as personally targeted price discounts, showing that using a richer model such as the one we propose substantially increases the benefits of personalization in discounts. The third chapter of this dissertation proposes a novel estimator for learning heterogeneous consumer preferences based on both browsing and purchase data from online retailers with large product assortments. This work was done in collaboration with Ilya Morozov. Despite increasing availability data on the product pages consumers browse prior to making a purchase, the existing marketing literature provides little guidance on how retailers can use it to make better marketing decisions. In this paper, we propose an empirical framework that allows to efficiently extract information from consumers' search histories and use it to design personalized product recommendations. Our framework is based on the standard consideration set model from the marketing literature. To extract information from the unstructured search data, we augment the model with rich consumer heterogeneity and include several unobserved product characteristics. We then propose a way to estimate this model's parameters using a latent factorization approach from the computer science literature. The proposed framework can be seen as combining a structural approach to modeling consumer consideration from marketing with nonparametric estimation methods commonly used in the computer science. We are in discussion with a large online retailer to gain access to data and to run an AB test to experimentally validate the effects of improved rankings and recommendations of products.
Download or read book New Product Diffusion Models written by Vijay Mahajan and published by Springer Science & Business Media. This book was released on 2000-09-30 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Product sales, especially for new products, are influenced by many factors. These factors are both internal and external to the selling organization, and are both controllable and uncontrollable. Due to the enormous complexity of such factors, it is not surprising that product failure rates are relatively high. Indeed, new product failure rates have variously been reported as between 40 and 90 percent. Despite this multitude of factors, marketing researchers have not been deterred from developing and designing techniques to predict or explain the levels of new product sales over time. The proliferation of the internet, the necessity or developing a road map to plan the launch and exit times of various generations of a product, and the shortening of product life cycles are challenging firms to investigate market penetration, or innovation diffusion, models. These models not only provide information on new product sales over time but also provide insight on the speed with which a new product is being accepted by various buying groups, such as those identified as innovators, early adopters, early majority, late majority, and laggards. New Product Diffusion Models aims to distill, synthesize, and integrate the best thinking that is currently available on the theory and practice of new product diffusion models. This state-of-the-art assessment includes contributions by individuals who have been at the forefront of developing and applying these models in industry. The book's twelve chapters are written by a combined total of thirty-two experts who together represent twenty-five different universities and other organizations in Australia, Europe, Hong Kong, Israel, and the United States. The book will be useful for researchers and students in marketing and technological forecasting, as well as those in other allied disciplines who study relevant aspects of innovation diffusion. Practitioners in high-tech and consumer durable industries should also gain new insights from New Product Diffusion Models. The book is divided into five parts: I. Overview; II. Strategic, Global, and Digital Environments for Diffusion Analysis; III. Diffusion Models; IV. Estimation and V. Applications and Software. The final section includes a PC-based software program developed by Gary L. Lilien and Arvind Rangaswamy (1998) to implement the Bass diffusion model. A case on high-definition television is included to illustrate the various features of the software. A free, 15-day trial access period for the updated software can be downloaded from http://www.mktgeng.com/diffusionbook. Among the book's many highlights are chapters addressing the implications posed by the internet, globalization, and production policies upon diffusion of new products and technologies in the population.
Download or read book Consumer Durable Goods written by Canada. Industry Canada and published by Industry Canada. This book was released on 1995 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consumer durable goods cover a wide range of sectors and subsectors in the Canadian economy. For the purposes of this discussion, consumer durable goods have been grouped to include the following selected categories: furniture and fixtures, hardware, sporting goods, and toys and games. Together, this group represents an important segment of the Canadian economy, employing 56, 000 people and exporting $2.3 billion worth of goods annually. This document presents statistical tables on industry and Uruguay Round.
Download or read book Empirical Analysis of Dynamic Consumer Choice Behavior written by Inseong Song and published by . This book was released on 2002 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2002 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Analytical Approaches to Strategic Decision Making Interdisciplinary Considerations written by Tavana, Madjid and published by IGI Global. This book was released on 2014-04-30 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using interdisciplinary approaches to strategic management can strengthen the decision making process. Incorporating various methods will also encourage productivity, expand knowledge of participants, and increase technical proficiency. Analytical Approaches to Strategic Decision-Making: Interdisciplinary Considerations aims to integrate different techniques into the worlds fast-changing and dynamic society to better equip all readers and practitioners with the most effective knowledge. Managers, CEOs, researchers, and academics in the fields of business and leadership will all benefit from this valuable resource through an enhanced understanding of best practices in decision-making and management.
Download or read book Models and Methods in Economics and Management Science written by Fouad El Ouardighi and published by Springer Science & Business Media. This book was released on 2013-09-16 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this book, distinguished and notable contributors wish to honor Professor Charles S. Tapiero’s scientific achievements. Although it covers only a few of the directions Professor Tapiero has taken in his work, it presents important modern developments in theory and in diverse applications, as studied by his colleagues and followers, further advancing the topics Tapiero has been investigating. The book is divided into three parts featuring original contributions covering the following areas: general modeling and analysis; applications to marketing, economy and finance; and applications to operations and manufacturing. Professor Tapiero is among the most active researchers in control theory; in the late sixties, he started to enthusiastically promote optimal control theory along with differential games, successfully applying it to diverse problems ranging from classical operations research models to finance, risk and insurance, marketing, transportation and operations management, conflict management and game theory, engineering, regional and urban sciences, environmental economics, and organizational behavior. Over the years, Professor Tapiero has produced over 300 papers and communications and 14 books, which have had a major impact on modern theoretical and applied research. Notable among his numerous pioneering scientific contributions are the use of graph theory in the behavioral sciences, the modeling of advertising as a random walk, the resolution of stochastic zero-sum differential games, the modeling of quality control as a stochastic competitive game, and the development of impulsive control methods in management. Charles Tapiero’s creativity applies both in formulating original issues, modeling complex phenomena and solving complex mathematical problems.
Download or read book American Doctoral Dissertations written by and published by . This book was released on 2001 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Consumer Choice Behavior and New Product Development written by Stelios Tsafarakis and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The extremely high costs associated with the commercial failure of a new product, stresses the importance of a model that will effectively forecast the market penetration of a product at the design stage. The purpose of our study is to discover heuristics that will better explain market share, an issue of considerable concern to industry, which also, if successfully pursued, will increase the value of the analytical tools developed for managers. A method easy to implement is presented, which improves the value of market simulations in conjoint analysis. The proposed approach deals with two issues common to traditional market simulations in the context of conjoint analysis applications - the lack of differential impact of attributes across alternatives and the absence of accounting for differential substitution across brands (i.e. the IIA problem). We deal with the first issue by “tuning” utilities with individual level exponents, as opposed to a common exponent under the “ALPHA” rule (the current state of the art approach). These exponents derive from the range, skewness and kurtosis of the distribution of utilities that a respondent assigns to various products. While these exponents are individual specific, the effects of the coefficients are assumed to be homogeneous across consumers to preserve model parsimony, while accounting for observed heterogeneity in the data. The second issue is studied in the model via a similarity “correction” for each pair of products. The performance of the approach is validated both on real data from a market survey concerning milk, and on simulated data through the design of a Monte Carlo experiment. The results of the simulation for different market scenarios indicate that the approach appropriately exhibits the theoretical properties that are necessary for the efficient representation of consumer choice behavior. In addition, the proposed model outperforms the state of the art methodology, as well as some more traditional approaches, with regard to the forecasting accuracy on market shares estimation, both on the real and the simulated data sets. The results obtained have important implications for marketing managers concerning the design of new products. A new concept can be tested before it enters the production stage, using data obtained from a market survey. The high predictive accuracy of the model may assist a firm in minimizing the uncertainty and risks associated with a new product launch. The case study with data from a real market survey, illustrates the practical applicability of the approach.
Download or read book The Proceedings of the 2023 Conference on Systems Engineering Research written by Dinesh Verma and published by Springer Nature. This book was released on with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Agent Based Strategizing written by Duncan A. Robertson and published by Cambridge University Press. This book was released on 2019-10-17 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Strategic management is a system of continual disequilibrium, with firms in a continual struggle for competitive advantage and relative fitness. Models that are dynamic in nature are required if we are to really understand the complex notion of sustainable competitive advantage. New tools are required to tackle challenges of how firms should compete in environments characterized by both exogeneous shocks and intense endogenous competition. Agent-based modelling of firms' strategies offers an alternative analytical approach, where individual firm or component parts of a firm are modelled, each with their own strategy. Where traditional models can assume homogeneity of actors, agent-based models simulate each firm individually. This allows experimentation of strategic moves, which is particularly important where reactions to strategic moves are non-trivial. This Element introduces agent-based models and their use within management, reviews the influential NK suite of models, and offers an agenda for the development of agent-based models in strategic management.
Download or read book Consumer Behaviour towards Consumer Durable Goods written by Dr. N. Ratna Kishor and published by Archers & Elevators Publishing House. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
