A choice-based multi-product diffusion model incorporating replacement demand

This study proposes an integrated forecasting model that incorporates both first purchase diffusion and replacement component of sales in predicting multi-product diffusion patterns. The model consists of a two-stage procedure that customers undertake during purchase occasions according to a diffusion process or replacement process, and at each occasion, they make purchase incidence decisions and product choices according to a choice model. By incorporating various exogenous factors in the choice model, the model can identify the impact of each factor on customers' purchase incidence decisions and choice decisions among various product sub-categories. This approach enables us to understand the overall process of customers' purchasing behavior and to separate total sales amount into sales to three consumer segments: first-time buyers, customers who repurchase the same product category and customers who change their previous product category. We applied the proposed model in the forecasting multi-product framework; forecasting sub-category level automobile sales and brand level mobile terminal sales in the South Korean market. The results of the empirical studies showed that incorporating the replacement components into the multi-product diffusion framework is useful not only in understanding the demand interaction among automobile categories and among mobile handset brands, but also in producing more accurate long-term sales forecasts compared to previous multi-product diffusion models.     

A micro-analytic threshold model for the timing of first purchases of durable goods

A micro-analytic threshold model to describe the timing of household purchases of consumer durable goods is developed and tested. The model incorporates unobserved heterogeneity via a generalized gamma distribution and accounts for time varying covariates. Further, we employ estimation methods applicable or purchase data observed at periodic intervals of time. The model outperforms other competing models for predicting the timing of purchase of durable goods in terms of fit and predictive ability. In particular, this model outperforms the logit model and the diffusion model. The generalized gamma timing model predicts well the time to purchase the durable good; we show how it can be employed for micro-segmentation of households. Several research directions and applications are described.     

A product diffusion model incorporating repeat purchases

A logistic-based model for forecasting the rate of product diffusion given aggregate time series data was constructed. The model differs from earlier models based on fitting the logistic to aggregate data in that it includes a submodel to separate replacement demand from first-time sales. We fit the theoretical model to data and show that forecasts will be significantly more accurate using this model instead of the logistic curve.     

Promotional programmes and consumer purchasing decisions: pecan demand models

A generalized Heckman model of purchase decisions is estimated incorporating perceived consumer quality attributes, ease of purchase, and familiarity with marketing outlets as factors influencing pecan purchases. Economic implications for evaluating consumer purchase decisions and the design of commodity promotion programmes for the pecan industry are addressed. Key marketing variables such as the variety of uses for nut products, the number of outlets used to purchase pecans, and consumer perceptions of positive quality features of pecans are significant in promoting purchases. Applications of a trade-off analysis examine key variables considered by the pecan industry in developing promotional programmes both to stabilize pecan purchases and to maintain the probability of pecan purchases.     

SELLING IN ADVANCE TO LOSS AVERSE CONSUMERS

This article examines the influence of information on market performance in an advance purchase setting. Information reduces the risk that an advance purchase results in a mismatch between consumer preferences and product characteristics. However, information may also raise the number of advance purchases by increasing firms' incentive to offer advance purchase discounts. Accounting for consumers' aversion toward losses/risks turns out to be crucial as it changes our assessment of policies aiming to improve consumers' information: Under monopoly, information can be detrimental both for efficiency and consumer surplus, whereas under competition, information is doubly beneficial because it mitigates intertemporal business stealing.     

Forecasting sales and product evolution: The case of the hybrid/electric car

We present a model that forecasts sales and product evolution, based on data on market and industry, which can be collected before the product is introduced. Product evolution can be incremental but can also take place by releasing new generations. In our model adoption of a new product is motivated by attribute improvements (enabled by technology evolution), and firms' attribute improvements strategies are motivated by market growth and directed by market preferences. The interdependency between attributes' improvements and cumulative adoption level makes the problem inherently dynamic. The dependency of attribute levels on adoption levels is assessed using industry and technology analysis. Market preferences and purchase intention response to attribute levels changes are assessed based on a conjoint study. The option of collecting and interpreting data about both demand and supply aspects, before the new product is introduced, enables us to estimate sales and technology progress endogenously rather than to require them as inputs. We demonstrate the method on the hybrid car market.     

Time inconsistency and alcohol sales restrictions

Restrictions on alcohol sales hours or days are commonly used tools in order to reduce alcohol consumption. However, a forward-looking consumer can buy in advance, and thereby mostly undo the impact of the restriction. I study whether time inconsistent consumer preferences can provide a justification for restrictions on alcohol sales time. I estimate a demand model, which allows a fraction of consumers to be time inconsistent, using scanner data of beer purchases and other shopping behavior. According to the estimation results, 16% of regular beer buyers, or only 3% of all consumers, behave as if they are time inconsistent. I find that in terms of consumer welfare, the sales restriction may be welfare improving, but is worse than increasing taxes.     

Forecasting demand for a newly introduced product using reservation price data and Bayesian updating

Forecasting demand during the early stages of a product's life cycle is a difficult but essential task for the purposes of marketing and policymaking. This paper introduces a procedure to derive accurate forecasts for newly introduced products for which limited data are available. We begin with the assumption that the consumer reservation price is related to the timing with which the consumer adopts the product. The model is estimated using reservation price data derived through a consumer survey, and the forecast is updated with sales data as they become available using Bayes's rule. The proposed model's forecasting performance is compared with that of benchmark models (i.e., Bass model, logistic growth model, and a Bayesian model based on analogy) using 23 quarters' worth of data on South Korea's broadband Internet services market. The proposed model outperforms all benchmark models in both prelaunch and postlaunch forecasting tests, supporting the thesis that consumer reservation price can be used to forecast demand for a new product before or shortly after product launch.     

The late take-off phenomenon in the diffusion of telecommunication services: network effect and the critical mass

Telecommunication services are distinctive in that their adoptions are influenced by network effect resulting in the late take-off phenomenon and the critical mass problem. In this paper we examined the late take-off phenomenon in the diffusion process of telecommunication services. We first compared the parameters of the diffusion process of consumer durables with those of fax services in the US and Korea. By analyzing the parameters of a new diffusion model based on the threshold model proposed by Markus, we found that the late take-off phenomenon resulted from the low heterogeneity of the threshold distribution for the potential adopters. A simulation approach was proposed for the theoretical implication of the critical mass problem in the start-up telecommunications services.     

A technology replacement model with variable market potential — An empirical study of CRT and LCD TV

The rapidly changing economic environment and increasingly fierce competition indicate that companies must innovate in both their products and marketing strategies if they are to continue to flourish. Specifically, the ability to accurately predict the demand for products is crucial when firms decide to allocate their resources, especially in the fast moving high technology industries, where there is very high investment in R&D and production facilities. This study establishes a forecast model for technology replacement based on the diffusion model with population growth used for the variable market potential. The proposed model is then applied to investigate the CRT and LCD TV market.The results suggest that the new model is more accurate than the constant market potential model in fitting and forecasting performance. Consumers who purchase a TV for the first time are likely more attracted to LCD TV rather than CRT TV. As for those individuals who already own a CRT TV, the attraction is not strong enough to encourage them to replace their current CRT TV with a new LCD TV. Moreover, it is noted that the falling price of LCD TV is an essential factor in encouraging purchases.     

Market potential dynamics in innovation diffusion: Modelling the synergy between two driving forces

The presence of a slowdown in new product life cycles has recently received notable attention from many innovation diffusion scholars, who have tried to explain and model it on a dual-market hypothesis (early market-main market). In this paper we propose an alternative explanation for the slowdown pattern, a dual-effect hypothesis, based on a recent co-evolutionary model, where diffusion results from the synergy between two driving forces: communication and adoption. An analysis of the synergistic interaction between communication and adoption, based on the likelihood ratio order or on a weak stochastic order, can inform us of which of the two had a driving role in early diffusion. We test the model on the sales data of two pharmaceutical drugs presenting a slowdown in their life cycle and observe that this is identified almost perfectly by the model in both cases. Contrary to the general expectation, according to which communication should precede adoption, our findings show that adoptions may be the main driver in early life cycle; this may be related to the drug's specific nature.     

Investigation of the effect of secondary market on the diffusion of innovation

In the high-tech product market, the number of hungry adopters, a new type of early adopters who buy new products and sell them soon in the on- or off-line secondary market to seek for the other new products, has been increasing due to the short product life cycle of high-tech products and the low transaction cost on the Internet. This new phenomenon means that it is inappropriate to consider customers only in the primary market as total adopters in innovation diffusion modeling, since purchasers in the secondary market also have a word-of-mouth effect on the remaining non-adopters. To explain this new phenomenon, we modify the basic Bass diffusion model by incorporating the effect of the secondary market and conduct an empirical analysis. As a result, we conclude that the basic Bass model is likely to overestimate sales volume and tends to forecast lagged peak time when there is an effect from the secondary market. This means that applying a diffusion model to high-tech products without considering the secondary market effect would provide an inaccurate market forecast.     

Forecasting future demand for large-screen television sets using conjoint analysis with diffusion model

The methodological framework proposed in this paper addresses two limitations of the basic Bass diffusion model: that it does not reflect competition among products nor does it forecast demand for products that do not exist in the marketplace. The model consists of four steps. First, to investigate consumer preferences for product attributes, we use conjoint analysis to estimate the utility function of consumers. Next we estimate the dynamic price function of each competing product to reflect technological changes and the evolving market environment. Then we derive dynamic utility function by combining the static utility function and the price function. Finally, we forecast the sales of each product using estimated market share and sales data for each period, which are derived from the dynamic utility function and from the Bass diffusion model, respectively.We apply this model to South Korea's market for large-screen televisions. The results show that (1) consumers are sensitive to picture resolution and cost and (2) in the near future, should the market see the introduction of liquid crystal display (LCD) TVs with screens larger than 50 inches, the high resolution and steep price drop of LCD will lead LCD TVs to capture a larger market share than TVs with other display types. Finally, our results show that TVs with 40-inch screens are preferred over TVs with larger screens.     

电商不同类型促销对购买行为的长期影响——以亚马逊电子书为例

促销的长期影响在学术界一直备受争议,并且传统研究更多地关注实体企业的促销效果,而对电商平台的促销活动研究较少。为了厘清电商平台的不同促销方式对消费者购买行为的长期影响,本文基于亚马逊电子书的销售数据,建立固定效应模型考察了降价和优惠券两种价格促销的长期影响。结果表明,降价促销会导致消费者未来购买数量减少、购买金额增加、购买时间间隔缩短;优惠券促销则会使得消费者未来购买数量增加、购买金额减少、购买时间间隔不变。在此基础上,本文进一步分析了消费者购买经验的调节作用。本文不仅丰富了已有促销长期影响的研究成果,而且对电商如何制定促销策略以优化促销长期效果提供了科学可行的建议,具有重要的理论意义和实践价值。     

VALUING THE SERVICES OF CONSUMER DURABLES

Although consumer durables are treated as nondurables in most economic accounts, economists have long recognized that they could be treated as capital. If an estimate of the value of the services of consumer durables was available, it could be included in personal consumption expenditures and purchases of the durables treated as a form of investment. Such treatment would give a better picture of changes in a nation's economic welfare over time and make international comparisons more meaningful.
This article reviews the economic literature on how the services of consumer durables can be valued. It examines six alternative measures: the (1) user cost; (2) capital recovery; (3) opportunity cost; (4) market rental value; (5) cost of a substitute; and (6) cash-equivalent value measures. The first three are based on the summation of the costs of the inputs used to produce the services, although only the first two are consistent with the principle that the purchase price of a durable equals the discounted present value of its expected future benefits. The fourth and fifth measures are based on the prices of marketed services while the sixth is derived from the consumer's demand function for the good's services. The article also discusses six major issues in implementing these measures: (1) imputing a rate of return to capital; (2) measuring declines in market value (depreciation and capital gains); (3) accounting for operating expenditures; (4) adjusting for capacity utilization; (5) deflating service values; and (6) defining consumer durables.     

Strategic Quality Decisions by Heterogeneously Informed Suppliers — The Role of "Noise Consumers"—

In a differentiated oligopoly market, it is often the case that consumers' ex post preferences over different product qualities depend upon the state of nature which is not yet observable to the consumers at the time of purchase. One of the most typical examples is a market for durable goods or long-term service contracts, where the state is indeed a future state which has not yet realised when the transaction is made. To analyse such situations, this paper models a two-stage game, in which multiple suppliers move first to choose the quality of their products based upon their idiosyncratic information about the state. Consumers then observe these products, update their beliefs about the state, and decide which products to purchase. Counterintuitively, suppliers' incentives to reveal their private information are higher when there is a fraction of consumers whose prior about the state is moderately inaccurate, than when every consumer has better prior information. Hence the presence of such "noise consumers" can make all consumers better off, even including noise consumers themselves.     

Forecasting the semiconductor industry cycles by bootstrap prediction intervals

In recent years, there has been a recognition that point forecasts of the semiconductor industry sales may often be of limited value. There is substantial interest for a policy maker or an individual investor in knowing the degree of uncertainty that attaches to the point forecast before deciding whether to increase production of semiconductors or purchase a particular share from the semiconductor stock market. In this article, I first obtain the bootstrap prediction intervals of the global semiconductor industry cycles by a vector autoregressive (VAR) model using monthly US data consisting of four macroeconomic and seven industry-level variables with 92 observations. The 24-step-ahead out-of-sample forecasts from various VAR setups are used for comparison. The empirical result shows that the proposed 11-variable VAR model with the appropriate lag length captures the cyclical behaviour of the industry and outperforms other VAR models in terms of both point forecast and prediction interval.     

Demographic processes in a model of innovation diffusion with dynamic market

In this paper we study a binomial innovation diffusion model for a variable size market by modelling the demographic process of entrance-exit from each market compartment. We examine from a theoretical point of view the effect of the simultaneous presence of economic and demographic parameters under the exponential market growth hypothesis, by presenting some general results on the adoptions and sales time path. We also enlighten the relevance of considering these variables in relative terms and show how, in presence of a dynamic, the diffusion process never saturates the market. Finally, we test our model on a data set for cellular phones market in different countries.     

Equilibrium in a durable goods market with lumpy adjustment

Durable goods are an important component of the business cycle. Equilibrium models of durable goods markets are made difficult by the lumpy nature of individual purchases. We show that a straightforward approximation of the distribution of durable goods holdings gives rise to a tractable equilibrium model. We analyze the case of competition as well as that of a monopoly producer.     

DYNAMIC PRICE COMPETITION WITH CAPACITY CONSTRAINTS AND A STRATEGIC BUYER

We analyze a simple dynamic durable good model. Two incumbent sellers and potential entrants choose their capacities at the start of the game. We solve for equilibrium capacity choices and the (necessarily mixed) pricing strategies. In equilibrium, the buyer splits the order with positive probability to preserve competition, making it possible that a high and low price seller both have sales. Sellers command a rent above the value of unmet demand by the other seller. A buyer benefits from either a commitment not to make future purchases or by hiring an agent to always buy from the lowest priced seller.