Modeling the effects of including/excluding attributes in choice experiments on systematic and random components

This paper examines the impact of attribute presence/absence in choice experiments using covariance heterogeneity models and random coefficient models. Results show that attribute presence/absence impacts both mean utility (systematic components) and choice variability (random components). Biased mean effects can occur by not accounting for choice variability. Further, even if one accounts for choice variability, attribute effects can differ because of attribute presence/absence. Managers who use choice experiments to study product changes or new variants should be cautious about excluding potentially essential attributes. Although including more relevant attributes increases choice variability, it also reduces bias.     

Modelling multinational telecommunications demand with limited data

Forecasting the diffusion of innovations in the telecommunications sector is a constantly recurring problem for national providers. The problem is characterised by short data series making the estimation of model parameters unreliable. However, the same innovation will be diffusing simultaneously in other national markets, although with a different start date. The use of this cross-sectional data in constructing innovation diffusion models is investigated here. Four models for pooling the cross-sectional data are described and two diffusion models are discussed although only one, the Gompertz model is used throughout. Three innovation data sets are used in the evaluation of the models: digital cellular telephones, ISDN connections and fax connections. The pooled diffusion forecasts proved to be more accurate in several comparisons relative to a naïve benchmark and to individual forecasts when available.     

The diffusion of successive generations of a technology: A more general model

In many cases of technological development, successive generations of a technology evolve, each more efficient than its predecessor. It has been assumed when modeling and forecasting the adoption of these technologies that the market reaction to each generation was similar. Using the terminology of the Bass model, this similarity is encapsulated in the assumption that the coefficients of innovation and imitation are constant. New data for two and three generations of mobile telephone technology from eleven countries are modeled. The modeling framework used—simultaneous estimation for successive generations using a full information maximum likelihood procedure—demonstrates that, in most cases, the hypothesis of constant coefficients can be rejected. Use of a model with changing coefficients is shown to considerably improve forecasting performance. These results were reinforced by analysis of data for four generations of IBM mainframes.     

A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best–worst scaling

We review the measurement of product attribute importance, and find little consensus in definition or measurement methods. We compare four measurement methods: 1) two direct methods whereby respondents report the importance of attributes using best–worst scaling or constant sum scales, and 2) two indirect methods derived from discrete choice experiments. Our comparisons rely on previous findings that choice experiments are externally valid to use as the standard. We find high agreement within direct or indirect methods, but less agreement between direct and indirect methods. Our results also demonstrate that inferences derived from indirect measures appear to be susceptible to context effects related to the particular attributes a researcher chooses to investigate. We discuss implications for current and future research.     

From a commodity to an experience: The moderating role of thematic positioning on congruity‐based product judgment

Research in positioning strategy suggests that a product schema, when presented in a moderately incongruent fashion, can evoke a greater degree of positive evaluation than if presented congruently with consumer expectations. This phenomenon has been coined the schema congruity effect. To date, one of the limitations of the phenomenon is that it has been applied almost exclusively to taxonomic stimuli, with little reference to thematic, eventlike stimuli. Two experiments verified that taxonomic and thematic product categories differ with respect to their unique characteristics. Consequently, despite successful replication of the schema congruity effect during taxonomic interpretation, when pushed thematically, the schema congruity effect failed to manifest. Furthermore, both experiments confirmed that, unlike taxonomic product categories that benefit from abstract and moderately incongruent positioning, thematic product categories benefit from concrete and congruent positioning. Implications for understanding the moderating role of thematic positioning on congruity‐based product evaluation as well as the differences between taxonomic and thematic stimuli are discussed. © 2010 Wiley Periodicals, Inc.     

Detecting the impact of market factors on sales takeoff times of analog cellular telephones

We use two approaches to model the hazard probability of the time-to-sales takeoff for cellular analog telephony to determine the impact of three market factors: price, number of competitors, and number of competing standards. We compare a fully parametric hazard model with discrete-time survival mixture analysis (DTSMA) in our study of data drawn from 70 countries from different economic sectors and geographic regions. Both approaches use control variables to capture observed heterogeneity. The possible relative advantage of DTSMA is its ability to recognize unobserved heterogeneity using latent classes. Failure to account for unobserved heterogeneity can cause underestimation of hazard probabilities; we investigate the change in inferences such an omission may cause. Applying DTSMA to this data set, we find that model parameters have appropriate signs and offer support for all three hypotheses: Relatively falling prices, relatively greater number of competitors, and relatively fewer competing standards are each associated with relatively higher hazard probabilities. In contrast, in the estimation of the fully parametric hazard model, we find that some parameters are wrongly signed, and only one hypothesis, the effect of competing standards, is supported.     

The direct and indirect effects of economic wealth on time to take-off

Our objective is to decompose the influence of the economic wealth on the time to sales take-off into a direct effect and an indirect effect through time to introduction. We use a traditional regression based and an advanced counterfactual framework for our analysis, based on adoption data for four generations of mobile phone from 172 countries. Our study extends the sales take-off literature by better understanding how the commercialization stage (time to introduction) affects the confirmation stage (time to sales take-off) in innovation diffusion while controlling for local market structure, socio-economic, demographic and cultural variables suggested in the literature. We show that economic wealth exerts: a positive direct effect by shortening sales take-off time; a negative indirect effect by shortening time to introduction which tends to extend time to sales take-off. The uncovering of this relationship is achieved by treating time to introduction as a mediating variable, departing from previous studies where it is treated as an exogeneous variable. We further show that the negative indirect effect is diluted in the case of high income countries but not in the case of upper middle-income countries. A sensitivity analysis shows the robustness of our findings. Our findings will help firms develop optimal market entry strategies considering the resources available.     

Modelling and forecasting national introduction times for successive generations of mobile telephony

An accurate prediction of the timing of a country's introduction of a new generation of mobile telephony benefits numerous agents including suppliers of network and consumer equipment, regulators, and network planners. We consider the estimation and prediction of the time interval between the international introduction of a generation of mobile telephony and its introduction into a specific country when a decision maker judges the introduction of a newer technology a worthwhile investment. Using literature-based socio-economic and geographical variables, we examine how well variation in international introduction times of four generations of mobile telephony in 172 countries can be explained and forecast. We model and forecast introduction times at two levels of granularity: we use Cox's proportional hazards model for the introduction time; we partition countries into introduction time-based segments and model segment membership using multinomial logistic regression. Our modelling of each generation considers three subsets of explanatory variables: All variables, socio-economic Covariates only, Regional dummies only. Over successive generations, the Covariates only models reveal the changing relevance of each socio-economic covariate. Model-based forecasting of the introduction time of the next generation is performed under three hypotheses making different uses of the information available at the time the relevant generation is launched internationally. However, changing socio-economic environments coupled with changing models impair forecasting accuracy, the lower accuracy of modelled introduction times is concentrated in 20% of countries. We speculate about the nature of the unobserved factors affecting these countries' decision processes.     

Modelling the dependence between the times to international adoption of two related technologies

The structure of the dependence between the times to adoption by a country of two related innovations, the fax and the cellular telephone, is modelled in two stages. The first stage is the choice of density function for the time to adoption. The second stage is describing the dependence relation. For the first stage, a Weibull density function is used with its scale factor adapted to account for the economic and technological environments in different countries. Environmental data are collected from several sources. Copulas are used to model the dependence relation, three single parameter copulas are considered, those due to Farlie-Gumbel-Morgenstern (FGM), Frank and Plackett. Their properties are described and a combined estimation of the copula and density function parameters carried out. The limitations of the FGM copula rule it out from further consideration. The other copulas coupled with the Weibull, using eight environmental variables, are shown to provide valuable insights into the effects of environmental variables on adoption times. Given that a country has adopted one technology, the model of the dependence relation is used to provide the conditional density of the time to adoption of the other technology.     

Supply Restricted Telecommunications Markets: The Effect of Technical Efficiency on Waiting Times

The paper is concerned with supply constraints in the provision of telecommunications services. As a measure of supply constraint we use the average waiting time for telephone connections. Duration models are employed to analyze a panel data set for 28 countries. In addition to economic variables, we consider the role of technical efficiency in causing supply constraints. Stochastic frontiers are used to determine the technical efficiency with which countries use labor and capital inputs to connect customers. When technical efficiency is included in duration models for waiting times until connection, we find that it is the major determinant.