Mohini Agarwal

Unified approach for modeling innovation adoption and optimal model selection for the diffusion process

Purpose - – Mathematical modeling of innovation diffusion is a constantly evolving field within marketing science. The diffusion process explains the dispersion of an innovation among potential buyers. Prior research on innovation diffusion has been based on modeling varied aspects of real life situations in marketing. One such aspect is studying the adoption process depending on the awareness and motivation level among the customers. Awareness is having knowledge of an innovation, whereas motivation is about the perception of an individual. In line with these aspects, the purpose of this paper is to propose a unified modeling framework for the adoption process based on the awareness and motivation about the product. Design/methodology/approach - – When the market is well informed about the product, there are some people who are motivated and some, who have adopted the product earlier and shall now influence others in their buying behavior. It is very much similar to queuing system in which some units are waiting in a queue for the service, service for some units are being processed and some units have already been served. This analogous behavior between two approaches has motivated the use of infinite server queuing theory in modeling adoption of the product. Thereafter, the authors have proposed a unification scheme to model different market scenarios. Findings - – From analyzing the values of comparison criteria, it was not clear that which among them is performing best. Thus there was a need for an approach which can judiciously find the optimal model. For this very purpose the authors applied distance-based approach which was capable of computing the optimal model based on the distance of attribute value from the optimal. The analysis performed on two real life sales data sets depict that model in which awareness is following logistic pattern and motivation and adoption are following a constant pattern is ranked one. Research limitations/implications - – The idea has been validated on product. It would be interesting to know how the methodology works on service. Originality/value - – The modeling framework discussed in this paper can be helpful to know from the available set of alternative, which among them is performing better in capturing the spread of the product in the market. The proposed framework offer some managerial guidance by highlighting the unusual aspects of diffusion process and also present an approach to judge the best among a set of different models.

Generalized Innovation Diffusion Modeling & Weighted Criteria Based Ranking

Research in the field of innovation diffusion has been based on modeling and understanding the differing behavior of adopters in marketplace. The acceptance of innovation depends upon how the information about the product has diffused in the social system. During products life cycle, adoption of the product takes place in the following manner; first the information about the product reaches the potential buyers and then from informed buyers the adoption takes place. First process can be termed as Product Awareness Process (PAWP) and the later one can be termed as Product Adoption Process (PADP). In this paper, we propose a generalized approach for innovation diffusion modeling that takes care of product awareness process and product adoption process as two separate scenarios (studied jointly) before the product is eventually bought by the user. Convolution of probability distribution function has been used to make the distinction between two processes. Furthermore, a set of five comparison criteria have been formulated and each criteria has been assigned different weights to rank the proposed models. Validation is done on two different consumer durables and results show that the weighted criteria approach is a very capable methodology for models comparison.

Modeling adoption process based on awareness and motivation of consumers

The existing product development environment has been changing into new development paradigms at a tremendous rate. This requires firms to be more market driven and conscious for successfully bringing an innovation in the market. Innovation acts as a key carrier of success for any organization, when an innovation is accepted to its full extent and is used by the potential adopters, it is termed as successful innovation. An understanding of adoption process helps developers to promote their product more proficiently. The adoption process is a sequence of stages before a potential adopter goes for its purchase. Thus an innovation has to undergo different stages of adoption before it is finally adopted by the consumers; this differentiation forms the main aspect of the paper. Here we have considered adoption as a three stage process in which firstly people become aware of an innovation then, some are positively motivated, and from them the adoption takes place. The three stages have been classified as Product Awareness, Positive Motivation and the Eventual Adoption. The new modeling framework is analyzed on different consumer durables and inferences are quite astonishing.

Optimal Introduction Timing Policy for a Successive Generational Product

Globalized economy has led firms to introduce new innovations in the market quite frequently. Optimal Introduction time is an important strategic decision for firms because an early introduction may not take off as customers; channel members and other required partners might not be receptive enough, on the other hand too late an entry results in loss of opportunity for the firm. The decision is even more critical when introducing successive generations over time. In this study, the authors have developed an analytical approach to help decide the optimal introduction time for successive generational product. The timing decision depends on whether firms push the product to market before competitors or invest more time in process & product design and improvement. The authors have examined the case where a firm introduces successive generations of a durable product for which demand is characterized by an innovation diffusion process. Results are supplemented by a numerical example.

OPTIMAL RELEASE TIME DECISION FROM FUZZY MATHEMATICAL PROGRAMMING PERSPECTIVE

Demand for high software reliability requires rigorous testing fol- lowed by requirement of robust modeling techniques for software quality pre- diction. On one side, firms have to steadily manage the reliability by testing it vigorously, the optimal release time determination is their biggest concern. In past many models have been developed and much research has been devoted towards assessment of release time of software. However, majority of the work deals in crisp study. This paper addresses the problem of release time predic- tion using fuzzy Logic. Here we have formulated a Fuzzy release time problem considering the cost of testing under the impact of warranty period. Results show that fuzzy model has good adaptability.

Remanufacturing: An Industrial Strategy for Economic Benefits

A successful new product development (NPD) always requires a well-defined, systematically planned, coherently organized, and cost effectively executed strategy along with the objective to satisfy customers. Supply chain management (SCM) is one conquering approach that integrates all resources for these activities into an endeavor that maximizes the positive impact on customers. Therefore, a competent supply chain management (SCM) is well-adequate tangible way to influence customers through their performance regarding time and place. Moreover, reverse logistic supply chain (RLSC) is a closed-loop chain that works as ‘Double Dividend’ for the company in terms of generating economic and environmental benefits. With this study, we have demonstrated that the concept of remanufacturing of products leads to more economical and sustainable benefits for the manufacturer fraternity. To explain the concept, we have proposed a methodological cost modeling framework that is based upon the diffusion of new product wherein; we have considered two different scenarios pertaining to remanufacturing phenomenon. The proposed framework has been validated on real-life sales data set pertaining to automobile industry.

Queuing theory-based innovation diffusion modelling incorporating change in adoption rate

Adoption has always been an important process to discuss among marketers. Major work in the field of innovation adoption has been based on theory of first purchase by consumers. Of late attention has also been given to multi-stage nature of diffusion process. There are practitioners who have verified adoption as multi-stage process (depending on awareness and motivation). Researchers have lately also understood the value of change in marketing strategy and other factors that often lead to change in the rate of adoption. In this paper, we have made use of this stage wise approach of market penetration along with change point concept, have developed a methodical approach based on infinite server queuing theory and predicted sales for consumer durables. Experimental results estimated on sales of two different consumer durables show that present proposal can depict the change in adoption rates and predict the behaviour of the product in more accurate manner.

Innovation diffusion modeling considering the time lag between awareness and eventual adoption

Purpose - Today, a firm’s major concern is to know the way in which an innovation is adopted in the marketplace. The purpose of this paper is to focus on the two-stage nature of diffusion process in which the time lag between people being informed and their act of making final purchase is considered. Design/methodology/approach - The paper discusses an approach based on the time lag for modeling awareness and adoption process as two separate and yet connected processes. Varying forms of time lag (constant, deterministic or random) have been considered while modeling the required framework. Furthermore, an equivalence approach has been shown between the present framework and the two well-known and established approaches of infinite queuing theory and hazard rate function. Findings - The results are verified on sales data of two different consumer durables and it show good prediction capability of proposed models in capturing the real-life scenario. Further, the equivalence approach helps us to quantify such scenarios which were difficult to be modeled with any one particular approach. Further, the possibility of capturing different market scenarios by studying various distribution functions has been identified. Research limitations/implications - The proposed methodology is based on a two-stage adoption process. The same can be extended to a multi-stage adoption process as in today’s competitive environment. “Motivation” is one such factor that is highly important which can be considered in some later studies. In future, the authors wish to study the multi-stage adoption process considering the different forms of time lag function. Practical implications - The equivalence approach discussed in the paper can help to cater the possibility of capturing different market scenarios by studying various distribution functions. Originality/value - The proposed approach helps to cater the time lag between awareness and adoption process and develop different mean value functions to account for the manner in which sales are happening under different circumstances. The proposed methodical approach can also help decision makers in managing their available resources in a prudent manner.

A discrete innovation diffusion model incorporating change in the adoption rate

New products play a significant role in the success of firms concerned with the introduction of innovative products. Mathematical modeling that can describe the life cycle of these products can provide major contribution in their successful diffusion. The Bass model of innovation diffusion is a main representative of the diffusion models. Many modifications have been made to the model since its development to answer the changing needs and limitations. The model was developed in continuous time, which limits its application on many real life applications having discrete time data. Due to this reason a discrete version of this model was proposed by another author Hirota. The model was based on Riccatis equation in mathematics. Although the model can be solved to exact solution but it is difficult to modify this model further and solve to get the exact solution. Further, in practice the pace of diffusion varies not only because of the life cycle phase but due to many other variations such as changes in advertising strategies, little product modifications, competitive products etc. In marketing this concept can be termed as change point. In the present article, we propose an approach to model the diffusion process using a discrete logistic function whose exact solution can be obtained using probability generating function (PGF), incorporating the aforesaid change point concept. The model is validated on the real life data sets. Therefore, the proposed model provides accurate parameter estimates, making it possible to predict when a product can be launched.