Adarsh Anand

Consumer behaviour-based innovation diffusion modelling using stochastic differential equation incorporating change in adoption rate

Bass innovation and diffusion model and many of its extended forms have been reported in marketing literature and applied successfully for predicting adoption curve of products from different segments of market. All these models assume that an adopter buys the product only once in his lifetime, however, this may not be true, because a consumer might buy the product more than once for his utility (repeat purchasing). Also, there can occur a situation that the consumer leaves the system without buying the product (balking). In this paper, we propose a diffusion model based on Ito’s type of stochastic differential equation with repeat purchasing and balking. It also incorporates the change-point concept, where the rate of product adoption per remaining potential adopter might change due to shift in marketing/promotional strategy, entry/exit of some of the competitors in the market. The applicability of the proposed model is illustrated using new product sales data.

A multi-attribute approach for release time and reliability trend analysis of a software

In a Software Development Life Cycle the testing phase is given a lot of importance. But testing cannot be done indefinitely due to many reasons ranging from marketing considerations to increase in cost. Hence it is pertinent to find the optimal release time during testing phase. Firms routinely face the challenging decision of when to stop testing and release the product in the market. It has been observed that the pace of introduction of new software is much higher in recent years in comparison to any time in the past. Thus to get the competitive edge it is critical to know about the optimal entry time. Too late an entry is likely to lead to significant loss of opportunity. On the other hand early introduction of a product might hinder its growth due to lack of receptiveness of users towards new technology. Many release time problems with optimization criteria like cost minimization, reliability maximization and budgetary constraints etc. have been discussed in the literature. The release time problem discussed in this paper depends on the combined effect of cost and the Failure Intensity function; therefore we formulated an optimal release planning problem based on multi-attribute utility theory. A numerical illustration is provided towards the end of the paper. Furthermore, a trend line for the reliability of software has also been plotted to show the behaviour of reliability.

A stochastic formulation of successive software releases with faults severity

Software companies are coming with multiple add-ons to survive in the pure competitive environment. Each succeeding up-gradation offers some performance enhancement and distinguishing itself from the past release. If the size of the software system is large, the number of faults detected during the testing phase becomes large, and the number of faults, which are removed through each debugging, becomes small compared to initial fault content at the beginning of the testing phase. In such a situation, we can model the software fault detection process as a stochastic process with continuous state space. In this paper, we propose a multi-release software reliability growth model based on Itôs type of differential equation. The model categorizes Faults in two categories: simple and hard with respect to time which they take for isolation and removal after their observation. The model developed is validated on real data set.

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.

Fault severity based multi-release SRGM with testing resources

In today’s environment of global competition where each company is trying to prove itself better than its competitors the software developers have to come up with multiple releases in order to survive in the market. Each release offers some innovative performance enhancement or some new functionality that distinguishing itself from the past release. But enhancing the product and upcoming with successive releases puts a constant pressure on even the best organized engineering organizations. The reason being, up-grading a software application is a complex process. Upgrading a software introduces the risk that the new release will contain a bug, causing the program to fail. Therefore, to capture the effect of faults generated in the software with multiple releases, we have developed a multi release software reliability model in this paper. The model uniquely takes into account the faults of the current release and the remaining faults of just previous release. The multi release software reliability growth model treats the fault removal rate as a function of testing resources consumed. In addition, the model also incorporates the severity of faults and considers that hard faults are removed with different rate than the rate required to remove simple faults. The model developed is validated on real data set with software which has been released in the market with new features four times.

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 Price and Warranty Length for Profit Determination: An Evaluation Based on Preventive Maintenance

Warranty is a two-sided coin: on one hand, it results in additional cost to the producer, and on the other hand, it acts as a protectional tool for buyers. To deal with this additional cost (cost of repairing faulty items), preventive maintenance during the warranty period often plays a helping hand to the manufacturer. The role of preventive maintenance is therefore important, as it slows down the rate of system degradation. In view of this, the current study presents an analytical approach to determine the optimal profit for the firm, where sales price and warranty length act as key decision variables under the impact of preventive maintenance provided by the firm. The two-dimensional innovation diffusion model has been utilized to estimate the sales, and Weibull distribution has been used to represent the lifetime distribution of the product. To validate the accuracy of the proposed framework, numerical illustration has been provided for analysis done on real-life sales data set.

Diffusion Modeling Based on Customer's Review and Product Satisfaction

The purpose of this paper is to determine the internal/external factors that lead to fluctuation in marketplace. Before introducing new products in the market, organization needs proper understanding of the market which can be realized through sound mathematical modeling and scientific decision making tools. The objective is as follows: market size is determined by the number of customers a product is flanked by; therefore, it becomes critical to understand satisfaction of demanders as one of the metric for measuring performance of the product. In this paper, the authors have discussed how the adoption takes place in accordance with the market fluctuation. For this purpose, they have developed four different methodical frameworks to help the management to estimate sales due to varying behaviour of market as per reviews about the product. Analysis and validation has been done on two different real life datasets. Weighted Criteria Value Approach WCVA has been applied to rank the models by using several goodness of fit collectively.