Prerna Manik

Differential Evolution Approach to Promotional Effort Allocation in Segmented Market for Multi-period Promotion Strategies in a Planning Horizon Incorporating Repeat Purchase

Promotional efforts play very important role in determining success of a product in the market. These efforts voice product qualities and help it establish relationship with consumers. Decisions pertaining to promotional effort allocation must be taken with enormous care as promotional effort expenditure is essential to produce sales by transforming potential customers from the state of unawareness to that of action. But at the same time product life cycle is small and the promotional resources are limited. So these resources must be used judiciously. In this paper, we examine the problem of optimal allocation of promotional effort resources among distinctive market segments under budgetary and minimum aspiration level constraints where the market is subject to repeat purchasing. The planning horizon is divided into multi time periods and the adoption pattern is studied in each period. The parameters of sales growth repeat purchase model are re-estimated using all the available sales growth data for each segment at the beginning of each time period. The new allocation problem is re-formulated and using the new estimates, promotional allocations are determined for the next period till we reach end of the planning horizon. The non-linear programming problem so formulated is solved using differential evolution which stands as a powerful tool for solving search and optimization problems. A numerical example has been discussed to illustrate the applicability of the approach.

Dynamic promotional allocation for multi-products in segmented market under first and repeat purchase behaviour

Promotion plays a vital role in influencing consumer behaviour in favour of the firms offerings culminating into product trial/adoption/repurchase. Sparse promotional effort resources and shortened product life cycles require that decisions related to promotional effort allocation must be taken judiciously and objectively. In this paper, we formulate and solve an optimisation problem of promotional resource allocation for the multi products of a product line sold across distinctive market segments. The problem is formulated using a diffusion model allowing repeat purchase under budgetary and minimum sales aspiration level constraint on each product under consideration and solved using differential evolution approach. In order to allocate resources dynamically the total planning horizon is divided into multi periods. Resources are re-allocated in each period to each product under consideration in each market segment after analysing the current adoption pattern and market potential. Model applicability is shown with the help of a numerical illustration.

Multi Stage Promotional Resource Allocation for Segment Specific and Spectrum Effect of Promotion for a Product Incorporating Repeat Purchase Behavior

Promotion plays an important role in determining fate of a product. It voices product qualities and persuades potential customers to make purchases. In todays diversified markets every customer has individual needs and preferences. This calls for market segmentation which facilitates companies to adopt customer driven marketing. Product is also promoted using mass promotion to influence larger markets and segments with a spectrum effect. Existing literature in promotion resource allocation optimization evades distinction in two types of promotion strategies while allocating resources and primarily focuses on either of them statically. In this paper, we formulate an optimization model which dynamically allocates differentiated and mass promotional resources in segments to maximize sales under budgetary and minimum market share aspiration constraint on each segment as well as on total market share including repeat purchase behavior. Planning horizon is divided into multi-periods, adoption pattern is studied in each period and then resources are allocated attuned to current market behavior. Dynamic allocation provides a way to track the market potential expansion due to promotion and plan the allocation for the uncaptured potential. The proposed optimization model is NP hard and very challenging to solve. Solution methodology is presented with practical application based on real-time data using differential evolution algorithm.

A Goal Programming Model for Advertisement Selection on Online News Media

Promotion plays an important role in determining success of a product/service. Out of the many mediums available, promotion through means of advertisements is most effective and is most commonly used. Due to increasing popularity of the Internet, advertisers yearn for placing their ads on web. Consequently, web advertising has become one of the major sources of income for many websites. Several websites provide free services to the users and generate revenue by placing ads on its webpages. Advertisement for any product/service is placed on the site considering various aspects such as webpage selection, customer demography, product category, page, slot, time, etc. Further, different advertisers bid different costs to place their ads on a particular rectangular slot of a webpage, that is, many ads compete with each other for their placement on a specific position. Hence, in order to maximize the revenue generated through the ads, optimal placement of ads becomes imperative. In this paper, we formulate an advertisement planning problem for web news media maximizing their revenue. Mathematical programming approach is used to solve the problem. A case study is presented in the paper to show the application of the problem.

Dynamic Testing Resource Allocation of Modular Software System for SRGM Incorporating Testing Efficiency Using Differential Evolution

Software reliability engineering has recently been playing a rapidly increasing role in the industry. This has occurred because it carefully plans and guides development and test so that software developing team develop a more reliable product faster and cheaper. Practically, a software testing process consists of several testing stages. A project manager should know how to allocate the specified testing resources among all the modules and develop quality software with high reliability. In this paper, we investigate an optimal resource allocation problem in modular software systems for flexible Software Reliability Growth Model (SRGM). The optimization model proposed for optimal allocation of testing resources among the modules of software subject to budgetary constraint is formulated and solution is obtained using Differential Evolution which stands as a powerful tool for solving search and optimization problems. The allocated testing resources for each of the modules are utilized to detect and remove the faults. The parameters are re-estimated using all the available fault detection data for each of the modules. The new allocation problem is re-formulated and allocation of testing resources for each of the modules is obtained. The process is terminated either the desired level of faults are removed from each of the modules or specified number of iterations is exhausted. The above problem has been discussed using numerical example to illustrate the applicability of the approach.

A Goal Programming Model for Selection and Scheduling of Advertisements on Online News Media

Digital revolution has resulted in a paradigm shift in the field of marketing with online advertising becoming increasingly popular as it offers the reach, range, scale and interactivity to organizations to influence their target customers. Moreover, web advertisement is the primary revenue stream for several websites that provide free services to internet users. The website management team needs to do a lot of planning and optimally schedule various advertisements (ads) to maximize revenue, taking care of advertisers’ needs under system constraints. In this paper, we have considered the case of news websites that provide news to its viewers for free with ads as the primary source of their revenue. The considered news website consists of many webpages with different banners for advertisement. Each banner consists of different number of partitions and cost per partition varies for different rectangular banners. Many ads compete with each other for their placement on a webpage on a specific banner, based on partition requirement, at specific time interval(s). Here, we have formulated a mixed integer 0–1 linear programming advertisement scheduling problem to maximize the revenue over planning horizon divided into time intervals under various system and technical constraints. A case is presented to show the applicability of the model. Branch and bound integer programming and goal programming techniques have been used to solve the formulated problem.

OPTIMAL PRICING AND PROMOTIONAL EFFORT CONTROL POLICIES FOR A NEW PRODUCT GROWTH IN SEGMENTED MARKET

Abstract : Market segmentation enables the marketers to understand and serve the customers more effectively thereby improving company’s competitive position. In this paper, we study the impact of price and promotion efforts on evolution of sales intensity in segmented market to obtain the optimal price and promotion effort policies. Evolution of sales rate for each segment is developed under the assumption that marketer may choose both differentiated as well as mass market promotion effort to influence the uncaptured market potential. An optimal control model is formulated and a solution method using Maximum Principle has been discussed. The model is extended to incorporate budget constraint. Model applicability is illustrated by a numerical example. Since the discrete time data is available, the formulated model is discretized. For solving the discrete model, differential evolution algorithm is used. Keywords : Market segmentation, price policy, promotional effort policy, differentiated market promotion effort, mass market promotion effort, optimal control problem, maximum principle, differential evolution algorithm. MSC : 34K10, 49J15, 49K15, 49M25, 68Q25, 93B40, 68T20.

Optimal Promotional Effort Control Policy for Segment Specific New Product Growth

We have incorporated the concept of market segmentation in the mixed influence diffusion model to study the impact of promotional effort on segment specific new product growth, with a view to arrive at the optimal promotional effort rate in a segmented market. Evolution of sales rate for each segment is developed under the assumption that practitioner may choose both differentiated market promotional effort and mass market promotional effort to influence the sales in unsaturated portion of the market. Accordingly, we have formulated the optimal control problem incorporating impact of differentiated market promotional effort as well as mass market promotional effort on sales rate for each segment, where mass market promotional effort influences each segment with a fixed spectrum. We have obtained the optimal promotional effort policy for the proposed model. To illustrate the applicability of the approach, a numerical example has been discussed and solved using differential evolution algorithm.