Estimation Of Market Potential Research Articles

The Evaluation of Trade Area Models and Analysis Methods for Site Selection from International Quick Service Restaurants Perspective

International quick service restaurants (QSRs) have become a stand-alone sector due to their significant market share throughout the world instead of being considered under the food and beverage sector. The success of QSR site selection is directly related to land use and market potential estimation. This relationship has a significant influence on urban texture, identity and cities' development processes, given the high number of QSRs in urban spaces. Diverging from the current retail sector dynamics, the QSR sector brings to the table different needs in terms of trade area characteristics and spatial characteristics. In this respect, the aim of this research is to conduct an analysis on the site selection decisions of international QSRs and to establish a conceptual framework for an applicable model. Accordingly, first, the relationship between trade area analysis and site selection of international QSRs is examined. After that, trade area models of The Proximal Area Model, Reilly's Law of Retail Gravitation Model, Central Place Theory, Huff Model, Analog Model and Geographic Interdependence Model are discussed according to their competence of QSRs’ site selection. Then they are analytically evaluated within the framework of today's economic, social and spatial development variables. Finally, Regression Analysis Methods and Geographical Information Systems (GIS), which are encountered in literature and used in practice are examined, and a new theoretical framework for a site selection model integrating Regression Analysis Methods and GIS is proposed.

Site Selection of Retail Shops Based on Spatial Accessibility and Hybrid BP Neural Network

The increase of consumer income has resulted in the rapid development of the retail industry in China, which provides high market potential for retail companies worldwide. However, site selection for retail shops has been a confusing business issue in practical business decisions. In this study, a two-step hybrid model in site selection for small retail shops was proposed. The two steps were spatial accessibility evaluation and market potential estimation. The spatial accessibility of target regions was evaluated based on the improved gravity model to determine regions that lack retail shops. Then, a PCA (principal component analysis)–BP (backpropagation network) model was established to estimate the market potential in the target regions. The two-step model could determine sites with the most market potential and low competition. We conducted the experiment in Guiyang, China and considered 18 socioeconomic factors to make the site selection convincing. Through the experiment, 42 locations were determined with high business value; the locations were recommended to the new retail shops. The accuracy of the PCA–BP model was then proven satisfactory by comparing it with other regression methods. The proposed model could guide retail chains in enhancing business location planning and formulating regional development policies.

Market Potential for Residential Biomass Heating Equipment

This paper provides estimates of market potential for biomass-residential-heating equipment in the US: that is, the greatest amount of biomass-residential-heating equipment that can be sold by the industry. The author's analysis is limited to biomass equipment used most to heat the housing unit. Assuming that households equipped with 10+ year old primary heating devices will replace rather than repair the devices he predicts that approximately 1.4 million units of residential home heating equipment will be replaced in 2015. The author's research also shows that customers do not ascribe much value to biomass home heating. The marketing implication for such a “negative” state is to find buyers who greatly value the benefits of biomass heating equipment.

Quantification of the energy efficiency gap in the Swedish residential sector

We present a method for quantifying the energy efficiency gap ex-ante. To do this we define the energy efficiency gap as being the difference between the ex-ante market and techno-economic energy savings potentials. The estimation of market potential is based on top-down (econometric) modelling of energy demand using data from the period 1970–2005. The techno-economic estimates are made using a bottom-up building stock model (ECCABS), to assess the effects and cost-efficiency of various energy efficiency measures. Common to these two modelling approaches are two scenarios of energy prices, which differ only with respect to the carbon tax component. We implement the method for the case of useful energy demand for space and water heating in the Swedish residential sector up to 2030. In comparison to the level of energy use in 2005 (74 TWh), the top-down model predicts for 2030 reductions in demand for the two price scenarios of 17 TWh and 21 TWh, respectively. The bottom-up model predicts corresponding reductions in demand of 25 TWh and 31 TWh, respectively. Thus, there is an energy efficiency gap between the two models of at least 8 TWh in 2030. An implicit discount rate of 10% would render the results from the bottom-up modelling identical to those from the top-down modelling. However the presence of the energy efficiency gap indicates that there is a need for enhanced policies in order to make future reductions in energy demand reach the levels predicted by the bottom-up modelling.

Market demand estimation for new product development by using fuzzy modeling and discrete choice analysis

Market demand estimation is an important process to assess the financial feasibility of new product development (NPD) projects. The development of models for market demand estimation involves market potential estimation and choice modeling. Previous studies commonly used conjoint analysis to develop utility functions which were then used in discrete choice models to generate market share models. The jury of executive opinion method is commonly used in industries wherein a number of experts and/or consultants are always involved in the market potential estimation. However, a high degree of fuzziness always exists in the data obtained from conjoint surveys and the market potential estimation because of the subjective judgments of respondents and experts. However, ignorance of the fuzziness would lead to the over-estimation of market demands. This research aims to tackle the fuzziness associated with market potential estimation and survey data in the development of market demand models. In this paper, a new methodology of developing fuzzy market demand models for NPD is proposed to address the fuzziness by which market demands can be estimated for the worst, normal, and best scenarios. The proposed methodology involves fuzzy choice modeling based on fuzzy regression and discrete choice analysis, and fuzzy estimate generation of market potential. To evaluate the effectiveness of the proposed methodology, a case study of market demand estimation of a new tablet PC is conducted based on the proposed methodology. The results of the implementation are compared with those based on a popular multinominal logit (MNL) based demand model. From the comparison, it can be noted that the estimated market demand based on the MNL model is very close to that for the normal scenario based on the proposed fuzzy demand model. However, the MNL model cannot provide estimates for other scenarios.

English

In this paper, we consider diffusion process of new services in the residential market. We described the main influences and decision factors of new telecommunication services adoption. In order to forecast the adoption of new service, diffusion theory is applied. Building upon the Bass diffusion model, we proposed an innovative approach, which encompasses a new model for residential market potential estimation. Based on such analyses, we performed the forecast of Internet Protocol Television (IPTV) demand in the Serbian market until the end of the year 2012. Such forecast are not only important for the providers introducing the innovation service, but also for all others that provide related services that complement or substitute for the innovation.   Key words: Diffusion theory, forecasting, Internet Protocol Television (IPTV), market potential, operator.

Market Potential Estimation for Tourism in Emerging Markets

The objective of this paper was to develop a useful framework for estimating demand for tourism in emerging markets. Tourism has become one of the most crucial sectors in a large number of emerging countries. Moreover, the tourism industry in such markets is forecasted to keep increasing in the next decade. Hence, understanding and accurately forecast demand in the industry is essential in order to manage this sector effectively. Using stepwise regression analysis, we found a number of im- portant variables in estimating demand for tourism in emerging markets. Our regression model can benefit travel agencies and policy makers dealing with the tourism industry.

Market Potential Estimation in International Markets: A Comparison of Methods

ABSTRACT Marketers use various market potential estimation techniques in international markets. These include method of analogy, proxy indicators, chain ratio method, time series analysis, and multiple regression modeling. This study shows how demand or market potential can be estimated using these methods and compares the findings. The study should be useful to both managers and academics interested in the theory and practice of demand estimation. Although emerging markets and durables are used as examples, the methods discussed are universal and can be applied in any country market.

The role of disqualification factors and double counting in estimating the market potential for consumer services

PurposeThe purpose of this paper is to review issues pertaining to estimating market potential for consumer services which may cause underestimates of market potential and result in inappropriate marketing strategies. Particular attention is paid to the issue of double counting disqualified individuals.Design/methodology/approachThe process of estimating market potential for consumer services is described. Attention is paid to the role of factors that disqualify groups of individuals from inclusion in the relevant market and the problem of double counting disqualified individuals. Secondary data for enlistees in the United States Army are used to illustrate the process.FindingsThe United States Army's estimate of its market potential was approximately twice as large as previous estimates when the double‐counting of disqualified individuals was eliminated.Research implications/limitationsThis is the first study appearing in the academic literature that directly addresses the issue of double‐counting disqualified individuals when estimating market potential. It is intended to raise awareness of the issue and lead to a more thorough coverage of the topic in marketing textbooks and other practitioner‐related materials.Practical implicationsThe process of estimating market potential applies to a broad range of service industries in which the double counting of disqualified individuals is an important issue. More accurate estimates of market potential can lead to more effective marketing strategies and improved allocation of marketing resources.Originality/valueA review of the literature indicates that, surprisingly, no previous studies have addressed these important issues. This article helps to fill that void.

Demand Forecasting for Preventive??AIDS Vaccines

An AIDS vaccine could play a very significant role in reversing the HIV pandemic, saving millions of lives. For a vaccine to have such an impact, it must be widely available and adopted and taken up rapidly in the countries most affected. A demand-forecasting model provides a valuable tool that can guide R&D spending decisions and identify policy actions to help achieve these goals. To identify the key determinants of vaccine demand, model global adoption and uptake dynamics, estimate potential demand and revenues associated with future preventive AIDS vaccines, and to conduct sensitivity analyses to assess the impact of each parameter on demand. A discrete, deterministic, linear, predictive mathematical model based on stratified population averages with a 30-year time horizon was developed to assess scenarios of future demand. This forecasting model was used to explore the effects of vaccine characteristics and a variety of regulatory, political, financial and health service factors on future demand and revenues. The intervention modelled was a preventive AIDS vaccine (efficacy: 30-90%; duration of protection: 3-5 years; in a two-dose prime-boost combination). The main outcome measure was the number of complete courses of vaccine administered. The model suggests that demand for a preventive AIDS vaccine with a medium efficacy (50%) and duration of protection (3 years) would average 68 million courses annually over a 30-year period. Under different scenarios, demand would peak at 38-152 million courses annually. On the basis of tiered pricing across public and private markets ($US2-100 per dose), these levels of peak demand would translate into $US2.5-5.5 billion in peak annual sales revenues. Private markets and high-income countries account for small volumes but large shares of projected revenues, while low-income countries account for large volumes and more modest, but still significant, sales revenues. Vaccinations to 'catch-up' those who are missed or not eligible for routine annual programmes (whether adolescent or high-risk populations) would account for 20-35% of cumulative vaccination courses across all scenarios. Demand was found to be sensitive to vaccine efficacy, duration of protection and price. Efforts to expedite regulatory review processes, improve immunization infrastructure and reduce political constraints could increase demand for an AIDS vaccine by 40 million additional courses a year compared with the medium efficacy (baseline) vaccine forecast. Our model can provide vaccine developers with credible estimates of market potential for an AIDS vaccine, and with a tool that can be used to improve forecasts over time as AIDS vaccine science progresses. It can also help governments to identify and pursue those policies that could best strengthen demand and uptake of a safe and effective preventive AIDS vaccine.

Trade Analysis of Retail and Service Industries in North Dakota for Planning Local Economic Development

Trade analysis of retail and service sectors allows economic development practitioners to evaluate the performance of these sectors in their respective communities. Estimation of market potential identifies specific business categories (e.g., computer stores) that have potential for further growth. Trade analysis of retail and service sectors in North Dakota shows that except in a few urban counties, such as Cass, Grand Forks, or Burleigh, these sectors were inefficient in retaining and attracting customer dollars. Market potential estimation of over 130 specific business categories showed that a considerable number of business categories have potential for further growth, e.g., computer and software stores, used merchandise stores, and heavy construction equipment rental and leasing services.

Forecasting the potential for new industrial products

Industrial marketing managers base new-product decisions and marketing strategy on estimates of market potential. They often evaluate current product sales, market share, and market penetration, using some forecast of market potential as a benchmark. For maximum benefit to marketers, the concept of market potential should be clear, consistent, and highly operational This paper discusses a life-cycle concept of market potential. A simple descriptive model shows how the concept relates to other marketing concepts and how it can be used operationally.

The Bass New Product Growth Model: A Sensitivity Analysis for a High Technology Product

This paper assesses the performance of the Bass New Product Growth Model in forecasting quarterly and annual sales of optical scanning equipment for supermarkets in the U.S. The model is run with both constrained and unconstrained estimates of market potential.