Dynamic Forecasts of New Product Demand Using a Depth of Repeat Model

1973 ◽  
Vol 10 (2) ◽  
pp. 115-129 ◽  
Author(s):  
Gerald J. Eskin
Keyword(s):  
Data Analysis ◽  
New Product ◽  
Consumer Products ◽  
Product Demand ◽  
Forecasting Models ◽  
Estimation Procedures ◽  
New Consumer

A depth of repeat model is presented that can forecast the demand for new consumer products. The relation of the model to other forecasting models is noted. Data analysis, estimation procedures, and the observed accuracy of forecasts are discussed.

The Effects of Sampling Variation on Sales Forecasts for New Consumer Products

1976 ◽  
Vol 13 (2) ◽  
pp. 138-143 ◽  
Author(s):  
Robert Shoemaker ◽  
Richard Staelin
Keyword(s):  
Sampling Error ◽  
General Procedure ◽  
New Product ◽  
Consumer Products ◽  
Actual Data ◽  
New Product Introductions ◽  
Sales Forecasts ◽  
Sampling Variation ◽  
New Consumer

A general procedure is outlined for estimating the sampling error in sales forecasts of new nondurable consumer products. The technique is illustrated for the Parfitt and Collins model with actual data from four new product introductions.

Dogmatism and Acceptance of New Products

1970 ◽  
Vol 7 (4) ◽  
pp. 483-486 ◽  
Author(s):  
Brian Blake ◽  
Robert Perloff ◽  
Richard Heslin
Keyword(s):  
New Products ◽  
New Product ◽  
Consumer Products ◽  
Personality Characteristics ◽  
New Consumer ◽  
The Relationship

A two-category typology of new consumer products was used to investigate the relationship between consumer personality characteristics and acceptance of new products. It was found that the influence of a consumer's dogmatism upon his acceptance of new products was mediated by the type of new product presented.

Application of Statistical Analysis Tools and Concepts to Big Data and Predictive Analytics to New Product Development

2020 ◽  
Vol 3 (1) ◽  
pp. 17-35
Author(s):  
Brian J. Galli
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Product Development ◽  
Competitive Advantage ◽  
New Product Development ◽  
New Product ◽  
Big Data Analysis ◽  
Life Cycles ◽  
The Impact

In today's fiercely competitive environment, most companies face the pressure of shorter product life cycles. Therefore, if companies want to maintain a competitive advantage in the market, they need to keep innovating and developing new products. If not, then they will face difficulties in developing and expanding markets and may go out of business. New product development is the key content of enterprise research and development, and it is also one of the strategic cores for enterprise survival and development. The success of new product development plays a decisive role both in the development of the company and in maintaining a competitive advantage in the industry. Since the beginning of the 21st century, with the continuous innovation and development of Internet technology, the era of big data has arrived. In the era of big data, enterprises' decision-making for new product development no longer solely relies on the experience of decision-makers; it is based on the results of big data analysis for more accurate and effective decisions. In this thesis, the case analysis is mainly carried out with Company A as an example. Also, it mainly introduces the decision made by Company A in the actual operation of new product development, which is based on the results of big data analysis from decision-making to decision-making innovation. The choice of decision-making is described in detail. Through the introduction of the case, the impact of big data on the decision-making process for new product development was explored. In the era of big data, it provides a new theoretical approach to new product development decision-making.

Dynamics of New Product Campaigns

1964 ◽  
Vol 28 (4) ◽  
pp. 60-63
Author(s):  
Harlan D. Mills
Keyword(s):  
New Product ◽  
Consumer Product ◽  
Consumer Reactions ◽  
New Consumer ◽  
Product Promotion

Introducing a new consumer product on a nationwide basis is much like playing a game of stud poker. Consumer reactions early in the campaign, when sufficiently well understood, can provide vital clues in accelerating or cutting off product promotion as required for maximum impact to corporate objectives.

Landslide data analysis using various time-series forecasting models

2020 ◽  
Vol 88 ◽  
pp. 106858 ◽  
Author(s):  
Akarsh Aggarwal ◽  
Mohammed Alshehri ◽  
Manoj Kumar ◽  
Osama Alfarraj ◽  
Purushottam Sharma ◽  
...  
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Forecasting ◽  
Forecasting Models ◽  
Landslide Data

Consumption attitudes and adoption of new consumer products: a contingency approach

2008 ◽  
Vol 42 (1/2) ◽  
pp. 238-254 ◽  
Author(s):  
Guangping Wang ◽  
Wenyu Dou ◽  
Nan Zhou
Keyword(s):  
Consumer Products ◽  
New Consumer ◽  
Contingency Approach

Backward ideation technique for generating new product ideas

1983 ◽  
Vol 8 (2) ◽  
pp. 95-114 ◽  
Author(s):  
O.A. Mascarenhas ◽  
S. J.
Keyword(s):  
New Product ◽  
Consumer Products ◽  
Market Opportunity ◽  
Product Idea ◽  
Attribute Space ◽  
Comprehensive Coverage

This paper reviews briefly new product idea generating techniques, and suggests another one, the backward ideation technique, that starts from existing successful or unsuccessful brands, and works its way backward, in looking for synergistic ideas andgaps that can offer new market opportunity for new brands and products. This technique is illustrated using two consumer products, toothpaste and footwear, the first with a smaller set of competing brands, the second with a multitude of types and varieties. In both cases it is found that the backward ideation technique affords a comprehensive coverage of the attribute space of each product, and provides a shortcut for arriving at new product designs and brands via new synergistic gaps unearthed in the process of backward ideation.

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