scholarly journals Marketing decision making using sentiment score with co-extracting opinion target words from reviews

2021 ◽  
Vol 1055 (1) ◽  
pp. 012074
Author(s):  
T M Saravanan ◽  
T Kavitha ◽  
S Hemalatha ◽  
Gourav Kumar
Keyword(s):  
Decision Making ◽  
Marketing Decision ◽  
Sentiment Score ◽  
Target Words

Judgment Based Marketing Decision Models: Problems and Possible Solutions

1981 ◽  
Vol 45 (4) ◽  
pp. 13-23 ◽  
Author(s):  
Dipankar Chakravarti ◽  
Andrew Mitchell ◽  
Richard Staelin
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Laboratory Experiments ◽  
Field Studies ◽  
Decision Models ◽  
Future Research ◽  
Marketing Decision ◽  
Recent Laboratory

This paper presents a comparative analysis of the findings of two field studies and three recent laboratory experiments that assessed the efficacy of judgment based models in aiding marketing decision making. This analysis indicates factors that may affect the effectiveness of these models. The implications of the findings for users of judgment based marketing decision models as well as model builders are discussed, and suggestions are made for future research to improve the models’ effectiveness.

Managerial Judgment in Marketing: The Concept of Expertise

1983 ◽  
Vol 20 (2) ◽  
pp. 110-121 ◽  
Author(s):  
Jean-Claude Larréché ◽  
Reza Moinpour
Keyword(s):  
Decision Making ◽  
Delphi Process ◽  
Group Consensus ◽  
Marketing Decision ◽  
Decision Calculus ◽  
External Measure ◽  
True Values

Judgment-based estimations often are used in marketing decision making and as inputs to decision calculus models. An evaluation of different approaches to integrating individual judgments is performed in the context of a marketing situation where the “true” values being estimated are known. Experts identified by a simple external measure of expertise are found likely to provide better estimates, followed by groups participating in a Delphi process. Experts identified by self-rated confidence and interpersonal group consensus are not found likely to provide better estimates than the average of the initial judgments of the members of a group.

The Delphi Process in Marketing Decision Making

1971 ◽  
Vol 8 (4) ◽  
pp. 443-448 ◽  
Author(s):  
Marvin A. Jolson ◽  
Gerald L. Rossow
Keyword(s):  
Decision Making ◽  
Field Experiment ◽  
Delphi Process ◽  
Subjective Probabilities ◽  
Marketing Decision

This article describes a field experiment which uses the Delphi Process to assign subjective probabilities to the set of possible demand levels for a company's product. The method is validated by the use of questions to which the “correct” answers are known.

Time and Outcome Valuation: Implications for Marketing Decision Making

1991 ◽  
Vol 55 (4) ◽  
pp. 54-62 ◽  
Author(s):  
John C. Mowen ◽  
Maryanne M. Mowen
Keyword(s):  
Decision Making ◽  
Marketing Decision

scholarly journals Artificial intelligence (AI) in strategic marketing decision-making: a research agenda

2020 ◽  
Vol 33 (2) ◽  
pp. 183-200 ◽  
Author(s):  
Merlin Stone ◽  
Eleni Aravopoulou ◽  
Yuksel Ekinci ◽  
Geraint Evans ◽  
Matt Hobbs ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Public Sector ◽  
Review Literature ◽  
Strategic Marketing ◽  
Sensitive Data ◽  
Content Type ◽  
The Public ◽  
Marketing Decision ◽  
The Face

Purpose The purpose of this paper is to review literature about the applications of artificial intelligence (AI) in strategic situations and identify the research that is needed in the area of applying AI to strategic marketing decisions. Design/methodology/approach The approach was to carry out a literature review and to consult with marketing experts who were invited to contribute to the paper. Findings There is little research into applying AI to strategic marketing decision-making. This research is needed, as the frontier of AI application to decision-making is moving in many management areas from operational to strategic. Given the competitive nature of such decisions and the insights from applying AI to defence and similar areas, it is time to focus on applying AI to strategic marketing decisions. Research limitations/implications The application of AI to strategic marketing decision-making is known to be taking place, but as it is commercially sensitive, data is not available to the authors. Practical implications There are strong implications for all businesses, particularly large businesses in competitive industries, where failure to deploy AI in the face of competition from firms, who have deployed AI to improve their decision-making could be dangerous. Social implications The public sector is a very important marketing decision maker. Although in most cases it does not operate competitively, it must make decisions about making different services available to different citizens and identify the risks of not providing services to certain citizens; so, this paper is relevant to the public sector. Originality/value To the best of the authors’ knowledge, this is one of the first papers to probe deployment of AI in strategic marketing decision-making.

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