Cited by 193Artificial Intelligence ApplicationsAI in Service InteractionsImpact of AI and Big Data on Business and Society

Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation

Open access
Eriksson, Theresa, Bigi, Alessandro, Bonera, Michelle·2020·The TQM Journal

Abstract

Purpose This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation. Design/methodology/approach Qualitative research based on exploratory in-depth interviews with industry experts currently working with artificial intelligence tools. Findings Key themes include: (1) Importance of AI in strategic marketing decision management; (2) Presence of AI in strategic decision management; (3) Role of AI in strategic decision management; (4) Importance of business culture for the use of AI; (5) Impact of AI on the business’ organizational model. A key consideration is a “creative-possibility perspective,” highlighting the future potential to use AI not only for rational but also for creative thinking purposes. Research limitations/implications This work is focused only on strategy creation as a deliberate process. For this, AI can be used as an effective response to the external contingencies of high volumes of data and uncertain environmental conditions, as well as being an effective response to the external contingencies of limited managerial cognition. A key future consideration is a “creative-possibility perspective.” Practical implications A practical extension of the Gartner Analytics Ascendancy Model (Maoz, 2013). Originality/value This paper aims to contribute knowledge relating to the role of AI in marketing strategy formulation and explores the potential avenues for future use of AI in the strategic marketing process. This is explored through the lens of contingency theory, and additionally, findings are expressed using the Gartner analytics ascendancy model.

Integrity signals

Registry

Crossref · 10.1108/tqm-12-2019-0303

Cites

61 of 61 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

3 of the 64 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Eriksson, T., Bigi, A., & Bonera, M.
Affiliations
  • Luleå University of Technology (SE)
  • University of Verona (IT)
  • University of Brescia (IT)
Corresponding author
Bigi, Alessandro
Venue
The TQM Journal
Publisher
Emerald
Published
2020-04-22
Volume
32
Issue
4
Pages
795-814
ISSN
  • 0954-478X (ISSN-L)
  • 1754-2731
OpenAlex
W3019168338
Cited by
193
References
64
Citations by year
2026: 26 · 2025: 37 · 2024: 59 · 2023: 35 · 2022: 19 · 2021: 15 · 2020: 2
FWCI
6.97
Type
journal article
Language
en
Open access
Locations
  • The TQM Journal (publishedVersion, cc-by)
  • Institutional Research Information System (Università degli Studi di Brescia) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
Keywords
artificial intelligence, marketing strategy formulation, strategic decision-making, organizational culture, organizational models, creative thinking, managerial cognition, contingency theory

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review