Related Experiment Videos
AI-Augmented marketing decision-making and competitive performance: A resource-based view of capability orchestration
1Management Department, College of Business Administration, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Acta Psychologica
|July 7, 2026
Summary
Artificial intelligence (AI) capability maturity enhances competitive performance by fostering Human-AI Integration and Marketing Agility. This layered development, supported by strong data governance, is key for sustained advantage.
Area of Science:
- Business Strategy
- Marketing Analytics
- Artificial Intelligence
Background:
- Artificial intelligence (AI) is increasingly integrated into marketing decision-making processes.
- The extent to which AI provides a sustained competitive advantage remains an open question.
- Existing research lacks a comprehensive understanding of the mechanisms linking AI capability maturity to competitive performance.
Purpose of the Study:
- To investigate the association between AI capability maturity and competitive performance.
- To examine the mediating roles of Human-AI Integration and Marketing Agility.
- To explore the moderating effect of Data Governance Quality on the Human-AI Integration-Marketing Agility relationship.
Main Methods:
- Survey data collected from 312 marketing and digital leaders.
- Partial Least Squares Structural Equation Modeling (PLS-SEM) used for data analysis.
- Resource-Based Theory and dynamic capabilities perspective guided the theoretical framework.
Main Results:
- AI capability maturity positively influences Human-AI Integration.
- Human-AI Integration positively impacts Marketing Agility and Competitive Performance.
- A serial mediation effect shows layered capability development is crucial, not just technology ownership.
- Data Governance Quality moderates the link between Human-AI Integration and Marketing Agility.
Conclusions:
- AI-enabled value creation depends on complementary integration and adaptive capabilities, extending Resource-Based Theory to intelligent systems.
- Effective AI implementation requires investment in integration routines, governance, and agile marketing processes.
- Psychological factors like trust calibration and interpretability are vital for successful Human-AI collaboration in decision-making.
Related Concept Videos
01:29Impression Management Techniques III: Aligning Actions
Aligning actions are communicative strategies individuals employ to maintain social harmony and preserve personal identity in the face of potential disruptions to social norms. These actions are particularly important in managing social impressions when one's behavior might be seen as inappropriate, incompetent, or morally questionable.Types of Aligning ActionsThe three principal types of aligning actions are disclaimers, accounts, and apologies.DisclaimersDisclaimers are preventive; they are...
01:20Decision Making
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Automatic decision-making is fast, intuitive, and relies on gut feelings...
01:14Impression Management Techniques IV: Altercasting
Altercasting is a strategic communication technique in which an individual imposes a specific identity or social role onto another person to influence their behavior and shape the interaction. By presuming a role—such as “responsible leader” or “patient person”—altercasting encourages the target to conform to that identity, often aligning their behavior with the expectations associated with the role. The power of this tactic lies in its subtlety; once a role is assigned, it becomes socially...
01:09Decision Making: P-value Method
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
01:14Decision Making: Traditional Method
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
01:08The Availability Heuristic
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):