Independent research

AI, commerce & consumer behaviour.

I'm Emmanuel Asika. I'm exploring how artificial intelligence changes the way people shop online, the decisions they make and the way retailers serve them.

Proposed study

Cloud-Based AI in E-commerce: Effects on Consumer Trust, Purchase Decisions and Retail Practices

The study will examine how cloud-based AI recommendations and shopping assistants influence consumer trust and decision-making, alongside their implications for retail operations. The aim is to understand where these tools help, where they create friction and how their effects vary across shoppers and shopping contexts.

My perspective combines MBA study in Cloud Computing with practical experience building e-commerce websites and digital products. The questions and methods below describe a proposed study; they are not a report of completed findings.

Research questions

  1. How do shopping decisions change?

    Examine how AI recommendations and conversational assistants affect product discovery, comparison, decision time and purchasing intention.

  2. What earns or weakens consumer trust?

    Explore how recommendation accuracy, explanations, privacy concerns and familiarity with AI influence trust, confidence and reliance on automated advice.

  3. How are retail practices adapting?

    Investigate retailers’ experiences of adopting AI for customer support and personalisation, including changes in workflows, skills and operating costs.

Proposed study design

A mixed-methods approach will connect consumer experiences with retailer perspectives. Scope and instruments will be refined before data collection.

Literature review
Map existing evidence on AI adoption, consumer behaviour and digital retail. Identify where findings differ across technologies, shopping contexts and research methods.
Consumer survey
Study shoppers’ experiences of AI tools, perceived usefulness, trust and privacy concerns. Define the target population and sample size as part of the final study protocol.
Controlled shopping experiment
Compare conventional search and filters with AI-assisted shopping using the same catalogue, prices and product information. Measure product choice, task time and confidence, and distinguish stated purchase intention from observed purchasing behaviour.
Retailer interviews
Use semi-structured interviews to understand reported changes in customer service, personalisation and adoption costs. Analyse these accounts alongside the consumer findings.

Participant research will use informed consent and follow applicable research ethics and data-protection requirements. Analysis will distinguish associations from causal effects and state the limits of the sample and study setting.

Planned outputs

A research report, a manuscript for potential publication and reproducible analysis code are the intended outputs. Where participant consent and data-protection requirements permit, supporting materials may include survey instruments and anonymised or aggregate data. Future outputs and updates will be linked from this page.

Selected reading

Existing studies informing the proposed research.