HRMM81 Assignment 1 2026
THE INFLUENCE OF HYPER-CONNECTIVITY, PERCEIVED USEFULNESS,
PERCEIVED EASE OF USE, AND TRUST ON CONSUMERS' BEHAVIOURAL
INTENTION TO USE AI-DRIVEN CHATBOTS
1.1 INTRODUCTION
Artificial intelligence (AI) is changing marketing in a big way. One common example is
AI chatbots, which many businesses use to talk to customers. These chatbots can
answer questions, suggest products, and give help at any time of the day or night
(Brandtzaeg & Følstad, 2017). However, even though chatbots are widely used, many
people do not continue using them. Some users stop after the first time, while others
prefer to speak to a real person. Because of this, it is important to understand what
makes people want to use AI chatbots.
The Technology Acceptance Model (TAM), introduced by Davis (1989), explains that
people are more likely to use technology if they find it useful and easy to use. Although
this model is widely used, today’s digital world requires some updates. People are now
always connected to the internet, using multiple devices and expecting quick responses
(Freeman & Hill, 2021). This constant connection may change how people see and use
AI tools like chatbots. Also, trust is very important. People want systems that are
reliable, work well, and protect their personal data. In fact, concerns about data privacy
may be even more important than how easy the system is to use.
, This proposal outlines a study that investigates the combined influence of hyper-
connectivity, perceived usefulness, perceived ease of use, and trust on consumers’
behavioural intention to use AI-driven chatbots. It means integrating hyper-connectivity
and trust into the TAM framework, the research aims to deliver a more nuanced
understanding of chatbot adoption. The proposed study will be set in South Africa, a
market where digital transformation is accelerating but where consumer trust in
technology remains complex. The following sections present the background, problem
statement, research objectives, and a brief methodological conclusion.
1.2 BACKGROUND OF THE STUDY
The Rise of AI-Driven Chatbots in Marketing
Chatbots are software applications that simulate human conversation through text or
voice (Gnewuch, Morana & Maedche, 2017). Powered by natural language processing
and machine learning, modern chatbots can understand intent, learn from interactions,
and personalise responses. For marketers, they offer scalable customer engagement,
cost reduction, and rich behavioural data. For consumers, they promise convenience,
speed, and constant availability. However, actual usage rates often lag behind
corporate enthusiasm. Research indicates that users may initially try chatbots but revert
to human channels if they perceive the bot as incompetent, difficult to use, or
untrustworthy (Mozafari, Weiger & Hammerschmidt, 2021).
Theoretical Foundation: The Technology Acceptance Model
TAM has become a cornerstone in information systems research. Perceived usefulness
(the belief that a technology will enhance performance) and perceived ease of use (the
belief that using the technology will be effortless) are proposed to influence behavioural
intention, which in turn predicts actual use (Davis, 1989). Later extensions (TAM2,
UTAUT) incorporated social influence and facilitating conditions. However, in an AI
context, the model’s parsimony may overlook key psychological and contextual factors.
THE INFLUENCE OF HYPER-CONNECTIVITY, PERCEIVED USEFULNESS,
PERCEIVED EASE OF USE, AND TRUST ON CONSUMERS' BEHAVIOURAL
INTENTION TO USE AI-DRIVEN CHATBOTS
1.1 INTRODUCTION
Artificial intelligence (AI) is changing marketing in a big way. One common example is
AI chatbots, which many businesses use to talk to customers. These chatbots can
answer questions, suggest products, and give help at any time of the day or night
(Brandtzaeg & Følstad, 2017). However, even though chatbots are widely used, many
people do not continue using them. Some users stop after the first time, while others
prefer to speak to a real person. Because of this, it is important to understand what
makes people want to use AI chatbots.
The Technology Acceptance Model (TAM), introduced by Davis (1989), explains that
people are more likely to use technology if they find it useful and easy to use. Although
this model is widely used, today’s digital world requires some updates. People are now
always connected to the internet, using multiple devices and expecting quick responses
(Freeman & Hill, 2021). This constant connection may change how people see and use
AI tools like chatbots. Also, trust is very important. People want systems that are
reliable, work well, and protect their personal data. In fact, concerns about data privacy
may be even more important than how easy the system is to use.
, This proposal outlines a study that investigates the combined influence of hyper-
connectivity, perceived usefulness, perceived ease of use, and trust on consumers’
behavioural intention to use AI-driven chatbots. It means integrating hyper-connectivity
and trust into the TAM framework, the research aims to deliver a more nuanced
understanding of chatbot adoption. The proposed study will be set in South Africa, a
market where digital transformation is accelerating but where consumer trust in
technology remains complex. The following sections present the background, problem
statement, research objectives, and a brief methodological conclusion.
1.2 BACKGROUND OF THE STUDY
The Rise of AI-Driven Chatbots in Marketing
Chatbots are software applications that simulate human conversation through text or
voice (Gnewuch, Morana & Maedche, 2017). Powered by natural language processing
and machine learning, modern chatbots can understand intent, learn from interactions,
and personalise responses. For marketers, they offer scalable customer engagement,
cost reduction, and rich behavioural data. For consumers, they promise convenience,
speed, and constant availability. However, actual usage rates often lag behind
corporate enthusiasm. Research indicates that users may initially try chatbots but revert
to human channels if they perceive the bot as incompetent, difficult to use, or
untrustworthy (Mozafari, Weiger & Hammerschmidt, 2021).
Theoretical Foundation: The Technology Acceptance Model
TAM has become a cornerstone in information systems research. Perceived usefulness
(the belief that a technology will enhance performance) and perceived ease of use (the
belief that using the technology will be effortless) are proposed to influence behavioural
intention, which in turn predicts actual use (Davis, 1989). Later extensions (TAM2,
UTAUT) incorporated social influence and facilitating conditions. However, in an AI
context, the model’s parsimony may overlook key psychological and contextual factors.
