Arab Open University Consumer Attitude Towards Artificial Intelligence Analysis Write about “An analysis of consumer attitude towards Artificial intelligen

Arab Open University Consumer Attitude Towards Artificial Intelligence Analysis Write about “An analysis of consumer attitude towards Artificial intelligence-enabled Fintech applications” (Exploring Customer Attitudes towards Artificial Intelligence mobile banking chatbots). And the structure of the report will be:

Structure:

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Factors:

Performance expectancy (PE)

H1: Performance expectancy positively influences the behavior intention to adopt AI-Mobile Banking Chatbots.

Effort expectancy (EE)

H2: Effort expectancy positively influences the behavior intention to adopt AI-mobile banking chatbots in Oman

Social influence (SI)

H3: Social influence positively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman

Facilitating conditions (FC)

H4: Facilitating conditions positively influence the behavioral intention to adopt AI-mobile banking chatbots in Oman

Hedonic motivation (HM)

H5: Hedonic motivation positively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Price value (PV)

H6: Price value positively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Habit (HT)

H7: Habit positively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Trust

H8: Trust positively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Perceived risk

H9 Perceived risk negatively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Technology Anxiety

H10: Technology anxiety negatively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Resistance to change

H11: Resistance to change negatively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Perceived reliability

H12: Perceived reliability negatively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Brand image (BI)

H13: Brand image positively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

H14: Self-efficiency positively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Perceived substitution crisis

H15: Perceived substitution crisis negatively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Government Support

H16: Government support positively influences the behavioral intention to adopt AI-mobile banking chatbots in Oman.

Reference

Note that:

I’ve uploaded attachments related to this report named “Conceptual model_1” and “UTAUT 2 model”.

*** Words count = 5000 words.

*** In-Text Citations and References using APA style.

*** I’ve uploaded attachments related to this report named “Conceptual model_1” and “UTAUT 2 model”.

*** Also an attachment have been uploaded named “Problem statement”. Perceived
substitution crisis
(PSC)
Performance
expectancy (PE)
Effort expectancy
(EE)
Government
Support (GS)
H15
H1
H16
H2
Social influence
(SI)
H3
Facilitating
Conditions (FC)
H4
Hedonic
Motivation (HM)
Behavioral intention towered
adopting Artificial Intelligence
Mobile Banking chatbots
H5
H6
Price value
(PV)
H7
Perceived
Credibility
Habit
(HT)
H8
Promotion
Trust
H9
(TR)
Perceived risk
Awareness of
services
H10
(PR)
Technology
Anxiety (TA)
Resistance to
change (RG)
Responsiveness
H11
Existing degree of
satisfaction
H12
Perceived
Reliability (PR)
Personalization
H13
Brand image
(BI)
Perceived
Security
H14
Self-Efficiency
(SE)
User
innovativeness
Problem statement
The modern financial solutions are regularly seeking to broaden their technologies, both to
improve customer service and rise delivery of services through the improvements in technology.
And this is to acquire competitive edge over other banks for economic advantages and to expand
its consumer base. Moreover, there is an obvious difference in the service level customers desire,
and the actual standard they currently receive; a service gap that leading banks hope to fill and
improve with the implementation of AI (Hoikkala & Magnusson, 2017).
The current implementation of AI, in the form of IA mobile banking chatbots and virtual
assistants in the banking sector, spawns a new field of research into customer attitude towards AI
as a form of customer service. Despite the potential of this new technology, there are always
barriers to overcome. Change and innovation is not always immediately embraced by customers,
and resistance is in many cases seen as a normal response to a change in customer practices and
habits (Ram, 1987,n Jonsson, S. and Bredmar, J., 2018). Customer resistance is therefore one of
the main reasons as to why change might not be fully received (Garcia, Bardhi, & Friedrich,
2007). In order to reduce the possible risk of failure for services or products, potential factors or
determinants of customer resistance have to be identified (Jonsson, S. and Bredmar, J., 2018)
Existing research tends to investigate customer attitudes in regard to already established online
banking services, where scholars have studied factors concerning attitude formation, adoption,
and acceptance. However, it seems that the implementation of AI into banking services is an
understudied field, and one could argue that a research gap exists. Therefore, this study aims to
bridge the gap between customer service in the banking industry and the adoption of AI.
Hopefully, this study will provide new knowledge on the factors that influence customer
attitudes with regard to the further digitalization of customer service in the banking sector.
Innovation spend in the financial space remains to be high, driven by the ever before raising
requirement for extra efficient financial services. In today’s competitive banking landscape,
client assumptions on response/turnaround times are increasing at a rate that huge banks are
having a hard time to overtake, compared to their brand-new generation peers. Customer-bank
call networks are also greatly turning towards the electronic platform. Despite this digital
change, consumers still need to depend heavily on lengthy phone and also IVR systems for even
basic financial query as well as procedures. Banks are looking to leverage developments in
technology such as artificial intelligence to minimize the time for client purchases right from the
application phase to debt disbursement as well as collections.

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