1.
Mobile Commerce

2.
E-commerce:
Commonly Knowns as Electronic Marketing.
It consist of buying and selling goods and
service over the internet.
E-commerce is the Purchasing selling and
exchanging goods and service over computer
network(internet) through which transaction
or terms of sales are performed Electronically.

3.
M-commerce:
Mobile commerce is also known as M-
commerce is a form of E-commerce.
M-commerce is the buying ad selling of goods
and service through wireless handheld
devices.
M-commerce is the process of paying for
services using a mobile phone or personal
organizer.

4.
Differences

5.
Services and Applications:
Mobile ticketing
Mobile money transfer
Content purchase and delivery
Information and services.
Mobile Banking
Mobile Browsing
Mobile marketing and advertisement.

6.
Literature Reviews Improve Accuracy of
Prediction of User’s Mobile-Commerce Future
Behavior
• The proposed MCP framework consists of three modules, 1)
Mobile network database, 2) data mining mechanism, and 3)
a behavior prediction engine. The detailed information of
store including its location will be store into mobile network
database. System has an “offline” mechanism for PMCPs
mining, and an “online” engine for mobile commerce
behavior prediction. When mobile users move between the
stores, the mobile information which includes user
identification, stores, and item purchased are stored in the
mobile transaction database.

7.
Literature Reviews
• In the offline data mining mechanism, we develop algorithm named as PMCP Mine
to find out user’s m-commerce patterns. When a mobile user moves and
purchases items among the stores, the next steps will be predicted according to
the mobile user’s identification and recent mobile transactions. The framework is
to support the prediction of next movement and transaction. 1) Support Only (SO)
2) Integrated Support & Matching Length (ISM) 3)Integration of Support &
Confidence (ISC).

8.
Sentiment Analysis Method:
• Sentiment analysis is an automated process that
determines the emotional tone behind a message.
• Sentiment analysis is powered by natural language
processing (NLP) and machine learning (ML)
algorithms. These artificially intelligent bots are
trained on millions of pieces of text to detect if a
message is positive, negative, or neutral.
• Sentiment analysis works by breaking a message
down into topic chunks and then assigning a
sentiment score to each topic.

9.
Sentiment Analysis Process

10.
Result & Analysis
• From online survey from google foam almost we take
response from 40 customers which is involve using
M-commerce applications. In this survey almost 55%
peoples are between 23 to 27 years and 50%
customer education are bachelor. From our survey
84% customer are used smartphone from access M-
commerce sites and customer almost 45% are used
very less time almost 1 hour in M-commerce
occasionally and mostly customers are engaged with
M-commerce 2 – 3 years and almost 31% are spend
5,000 per month and 73% customers are voted
Daraz.pk is mostly used M-commerce in Pakistan

11.
Result & Analysis
• According to our survey almost 55.3% customers voted agree
and 31.6% voted strongly agree and 5.3% voted Neutrals and
7.9% voted disagree that MCA improved organized shopping’s
• In our survey mostly customers are understand that
scamming, hacking data and fake seller, duplicate parcel, late
seller response and online payment methods are biggest
issues in M-commerce and E-commerce applications. In our
survey mostly customer’s choice saving time, comforts,
cashback and discount offers are factors which influence the
adoption of mobile commerce. In our survey result customers
simple UI, Easy way of process of shopping, not show any ads
on screen, error free application and working fast during high
traffic is influence the adoption of mobile commerce in
usability, simplicity & effectiveness perspective.

12.
Conclusions:
• Today M-commerce is play important role in our daily life it's
become part of our life and mobile commerce are growing day by
day more rapidly and target wider audience. It became necessary
part of life because it’s provide facilities and also provide business
opportunities. In Pakistan M-commerce trend started growing in
pandemic of 2019 and the adoption of M-commerce increasing
year by year now peoples are adopt this trend to avoid felling
behinds. Our survey also suggest that the peoples are show intent
to using M-commerce applications from shopping, banking, food
delivery and transaction purpose. Online scam, frauds, fake
products and security problems are biggest issues that’s is reported
from customers sides but overall customers are satisfy from service
and product provided by M-commerce applications and according
to reports 6.9% retail transaction take place through mobile in 2022
and predict that m-commerce will account for 10.4% of all retail
income by means of 2025.