Research report.pdf

A Mutual-Aid Intelligent Delivery Service For Indian University
Campuses: An Analysis On The Current Mobility System
Chirasmita Das
Harleen Dhawan
O Lakshmi Prathyusha
Interaction Design, National Institute of Design, Bangalore
Design Research, 2nd Semester
Prof. Mamata N. Rao, Prof. Neha Mandlik
Mar 13, 2023

STUDY ON THE DELIVERY SYSTEMS IN UNIVERSITIES 2
Acknowledgments
We would like to express our gratitude to Prof. Mamata N. Rao and Prof. Neha for their guidance
and support throughout the study. We also extend our thanks to the university of GKVK, IISc,
NIT, and NID, Bangalore for providing us with the necessary resources and facilities to carry out
this research.
We are also grateful to all the survey takers and students who participated in this study by
sharing their valuable experiences during personal interviews and providing us with noteworthy
insights into the current delivery system and general mobility system inside their university
campuses. Their contributions have been invaluable to this research, helping us see beyond the
assumptions at the initial stages of the research.

Table of contents
Abstract 6
Introduction 7
Background study 8
Methodology 8
Pilot Study (phase 1): 10
Aim 10
Objective 10
Research Design 10
Target audience for pilot study 10
Inclusion & exclusion criteria: 11
In-person Interviews - 11
Focus Groups 12
Scenario testing and sketching 13
Co-Design Workshop 14
Conclusion of Pilot Study 16
Research study (phase 2) 16
Aim 16
Objective 16
Research Design 17
Target audience 17
Research questions 17
In-depth Interviews 18
Surveys 20
Visual Ethnography 22
Analysis of data 25
Analysis of the survey results: 25
Data on buying behavior: 26
Codes: 27
Analysis of field study: 30
Analysis of Visual Ethnography : 31
Case Study 1 31
Case Study 2 37
Case Study 3 42
Analysis of in-depth personal interviews and contextual inquiry 45

Empathy mapping tool: 45
Brief of analysis: 46
Journey Mapping For The Current Delivery Systems For Students 47
Importance Of Having An Alternative Method Of mobility Inside Campuses 49
Decision-Making Factors For The Choice Of Conveyance 49
Results and Key Findings 51
The Missing Last Mile 52
Effect on Purchasing Behavior 53
Need for an intelligent (tech-based) shuttle system (The missing first and last
mile) 54
Discussion Section 55
Correlation with other studies and additional insights 55
Behaviors, needs and motivation in current on-campus delivery system 55
Behaviors, needs and motivation in current on-campus mobility system: 56
Perception of short distance travel: 56
Conclusion 57
Limitations and future scope: 58
Limitations 58
Further scope for research 58
Proposal 59
Two-Pronged Approach 59
Design prompts for the mutual-aid technology 59
References 63
Literature review and background study 63
From discussion section 65
Appendix 66
Appendix A 66
Appendix B 66
Appendix C 66
Online survey questionnaire reference 71
Key results of online survey (detailed in analysis section) 73
Key results of in-depth interviews and focus group 75
Field study 76
In-depth interviews, focus groups and co-design workshop 78
Co-Design Workshop 79

Abbreviations
AI - Artificial Intelligence
AV- Autonomous vehicles
ADV - Autonomous Delivery Vehicle
COD - Cash on Delivery
IOT- Internet of things
ML - Machine Learning
SAV - Shared autonomous vehicle
TAM - Total addressable market
SAM - Serviceable Addressable Market
SOM - Serviceable Obtainable Market

Mutual-Aid Intelligent Delivery Service For Indian University Campuses:
An Analysis On The Current Mobility System
Abstract
With an increase in the number of smartphone and internet users in India, early-age adoption of
technology and a change in buying behaviors are observed (“Understanding Consumer Behavior:
Insights” from McKinsey and Forrester, 2021). The convenience and accessibility of online
platforms, especially for students, are a significant part of the online delivery market in India.
However, many campuses do not allow delivery services, which leads to the missing ‘last mile’.
Based on field studies, in-depth interviews, co-design workshops and surveys, the degree of
satisfaction with the current delivery system was determined by understanding the pain points,
needs, behaviors and expectations of the two parties, i.e., students and delivery agents. The
demands, feasibility and requirements on the missing tech-based ‘last-mile’ delivery service
on campus are also studied by other methods like visual ethnography and contextual in-quiry
and the obtained qualitative data was analyzed with journey maps of touch points and
empathy mapping tools.
Our research revolved around understanding the current system as well as feasibility and
requirements to adapt to a new tech-based system. In addition to the delivery service, the need
for smooth on-campus mobility services is also highlighted in the study which also suffers from
the first and last mile problem.
Implementing a sustainable and efficient delivery service, along with an optimized mobility
service, will not only benefit the young generation but also promote the growth of the
e-commerce economy. Ultimately, our study emphasizes the importance of addressing the
evolving needs of university students and adapting to the changing landscape of the
e-commerce industry.

Introduction
The delivery system is an essential service in a university campus that caters to the needs of
students and other members of the campus community. However, the current delivery system in
the Indian context faces various challenges that hinder its effectiveness and efficiency. In this
study, we aim to investigate the current delivery system inside a university campus in the
Indian context and identify patterns and correlations among different variables. Ultimately,
identify the pain points of the current system and understand the needs, behaviors, and
expectations of the two parties, i.e., students and delivery agents, and explore the feasibility and
requirements for a mutual-aid intelligent delivery service for the university students.
To achieve our objectives, we conducted field studies, in-depth interviews, participatory
workshops, and surveys to determine the degree of satisfaction with the current system. There is
a gap in traditional models, which are incapable of meeting the needs for optimized pick-up,
delivery, segregation, storage, and distribution.
(Discussed at length in analysis section)
In addition to the previous study, the study highlights the hassle of a missing mile in the context
of mobility inside the campus from one point to the another and the challenges faced by the
traditional shared shuttle services in the current mobility service. Thus, our study not only
identifies the issues with the current delivery system but also proposes solutions to enhance the
campus delivery service and the overall mobility service.
Background data analysis offers suggestions on how the delivery system can be made more
effective with intervention of intelligent technology like drone-based systems, automated
delivery, and other IOT-based systems. In the research the demands on the missing tech-based
‘last-mile’ delivery service on campus are also studied.

Background study
Literature review on a mutual-aid delivery system in Indian university campuses is essential for
understanding the potential of last-mile delivery solutions in this context. The review highlights
the need for efficient and sustainable delivery systems, particularly given the growth of
e-commerce and the demand for short distance travel.
Additionally, background data analysis offers suggestions on how the delivery system can be
made more effective with intervention of intelligent technology like drone-based systems,
automated delivery, and other IOT-based systems. The integration of such technologies in the
delivery system could help to address the challenges of last-mile delivery in Indian university
campuses.
Furthermore, in the research, the demands on the missing tech-based ‘last-mile’ delivery service
on campus are also studied, which could provide valuable insights into the potential of
mutual-aid delivery systems in this context. Overall, the literature review highlights the
potential of mutual-aid delivery systems incorporating intelligent technology for optimizing
the system of doorstep delivery service by bridging the existing gap of last-mile in Indian
university campuses.
( Refer Appendix A for literature review )
Methodology
A series of systemic steps were utilized to accurately define the scope and context of our
research, followed by a combination of methods to gather relevant data. The research study
began by exploring the broader topic of short-distance mobility, specifically addressing the
transportation needs for first and last mile travel within a larger context. Through a pilot

study, we obtained valuable insights that helped to narrow down our research focus to a more
relevant and necessary direction.
The approach was mainly qualitative with methods like in-depth interview, field study through
contextual inquiry and visual ethnography, participatory workshop, scenario testing and was
supported with a quantitative approach of questionnaire based survey.
Our methodology for this research involved the following steps:

Pilot Study (phase 1):
An initial pilot study was conducted with this demographic in order to test out hypotheses for the
requirement and feasibility of mobility systems for short distances (first and last mile transport)
in an urban context.
Aim
Perception and expectations of Indian urban youth for short distance mobility (first and last mile)
in an urban context.
Objective
To explore young people's attitudes, beliefs, and expectations toward short distance travel.
Research Design
Target audience for pilot study
The total number of participants in the pilot phase of this study were 40. Since the broader scope
of our research was mobility for first and last mile in an urban context we pin-pointed the key
users who are most affected. Further classification of the demographic led to a target audience of
urban youth of an age range of 18 to 30 years old. We consolidated our focus group to be
college students in an urban setting, more specifically the city of Bangalore.

Inclusion & exclusion criteria:
Urban youth falling in the age group of 18-30, who frequently use public mobility services
within the city and for short distances around their college campus. The key reasons for this
sample were:
● Migrated students who are new to the city for educational purposes.
● Economic capabilities of students as they are not able to afford personal vehicles.
● Frequent commute group.
Urban youth owning a personal vehicle and not very frequent commuters will not be considered.
In-person Interviews -
Duration - 15 minutes
Participants - 8 people
[Study protocol material is provided in appendix section]
A heterogeneous pool of urban youth with varying levels of technical knowledge were chosen at
random for qualitative interviews. The questions were open ended and aimed to investigate
people’s perception of the concept of “short distance” and their pain points faced due to the
same. The questions investigated peoples’ frequency of mobility of short distances, their modes
and reasons for transportation, their pain points and perceptions regarding it. The participants
were even questioned on their speculation and perception on technological interventions to solve
the problem. This led to unique findings such as :
- The urban youths’ perception of short distances did not quantify the distance our
assumption for last mile mobility. A recurring pattern was their perception of 5-10
kms as a short distance.
- Majority of the youth did not mind the 1-2 km last mile travel between places or from

public services. A large number of them preferred walking or used other means of
transport.
- A large number of participants determined the need for last mile mobility in the case of
carrying goods and luggages.
- Many participants revealed that they did not think new-age technological advancements
would accurately function in the current urban Indian context with the existing level of
infrastructure and capabilities.
Focus Groups
Duration - 30-45 minutes
[Study protocol material is provided in appendix section]
Two focus groups were conducted with six participants in each group. The groups consisted of a
homogenous pool of urban youth (college students) of two different levels of technical
knowledge. Similar to the in-person interviews, open-ended questions were asked to the
participants about their frequency of mobility of short distances, their modes and reasons for
transportation, their pain points and perceptions regarding it. They were questioned on their
speculation and perception on technological interventions to solve the problem. This resulted in a
group discussion on the above points with the following results.
- The group discussions resulted in voicing multiple opinions on the matter which had
certain effects. It influenced personal perceptions of the participants in the groups which
in certain cases, led to an identical final viewpoint. It also left some participants unable
to address a conflicting opinion.

- The findings in perception were similar to the in-person interviews. Considering the
urban context of the city of Bangalore, due to its traffic and congestion, many participants
felt that 5-10 kms or 45 min of travel could be considered a short distance.
- As for the topic of last mile mobility, many people preferred walking as a change of
pace from constant idleness or did not feel an extreme need for an intervention in the
current setting.
- Similar concerns about the present infrastructure conditions hindered acceptance of
advanced technological interventions for first and last mile travel.
Scenario testing and sketching
The purpose of this research design was to gain insight into the participants' speculative
perceptions regarding the preferred mode of mobility for short distances, specifically in an
urban context. Participants were given ten minutes to conceptualize their mode of mobility on a
blank sheet of paper. This was not a problem since the sample participants were students at a
design college. Below are the results.

- A common theme visualized in the sketches were compact sizes allowing for singular or
couple passenger transport.
- A certain number of sketches envisioned an autonomous system of driving, while some
of them depicted allowances for storage and carrying goods.
- Several sketches were based on a public system of transportation on a fixed
short-distance path in a selected area.
Co-Design Workshop
A co-design workshop was formulated to understand the urban youths’ perceptions on what
quantifies a short distance and the mobility systems they utilize for such distances. A
common map, familiar with the targeted participants, was created with frequently traversed short
distances with a minimum of 500 mts to a maximum of 5 kms. Icons were placed to map the
mobility systems they used to travel different distances. Long range forecasting and narration
were applied to understand the participants’ thought process while placing their icons.
Map depicting frequently traveled places around NID Campus within 5 kms.

Icons used to map their preferred mobility method.
- The research method did not pan out as planned as the participants tended to map out
their usual mode of travel rather than their preferred. Since they were used to a
certain mode of convenience, they did not find it very bothersome.
- A large number of participants did not mind walking short distances such as the last
mile between homes and metro stations.
Conclusion of Pilot Study
The results from the pilot study pointed at three key factors to take into consideration.
● Last mile travel for short distances such as 1-2 km was not very problematic for our
participants.
● Mobility measures for last mile travel were required for special case scenarios such as
luggage or goods to carry, bad weather as well as collection and drop-off of parcels and
delivery.
● New technologies in public mobility systems would be feasible in controlled
environments and not in the current unstable infrastructure and social conditions.

Research study (phase 2)
Based on the findings from the pilot study, the research question was refined to address a more
pertinent and unseen problem related to short distance mobility. The second phase of the research
intended to understand the pain points regarding the last mile of pickup and delivery of
e-commerce packages and ordered goods in a controlled environment such as university
campuses.
Aim
Perception of Indian students on adoption of technology for the last mile delivery and
distribution of goods in large educational campuses.
Objective
Exploratory research intended to seek the pain points, needs, behaviors and expectations of the
two parties i.e., students and delivery agents towards delivery systems inside campuses and the
intervention of technology.
Research Design
Target audience
The total number of participants in phase two of the study was 85. Since our context was defined
to controlled environments, specifically Indian University campuses, our target audience
were students and facilitators within the campus, as well as the delivery agents. There was a
large range of variation in the size of campuses chosen, as well as the user group of students

who hailed from them. Our participants included students who were currently enrolled in
universities as well as students who had graduated. (maximum 3 years prior)
Research questions
RQ1
What are the pain points in the current traditional delivery system for online packages inside
university campuses, in an Indian context?
Sub questions:
Needs, expectations, beliefs and expectations from both the parties (Delivery agents and
students)
Touch points of the service and betterment
Willing to adapt to a new technology or a service
RQ2
What are the feasibility and requirements for implementing a mutual-aid intelligent delivery
service for university students, and how does it compare to the current delivery system?
RQ3
What are the perceptions, beliefs and attitudes of students on adoption of a mutual-aid
intelligent delivery service for university students, and how does it compare to the current
delivery system?
RQ4
Based on the researched data, a demand for a better tech- based on-campus mobility service was
highlighted.
What are the pain points in the traditional shared shuttle services in the current mobility system.
Sub questions:
Needs, behaviors, expectations and motivations of primary users.

Most common modes of transportation and nature of environment
Factors influencing the choice
RQ5 - Future scope
highlighted
How can technology such as machine learning, artificial intelligence, and predictive analytics be
used to optimize the delivery service for university students?
In-depth Interviews -
The participants for the in-person interviews consisted of a heterogeneous group of students
from Indian Universities varying in sizes (1 acre to 1000 acres) as well as climatic and terrain
conditions. The interview method consisted of a mix of in person interviews and telephonic
interviews for a set of 11 questions. The questions were open ended and aimed towards gathering
qualitative data on users current system of delivery and distribution within their campuses and
their pain points. The set of questions is as follows.
1. What institutions have you been part of and how big were the campuses?
2. What were the weather conditions and terrain of the institute like?
3. How frequently did you receive ordered packages and of what kind?
4. Were the delivery partners allowed inside the campus? How did you collect the
packages? Could you talk us through the journey?
5. How convenient was the delivery system? What were your problems regarding it, if any?
6. How secure was the system? Has your delivery ever gotten lost, missing or canceled due
to a timing/ navigation problem?

7. Who takes responsibility in case of a mishap? Is it the delivery agent, company or
college? Or no one.
8. Would you be comfortable receiving packages through an automated delivery
technology? If yes, what kind of packages? (food, FMCG medicines, electronics, books,
groceries etc)
9. What are your concerns regarding this? What problems would you like it to resolve?
10. What features would you like this automated delivery service to have?
11. Would you like it to cater to any other needs other than delivery?
- From the interviews, we learned that in a lot of campuses delivery partners were
allowed inside but until a selected gathering point where they would wait for the
students to drop off or pick up their packages.
- These exchange systems were allotted to specific times during the day. This required
students to plan well in advance. It also required the delivery partners to stay for long
durations within the campus with the packages.
- The users did not prefer to order expensive electronics or items via e-commerce systems
in such a scenario for fear of safety and uncertainty.
- A pertinent problem of in-campus mobility flexible to the users schedule and activities
arose through the survey, especially for students in large campuses.
(Discussed at length in the Analysis section)

Surveys
A google forms survey was conducted with 50 participants of students currently enrolled in
Indian residential university campuses, or graduates within the past 3 years. The survey
consisted of 12 multiple choice and yes/no questions with a few of them requiring one statement
answers. The survey aimed to understand the quantitative data regarding the delivery systems
within large campuses and find any outliers. The questions were similar to the in-person
interview questions and enquired about the current context of mobility, distribution and delivery
across a large range of campuses. The questionnaire was as follows;
1. How big was/is your campus (approximate acres of land) - MCQ
2. Was/is it a residential campus? YES/NO
3. Were/are the delivery partners allowed inside the campus? YES/NO
4. What was/is the system in place for the distribution of delivered packages within the
campus? (e.g. Amazon, Zomato, Myntra package etc.) - MCQ
5. If not, please specify how you collect the package. - STATEMENT
6. How frequently did/ do you receive packages on the university campus? - MCQ
7. How convenient is the system for delivery of such packages? (5 being very convenient) -
MCQ
8. How secure would you rate the current system for delivery of such packages? (5 being
very secure) - MCQ
9. Have you had an incident where your package went missing, got lost or got canceled due
to a navigation/timing problem? - YES/NO
10. Did an untimely delivery of the package disturb your schedule? (e.g. when you were
attending a class). - STATEMENT
11. What type of goods would you be comfortable receiving via an automated delivery
technology? - MCQ
12. What is your most common mode of payment for online delivery? - MCQ

- 60% of the respondents hailed from residential campuses of size 50 acres and above.
- Significantly less number of respondents were able to collect their parcel at the
doorstep ( discussed at length in the Analysis section). Most of them had to obtain it
from the main gate or from a designated delivery spot.
- There were fixed timings to collect and drop off packages. Due to such restrictions, most
users tended to order packages around once a month.
- Students had to plan in advance to pick up their ordered packages by either asking a
friend to pick it up for them or having to excuse themselves from class.
- Some insights regarding the buying behaviors have been discussed at length in the
Analysis section.

Visual Ethnography
Duration - 3 hours each
Participants - 3 campuses
A visual ethnographic study was conducted in 3 different large Indian University campuses of
varying sizes and context. The campus layout, its mobility systems, entry and exit points, high
density points, delivery and pick-up mechanism, as well as location and proximity of the
residential areas were studied. Students' movement and behavior patterns during their daily
routine and while collecting or dropping-off their e-commerce packages were observed. The time
and duration of activities were noted and its frequency was enquired. Comparison between the
data collected from the three campuses provided rich qualitative data about the delivery and
distribution systems in place.
Case Study 1
College of Agriculture, Bengaluru at Gandhi Krishi Vigyan Kendra
Part of University of Agricultural Sciences, Bangalore
Campus size - 1300 acres
No of students - 800 students (600 undergraduate students and 200 masters and phd students.)
Campus Layout - The residential blocks are in close proximity to the academic and canteen
buildings. The research blocks are located a little farther away and the agricultural fields are in
the campus outskirts. The distance from the main entry point to the residential blocks is over
1 km.
Characteristics - Agricultural university where students are immersed in a slow-paced
environment. The students prefer walking as a mode of mobility within their campus. This is
aided by the campus greenery and comfortable weather of the city of Bangalore. Due to the large
size of the campus, external vehicles are permitted entry which poses a problem to the residential
students.

Case Study 2
National Institute of Technology, Tiruchirappalli, Bangalore
Government undergraduate, postgraduate and doctoral University
No. of students - 5000 (3500 undergraduate students and 1500 masters students)
Campus Layout - The campus is linear in layout. It is spread across 540 acres with the rest of the
space left as barren land. It has 5 main blocks and 2 residential units.

Case Study 3
Indian Institute of Science, Bangalore
Government-deemed university for higher education and research in science, engineering,
design, and management.
No. of students - 5023 students
Campus Layout - The campus layout is non linear and spread out across 440 acres.
Characteristics -IISc is the premier institute for advanced scientific and technological research
and education in India. Here the students are immersed in a hustle-culture. The students prefer
owning a personal ( 2-wheeler) vehicle or cycle as a mode of mobility within their campus. It is a
residential campus with all the facilities inside the university.
The results of visual ethnography and key highlights of this research are discussed in the
Analysis section.

Analysis of data
The research gave insights on the pain points, needs, behaviors, motivation and expectations
of the two stakeholders in the current scenario of the delivery system inside a university campus,
i.e. the delivery agents and the student ordering the package through online service.
Analysis of the survey results:
The survey involved around 48 participants. Participants were students in nature and from
various colleges across the country (refer to appendix c). It was sampled randomly from different
cities (tier 1, tier 2, tier 3) and different personas of participants with varying
socio-cultural-economic backgrounds.
The questionnaire designed for the survey ( detailed in methodology section, presented in
Appendix C ) aims to find the data for allowance of delivery agents inside campus, convenience,
needs, and pain points of the current system, preferences, and expectations. The data collected is
as follows:
Are delivery agents allowed inside the campus?

What is the current system in place for delivery and distribution of goods?
X axis: Responses of participants about current system
Y axis: % of sample
Data on buying behavior:
How frequently did/ do you receive packages on the campus?
X axis: Responses of participants
Y axis: % of sample

Most comfortable mode of payment
Codes:
The open ended questions in the survey revealed the following common themes:
- Weather, location, environmental aspect
- Schedule and time
- Safety and security
- Convenience and friction to use
- Hedonic motivation
For a delivery agent they looked like:
- Navigational issues
- Ease of service
- Customer details (spotting the customer, accuracy)
- Safety and security
- Language barrier
- Physical health
- Hedonic motivation

How did the students feel about the current system?
-

How did the delivery agents feel about the current system?
Data table showcasing the qualitative data point from the sample.

Analysis of field study:
The field study involved around 45-50 participants from 3 different universities in Bangalore,
India. The field study involved contextual in-quiry on site and visual ethnography. The
participants were sampled randomly, the personas of participants were varying in
An urban campus tends toward vertical connectivity, whereas a rural campus tends toward
horizontal connectivity and is more automobile-dependent. Rural campuses often include
sloped areas, with rugged terrains and unpaved, unpredictable pathways.
Weather conditions such as temperature, humidity, and precipitation are also important factors
that influence the mobility patterns within the campus. These Factors have inhibited
wide-spread adoption of bicycle and pedestrian friendly policies. Although campus shuttle bus
services are typically provided, they encounter the ﬁrst and last mile problem, due to which
students are often found preferring to walk than go through the hassle of it.
Overall, the field study observed the following through:

Analysis of Visual Ethnography :
Case Study 1
College of Agriculture, Bengaluru at Gandhi Krishi Vigyan Kendra
Part of University of Agricultural Sciences, Bangalore

The Existing System for Delivery Service Within The Campus :
The campus, being a large 1300 acres in size, has several departments and hostels with separate
security for each block. The system of delivery works in a way such that over time, with the

growing use of e-commerce and online food delivery, the delivery agents have been permitted
inside the campus, only till the hostel gate. Students have to leave hostel premises or walk from
their respective department buildings to collect their packages from the delivery agents.
The agents often have to wait around 30 min to hand over the packages, which comes across as
a hassle and inefficient for the delivery agents. In case the students are not available to pick up
the package by hand, they drop off the packages at the hostel security room.
For the students, this situation is not just a hassle to walk till the gate at the time of delivery, but
also a cause of discomfort for girls, especially in the case of night time.
The Existing System for Mobility Within The Campus :
● On average, students walk 4 km to and from various buildings inside their campus
everyday.
● Distance from the main gate to the hostels and classroom is 1 km.

● Distance between classrooms and laboratories is around 600 mts.
● Field studies take place more than 1 km away from campus.
Due to the socio-cultural background of most students and the slow paced life of the campus,
most students do not mind traversing such large distances by walk.
After walking, the cycle is the next most commonly used mode of transport.
The reasons of preference of these modes was also investigated (detailed below)
The key reasons of preference of these modes:
Data collected through contextual inquiry, visual ethnography and interviews -
- Availability and frequency is too low
- Poor time efficiency - Wait time is high
- Stops and pickups for these shuttles are not well planned, hassle of
- first and last mile
- In some cases the cost of these shuttle is also high
- Sometimes they simply prefer walking

The enormous campus of 1300 acres is open to the public at the early hours of the day, however,
vehicles from outside are often seen taking the route as a shortcut to external roads throughout
the day. This lack of regulation of external motor vehicles in such a large campus creates
congestion and brings forth safety-security concerns for the students.

The shuttle (as seen in the top-left image) provided inside the campus was often spotted roaming
vacant. This was due to the limited availability, very specific spots for pick-up and drop-off,
and restricted timings (mostly in the morning and post classes, to and fro from hostel to various
departments).
Due to this, students were mostly seen walking around or using personal vehicles (cycles or 2
wheeler). Due to the pleasant weather of Bangalore and a laid-back, zen environment of the
campus culture, walking was not seen as a hassle by the students (as per in-depth interviews

mentioned later). More students were seen walking in the evening back to the hostel than in the
morning.
Case Study 2
National Institute of Technology, Tiruchirappalli, Bangalore
Government undergraduate, postgraduate and doctoral University

In the case of a relatively smaller campus than the first, the delivery system was more
systematically arranged. The delivery agents for the e-commerce services would wait at
designated common spots inside the campus, such as the stationery shop, canteen, during specific
hours regulated by the university (1pm-3pm). Students have to walk here and pick up their
packages within the timeframe, which is an easier method as the students have a sense of
schedule and system to rely on.
The delivery agents would all wait in the designated area, with the packages displayed down on
the floor as a makeshift display of packages for the students to come and identify their packages.
As seen in the images above, the storage of the packages to be received later by the students at a
later time, although convenient, is very less secure and safe, kept in a haywire manner with no
system. Hence, storage, segregation and distribution of the packages comes off as the major
challenge in this case where all delivery agents are waiting at the same room in the same
time-frame.

Students commute 6 kms to and fro from their hostels to the lecture hall complex everyday.
● Due to the linear campus layout, the distance between hostels and the lecture hall
complex is 1.5 km one way. This distance is traversed 4 times during a full day of class.
● The distance from the hostels to the supermarket and Medical center is 1.2 km.
● There is no uniformity in distances among the students as the placement of various
hostels and department blocks are scattered throughout the campus.
● The main mode of transportation is personal cycles. This becomes difficult due to the
hostile weather conditions and when carrying equipment.

Walking and cycling are the main modes of transportation within the campus. Due to the large
size of the campus, most students own a personal cycle for their convenience, with parking areas
provided for the same near the hostel gates and department buildings, as seen in the images.

Bus service and battery operated shuttle service are provided by the college at specific times to
specific places. Autos are available at the girls hostel. They charge 50/- per ride and drop the
student at any location within the campus, which is another reason why students prefer to own a
personal vehicle than pay for each commute with restricted timings and pick-up, drop-off spots
(as confirmed during in-depth interviews mentioned later).
Having a more fast-paced lifestyle, this campus had a more independent culture where students
preferred to own vehicles and drive around the campus to reach quicker and avoid the first and
last mile gap of public transport.

Case Study 3
Indian Institute of Science, Bengaluru
Being a yet smaller campus, the spots where delivery agents meet the customers was more
properly regulated than in the first two cases, where a separate designated spot, called ‘Amazon
pickup counter’ is set up for package deliveries related to e-commerce (as seen in the image
above). The delivery agents coming in and navigating their way around the campus comes off as

a major challenge, alongwith waiting for the students to come and receive their respective
packages, alongwith the storage and segregation of packages left in the counter to be received
later by the students - which is left in a haywire manner with almost no security.
The Existing System for Mobility Within The Campus :

Bus service and battery operated shuttle service are provided by the college at specific times to
specific places. Autos are available at the girls hostel. They charge 50/- per ride and drop the
student at any location within the campus, which is another reason why students prefer to own a
personal vehicle than pay for each commute with restricted timings and pick-up, drop-off spots
(as confirmed during in-depth interviews mentioned later).
Having a more fast-paced lifestyle, this campus had a more independent culture where students
preferred to own vehicles and drive around the campus to reach quicker and avoid the first and
last mile gap of public transport.
As seen in the images above, students with special needs, such as a student with large or
heavy luggage, or a student with injury or disability were observed to have a major
challenge to make their way to their destinations, especially in case of using public
transport which does not support for the gap of first and last mile.

How did the students feel about the current system?
Analysis of in-depth personal interviews and contextual inquiry
The data was collected through an unstructured interview format (detailed in methodology
section, questionnaire attached in appendix C). It aimed to find the data for allowance of delivery
agents inside campus, convenience, needs, and pain points of the current system, preferences,
and expectations.
Empathy mapping tool:
An empathy map helps to know more about the potential audience. This tool helps to understand
the reason behind some actions of the user. It helps build Empathy towards users and helps
design teams shift focus from the product/service/system to the users.

Brief of analysis:
The analysis of pain-points of the existing system of delivery service indicated the demand for a
more convenient, efficient and optimized delivery system that meets the need of both the
students in their busy and demanding lifestyle, as well as the challenges faced by the delivery
agents to ensure a successful delivery.
Through interviews it was revealed that the challenges faced are:

- Largely in the last-mile of the delivery.
- They acknowledged that the common storage and distribution space is too often overly
crowded; their parcels are often mistakenly misplaced up by others.
- They often have trouble coordinating time with the delivery agents amidst the
uncompromising schedule of the college.
- It is difficult to carry large or heavy parcels to their hostel rooms from the gate;
amongst many others.
- It is also found that they would like a platform where they can find someone who can
help them pick up their parcels without leaking their privacy or causing problems with
safety.
The challenges are not only on the student side but also on the delivery agent’s side.
- Firstly, navigating through the campus poses a significant challenge for delivery agents,
leading to difficulties in locating the intended recipients.
- Secondly, the high waiting time associated with delivering packages within the campus
further exacerbates these issues, leading to delays and reduced efficiency.
- Moreover, tracking customer locations within the campus can also prove challenging,
leading to further complications for the delivery agents.
- Additionally, language barriers and coordination issues also pose significant challenges
for the delivery agents, further impeding the delivery process.
- Lastly, security and safety concerns within the campus further contribute to the
reluctance of delivery agents to enter the campus, highlighting the need for
comprehensive safety measures to address these concerns.
Journey Mapping For The Current Delivery Systems For Students
The research highlights that the current system of delivery for students is as follows:
Journey maps showcasing the qualitative data point about needs, behaviors, motivations from
the sample.

The above data will differ as per different scenarios, as per the factors such as: Terrain of the
landscape, weather, level of urgency, time of the day, physical health, type of good (perishable,
non-perishable, size, weight), etc.
Importance Of Having An Alternative Method Of mobility Inside Campuses
The importance of having an alternative to the existing traditional method of transportation
on college campuses is evident due to several compelling reasons:
- Firstly, unfavorable weather conditions, such as extreme heat, steep terrain, or other
climatic factors, can impede the ability of students to navigate the campus effectively.
- Secondly, most students have various items to carry, including books, laptops, and other
essential materials, making it challenging to walk long distances.
- Furthermore, the tight schedules of students in colleges leave little room for travel
delays or prolonged journeys, making an efficient and reliable transportation system
essential.
- Additionally, not everyone can walk, including differently-abled individuals and elderly
faculty members, highlighting the importance of an equitable provision of transportation
services on campus.
Decision-Making Factors For The Choice Of Conveyance
These factors emphasize the critical role of alternative optimized rather intelligent
transportation systems in facilitating accessibility, promoting productivity, and ensuring equity
on college campuses.
The study findings indicate that a campus must have an intelligent (may be autonomous)
on-campus mobility service that caters to specific decision-making factors, including but not
limited to:

- Age and gender - The behavior patterns of mobility inside the campus differs between
students from that of faculties, owing to their age and/ or gender.
- Cost of conveyance - expense of owning a personal vehicle, or daily expense for shuttle
service for movement in and around the campus.
- Customer attitude - lack of trust or familiarity towards new technologies can indirectly
influence the degree of acceptance and satisfaction with the implemented technology.
- Climate and weather conditions - external factors such as rain, heat, etc. that influence
the choice of conveyance and/ or coordination of time with the delivery agents.
- Goods in hand (luggage) - Heavy or large items carried in hand by the students affect
the choice of conveyance, where on other times they might prefer to simply walk to their
destination.
- Level of urgency - level of urgency affects the mode of conveyance chosen by students
both for general mobility around the campus and for reaching the delivery agents at the
time of delivery (eg. perishable food items).
- Lifestyle - sedentary or active, convenience, routine of the inhabitants
- Nature of study of the students
- Physical condition - permanent or situational impairment, lifestyle diseases etc.
- Road access - policy regulating where to drive and park, dwell time on road or pavement
during delivery and shuttle services add to the first and last mile challenges
- Time of day - Students often preferred to walk in the evenings post class in a more
leisurely way as opposed to the hurry in the morning to reach class on time, where they
prefer to use their personal vehicles.
- Topography - Topography, road network design and so forth, influence routing and
energy usage.

Results and Key Findings
At the end of the data collection, 151 stakeholders were involved in the study. The participants
were distributed across the country and across different cities (tier 1, tier 2, tier 3) and
The approach was mainly qualitative with methods like in-depth interview, field study through
contextual inquiry and visual ethnography, participatory workshop, scenario testing and was
supported with a quantitative approach of questionnaire based survey.
(Refer to appendix C)
RQ1
What are the pain points in the current traditional delivery system for online packages inside
university campuses, in an Indian context?
Sub questions:
Needs, expectations, beliefs and expectations from both the parties (Delivery agents and
students)
Touch points of the service and betterment
Willing to adapt to a new technology or a service
RQ2
What are the feasibility and requirements for implementing a mutual-aid intelligent delivery
service for university students, and how does it compare to the current delivery system?
RQ3
What are the perceptions, beliefs and attitudes of students on adoption of a mutual-aid
intelligent delivery service for university students, and how does it compare to the current
delivery system?
RQ4
highlighted.

What are the pain points in the traditional shared shuttle services in the current mobility system.
Sub questions:
Needs, behaviors, expectations and motivations of primary users.
Most common modes of transportation and nature of environment
Factors influencing the choice
RQ5 - Future scope
highlighted
How can technology such as machine learning, artificial intelligence, and predictive analytics be
used to optimize the delivery service for university students?
The Missing Last Mile
The key finding from the study was that the delivery system within campus settings faces a
significant gap between key stakeholders, namely delivery agents and students. Unfortunately,
the prevailing circumstances do not support a mutual aid service. Despite the need of delivery
agents in the campus ecosystem, most campuses prohibit their entry, and even when permitted,
due to their reluctance of entry (detailed below) within large campuses gives rise to significant
challenges. To mitigate these issues, designated delivery spots are commonly established for
online orders and packages.
However, in both the cases (allowing or not allowing) the unreliability creates an uncertain
situation that ultimately leads to an incomplete last mile in the delivery system.
One of the significant findings of this study indicates that the conventional delivery service
approach lacks efficacy in addressing the challenges associated with identifying, tracking,
sorting, storing, and distributing packages.
The research also highlights several factors that contribute to the delivery agents' reluctance to
enter the campus for package delivery.

( Discussed at length in analysis section )
Additionally, the study reveals that there is a growing preference for technology over human
intervention, highlighting the potential for leveraging technological advancements to enhance
the service's intelligence, efficiency, sustainability, accuracy, and speed. Incorporating these
advancements can foster greater trust among stakeholders, ultimately strengthening the service's
credibility and reliability. Hence, technology such as machine learning (ML), artificial
intelligence (AI), and predictive analytics can be used to optimize the delivery service for
university students as well as segregation and storage of ordered packages for an optimized
delivery system.
Effect on Purchasing Behavior
The impact of this last mile gap is noteworthy, as it has been observed to influence students'
purchasing behavior, which accounts for a considerable proportion of e-commerce revenue.
X axis: Responses of participants
Y axis: % of sample

Most comfortable mode of
payment
Need for an intelligent (tech-based) shuttle system (The missing first and last mile)
The research has also identified some significant limitations of the traditional campus shared
shuttle system, indicating a pressing need for a comprehensive re-evaluation of this service. The
findings of this study emphasize the need for a more intelligent (may be autonomous)
on-campus mobility service that can provide a viable alternative to the current shuttle system.
The limitations of the traditional shuttle service, including its inability to provide a smooth and
optimized mobility experience, underscore the importance of adapting to the evolving needs of
the campus community. Thus, it is imperative to identify more effective alternatives that can
cater to these needs and provide an enhanced mobility service that improves the overall campus
experience for students and other members of the community.
( Discussed at length in analysis section )

Discussion Section
This chapter discusses the findings of the study and compares them to the theory and findings
based on the literature review. The additional contributions have also been discussed.
(Detailed in the inference section)
Correlation with other studies and additional insights
Behaviors, needs and motivation in current on-campus delivery system
1. According to a study conducted in 2021 there is a ‘missing last mile in delivery
systems’ (Hunan university, School of design, 202). This study examined how Intelligent
Delivery Services can be applied to college campuses using Innovative Strategies. The
results were found to be the same.
2. We also found that this missing last mile in delivery systems leads to an uncertain
situation. This in turn affects purchasing behavior. For example, in the study, students
ordered less to cut the hassle of improper delivery systems. In addition, they preferred to
pre-pay rather than cash on delivery. Among youth, COD is the most popular method
of delivery due to perceived security (Al Falah University, United Arab Emirates, Dubai,
2107, 23) which in this case due to unreliability, results in a reduction in e-commerce
revenue from this target group.
3. We also found that the sample was willing to trust technology over humans for factors
stated like quickness, accuracy, price, privacy, security, efficiency and sustainability. It
supports the study of Sebastian Kasper (Kasper, 2020) which found the factors for
acceptance of technology in delivery (ADV). The factors include: facilitating conditions,
price sensitivity, privacy security, compatibility, and hedonic motivation

Behaviors, needs and motivation in current on-campus mobility system:
The research also highlighted a need for an efficient on-campus intelligent mobility
system as opposed to a conventional shuttle system as they suffer from the first and last
mile problem. A study conducted in September 2017 (IEEE Transactions on Intelligent
Transportation Systems, 2017) validated the same.
4. The study also found that there are several factors which influence the decision of mode
of transport within campus, the most common mode being ‘walk’ and ‘bicycle’ we tried
to find the whys and hows. The factors which influence this were listed above in the
report.
Perception of short distance travel:
5. A study conducted on “How do college students perceive future shared mobility with
autonomous vehicles” (University of Alabama students, 2022) found a significant
relationships between the willingness to pay and various factors related to respondents’
socio-demographics, awareness of AV companies, and experiences with human-driver
ride-hailing services is similar to the finding. We also found that people are more likely
to rent/service an autonomous vehicle than buy it.
6. A study on “A Study on Implementing Autonomous Intra City Public Transport System
in Developing Countries - India” (Science direct, 2017) , highlighted a finding that a
feasible method of implementing the autonomous vehicular technology should be
designed, it supports the finding that AV vehicles might not be well-suited for
developing countries like India due to Infrastructure and network issues.
7. In line with the previous studies, we also found that different socio-cultural-regional
variables like economic background, lifestyle, daily commute patterns etc can affect the

perception of short distance amongst people. In the chosen sample the average
perception of short distance was 5-10 kms.
All the research studies listed above are mentioned in the reference section.
Conclusion
As the future of our society and a significant contributor to the e-commerce economy, the young
generation's needs must be addressed in the delivery and mobility services provided on
university campuses. By implementing sustainable and efficient delivery services, along with
an intelligent mobility system, we can not only cater to the needs of the young generation but
also promote the growth of the e-commerce industry.
Our research underscores the importance of addressing the missing last mile gap, which
significantly influences students' purchasing behavior, accounting for a substantial proportion
of e-commerce revenue.
Our study also indicates that technology-based delivery and mobility systems are preferred
over human-based ones due to factors such as quickness, accuracy, price, privacy security,
efficiency, and sustainability. Additionally, socio-demographic factors, economic background,
lifestyle, and daily commute patterns influence the perception of short-distance travel.
We hope our findings will inspire further research in this area and encourage the adoption of
intelligent systems to meet the evolving needs of the campus community while adapting to
the changing landscape of the e-commerce industry.

Limitations and future scope:
Limitations-
● The sample size for the study was relatively small (151 participants involved).
● The study was conducted during a specific period, and factors such as seasonal changes,
cultural events, socio-political trends, repercussions of COVID-19 etc. may influence the
results. (DYMEK et al., n.d.)
● The study relied on self-reported data and may be subject to response bias.
● The study does not address the potential environmental impact of implementing the
suggested changes.
Different cultural backgrounds and conditions may affect individuals’ willingness to accept new
technology. The mindset of the target audience might also add into the bias. Identifying different
socio-cultural variables is the key.
Further scope for research
There could be more studies on the acceptance of intelligent systems with automation to be
conducted in the future.
- First, future studies could conduct stratified sampling of different socio-geographical
areas (tier 1 vs tier 2 cities) to make the results more representative.
- Future studies could focus on unique mobility requirements in terms of layout,
population, and demand and patterns.
- Exploring the potential for collaboration with the delivery and transportation industries to
develop innovative solutions that integrate with the on-campus mobility systems could
also be studied further.

Proposal
Two-Pronged Approach
After analyzing the challenges faced by students and delivery agents in the current on-campus
delivery and mobility systems, our research suggests a two-pronged approach to tackle the
problem of the “missing mile”.
- Firstly, we propose the establishment of a mutual-aid intelligent delivery service that can
efficiently handle the drop-in, storage, pickup, and doorstep drop-off of online packages
on educational campuses without human intervention. This service would ensure a
seamless delivery experience for students while optimizing the use of campus resources.
- Secondly, we recommend the implementation of an automated intelligent mobility
service within the campus that caters to students' needs in a flexible manner. Such a
service would provide students with a quick, reliable, and sustainable mode of
transportation, addressing the current limitations of the traditional campus shuttle system.
The use of autonomous or semi-autonomous vehicles for this service would reduce
human error and increase efficiency while improving the overall campus experience for
students.
Our proposal aligns with the evolving needs of the campus community and the changing
landscape of the e-commerce industry. It would not only cater to the young generation's needs
but also contribute to the growth of the e-commerce economy.
Design prompts for the mutual-aid technology
Some prompts to consider before designing an autonomous technology for last mile delivery
service inside a university campus could include:

● Understanding the target audience: It is important to understand the needs and
preferences of the target audience, such as students, faculty, and staff, before designing
the vehicle. This can be achieved through user research and surveys.
● Analyzing the campus infrastructure: The campus layout, road network, parking
facilities, and pedestrian traffic should be analyzed to ensure that the autonomous vehicle
can navigate effectively and safely.
● Identifying delivery requirements: The type of packages that need to be delivered, their
size and weight, and delivery timelines should be analyzed to determine the design
requirements of the autonomous vehicle.
● Determining the features required: Based on the above prompts, the features required in
the autonomous vehicle can be determined, such as size, capacity, speed, range, safety
features, and communication systems.
● Considering legal and regulatory requirements: Legal and regulatory requirements
related to autonomous vehicles, such as licensing and insurance, should be considered
before designing the vehicle.
● Identifying potential issues: Possible issues that may arise during the implementation of
the autonomous vehicle, such as privacy concerns, security threats, and social
acceptance, should be identified and addressed in the design.
● Testing and evaluation: The autonomous vehicle should be tested and evaluated in a
controlled environment before deploying it on the campus to ensure that it meets the
design requirements and is safe to use.

● The size and weight of packages that will be delivered will be determined by analyzing
the type of items that will be transported, their dimensions, and weights. The designer
will then create a vehicle design that can accommodate these packages efficiently.
● The number of packages the vehicle will need to transport at once will depend on the
volume of deliveries and the capacity of the vehicle. The designer will need to analyze
the delivery data to determine the optimal number of packages that the vehicle can carry
at once.
● The maximum speed and distance the vehicle should cover will depend on the size of the
campus, the number of stops, and the terrain. The designer will analyze this information
to determine the appropriate speed and distance capabilities for the vehicle.
● The weather conditions the vehicle will need to operate in will be analyzed to determine
the type of materials, sensors, and software needed to ensure safe operation in different
weather conditions.
● The level of autonomy required for the vehicle will depend on the complexity of the
campus, the presence of pedestrians, and other vehicles. The designer will need to
determine the appropriate sensors, software, and other features to ensure safe operation.
● The charging and maintenance infrastructure required for the vehicle will be
determined by analyzing the existing infrastructure on campus and determining the
optimal locations for charging and maintenance stations.
● The budget for the vehicle's development and deployment will be determined by
analyzing the costs of materials, labor, and other expenses associated with designing and
deploying the vehicle.

● The safety features that the vehicle should have to ensure the safety of pedestrians and
other vehicles on campus will be determined by analyzing the potential risks and
developing appropriate safety measures.
● The aesthetic and branding considerations for the vehicle's design, such as color, shape,
and materials, will be determined by analyzing the campus's visual identity and
developing a design that is consistent with the university's branding.
● The legal and regulatory requirements that the vehicle must meet to operate on campus
will be determined by researching local and national regulations and ensuring that the
vehicle design and operation meet all legal requirements.
In conclusion, we urge universities and educational institutions to consider the adoption of
intelligent delivery and mobility systems, which have the potential to revolutionize the
on-campus delivery and transportation landscape.

References
Literature review and background study
Halaweh, M. (2017b). Intention to Adopt the Cash on Delivery (COD) Payment Model for E-commerce
Transactions: An Empirical Study. Lecture Notes in Computer Science, 628–637.
https://doi.org/10.1007/978-3-319-59105-6_54
Westgarth, A. (2022, December 13). Efficiency Delivered: Benefits of Autonomous Robot Delivery on College
Campuses. Spiceworks.
https://www.spiceworks.com/tech/iot/guest-article/benefits-of-autonomous-robot-delivery-on-college-campuses/
Marr, B. (2020, May 29). Demand For These Autonomous Delivery Robots Is Skyrocketing During This Pandemic.
Forbes.
https://www.forbes.com/sites/bernardmarr/2020/05/29/demand-for-these-autonomous-delivery-robots-is-skyrocketin
g-during-this-pandemic/?sh=254024887f3c
Fu, X., Nie, Q., Liu, J., Zhang, Z., & Jones, S. J. (2021). How do college students perceive future shared mobility
with autonomous Vehicles? A survey of the University of Alabama students. International Journal of
Transportation Science and Technology, 11(2), 189–204.
https://doi.org/10.1016/j.ijtst.2021.11.006
(n.d.). Forbes.
https://www.forbes.com/sites/bernardmarr/2020/05/29/demand-for-these-autonomous-delivery-robots-is-sk
yrocketing-during-this-pandemic/?sh=42c9e567f3c0
Hunan University, School of design. (2021, July 03). A Study on the Application of Innovative Strategies on
Intelligent Mutual-Aid Delivery Services on College Campuses. International Conference on
Human-Computer Interaction, 1(1), 18. 10.1007/978-3-030-78224-5_5
DYMEK, D., GRABOWSKI, M., & PALIWODA, G. (n.d.). Impact of COVID-19 Pandemic on Students' Online
Behavioral Pattern -. IBIMA Publishing.https://ibimapublishing.com/articles/JELHE/2022/881022/

Understanding consumer behavior: Insights from McKinsey and Forrester. (2021, August 31). McKinsey.
https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/understanding-the-ever-evolv
ing-always-surprising-consumer
Application of innovative strategies on intelligent mutual aid delivery service on college campus. (n.d.). Google
books.
https://books.google.co.in/books?id=k7I2EAAAQBAJ&pg=PA60&lpg=PA60&dq=A+Study+on+the+Appl
ication+of+Innovative+Strategies+on+Intelligent+Mutual-Aid+Delivery+Services+on+College+Campuses
+beijing&source=bl&ots=dMalXJ3RGX&sig=ACfU3U0H6HToqy4Q4LME9M4gaPaWpJmqVQ
DYMEK, D., GRABOWSKI, M., & PALIWODA, G. (n.d.). Impact of COVID-19 Pandemic on Students' Online
Behavioral Pattern -. IBIMA Publishing. https://ibimapublishing.com/articles/JELHE/2022/881022/
IEEE Transactions on Intelligent Transportation Systems (Ed.). (2017). Autonomous Campus Mobility Services
Using Driverless Taxi. Autonomous Campus Mobility Services Using Driverless Taxi, 18(12), 3513 - 3526.
10.1109/TITS.2017.2739127
Kasper, S. (2020, feb 1). Acceptance of autonomous delivery vehicles for last-mile delivery in Germany. Acceptance
of autonomous delivery vehicles for last-mile delivery in Germany, 1(1), 25.
https://doi.org/10.1016/j.trc.2019.12.016

Understanding consumer behavior: Insights from McKinsey and Forrester. (2021, August 31). McKinsey.
https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/understanding-the-ever-evolv
ing-always-surprising-consumer
From discussion section
Al Falah University, United Arab Emirates, Dubai. (2107, May 17). Intention to Adopt the Cash on Delivery (COD)
Payment Model for E-commerce Transactions: An Empirical Study. Intention to Adopt the Cash on
Delivery (COD) Payment Model for E-commerce Transactions: An Empirical Study, 1(2), 18.
https://doi.org/10.1007/978-3-319-59105-6_54
IEEE Transactions on Intelligent Transportation Systems (Ed.). (2017). Autonomous Campus Mobility Services
Using Driverless Taxi. Autonomous Campus Mobility Services Using Driverless Taxi, 18(12), 3513 - 3526.
10.1109/TITS.2017.2739127
Kasper, S. (2020, feb 1). Acceptance of autonomous delivery vehicles for last-mile delivery in Germany. Acceptance
of autonomous delivery vehicles for last-mile delivery in Germany, 1(1), 25.
https://doi.org/10.1016/j.trc.2019.12.016

Appendix
The following is a repository of materials developed for the research study. For better
understanding it is categorized as:
Appendix A
Topic details
Background study (Literature review)
Appendix B
Methodology
Preparation of research
Study protocols
Appendix C
Data collection
Analysis
Results

Appendix A

Appendix B

Appendix C
Analysis of qualitative data was performed by making codes, which involved identifying
common themes and sub themes occurring.

Online survey questionnaire reference

Key results of online survey (detailed in analysis section)

Key results of in-depth interviews and focus group
The responses were documented through audio recordings, photographs and transcribed into
spreadsheets. For privacy the identification of participants is undisclosed.

Field study
The responses were documented through audio recordings, photographs and transcribed into
spreadsheets. For privacy the identification of participants is undisclosed..

In-depth interviews, focus groups and co-design workshop

Co-Design Workshop

Thank you
Interaction Design, National Institute of Design, Bangalore
Design Research, 2nd Semester
Prof. Mamata N. Rao, Prof. Neha Mandlik
Mar 13, 2023

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