1
A RESEARCH ON
“HUMAN CRITICAL SUCCESS FACTORS FOR SUSTAINABLE SUPPLY
CHAIN RESILIENCE”
BY
AVLEEN KAUR
(210A3010080)
ADVANCED BUSINESS RESEARCH PROJECT
SCHOOL OF MANAGEMENT
BML MUNJAL UNIVERSITY
DATE: 31ST MARCH 2023
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A RESEARCH ON
“HUMAN CRITICAL SUCCESS FACTORS FOR SUSTAINABLE SUPPLY
CHAIN RESILIENCE”
BY
AVLEEN KAUR
(210A3010080)
ADVANCED BUSINESS RESEARCH PROJECT
SCHOOL OF MANAGEMENT
BML MUNJAL UNIVERSITY
DATE: 31
ST
MARCH 2023
DECLARATION
I hereby declare that the Project Report titled “Human Critical Success Factors for Sustainable
Supply Chain Resilience” in BML Munjal University is my own work to the best of my
knowledge and belief. It contains no material previously published or written by another person or
material which to substantial extent has been accepted for the award of any other degree, diploma,
or program of any other institute, except where due acknowledgement has been made in text.
AVLEEN KAUR 31
ST
MARCH 2023
(210A3010080)
TABLE OF CONTENTS
TABLES AND FIGURES
HEADING PAGE NO.
Table - 1: Characterization of Identified Human Critical Success Factors
Table - 2: Experts’ characteristic details and major responsibilities
Table - 3: Fuzzy linguistic scale adopted in this study
Table - 4: Interdependency of each success factor over the other on a
linguistic scale
Table - 5: Fuzzy relation matrix of interdependency between parameters
Table - 6: Fuzzy initial direct relation matrix
Table - 7: Fuzzy normalized initial direct relation matrix
Table - 8: Fuzzy total direct relation matrix
Table - 9: Prominence and Influence of each success factors
Table - 10: Average Scores of HCSFs using Rows and Columns
Table - 11: HCSFs categories into Causes and Effects
HEADING PAGE NO.
Figure 1: Characterization of the considered success factors
SECTION 1 - INTRODUCTION
This year 2022 has been an inspiring and achievement-oriented year for India, economically, as it
became the fifth largest nation in the world that has registered the highest ever foreign direct
investment – inflows and exports. Because of this growth, India has now started focusing its
growth engines on infrastructural and logistics sector to become a network hub, rather than a node
in the global supply chain market. Using these business strategies of “China plus one”, India has
now been awarded with a remarkable opportunity to integrate the economy in the high and
sophisticated and resilient supply chain network with the Indo Pacific market. To promote the
vision of “Atmanirbhar Bharat”, India has started capitalising groupings such as SCRI, QUAD,
and IPEF to attract resilient supply chain models and value chain networks towards making its
own industrial and manufacturing sector.
Supply Chain Resilience refers to an organization's ability to withstand and recover from
disruptions or unexpected events that could negatively impact its supply chain performance. In
today's fast-paced and interconnected world, supply chain resilience has emerged as a critical
factor in ensuring the long-term success of businesses. (Fahimnia et al. 2019). The major reasons
highlighted for this are tighter regulations, consumers pressures, increased competition,
challenging markets, outsourcing, globalization, uncertainty in demand and a push towards
economic competitiveness (Ansari & Kant, 2017 ; Grant et al., 2017 ). With the increasing
frequency and severity of disruptions caused by various factors, including natural disasters,
political instability, pandemics, and economic downturns, organizations are recognizing the
importance of building resilient supply chains that can withstand and recover from unexpected
events. (Tirkolaee et al., 2022)
Apart from Resilience, Sustainability has also become a major focus for businesses worldwide. In
general, sustainability refers to the ability of a supply chain to operate in a socially, economically,
and environmentally responsible manner while being able to adapt to changing conditions and
minimize negative impacts on society and the environment. A research paper by M. Ali et al.
(2020) highlighted the importance of sustainability in supply chain resilience. The paper
emphasized that sustainable practices, such as ethical sourcing, efficient resource use, and
stakeholder collaboration, can help supply chains to better manage risks and disruptions, and
ultimately improve their resilience. Another study by A. Gunasekaran et al. (2018) examined the
relationship between sustainability and supply chain resilience in the context of food supply
chains. The study found that sustainable practices, such as local sourcing, transparency, and
responsible waste management, can improve the resilience of food supply chains and reduce their
vulnerability to disruptions. Furthermore, a research paper by S. Zhang et al. (2021) explored the
role of digital technologies in enhancing the sustainability and resilience of supply chains. The
study found that digital technologies, such as blockchain, artificial intelligence, and the Internet of
Things, can enable supply chains to more effectively track and manage their sustainability
performance, and respond to disruptions in a timely and efficient manner. In this context, the
concept of supply chain resilience has emerged as a critical factor in ensuring sustainable business
operations. (Kamalahmadi & Parast, 2016).
Achieving sustainable supply chain resilience requires a comprehensive approach that considers
various factors, including the human aspect of the organization. (Ipek et al., 2022). While
technology and infrastructure are important elements, the human element is equally critical in
ensuring that organizations can respond effectively to disruptions. In this regard, the identification
and management of critical success factors (CSFs) that are specific to human factors can help
organizations achieve sustainable supply chain resilience. Research has shown that leaders who
prioritize sustainability and resilience can positively impact the performance of the supply chain
(Ranjan et al., 2021).
This research study aims to identify the stakeholder’s requirements and relevant human critical
success factors for sustainable and resilient initiatives in the supply chain. The study intends to
attain the following objectives:
i) To identify key HCSFs for adoption of sustainable supply chain resilience practices
ii) To assess the listed HCSFs by identifying their inter-relationships in adoption of
sustainable supply chain resilience practices
iii) To outline key practical implications and strategies that may facilitate decision
makers to achieve a system of sustainable supply chain resilience
To achieve these objectives, a comprehensive literature review was conducted in the Second
Section of this paper, drawing on relevant academic and industry sources. Appropriate critical
success factors are identified based on a literature survey as well as discussions with decision
makers and connoisseurs. The Third Section identifies research gaps and characterizes the
identified HCSFs by using fuzzy DEMATEL. The case examples of an Indian auto mobile
company as the industry pioneer which shows the real-world applicability of the proposed model.
The Fourth Section presents the Findings and Discussions. The Fifth Section discusses the
theoretical and practical implications of the findings to implement supply chain resilience practices
in the workplace. Finally, the Last Section concludes the paper with Limitations and Future Scope.
This research will contribute to the development of a more comprehensive and holistic approach
to supply chain resilience that considers the critical role of human factors.
For instance, support from top management, environmental training, and employee empowerment
for environmental issues are some frequently cited reasons for adopting Sustainability Practices,
(Jabbour, Jugend, et al., 2015; Jabbour, Neto, et al., 2015; Pellegrini et al., 2018) The study by
Yusliza et al. (2019) also underpins the importance of top management support to the practice of
Global HRM and sustainability in manufacturing organizations.
The whole concept of Supply Chain and Operations Management is built around the assumption
that human resources are predictable and deterministic in their behaviours and make decisions that
are observable, emotionless, and independent of the product (Gino F. and Pisano G, 2008). To
develop a sustainable and LARG (Lean, Agile, Resilient and Green) culture, it is evident to create
and put more emphasis on the human success factor approach. Human Critical Success Factors
(HCSFs) are as equally essential as other factors like technology to execute supply chain practices
effectively (Kumar et al..2019). Green Human Resources Factors impact the organisational
performance (Masri and Jaaron, 2017). Similarly, in a study conducted by Anthony (2019),
employee behaviour is observed to be crucial for the environmental performance of organisations.
A study conducted by Nejati et al. (2017) reported a significant and positive impact of Green
Human Resource Management (GHRM) and Green Supply Chain Management (GSCM), where
the role of change management was explored. Findings suggested that resistance to change has a
moderating effect on the GHRM and GSCM relationship and tends to hamper the development of
a sustainable corporate culture. Therefore, policies and procedures must be formulated in a way
which provides support to the employees for transforming organisational operations to attain
environmental sustainability (Ahuja, et al.., 2019).
SECTION 3 - RESEARCH METHODOLOGY
3 .1. Solution Methodology
Dr. Kees van Montfort and his team developed the methodology of DEMATEL in Geneva
Research Centre of the Battelle Memorial Institute to understand the relation between various
parameters in a system. Diagraphs which are typically the outcome of this technique help
visualizing and understanding the interdependency between variables. Since the perception of
decision makers vary for a particular query, using Fuzzy ratings as discussed in the sections would
benefit in capturing the ambiguity. The typical steps involved in fuzzy DEMATEL are as follows:
Step-1: Identification of key success factors, Preparation of questionnaire, and constituting the
expert panel
In this step, the human critical success factors of sustainable supply chain resilience are identified
through extensive literature survey. These fourteen different factors are:
Table - 1: Characterization of Identified Human Critical Success Factors
HCSF
Category
HCSF Reference Description of HCSF
Top
Management
Support
Sustainable
Leadership
(Chau, K. Y., Tang,
Y. M., Liu, X., Ip, Y.
K., & Tao, Y.
The ability of leaders to make
decisions and take actions that
balance economic, environmental,
and social factors in the supply chain
Green
Motivation
Liu, S., Eweje, G.,
He, Q., & Lin, Z.
The drive or incentive for companies
to adopt environmentally sustainable
practices and reduce their negative
impact on the environment.
Employee
Engagement
Masri and Jaaron
It can be defined as the degree to
which employees invest their
behavioural, cognitive, and emotional
energies towards positive
organizational outcomes.
Job Related
Factors
Rewards and
Incentives
Pellegrini et al.
The use of compensation, recognition,
and other benefits to motivate and
encourage individuals and teams to
achieve specific goals and objectives
related to the movement of goods and
materials through the supply chain.
Role Clarity Li et al. (2014) The degree to which individuals and
teams understand their roles,
responsibilities, and expectations
within the larger supply chain
network.
Health and
Safety
Raut, Narkhede, and
Gardas ( 2017 )
The measures and practices put in
place to ensure the well-being and
protection of employees, customers,
and stakeholders in the movement of
goods and materials.
Individual
Factors
Mindfulness (Dennehy et al,.
The practice of being present and fully
engaged in the current moment and
task at hand, while maintaining a non-
judgmental and open-minded
perspective.
Attitude
Towards
Environment
(Shen, Bin, et al,
The beliefs, values, and behaviors of
individuals and organizations in
relation to environmental
sustainability and responsibility.
Trust And
Respect
Kabra, G., &
Ramesh, A. (2016)
The attitudes and behaviors that
individuals and organizations exhibit
towards each other, based on mutual
trust and respect.
Table - 2: Experts’ characteristic details and major responsibilities
Experts Education Experience
(in years)
Key Responsibilities Job title
1 B.Tech. 10 Strategy building for after sales
services, forecasting and planning
the demand and maintenance
activities
Deputy Manager -
Service Operations
2 B.Tech. ,
MBA
12 Optimisation of Quality
Management tools, maintaining
CSR records, and validating
quality productions
Section Head -
Operational
Excellence
3 B.Tech.,
MBA
14 Employee training on
sustainability and green initiatives,
examining and enabling pro
environmental behaviour
Deputy Manager -
HR
4 B.Tech. 11 Planning, Monitoring, and
Mitigating challenges during shop
floor production and escalation
management
Risk Mitigation
Analyst
5 B.Tech.,
MBA
15 Strategizing and devising relevant
objectives for production team,
forecasting demand, calculating
and managing production
efficiency
Production
Manager
12 B.Tech.,
MBA
15 Enabling and Deducing cost
efficient and environmental
friendly manufacturing activities
General Manager -
Lean
Manufacturing
13 B.Tech. 11 Checking production quality, cost
of poor quality, competition and
external analysis of environment,
maintaining quality Kaizen records
Quality Assurance
and Risk Planner
14 B.Tech.,
MBA
15 Executing the initiatives under
Business Excellence such as
Malcolm Baldridge Excellence
model, Six Sigma, TPM & TQM
Head, Business
Excellence
15 B.Tech. 13 Monitoring, reviewing and
checking the quality of spare parts
produced and ensuring product
approval and quality concerns by
customer
Customer Quality
Engineer
Step-2: Collection of responses from the experts and conversion into fuzzy scale
The perception related to interdependency of each factor, corresponding to various experts from
automobile industry is collected on a linguistic scale. The linguistic scale contains five different
categories that can distinguish the interdependence of factors. The collected linguistic scale
judgement will further be converted into trapezoidal fuzzy weights which are trapezoidal fuzzy
numbers (TrFN), to quantify the interdependency between factors. The linguistic scale adopted,
and its corresponding fuzzy weights is shown in Table 3. It can be noted that the attributes of the
equivalent fuzzy trapezoidal weight satisfy the condition as discussed in section 3 .1. In line with
the scale provided in Table 3 , response is collected from various experts in the constituted panel
and the corresponding fuzzy scales are shown in Table 4 and Table 5 respectively.
Table - 3 : Fuzzy linguistic scale adopted in this study (modified after Luthra et al. 2016)
Linguistic Score Explanation Equivalent fuzzy trapezoidal weight
O No influence (0, 0, 0.1, 0.2)
VL Very low influence (0.1, 0.2, 0.3, 0.4)
L Low influence (0.3, 0.4, 0.5, 0.6)
H High influence (0.5, 0.6, 0.7, 0.8)
VH Very high influence (0.7, 0.8, 0.9, 1)
Table - 4 : Interdependency of each success factor over the other on a linguistic scale
A b c d e f g h i j k l m n
a O O O H VH VH H VH H VH VH O O H
B VL O L VH H H H H VH VH H VH L H
c O L O H VH VH VH VH H O VH H VH H
D VL VH H O H VL H H H L H H H H
e VL VH O H O VH H VH VH H H L VH H
f VH H VH VH H O VH VH H H H VH H VL
G O L VH VH H VH O H H O VH H H H
H H VH O H H VH VH O VH O H H H VH
i L H VH VH VH H VH H O H VH L VH H
j L VH H H VH H VH VH VH O H H H VL
K VL H VH VH VH H H H H VH O VH H H
l VL H O H H H VH H H H VH O VH L
m VH L H VH VH H H O VH VH VH H O H
N VH H VH VH VH H VH H O H H VH H O
Step-3: Constructing Fuzzy initial direct relation matrix
The equivalent fuzzy numbers are converted into crisp ratings using a defuzzification technique.
This study considered bisection of area method to convert the equivalent trapezoidal weights into
crisp number. Since the expert panel constituted contains numerous experts, an average fuzzy
matrix is constructed by considering the response of all the experts from the industry pioneer
company as shows in Table 6.
Step-4: Evaluating the normalized initial direct relation matrix
The initial direction relation matrix can mathematically obtained using Eq 3 and Eq 4 [2].
!"
"$%
!"
!$%
2 = # × 4 ( 4 )
where A is the fuzzy initial direct relation matrix. The fuzzy normalized direct relation matrix thus obtained is shown in Table 6.
Step-5: Constructing total relation matrix
Total relation matrix can be formulated using Eq 5
&%
where, I is the identity matrix, T is the total relation matrix. The obtained total relation matrix is shown in Table 7.
Step-6: Evaluation of row and column matrix depicting the overall effect
In this step, the overall effect of each parameter is evaluated which is achieved by evaluating the sum of each row and columns
respectively. This can mathematically be expressed using Eq 5 and Eq 6.
!"
"$%
#×%
@ = A< =
!"
!$%
B
#×%
where, R represents effect of i on j; C represents the effect experience by j due to i. The evaluated attributes are presented in Table 8.
Step-7: Determining the Prominence and Influence
The cumulative sum of R and C reflects the prominence of each factor whereas the difference between R and C indicates influence.
Therefore, if the magnitude of R – C is negative it can be categorized as an effect factor and would belong to cause if R – C is positive.
The prominence i.e. D+R would help the decision maker in interpreting the hierarchy of the identified success factors.
Table - 7 : Fuzzy normalized initial direct relation matrix
Table - 8 : Fuzzy total direct relation matrix
- ABSTRACT
- SECTION 1 - INTRODUCTION
- SECTION 2 - LITERATURE REVIEW
- SECTION 3 - RESEARCH METHODOLOGY
- 3.1. Solution Methodology
- 3.2: Case Company Profile:
- SECTION 5 - THEORETICAL AND PRACTICAL IMPLICATIONS
- 5.1: Theoretical Implications:
- 5.2: Practical Implications:
- SECTION 6 - CONCLUSION, LIMITATION AND FUTURE SCOPE
- REFERENCES............................................................................................................................
- QUESTIONNAIRE:
- a 0.01 0.05 0.06 0.06 0.07 0.07 0.07 0.06 0.07 0.05 0.07 0.06 0.07 0. A b C D e f g h i j k l m n
- b 0.07 0.01 0.07 0.07 0.06 0.06 0.07 0.06 0.08 0.07 0.08 0.08 0.07 0.
- c 0.03 0.06 0.01 0.07 0.08 0.08 0.08 0.07 0.07 0.07 0.07 0.06 0.07 0.
- d 0.06 0.06 0.06 0.01 0.07 0.06 0.07 0.07 0.07 0.07 0.07 0.07 0.06 0.
- e 0.06 0.06 0.06 0.07 0.01 0.07 0.08 0.08 0.07 0.08 0.07 0.07 0.08 0.
- f 0.06 0.06 0.06 0.07 0.06 0.01 0.08 0.06 0.07 0.07 0.08 0.07 0.07 0.
- g 0.07 0.07 0.07 0.07 0.07 0.08 0.01 0.08 0.07 0.07 0.08 0.07 0.07 0.
- h 0.07 0.07 0.07 0.07 0.08 0.08 0.08 0.01 0.08 0.08 0.08 0.07 0.07 0.
- i 0.07 0.06 0.08 0.07 0.08 0.07 0.08 0.08 0.01 0.07 0.08 0.06 0.07 0.
- j 0.07 0.06 0.06 0.07 0.07 0.08 0.08 0.08 0.07 0.01 0.07 0.06 0.07 0.
- k 0.08 0.07 0.08 0.08 0.08 0.08 0.07 0.07 0.07 0.08 0.01 0.08 0.07 0.
- l 0.06 0.07 0.06 0.08 0.08 0.08 0.08 0.08 0.08 0.07 0.08 0.01 0.07 0.
- m 0.07 0.06 0.07 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.07 0.01 0.
- n 0.07 0.06 0.07 0.08 0.08 0.07 0.08 0.07 0.07 0.07 0.07 0.07 0.08 0.
- a 0.77 0.80 0.82 0.90 0.94 0.93 0.96 0.89 0.91 0.88 0.95 0.87 0.89 0. A b c D e f g h i j k l m n
- b 0.88 0.80 0.88 0.96 0.99 0.98 1.01 0.95 0.97 0.95 1.01 0.94 0.94 0.
- c 0.83 0.83 0.81 0.94 0.98 0.97 0.99 0.93 0.94 0.92 0.98 0.90 0.93 0.
- d 0.84 0.83 0.85 0.88 0.97 0.95 0.98 0.93 0.93 0.91 0.97 0.90 0.91 0.
- e 0.90 0.88 0.90 0.99 0.97 1.02 1.04 0.99 0.99 0.98 1.04 0.96 0.98 0.
- f 0.87 0.85 0.87 0.95 0.99 0.92 1.01 0.94 0.95 0.94 1.01 0.93 0.94 0.
- g 0.92 0.91 0.93 1.01 1.05 1.05 1.00 1.01 1.01 0.99 1.06 0.98 1.00 1.
- h 0.94 0.92 0.94 1.03 1.08 1.07 1.09 0.96 1.03 1.02 1.08 0.99 1.02 1.
- i 0.92 0.90 0.94 1.01 1.06 1.04 1.07 1.01 0.95 1.00 1.07 0.96 0.99 1.
- j 0.90 0.88 0.90 0.99 1.03 1.03 1.05 0.99 0.99 0.92 1.04 0.95 0.98 0.
- k 0.96 0.94 0.97 1.06 1.10 1.08 1.10 1.04 1.04 1.04 1.03 1.01 1.03 1.
- l 0.93 0.93 0.94 1.04 1.07 1.06 1.09 1.03 1.04 1.01 1.08 0.93 1.01 1.
- m 0.97 0.94 0.97 1.06 1.11 1.09 1.11 1.05 1.06 1.05 1.11 1.02 0.98 1.
- n 0.91 0.88 0.92 1.01 1.05 1.03 1.06 0.99 0.99 0.98 1.04 0.97 0.99 0.