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CSR and Blockchain technology: A
proposed model for sustainable growth
Dr. Kuldeep Singh
Assistant Professor
JAIN (Deemed to be University)
Introduction
• CSR refers to the obligations of businessmen to pursue those policies, to make those decisions, or to follow those lines
of action which are desirable in terms of the objectives and values of our society.
“Howard Bowen 1953”
• The Indian Companies Act, 2013
• Section 135 of the Companies Act, 2013 prescribes the requirements of CSR on certain companies.
Fig. 1 Applicability of CSR Provision
CSR Eco-System
Reference for critical parts of an eco-system has been taken from Indian Philanthropy report, 2014, by Bain & Co.
CSR Eco-System
Objective of the study
• To know the factors related to technology and
firms’ socially responsive behavior influencing
Sustainable Growth.
• To know the relationship between factors.
• To prioritize the sustainable growth Factors.
Data and Methodology
• The first phase includes an extensive literature
review to find out 10 factors.
• Final selection of factors has been made by
having discussions and interviews with experts.
• In the second phase, we have used ISM
modeling to determine the contextual
relationship between factors.
Why ISM and MICMAC ?
• Interpretive structural modeling (ISM) is a well-established
methodology for identifying relationships among specific
items, which define a problem or an issue.
• ISM approach starts with an identification of variables, which
are relevant to the problem or issue.
• Then a contextually relevant subordinate relation is chosen.
• Having decided the contextual relation, a structural self-
interaction matrix (SSIM) is developed based on pairwise
comparison of variables.
• After this, SSIM is converted into a reachability matrix (RM)
and its transitivity is checked. Once transitivity embedding is
complete, a matrix model is obtained. Then, the partitioning of
the elements and an extraction of the structural model called
ISM is derived.
• The purpose of MICMAC analysis is to analyze
the drive power and dependence power of
factors. MICMAC principle is based on
multiplication properties of matrices26. It is done
to identify the key factors that drive the system in
various categories. Based on their drive power
and dependence power, the factors, have been
classified into four categories i.e. autonomous
factors, linkage factors, dependent and
independent factors.
Enablers List
Sr. No. Enablers References Expert Mean Score
1 Sustainable Growth Babcock, 1970 [16]; Dutia, 2014
[17]
4.09
2 CSR Singh & Misra, 2021 [12] 3.82
3 Blockchain Technology Yadav, Misra, & Goundar, 2020 [18]
Singh, Misra, & Yadav, 2022 [19]
3.73
4 Competitive Market Conditions Nabiullina et al., 2016 [20] 4.09
5 Voluntary Management of Social and
Environmental Issues
Lee & Lee, 2019 [21] 4.18
6 Stakeholder Relationships Mainardes, Alves, & Raposo, 2012
[22]
3.64
7 Responsive Governance Bekkers, 2005 [23] 3.73
8 Sustainable Strategy Carneiro et al., 2016 [24] 3.45
9 Transparency and security of Transaction
Information
Xu et al., 2021 [25]; Yadav, Misra,
Rana, Singh, & Goundar, 2022 [26]
3.55
10 Technological Connectivity Schultz, Castelló, & Morsing, 2013
[27]
4
Structural self-interaction matrix
• Four symbols are used to explain the
relationship.
• V Variable i helps in achieving benefits for variable j
• A Variable j helps in achieving benefits for variable i
• X Variable i and Variable j helps in attaining benefits for
themselves
• O benefits of the variable i and variable j are not related
• Based on the V, A, X, O methodology the self-structured
interaction matrix (SSIM) is developed for the 10 factors
essential for sustainable growth
SSIM matrix of agripreneur
inclination model
F10 F9 F8 F7 F6 F5 F4 F3 F2 F1
F1 A A A A A A O A A
F2 A V A A V A V A
F3 V V A V O O V
F4 A V A A O A
F5 A V A X V
F6 A O A A
F7 V V A
F8 V V
F9 A
F10
Reachability Matrix
• The reachability matrix is derived from the SSIM.
• The symbols (V, A, X, O) are substituted with
binary numbers (0 and 1). The subsequent rule
is used to replace V, A, X, and O of SSIM to get
the initial reachability matrix.
Rules to replace VAXO to get
Reachability Matrix
SSIM matrix Reachability matrix (ij) Reachability matrix (ji)
• if i, j entry in the SSIM matrix is V in the reachability matrix i, j entry
becomes 1
in the reachability matrix j, i entry
becomes 0
• if i, j entry in the SSIM matrix is A in the reachability matrix i, j entry
becomes 0
in the reachability matrix j, i entry
becomes 1
if i, j entry in the SSIM matrix is X in the reachability matrix i, j entry
becomes 1
in the reachability matrix j, i entry
becomes 1
• if i, j entry in the SSIM matrix is O in the reachability matrix i, j entry
becomes 0
in the reachability matrix j, i entry
becomes 0
Initial reachability matrix
Enablers E -1 E -2 E -3 E -4 E -5 E -6 E -7 E -8 E -9 E-10
E-1 1 0 0 0 0 0 0 0 0 0
E-2 1 1 0 1 0 1 0 0 1 0
E-3 1 1 1 1 0 0 1 0 1 1
E-4 0 0 0 1 0 0 0 0 1 0
E-5 1 1 0 1 1 1 1 0 1 0
E-6 1 0 0 0 0 1 0 0 0 0
E-7 1 1 0 1 1 1 1 0 1 1
E-8 1 1 1 1 1 1 1 1 1 1
E-9 1 0 0 0 0 0 0 0 1 0
E-10 1 1 0 1 0 1 0 0 1 1
Final Reachability Matrix with
Transitivity Analysis
Enablers E-1 E-2 E-3 E-4 E-5 E-6 E-7 E-8 E-9 E-10 Driv. P.
E-1 1 0 0 0 0 0 0 0 0 0 1
E-2 1 1 0 1 0 1 0 0 1 0 5
E-3 1 1 1 1 1* 1* 1 0 1 1 9
E-4 1* 0 0 1 0 0 0 0 1 0 3
E-5 1 1 0 1 1 1 1 0 1 1* 8
E-6 1 0 0 0 0 1 0 0 0 0 2
E-7 1 1 0 1 1 1 1 0 1 1 8
E-8 1 1 1 1 1 1 1 1 1 1 10
E-9 1 0 0 0 0 0 0 0 1 0 2
E-10 1 1 0 1 0 1 0 0 1 1 6
Dep. P. 10 6 2 7 4 7 4 1 8 5 54
Sustainable Growth
Competitive Market Conditions
Technological Connectivity
CSR
Blockchain Technology
Sustainable Strategy
Responsive Governance
Voluntary Management of Social and Environmental Issues
Stakeholder Relationships Transparency and Security of Transactions
Finding and Outcomes
• The matrix of Cross Impacts - Multiplication
Applied to a Classification (MICMAC) is used
to define the outcomes of this present study.
• This analysis is used to classify the key
variables into four categories namely,
dependent criterion, independent criterion,
autonomous criterion, and linkage criterion.
• The identification and classification are made
on the basis of driving force and dependence
power of all the factors.
Conclusion
• This study provides a hierarchal structure of technology and
socially responsible enablers.
• ISM model shows that sustainable strategy is an important
factor that influences the use of Blockchain technology for
managing the socially responsible activities towards attaining
the sustainable growth.
• The finding draws attention to corporates and institutional
heads for their support and continuously giving efforts for
making social contribution in a responsive governance
framework.
• Some other factors can also be considered for future study.
The study used only expert mining for validation of factors. As
no statistical validation has been tackled, therefore researcher
can apply structural equation modeling (SEM) in their future
study for further statistical validation.
References
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Cryptocurrencies, vol. 1, no. 2, p. 154, 2020, doi: 10.1504/IJBC.2020.108997.
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Thank you

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IEEE-DSITM_PPT.pptx

  • 1. CSR and Blockchain technology: A proposed model for sustainable growth Dr. Kuldeep Singh Assistant Professor JAIN (Deemed to be University)
  • 2. Introduction • CSR refers to the obligations of businessmen to pursue those policies, to make those decisions, or to follow those lines of action which are desirable in terms of the objectives and values of our society. “Howard Bowen 1953” • The Indian Companies Act, 2013 • Section 135 of the Companies Act, 2013 prescribes the requirements of CSR on certain companies. Fig. 1 Applicability of CSR Provision
  • 3. CSR Eco-System Reference for critical parts of an eco-system has been taken from Indian Philanthropy report, 2014, by Bain & Co.
  • 5. Objective of the study • To know the factors related to technology and firms’ socially responsive behavior influencing Sustainable Growth. • To know the relationship between factors. • To prioritize the sustainable growth Factors.
  • 6. Data and Methodology • The first phase includes an extensive literature review to find out 10 factors. • Final selection of factors has been made by having discussions and interviews with experts. • In the second phase, we have used ISM modeling to determine the contextual relationship between factors.
  • 7. Why ISM and MICMAC ? • Interpretive structural modeling (ISM) is a well-established methodology for identifying relationships among specific items, which define a problem or an issue. • ISM approach starts with an identification of variables, which are relevant to the problem or issue. • Then a contextually relevant subordinate relation is chosen. • Having decided the contextual relation, a structural self- interaction matrix (SSIM) is developed based on pairwise comparison of variables. • After this, SSIM is converted into a reachability matrix (RM) and its transitivity is checked. Once transitivity embedding is complete, a matrix model is obtained. Then, the partitioning of the elements and an extraction of the structural model called ISM is derived.
  • 8. • The purpose of MICMAC analysis is to analyze the drive power and dependence power of factors. MICMAC principle is based on multiplication properties of matrices26. It is done to identify the key factors that drive the system in various categories. Based on their drive power and dependence power, the factors, have been classified into four categories i.e. autonomous factors, linkage factors, dependent and independent factors.
  • 9. Enablers List Sr. No. Enablers References Expert Mean Score 1 Sustainable Growth Babcock, 1970 [16]; Dutia, 2014 [17] 4.09 2 CSR Singh & Misra, 2021 [12] 3.82 3 Blockchain Technology Yadav, Misra, & Goundar, 2020 [18] Singh, Misra, & Yadav, 2022 [19] 3.73 4 Competitive Market Conditions Nabiullina et al., 2016 [20] 4.09 5 Voluntary Management of Social and Environmental Issues Lee & Lee, 2019 [21] 4.18 6 Stakeholder Relationships Mainardes, Alves, & Raposo, 2012 [22] 3.64 7 Responsive Governance Bekkers, 2005 [23] 3.73 8 Sustainable Strategy Carneiro et al., 2016 [24] 3.45 9 Transparency and security of Transaction Information Xu et al., 2021 [25]; Yadav, Misra, Rana, Singh, & Goundar, 2022 [26] 3.55 10 Technological Connectivity Schultz, Castelló, & Morsing, 2013 [27] 4
  • 10. Structural self-interaction matrix • Four symbols are used to explain the relationship. • V Variable i helps in achieving benefits for variable j • A Variable j helps in achieving benefits for variable i • X Variable i and Variable j helps in attaining benefits for themselves • O benefits of the variable i and variable j are not related • Based on the V, A, X, O methodology the self-structured interaction matrix (SSIM) is developed for the 10 factors essential for sustainable growth
  • 11. SSIM matrix of agripreneur inclination model F10 F9 F8 F7 F6 F5 F4 F3 F2 F1 F1 A A A A A A O A A F2 A V A A V A V A F3 V V A V O O V F4 A V A A O A F5 A V A X V F6 A O A A F7 V V A F8 V V F9 A F10
  • 12. Reachability Matrix • The reachability matrix is derived from the SSIM. • The symbols (V, A, X, O) are substituted with binary numbers (0 and 1). The subsequent rule is used to replace V, A, X, and O of SSIM to get the initial reachability matrix.
  • 13. Rules to replace VAXO to get Reachability Matrix SSIM matrix Reachability matrix (ij) Reachability matrix (ji) • if i, j entry in the SSIM matrix is V in the reachability matrix i, j entry becomes 1 in the reachability matrix j, i entry becomes 0 • if i, j entry in the SSIM matrix is A in the reachability matrix i, j entry becomes 0 in the reachability matrix j, i entry becomes 1 if i, j entry in the SSIM matrix is X in the reachability matrix i, j entry becomes 1 in the reachability matrix j, i entry becomes 1 • if i, j entry in the SSIM matrix is O in the reachability matrix i, j entry becomes 0 in the reachability matrix j, i entry becomes 0
  • 14. Initial reachability matrix Enablers E -1 E -2 E -3 E -4 E -5 E -6 E -7 E -8 E -9 E-10 E-1 1 0 0 0 0 0 0 0 0 0 E-2 1 1 0 1 0 1 0 0 1 0 E-3 1 1 1 1 0 0 1 0 1 1 E-4 0 0 0 1 0 0 0 0 1 0 E-5 1 1 0 1 1 1 1 0 1 0 E-6 1 0 0 0 0 1 0 0 0 0 E-7 1 1 0 1 1 1 1 0 1 1 E-8 1 1 1 1 1 1 1 1 1 1 E-9 1 0 0 0 0 0 0 0 1 0 E-10 1 1 0 1 0 1 0 0 1 1
  • 15. Final Reachability Matrix with Transitivity Analysis Enablers E-1 E-2 E-3 E-4 E-5 E-6 E-7 E-8 E-9 E-10 Driv. P. E-1 1 0 0 0 0 0 0 0 0 0 1 E-2 1 1 0 1 0 1 0 0 1 0 5 E-3 1 1 1 1 1* 1* 1 0 1 1 9 E-4 1* 0 0 1 0 0 0 0 1 0 3 E-5 1 1 0 1 1 1 1 0 1 1* 8 E-6 1 0 0 0 0 1 0 0 0 0 2 E-7 1 1 0 1 1 1 1 0 1 1 8 E-8 1 1 1 1 1 1 1 1 1 1 10 E-9 1 0 0 0 0 0 0 0 1 0 2 E-10 1 1 0 1 0 1 0 0 1 1 6 Dep. P. 10 6 2 7 4 7 4 1 8 5 54
  • 16. Sustainable Growth Competitive Market Conditions Technological Connectivity CSR Blockchain Technology Sustainable Strategy Responsive Governance Voluntary Management of Social and Environmental Issues Stakeholder Relationships Transparency and Security of Transactions
  • 17. Finding and Outcomes • The matrix of Cross Impacts - Multiplication Applied to a Classification (MICMAC) is used to define the outcomes of this present study. • This analysis is used to classify the key variables into four categories namely, dependent criterion, independent criterion, autonomous criterion, and linkage criterion. • The identification and classification are made on the basis of driving force and dependence power of all the factors.
  • 18.
  • 19. Conclusion • This study provides a hierarchal structure of technology and socially responsible enablers. • ISM model shows that sustainable strategy is an important factor that influences the use of Blockchain technology for managing the socially responsible activities towards attaining the sustainable growth. • The finding draws attention to corporates and institutional heads for their support and continuously giving efforts for making social contribution in a responsive governance framework. • Some other factors can also be considered for future study. The study used only expert mining for validation of factors. As no statistical validation has been tackled, therefore researcher can apply structural equation modeling (SEM) in their future study for further statistical validation.
  • 20. References • [1] D. Jamali and R. Mirshak, “Corporate Social Responsibility (CSR): Theory and Practice in a Developing Country Context,” J. Bus. Ethics, vol. 72, no. 3, pp. 243–262, Mar. 2007, doi: 10.1007/s10551-006-9168-4. • [2] M. Tingchi Liu, I. Anthony Wong, C. Rongwei, and T.-H. Tseng, “Do perceived CSR initiatives enhance customer preference and loyalty in casinos?,” Int. J. Contemp. Hosp. Manag., vol. 26, no. 7, pp. 1024–1045, Oct. 2014, doi: 10.1108/IJCHM-05-2013-0222. • [3] F. Zerbini, “CSR Initiatives as Market Signals: A Review and Research Agenda,” J. Bus. Ethics, vol. 146, no. 1, pp. 1–23, Nov. 2017, doi: 10.1007/s10551-015-2922-8. • [4] J. Yadav, M. Misra, and S. Goundar, “An overview of food supply chain virtualisation and granular traceability using blockchain technology,” Int. J. Blockchains Cryptocurrencies, vol. 1, no. 2, p. 154, 2020, doi: 10.1504/IJBC.2020.108997. • [5] R. Bustami, D. Na, E. Nasruddin, and S. R. A’mmari, “Exploring ISO 26000 and Global Reporting Initiatives (GRI): a neo-institutional analysis of two CSR institutions,” Int. Econ. Lett., vol. 2, no. 2, pp. 10–18, 2013. • [6] M. P. Sharfman and C. S. Fernando, “Environmental risk management and the cost of capital,” Strateg. Manag. J., vol. 29, no. 6, pp. 569–592, Jun. 2008, doi: 10.1002/smj.678. • [7] A. Bhattacharya, V. Good, H. Sardashti, and J. Peloza, “Beyond Warm Glow: The Risk-Mitigating Effect of Corporate Social Responsibility (CSR),” J. Bus. Ethics, vol. 171, no. 2, pp. 317–336, Jun. 2021, doi: 10.1007/s10551-020-04445-0. • [8] M. Karwowski and M. Raulinajtys‐Grzybek, “The application of corporate social responsibility (CSR) actions for mitigation of environmental, social, corporate governance (ESG ) and reputational risk in integrated reports,” Corp. Soc. Responsib. Environ. Manag., vol. 28, no. 4, pp. 1270–1284, Jul. 2021, doi: 10.1002/csr.2137. • [9] M. Morsing and L. J. 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Manag., vol. 51, no. 3, pp. 305–324, Jan. 2021, doi: 10.1108/IJPDLM-08-2019-0234. • [26] J. Yadav, M. Misra, N. P. Rana, K. Singh, and S. Goundar, “Netizens’ behavior towards a blockchain-based esports framework: a TPB and machine learning integrated approach,” Int. J. Sport. Mark. Spons., vol. 23, no. 4, pp. 665–683, Aug. 2022, doi: 10.1108/IJSMS-06-2021-0130. • [27] F. Schultz, I. Castelló, and M. Morsing, “The Construction of Corporate Social Responsibility in Network Societies: A Communication View,” J. Bus. Ethics, vol. 115, no. 4, pp. 681–692, Jul. 2013, doi: 10.1007/s10551-013-1826-8.