Investment strategies in Industry 4.0 for enhanced supply chain resilience: an empirical analysis

Figures & data

Table 1. Survey pilot results assessment methodologies.

Descriptive statistics	It involves analyzing the basic statistical properties of the survey results, such as means, standard deviations, and frequencies, to gain an overall understanding of the data’s distribution and variation. It was utilized by Rauch et al. (2009) examining entrepreneurial orientation and business performance.
Reliability analysis and internal consistency	It examines the consistency and stability of the survey instrument’s measurements by calculating Cronbach’s alpha, a measure of internal consistency. This analysis helps to identify items that may need to be revised or removed to improve the survey’s reliability. It was utilized by Alshawi et al. (2017) to investigate digital transformation in organizations
Validity analysis	It examines the extent to which the survey instrument measures what it intends to measure by assessing the survey’s content validity, construct validity, and criterion-related validity. It was used by Mohr and Webb (2005) while studying the impact of corporate social responsibility on customer loyalty.
Factor analysis	It involves grouping similar survey items into distinct factors or dimensions, which can help to identify underlying patterns and relationships within the data. It was utilized by Kim and Le (2021) while examining the job satisfaction and employee turnover.
Cognitive interviews	It involves conducting individual interviews with pilot survey respondents to assess their comprehension of the survey questions, their interpretation of the response options, and their thought processes when answering the questions. It was utilized by Hamari et al. (2014) while examining the impact of gamification on learning outcomes, the authors used cognitive interviews to assess the pilot survey respondents’ understanding of the survey questions and their interpretation of the gamification elements used in the study. It was also used by Schmidt and Rossmann (2019) to evaluate the understanding of supply chain executives about digital transformation and its impact on supply chains. It was also utilized by Indorf and Hinz (2018) evaluate the usability of digital supply chain management systems, and by Thomése et al. (2016) evaluate the usability of digital supply chain management systems.

Figure 1. Survey respondents’ category.

Figure 2. Survey respondents’ geographical distribution.

Figure 3. Recommended I4.0 technologies for SC agility.

Figure 4. Recommended I4.0 technologies for SC structure.

Figure 5. Recommended I4.0 technologies for SC visibility.

Figure 6. Recommended I4.0 technologies for SC information sharing.

Figure 7. Recommended I4.0 technologies for SC risk & revenue sharing.

Figure 8. Recommended I4.0 technologies for SC geographical distribution.

Figure 9. Recommended I4.0 technologies for SC partners collaboration.

Table 2. Survey based Roadmap: Connecting SCR & SCV drivers through I4.0.

SCV drivers SCR drivers	Supply Side Risk	Operation Process Risk	Demand Side Risk	Env. Risk
SC Agility	AI	IoT	BDA	CC
SC Structure	CC	IoT	AI	CPS
SC Visibility	IoT	IoT	CPS	BDA
Information Sharing	IoT	CC	IoT	BC
Risk & Revenue Sharing	IoT	BDA	IoT	CC
Geographical Distribution	CC	AM	BDA	AI
Collaboration with SC partners	CC	CC	BC	AI

Figure 10. I4.0 technologies with respect to GRACIAS verification channels.

Figure 11. IoT and BC with respect to GRACIAS verification channels.

Table

○	Supply chain and logistics professional and academic
○	Supply chain and logistics professional
○	Supply chain and logistics academic
○	None of the above

Table

○	I have knowledge about DSCR and Industry 4.0
○	I have knowledge about DSCR
○	I have knowledge about I4.0
○	None of the above

Table

○	North America	○	East Asia
○	South America	○	South Asia
○	Eastern Europe	○	Southeast Asia
○	Western Europe	○	Northast Asia
○	Africa	○	Oceania
○	Gulf Cooperating Council

Table

○	<999	○	5,000-9,999
○	1,000-4,999	○	10,000-99,999

Table

○	Diploma	○	Master’s degree
○	Bachelor’s degree	○	PhD or higher

Table

○	Less than five	○	11 to 20
○	6 to 10	○	More than 20

Table

○	To a great extent	○	To minor extent
○	To a moderate extent	○	I don’t know

Table

1)	SC Agility,	5)	SC Revenue & Risk sharing,
2)	SC Structure,	6)	SC Geographical Distribution, and
3)	SC Visibility,	7)	Collaboration with SC Partners.
4)	SC Information Sharing,

Table

1)	Supply side risk,	3)	Demand side risk
2)	Operation process risk,	4)	Environment risk

Table

	Supply Side Risk	Operation Process Risk	Demand Side Risk	Environment Risk
Additive Manufacturing	○	○	○	○
Artificial Intellegence	○	○	○	○
Cloud Computing	○	○	○	○
Blockchain	○	○	○	○
Internet of Things	○	○	○	○
Big Data Analytics	○	○	○	○
Cyber Physical Systems	○	○	○	○

Table

	Supply Side Risk	Operation Process Risk	Demand Side Risk	Environment Risk
Additive Manufacturing	○	○	○	○
Artificial Intellegence	○	○	○	○
Cloud Computing	○	○	○	○
Blockchain	○	○	○	○
Internet of Things	○	○	○	○
Big Data Analytics	○	○	○	○
Cyber Physical Systems	○	○	○	○

Table

	Supply Side Risk	Operation Process Risk	Demand Side Risk	Environment Risk
Additive Manufacturing	○	○	○	○
Artificial Intellegence	○	○	○	○
Cloud Computing	○	○	○	○
Blockchain	○	○	○	○
Internet of Things	○	○	○	○
Big Data Analytics	○	○	○	○
Cyber Physical Systems	○	○	○	○

Table

	Supply Side Risk	Operation Process Risk	Demand Side Risk	Environment Risk
Additive Manufacturing	○	○	○	○
Artificial Intellegence	○	○	○	○
Cloud Computing	○	○	○	○
Blockchain	○	○	○	○
Internet of Things	○	○	○	○
Big Data Analytics	○	○	○	○
Cyber Physical Systems	○	○	○	○

Table

	Supply Side Risk	Operation Process Risk	Demand Side Risk	Environment Risk
Additive Manufacturing	○	○	○	○
Artificial Intellegence	○	○	○	○
Cloud Computing	○	○	○	○
Blockchain	○	○	○	○
Internet of Things	○	○	○	○
Big Data Analytics	○	○	○	○
Cyber Physical Systems	○	○	○	○

Table

	Supply Side Risk	Operation Process Risk	Demand Side Risk	Environment Risk
Additive Manufacturing	○	○	○	○
Artificial Intellegence	○	○	○	○
Cloud Computing	○	○	○	○
Blockchain	○	○	○	○
Internet of Things	○	○	○	○
Big Data Analytics	○	○	○	○
Cyber Physical Systems	○	○	○	○

Table

	Supply Side Risk	Operation Process Risk	Demand Side Risk	Environment Risk
Additive Manufacturing	○	○	○	○
Artificial Intellegence	○	○	○	○
Cloud Computing	○	○	○	○
Blockchain	○	○	○	○
Internet of Things	○	○	○	○
Big Data Analytics	○	○	○	○
Cyber Physical Systems	○	○	○	○

Table

	G	R	A	C	I	A	S
Additive Manufacturing	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]
Artificial Intellegence	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]
Cloud Computing	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]
Blockchain	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]
Internet of Things	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]
Big Data Analytics	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]
Cyber Physical Systems	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]	[1….7]

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