Determining the priority levels of criteria for evaluating the digital transformation level of businesses in vietnam nguyen thi anh tuyet

Six criteria are used to assess the digital transformation level of businesses in Vietnam, including infrastructure and digital technology, data and information assets, strategy, digital

International Journal of Management & Entrepreneurship Research

International Journal of Management & Entrepreneurship Research

International Journal of Management & Entrepreneurship Research Vol 5 No 6 (2023)

Published: 2023-06-01

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• DETERMINING THE PRIORITY LEVELS OF CRITERIA FOR EVALUATING THE DIGITAL TRANSFORMATION LEVEL OF BUSINESSES IN VIETNAM

Luu Huu Van, Nguyen Thi Anh Tuyet

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International Journal of Management & Entrepreneurship Research, Volume 5, Issue 6, June 2023

DETERMINING THE PRIORITY LEVELS OF CRITERIA FOR EVALUATING THE DIGITAL TRANSFORMATION

LEVEL OF BUSINESSES IN VIETNAM

Luu Huu Van1 & Nguyen Thi Anh Tuyet2

1

Academy of Policy and Development, Ministry of Planning and Investment,

Nam An Khanh Urban Area, Hanoi 100000, Vietnam

2

East Asia University of Technology, Trinh Van Bo Road, Hanoi 100000, Vietnam

_

Corresponding Author: Nguyen Thi Anh Tuyet

Corresponding Author Email: tuandat151107@gmail.com

Article Received: 03-05-23 Accepted: 29-05-23 Published: 13-06-23 Licensing Details: Author retains the right of this article The article is distributed under the terms of

the Creative Commons Attribution-Non Commercial 4.0 License ( http://www.creativecommons.org/licences/by-nc/4.0/ ), which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the Journal open access page

_

ABSTRACT

The objective of this research is to determine the priority levels of criteria for evaluating the digital transformation level of businesses in Vietnam In this study, the Analytic Hierarchy Process (AHP) method using fuzzy numbers is employed Data for the research is collected through interviews with a group of experts and managers Six criteria are used to assess the digital transformation level of businesses in Vietnam, including infrastructure and digital technology, data and information assets, strategy, digital transformation of corporate culture, digital experience for customers, and operations The analysis results indicate that the infrastructure and digital technology criterion plays the most important role in assessing the digital transformation level of businesses in Vietnam

Keywords: AHP, Digital Transformation Level, Fuzzy Numbers

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INTRODUCTION

Digital transformation plays a crucial role in impacting the entire organization and bringing about changes in various aspects of the business such as work processes, infrastructure,

OPEN ACCESS

International Journal of Management & Entrepreneurship Research

P-ISSN: 2664-3588, E-ISSN: 2664-3596

Volume 5, Issue 6, P.No.410-417, June 2023

DOI:10.51594/ijmer.v5i6.500

Fair East Publishers

Journal Homepage: www.fepbl.com/index.php/ijmer

International Journal of Management & Entrepreneurship Research, Volume 5, Issue 6, June 2023

business models, and human resource management (Gilchrist, 2016; Schallmo et al., 2017; Hausberg et al., 2019) Digital transformation contributes to increased productivity and wealth, encompassing both digitization and digitalization (Autio, 2017; Rose and Chilvers, 2018; Vial, 2019; Kelly Rijswijk et al., 2021) Digitization and intelligent automation will contribute to the overall increase in global domestic product in the coming years (Pricewaterhouse Coopers, 2019)

Digital transformation can be applied to all aspects of the agricultural system and reflects the change in managing overall resources towards high optimization, individualized, intelligent, and predictive management, in real-time, super-connected, and data-driven (Trendov et al., 2019) Some studies indicate that digital transformation is a solution to the challenges that agriculture faces as part of the transition to Agriculture 4.0 and contributes to transforming the agricultural system (World Bank, 2019; Trendov et al., 2019; Klerkx and Rose, 2020; Herrero

et al., 2021; Klerkx and Begemann, 2020) Kelly Rijswijk et al (2021) have pointed out that digital technology is often seen as an opportunity to create a sustainable future for agriculture Therefore, digital transformation in agriculture is considered a global policy priority (Trendov

et al., 2019; World Bank, 2017, 2019; Kelly Rijswijk et al., 2021)

However, currently, the majority of small and medium-sized enterprises (SMEs) in developing countries in general and Vietnam in particular still lack awareness of the importance of digital transformation These businesses are not truly prepared for digital transformation, thus they are unable to build and transition to digital business models and take advantage of the opportunities brought about by digitization (Lokuge et al., 2019) Vietnam, with its starting point as a relatively backward economy, faces limitations in harnessing the advantages of the agricultural sector Small and medium-sized enterprises still have certain limitations Therefore, keeping up with the trends of the times is essential during the period of integration Vietnam is an agricultural country, with a significant portion of its land being coastal areas, thus the development of the advantages of the agricultural sector holds great potential

In recent years, most basic infrastructure and digital technology groups in agriculture have been deployed or started to be tested in Vietnam and other developing countries Some models and standards have been used to analyze and assess the level of digital transformation

in small and medium-sized enterprises, as indicated in recent studies Baumüller (2015) highlighted the application of GIS technology and remote sensing to develop software for early detection and warning of forest fires from satellite images, software for monitoring and early detection of forest loss and degradation Additionally, the M-Farm application in Kenya led to farmers changing their farming models, resulting in higher market prices Jerome Buvat

et al (2017) pointed out that the cultural factor within businesses also plays an important role

in digital transformation Businesses need to change their mission, vision, and core values to engage employees in the process of change and cultural transformation within the organization Juan Antonio et al (2020) revealed that in the field of livestock farming, the Internet of Things (IoT) technology, including basic communication infrastructure, is used to connect smart objects ranging from sensors, vehicles, mobile devices to remote data collection based on intelligent analysis, user communication, and agricultural revolution Carlos et al (2021) analyzed digital transformation in the olive industry in the short and medium term using various methods such as SWOT, PESTLE, and the Analytic Hierarchy Process (AHP)

International Journal of Management & Entrepreneurship Research, Volume 5, Issue 6, June 2023

Criteria such as technology, technical level, and socio-economic and political factors were used in the research to analyze digital transformation in the agricultural sector in the Andalusia region The criterion of digital customer experience has also been highlighted by several authors in the context of digital transformation Ameen et al (2021) developed a theoretical model integrating trust and sacrifice, which are considered intermediate factors for the impacts of the remaining four factors, including individual, convenience, service quality, and AI support Huang et al (2021) identified four main customer experiences with service robots, including experiences of decision-making hesitation, perceptual experiences, emotional experiences, and affection experiences Molinillo et al (2022) conducted a survey

of 545 users of retail applications to study the retail application experience of customers in relation to customer loyalty These technologies will have their own position and impact in the agricultural value chain and can provide the agriculture sector with tools and information for more informed decision-making, improved productivity, and effective management Strategic standards are also one of the important criteria that affect the digital transformation

of businesses

Fernandez-Vidal et al (2021) have pointed out that most companies choose small transformation strategies to achieve larger transformation goals The research provides conceptual guidelines for selecting appropriate strategic tools Chanias et al (2019) analyzed digital transformation strategic planning in digital organizations from the perspective of a financial service provider The article highlights the model's results, which indicate that digital transformation strategy is a highly dynamic process involving iterative learning and doing Orhan et al (2022) identified the driving force behind business strategies, and digital transformation has enabled significant changes in the passenger journey of airlines In the context of the Covid-19 pandemic, digital infrastructure standards are also one of the important criteria that impact digital transformation in businesses worldwide Most businesses have had to operate and work remotely, transitioning to digital operations Employees and business leaders have had to enhance their technological capabilities or apply technologies in their business operations (Breier et al., 2020; Paolo and Lapo, 2022) The application of digital infrastructure contributes to cost reduction, helps limit and increase the value of products, and improves product quality, bringing new breakthroughs for businesses Nowadays, businesses are adopting data modeling, which brings benefits such as cost reduction, time-saving in data analysis and evaluation, and helps identify business principles and processes Therefore, according to the author, data and company assets are also important criteria with significant impact on digital transformation in small and medium-sized enterprises Furthermore, operational standards are also an important criterion that influences the digital transformation process in businesses Businesses with sound and proper operational practices will bring effectiveness and stability to the company Table 1 presents 6 groups of criteria for measuring the level of digital transformation in businesses

Table 1

Criteria for Measuring the Level of Digital Transformation in Businesses

No Criteria References

1 Infrastructure and

Digital Technology (C1)

Baumüller (2015), Jerome Buvat et al (2017), Chanias et al (2019), Fernandez-Vidal et al (2019), Juan Atonio et al (2020), Breier et al (2020), Carugati et al (2020), Ameen et al (2021), Huang et al (2021), Carlos et al (2021), Molinillo et al (2022), Orhan et al (2022), Paolo and Lapo (2022)

2 Data and Information

Assets (C2)

International Journal of Management & Entrepreneurship Research, Volume 5, Issue 6, June 2023

3 Strategy (C3)

4

Digital Transformation

of Organizational

Culture (C4)

5 Digital Customer

Experience (C5)

6 Operations (C6)

Fuzzy AHP

In this study, the fuzzy analytic hierarchy process (FAHP) proposed by Chang (1996) was used to determine the priority level of the digital transformation measurements for businesses The steps of Chang's (1996) method are presented as follows:

Step 1: Determine the value of the fuzzy composite number

The value of the fuzzy composite number for the i-th criterion is calculated using the Equation:

1



 

   

 

  (1)

where:

i

j

1 1

i

n m

j

i j

 



i = 1, 2, …., n; j = 1,2,…, m

Step 2: Comparison of two fuzzy numbers

The degree of possibility of the comparison between two fuzzy numbers is determined as follows:

1 2

y x



    (2)

Theo đó, V S( 1S2)

l u

l u

others





 



  



Step 3: Calculate the degree of possibility of the occurrence of the relationship that a fuzzy number is better than the remaining fuzzy numbers

Step 4: Calculate the vector W'

W '( '(d A), '(d A ), , '(d A n))T (5) assuming that:

'( i) minV(Si t)

d A  S and i= 1,2,…, n; t = 1, 2, ….n and i ≠ t

Normalized weights:

International Journal of Management & Entrepreneurship Research, Volume 5, Issue 6, June 2023

W( (d A), (d A ), , d(A ))n T và

1

W W

i

i n

i i

W





The Application of the Analytic Hierarchy Process in Determining the Priority Level of Digital Transformation Measurement Criteria in Businesses in Vietnam

Table 2 presents the linguistic variables and corresponding fuzzy numbers used in the study The research's input data was collected through in-depth interviews with experts

Table 2

Linguistic Variables and Fuzzy Numbers

Levels Fuzzy number Inverse fuzzy number Definition

1 (1,1,1) (1,1,1) Equally important

2 (2,3,4) (1/4,1/3,1/2) Somewhat more important

3 (4,5,6) (1/6,1/5,1/4) More important

4 (6,7,8) (1/8,1/7,1/6) Much more important

5 (9,9,9) (1/9,1/9,1/9) Extremely more important

a Determine the comparative relationship between pairs of criteria Table 3 presents the average comparison values between the criteria for measuring the level of digital transformation of businesses based on expert interviews and Table 1

Table 3

Average Comparison Values between Criteria

C1 (1, 1, 1) (6,7,8) (9,9,9) (4,5,6) (2,3,4) (2,3,4)

C2 (0.13,0.14,0.1

(0.25,0.33,0.50 )

(0.17,0.20,0.25 )

(0.17,0.20,0.2 5)

C3 (0.11,0.11,0.1

1)

(0.25,0.33,0.50

(0.17,0.20,0.25 )

(0.13,0.14,0.17 )

(0.13,0.14,0.1 7)

C4 (0.17,0.20,0.2

5) (2,3,4) (4,5,6) (1,1,1)

(0.25,0.33,0.50 )

(0.25,0.33,0.5 0)

C5 (0.25,0.33,0.5

0) (4,5,6) (6,7,8) (2,3,4) (1,1,1)

(1,1,1)

C6 (0.25,0.33,0.5

0) (4,5,6) (6,7,8) (2,3,4) (1,1,1)

(1,1,1)

b Calculate the aggregated value for criteria

Table 4 presents the aggregated values of the criteria for measuring the level of digital transformation of businesses using Equation 1

Table 4

Aggregated Values of the Criteria

TT Criteria Aggregated Values

1 C1 (0.256,0.353,0.487)

2 C2 (0.040,0.061,0.094)

3 C3 (0.019,0.024,0.033)

4 C4 (0.082,0.124,0.187)

5 C5 (0.152,0.218,0.312)

6 C6 (0.152,0.218,0.312)

c Comparison between two aggregated values

Using equations 2 and 3, the comparison results between the aggregated values are presented

in Table 5

International Journal of Management & Entrepreneurship Research, Volume 5, Issue 6, June 2023

Table 5

Comparison Results between Criteria

Comparison Value Comparison Value Comparison Value Comparison Value Comparison Value

V(S1>=S2) 1 V(S2>=S1) 0 V(S3>=S1) 0 V(S4>=S1) 0 V(S5>=S1) 0.29 V(S1>=S3) 1 V(S2>=S3) 1 V(S3>=S2) 0 V(S4>=S2) 1 V(S5>=S2) 1 V(S1>=S4) 1 V(S2>=S4) 0.16 V(S3>=S4) 0 V(S4>=S3) 1 V(S5>=S3) 1 V(S1>=S5) 1 V(S2>=S5) 0 V(S3>=S5) 0 V(S4>=S5) 0.27 V(S5>=S4) 1

Table 6

Occurrence Level of One Criterion being More Important than the Remaining Criteria

The occurrence level of the relationship Values

d Determining the importance level of the criteria

Table 7 presents the results of the importance level of the criteria measuring the digital transformation of businesses using equation (6)

Table 7

Importance Level of the Criteria

Importance level Value

The analysis results from Table 7 reveal the priority level of the weights: the criterion Infrastructure and Digital Technology (C1) has the highest impact on digital transformation in the agricultural sector, with an impact level of W(C1) = 0.539 The two criteria Customer Digital Experience (C5) and Operations (C6) have the same impact level of W(C5) = W(C6)

= 0.158, making them the second most influential factors/criteria in the digital transformation

of the agricultural sector The fourth most impactful criterion on digital transformation in the agricultural sector is Digital Transformation of Organizational Culture (C4), with an impact level of W(C4) = 0.144 Lastly, the two criteria Data and Information Assets (C2) and Strategy (C3) have no impact on digital transformation in the agricultural sector, with impact levels of W(C2) = W(C3) = 0

CONCLUSION AND RECOMMENDATIONS

Based on the overview and research findings, digital transformation is an inevitable trend for businesses To achieve successful digital transformation, businesses need to focus on the criteria analyzed in Table 7 However, particular attention should be given to the

"Infrastructure and Digital Technology" factor as it has the highest impact level Subsequently, businesses should gradually lower the priority for the remaining factors The second-priority criteria are "Customer Digital Experience" and "Operations." Specifically, the criterion "Customer Digital Experience" involves applying digital tools and platforms to business operations to support customers in choosing products and services The next priority criterion is "Digital Transformation of Organizational Culture." Lastly, the two criteria that

International Journal of Management & Entrepreneurship Research, Volume 5, Issue 6, June 2023

have no impact on digital transformation in the agricultural sector are "Data and Information Assets" and "Strategy," both with an impact level of 0 This is not reasonable as impact levels should be greater than 0 This limitation highlights the need for future improvement of the Analytic Hierarchy Process (AHP) method or the application of more suitable methods to determine the priority level of criteria for assessing the level of digital transformation in businesses

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