Research on the Impact of Digitization and Intelligentization on the

Creation of Shared Value by Small, Medium-sized and Micro

Enterprises

Shicheng Liu

and Mengting Jin

College of Literature Law & Economics, Wuhan University of Science & Technology, Wuhan, China

Keywords: Digitization, Intelligentization, Shared Value.

Abstract: With the development of a new round of industrial upgrading and technological revolution, China's

manufacturing enterprises are also gradually moving towards the direction of digital and intelligent

transformation and upgrading. Can such enterprises benefit the society and create shared value while carrying

out transformation and upgrading? Based on the sample data of the top three representative enterprises of

China's intelligent manufacturing enterprises in 2019, this paper uses the content analysis method to measure

the shared value measures of the sample enterprises, calculates the intelligence degree of the enterprises

according to the intelligence degree im formula, and empirically analyzes the impact of the intelligence degree

of manufacturing enterprises on the shared value created by enterprises. It is found that the degree of

digitization and intelligence of enterprises plays a positive role in creating shared value. Therefore, we put

forward ten possible ways to promote enterprises to realize shared value by implementing digitization and

intelligence.

1 INTRODUCTION

In today's era, the world is rapidly entering the era of

digital economy, and the opportunities and challenges

of enterprise digital intelligent transformation and

upgrading are also coming one after another. Based

on the "Internet plus" era, the popularity of new

technologies and the impact of innovation driven, the

matching efficiency of idle resources has also been

improved, thus promoting the creation of shared

value. In the context of modern economy, shared

value plays a complementary role. It can not only

assist the government in social management, reform

the operating environment of traditional industries

and improve social welfare, but also ease labor

relations, optimize transaction relations, develop

green economy and broaden the boundary of public

goods.

Reviewing the current research status of shared

value in China, domestic scholars have provided

analysis ideas and model construction of various

industries, and provided a large number of theoretical

Fund project: Key projects of Hubei SME research center in

2022(Project No: HBSME2022B02)

ideas on how to create and realize and how to measure

shared value. But for possible new ways (combined

with digitization and intelligentization) is still rarely

involved. Therefore, this paper aims to analyze the

impact of the digitization and intelligentization of a

specific enterprise on the creation of shared value,

hoping to contribute to this research, provide some

suggestions on how to realize a more intelligent

shared value strategy, and help enterprises integrate

their own economic goals with social goals work

together.

2 LITERATURE REVIEW

Domestic and foreign scholars' research on shared

value is common in many disciplines, such as

corporate strategic management, corporate economy,

corporate social responsibility and so on. At present,

the relevant research on the concept of shared value

has not been clearly defined. The debate on relevant

research is mainly divided into two factions: one is to

890

Liu, S. and Jin, M.

Research on the Impact of Digitization and Intelligentization on the Creation of Shared Value by Small, Medium-sized and Micro Enterprises.

DOI: 10.5220/0011356400003440

In Proceedings of the International Conference on Big Data Economy and Digital Management (BDEDM 2022), pages 890-894

ISBN: 978-989-758-593-7

accept Porter's point of view, that is, shared value is

that enterprises can not only achieve their own

economic goals, but also contribute to the

improvement of community economic and social

conditions (Porter, 2011, Kramer, 2011); Others

believe that shared value is only a way to create their

own value for all stakeholders. Some scholars choose

to vaguely define shared value as a new path to help

enterprises or organizations achieve economic

achievements. So far, foreign academic circles have

still failed to give a unanimously recognized

definition of shared value. The core reason is that

three questions have not been well answered, that is,

what is the specific way to create shared value? What

results can shared value bring to us? Who are the

beneficiaries of this result?

After reviewing many foreign studies on shared

value, it can be found that although many disciplines

use the concept of shared value to enrich the relevant

theories of this discipline, they are often

misunderstood and over understood due to the lack of

unified recognition and definition. Looking at the

relevant domestic research on shared value, we can

also find that no matter what perspective the shared

value research is based on, the quantitative research

is very limited, and there are few qualitative and

quantitative studies. Therefore, this paper attempts to

adopt the generally recognized definitions and

theories of Porter and others on shared value, analyze

the specific path that enterprises can create shared

value while transforming and upgrading digital and

intelligent, and integrate the evaluation index system

of digital, intelligent and shared value to measure the

concept of shared value, Verify the impact of the

digital and intelligent development of manufacturing

enterprises on the creation of shared value.

3 RESEARCH DESIGN

Porter and others believe that shared value is a

conceptual model for enterprises to realize their own

economic interests by creating shared value to meet

social interests, which can not only help enterprises

achieve economic success, but also improve

enterprise efficiency and expand the scale of product

market. Porter believes that if enterprises want to

create shared value, they can mainly start from the

following three ways: first, rethink products and

markets; Second, redefine the productivity of the

value chain; Third, improve the local industrial

cluster environment and promote the development of

industrial clusters.

To sum up, can enterprises improve their business

efficiency, reduce their costs, expand their market

scale, increase their performance and create shared

value by taking more measures related to improving

their digital and intelligent degree, starting from the

above three ways? Therefore, this paper hopes to

conduct factor influence research from the two

directions of digitization and intelligence, obtain

certain theoretical results, and put forward

assumptions:

H1: the degree of digitization and intelligence has

a positive impact on enterprises to create shared

value. That is, the higher the degree of digitization

and intelligence of the enterprise, the more shared

value the enterprise creates.

This paper selects the top three Chinese intelligent

manufacturing enterprises from the "top 100 Chinese

intelligent manufacturing enterprises in 2019"

released by Lyon business school in France as the

research object, They are Foxconn Technology

Group (Industrial Fulian), Haier Group Corporation

and Huawei Technology Co., Ltd. obtain the text

content such as shared value measures related to

digitization and intelligence adopted by the enterprise

from the official website of the sample enterprise, the

2019 annual report released by the enterprise, the

2019 corporate social responsibility report or the

sustainable development report, and then use the

content analysis method to extract and analyze the

content analysis.

According to the current research status at home

and abroad, few studies can directly quantify the

degree of digitization and intelligence, and

digitization and intelligence are not separated.

Digitization is the basis of intelligence, and

digitization and intelligence are different stages of

enterprise development. These two stages are not

completely progressive, but also overlap to a certain

extent, Therefore, intelligence is the development

trend of digitization. In order to facilitate quantitative

research, this paper combines the digitization degree

and intelligence degree of the enterprise into the

variable of intelligence degree, constructs the

research model as shown in Fig.1, and reduces the

digitization and intelligence factors to an

intermediary factor, intelligence degree IM, so as to

analyze its impact on the creation of shared value SV.

Research on the Impact of Digitization and Intelligentization on the Creation of Shared Value by Small, Medium-sized and Micro

Enterprises

891

Figure 1: Research model.

4 VARIABLE MEASUREMENT

This paper selects the shared value of the sample

enterprises as the explained variable. Because this

variable is difficult to measure directly, this paper

mainly measures the effect of the shared value

measures implemented by the sample enterprises.

On the basis of reviewing and learning the

research results in this research field, this paper refers

to the three shared value approaches proposed by

Porter and the refinement results of these three

approaches (Fu, 2013) with reference to the research

results of Fu Hongzhen, endows the factors related to

the degree of digital intelligence, and considers the

measures taken by enterprises related to digital

intelligence, Ten shared value measures are

summarized, as shown in Tab.1. Finally, the

evaluation team will evaluate and discuss the shared

value measures implemented by the three sample

enterprises, rate them according to the

implementation and effect of a certain measure

(divided into high, medium and low levels), and

count the rating of each sample.

The explanatory variable is intelligence IM,

Referring to the research results of Deng Xiang et al.

(Deng, et al, 2019), which used the number of patent

applications related to artificial intelligence to

measure the level of artificial intelligence (Deng,

2019, Huang, 2019), Zhao Gang verified the action

mechanism of R&D investment, human capital and

intelligent equipment on the intelligent

transformation of high-end equipment manufacturing

enterprises (Zhao, 2020). Therefore, based on the

research of these scholars, this paper adds dimensions

such as R&D investment and R&D personnel, hoping

to reflect the intelligence level of intelligent

manufacturing enterprises from a more

comprehensive dimension. Finally, five indicators

are selected to construct the comprehensive

intelligence index IM of the sample enterprises: the

cumulative number of patents, the number of R&D

personnel, the ratio of the number of R&D personnel

to the total number of employees, R&D investment,

and the ratio of R&D investment to operating

revenue. According to the results of principal

component analysis conducted by Lou Yong, etc., the

component score coefficient matrix (Lou, 2021,

Wang, 2021, Hao, 2021) obtained is adopted, as

shown in Table 2. In order to make the model easy to

test, this paper takes the natural logarithm as the

comprehensive index of intelligence, and the

calculation formula of the comprehensive index of

intelligence is as follows:

IM=ln(0.325*patent+0.414*rdstaff+0.395*rdstad

en+0.024*rd+0.013rddensity)

Referring to the relevant research of Li Qinghua

et al. (Li, 2021, Guo, 2021, Liu, 2021) and Fu

Hongzhen, this paper takes the enterprise scale,

enterprise age and enterprise nature as the control

variables of the research model, and its measurement

method is shown in Tab. 2.

According to the measurement method of control

variables provided in Table 2, the measurement

results of the three sample enterprises as of 2019 are

obtained. The enterprise scale difference rate of the

three intelligent manufacturing enterprises is less

than 0.1, the enterprise age difference rate is also

within 0.1, and the nature of the enterprises is also

non-state-owned. Therefore, it can be considered that

the three enterprises have similar enterprise scale,

similar enterprise age and consistent enterprise

nature. It can be considered that these three variables

are at the same level, and there is no significant

difference in the effect on the explained variables.

Table 1: Measurement methods of control variables.

Control variable Measurement method

Enterprise scale

Natural logarithm of total assets of the enterprise at the end of 2019

Enterprise age

Number of years from establishment to 2019

Nature of enterprise

If the enterprise is state-owned or state-controlled, the value is 1, while

the value of non-state-owned or non-state-controlled is 0

BDEDM 2022 - The International Conference on Big Data Economy and Digital Management

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Table 2: Measures of shared value.

Three ways to create

shared value (number and

content)

Measurement of specific measures of

shared value (number and content)

Measurement example

Path 1: Reimagine products

and markets

SV1

：

Provide intelligent products or

services that meet social needs.

Provide smart electrical appliances

and smart terminal products.

SV2

：

Provide corresponding intelligent

products or services for the edge market.

Invest in the field of intelligence

and participate in the construction of

new concept equipment for the Internet

of Everything.

Path 2: Redefine the

productivity of the value chain

SV3

：

Incentivize outstanding employees

who have contributed to the process of enterprise

intelligence.

By formulating a series of

measures to effectively reward and

stimulate employees' potential, mobilize

employees' enthusiasm for work,

improve their innovation ability, and

retain innovative talents.

SV4

：

Develop the application of artificial

intelligence and the industrial Internet.

Establish intelligent laboratories,

robotics research institutes, etc.

SV5

：

Through the intelligent management

and innovation of the product production process,

the utilization rate of resources is improved and

the cost is reduced.

Improve the utilization rate of raw

materials through the intelligent plan

transformation of the production

process.

SV6

：

Research and develop smart devices to

save or provide energy.

Construct solar power stations and

other facilities.

Path 3: Improve the

environment of local industrial

clusters and promote the

development of industrial

clusters

SV7

：

Provide intelligent solutions for

upstream and downstream enterprises, improve

their management efficiency, and indirectly help

the enterprises themselves.

Provide suppliers with intelligent

professional talents and promote

common development and progress

with partners.

SV8

：

Cooperate with scientific research

institutions in the field of intelligence and

intelligence research institutes in universities.

Jointly establish smart project

research and development funds with

universities, organize or sponsor smart

robot competitions, etc.

SV9

：

Cooperate with universities and

vocational schools to train intelligent professional

and technical personnel.

Establish cooperative relations

with universities or vocational schools,

provide internship bases, and oriented

training of intelligent-related

professionals required by enterprises.

SV10

：

Promote the transformation and

upgrading of industrial intelligence.

Participate in the formulation of

certain technical standards for

intelligent equipment.

This paper uses the content analysis method to

collect the variable data of shared value measures of

three intelligent manufacturing sample enterprises in

2019, draws lessons from the relevant methods of

domestic scholar Zhang Yin (Zhang, 2012, Huang,

2012), and establishes a two person review group to

analyze and comment on the collected text content. In

the end, the two reviewers reached an agreement on

the evaluation results, accounting for about 97% (29

items in total). For the text content of which the

remaining 3% (1 item in total) could not reach a

consensus, a senior expert in enterprise management

was invited to assist in the analysis, and the final

evaluation results were subject to the expert opinions.

The items with different opinions of the two

reviewers were (sample 1, sv9). According to the

judgment of enterprise management experts, the

effect of this measure taken by sample 1 enterprises

is poor, and the final evaluation result is "low".

According to the calculation formula of the

explanatory variable intelligence degree IM, after

collecting five data of the three intelligent

manufacturing enterprises in 2019, including the

cumulative number of patents, the number of R&D

Research on the Impact of Digitization and Intelligentization on the Creation of Shared Value by Small, Medium-sized and Micro

Enterprises

893

personnel, the ratio of the number of R&D personnel

to the total number of employees, R&D investment,

and the ratio of R&D investment to operating

revenue, the intelligence degree rating of each

sample, the index data and the intelligence degree im

rating results are obtained, As shown in Tab.

Ⅲ

, the

final statistical results are drawn into a composite

diagram, as shown in Fig. 2.

Table 3: Analysis results of intelligence degree of each

sample.

Name Sample 1 Sample 2 Sample 3

patent

4276 53000 85000

rdstaff

40000 16679 96000

rdstaden

21.71% 16.72% 49.00%

9,427 6,711 131,659

rddensity

2.31% 3.34% 15.30%

9.8 10.1 11.16

Figure 2: SV rating times and IM rating.

It can be seen from the above figure that the

shared value SV rating of sample 3 is generally high,

ranking first; The shared value SV rating of sample 2

is slightly lower than that of sample 3, ranking

second; Sample 1 had the lowest shared value SV

rating. According to the intelligence im rating results

of the three samples, enterprises with higher

intelligence will perform better in creating shared

value.

5 CONCLUSIONS

It is found that the higher the development degree of

digitization and intelligence of manufacturing

enterprises, the more it can promote enterprises to

create shared value. In addition, this paper also

summarizes 10 possible ways for manufacturing

enterprises to improve shared value by implementing

shared value measures related to digitization and

intelligence. Enterprises taking shared value

measures is conducive to improve corporate social

responsibility and ease the conflict between corporate

social responsibility and corporate performance.

Enterprises can create more shared value while

improving the degree of digitization and intelligence,

so as to improve the social evaluation of enterprises

and bring performance growth to enterprises.

ACKNOWLEDGEMENTS

Special thanks to the funding of Key projects of

Hubei SME research center in 2022 (Project No:

HBSME2022B02).

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Sample1 Sample2 Sample3

low middle high IM

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