A Study of the Competitiveness and Development Strategy of Korean Venture Companies in the Fourth Industrial Revolution Using SWOT/AHP

Abstract

This study derives the SWOT (Strength, Weakness, Opportunity, Threat) factors and competitiveness index necessary for Korean venture companies to succeed in the fourth industrial revolution. It suggests a SWOT strategy as well as an action plan in which the government and related parties prepare to secure global competitiveness, along with a very basic and systematic analysis. A total of 21 SWOT sub-factors were selected through a literature review and report analysis and were evaluated by various industry, academics, and policy experts via a Delphi survey. The results of pairwise comparative analysis using the AHP (Analytic Hierarchy Process) technique showed that the importance of the 4 SWOT quadrants could be arranged in order as strength (48%) → opportunity (25%) → threat (16%) → weakness (11%). Looking at the competitiveness index according to industry, ‘Artificial intelligence·Intelligent Robots·Autonomous driving (a)’, ‘Blockchain·Fintech (d)’, ‘Bio-health (f)’, and ‘Big data·Cloud (c)’ possessed high competitiveness. The ‘Internet of Things·5G (b)’, ‘3D printing·Virtual reality (g)’, and ‘New materials·Energy (e)’ industries were the least competent industries. Optimal strategies derived through an analysis of the competitiveness index are as follows: the S-O (Strength-Opportunity) strategy was optimal for industries such as ‘Internet of things·5G (b)’, ‘Big data·Cloud (c)’, ‘Bio-health (f)’, the S-T (Strength-Threat) strategy was optimal for ‘Artificial intelligence·Intelligent Robots·Autonomous driving (a)’, ‘Blockchain·Fintech (d)’ and ‘New materials·Energy (e)’. Finally, the W-T (Weakness -Threat) strategy should be prioritized for the ‘3D printing·Virtual Reality (g)’ industry. The implication of the study outlined above is that policies supporting the strengths and weaknesses of a company must be established beforehand for Korean venture companies to secure competitiveness in the fourth industrial revolution. First, it is of the utmost importance to develop a business faster by utilizing the excellent ICT infrastructure of Korea. Second, the Korean government should take a leading role in mediating the sharing of the resources (manpower, technology, equipment, etc.) that are available from each university, company, and research institute. Third, the government should prepare a technology development roadmap for commercialization as well as source technology for the fourth industrial revolution.

1. Introduction

With the advent of accelerated industrial development and the rapid change in the economic paradigm brought about by COVID-19, the future of global competition is expected to undergo unpredictable changes. Such an uncertain economic environment is characterized by rapid technological innovation, typified by the fourth industrial revolution (hereafter known as the 4 IR). With acceleration in the development of ICT and data analysis technology, as well as the progression of the online services industry, this era of convergence and inter-dependent relations between industries is also rapidly progressing [1,2]. In this wave of change, it is crucial to reorganize the industrial structure, which is currently centered on large enterprises, to promote the global competitiveness and capabilities of small and medium-sized ventures in the high-tech scene. Such environmental changes may present a crisis overall, but they also create opportunities for technology innovators.

There have been many arguments surrounding the definition, as well as the economic outlook, of the 4 IR. However, many theories and policies still have little certainty. Predicting the social and lifestyle changes brought about by the 4 IR is incredibly difficult and many theories that outline the development trend of technology and business strategies have been proposed [3,4].

Therefore, it is pivotal to delineate the concept of the 4 IR, predict changes in each industrial field, and clarify the major defining technologies of this era. Based on our understanding of the above, it is important to understand what SWOT factors are necessary for Korean venture companies (a venture company (venture business) is a technology-intensive SME that challenges existing businesses by developing cutting-edge new technologies and ideas) to gain competitive advantage in the 4 IR, and how significant each contributory factor is, as well as the overall competitiveness of Korean venture companies. In this respect, this study was designed to provide insight into the factors needed to enhance competitiveness and the qualitative growth of Korean venture companies. This study will also serve as an empirical framework that can be utilized in follow-up research. The main contents are summarized below.

First, the important SWOT factors of Korean venture companies will be outlined; these were established by conducting a Delphi survey based on the literature review.

Second, a research model for calculating the competitiveness index of Korean venture companies will be presented. The competitiveness index for each SWOT sub-factor and the competitiveness index for each industry (in the field of technology) related to the 4 IR will be quantitatively presented.

Third, using the SWOT/AHP methodology and competitiveness index analysis, this study will derive the optimal and prioritized strategies of Korean venture companies for securing global competitiveness in the 4 IR. The answers to the research questions: “What policies and support does the government need and what kind of efforts should be made by venture companies?”, “What is the action plan to reach the goal?” will be tackled from a business strategy perspective.

2. Materials and Methods

2.1. Literature Review

According to a detailed survey of venture companies in Korea, among 36,500 venture companies, there are 6632 companies that can handle the fourth industrial revolution and the related products or services, accounting for about 18.2% of the market. Among them, 20.9% of companies answered that they have worldwide technological competitiveness, while 47.7% of companies have domestic competitiveness. This means that the level of technology did not meet expectations. On the other hand, they are experiencing management difficulties, with financing at a rate of 75%, technology commercialization of 60%, overseas market development of 49%, and new technology development of 48% [5]. In addition, the national R&D budget has grown by only 2.2% in CAGR (Compound Annual Growth Rate) over the past 7 years, indicating that the government’s active R&D investment is insufficient [6]. As a result, basic and applied research capabilities in the field of the fourth industrial revolution were found to be insufficient in most fields, and the level of technology was still remarkably low at the level of 67~88%, compared to those countries with global-leading technology in each field [6].

We found that fund-raising is one of the major management difficulties facing venture companies in Korea. Looking at the contents of the existing literature on venture capital, venture capitalists (especially CVC: corporate venture capital) are not merely financial investors. They contribute greatly to the cultivation of entrepreneurial leadership and the creation and revitalization of the knowledge-based innovation ecosystem [7]. In addition, venture capitalists are very important in securing the competitiveness of venture companies as they provide comprehensive support and cooperation to new venture companies in which they have invested, ranging from management know-how, technological innovation, product development, and marketing to overall management [8]. According to an analysis of venture capital investment decision-making criteria, market growth, market formation potential, and the novelty of products and services are considered important factors in investment decision-making [9].

While Korean venture companies secure start-up funds relatively easily, it is very difficult to obtain an angel investment of about 90,000USD to 300,000USD, the amount that is considered necessary for the next stage of new product development and marketing for sustainable growth. For this reason, it is very rare for venture companies to pass successfully through the so-called “Death Valley”. The problem with securing angel investment funds lies in that it is extremely difficult to recover funds without an IPO. While it is easy to recover funds through mergers and acquisition in other countries, less than 1% of cases in Korea recover investment capital through venture company mergers and acquisition, with the payback period being 13 years (twice the average in developed countries of 7 years). This point acts as a hurdle that lowers the investment motivation of venture capital investors in the Korean market [10].

The following three-step processes were performed in order to derive the most suitable SWOT factors based on previous studies.

The first step requires understanding the determinants of competitiveness within a broader framework: by reviewing various theories on competitiveness at national, industrial, and corporate levels, major determinants were derived. According to M. Porter’s (1990) diamond model, a country’s industrial competitiveness is determined by the four diamond axes: ① factor conditions; ② demand conditions; ③ related and supported industries; ④ corporate strategy, structure, and competition [11]. In addition, Rugman and D’Cruz (1993) argued for the double diamond model, wherein competitiveness should be analyzed using both domestic and foreign diamonds together [12,13,14]. Because competition in the 4 IR takes place at a global level, amid myriad innovative technologies, products and services are not only in the domestic market [15].

In the second step, as a result of searching for existing papers related to the 4 IR in various fields, most of the papers target a particular industry (e.g., artificial intelligence, autonomous vehicles, the Internet of Things, cloud computing, smart education, etc.) in preparation for the advent of the 4 IR era. Various research has been conducted worldwide on competitiveness and SWOT factors in individual fields of industry and technology; however, it is incredibly difficult to find papers that analyze SWOT factors that span industry as a whole. Moreover, they fail to suggest the directions of policy and strategy at a macro level to explain the country’s overall industrial competitiveness. In order to assess the SWOT factors of companies and industries in the 4 IR, the venture business ecosystem [16,17], hidden champion [18,19,20], and born global company [16] were reviewed to assess SWOT factors in detail.

In the third step, major domestic and foreign reports on the 4 IR’s competitiveness index were studied. Every year, the WEF (World Economic Forum) publishes the Global Competitiveness Index (GCI), which is broadly divided into 4 fields (enabling environment, human capital, market, and innovation ecosystem), and each field is divided into 12 major elements: (1) institutions; (2) infrastructure; (3) ICT adoption; (4) macroeconomic stability; (5) health; (6) skills; (7) product markets; (8) labor markets; (9) financial systems; (10) market size; (11) business dynamism; (12) innovation capability [21]. In addition, the Korea Institute for Foreign Economic Policy (KIEP) compared competitiveness by dividing it into 6 major elements and analyzed it in relation to the capability of the 4 IR: (1) digital competency; (2) flexibility; (3) innovation competence; (4) R&D and innovation clusters; (5) innovative start-up capability; (6) sectional competence [22]. As seen from the competitiveness-related items derived above, innovative capabilities and the assimilation of various technological strengths are very important. This includes technologies such as autonomous solutions, automation technology, hyper-connectivity, and convergence technology, as well as data analysis. Thus, flexible thinking that can create new ideas, and the ecosystem and institutional support that can support it, act as important competitive factors.

In previous studies, research on the business environment [23,24,25] and competitive advantage were conducted individually according to nation. [1,22,26,27]. Since the characteristics of venture companies were not classified by SWOT (that is, strengths/weaknesses/opportunities/threats) and there was no hierarchy of importance within those factors, there has been little in the way of an integrated holistic development strategy of venture companies in 4 IR. This paper takes a different approach. A careful analysis will be conducted on the 4 SWOT factors of Korean venture companies in 4 IR using the AHP methodology and will aim to deduce a holistic development strategy, as well as an action plan formulated upon the reasoning of competitiveness index analysis.

2.2. Derivation of SWOT Factors

From the three steps of the literature review outlined above, 3 major and 6 internal environmental sub-factors of ventures companies’ global competitiveness were deduced: (1) infrastructure factors (① digital competency, ② R&D and innovation cluster); (2) corporate environment factors (③ innovation, ④ flexibility); (3) Government support factors (⑤ R&D, ⑥ laws, systems, and regulations). As for external environmental factors, a total of 3 major and 5 sub-factors were derived correspondingly: (1) environmental factors (① social environment, ② employment environment); (2) the industry’s growth potential (③ market size, ④ startup ecosystems); (3) global factors (⑤ global factors). The internal factors were then classified into strengths and weaknesses, alongside external factors that were also categorized into either opportunities or threats, resulting in a total of 19 SWOT sub-factors. These sub-factors were validated and corrected through a Delphi survey and in-depth research to ensure objectivity [28,29].

The derivation of SWOT factors in each step, as well as the sub-factors of strength, weakness, opportunity, and threat, are summarized in Figure 1 and

Table 1. SWOT factors of Korean ventures, eventually derived through the literature review.

Strength		Weakness
S1	ICT infrastructure and utilization	-	-
S2	SOC infrastructure	W1	Weak organic collaboration ecosystem
S3	Rapid and flexible commercialization capability	W2	Lack of global collaboration
S4	Business activation in platform big data in the non-face-to-face sector	W3	Inferior in high-tech manufacturing technology, materials, parts, and equipment
S5	R&D budget in 4 IR	W4	Poor attractiveness for foreign investors
S6	Active support from the government	W5	Difficulty in business due to overlapping regulations
Opportunities		Threats
O1	Stable macroeconomics and SOC	T1	Market uncertainty
O2	Excellent education system and skilled manpower	T2	Lack of labor market flexibility
O3 *	Creation and expansion of new domestic and international markets	T3	Difficulty entering overseas markets due to protectionism
O4	Nurturing innovation clusters actively	T4	Deficient utilization of venture capital by SMEs
O5 *	Global competitiveness in the Digital New Deal area	T5	Preoccupation of intellectual property and standardization by developed countries

* Among the sub-factors, two items, O3 and O5, were added, reflecting the opinion of the respondents of the first Delphi survey; finally, 21 factors were confirmed.

.

3. Research Design and Methods

3.1. Collection and Investigation of Data

3.1.1. Delphi Survey

To validate the 19 SWOT factors extracted from the three-step literature review, a Delphi survey was conducted twice against an expert group of 11 respondents between 20 December 2020 and 11 January 2021. Through a rigorous validation and correction process, 2 more sub-factors were added to the list of 19, resulting in a total of 21 factors.

3.1.2. AHP Survey

In order to conduct a pairwise comparison to calculate the weight of importance for each sub-factor, 11 experts were added to each existing group of 11 for the Delphi survey target group, resulting in a total of 22 experts. The corresponding AHP pairwise survey was conducted from 17 January 2021 to 25 February 2021. The consistency ratio is an index indicating the ratio of consistent responses in a pairwise comparison between items. If it is less than 0.1, they are considered to have consistently responded. The consistency ratio (CR) is calculated as follows: CR = (CI/RI) × 100% and CI (consistency index) = (λmax − n) / (n − 1). λmax will converge to n eventually, where n is the number of items and RI is a random index that is applied differently, depending on the size of the matrix. Out of 22 respondents, 6 respondents whose CR exceeded the standard value (CR > 0.1) [34,35] were excluded from the analysis, resulting in a total of 16 valid and verified responses.

3.1.3. Competitiveness Survey

A survey on competitiveness (response) capability was conducted between 16 June and 16 July 2021, for the purpose of deriving the competitiveness index. The target research companies were scrutinized from credible sources: the Korea Venture Business Association (KOVA), Small and Medium Business Technology Innovation Association (INNOBIZ), the Korea Women’s Venture Association (KOVWA), RM1 (Risk Manager No.1). In order to secure at least 25 effective samples by industry, 1000 companies were surveyed initially. A total of 318 valid sample companies were acquired. In the survey, 21 SWOT sub-factors were measured on a 5-point Likert scale (1: very low, to 5: very high), and other general questions on ‘associated technology or industry’ (13 groups), ‘business period’ (4 groups), ‘sales volume’ (4 groups), ‘number of employees’ (4 groups) and ‘R&D cost by sales volume’ (4 groups) obtained responses at a nominal scale according to group.

3.2. Research Framework and Analysis Methods

3.2.1. Research Framework

The research framework is summarized as follows (Figure 2).

• First, through a literature review and reports analysis on Korean ventures in 4 IR, we first derived plausible SWOT factors. Next, we conducted a Delphi survey and an in-depth interview of industry, academia, and policy experts to confirm these factors.
• Second, a hierarchical structure diagram for SWOT/AHP analysis was devised [36].
• Third, a pairwise comparison on the SWOT factors deduced above with the help of expert groups’ advice.
• Fourth, the weight of importance for each SWOT factor was calculated using Super Decision, as developed by Thomas L. Saaty [37]. The Super Decision software (http://www.Superdecision.com; accessed on 22 February 2021) is used for decision-making that requires dependence and feedback. It implements the analytic hierarchy process (AHP) and the analytic network process (ANP). This software provides tools to create and manage AHP and ANP models, enter your judgments, obtain results, and perform sensitivity analysis on the results.
• Fifth, a competitiveness survey was conducted with a number of Korean venture companies to identify their competitiveness in terms of each of the SWOT sub-factors.
• Sixth, we calculated the competitiveness index of each sample group.
• Seventh, the global competitiveness index was used to deduce an order of development strategy (S-O, S-T, W-O, and W-T) and propose an action plan for each development strategy.

3.2.2. Analysis Method

Validation of the SWOT Factors

This research placed considerable importance on validating the plausibility and reliability of the SWOT factors deduced through the three-step literature review. With an expert group of 11 respondents, two Delphi surveys and validity tests were conducted in succession. The item validity (contents validity ratio (CVR)) is an index that measures the suitability of each questionnaire item for the Delphi survey; the formula for CVR is shown below. The obtained CVR was again validated against the content validity index developed by Lawshe [36]:

CVR = (N − NE/2)/(NE/2),

(1)

where N is the number of respondents who scored 3 or higher on a 5-point Likert scale, and NE is the total number of respondents.

The obtained CVR in the first survey, ‘T2: Lack of flexibility in the labor market’, fell short of the standard value (CVR = 0.4 < 0.59) among 19 items. The questions were then revised and improved after reflecting on the feedback from the first survey: five sub-factors of the questionnaire were revised in terms of expression and two sub-factors were added, respectively, as O3 and O5. This revision added credibility to the results as all items were above the standard value (CVR > 0.59); then, we finalized 21 factors as SWOT sub-factors to measure the competitiveness of Korean venture companies. The demographic of the expert panel and the detailed process of validation are referred to in Appendix A, Appendix B and Appendix C.

Weight Analysis Results for SWOT Factors

As mentioned above in Section 3.1.2, in the AHP survey, we calculated the weight of each SWOT factor using the Super Decision program. The detailed coding table by 16 respondents is shown in Appendix D.

As shown in

Table 2. Weight and ranking of SWOT sub-factors.

		Global Weight
		Industry Expert a	Rank	Academia Expert b	Rank	Policy Expert c	Rank	Global	Rank
Strength	S1	9%	3	6%	6	9%	5	8%	3
	S2	6%	6	3%	14	5%	7	5%	9
	S3	11%	2	8%	4	20%	1	12%	1
	S4	11%	1	11%	1	9%	4	11%	2
	S5	6%	5	7%	5	5%	10	6%	6
	S6	4%	12	10%	2	4%	12	6%	7
Weakness	W1	4%	11	3%	13	4%	11	4%	13
	W2	2%	18	3%	15	1%	20	2%	18
	W3	2%	16	2%	19	2%	14	2%	17
	W4	2%	20	1%	21	1%	21	1%	21
	W5	3%	14	2%	20	2%	17	2%	15
Opportunity	O1	1%	21	2%	18	4%	3	2%	19
	O2	4%	13	4%	12	6%	6	5%	11
	O3	6%	8	5%	10	11%	2	7%	5
	O4	5%	10	6%	8	5%	8	5%	8
	O5	8%	4	8%	3	5%	9	7%	4
Threat	T1	2%	17	3%	16	2%	16	2%	15
	T2	6%	7	5%	9	3%	13	5%	10
	T3	2%	19	2%	17	1%	19	2%	20
	T4	5%	9	6%	7	1%	18	4%	12
	T5	2%	15	4%	11	2%	15	3%	14
Global		100	-	100	-	100	-	100	-

^a ‘Industry Expert’ refers to a CEO or executive-level expert who runs a company in 4 IR. ^b ‘Academic Expert’ refers to a university professor and researchers in 4 IR. ^c ‘Policy Expert’ refers to a person who is in a decision-maker position in establishing and implementing related policies in government, affiliated institutions, and organizations in 4 IR.

, the following SWOT factors were given higher weight (over 5%):

• ‘S3: Rapid and flexible commercialization capability’ (12%);
• ‘S4: Business activation in platform·big data·non-face-to-face sector’ (11%);
• ‘S1: ICT infrastructure and utilization’ (8%);
• ‘O5: Global competitiveness in Digital New Deal area’ (7%);
• ‘S5: R&D budget in 4 IR’ (6%);
• ‘S6: Active support from the government’ (6%);
• ‘O4: Nurturing innovation clusters actively’ (5%).

The following factors scored a lower weight (below 3%):

• ‘W2: Lack of global collaboration’ (2%);
• ‘W3: Inferiority in advanced manufacturing technology, materials, parts, and equipment’ (2%);
• ‘W4: Poor attraction for foreign investors’ (1%);
• ‘W5: Difficulty in business due to overlapping regulations’ (2%);
• ‘O1: Stable macroeconomics and SOC’ (2%); and
• ‘T3: Difficulty entering overseas markets due to protectionism’ (2%).

Competitiveness Index

The AHP analysis was performed using the Super Decision software developed by Professor Thomas L. Saaty [37,38]. The obtained responses for SWOT factors were used to explain the internal/external competitiveness of Korean venture companies, which were then used to derive the global competitiveness index:

$$Is={\sum }_{i=1}^{n}Wsi\times \frac{Ssi}{Smax}\times 100,$$

(2)

where Is represents the competitiveness index of strength, Wsi is the relative weight of strength i factor [37], Ssi is the rating scale for strength i factor, and Smax is the highest value on the ratings scale of the strength i factor. The competitiveness index was calculated for weakness (Iw), opportunity (Io), and threat (It) in the same way [39]. The rating scale (Ssi) of SWOT factors was measured on a Likert 5-point scale, with a target group of 318 companies in 4 IR.

4. Discussion

4.1. Empirical Analysis

As shown in

Table 3. Classification by related technology.

Industry	Related Technology	Number of Samples	%
a	Artificial Intelligence·Intelligent Robots·Autonomous Driving	54	17
b	Internet of Things·Mobile 5G	41	13
c	Big Data·Cloud	53	17
d	Blockchain·Fintech	30	9
e	New Materials·Energy	43	14
f	Bio-Health	31	10
g	3D Printing·Virtual Reality	27	8
h	Others	39	12
Total		318	100

, 12 defining technologies of 4 IR were categorized into 8 industry groups, as referenced by research conducted by the Korea Institute for Industrial Economics and Trade (KIET) regarding an ‘Analysis of the effect and relationship of technology introduction in 4 IR’ [40] and ‘4 IR-related keywords’. To derive a statistically sound conclusion, at least 25 samples were obtained for every industry. The summary is provided below, sorted by factor. Out of a total of 318 samples, 54 companies belonged to Industry (a): ‘Artificial Intelligence·Intelligent Robots·Autonomous Driving’ and only 27 companies belonged to Industry (g): ‘3D printing·Virtual Reality’.

As shown in

Table 4. Sample characteristics.

Group		Industry								Total	%
		a	b	c	d	e	f	g	h
Business experience	Under 1 year	1	4	6	4	2	1	1	0	19	6
Business experience	1~3 year	8	4	9	7	6	2	3	6	45	14
Business experience	3~7 year	17	12	16	16	16	13	10	10	110	35
Business experience	Over 7 years	28	21	22	3	19	15	13	23	144	45
Employees	Under 10 persons	22	23	35	13	30	19	9	26	177	56
Employees	10~50 persons	23	12	18	13	9	8	17	9	109	34
Employees	50~100 persons	6	5	0	3	4	3	1	4	26	8
Employees	Over 100 persons	3	1	0	1	0	1	0	0	6	2
Annual sales	Under 1 Bil. KRW	20	22	31	15	25	18	11	22	164	52
Sales volume	1~5 Bil. KRW	17	10	19	8	11	7	12	11	95	30
Sales volume	5~10 Bil. KRW	12	7	3	6	3	5	1	4	41	13
Sales volume	Over 10 Bil. KRW	5	2	0	1	4	1	3	2	18	6
R&D ratio to sales	Under 5%	14	6	21	6	15	11	7	24	104	33
R&D cost ratio for sales	5~under 7%	7	17	16	5	12	9	5	8	79	25
R&D cost ratio for sales	7~under 10%	20	9	11	10	6	8	4	7	75	24
R&D cost ratio for sales	Over 10%	13	9	5	9	10	3	11	0	60	19

and

Table 5. Reliability test results.

Factors		Reliability Test
		CITC 1	Cronbach’s α
			Ex. Factor a	Inc. All b
S	S1. ICT infrastructure and utilization	0.642	0.753	0.803
	S2. SOC infrastructure	0.611	0.762
	S3. Rapid and flexible commercialization capability	0.396	0.806
	S4. Business activation in platform, big data, non-face-to-face sector	0.559	0.774
	S5. R&D budget in 4 IR	0.603	0.762
	S6. Active support from the government	0.559	0.773
W	W1. Weak organic collaboration ecosystem	0.332	0.709	0.703
	W2. Lack of global collaboration	0.542	0.626
	W3. Inferior in high-tech manufacturing technology, materials, parts, and equipment	0.570	0.612
	W4. Poor attraction for foreign investors	0.491	0.648
	W5. Difficulty in business due to overlapping regulations	0.390	0.687
O	O1. Stable macroeconomics and SOC	0.351	0.722	0.720
	O2. Excellent education system and skilled manpower	0.526	0.653
	O3. Creation and expansion of new domestic and international markets	0.549	0.644
	O4. Nurturing innovation clusters actively	0.464	0.678
	O5. Global competitiveness in the Digital New Deal area	0.509	0.660
T	T1. Market uncertainty	0.323	0.701	0.693
	T2. Lack of labor market flexibility	0.515	0.612
	T3. Difficulty entering overseas markets due to protectionism	0.390	0.667
	T4. Weak utilization of venture capital by SMEs	0.514	0.616
	T5. Preoccupation of intellectual property and standardization by developed countries	0.529	0.614

^a Cronbach’s α excluding each relevant factor, ^b Cronbach’s α including all factors. ¹ Corrected item total correlation (CITC): if the total correlation coefficient of the corrected items is generally 0.3 or more, it can be considered that there is no advantage in improving reliability even if the corresponding items is excluded.

, the proportion of those companies with more than 7 years of business experience was highest at 37%, and those with experience in the range of 3 to 7 years accounted for 35%. This leads to a self-evident proportion whereby 80% of companies have more than 3 years of business experience.

As for a company’s employees and annual sales, 56% of companies had fewer than 10 employees and only 2% had more than 100 employees. Regarding sales volume, 52% reported sales of less than 1 billion Korean won (KRW), and 30% had sales in the range of 1 to 5 billion KRW; it is notable that only 6% of the total companies surveyed showed sales surpassing 10 billion KRW.

In addition, the R&D ratio with respect to total sales was studied. 33% of companies devoted less than 5% of total sales to R&D, and only 19% of companies had an R&D devotion rate of 10%.

A reliability test was conducted individually on 4 major SWOT factors, as each factor possessed certain characteristics of distinction and variation. The reliability coefficient (Cronbach’s alpha) was obtained as the following values: strength (0.803), weakness (0.703), opportunity (0.720), and threat (0.693). All four factors had a value with a recognition standard of 0.6, indicating that a decent level of reliability was secured for each SWOT factor [41].

Table 6. Competitiveness index by SWOT.

Internal	Strength	S1	S2	S3	S4	S5	S6	total
	Isi	63.23	64.68	67.34	64.11	61.71	65.76	64.70
	Weakness	W1	W2	W3	W4	W5	-	total
	Iwi	61.27	59.24	61.52	58.80	60.25	-	60.2
External	Opportunity	O1	O2	O3	O4	O5	-	total
	Ioi	57.34	60.82	64.43	62.78	61.96	-	62.23
	Threat	T1	T2	T3	T4	T5	-	total
	Iti	56.96	65.57	62.15	62.09	61.27	-	62.27

shows the internal/external competitiveness index for each sub-SWOT factor with respect to strengths, weaknesses, opportunities, and threats. In order of significance, competitiveness for each element was calculated as the following:

Strength: 64.70

Threat: 60.50

Opportunity: 62.23

Threat: 62.27

Overall, the four elements displayed similar levels of competitiveness. Sub-factors of less significance (with a low competitive index) are outlined below.

The competitiveness index of the strength factor was high, but ‘S5. R&D budget in 4 IR’ was relatively low at 61.71. As for the weakness factors, ‘W2. Lack of global collaboration’ was 59.23 and ‘W4. Poor attraction of foreign investment’ was notably lowest at 58.80. Among the opportunity sub-factors, ‘O1. Stable macroeconomics and SOC’ was 57.34 and ‘O2. Excellent education system and skilled manpower’ was 60.82. Lastly, in terms of threat factors, ‘T1. Market uncertainty’ was 56.96, and ‘T5. Preoccupation with intellectual property and standardization by developed countries’ was 61.27, indicating a low competitiveness index.

Table 7. Competitiveness index, shown by industry.

	Industry								Total
	a	b	c	d	e	f	g	h	Total
S	69.76	61.97	70.30	66.27	60.19	65.64	58.29	60.18	64.70
W	64.23	56.28	62.63	62.22	57.33	61.87	59.19	58.67	60.50
O	63.71	63.63	61.98	64.09	58.95	66.33	60.35	59.11	62.23
T	66.02	60.50	61.60	65.61	61.17	62.77	62.75	57.74	62.27
Total	65.93	60.59	64.13	64.55	59.41	64.15	60.14	58.92	62.42

shows the competitiveness index of SWOT factors by industry group. The competitive index was highest at 65.93 for ‘Artificial Intelligence·Intelligent Robots·Autonomous Driving (a)’, and is closely followed by ‘Blockchain·Fintech (d)’ at 64.55 and ‘Bio Health (f)’ at 64.15, ‘Big Data·Clouding (c)’ exhibited a relatively strong competitiveness index at 64.13, while sectors like ‘Internet of Things·Mobile 5G (b)’, ‘3D printing·Virtual Reality (g)’, ‘New Materials·Energy (e)’ and ‘Others (h)’ displayed low competitiveness, the index being 60.59, 60.14, 59.41 and 58.92, respectively.

If we delve deeper into individual technology within an industry using the four facets of SWOT analysis, the competitiveness index of the strength factor for ‘Big Data·Cloud (c)’ was the highest at 70.30, and the index of weakness factor for ‘Internet of Things·Mobile 5G (b)’ was lowest at 56.28. Contrary to common perceptions, startups engaged in ‘Internet of Things·Mobile 5G (b)’ displayed a low level of competitiveness.

Analyzed within 21 sub-factors, the ‘Artificial Intelligence·Intelligent Robots·Autonomous Driving (a)’ sector stood highest at 73.33 for the ‘S3. Rapid and flexible commercialization capability’ factor. Conversely, ‘3D printing·Virtual Reality (g)’ had the lowest competitiveness index at 51.11 for the ‘O2. Excellent education system and skilled manpower’ factor.

4.2. Derivation of Development Strategy and Action Plan

4.2.1. Prioritization of Development Strategy

The development strategy was formulated in consideration of the unique characteristics exhibited by each industry. It was found that for industries with high competitiveness: ‘Artificial Intelligence·Intelligent Robots·Autonomous Driving (a)’ and ‘Blockchain·Fintech (d)’ industries, the S-T strategy should be prioritized to utilize strengths to overcome any crisis. As for companies in ‘Bio-Health (f)’, the S-O strategy was the best strategy by which to employ the strength to seize business opportunities. As for ‘Big Data·Cloud (c)’, the S-O strategy and the S-T strategy were equally valuable and prioritized. Overall, the results showed that the S-O and S-T strategies must be chosen for the four industries with high competitiveness. Each industry by development strategy is summarized in

Table 8. Summary of the first-priority industry by development strategy.

S-O Strategy	S-T Strategy
- Internet of Things·Mobile 5G (b) - Big Data·Cloud (c) - Bio-Health (f) - Others (h)	- Artificial Intelligence·Intelligent Robots·Autonomous Driving (a) - Big Data·Cloud (c) - Blockchain·Fintech (d) - New Materials·Energy (e)
W-O strategy	W-T strategy
- none	- 3D printing·Virtual Reality (g)

.

A development strategy was derived for industries with low competitiveness, as shown below. In the case of the ‘Internet of Things·Mobile 5G (b)’ and ‘New Materials·Energy (e)’ industries, the S-O and S-T strategies were ranked first and second, despite all development strategies having less significance. This is with regard to the industry’s characteristics as the ‘Internet of Things·Mobile 5G (b)’ is closely related to the ICT infrastructure (the factor with the highest competitiveness). Since the competitiveness of venture companies, in contrast to large companies, are relatively low, it is deemed pivotal to focus on raising competitiveness in general while complementing a company’s weaknesses and upholding its strengths. Similarly, startups in the ‘New Materials·Energy (e)’ industry must rebuild around their weaknesses to raise their overall efficacy and competitiveness in their business environment.

As for ‘3D printing·Virtual Reality (g)’, the industry with the lowest competitiveness, the W-T strategy must be prioritized above all others to overcome crises while supplementing weaknesses.

4.2.2. Action Plan

Based on the results derived from the weight analysis and the competitiveness index, the strategic directions in which Korean venture companies can strengthen global competitiveness in 4IR are presented below in Figure 3.

5. Conclusions

5.1. Results and Findings

In this study, a total of 21 SWOT factors were derived through an extensive literature review and a survey of experts. These SWOT factors help us understand how Korean venture companies should respond to internal and external environmental change, an element crucial for them to be competitive internationally.

To analyze the weight of each factor, a pairwise comparison was conducted using the AHP technique (a systematic decision-making technique). All 21 sub-factors were validated by groups of industry experts, academia experts, and policy experts, all of whom are professionals who have knowledge of the business mechanics in 4 IR. The results of the analysis are as follows.

First, Korean venture companies’ views and perspectives on the significance of the four SWOT facets are as follows: strength (48%), opportunity (25%), threat (16%), and weakness (11%). From this result, it can be deduced that macro policies must support the development of an S-O strategy in order for venture companies to preoccupy the global market.

Second, a detailed analysis of individual factors showed that the three pivotal factors deemed most important in 4 IR were ‘S3. Rapid and flexible commercialization capability (11.9%)’, ‘S4. Platform, big data, non-face-to-face business activation (10.9%)’ and ‘S1. ICT infrastructure and utilization (8.3%). On the other hand, the three least critical factors were ‘O1. Stable macroeconomics and SOC (2.0%)’, ‘T3. Difficulty entering overseas markets due to protectionism (1.8%)’, and ‘W4. Poor attraction of foreign investment (1.3%)’.

The results above suggest that ICT technology must be at the foundation of Korean venture companies to ensure their competitiveness in the era of the fourth industrial revolution, to radically innovate in platform-based, big-data, online businesses, especially against the backdrop of the COVID-19 pandemic [42].

Third, the competitiveness index was segmented and studied according to industry and SWOT factors. ‘Artificial Intelligence·Intelligent Robots·Autonomous Driving (a)’, exhibited the greatest significance, closely followed by ‘Blockchain·Fintech (d)’, ‘Bio-Health (f)’ and ‘Big Data·Cloud (c)’. On the contrary, industries such as the ‘Internet of Things·Mobile 5G (b)’, ‘3D printing·Virtual Reality (g)’, ‘New Materials·Energy (e)’, and ‘Others (h)’ displayed the least competitiveness in terms of the 4 IR. When studied according to individual sub-factor, the highest competitiveness index for the strength factor was ‘Big Data·Cloud (c)’ at 70.30, and the lowest competitiveness index for the weakness factor was ‘Internet of Things·Mobile 5G (b)’ at a mere 56.28. When analyzed in terms of dimensions, the ‘Artificial Intelligence·Intelligent Robots·Autonomous Driving (a)’ sector had the highest score of 73.33 for the ‘S3. Rapid and flexible commercialization capability’ factor. ‘3D printing·Virtual Reality (g)’ exhibited the lowest competitiveness for the ‘O2. Excellent education system and skilled manpower’ factor.

Fourth, strategic indices were calculated for four strategies (S-O, S-T, W-O, and W-T) to determine the optimal strategy to prioritize within a specific industry. Exhaustive analysis of the competitiveness index revealed that the S-O strategy was optimal for ‘Internet of Things·Mobile 5G (b)’, ‘Big Data·Cloud (c)’, and ‘Bio-Health (f)’ to seize novel business opportunities. The S-T strategy was deemed excellent for industries such as ‘Artificial Intelligence·Intelligent Robots·Autonomous Driving (a)’, ‘Blockchain·Fintech (d)’, and ‘New Materials·Energy (e)’ for leveraging business expertise to overcoming crises. Finally, the W-T strategy was presumed to be optimal for ‘3D printing·Virtual Reality (g)’ to surmount threats whilst supplementing business weaknesses.

5.2. Implications and Limitations

Based on the results of weight and competitiveness analyses presented in this study, we would like to suggest the following strategic directions for Korean venture companies to strengthen global competitiveness in 4 IR.

First, flexible and agile policies must be developed that stem from Korea’s strength and versatility of ICT infrastructure [43,44]. In particular, the government must lift regulations, provide institutional support, and draw up large R&D budgets for companies within the Digital New Deal business domain to support the scale-up of innovative venture companies, especially within the platform, big-data, and online businesses. Investments must be made at the ecosystem level by fostering innovation clusters and supporting the business infrastructures of venture companies.

Second, joint business development and marketing between SMEs and larger firms is mandatory, as venture companies lack either the international influence or funds to expand overseas. The government should play an active intermediary role, to enable collaborative research between industry, government, and academia, as well as facilitate the exchange and sharing of infrastructure and personnel between different business and academic entities. Laws and regulations surrounding employment and labor must be reorganized in order to facilitate a ‘human resource sharing system’, while at the same time innovating the educational system to nurture future scholars and leaders of the 4 IR.

Third, serious efforts must be made to protect intellectual property, patents, and personal information in response to the intensified global competition. The monopoly of materials and standardized supplies by foreign leading companies must be prevented at all costs [45]. Therefore, the government must go beyond securing competitiveness for current key technologies to preempt key technologies of the future. Protection and acquisition to secure source technologies will require a roadmap in the long term, to coordinate organizational efforts and elaborate upon commercialization plans. All in all, it is pivotal to strategize a working plan for an ecosystem where innovative technology can flourish.

Fourth, it is necessary to actively seek ways to revitalize the venture business and the mergers and acquisition market and cut down the time it takes to move from start-up to IPO. In addition, while inducing venture companies to turn their eyes away from the domestic market to pursue a broader global market expansion strategy, efforts to attract foreign expertise and investment to Korea must be reinforced. This is because having a global perspective is very crucial to guarantee the future dynamism and growth of the venture industry [10].

At a time when the views surrounding the 4 IR are divided and in disagreement, this study was designed to quantitatively measure the importance of SWOT factors and calculate a competitive (response) index. From this quantitative research, the directions of macro policies, as well as the implications of Korean venture companies, were analyzed, an insight into the Korean venture companies’ optimal development strategy was offered and an action plan was proposed. This research is expected to contribute significantly to the research of Korean venture companies’ competitiveness in 4 IR, which is yet to be made in the future.

A notable limitation of the research is that there were few literature studies that studied Korean venture companies as a whole from the SWOT perspective. This article was thus intended to supplement the blind spots of the existing literature studies, through a rigorous investigative process of an expert survey. Due to the small number of expert samples, however, it is difficult to say whether the opinions derived accurately represent the views surrounding the ecosystem of Korean venture companies. In addition, this study was limited in elaborating detailed strategies for each specific industry or technology within the scope of this research.

In addition, the limitations of the cross-sectional survey were self-evident as it was not possible to analyze changes in the importance of SWOT factors and related technologies. As this study focuses on the Korean business landscape, business strategies were not compared with venture companies in other nations in terms of intensity. Based on the limitations and the aftermath of this research, follow-up research must aim to derive strategic directions, according to industry, with respect to the key defining technologies, and add longitudinal comparisons between startups of other nations.