How Has the Aquaculture Supply Chain’s Competitiveness Changed After the COVID-19 Pandemic in Emerging Countries? The Case of Vietnam

Abstract

Global supply chains are facing many changes after the COVID-19 pandemic. This change impacts the way each supply chain measures its key performance indicators and determinants for its competitiveness. Aquaculture supply chains (SCA) play an essential role in global trading and fluctuated significantly during the COVID-19 pandemic when many aquaculture supply chains from emerging countries faced disruption. Therefore, after the COVID-19 pandemic, these supply chains have changed their measures and determinants to improve global competitiveness. This paper examines the change in this measure and determinants of the aquaculture supply chain in Vietnam, one of the world’s top 10 biggest exporting countries of aquaculture products. The paper reviews the list of measures and determinants of the aquaculture supply chain before and after the COVID-19 pandemic from the literature. It forms the framework under the shade of Resource-Based View theory. A total of 38 interviews with managers and CEOs of 36 enterprises and two government agencies in the aquaculture supply chain in Vietnam were conducted to explore the strategic changes in the measures of determinants to cope with the new circumstances of current global trade. The findings contribute to enriching the theory in the new VUCA (volatility, uncertainty, complexity, and ambiguity) business environment after the COVID-19 pandemic. In this context, SCA should be defined by supply chain virtues that are associated with the new business environment, such as SC resilience, SC sustainability, SC reliability, SC integration, etc. This finding implies a new horizon for RBV applications, highlighting their adaptability. It suggests that the measures defining competitive advantage in the new business environment should extend beyond the traditional tangible and intangible resources under business certainty. They should also encompass those that differentiate the firms and their supply chain during business turbulence.

1. Introduction

The supply chain’s purpose is to coordinate the process of managing material, information, and financial flows to provide extra value-added services to the end customers [1,2]. Mangal & Gupta (2015) [3] illustrate that becoming profitable is one of the primary purposes of all stakeholders of a supply chain, which means they must be involved in such a way that their supply chain can gain profit or reduce costs regardless of the uncertainty while coping with the higher and higher requirements of innovation and sustainability [4]. Therefore, competitiveness, a concept that is widely used but not based on a shared definition, is crucial in supply chain management. It refers to the ability of a supply chain to outperform its rivals in meeting the needs of the end customers [5].

There is a common understanding that the concept of competitiveness is multidimensional and, consequently, is challenging to deal with theoretically and empirically [6]. In the context of supply chains, supply chain competitiveness is gaining a competitive advantage over other competing supply chains [7]. Consequently, factors that influence the ability of a supply chain to achieve and sustain competitive advantages are named determinants. So far, determinants of supply chain competitiveness refer to the critical factors or enablers that influence the ability of a supply chain to perform effectively and maintain an edge over competitors. These determinants are typically strategic choices made by the organization [8]. At the same time, measures often relate to the metrics used to evaluate that competitiveness. These metrics or key performance indicators (KPIs) are used to assess the competitive strength of a supply chain. They reflect how effectively a supply chain operates in comparison to competitors and its ability to meet customer expectations [9]. Therefore, it is not just important, but also urgently needed to understand the measures and determinants of supply chain competitiveness to boost it. In some specific contexts, the measures can be the determinants and vice versa.

Aquaculture supply chains (SCAs) always play an essential role in global trading since aquaculture products are one of the most highly traded food commodities [10], and global seafood trade has grown at an average annual growth rate of 5%, reaching $177.5 billion in 2021 [11]. Farmed aquaculture products play a key role in this development as their production rapidly increases [12,13]. However, after the COVID-19 pandemic, global supply chains are facing many changes; in other words, the world is going to be significantly different [14]. Many SCAs in emerging countries have faced disruption and fluctuated substantially during the COVID-19 pandemic, leading to uncertain growth of the global supply chain of aquaculture trade recently. In contrast, global trade tensions have increased [15]. Therefore, to maintain the SC competitive advantages, the measures and determinants for supply chain competitiveness are important factors for allocating the right resources to each competitive advantage.

In many emerging countries, the aquaculture sector is a vital component of the country’s economy and the global aquaculture supply chain. Vietnam, in particular, has made a significant economic impact, consistently ranking in the top five of the world’s largest aquaculture supply chains from 2020 to 2024 [11]. Currently, Vietnam’s aquatic products contribute approximately 25% to the agricultural sector’s GDP [16]. In 2024, Vietnam’s seafood export turnover ranked fourth globally, demonstrating the sector’s economic potential and leading Vietnam to the top five largest seafood exporting countries, with an annual export turnover of 9 to 11 billion USD [17].

Given the pivotal role of SCAs in the global economy and their recent volatility, particularly in developing countries, our research team has undertaken a study to understand how the measures and determinants of competitiveness have evolved before and after the COVID-19 pandemic in emerging countries, with a specific focus on Vietnam. Drawing from the existing literature, our study aims to shed light on the measures and determinants of supply chain competitiveness (SCC) and how Vietnam’s aquaculture supply chains have been managed and operated to sustain their competitiveness. To achieve this, we have formulated two guiding research questions.

The first question we address is, “What are the measures and determinants of SCC of aquaculture before and after the COVID-19 pandemic?” To answer this question, our research team conducted an extensive review of the existing academic literature on SCC, with a focus on high-quality peer-reviewed papers. This thorough review has enabled us to identify and analyze all measures and determinants that contribute to SCC, instilling confidence in the robustness of our research methodology.

The second question, “How do Vietnam’s SCAs foster global competitiveness as a case of emerging countries through those measures and determinants?” necessitates primary data for an answer. To this end, our research team conducted interviews with 36 stakeholders of Vietnam’s SCAs, including farmers, processors, traders/exporters, logistics providers, and 2 government agencies. This comprehensive analysis allowed us to construct a detailed current overview of the country’s SCC of aquaculture and validate the findings from the SCC literature, thereby ensuring the robustness of our study.

The remainder of the paper is structured as follows. The second section provides a comprehensive literature review and analysis of SCC in aquaculture. The third section outlines our rigorous methodology for collecting primary data, while the subsequent section presents the case findings. The fifth section delves into the theoretical and practical implications of our research. Finally, the conclusion section wraps up the paper, highlighting the research’s contributions and acknowledging its limitations.

2. Literature Review

Globalization has paved the way for firms to achieve competitiveness through their supply chain management (SCM) [18]. The concept of supply chain competitiveness (SCC) has been a key area of interest for operations and SCM scholars [19,20,21,22]. Numerous studies have explored the dynamics of gaining or losing competitive advantages [23,24] using various SCC measures and determinants. However, a unique gap in the literature exists: no study has ventured into the realm of changes in SCC measures and determinants post-COVID-19. This study aims to fill this void, particularly in the context of the SCA, making it highly relevant to this sector.

A comprehensive literature search is conducted for the first research question to specify the measures and determinants used for the SCA. The databases used are the Web of Science (WoS) and Scopus, which contain the most relevant peer-reviewed articles published in mainstream journals. Because the research focuses on the most updated measures and determinants before and after the COVID-19 pandemic, the results were filtered for only peer-reviewed articles published between January 2000 and August 2024. The keywords used were “TS = (supply chain competi* OR supply chain measur* OR supply chain determina*) AND TS = (aquaculture* OR fisher*)” for WoS and “TITLE-ABS-KEY(supply chain competi* OR supply chain measur* OR supply chain determinan*) AND TITLE-ABS-KEY(aquaculture* OR fisher*)” for Scopus.

The search yielded 204 and 242 results for WoS and Scopus, respectively. In the selection stage, duplicates were removed to yield 286 papers. Subsequently, the title and abstract of each article were manually examined for relevance to ensure that the papers focused on measures and determinants for sustainable competitiveness in the SCA. In the final stage, 110 articles were systematically read to answer the research question.

As the COVID-19 pandemic occurred between 2020 and 2021, we divided our list of reviewed papers into two periods: one from 2000 to 2021 (70 papers), and one from 2022 until August 2024 (40 papers). This division was made to ensure that we captured the most recent and relevant research on supply chain competitiveness measures and determinants, particularly in the context of the post-COVID-19 era.

2.1. Measures of SCA Competitiveness Before and After the COVID-19 Pandemic

Measures of supply chain competitiveness are instrumental in evaluating and enhancing supply chain performance. Our extensive literature review and analysis have led to the identification of 20 top measures of SCA competitiveness (Table 1). This list, a source of profound insights, delineates the most popular measures from the pre- and post-COVID-19-pandemic periods, thereby enhancing the awareness of SCAs’ competitive advantages.

According to Table 1, fifteen key indicators are unchanged over time, but five of them have attracted much more attention from researchers in the post- than pre-COVID-19-pandemic period, relatively. They are as follows:

• (1). Market share/access (78% vs. 35.7%) is the top export performance indicator that reflects a country’s ‘degree of dominance’ or competitiveness in the market [25]. The significant increase from 35.7% to 78% in the post-COVID-19-pandemic period indicates a heightened focus on this indicator. Many studies show that the constant market share is a vital indicator for global SC competitiveness of catfish and basa (tra) exports of Vietnam, China, Thailand, and others in the US market [26], among other major exporting countries worldwide.

• (2). SC sustainability (45% vs. 35.7%).

• (3). SC efficiency and performance (53% vs. 34.2% and 15.7%) is a relevant comparative advantage approach for SC competitiveness in every individual country [90] among other major exporting countries. For instance, the competitiveness of eel aquaculture in Taiwan, Japan, and China was discussed using the net private profitability and resource cost [91].

• (4). SC productivity and profitability indicators are two essential metrics to measure competitiveness [55,56] in which competitive advantage enables a firm to gain higher profit than the average profit of competitors [92]. In addition, production cost is a key measure of salmon producing competitiveness, since lower price resulted in the competitiveness of Norwegian salmon aquaculture products to other food producers [34,43].

• (5). Finally, market price (40% vs. 28.5%) is also an important measure of SCA competitiveness which attracted more attention after the COVID-19 pandemic [32,33,64,78,79].

Five measures that did not draw much attention pre-COVID-19 have become essential during and after the COVID-19 pandemic. Notably, SC Resilience has seen a significant increase from 6% to 43%, SC Compliance from 0% to 18%, SC Safety and SC Security both from 0% to 15%, and SC Reliability from 0% to 10%. These substantial increases in SC measures reflect the adaptability and resilience of the supply chain in the face of the pandemic. The changes in SCC measures also highlight the critical impacts of the COVID-19 pandemic on global supply chains, exposing vulnerabilities and reshaping the dynamics of SCC.

2.2. Determinants of SCA Competitiveness Pre and Post COVID-19 Pandemic

Various determinants of SCA competitiveness have been identified in empirical studies employing a similar strategy to gather and analyze them (Table 2). These determinants, which influence a supply chain’s ability to achieve and maintain competitive advantages, have shown a shift in priorities before and after the COVID-19 pandemic.

Before and after the COVID-19 pandemic, the top ten essential determinants of SCA’s competitiveness remained unchanged. However, the nature of their importance has shifted. For instance, Economic Factors and Market Demand were the two most important determinants before the COVID-19 pandemic, while Government/Policy Factors and Environmental Factors drew the most attention after the COVID-19 pandemic. This shift in priorities reflects the evolving landscape of SCA competitiveness. Examples of Government/Policy Factors are mentioned as the constraints to the growth of EU aquaculture in the form of regulatory barriers causing additional compliance costs that reduce industry competitiveness [93], or the relaxation of the restriction leading to lower production costs for Norwegian salmon [43], or the requirement for sanitary and phytosanitary measures (SPS) as the trade barrier challenges faced by Bangladesh fishery and aquaculture section affecting the global competitiveness of the industry [94]. However, after the COVID-19 pandemic, the first two key measures are Governmental Factors and Policy [61,78].

Regarding Market Demand, before the COVID-19 pandemic, Bostock et al. (2016) indicated that changing markets affect the competitiveness of EU aquaculture production. However, after the COVID-19 pandemic, the Market Demand factor only played the fourth key determinant in the literature [45,89].

Our research identified Environmental and Social Factors as the fourth and third essential factors pre- and post-COVID-19-pandemic, respectively [46]. These factors, which encompass health and ecological sustainability, the regulatory environment, food safety, legal and labor standards, interstate transport of aquatic products, fish health, and culture of commercially harvested fish, have a significant impact on the competitiveness of US aquaculture. The increased managerial and labor time spent and direct costs, as revealed by our research, underscore the urgent need to address these issues to maintain the industry’s competitiveness [95,96,97].

Technology adoption remained fifth in the list in both time periods, analyzed from different perspectives by authors. For instance, the strength of the link between competitiveness and technology, which is expected to reduce product cost, appears to be the main focus of attention in the aquaculture industry literature [58].

Economic Factors played the first determinant before the COVID-19 pandemic, mainly because SCA stakeholders in developing countries, who are key players in the region’s economic landscape, believe that economic factors can impact competitiveness from one developing country to others in Asia [98]. Their belief was largely due to the economies of scale in farms, which contributed to a decrease in production cost [43,99]. However, after the COVID-19 pandemic, this factor has seen a significant shift in importance. The pandemic has brought to light the critical role of other factors such as Government, Policy, Environment, Market Demand, and Technology Adoption, which have now surpassed economic factors in determining competitiveness [35].

In conclusion, the researcher’s analysis post-COVID-19-pandemic has identified Governmental (85%), Policy (70%), and Environmental (68%) as the top three determinants of competitiveness. The research has also brought to light new determinants such as Innovation (18%), Collaboration and Coordination (18%), and Risk (10%), which now feature in the Top 20. This research is valuable in understanding the changing business environment post-COVID-19, and the role of these new determinants in shaping competitiveness.

Table 2

Determinants of SCA competitiveness before and after COVID-19 pandemic.

#	Before COVID-19	# Papers	%	Publications	#	After COVID-19	# Papers	%	Publications
1	Economic factor	28	40%	[67,72,82,100,101]	1	Governmental factors	34	85%	[78]
2	Market demand	24	34%	[51,60,101,102]	2	Policy	28	70%	[61]
3	SC structure	23	33%	[39,80,102]	3	Environmental factors	27	68%	[46]
4	Environmental factors	19	27%	[48,80,103]	4	Market demand	25	63%	[45,89]
5	Technological adoption	18	26%	[48,73,104]	5	Technological adoption	20	50%	[58]
6	SC Infrastructure	14	20%	[27,105]	6	Economic factor	19	48%	[35]
7	Regulatory factors	12	17%	[39,52,102]	7	SC infrastructure	13	33%	[58]
8	Social factors	11	16%	[72,83]	8	Social factors	12	30%	[45,75]
9	Resource management	9	13%	[49,103]	9	Regulatory factors	12	30%	[61]
10	Policy and government	7	10%	[32,71]	10	Consumer behavior	11	28%	[52]
11	Socioeconomic factors	7	10%	[73,104]	11	Geographical factors	9	23%	[75]
12	Coordination Collaboration	4	6%	[42,44,86]	12	SC structure	8	20%	[36,58]
13	Geographical factors	4	6%	[44,104]	13	Innovation	7	18%	[40,87]
14	Logistical factors	3	4%	[25,48]	14	Collaboration/ Coordination	7	18%	[30]
15	Innovation	3	4%	[80,86]	15	Logistical factors	5	13%	[106]
16	Culture, community management	3	4%	[72,84]	16	Resource management	5	13%	[40]
17	Information sharing	2	3%	[25,107]	17	Socioeconomic factors	4	10%	[53]
18	Seasonality	2	3%	[63,108]	18	Risk factors	4	10%	[36]
19	External support	2	3%	[38,77]	19	Credit access	3	8%	[35,87]
20	Intermediary power	2	3%	[31,109]	20	Commitment	3	8%	[29,30]
Note	SC sustainability	7	10%	[64,84]	Note	SC sustainability	12	30%	[61,75]

3. Theoretical Foundation

This study is firmly grounded in the well-known Resource-Based View (RBV) theory. RBV postulates that the firm outperforms its competitors through unique and firm-specific resources that are costly for others to imitate and substitute [110]. In this respect, it is argued that these resources are core elements of RBV [111]. Across the literature, RBV is one of the most accepted and applied strategic management theories, incorporating resources and capabilities as an essential and irreplaceable source for gaining sustainable competitive advantages [110,112,113,114,115]. Under the shade of RBV theory in the supply chain context, each specific supply chain has its own measures and determinants to gain its competitive advantages.

Using RBV theory, this study aims to understand the measures and determinants of SCAs in an emerging economy like Vietnam. This is not just a theoretical exercise but a practical necessity that will help researchers and practitioners identify the key resources for success within the context of emerging countries. This study’s unique contribution lies in providing insights on which resources are most important for SCAs pre- and post- COVID 19 in these countries, aligning the choices of measures and determinants with their available resources.

4. Context of Vietnam

Vietnam is a well-known exporter of aquaculture and fishery products. In 2023, Vietnam was ranked among the top five countries globally regarding food safety management capacity. It is also one of the five largest seafood exporting countries in the world in terms of value, with export turnover ranging from 9 to 11 billion USD annually [116].

Vietnamese aquaculture products are exported to nearly 170 markets, including primary and demanding markets such as the EU, the US, Japan, Australia, the UK, South Korea, and China. The aquaculture sector is always in Vietnam’s top 10 major export sectors, directly driving employment and providing livelihoods for over 4 million workers. The aquaculture industry is one of the few sectors for which the Prime Minister of Vietnam issues a development strategy every 10 years [116].

Looking at Vietnam’s economy, 75% is generated by foreign-invested enterprises (FDI), while Vietnamese enterprises contribute approximately 25% to the overall export turnover [116]. However, in the aquaculture and seafood production sector, most enterprises are privately owned Vietnamese businesses, with very few FDI enterprises investing in crucial links such as processing for seafood export. The export turnover created by Vietnamese enterprises accounts for 92–95% of Vietnam’s aquaculture and seafood exports, which is a crucial indicator receiving attention from the government based on the value it brings to the Vietnamese people.

In the market, aquaculture and seafood exports account for 10–12% of the total export turnover of domestic manufacturing sectors. The ratio of Vietnamese private enterprises in the seafood processing and export industry is over 97% [116], which reflects the Vietnamese business community’s significant internal capacity and effort in integration, competition, and creating high-value-added products.

Despite the success, approximately 80% of aquaculture farms and households in Vietnam are small, with less than ten workers, and medium-sized, with less than twenty workers. All logistics activities are the responsibility of manufacturers and exporters/traders. Therefore, all researchers and practitioners question how the sector has become one of the top five largest exporters in the world.

5. Methodology

Due to the nature of Vietnam’s aquaculture supply chain (VSCA), which contains mainly local farming and processing enterprises and therefore is under the impacts of social and cultural perspectives, this study was designed following the interpretivism paradigm, which believes that the nature of reality is socially constructed, subjective, and varies according to individuals. This paradigm guided our approach to the study, encouraging us to observe and engage with each supply chain stakeholder at the exporting end to gain knowledge. The interview method, a cornerstone of our research, enabled us to delve into the reasons for gaining competitive advantages for the whole sector and the SCA, ensuring a comprehensive understanding. Scholars such as [117,118] have underscored the value of in-depth interviews in facilitating a deep analysis of exploratory studies. In line with this, our study, which sought to understand the complex nature of Vietnam’s aquaculture supply chain (VSCA), was inherently exploratory. As a result, a qualitative research approach, with its focus on understanding the nuances and complexities of the VSCA, was deemed the most suitable for our study.

For the selection of the interview sample, our research team took into account various recommendations, including [119], which suggests a range of 5 to 25 interviews for a phenomenological study and 20–30 for a grounded theory study. However, considering the need for a sample of heterogeneity and the research objectives, Kuzel (1992) and Guest et al. (2006) [120,121] proposed that six to eight interviews are sufficient for a homogeneous sample and twelve to twenty for achieving maximum variations. In line with this, our team conducted in-depth interviews with a diverse range of 36 enterprises and two government agencies (a total of 38 participants, including aqua farms, production enterprises, and trading companies) and 2 government agencies. The participants, all senior managers with over 5 years of experience in SCA, each provided a comparison of VSCA’s competitiveness before and after the COVID-19 pandemic, thereby contributing to a comprehensive and representative study.

Because the selected interviewees (Table 3) were involved in a wide range of supply chain activities, from farm operation and management to manufacturers’ production and sale and logistics service operation and management, their insights, based on their hands-on experience, helped in drawing a deeper understanding of the issues involved in SCA crossing the entire spectrum of the measures and determinants following the most available resources to provide a comprehensive practice. The interviews were conducted both online and face-to-face. Each interview lasted 45 to 90 min, depending on the stakeholders’ willingness to share. After interviews, the researchers utilized the NVivo 14 software package to manage the study’s code nodes and data structures and perform data analysis. The themes that arose from the analysis were generalized, reflecting the collaborative nature of the research.

6. Data Analysis

As mentioned, the interpretivism paradigm believes that the nature of reality is socially constructed, subjective, and varies according to the individual. Therefore, it may cause potential biases such as confirmation or observer bias and impact the findings [122]. However, the researchers utilize RBV theory to motivate the relevant research gaps. Themes such as measures and determinants pre- and post-COVID-19-pandemic provided overarching topics to be explored in the interviews. This method is selected because this research context (i.e., measures and determinants of SCA before and after the COVID-19 pandemic) is purely unexplored, and there is no analysis of the changes in measures and determinants after the COVID-19 pandemic. Thus, the researchers kept an open mind to follow the story of the interviewees.

The data analysis procedure is an iterative process of open, axial, and selective coding [122]. During the open coding phase, the transcribed interviews were analyzed line by line to identify key phrases and sentences describing events explained by the interviewees. Each code represented a summarized interpretation of an event. The researchers selected codes based on relevant topics discussed in the literature (the open coding scheme) and new themes that emerged directly from the interview content (in vivo coding). This process, crucial for maintaining academic rigor, ensured that the emerging themes were aligned with the existing literature. In the axial coding phase, the concepts identified during the open coding phase were compared and analyzed in relation to one another. Similarly to the process mentioned by [123], the researchers examined the relationships among the identified concepts and grouped them into relevant categories (cross-referenced to form broader “umbrella concepts”, referred to as categories). They focused on establishing connections between concepts and categories during the selective coding phase to develop core themes. These core themes were tentatively aligned with and organized into key measures and determinant domains. At this stage, the researchers compared the findings with the existing literature to refine and logically reorganize the measure and determinant domains, ensuring they accurately reflected the interview data. This process completed the data analysis lifecycle. The themes and categories derived from the analysis are detailed in the findings section (as illustrated in Figure 1) and then are summarized in Table 4.

7. Findings

The interview outcomes present three models of VSCA, in which the stakeholders decided the competitiveness measures and determinants accordingly. In all three models, processors/manufacturers can negotiate prices with farmers, collectors, and 3PLs. However, it is crucial to note that customers hold significant power in price negotiations of finished products sold in the importing countries’ market.

• Model 1: Small-Scale Aquaculture Farmers and Processors/Manufacturers

In Vietnam, most farms are small-scale, smaller than 1.5 hectares (78%). However, only about 40–45% of small-size farms follow the structure of Model 1. In this model, the collectors collect the raw products from the farmers and decide their market price. In contrast, the manufacturers decide on collectors and 3PLs and retain price negotiation power. The manufacturers in Model 1 (Figure 2) mainly cut and pack the raw products for export. If the standards of importing countries, such as strict regulations on chemical residues or specific product sizes, are higher than those of the local government and the raw products do not meet the standards of the importing countries, the manufacturers will refuse to buy, and the collectors will bring the unqualified products to the local flea markets.

• Model 2: Medium-Scale Aquaculture Farmers and Processors/Manufacturers

Model 2 (Figure 3), adopted by approximately 50% of farms, is a collaborative effort between manufacturers and farmers. Manufacturers play a crucial role in this model, investing in farm development and equipment, training farm workers, and purchasing high-quality raw products. Their expertise is particularly valuable in guiding farmers to meet the standards of international markets, ensuring the export-readiness of the products.

• Model 3: Corporations who integrate all the stakeholders into VSCA

Only six corporations integrate suppliers into their supply chain in Vietnam, where the manufacturers operate their farms and workers (Model 3, Figure 4). These manufacturers are at the forefront of innovation, implementing high technologies and digital technologies to strictly follow the standards of the importing countries. This model has no unqualified products for the local market but 100% for export purposes. The manufacturers implement a variety of advanced technologies and export a wide variety of finished products (as value-added foods) to different countries, not only raw products.

7.1. Measures for Vietnam’s SCA Competitiveness

The findings on measures for VSCA competitiveness are presented in Table 4 under the shade of Resource-Based View (RBV) theory, which emphasizes the internal resources and capabilities of a firm as sources of competitive advantage. The COVID-19 pandemic significantly impacted VSCA, exposing vulnerabilities and reshaping the dynamics of supply chain competitiveness, even though some essential measures for VSCA’s competitiveness are unchanged (market share/access; cost efficiency), which are also similar to the findings from the literature. However, different from the literature, measures for SC sustainability and SC resilience are taking over the vital role of price and profitability metrics in the opinions of SCA stakeholders.

However, the analysis also shows that the selected measures for SCC depend on the model type of the SC, which has never been mentioned in any of the literature. For instance, the stakeholders of Model 1 (M1) and Model 2 (M2) informed us that even though they know the vital role of sustainable strategy and resilience, they still cannot implement these measures in their upcoming annual plan due to the limited resources available. Instead, they can only focus on exporting at a higher volume than the previous year by searching for more suitable markets. These processors and traders usually set up their yearly plan to increase 5% to 10% annually in terms of export volume and value, which indirectly increases their market share. Even Model 3 (M3), which has more resources available, faces higher market requests after the COVID-19 pandemic. However, the stakeholders in Model 3 are implementing more innovation, particularly digital technologies, which can significantly enhance their SCA’s transparency for sustainable objectives, forming the 7th measure of Technology Adoption and paving the way for a more transparent and efficient supply chain management in the future.

Due to the limited financial and capability resources for technology investment, other five key measures that VSCA will aim for in the recent and near future are as follows: Customer Responsiveness and Retention (6th, CRR—agreed by 11 interviewees), Product Innovation (7th, agreed by 7 interviewees), SC Performance (8th, agreed by 14 interviewees), Price (9th, agreed by 20 interviewees), and in association with SC Integration (Agreed by 8 interviewees).

“We were successful increasing the exporting volume and value in 2022, but then these are slightly dropped in 2023. We must keep our customers so must figure out how to improve our SC through innovation and higher efficiency”

(I4–16, I19–24)

These findings, which differ from the literature’s top five to ten measures of market price, SC capacity/capability, SC profitability, and SC compliance, can be explained through RBV. This theoretical framework helps us understand that the resources of a developing country like Vietnam, such as Traditional Network, Low-cost HR, Production, and materials, shape its supply chain measures. However, the country lacks financial resources for investment (i.e., M1, M2), inventory resources, high-quality HR, suppliers’ control, SC control, and sourcing.

7.2. Determinants for VSCA Competitiveness

Using the same data analysis process presented in Figure 1 to compare this study with the literature and discuss the study innovation, Table 5 illustrates that the determinants have changed after the COVID-19 pandemic. From the interview outcomes, the VSCA’s stakeholders show slightly different perspectives before and after the COVID-19 pandemic, where the first three determinants are kept the same (1st, 2nd, 3rd) but change their priority in sequence. They are Government/Policy, Market Demand, and the regulations that import countries pursue. A significant 80% of interviewed Vietnamese stakeholders agreed that the Vietnamese government is performing sufficiently in setting Trade Agreements between Vietnam and the importing countries, a testament to the government’s impactful role in VSCA. The stakeholders in VSCA recognized the role of governments and associations in boosting communication and new market approaches for VSCA. However, the tightening regulatory process in importing countries poses a challenge for VSCA, which requires VSCA to focus on a more transparent SC. Within this context, each model of VSCA aims for a different target: stakeholders in M1 are now discovering and learning about the national regulations in terms of going to the national strategy toward sustainability, and stakeholders of M2 are implementing them, while M3 has already implemented a clear vision in their farms and processing sites according to the regulatory guidelines given by importing countries.

The interviewees also explained the changing pattern of the key determinants pre- and post-COVID-19 pandemic. The focus of this shift is towards Sustainability (including environmental factors) and Technology Innovation, as well as SC Structure/Cooperation, beyond the traditional determinants such as Economic and Logistics factors. During interviews, the stakeholders confirmed that the infrastructure and logistics are essential for implementing green practices in their distribution centers and transportation network. However, they are listed behind Sustainability and Technology Innovation after the COVID-19 pandemic, which shows the priority of having more sustainable, innovative SC.

“The most important determinants for us currently are the government support, the market demand associating with the regulatory in importing countries”

(I14, I17, I19, I23, I25, I26, I30)

However, under the RBV theory, due to the limitation of resources, only M3 can innovate technology used for farming, harvesting, and R&D. Some manufacturers in M2 complained that the cost of technology is too high while not bringing a better outcome in production than those in traditional methods. Additionally, stakeholders in M1 only want to keep the lowest cost possible and presently say no to innovation due to a lack of capital budget.

“Corps have invested innovative technologies in farms, processing, R&D”

(I19, I35, M3)

“The workers did better at cutting than cutting machines”

(I12, I15, I16, I18, M2)

“We focus our resource on farming and processing”

(I4, I6, I7, I12, M1)

Finally, different from the literature, which did not prioritize the vital role of collaboration in competitiveness, VSCA’s stakeholders recognize the importance of the linkage between the buyers and suppliers, which reflects trust and flexibility but not much about information sharing and supplier management. This situation correctly reflects the circumstances of an emerging country, providing a valuable insight into the unique challenges and opportunities in such environments. Also, they confirmed that social factors such as worker skills also affect the products’ quality for exporting purposes. However, human resources have not been invested in correctly.

8. Implications

The study thoroughly reviewed the literature on the SCA’s measures and determinants pre- and post-COVID-19-pandemic and then analyzed Vietnam as a case study under the shade of RBV. This research, with its practical implications, is a valuable resource for both academics and practitioners in the field of supply chain management. First, while the literature indicates consistent traditional resource-based SCA measures such as market share, cost efficiency, productivity, capacity, etc., which are aligned with the core of the RBV theory, findings from this research contribute to enriching the theory in the new VUCA (volatility, uncertainty, complexity, and ambiguity) business environment after the COVID-19 pandemic. This research has confirmed that SCA in the new context should also be defined by supply chain virtues associated with the new business environment, i.e., SC Resilience (ability to adapt to disruptions), SC Sustainability (long-term viability), SC Reliability (consistency in performance), SC Integration (seamless coordination), etc. These findings imply a new horizon for RBV applications. The measures that help define competitive advantage in the new business environment should go beyond the traditional tangible and intangible resources under business certainty and encompass those that differentiate the firms and their supply chain during business turbulence. The aforementioned academic contribution also leads to another related to the determinants of SCA in terms of expanding the application of the RBV theory. Specifically, while confirming the currency of key determinants of SCA in the literature, findings from this research also suggest that SCA in the new business environment of VUCA nature would be affected by technology innovation, sustainability orientation, SC structure/cooperation, etc., which correspond well to the new measures of SCA. This interesting finding implies that factors that help firms and their supply chains leverage the environment in the new business environment would contribute to their competitive advantage. Again, this can be considered a significant contribution to expanding the RBV application, specifically in the context of the VUCA business environment.

The findings also add a new perspective to the literature on how a developing country prioritizes the measures and determinants for SCA competitiveness due to the lack of resources. The research, a collaborative effort, proposes a new framework of competitiveness measures and determinants for Vietnam as a case of emerging countries. This discovery takes researchers to other potential research, such as the competitiveness of suppliers and market entry for new players. Likewise, it offers the empirical foundation through previous studies on the competitiveness of the supply chain of aquaculture and fishery, making the audience feel included in a larger community of researchers and stakeholders.

The study provides a practical list of measures and determinants that SCA’s stakeholders can implement for SCAs in emerging countries. It helps the SCA’s stakeholders recognize the priority of the shortage of capital and resources, empowering them to make informed decisions. The discussions are critical for SC managers to understand and manage their resources within their SC’s unique context. In addition, the analysis of VSCA allows involving professionals in identifying suitable management strategies for a more sustainable and efficient SCA, further enhancing their understanding and control over the supply chain.

9. Limitations

The study has some limitations, such as the study’s database and the methodology. Because only peer-reviewed academic papers are selected, other sources of information or published materials elsewhere have been ignored; precisely, different types of peer-reviewed publications, likely proceedings papers, books, and PhD theses were not investigated to contribute to this analysis. Additionally, some non-peer-reviewed sources could offer new concepts or other determinants and measures that could enrich the analysis. Therefore, the study could benefit from exploring these alternative sources. Also, the qualitative method, such as the interview, has its disadvantages because the experts’ opinions do not provide much statistical data.

10. Conclusions

By reviewing 110 articles, this paper analyzed measures and determinants of SCA competitiveness for mapping the states of the pre- and post-COVID-19-pandemic period. From the literature, we found that there has been a massive change in prioritizing measures and determinants before and after the COVID-19 pandemic. This discovery opens more directions for future research. Additionally, the empirical analysis of this study immediately fills this literature gap. Our case study of Vietnam confirms some of the existing views on the measurements, which can be implemented to improve SCA’s competitiveness and introduce new insights. It highlights the role of the scale of SC in resource allocation and the specific measures that small- and medium-scale businesses will focus on. This case study significantly contributes to the understanding of SCA competitiveness.

A similar situation arose in the determination of competitiveness determinants for SCAs. While all stakeholders acknowledge the crucial role of key determinants such as government support, policy, market demand, and regulations, there are more favorable determinants to large-scale enterprises, which smaller enterprises may struggle to implement due to resource constraints. This scenario provides practitioners with a practical understanding of emerging countries and the ability to adapt supply chains accordingly. These findings contribute to the literature by presenting an extensive list of measures and determinants for analyzing SCA competitiveness and offering actionable insights for practitioners in the field.

Author Contributions

Abstract, Introduction, Data analysis, Findings: T.-T.N.; Literature review: J.Y.T.; Data collection/Interview: H.-V.P., T.H.T.T.; Literature analysis and Data validation: C.M.P.; Implications, Limitations, and Conclusions: V.V.T. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of INSTITUTE OF STRATEGY, POLICY ON SCIENCE AND TECHNOLOGY (protocol code o.: 21/VCLCS on 29 March 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data sharing is not applicable due to the confidential information of interviewees.

Conflicts of Interest

Author Jackie Yen Tan was employed by BorderDollar. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. Example of data structure.

Figure 2. The model of VSCA formed by small-scale farms and manufacturers.

Figure 3. The model of VSCA formed by medium-sized farms and manufacturers.

Figure 4. The model of VSCA formed by corporations integrating all stakeholders.

Table 1

List of priority measurements for SCAs’ pre- and post-COVID-19-pandemic competitiveness.

#	Indicators Pre-COVID-19	# Papers	%	Publications	Indicators Post-COVID-19	# Papers	%	Publications
1	Market Share/ Market Access	25	35.7%	[25,26,27]	Market share/ Access	31	78%	[28,29,30]
2	SC Sustainability	25	35.7%	[31,32,33,34]	SC Efficiency/ Cost efficiency	21	53%	[35,36,37]
3	SC Efficiency/ Cost efficiency	24	34.2%	[27,38,39]	SC Performance	21	53%	[40,41,42]
4	Market Price	20	28.5%	[34,43,44]	SC Sustainability	18	45%	[45,46,47]
5	SC Compliance	11	15.7%	[48,49,50,51]	SC Resilience	17	43%	[41,52,53]
6	Performance/ Productivity	11	15.7%	[54,55,56]	Market Price	16	40%	[28,57,58]
7	Profitability/Cost/ Revenue	11	15.7%	[54,55,56]	SC Capacity	13	33%	[46,59,60]
8	Products’ Quality	7	10.0%	[27,48]	SC Capability	12	30%	[28,61,62]
9	SC Capacity	6	8.6%	[63,64]	SC Profitability	9	23%	[36,53,65]
10	SC Stability	4	5.7%	[64,66]	SC Compliance	7	18%	[67,68]
11	SC Consumer Satisfaction	4	6%	[69,70]	SC Safety	6	15%	[30,61]
12	SC Aadaption	4	6%	[71,72,73]	SC Integration	5	13%	[74,75]
13	SC Resilience	4	6%	[76,77]	SC Quality	5	13%	[78,79]
14	SC Productivity	3	4%	[25,80]	SC Security	6	15%	[30,61]
15	SC Capability	3	4%	[72,81]	SC Risk	5	13%	[61,82]
16	SC Risk	2	3%	[25,27]	SC Stability	5	13%	[57,58]
17	SC Agility	2	3%	[83,84]	SC agility	4	10%	[47,85]
18	SC Integration	2	3%	[66,86]	SC Reliability/Responsiveness	4	10%	[78,87]
19	SC Relationship	2	3%	[31,88]	SC Flexibility	3	8%	[78,89]
20	SC Value Addition	1	1%	[48]	SC Value Addition	3	8%	[35,65]

Table 3

Interviewees’ experience and expertise.

No	Interviewee Companies	Number of Companies	Number of Interviewees	Positions	Remark
1	Aquaculture Farms (Prawn, White Fishes)	12	12	Farm owner, Farm manager(From I1 to I12)	Minimum of 10 years of experience
2	Aquaculture Corporation(Farms-Manufacturer-Exporter)	6	6	Managers, senior managers(From I13–I18)	Minimum of 5 years of experience
3	Manufactures/Exporters	12	12	CEO, Manager,(From I19 to I30)	Minimum of 5 years of experience
4	Logistics providers	4	4	CEO, Manager,(From I31 to I34)	Minimum of 5 years of experience
5	Collectors/Middlemen	2	2	From I35–I36	Minimum of 5 years of experience
5	Government agencies	2	2	Head of Department(From I23 to I24)	N/A
	TOTAL	38	38

Table 4

VSCA measures before and after COVID-19 according to RBV.

#	Key Measures Before COVID-19	Key Measures After COVID-19	Lacked Resources	Available Resources
1	Market Share/Access	Market Share/Access	Financial resource for investment (M1, M2),Inventory recourse,High-quality HR, Suppliers’ control,SC control (M1, M2), Sourcing	Traditional Network,Low-cost HR, Low production cost, Low cost of materials, Financial Resource (M3)
2	Cost Efficiency	Product quality
3	Price	SC/Cost Efficiency
4	Productivity	SC Sustainability
5	Profitability	SC Resilience
6	Stability	CRR
7	Capacity	Innovation
8	Customer Retention	Performance
9	Compliance	Price
10	Relationship	Integration

Table 5

VSCA determinants before and after COVID-19 according to RBV.

#	Before COVID-19	After COVID-19	Lacked Resources	Available Resources
1	Market demand	Government/policy	Financial resource for business and logistics infrastructure, high-tech development,High-quality markets,Market Knowledge,Global SC networks	Strong support from Vietnamese government,Farming and processing resource,Existing customers
2	Regulatory factors	Market demand
3	Government/policy	Regulatory factors
4	Infrastructure	Sustainability
5	Logistical factors	Innovation/Tech adoption
6	Economic factors	Structure/cooperation
7	Innovation factor	Logistical factors
8	Resource management	Infrastructure
9	Seasonality	Economic factors
10	Environmental factors	Social factors

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