Agri-Food Export Barriers: A Comparative Analysis of Australia’s Meat, Horticulture, and Aquaculture Sectors

Abstract

This study aimed to examine the range of external export barriers that three Australian agri-food sectors, i.e., red meat, horticulture, and aquaculture, encounter, and to empirically measure and compare the perceived severity of these barriers by producers across the three sectors. A computer-assisted telephone interviewing survey was conducted to assess producers’ perception of individual export barriers. The results suggest that highly ranked export barriers for the three sectors are: high labor costs, market and financial risks, a lack of provenance information for competitiveness, and production risks. Some variations in the rated severity of barriers were observed across the three sectors and between producers who were currently exporting and those who were not, suggesting that non-exporters may consider the barriers different from exporters. While some barriers can be addressed through cross-sector planning, others require the development of sector specific strategies.

Keywords:

• Agri-food
• aquaculture
• Australia
• barriers
• export
• horticulture
• market access
• measure
• meat
• trade

Introduction

Agri-food products can be defined as outputs from primary food production systems such as agriculture, forestry, fishing, and aquaculture (e.g., crops, meat, seafood) that can be raw or include some level of processing/value adding (e.g., slaughter) (adapted from OECD, 2023). International trade in agri-food products is important to ensure food and nutrition security in countries that are unable to produce sufficient variety and/or volume of agri-food to meet the demand of their population (e.g., due to high production costs or lack of land/water). Protective measures that ensure the continuity of agriculture production and agri-food trade should therefore be taken. Agri-food trade can also offer consumers in importing countries the choice to access diverse, premium, and counter-seasonal products. Trade is also vital for countries with a comparative advantage in food production as it can provide employment opportunities, increase income, improve capacity utilization and trade balances, and positive spillover effects to other sectors (e.g., technology, knowledge, best practice in production and supply chain management), which subsequently leads to economic growth (e.g., Ahmed, Julian, Baalbaki, & Hadidian, 2006; Fleming, Abler, & Goetz, 2010; Fleming & Abler, 2013).

A range of barriers (e.g., tariffs, financial risks, and freight costs) can affect the export of agri-food products, which are broadly considered as constraints inhibiting producers to initiate, develop, and sustain the distribution of their products to overseas markets (Leonidou, 1995a). These export barriers can have negative implications for exporting countries (e.g., lost opportunities in selling agri-food products and in gaining higher returns, specifically if the domestic market is saturated). Therefore, agri-food producing industries have an incentive to identify and address export barriers.

The focus of this study is on export barriers that Australia’s agri-food production industry encounters. Australia exports approximately 72% of the total agricultural production annually with a total value of AUD 76 billion (ABARES, 2023b). This includes red meat, sugar, canola, wheat, rice, dairy products, fruit, nuts and seafood (ABARES, 2022; Steven, Dylewski, & Curtotti, 2021). The major export markets for Australian agri-food products include China, Japan, USA, Indonesia, Hong Kong, Republic of Korea, and Singapore (ABARES, 2023b; Steven et al., 2021). Yet, there is a perception that Australia’s agri-food export volume could be further increased, specifically for boxed/packed chilled and frozen red meat (e.g., beef, lamb), fresh/chilled horticulture products (e.g., oranges, mandarins, stone fruit, cherries, grapes, potatoes), and fresh/chilled aquaculture products (e.g. salmonids, tuna, abalone, oysters) (e.g., Cobcroft, Bell, Fitzgerald, & Jerry, 2020; KPMG, 2020; QLD DAF, 2018).

While there is a range of studies that note the existence of individual export barriers affecting specific agri-food sectors in Australia (e.g., Babacan & Tremblay, 2020; Greenville, 2019; KPMG, 2020; Tremblay, Babacan, & McHugh, 2020), the barriers have not been summarized and compared in their perceived severity by agri-food producers across different sectors. Hence, the current understanding about export barriers at sector and cross-sector scale is fragmented.

This study aimed to improve the understanding of the range of export barriers that agri-food sectors in Australia (i.e., red meat, horticulture, and aquaculture) currently encounter, and to empirically measure and compare the perceived severity of these barriers by producers.

The scope of this study is defined as identifying and comparing export barriers at a sector scale (e.g., red meat, horticulture, aquaculture). The focus is specifically on perceived external export impediments (e.g., tariffs, production risk, infrastructure availability, competition in export markets, collaboration among producers) (e.g., Kahiya, 2018; Leonidou, 2004; Morgan, 1999). This perspective excludes potential firm internal barriers such as decision maker and firm characteristics (e.g., managers’ attitude, socio-demographics, firm size).

Findings from a literature review and focus group consultations were used to identify and categorize potential firm external agri-food export barriers. A computer-assisted telephone interviewing (CATI) survey with producers of the three agri-food sectors (red meat, horticulture, and aquaculture) was undertaken to empirically assess the perceived severity of individual export impediments.

While the results from this study have immediate relevance for Australian agri-businesses, peak industry bodies, and policymakers, they may also be of interest for similar stakeholders in other agri-food export-orientated countries.

Export barriers

The literature offers a range of studies which focus on identifying and comparing export impediments that firms in manufacturing industries encounter (e.g., Arteaga-Ortiz & Fernández-Ortiz, 2010; Kahiya & Dean, 2016; Leonidou, 2004; Suarez-Ortega, 2003; Sudarević & Radojević, 2014; Uner, Kocak, Cavusgil, & Cavusgil, 2013). Many export barriers have been identified in these studies which include their categorization according to themes that these impediments share. For example, export barriers can be classified as external (e.g., industry and export market characteristics, macroeconomic factors) and internal (e.g., manager attitudes and demographics, firm characteristics) from a firm/organizational perspective (Kahiya, 2018; Leonidou, 2004; Morgan, 1997; Sousa, Martínez-López, & Coelho, 2008). A categorization into domestic or foreign barriers (e.g., trade regulation such as tariffs, and consumer demand) from a market perspective has also been proposed (Kahiya, 2018; Morgan, 1999; Suarez-Ortega, 2003). In contrast, Kahiya, Dean, and Heyl (2014) and Arteaga-Ortiz and Fernández-Ortiz (2010) classified export barriers into knowledge/experience (e.g., lack of information, company ignorance of basic aspect of exporting), resource (e.g., lack of financial resources, insufficient production capacity), procedure (e.g., complexity of documentation or bureaucracy linked to export operations, logistics difficulties), and exogenous (e.g., uncertainty in international markets, strong international competition). The use of these different perspectives on export barriers suggests that their application depends on the context and aim of analysis.

However, limited focus has been put on summarizing impediments that firms experience in the context of agri-food export (e.g., Ramaseshan & Soutar, 1995). Agri-food products differ to manufactured goods, for example, due to its perishability characteristic and associated food safety risks, biosecurity risks and production in mostly rural regions with potential logistical and infrastructure challenges (e.g., underdeveloped road networks). Accordingly, food standards, guidelines and codes, such as the Codex Alimentarius, exist to protect consumer health and promote fair practices in food trade (FAO/WHO, 2022). Given these industry-specific product traits, export impediments that agri-food producers encounter may differ to the ones that producers in other industries experience.

The focus of this study was on export barriers in agri-food firms’ external environment (e.g., Leonidou, 2004; Morgan, 1997, 1999; Sudarević & Radojević, 2014). The rational for taking this perspective is based on the need for an improved understanding of the firm external environment and how it may vary across agri-food sectors. Such understanding is vital for industry/sector managers and policy makers to develop effective strategies that remove or minimize these export impediments (e.g., facilitate export through developing industry/sector wide export strategies and marketing plans, targeted intergovernmental trade negotiations) (e.g., Ahmed et al., 2006; Arita, Beckman, & Mitchell, 2017; Leonidou, 1995b).

A compendium of potential agri-food export barriers that focuses on the firm external environment is presented in Figure 1. This compendium has been developed through a literature review which is outlined in detail in the supplementary material.

Figure 1. Compendium of firm external agri-food export barriers by category. Source: Kahiya (2018), Arteaga-Ortiz and Fernández-Ortiz (2010), Leonidou (1995b), Suarez-Ortega (2003), Uner et al. (2013), Sudarević and Radojević (2014), Ramaseshan and Soutar (1995). Additional sources are provided in Table S.1 in the supplementary material.

The compendium comprises 49 individual export barriers (Figure 1). The identified export barriers were categorized into a) trade regulation, b) the market, c) product supply and distribution, and d) the enabling environment to recognize shared themes and similarities among the individual items in the compendium. The categorization of export barriers was based on the (manufactured goods focused) literature (e.g., Kahiya, 2018; Leonidou, 2004; Morgan, 1997; Sousa et al., 2008) and discussion with a focus group which represented the three agri-food sectors (see supplementary material) to ensure that the agri-food context was considered in identifying the thematic groups.

The category “trade regulation” comprises individual export barriers that are related to trade directives such a tariffs/taxes, sanitary and phytosanitary (SPS) requirements (i.e., to minimize biosecurity risk), and technical requirements (e.g., technical barriers to trade (TBT) such as product labeling) that apply to agri-food exports (e.g., Kahiya, 2018; Morgan, 1999). This category also includes impediments linked to pre-shipment inspection/formalities, obtaining export permits and associated costs.

“The market”, as the second category, includes impediments that are associated with market situations (e.g., high competition or lack of demand for products in export markets, high demand for products in the domestic market), food quality standards (e.g., high quality, environmental or ethical/social food attribute requirements), as well as market and financial risks (e.g., Kahiya, 2018; Morgan, 1997, 1999).

The third category, “product supply and distribution”, encompasses export barriers that can affect agri-food production, supply, and distribution. For example, production risks (e.g., severe weather, pests, and diseases), availability of inputs (e.g., labor), collaboration aspects (e.g., trust among supply chain stakeholders), and freight costs.

The “enabling environment”, as the fourth category, comprises impediments that describe the firm external conditions which can facilitate product export or support agri-businesses in their export decision making process (e.g., Morgan, 1997; Suarez-Ortega, 2003). This includes the potential lack of access to capital investment, export links, information about markets, collaborations among producers, support by peak industry bodies, and infrastructure (e.g., road, rail, air/seaport network).

The compendium of external agri-food export barriers was used as a baseline in this study to empirically address producers’ perceived severity of these impediments.

Australian agri-food sectors

The three Australian agri-food sectors (i.e., red meat, horticulture, and aquaculture) selected for this study differ in their production and export volume, the economic value they generate, and their export maturity (e.g., ABARES, 2021; 2022). For example, the Australian red meat sector produces a very high volume and value with about 71% of the total production volume being exported (ABARES, 2022) (Table 1). Beef/veal is the key product exported with about 74% of the total red meat export volume (ABARES, 2022). The meat sector is characterized by a maturely developed export supply chain (Greenwood, Gardner, & Ferguson, 2018) and is globally recognized as one of the key exporters of high-quality meat products (ABARES, 2022; MLA, 2020). Major export countries for Australian red meat include China, Japan, Korea, USA, Qatar, United Arabic Emirates (ABARES, 2022). Australia also exports live cattle and sheep, yet these are not the focus of this study. Other red meat, e.g., pork and white meat, e.g., chicken, are predominantly produced for Australia’s domestic market and were therefore not included in this study (ABARES, 2023a).

Table 1. Overview of the three Australian agri-food sectors.

Production year 2019/20	Red meat*	Horticulture^#	Aquaculture^^
Key products produced	Beef, veal, lamb, mutton	Apples, pears, grapes, oranges, mandarins, bananas, mango, avocado, pineapple almonds, macadamia, potatoes, tomatoes, carrots, onions, lettuce, cabbages	Salmonids, tunas, prawns, oysters, barramundi, abalone
Total production volume/value	3,464 kt / AUD N/A	7,457 kt / AUD 10.18 billion	106,139 t / AUD 1.60 billion
Key export products (volume/value)	Packed/boxed chilled and frozen beef/veal (74%), lamb (16%), mutton (10%) (1,752kt / AUD 15.31 billion)	Fresh/chilled fruit (e.g., grapes, oranges, mandarins), vegetables (e.g., potatoes, tomatoes, onions), almonds, macadamia (4,483kt / AUD 3.02 billion)	Fresh/chilled salmonids and tuna (27,917 t/ AUD 357 million)
Current key export markets	China, Japan, Korea, USA, Qatar, United Arabic Emirates	China, Japan, New Zealand, Vietnam, Hongkong Singapore, USA, United Arabic Emirates, Saudi Arabia, South Korea	China, Hongkong, Japan, Indonesia, Thailand, USA, Vietnam

Sources: *(ABARES, 2022), (MLA, 2020), ^#(ABARES, 2022), (ABS, 2021), ^{^}(Steven et al., 2021).

Notes: 2019/20 was selected since the Covid-19 pandemics significantly impacted export volumes in more recent years 2020–2022. ‘t’ for tonnes, ‘kt’ for kilo tonnes, ‘AUD’ for Australian Dollars, ‘N/A’ for not available for red meat only.

The Australian horticulture sector produces a wide range of fruit (e.g., apples, pears, grapes, oranges, mandarins, bananas, mango, avocado, pineapple), vegetables (e.g., potatoes, tomatoes, carrots, onions, lettuce, cabbages), and nuts (e.g., almonds, macadamia, walnuts) (ABS, 2021; HortInnovation, 2020) (Table 1). Horticulture export is dominated by fresh/chilled fruit (e.g., grapes, oranges, mandarins) and nuts (e.g., macadamia) (ABARES, 2022; HortInnovation, 2020). Fresh vegetables are predominantly produced for the domestic market with minor export of potatoes, tomatoes, carrots and onions (ABARES, 2022). Major export markets for Australian horticulture products include China, Japan, New Zealand, Vietnam, Hongkong Singapore, and the USA (HortInnovation, 2020).

Aquaculture is a gradually emerging agri-food sector in Australia. It currently produces a relatively small volume and value of food in comparison to the red meat and horticulture sectors (Table 1). While salmonids and tunas are presently the key export products that the aquaculture sector produces, cultured prawns, oysters, and barramundi are supplied to meet the domestic demand for seafood (Schrobback, Pascoe, & Zhang, 2019; Schrobback & Rolfe, 2021). Major export markets of Australian aquaculture products are China, Hongkong, Japan, Indonesia, Thailand, USA, Vietnam (Steven et al., 2021).

Given the different characteristics of the three agri-food sectors, distinction in the perceived severity of export barriers by producers are expected. Yet, there may also be similarities. Insights into firm external export barriers for each sector and a comparison across sectors can offer a baseline for policy and industry managers to address them in a manner that further facilitates trade in agri-food products.

Methods

The compendium of export barriers (Figure 1) was considered as a baseline for the empirical analysis in the Australian agri-food export context. Prior to the empirical analysis focus group interviews with representatives of the three agri-food sectors were conducted to verify the identified potential export barriers and categories from the literature review. Details on how the focus group interviews were conducted and findings are provided in the supplementary material.

To measure and compare the perceived severity of these barriers by producers, a CATI survey was conducted with producers from the Australian red meat (i.e., beef, lamb), horticulture (i.e., fresh fruit and vegetables), and aquaculture sectors.

The CATI survey with producers from all three sectors was conducted during June 2021 and took about 10 minutes for participants to complete. The survey was undertaken by a commissioned independent company that specializes in Australian agri-business market research. Survey participants were sourced from the database of this service provider. Hence, participant selection may not be completely random, which can be a bias that may affect the results of this study.

The survey included questions about the participant’s socio-demographic characteristics (e.g., gender, age, experience in the sector), information about their production (e.g., type of product) and export status (i.e., currently exporting or not) and export pathway if currently exporting. The main part of the survey was for the participants to rate their perception of the severity of each export barrier. For that, the export barriers identified from the literature review and focus group interviews (Figure 1, supplementary material) were translated into corresponding statements. For example, the barrier “taxes/tariffs” was measured using the statement “Taxes/tariffs charged by the import country is a major barrier for export”. Participants were asked to indicate the extent to which they agreed with each statement on a 5-level Likert scale. These levels were defined as 1 for “strongly disagree,” 2 for “disagree,” 3 for “neither agree nor disagree,” 4 for “agree,” 5 for “strongly agree,” and “Don’t know” for no knowledge. When rating each statement, participants were instructed to either consider the export market to which they currently export their product, or if they did not presently export, they were asked to consider the market that they perceived as the highest value generating export market for their produce.

To analyze the perceived severity of export barriers by the survey respondents, the mean score for each barrier across the three sub-samples (i.e., three sectors) were calculated and subsequently ranked from highest to lowest. Export barriers with the highest mean score and highest rank suggest the most severe impediments and vice versa as perceived by participants. “Don’t know” responses to the rating task, indicating that participants were not familiar with specific barriers, were excluded in the mean score analysis.

For the descriptive sample statistics Tukey’s honest significance difference test (Haynes, 2013) was used to compare differences between the means within the three sub-samples. A p-value of less than 10% significance indicates that there is a significant difference between the means of sub-samples. To explore potential variation of the perceived severity of each market barrier between exporters and non-exporters in each sector, Levene’s test for equality of variance of mean scores was undertaken. The derived t-statistic with a p-value less than 10% significance suggests the rejection of the null hypothesis for equal variance of mean scores in the sub-samples, implying a significant difference in scores between sub-samples.

Results

Descriptive sample statistics

The descriptive statistics from the CATI survey are presented in Table 2. The total sample size consisted of 146 participants, including 51 from the meat sector, 47 from the horticulture sector, and 48 from the aquaculture sector.

Table 2. Descriptive survey sample statistics representing target agri-food sectors.

Observations	Meat		Horticulture		Aquaculture		Full sample
	N	%	N	%	N	%	N	%
Producers	51	35%	47	32%	48	33%	146	100%
Current export status of producers
Exporters	16	31%	24	51%	14	29%	54	37%
Non-exporters	35	69%	23	49%	34	71%	92	63%
Export pathway (exporters only)
Use of export agent	14	88%	22	92%	8	57%	44	81%
Manages entire export supply chain	1	6%	2	8%	6	43%	9	17%
Other	1	6%	0	0%	0	0%	1	2%
Gender
Male	50	98%	40	85%	40	83%	130	89%
Female	1	2%	7	15%	8	17%	16	11%
Age groups
18–24 years	0	0%	0	0%	0	0%	0	0%
25–30 years	0	0%	0	0%	0	0%	0	0%
31–40 years	2	4%	5	11%	2	4%	9	6%
41-50 years	9	18%	6	13%	13	27%	28	19%
51–60 years	15	29%	13	28%	15	31%	43	29%
Older than 60 years	25	49%	23	49%	17	35%	65	45%
Refuse response on age	0	0%	0	0%	1	2%	1	1%
Meat sub-sector representation
Beef	27	53%					27	18%
Lamb	24	47%					24	16%
Horticulture sub-sector representation
Pome fruit (e.g., apples, pears)			4	9%			4	3%
Stone fruit (e.g., cherries, peaches)			10	21%			10	7%
Citrus fruit (e.g., oranges, lemons)			13	28%			13	9%
Root vegetable (e.g., potatoes, carrots)			1	2%			1	1%
Leaf vegetable (e.g., broccoli, cauliflower)			3	6%			3	2%
Berries (e.g., strawberries, blue berries)			5	11%			5	3%
Grapes			9	19%			9	6%
Other			2	4%			2	1%
Aquaculture sub-sector representation
Fish (e.g., tuna, finfish, barramundi, perch)					15	29%	15	10%
Crustaceans (e.g., prawn, crab, yabbies)					9	18%	9	6%
Shellfish (e.g., abalone, oysters, mussels)					23	45%	23	16%
Other (e.g., sea cucumber, seaweed)					4	8%	4	3%
Producer’s experience	N	Mean (St. Dev.)	N	Mean (St. Dev.)	N	Mean (St. Dev.)	N	Mean (St. Dev.)
Years of experience in industry	51	41.2 (12.68)	47	34.11 (14.11)	48	25.79 (11.26)	146	33.70 (12.68)
Self-rated level of export experience^#	20*	2.5 (1.40)	24	3.00 (1.15)	14	3.93 (1.14)	58	3.14 (1.23)

Notes: ‘N’ for number of observations, % for proportion of subsample, ‘St. Dev.’ for standard deviation, *Included current exporters (n = 18) and respondents who exported in the past (n = 2). ^#Exporters were asked to rate their experience in product export on a scale from 1 (very low export experience) to 5 (very high export experience)

The meat sub-sample was relatively evenly represented by producers of beef and lamb. The horticulture sample represents a high proportion of producers from citrus and stone fruit, grape, and berry that are considered as high-value export products (HortInnovation, 2019). The aquaculture sample is dominated by producers from the shellfish sectors and fish sectors that reflects Australian aquaculture production by volume (ABARES, 2020). Tuna, abalone, and oysters are also considered as high-value seafood products, of which only tune is currently exported (ABARES, 2020). The socio-economic characteristics of the total sample align with agricultural producer profiles in Australia (Binks, Stenekes, Kruger, & Kancans, 2018; Schrobback, Coglan, & Pascoe, 2014). Aquaculture respondents had the lowest industry experience with approximately 15 and 8 years less than meat and horticulture respondents, respectively (mean: 25.79 years, mean difference in years compared to meat: −15.40, p-value: 0.000, and to horticulture: −8.32, p-value: 0.005). Horticulture respondents also had significantly lower industry experience compared to meat respondents (mean difference to meat: −7.09 p-value: 0.019). However, aquaculture exporters rated their export experience significantly higher than that of meat (mean difference: −1.429, p-value: 0.006) and horticulture (mean difference: −0.929, p-value: 0.087) exporters (Table 2).

Ranking of perceived severity of export barriers within and across agri-food sectors

Table 3 presents the ranking of all 49 barriers according to their mean score within each sector (see respective sector’s “Rank” column).

Table 3. Results of producer’s ratings of export barriers, grouped by categories (see Figure 1).

Cat.	ID	Export barrier	MEAT (N = 51)				HORTICULTURE (N = 47)				AQUACULTURE (N = 48)
			Rank	Mean	Std. Dev.	Don’t know	Rank	Mean	Std. Dev.	Don’t know	Rank	Mean	Std. Dev.	Don’t know
Trade regulations	1	Taxes/tariffs	2	3.92	1.04	4%	7	3.90	1.29	17%	22	3.21	1.46	10%
	2	Sanitary/phytosanitary requirements	35	2.98	1.16	10%	11	3.70	1.06	9%	40	2.70	1.17	10%
	3	Costs of meeting sanitary/phytosanitary requirements	23	3.13	1.11	10%	18	3.53	1.20	19%	35	2.90	1.34	13%
	4	Maximum residue limits	47	2.45	1.19	8%	43	3.00	1.33	4%	47	2.27	1.21	15%
	5	Costs of meeting maximum residue limits	41	2.72	1.05	10%	35	3.25	1.26	6%	45	2.38	1.17	17%
	6	Technical requirements (e.g., labeling, packaging)	39	2.76	1.16	27%	34	3.26	1.31	19%	42	2.66	1.16	8%
	7	Costs of meeting technical requirements	27	3.11	0.92	25%	16	3.55	1.20	19%	36	2.88	1.20	10%
	8	Pre-shipment export inspections/formalities	33	3.03	1.03	25%	26	3.35	1.23	15%	33	2.93	1.21	8%
	9	Costs of meeting pre-shipment requirements	16	3.37	1.00	25%	10	3.78	1.08	21%	38	2.84	1.22	8%
	10	Obtaining export permits/licenses	10	3.50	0.86	41%	32	3.29	1.45	28%	23	3.20	1.25	8%
	11	Costs of obtaining export permits/licenses	11	3.48	0.99	43%	12	3.67	1.05	30%	19	3.36	1.21	13%
		Mean scores for ‘Trade regulation’	25.82	3.13	1.05	21%	22.18	3.48	1.22	17%	34.55	2.85	1.23	11%
The market	12	Lack of demand for AUS product in export market	40	2.73	1.25	6%	46	2.84	1.43	9%	46	2.36	1.15	6%
	13	Strong domestic demand for agri-food product	18	3.29	1.06	0%	41	3.04	1.37	2%	6	3.79	1.40	0%
	14	AUS producer’s preference to supply the domestic market	26	3.12	1.25	4%	13	3.62	1.32	4%	4	4.00	1.09	0%
	15	High food quality standards in export market	24	3.13	0.91	22%	15	3.60	1.21	11%	37	2.88	1.10	15%
	16	Cost of meeting food quality standards in export market	28	3.09	1.05	10%	38	3.16	1.26	4%	27	2.98	1.22	13%
	17	High food safety standards in export market	31	3.05	0.94	27%	37	3.18	1.24	15%	41	2.67	1.10	13%
	18	Cost of meeting food safety standards in export market	29	3.09	1.10	14%	39	3.05	1.06	11%	28	2.98	1.17	15%
	19	Environmental sustainability product requirements in export market	48	2.41	1.09	43%	47	2.64	1.27	23%	49	2.08	1.14	17%
	20	Ethical/social product requirements in export market	45	2.60	1.31	31%	48	2.63	1.26	19%	48	2.26	1.11	13%
	21	Competition in export market	1	3.94	0.76	8%	5	4.00	0.99	15%	25	3.15	1.23	17%
	22	Market risks (e.g., geopolitical tension)	4	3.86	0.93	2%	4	4.10	1.06	11%	1	4.09	0.98	8%
	23	Financial risks (e.g., payment security, exchange rate)	3	3.87	0.85	8%	2	4.35	0.69	9%	9	3.59	1.34	4%
		Mean scores for ‘The market’	24.75	3.18	1.04	15%	27.92	3.35	1.18	11%	26.75	3.07	1.17	10%
Cat.	ID	Export barrier	MEAT (N = 51)				HORTICULTURE (N = 47)				AQUACULTURE (N = 48)
			Rank	Mean	Std. Dev.	Don’t know	Rank	Mean	Std. Dev.	Don’t know	Rank	Mean	Std. Dev.	Don’t know
Product supply & distribution	24	Production risks (e.g., extreme weather events, disease)	8	3.57	1.20	0%	6	3.98	1.11	2%	5	3.83	1.17	2%
	25	Lack of consistent high-quality supply volumes	14	3.40	1.25	2%	9	3.79	1.27	0%	8	3.67	1.24	0%
	26	Resource limitation (e.g., water) for increased production	9	3.57	1.26	4%	19	3.51	1.20	0%	20	3.35	1.19	0%
	27	Limited labor resources	13	3.41	1.19	0%	3	4.29	0.92	4%	10	3.58	1.05	0%
	28	High labor costs in AUS	5	3.86	1.10	4%	1	4.48	0.75	2%	2	4.08	0.92	0%
	29	Level of technology adoption to improve farm productivity	42	2.71	1.17	6%	40	3.05	1.33	6%	32	2.96	1.28	6%
	30	Limited product varieties/breeds available in AUS to meet export demand	49	2.08	0.91	4%	49	2.23	1.03	6%	44	2.42	1.16	6%
	31	Lack of access to export finance/insurance options for agri-food export	34	3.00	1.02	53%	24	3.39	1.12	34%	31	2.97	1.20	33%
	32	Need for individual business/product branding/marketing	32	3.04	1.23	10%	25	3.36	1.25	11%	21	3.24	1.15	6%
	33	Lack of provenance information as part of product branding/marketing	7	3.66	1.01	8%	8	3.81	1.03	9%	3	4.04	0.86	2%
	34	Lack of trust among supply chain stakeholders in AUS	44	2.63	1.03	22%	44	2.95	1.04	15%	43	2.62	1.01	6%
	35	Lack of trust among supply chain stakeholders in export market	22	3.20	1.11	31%	30	3.33	1.16	30%	15	3.47	1.01	21%
	36	Exporters limited understanding of business etiquette in export markets	43	2.70	1.21	16%	45	2.88	1.19	13%	26	3.15	1.08	17%
	37	Digital traceability requirements in export market	25	3.13	1.11	10%	17	3.54	1.07	17%	39	2.82	1.15	8%
	38	Reliability of cold chain systems to ensure product quality/safety	46	2.53	1.11	29%	33	3.27	1.33	21%	29	2.98	1.12	13%
	39	Supply chain fragmentation affecting competitiveness of the AUS product	15	3.39	1.03	35%	14	3.61	1.00	19%	13	3.51	1.17	15%
	40	Export freight costs	37	2.81	1.18	16%	22	3.44	1.18	9%	7	3.71	1.18	6%
		Mean scores for ‘Product supply & distribution’	26.18	3.10	1.12	15%	22.88	3.47	1.12	12%	20.47	3.32	1.11	8%
Enabling environment	41	Establishment of export links	12	3.44	1.29	37%	36	3.24	1.05	19%	24	3.17	1.24	4%
	42	Insufficient capital investment for export readiness	19	3.28	1.11	22%	20	3.46	1.08	13%	18	3.40	1.24	10%
	43	Insufficient capital investment at post-production level	36	2.98	1.17	16%	31	3.31	1.02	11%	16	3.47	1.06	21%
	44	Access to up-to-date market information	20	3.27	1.14	12%	23	3.44	1.12	9%	17	3.42	1.16	10%
	45	Access to information about product specific export requirements	21	3.26	1.02	24%	42	3.03	1.23	15%	30	2.98	1.10	10%
	46	Lack of collaboration between producers	30	3.06	1.15	8%	21	3.45	1.23	11%	12	3.53	1.21	2%
	47	Limited support by industry peak bodies	38	2.80	1.07	14%	27	3.35	1.21	9%	11	3.58	1.22	6%
	48	Limited government support for producers for export readiness	17	3.36	1.06	14%	29	3.34	1.22	13%	14	3.51	1.03	15%
	49	Lack of infrastructure (e.g., roads, ports, logistics) to support export	6	3.73	1.02	4%	28	3.35	1.27	9%	34	2.91	1.38	8%
		Mean scores for ‘Enabling environment’	22.11	3.24	1.11	17%	28.56	3.33	1.16	12%	19.56	3.33	1.18	10%

Notes: ‘N’ is the total number of respondents for each sector. ‘Cat.’ for export barrier category. ‘ID’ is the individual identifier of export barriers. ‘Mean’ indicates the mean score of all responses for individual barriers. ‘Std. Dev.’ for standard deviation. ‘Rank’ indicates the rank an individual barrier based on its mean score across responses in comparison to all other mean scores of barriers of the sector. ‘Don’t know’ indicates the proportion of respondents who were unable to provide a rating for respective export barriers within each sub-sample. AUS for Australia(n). Black-shaded cells identify the ten highest ranked, and the grey-shaded cells identify the ten lowest ranked, export barriers according to mean scores by sector and across sectors.

Highest ranked export barriers

The highest ranked export barriers in perceived severity were very similar across the three sectors. For example, within the top ten highest ranked barriers, five were shared by all three sectors. They were: “high labor costs in Australia” (ID28), “lack of provenance information as part of product branding/marketing” (ID33), “production risks” (ID24) (e.g., diseases, pests, extreme weather events), “market risks” (ID22) (e.g., geopolitical tensions), and “financial risks” (ID23) (e.g., payment security, exchange rate fluctuation) (see black shaded cells in Table 2). The results also revealed differences in the highest ranked barriers across the three sectors. For example, “competition in export market” (ID21) ranked 1st and 5th for meat and horticulture respectively, but only 25th for the aquaculture sector. Similarly, “Taxes/tariffs” (ID1) was ranked 2nd and 7th by meat and horticulture respectively, but only 22nd for aquaculture. Furthermore, some barriers were regarded as highly challenging by one sector but not by the other two sectors. For example, the “lack of infrastructure (e.g., roads, ports, logistics) to support product export” (ID49), “resource limitation (e.g., water) for increased production” (ID26), and “obtaining export permits/licenses” (ID10) were ranked 6th, 9th, and 10th respectively by the meat sector, but were reported as less challenging for horticulture (28th, 19th, and 32nd respectively) and aquaculture (34th, 20th, and 23rd respectively). These findings suggest that while there are shared barriers across the three sectors, there are also distinct export challenges facing each agri-food sector.

Lowest ranked export barriers

The results also show similarities in the perceived lowest ranked export barriers across the three sectors (shaded in grey in Table 3). The five barriers that all three sectors considered minor export impediments were: “limited product varieties/breeds available in Australia to meet export demand” (ID30) (implying that sufficient varieties/breeds are available), “environmental sustainability in export markets” (ID19), “ethical/social requirements in export markets” (ID20), “maximum residue limits” (ID4), and the “lack of demand for Australian product in the export market” (ID12) (implying that demand is sufficient).

Like the highest ranked barriers, differences were also apparent across the ten lowest ranked barriers across the three sectors. For example, “level of technology adoption to improve farm productivity” (ID29) and “exporters” limited understanding of business etiquette in export markets’ (ID36) ranked 42nd and 43rd respectively by meat sector and 40th and 45th respectively by horticulture but ranked comparatively more challenging by aquaculture at 32nd and 26th respectively.

Furthermore, some barriers were regarded as least challenging by one sector but as more problematic by the other two sectors. For example, “reliability of cold chain systems to ensure product quality/safety” (ID38) ranked 46th by meat sector but was 33rd and 29th respectively for horticulture and aquaculture. Similarly, “strong domestic demand for agri-food product” (ID13) and “access to information about product specific export requirements” (ID45) ranked 41st and 42nd for horticulture but were 18th and 21st respectively by meat, and 6th and 30th respectively by aquaculture.

It should also be noted that the “Don’t know” option was frequently selected in some of the highest and lowest ranked barriers, e.g., for meat “obtaining export permits/licenses” (ID10, ranked 10th, 41% “Don’t know” responses) and “Environmental sustainability product requirements in export market” (ID19, ranked 48th, 43% “Don’t know” responses) (see Table 3). This result indicates that producers may not be sufficiently familiar with these potential barriers.

Ranking of export barriers within categories

Examining export barriers from the perspective of the four categories, it is evident that most of the highest and lowest ranked barriers fall within the categories “product supply and distribution” and “the market” (see column “Cat.” in Table 3). For example, “high labor cost in Australia” has a rank of 1 and “limited product varieties/breeds available in Australia to meet export demand” was ranked 49 (last). Both barriers are classified within the “product supply and distribution” category. Similar variations of barrier rankings were found within the categories “trade regulation” and “enabling environment” but to a lesser extent. These empirical results imply that evaluation of perceived severity of export barriers by categories may not be appropriate in this case study, meaning it is not possible to determine which category of export barriers is perceived as most severe by producers. Hence, the export barrier categories should here only be considered as groups of export impediment according to a common theme.

Comparison of perceived severity of export barriers between exporters and non-exporters within each sector

Table 4 presents the barriers which exporters ranked significantly higher or lower compared to non-exporters (Table S.2 in the supplementary material provides more detailed results). The results indicated very different patterns across the three sectors.

Table 4. Statistical differences between exporter and non-exporter ratings of export barriers by agri-food sectors.

MEAT (N = 11/49)			HORTICULATURE (N = 3/49)			AQUACULTURE (N = 11/49)
ID	Barrier	t-statistic	ID	Barrier	t-statistic	ID	Barrier	t-statistic
Barriers which exporters ranked significantly HIGHER compared to non-exporters
5	Costs of meeting maximum residue limits (TR, Rank 41)	2.93***				31	Need for individual business branding for product (PSD, Rank 21)	1.70*
8	Pre-shipment inspections/ formalities (TR, Rank 33)	2.77***
14	Producers’ preference to supply the domestic market (TM, Rank 26)	1.75*
31	Available export finance/insurance options for agri-food export (PSD, Rank 34)	2.19**
36	Exporters limited understanding of business etiquette in export markets (PSD, Rank 43)	1.72*
37	Digital traceability requirements in export market (PSD, Rank 25)	1.72*
42	Insufficient capital investment for export readiness (EE, Rank 19)	2.78***
43	Insufficient capital investment at post-production level (EE, Rank 36)	2.22**
47	Limited support by industry peak bodies (EE, Rank 38)	2.14**
Barriers which exporters ranked significantly LOWER compared to non-exporters
21	Competition in export market (TM, Rank 1)	−1.69*	2	Sanitary/phytosanitary requirements (TR, Rank 11)	−1.70*	6	Technical requirements (TR, Rank 42)	−1.93*
25	Lack of consistent high-quality supply volumes (TM, Rank 14)	−1.85*	36	Exporters limited understanding of business etiquette in export markets (PSD, Rank 45)	−2.28**	9	Costs of meeting pre-shipment requitements (TR, Rank 38)	−2.15**
			40	Export freight costs (PSP, Rank 22)	−2.21**	13	Strong domestic demand for agri-food product (TM, Rank 6)	−3.91***
						14	Producers’ preference to supply the domestic market (TM, Rank 4)	−3.58***
						25	Lack of consistent high-quality supply volumes (PSD, Rank 8)	−1.65*
						29	Level of technology adoption to improve farm productivity (PSD, Rank 32)	−2.90***
						31	Available export finance/insurance options for agri-food export (PSD, Rank 31)	−1.72*
						42	Insufficient capital investment for export readiness (EE, Rank 18)	−2.06**
						43	Insufficient capital investment at post-production level (EE, Rank 16)	−1.71*
						44	Access to up-to-date market information (EE, Rank 17)	−2.32**

Notes: ‘N’ represents the total number of export barriers out of 49 for which a difference in barrier ratings between exporters and non-exporters was identified. ‘t-statistic’ refers to t-test of equality of means. * indicates significant at 10% level, ** indicates significant at 5% level, *** indicates significant at 1% level. ‘TR’ for barrier category trade regulation, ‘TM’ for barrier category the market, ‘PSD’ for barrier category product supply and distribution, ‘EE’ for barrier category enabling environment. ‘Rank’ in brackets refers to ‘Rank’ in Table 3. Barriers in bold font or italic font indicate highly ranked and lowest ranked barriers respectively overall (see Table 3). Only barriers with a significant difference in the mean score between exporters and non-exporters are presented here. More detailed results are available in Table S.2 in the supplementary material.

Meat sector

The results for the meat sector suggest that there is a relatively high number of export barriers (11 out of 49) that are perceived differently between exporters and non-exporters. Of the identified 11 disparities, the exporters perceived 9 barriers as more challenging than non-exporters (see the first column in Table 4). For example, exporting meat producers rated constraints such as “costs of meeting maximum residue limits” (ID5), “pre-shipment inspections/formalities” (ID8), and “Australian producers’ preference to supply the domestic market” (ID14) significantly higher than non-exporters of this sector. Conversely, “competition in export markets” (ID21) and “lack of consistent high-quality supply product volumes” (ID25) were perceived as significantly lower by exporters compared to non-exporters. This result suggests that there is a mismatch of the perceived severity of individual barriers among exporters and non-exporters in the Australian meat sector.

Horticulture sector

There is less variation in the perceived severity of export barriers between exporters and non-exporters in the horticulture sector (see the middle column of Table 4). There were only three barriers rated significantly less challenging by exporters compared to non-exporters, namely “sanitary/phytosanitary requirements” (ID2), “exporters limited understanding of business etiquette in export markets” (ID36), and “export freight costs” (ID40).

Aquaculture sector

The ratings between exporters and non-exporters in aquaculture also displayed noticeable differences (11 out of 49). However, the differences were dominated by exporters perceiving barriers as less challenging than non-exporters (see the third column of Table 3). For example, “strong domestic demand for agri-food product” (ID13) and “access to up-to-date market information” (ID44) among others were regarded as less challenging by exporters, while the “need for individual business/product branding/marketing” (ID32) was perceived more challenging by the exporters.

Furthermore, the results in Table 4 indicate that exporters across all three sectors tended to rate the lower ranked barriers (see rank details in brackets for each listed export barrier, corresponding with results in Table 3) higher than non-exporters. This is also the case for most barriers that exporters ranked lower than non-exporters, except a few impediments which ranked high overall (e.g., “competition in export market” ranked 1st for the meat sector, “strong domestic demand for agri-food product” ranked 6th for aquaculture). Assuming that exporters’ ratings reflect more informed evaluation and experiences with export impediments than those of non-exporters, these fundings suggest that non-exporters perceive/anticipate some export barriers to be more severe than active exporters have found them to be in practice.

Discussion

The aims for this study were to improve the understanding of the range of firm external export barriers that agri-food sectors (red meat, horticulture, and aquaculture) in Australia currently encounter, and to empirically measure and compare the perceived severity of these barriers by producers.

The findings suggested that all three Australian agri-food sectors appear to perceive similar key export impediments, namely high labor costs, market and financial risks, the lack for provenance information for branding competitiveness, and production risks. Some of these results are not surprising. For example, the challenge of high labor cost, which is related to limited labor resource (i.e., farm workers) and relatively high salary standards in Australia in international comparison (which affects the cost competitiveness of Australian producers), has been recognized as one of the key challenges to agricultural production (and subsequently export) in Australia in the past (e.g., Campbell, 2019; Martin, Randall, & Jackson, 2020; Tan & Lester, 2012). Strategies to address this issue have been implemented such as migrant and seasonal worker programs (Campbell, 2019). However, these programs have not been without issues such as poor working conditions and low wages for migrant workers (Government News, 2019; Howe, Clibborn, Reilly, van den Broek, & Wright, 2019). An increased emphasis on the deployment of automation technologies in farming systems and through agri-food supply chains may help reduce dependency on scarce human farm labor and contribute to addressing this barrier (Wu, Dawson, Fleming-Muñoz, Schleiger, & Horton, 2019). Yet, this transformation will likely require considerable research, investment, and time to be realized.

The results also showed that producers in all three sectors perceived high market and financial risks as export barriers. These could potentially be reduced by increased market differentiation (Waldron, 2020). The Australian government in collaboration with industry peak bodies may need to further support producers’ ability to access higher-value markets (e.g., through trade agreements) by helping mitigate market and financial risks.

Production risks, perceived by respondents as a key export barrier, are likely to become more severe in future due to climate change (e.g., Ghahramani & Bowran, 2018; Gunasekera, Kim, Tulloh, & Ford, 2007; Steffen, Sims, Walcott, & Laughlin, 2011). To address this risk, commitment from government and industries to mitigate climate change (e.g., carbon neutral production) is needed as well as integrated industry and regional strategies (e.g., increased resource efficiency, farming systems changes, technology, and skill development) to adapt the agri-food production sector to the challenges of climate change (Australian Government, 2013; Dowd et al., 2014).

Participants of all three sectors highlighted the lack of provenance information (ID33) to support Australian agri-food products’ competitiveness in export markets in addition to the country-of-origin labeling. This implies that value could be added to agri-food export products by providing information on producer entities, origins, and processes involved in producing or delivering the product. This finding is consistent with previous recommendations for Australian meat exports (McKinna & Wall, 2020). However, the results of the present study suggest that traceability requirements in export countries, which are closely linked to the provision of provenance information, were not considered as a major challenge at present (see Table 3). Improved provenance information could offer Australian producers a competitive advantage over suppliers from other countries in export markets. Hence, additional research is needed to identify consumers’ and importers’ perspectives on provenance information supplied for agri-food products as well as technologies to provide secure platforms to transmit and verify the accuracy of such information.

The observed variation in the perceived severity of certain export barriers across the agri-food sectors highlights the importance for assessing each industry’s export ability individually. Variation in the perceived severity of export barriers across sectors may arise due to the specific agri-food product characteristic, regulations affecting the product (e.g., sanitary/phytosanitary requirements), the level of general industry development including export readiness, peak body support, and producers’ export experience. Yet, further assessment of such inference is needed to verify these claims. For strategic and targeted export development, it remains important to assess and address trade impediments for each agri-food sector individually rather than relying on results that are aggregated across many sectors.

Furthermore, the results on differences between exporters and non-exporters (Table 3) showed that producers’ perception of export barriers differ depending on whether they were exporting or not. This was most evident for the meat and aquaculture sectors. Similar to recent findings by Akbar et al. (2020), this result may imply that there is information asymmetry present within these sectors about various export aspects which could potentially affect the export readiness of producers who currently do not export but intend to do so. Unfortunately, the collected data and sample size does not allow a more detailed investigation of these aspects (e.g., future export intentions and incentives of current non-exporters were not assessed). However, this could be scope for future research.

To address the identified information gap between exporters and non-exporters, workshops and newsletters could be offered by industry peak bodies to ensure non-exporters have sufficient information to support their decision of becoming involved in product export. Export awareness raising activities such as targeted information sharing and engagement may also be beneficial to overcome producers’ knowledge gap about other export barriers where a high proportion of ‘Don’t know’ responses was recorded (see Table 2).

The findings also suggest that environmental sustainability (ID19) and ethical/social (ID20) product requirements are currently not seen as export barriers by producers, despite globally increasing consumer awareness for sustainably and ethically produced food. This could imply that the existing product requirements in export markets may not be significantly different to the requirements in Australia, which producers are currently expected to meet within the domestic market. Yet, further verification for this assumption is needed. Given the increasing global consumer awareness and rising concern about sustainability and ethical/social aspects of food production (e.g., carbon neutrality, animal health/wellbeing, fair labor treatment), this may become a more severe export barrier in future. Trends in the demand for such food attributes in domestic and export markets should be closely monitored by agri-food sectors.

While this study identified current export barriers and the producers’ perceived severity it should be noted that other export constraints may arise in the future. These may occur with changes in consumer expectations for food attributes, production, processing, and distribution processes. Shifting demand for product volumes in export markets could also become future export barriers. Furthermore, changes in the global macro environment (e.g., political, economic, or environmental) may lead to the development of new export impediments or changes in their ranking as more or less severely perceived. Hence, agri-food sectors aiming to export their product should continue to monitor, identify, and address existing and emerging export impediments in future.

A comparison of the study results to previous literature proved difficult since assessments of impediments that have (a) their origin in the firm external environment, (b) were conducted in the context of agri-food products, and (c) cover a large range of impediments within and across sectors which has previously not been undertaken.

A limitation of this study is the sample size used for analysis. While there are no statistics available about the exact population size of producers in all three Australian agri-food sectors, it can be assumed that the sub-samples (i.e., 51, 48, 47 observations respectively) are relatively small compared to the population in the respective sectors. Yet, a sample size of 30 is usually considered as sufficiently large to approximate a normal distribution of means within a population (i.e., the central limit theorem (Kwak & Kim, 2017; e.g., Ross, 2017)). Since this threshold is met by the size of the collected sub-samples, the robustness of the results shown in Table 2 are likely not affected by a sample size bias. However, the validity of result for the analysis of difference between exporters and non-exporters ratings of export barriers by agri-food sector (Table 3), for which the sub-sample is less than 30 observations (Table 2), may be compromised. Therefore, these results should be interpreted with caution.

In addition, the timing at which the survey was conducted may also have affected the empirical results. For example, data collection for this study took place (in June 2021) during the COVID-19 pandemic that severely affected Australian agri-food exports (e.g., through increasing protectionism in export countries, concern about food safety and supply chain transparency by importers, labor shortage) (Greenville, McGilvray, & Black, 2020; Martin et al., 2020; Snow et al., 2021). These extraordinary circumstances may be reflected in the survey responses (e.g., high ranking of lack of infrastructure such as logistics and flights, lack of labor resource). Furthermore, significant trade tensions between China and Australia were eminent at the time of data collection, which may have contributed to the very high ranking of market risks.

Although focus group interviews were conducted to validate the identified export barriers, some of the impediments may have been conflated by the participants in the CATI survey due to their perceived similarity (e.g., market risks (ID22), financial risks (ID23)) or due to causation among the barriers (e.g., high labor costs (ID28) and limited labor resources (ID27)). However, no evidence for this was available from the survey responses.

In this study a descriptive approach was chosen to gain an improved understanding about the range and categories of export barriers and to measure the severity of these impediments. This approach does not provide information about cause and effect for export barriers which was beyond the scope of this study.

Further research in this area may include an analysis of firm internal export barriers such as the relationship between the characteristics of individual agri-food businesses and producers’ rating of export barriers. Future research could also assess the relationship between the agri-food businesses’ perceived export barriers and their current export performance. Furthermore, the agri-food sectors should continue to assess the importance of agri-food attributes (e.g., environmental sustainability product requirements) and explore potential emerging agri-food attributes which could provide Australian producers a competitive advantage in export markets.

Conclusion

The overall objective of this study was to improve the understanding about the range and categories of export barriers that Australian agri-food producers (red meat, horticulture, and aquaculture) encounter.

The study offered a large compendium of potential external export barriers and showed that some of the most and least challenging export impediments were shared by the three agri-food sectors, while variation also existed across sectors. In addition, there were some significant differences between exporters and non-exporters in their perceived severity of some export barriers within each sector. These findings offer the basis for addressing barriers to export and facilitating international trade of agri-foods which will require active efforts from many parties. For example, the findings suggest that governments and peak industry bodies could play key roles in addressing the identified export impediments. Leadership by industry peak bodies is vital in representing the interests of their individual agri-food sector internationally and domestically to strengthen their competitiveness. It will also be important to improve the awareness of non-exporters about the barriers through activities including workshops and the provision of information on markets and export processes and regulatory aspects. Furthermore, industry peak bodies and the Australian government will need continued collaboration in gaining improved access to existing and new agri-food export markets (e.g., via lower tariffs, free-trade agreements).

The developed compendium of export barriers (Figure 1) and the empirical methods presented in this study may assist other agri-food producing industries by providing a framework for assessing export impediments. The empirical methods can also be used as a benchmarking tool to track changes to the range of impediments and their perceived severity over time. This can offer a basis for decisions that facilitate increased trade volumes, income generation, and economic growth in agri-food producing countries and opportunities to improve food security and choice in importing countries.

Disclosure statement

No potential conflict of interest was reported by the author(s).