https://doi.org/10.52973/rcfcv-e34394
Received: 20/02/2024 Accepted: 18/03/2024 Published: 25/06/2024
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Revista Científica, FCV-LUZ / Vol. XXXIV, rcfcv-e34394
ABSTRACT
This study aimed to conduct an economic analysis of enterprises
involved in Pearl Mullet shing in Lake Van. The primary data source
for this study was information gathered from 72 shing enterprises
actively engaged in Pearl Mullet shing in Lake Van. Besides the
economic analysis of these enterprises, the factors inuencing sales
income were estimated using multiple linear regression analysis. It
was observed that fuel and oil expenses were the highest, followed
by labor expenses and net expenses among the cost components
within these enterprises. According to the regression analysis, fuel
and oil costs, labor costs, net costs, and other costs were statistically
signicant (P<0.05). Consequently, the establishment of a sh market
in the study area, the implementation of measures to facilitate the use
of SCT–free diesel oil, the construction of suitable boatyards for boat
maintenance and repair, and the formation of a robust organization
are believed to have a positive impact on the sales revenues and
protability of these enterprises.
Key words: Protability; cost; regression analysis; sheries; lake Van
RESUMEN
Este estudio tuvo como objetivo realizar un análisis económico de las
empresas involucradas en la pesca del pez salmonete perla en el Lago
Van. La fuente principal de datos para este estudio fue la información
recopilada de 72 empresas pesqueras que participan activamente en
la pesca del pez salmonete perla en el lago Van. Además del análisis
económico de estas empresas, estimamos los factores que inuyen
en los ingresos por ventas mediante un análisis de regresión lineal
múltiple. Se observó que los gastos de combustible y lubricantes
fueron los más altos, seguidos por los gastos laborales y los gastos
de redes de pesca, entre los componentes de costos dentro de estas
empresas. Según el análisis de regresión, los costos de combustible
y lubricantes, costos laborales, costos netos y otros costos fueron
estadísticamente significativos (P<0,05). En consecuencia, se
cree que el establecimiento de un mercado de pescado en el área
de estudio, la implementación de medidas para facilitar el uso de
gasóleo libre de SCT, la construcción de astilleros adecuados para el
mantenimiento y reparación de embarcaciones y la formación de una
organización sólida han tenido un impacto positivo en los ingresos
por ventas y la rentabilidad de estas empresas.
Palabras clave: Rentabilidad; costo; análisis de regresión; pesca;
lago Van
Economic analysis of enterprises shing Pearl Mullet
(Alburnus tarichi Guldenstaedtii, 1814) in Lake Van
Análisis económico de la pesca de salmonete perla
(Alburnus tarichi Guldenstaedtii, 1814) en el lago Van
Ömer Gezginç
1
* , Yavuz Cevger
2
1
Ankara University, Institute of Health Sciences, Department of Animal Health Economics and Managements. Ankara, Türkiye.
2
Ankara University, Faculty of Veterinary Medicine, Department of Animal Health Economics and Managements. Ankara, Türkiye.
*Corresponding Author: omergezginc@gmail.com
FIGURE 1. Map of the study area
Economic analysis of fishing enterprises in Lake Van / Gezginç and Cevger ________________________________________________________
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INTRODUCTION
In the World, the aquaculture sector has become one of the most
developed sectors due to the increasing population and the demand for
animal products [1, 2]. This sector plays a signicant role in promoting
human health, nutrition, and employment in various countries. In
Turkey, the aquaculture sector has also witnessed rapid and effective
development, contributing to human health and nutrition [2, 3].
Turkey, surrounded by seas on three sides, holds a strategic position
in aquaculture due to its abundant rivers, dams, lakes, and ponds [4,
5]. Among these water resources, Lake Van stands out as Turkey’s
largest lake, covering an area of 3712 km
2
, with an average depth
of 171 m and a maximum depth of 451 m (FIG. 1). Lake Van is a lake
surrounded by the provinces of Van and Bitlis. This lake is renowned
as the world’s largest alkaline lake – it’s a saline soda lake–, offering
a pH level of 9.7–9.9 and a salinity of approximately 0.22%. Pearl
Mullet (Alburnus tarichi) is the only species that can live in Lake Van;
it has this unusual water feature, is economically important and is
shed [6, 7]. Pearl Mullet is recognized as an endemic species with
a declining population trend [8].
In Lake Van, the Pearl Mullet shing season spans nine months, with
a shing prohibition from April 15th to July 15th, coinciding with the
sh’s breeding period. During this timeframe, Pearl Mullet migrate
to the freshwater rivers that ow into Lake Van. These migrations
occur when the water temperature in the rivers reaches 13°C, and
when an ion balance between the lake and the river is established.
The broodstocks, responsible for egg–laying, return to the lake during
this process [6]. This reverse migration, against the river’s current,
also creates a visually stunning spectacle.
In Turkey, the total quantity of aquaculture products harvested from
inland waters in 2022 amounted to 33,256 tonnes, with a Pearl Mullet
catch totaling 9,991 tonnes [9]. Based on these statistics, Pearl Mullet
shing accounted for 30% of the total catch from inland waters in
Turkey. In this respect, Pearl Mullet shing is an important source of
livelihood for people living in rural areas on the shores of lakes, and it
has touristic and ecological importance because of the visual feasting
it creates during its migration to fresh water, which is necessary for
breeding biology in Pearl Mullet. With these characteristics, Pearl
Mullet has serious economic potential in the Lake Van basin.
The social and economic aspects are of equal importance alongside the
conservation and development of Pearl Mullet stock. The Mediterranean
General Fisheries Commission has emphasized the signicance of
socioeconomic data for effective sheries management policies [10].
In the aquaculture sector, enterprises must consistently monitor their
annual production costs to optimize benets while minimizing expenses
through the utilization of production factors [11]. Previous research has
examined the socioeconomic and technical aspects of Pearl Mullet
shing in Lake Van [12, 7]. This study represents the rst comprehensive
analysis of the economic aspects, including cost and protability, of
enterprises engaged in Pearl Mullet shing in Lake Van.
The primary objective of this study was to conduct an in–depth
economic analysis, including cost and protability assessment of the
enterprises involved in Pearl Mullet shing in Lake Van. Additionally,
the study aimed to determining the problems related to the sector,
to solve these problems and to present recommendations regarding
economic policy measures that can be taken in the development of
this branch of production.
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MATERIAL AND METHODS
The primary dataset for this study comprises information from
a total of 72 fishing enterprises. Among these, 11 are located in
Bitlis, while 61 are in Van. These enterprises hold Fisheries License
Certicates issued by the Provincial Directorates of Agriculture and
Forestry in Bitlis and Van and are actively engaged in Pearl Mullet
shing in Lake Van. Data regarding the shing activities of these
enterprises during the 2020–2021 and 2021–2022 seasons were
collected using the complete census method [13].
In terms of scale, the grouping of the shing enterprises included in
the scope of the research was within the scope of “small–scale shing
enterprises”. In the literature on the denition of small–scale sheries,
a general denition of the subject has not yet been put forward. The
Food and Agriculture Organization of the United Nations (FAO) has
acknowledged that numerous factors, including vessel structure, size,
shing gear, technology, and seasonality, prevent the establishment of
a universal denition for small–scale shing [14]. Nevertheless, in many
studies on this topic, a boat length of 12 m has been used as a reference
point for classifying small–scale sheries [15, 16]. Consequently, in
this study, shing enterprises were categorized into two groups:
those with a vessel length of 12 m or less (34 enterprises) and those
with a vessel length exceeding 12 m (38 enterprises). This approach
was adopted to facilitate comparable analysis results by ensuring a
relatively balanced distribution of enterprises between the two groups.
The data collected were analyzed and assessed based on the
categories established according to boat lengths. This analysis was
conducted using SPSS Statistics Version 25 (IBM Corp. Released
2017, IBM SPSS Statistics for Windows 25.0. Armonk, NY: IBM Corp.)
and Microsoft Excel. The data were scrutinized and evaluated with
reference to these boat length categories. During the data evaluation
process, descriptive statistics, including percentage, mean, and
standard deviation values, were employed.
The factors inuencing the sales income of enterprises engaged
in Pearl Mullet shing in Lake Van were determined through multiple
linear regression analysis. The sales revenue function model was
constructed with the entry method. Before applying these models, the
assumptions of multiple linear regression, including linearity, normal
distribution, zero mean of error terms, constant variance, absence of
autocorrelation, and absence of multicollinearity among independent
variables, were thoroughly assessed. As all these conditions were
satised, the models were considered appropriate for analysis.
Within the framework of these approaches, the regression equation
for the sales revenue function model was formulated as follows:
Y=b
0
+b
1
X
1
+b
2
X
2
+b
3
X
3
+b
4
X
4
+ɛ
○ Y = Pearl Mullet Sales Revenue (dependent variable),
○ X
1
= Fuel and Oil Costs: Diesel and motor oil expenses for Pearl
Mullet shing in ₺ (Turkish Lira),
○
X
2
= Labor Costs: Expenses for family labor force and foreign
labor force in ₺,
○
X
3
= Net Costs: Expenses for nets used in Pearl Mullet shing in ₺,
○
X
4
= Other Costs: Expenses like provisioning, clothing, loan
interest, reel and boat maintenance and repair, co–operative
dues, fees, visa renewal, transport, etc. in ₺,
○ ɛ = Error Term
It is important to note that a strong correlation between
independent variables is not desirable. A high correlation between
independent variables can indicate the presence of multicollinearity,
and when the correlation value is 0.90 or higher, it suggests a serious
multicollinearity problem. The correlation between independent
variables should not be 0.90 or greater [17, 18]. The Durbin–Watson
value was used to evaluate the autocorrelation status, and a value
between 1.5 and 2.5 indicated that there was no autocorrelation [19].
RESULTS AND DISCUSSION
The proportional distributions of the cost components comprising
the expenses in the enterprises involved in Pearl Mullet shing in
Lake Van are displayed in TABLE I. Meanwhile, TABLE II provides
the average values of these cost components. Additionally, TABLE
III presents the average values of the sales revenues, expenses, and
net prot / loss for these enterprises.
Upon reviewing TABLE I, it becomes apparent that fuel and oil expenses
ranked as the highest, followed by labor expenses in the second position,
and netting expenses in the third position, for both shing seasons.
When considered in terms of groups, fuel and oil costs exhibited a similar
pattern in both groups. However, labor costs were lower in the enterprises
with a vessel length of 12 m or less compared to the other group.
TABLE I
Proportional Distribution of Expense Items
Composing Costs in Enterprises by Groups
Cost Elements
Fishing
Season
Enterprises
with ≤ 12 m
boat length
Enterprises
with > 12 m
boat length
General
% % %
Fuel and Oil Costs
2020–2021 31.6 30.4 30.9
2021–2022 39.3 37.0 38.1
Labor Costs
2020–2021 27.8 32.0 30.1
2021–2022 24.8 30.0 27.6
Ration Costs
2020–2021 5.3 5.7 5.5
2021–2022 6.1 5.9 6.0
Clothing Costs
2020–2021 1.0 0.9 1.0
2021–2022 0.9 1.0 0.9
Net Costs
2020–2021 17.9 15.3 16.5
2021–2022 13.5 12.6 13.0
Loan Interest
2020–2021 4.6 4.1 4.3
2021–2022 4.5 3.6 4.1
Reel (Purse Seine)
Costs
2020–2021 0.4 0.4 0.4
2021–2022 0.3 0.4 0.3
Other Costs
2020–2021 0.8 1.1 1.0
2021–2022 0.5 0.7 0.6
Depreciation Costs
2020–2021 4.4 3.8 4.1
2021–2022 4.0 3.6 3.8
Boat Maintenance
and Repair Costs
2020–2021 2.7 3.1 2.9
2021–2022 2.6 2.0 2.3
General Administration
Costs
2020–2021 3.5 3.2 3.3
2021–2022 3.5 3.2 3.3
Economic analysis of fishing enterprises in Lake Van / Gezginç and Cevger ________________________________________________________
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There was an 8% rise in the proportional distribution of fuel and
oil costs within the cost components compared to the previous
season. This increase in fuel and oil expenses can be attributed to
the impact of various factors, including the Covid–19 pandemic, the
Russia–Ukraine war, and the signicant surge in oil prices resulting
from unfavorable developments in the Turkish economy. Although
there have been uctuations in all other cost items apart from fuel
and oil costs, they have not seen signicant changes. Compared with
those of the other groups, the labor costs of the enterprises with a
boat length of 12 m or less were lower. This difference may be due
to the difference in the daily wage amounts between the groups.
The ndings of various studies conducted by Reddy [20], Ünal
[21], Rad and Delioğlan [22], Luong [23], Taşdan et al. [16], Doğan
and Gönülal [24], Cambiè et al. [25], Cesur et al. [26], Guillen and
Maynou [27], Sangün et al. [28], Güngör et al. [29], Agbebi et al. [30],
Birkan and Öndes [31], Ashley–Dejo and Adelaja [32] consistently
indicate that fuel and oil costs constitute the largest portion of the
cost elements. Consequently, it is evident that these studies align
with the ndings of the study.
The studies conducted by Üze [33], Inoni and Oyaide [34], Coşkun
[35], Peixer and Maroni Neto [36], Çeliker et al. [37], Doğan [38], and
Çeliker et al. [39] have consistently identied labor costs as having
the most signicant share among the cost elements that comprise
the overall cost. These ndings are inconsistent with the study. The
reason for this difference may be that the prices of fuels and labor
vary according to region and year. The variation in costs could also be
attributed to the utilization of diesel without SCT (special consumption
tax). This factor may have an inuence on the overall cost structure
and contribute to differences in expenses observed in various studies.
In TABLE II it can be seen that during the 2020–2021 season, the
expenses were ranked as follows: Fuel and oil costs came in rst
at ₺50,733.06 (€5,684.3). Labor costs ranked second at ₺49,411.11
(€5,536.2). Net costs were in the third position at ₺27,026.39 (€3,028.1).
In the 2021–2022 season, the expense ranking was as follows: Fuel
and oil costs remained in the top position with ₺98,574.44 (€11,044.6).
Labor costs came second at ₺71,441.67 (€8,004.56). Net costs ranked
third with ₺33,638.89 (€3,796.9). When comparing the two groups,
it is notable that labor costs were lower in enterprises with a vessel
length of 12 m or less compared to the other group.
In a study conducted on fisheries in the Marmara Sea, it was
determined that the average fuel cost was the highest at €8,540,
and the average labor cost was the second highest at €7,976 [29]. The
outcomes from this study are consistent with the results mentioned.
However, it is worth noting that the average values of labor and fuel
costs in the studies conducted by Aksoy and Koç [40], Güngör et al.
TABLE II
Mean Values of the Cost Elements of the Enterprises at the Group Level (₺)
Cost Elements
Fishing
Season
Enterprises
with ≤ 12 m
boat length
Enterprises
with > 12 m
boat length
General
Fuel and Oil Costs
2020–2021 49,327.94 51,990.26 50,733.06
2021–2022 98,502.35 98,638.95 98,574.44
Labor Costs
2020–2021 43,350.00 54,834.21 49,411.11
2021–2022 62,026.47 79,865.79 71,441.67
Ration Costs
2020–2021 8,327.94 9,684.21 9,043.75
2021–2022 15,408.82 15,600.00 15,509.72
Clothing Costs
2020–2021 1,611.62 1,583.68 1,596.88
2021–2022 2,215.29 2,628.68 2,433.47
Net Costs
2020–2021 27,885.29 26,257.89 27,026.39
2021–2022 33,773.53 33,518.42 33,638.89
Loan Interest
2020–2021 7,147.06 7,105.26 7,125.00
2021–2022 11,227.94 9,717.11 10,430.56
Reel (Purse Seine)
Costs
2020–2021 700.00 627.89 661.94
2021–2022 808.82 953.95 885.42
Other Costs
2020–2021 1,207.35 1,780.79 1,510.00
2021–2022 1,368.62 1,822.37 1,608.10
Depreciation Costs
2020–2021 6,833.33 6,496.49 6,655.56
2021–2022 10,127.45 9,464.91 9,777.78
Boat Maintenance
and Repair Costs
2020–2021 4,242.65 5,361.84 4,833.33
2021–2022 6,441.18 5,585.53 5,989.58
General Administration
Costs
2020–2021 5,440.07 5,512.82 5,478.47
2021–2022 8,653.55 8,542.83 8,595.12
₺: Turkish Lira
TABLE III
Mean Sales Revenue, Costs, and Net Prot/Loss Values of Enterprises
Enterprises
Sales Revenue (₺) Cost (₺) Net Prot / Loss (₺)
2020–2021 2021–2022 2020–2021 2021–2022 2020–2021 2021–2022
Enterprises with ≤
12 m boat length
240,661.76 414,411.76 154,867.37 249,127.56 85,794.39 165,284.20
Enterprises with >
12 m boat length
260,921.05 430,657.89 170,116.94 264,888.53 90,804.11 165,769.36
General
251,354.17 422,986.11 162,915.76 257,445.85 88,438.41 165,540.26
₺: Turkish Lira
[41] do not align with the ndings of the present study, indicating
some disparity in cost patterns across these different researches.
The reason for this inconsistency may be that the prices of the cost
elements that make up the shing costs vary according to year and
region. It is also thought that the use of SCT–free diesel oil is effective
because of the difference in fuel costs.
For the 2020–2021 shing season (TABLE III), the average sales
revenue amounted to ₺251,354.17 (€28,163), while the average cost was
₺162,915.76 (€18,254), resulting in an average net prot of ₺88,438.41
(€9,909). In the 2021–2022 shing season, the corresponding gures
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were as follows: Average sales revenue: ₺422,986.11 (€47,393), Average
cost: ₺257,445.85 (€28,845), Average net prot: ₺165,540.26 (€18,548).
When comparing the two shing seasons covered in the study,
it is evident that there was an increase in the average values of
sales revenue, cost, and net profit. This increase amounted to
approximately 2 times for average sales revenue and average net
prot, while it was approximately 1.5 times for average cost, between
the two period of years studied. The primary factor contributing to
the rise in average cost is believed to be the increase in fuel prices.
On the other hand, the increase in average sales revenue and average
net prot is attributed to higher sales prices for Pearl Mullet and an
increased catch volume compared to the previous season. While
the sales price was high, the increase in catch volume increased
sales revenue and net prot. Furthermore, these three parameters
exhibited an increase in values as the length of the vessels increased.
In a study on sheries in the Aegean Sea, the average annual gross
prot of enterprises was reported as €8,757 [31], which is notably like
to the value observed in the 2020–2021 season of the current study.
However, when examining average net prot, average income, and
average cost in studies conducted by Dağtekin [42], Üze [33], Çeliker
et al. [37], Çeliker et al. [39], Coşkun [35], Taşdan et al. [16], Cesur et
al. [26], Doğan [38], Dartay et al. [43], Güngör et al. [29], and Güngör et
al. [41], they appear to be inconsistent with the ndings of this study.
These differences could be attributed to various factors, including
regional variations, methodological distinctions, and time–specic
circumstances. This inconsistency may be due to differences in the
economic value of the sh caught, the amount of sh caught and the
associated costs according to the year, the differences in the shing
areas, and the differences in the shing technology and methods used.
The outcomes of the nancial protability and economic ratios of
the enterprises can be found in TABLE IV.
season. However, in the following shing season, it was determined
that both groups of enterprises achieved a similar level of success.
Based on the data from the Central Bank of the Republic of Turkey
(CBRT), the average interest rate on time deposits was 16.42% in
the 2020–2021 shing season and 22.92% in the 2021–2022 shing
season [44]. It was observed that the nancial protability rates in
this study exceeded the time deposit interest rates during these
periods. Therefore, it can be concluded that Pearl Mullet shing in
Lake Van was a protable economic activity during these periods.
When considering the alternative cost of capital, it is also possible to
assert that an income exceeding the alternative cost was obtained.
The average nancial protability value of 40.4% reported by
Rad and Delioğlan [22] in their study on the economic situation of
Taşucu trawlers is consistent with the ndings of the present study.
Additionally, in a study conducted by Çeliker et al. [39] on shermen
in the Aegean Sea, the average nancial protability was determined
to be 32.43%. These gures are in line with the nancial protability
values observed in this study, suggesting some degree of similarity in
the economic performance of the enterprises across these different
studies. While these values are like to the values in this study for the
2020–2021 season, they were found to be incompatible with the values
for the 2021–2022 season. In various studies conducted by different
researchers, varying levels of average nancial protability were
observed among shermen in different regions: Çeliker et al. [37]
found an average nancial protability of 9.61% among shermen
in the Black Sea region. Coşkun [35] reported an average nancial
protability of 17.9% in Sinop province. Üze [33] determined an
average nancial protability of 5.99% in Kastamonu. These results
illustrate the diversity in economic performance and protability
among shermen in different geographical areas and contexts. These
values were not consistent with the study. This incompatibility may
arise from differences in shing areas, economic values of hunted
species, net prots, equity capital of enterprises, and shing seasons.
Within the scope of the research, economic ratios above 1 serve
as indicators of protable operation for enterprises engaged in Pearl
Mullet shing in Lake Van. The results of the regression analysis are
presented in TABLE V.
As per the information in TABLE V, the adjusted R² value was
calculated to be 0.909. This value signifies that approximately
90.9% of the variation in the dependent variable within the model
is accounted for by the independent variables, while the remaining
9.1% can be attributed to variables not incorporated into the model.
Additionally, the Durbin–Watson value for this model was recorded as
1.912. Since this value falls within the range of 1.5–2.5, it suggests that
there is no autocorrelation present in the model. When P values were
examined, fuel and oil costs, labor costs, net costs and other costs
were found to be signicantly different at the P<0.05 level. According
to the production function model for all enterprises, the estimated
equation for Y= Total Pearl Mullet Sales Revenue is as follows:
Y = 20937.565 + 2.231X
1
+ 1.021X
2
+ 1.019X
3
+ 1.240X
4
+ ɛ
According to regression analysis, the relationship between the
dependent variable, total Pearl Mullet sales revenue (Y), and the
independent variables in the estimated model equation was found
to be in the predicted direction. In a study on sheries in Zonguldak
province, regression analysis was conducted, with gross revenue
as the dependent variable and diesel fuel costs, engine power, and
the number of days spent at sea as independent variables. It was
determined that there was a signicant relationship between gross
TABLE IV
Mean Values of the Financial Ratio and Economic
Ratio of the Enterprises (Mean ± SD)
Enterprises
Financial Rationality Rate of Economization
2020–2021 2021–2022 2020–2021 2021–2022
Enterprises with ≤
12 m boat length
32.56 ± 8.67 42.16 ± 11.96 2.19 ± 0.67 1.87 ± 0.30
Enterprises with >
12 m boat length
34.50 ± 9.37 41.53 ± 8.50 2.03 ± 0.51 1.84 ± 0.26
General 33.59 ± 9.04 41.83 ± 10.21 2.10 ± 0.59 1.86 ± 0.27
Based on the data presented in TABLE IV, regarding nancial
protability, during the 2020–2021 shing season, it was greater in
the enterprises with a boat length exceeding 12 m compared to the
other group. However, in the 2021–2022 shing season, the values
were relatively similar between the two groups. In terms of economic
ratios, it was observed that the values in both groups were quite
comparable in both shing seasons.
The average nancial protability, which represents the protability
of equity capital, indicated that enterprises with a boat length
exceeding 12 m performed more successfully than those with a boat
length of 12 m or less, with a 2% difference in the 2020–2021 shing
Economic analysis of fishing enterprises in Lake Van / Gezginç and Cevger ________________________________________________________
6 of 8
revenue and diesel fuel costs at the P<0.05 level. This nding aligns
with the observation of a signicant relationship between gross
revenue (income from sh sales) and fuel costs [40].
Several issues were identied during the study that had an adverse
impact on the protability of the enterprises. These problems include:
a) Owners’ inability to inuence price determination, as they commence
the season in debt to brokers. b) Insuciencies in both quantity and
quality regarding organization. c) Inability of the enterprises to take
advantage of SCT–free diesel oil support. d) Absence of suitable dry
docks for boat maintenance, repairs, and modications.
At the start of the season, the fish prices remain low because
enterprise owners cannot influence price determination due to
their indebtedness to brokers. This negatively impacts enterprise
protability. Establishing a local sh market and promoting collaborative
efforts among shermen are considered effective strategies to enable
enterprise owners to have more inuence over prices.
It was observed that enterprise owners involved in Pearl Mullet
shing do not benet from the use of SCT–free fuel, a benet also
provided by the Ministry of Transport and Infrastructure for shing
vessels. During the eld research revealed that they face challenges
in utilizing this support due to bureaucratic complexities and high
associated costs. This situation results in increased enterprise
expenses and reduced protability. It is believed that streamlined
procedures, implemented by competent authorities to facilitate
shing vessels’ access to SCT–free diesel oil, will have a positive
impact on enterprise protability.
Due to the lack of suitable dry docks for the maintenance and
repair of boats, the maintenance and repair costs increase when
construction machinery is used to tow boats to land. It is believed that
the construction of suitable towing places by competent authorities
will have a positive impact on enterprise protability.
CONCLUSION AND IMPLICATIONS
Based on the results of nancial protability and economic ratios,
it has been ascertained that Pearl Mullet shing in Lake Van is a
nancially viable activity. In this regard, it is believed that Pearl Mullet
shing plays a crucial role in generating employment opportunities
in the rural areas surrounding the lake and curbing the migration
of young populations from rural to urban areas. Apart from these
signicant contributions, it is also considered of utmost importance
to prioritize the conservation of the declining population of Pearl
Mullet to ensure the sustainability of this shing activity.
It has been ascertained that the shing enterprises examined had
similar values in different variables (such as cost elements, sales
revenue) depending on their vessel sizes. This situation offers production
posibility through shing for both enterprises with a vessel length of 12
m or less, and businesses with a vessel length exceeding 12 m.
The establishment of a fish market in the study region, the
simplification of procedures for SCT–free diesel oil usage, the
construction of appropriate boat docks for maintenance and repair,
and the establishment of a robust organization are believed to have
a positive impact on sales revenues and enterprise protability.
Conict of interest statement
The authors declare that they have no conict of interest
ACKNOWLEDGEMENTS
This study is produced from the doctoral thesis of the rst author,
Ankara University, Instıtute of Health Sciences, Department of Animal
Health Economics and Managements. Ankara, Turkey.
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TABLE V
Results of Regression Analysis According to the Production Function Model of Pearl Mullet Sales Revenue in Enterprises
Variables
Non–Standardized Standardized
t Value Sig. (P)
Collinearity Statistics
B Beta (β) Beta (β) Tolerance VIF
Fixed 20937.565 9545,246 2.194 0.030
Fuel and Oil Costs 2.231 0.145 0.586 15.407 0.000 0.437 2.286
Labor Costs 1.021 0.116 0.262 8.839 0.000 0.719 1.392
Net Costs 1.019 0.315 0.099 3.236 0.002 0.683 1.463
Other Costs 1.240 0.251 0.189 4.942 0.000 0.433 2.308
R² Adjusted R² Durbin–Watson
0.912 0.909 1.912
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