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Osmani, M., Kolaj, R., Borisov, P. & Arabska, E. (2021).Competitiveness between figures and metaphors; are farm-ers' apple producers enough competitive? Bulg. J. Agric. Sci., 27 (Suppl. 1), 31-43 There is a growing concern over competitiveness everywhere, especially among farmers'. The research focuses on the competitiveness or ability to compete of small farmers' apple-producers in the Dibra region, in Albania. Its purpose is to assess the level of competitiveness of farmers' and to identify major factors that determine this level. Primary data obtained through direct observation of farmers' and statistical methods such as groupings, descriptive statistics, graphs, and statistical methods such as non-parametric correlation were used to conduct the research. To analyze the competitiveness, we use the data on the difficulties and problems that farmers' face while selling their produce. The study reveals a very low ability to compete, and major reasons for this are unfair competition and the functioning of the market, high costs of production and marketing, lack of state support, especially for the use of quality inputs and price subsidies, very limited resources to obtain loans for capital investment and working capital, but to some extent also because of the reduced the negotiating power due to lack of information and lack of collective action. Finally, some political implications along the lines of results provided by the study have been outlined, in order to enhance the farmers' ability to compete.
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Bulgarian Journal of Agricultural Science, 27 (Suppl. 1) 2021
Agricultural Academy
Competitiveness between figures and metaphors; are farmersapple
producers enough competitive?
Myslym Osmani1, Rezear Kolaj1*, Petar Borisov2 and Ekaterina Arabska3
1Agricultural University of Tirana, Faculty of Economics and Agribusiness, 1029 Tirana, Albania
2Agricultural University, Department of Management and Marketing, Faculty of Economics, 4000 Plovdiv, Bulgaria
3University of Agribusiness and Rural Development, Faculty of Economics and Management, 4003 Plovdiv,Bulgaria
*Correspondinga uthor:,
Osmani, M., Kolaj, R., Borisov, P. & Arabska, E. (2021).Competitiveness between gures and metaphors; are farm-
ersapple producers enough competitive? Bulg. J. Agric. Sci., 27 (Suppl. 1), 31–43
There is a growing concern over competitiveness everywhere, especially among farmers’. The research focuses on the
competitiveness or ability to compete of small farmers’ apple–producers in the Dibra region, in Albania. Its purpose is to assess
the level of competitiveness of farmers’ and to identify major factors that determine this level. Primary data obtained through
direct observation of farmers’ and statistical methods such as groupings, descriptive statistics, graphs, and statistical methods
such as non–parametric correlation were used to conduct the research. To analyze the competitiveness, we use the data on the
difficulties and problems that farmers’ face while selling their produce. The study reveals a very low ability to compete, and
major reasons for this are unfair competition and the functioning of the market, high costs of production and marketing, lack
of state support, especially for the use of quality inputs and price subsidies, very limited resources to obtain loans for capital
investment and working capital, but to some extent also because of the reduced the negotiating power due to lack of informa-
tion and lack of collective action. Finally, some political implications along the lines of results provided by the study have been
outlined, in order to enhance the farmers’ ability to compete.
Keywords: competitiveness;cost; competition;marketing;state support; agriculture
Topic.The horticulture in Albania occupies an import-
ant and growing place in agricultural production. One of
the important agricultural crops is apples,whose production
volume varies approximately between 70 000–80 000 tons/
year. Dibra region in north–eastern of Albania ranks second
in the country (MARD, 2014) for apple production. Dibra
has more than 500 000 apple trees planted in more than 460
ha that include Golden, Starking and Granny Smith varieties
(Freshplaza, 2018).Based on the appropriate climatic–soil
characteristics the development of horticulture in the area
has been traditionally prominent. Apple growing has been
of great relevance compared to other cultivars and is among
main important fruits for farmers’ in Albania (Spornberger
et al., 2014).
The increase of apple production has come from the
increase of planted areas, but also from the increase of the
productivity(FAOSTAT, 2018).The growth of the latter has
been influenced by the use of cultivars and new technologies
and the increased use of chemical fertilizers, stimulants and
various additives. Moreover, the increasing effects of con-
centration and the specialization of farmers’ and agricultural
service providers, has led to improved technical assistance
and methods followed, since tillage and up to post–harvest
and treatment and storage of the product. There is a positive
32 Myslym Osmani, Rezear Kolaj, Petar Borisov and Ekaterina Arabska
relation between productivity in agriculture and complemen-
tarity effects across farm outputs with tendency of scales
economy and overall specialization (Kim et al., 2012).
However, the increase in apple production emphasizes
the growing need for functional–markets–sales, which often
have not been able to absorb the entire supply, leading to un-
realized incomes and increasing financial losses of farmers’.
The reasons for these developments affect a range of com-
plex issues because of their multiplicity and interdependence.
They can be related with the farmer or the farm structure,
but also with functioning of markets, pursued economic–
agricultural and trade policies, especially with the business
climate and the environment in the agricultural sector. The
changing structure of agriculture in developed countries has
been linked to technology, economy and wide market forces
and governmental policies(Huffman et al., 2000).
Thesis.In the conditions of a complex situation of growth
of domestic production, which corresponds to a large num-
ber of farmers’ engaged in sales in an unintegrated and un-
certain market,farmers’ in the Dibra region tend to realize
about 10,000–12,000 tons of apples/year and the spectrum of
local farmers’ difficulties in the sales realization process can
be considerable. These sales difficulties can also be under-
stood as a weak competitive ability or deteriorating of farm-
ers’ apple–producers. According to Latruffe (2010)with the
competitiveness can understand the ability of farms to sell
products that meet demand in terms of price, the quality and
the quantity and at the same time provide timely benefits.
Difficulties in sales or poor farm competitiveness repre-
sent a problem that is associated not only with the financial
aspect of the farm activity and multifaceted impacts. The
most evident consequence of the low ability to compete is
the deteriorating standard of living of thousands of small
farmers’ households and schooling opportunities for their
children, as well a restricted capacity to invest in new farm
technology and know–how, storage and post–harvest tech-
nology as well as paying for better advisory services, etc. On
the other hand, these developments have damaged function-
ing of this market segment, causing losses of a large number
of urban consumersa nd as Lanfranchi points out, without
neglecting the economic consumer variables the process of
purchase implies a series of aspects linked to the individual’s
culture and identity (Lanfranchi et al., 2016). Consumers are
accustomed to looking for ‘the apple of Dibra’ in the market,
they are accustomed to buy traditionally this regional ‘dif-
ferentiated–product’1and in this context ‘urban consumers
1 By Sharp et al. (2010), “dierentiated product” is a product with
incremental value in the market which is determined by its specic
attributes that distinguish it from other products.
make up an important electorate’(Röling et al., 2007).
Research problem. Although in general economic wis-
dom has defined a wide range of factors that can play a role
in the competitiveness of farms in the Albanian context,
especially in the regional context, the concrete factors that
may have a role, as well as their relative or comparative
importance has remained unknown. This is a knowledge
gap that needs to be filled, and it constitutes the research
problem. Effective policy implications and measures could
be developed to enhance small apple farmers’ ability to
compete inspired by new knowledge obtained through the
Purpose. The purpose of this research is to evaluate the
level of competitiveness, as well as to identify factors (in
their current conditions) that are affecting farms in the case
of apple–producing farmers’ in north–eastern Albania in the
Dibra region.
Research questions
Questions intended to receive a response through
this research are:
Are farmers’ apple–producers enough competitive?
What is the degree of market competitiveness of
farmers if expressed on a numerical scale?
What are some of the factors that can affect the cur-
rent level of competitiveness?
What are the factors that currently play a crucial role
in terms of competitiveness?
The following hypotheses are to be verified:
H1. Farmers’ competitiveness or their ability to com-
pete is negatively affected by unfair competition,
problems with production and marketing costs, lack
of finance including credit, lack of state support to
farmers’, lack of training, poor market access, the
pressure of traders on farmers’, and poor functioning
of the wholesale market.
H2: Farmers’ competitiveness or their ability to com-
pete is positively affected by appropriate assistance
for production and marketing standards, and ade-
quateness of the market of information.
H3. Age affects negatively the ability to compete,
with older farmers’ facing more problems with sales,
or being less competitive.
H4. Education affects positively the ability to com-
pete, farmers with higher education being more
For the realization of the study a mixed descriptive–ex-
ploratory approach was used.
Competitiveness between gures and metaphors; are farmers’ apple producers enough competitive?
Review of literature
There is a wide discussion inliterature and authors argue
that competitiveness however does not have a definition
in economic theory (Sharples, 1990a; Ahearn et al., 1990;
Banse et al., 1999). While Krugman sees as a ‘dangerous
obsession’, he ironizes a little when it says that “influential
people have used the word ‘competitiveness’ to mean that
countries compete just like companies, professional econo-
mists know very well that this is a poor metaphor”, visualiz-
ing further the importance of location forces to competitive-
ness ofnew EU members (Krugman, 1994; Krugman, 1996;
Krugman et al.,1990). Anyhow, it can be defined “as the
ability to face competition and to be successful when facing
competition” (Latruffe, 2010). Basic economics hold that the
producer with the lowest cost of production will be the most
successful competitor and he is said to have the best underly-
ing ‘competitive advantage’ (Vollrath, 1989). Reinert noted
a contradiction between ‘competitiveness’ and neo-classical
theory including Krugman, emphasizing that the relative or
absolute productivity levels will not necessarily lead to com-
petitiveness and some very efficient producer’s ore some na-
tions are desperately poor – being efficient in products which
do not provide competitiveness in the income–raising mean-
ing of the word (Reinert, 1994).Coppola by evidenced that
the farm competitiveness over the last decade has become a
topic of increasing relevance in the EU agricultural and rural
policies,highlights that competitiveness affected by a broad
spectrum of issues such as endogenous characteristics and
exogenous factors(Borisov et al., 2014; Coppola et al., 2018;
Popova, 2019).Analyzes of competitiveness may differ with
respect to the level of investigation (Frohberg et al., 1997).
The charge of inadequate and unfair competition deserves
a careful investigation, even if it is eventually found to be
unsubstantiated (James Jr, 2013).
Economists generally agree that agriculture is an increas-
ing–cost industry and increase in trade conflicts have gener-
ated interest in issues of competitiveness (Sharples, 1990b).
Freebairn, identifying the importance of costs for sales mar-
kets and exports sets out that competitiveness in agriculture
based in three aspects, which include dimensions of labor
costs, the productivity of labor, and industrial harmony,
which also interacting with each other (Freebairn, 1987).
The process of increasing competitiveness of the sector re-
quires a permanent effort in looking for new possibilities of
improving the production efficiency and this relates to cost
reduction (Matośková et al., 2009).Among several factors,
competitiveness in agriculture over time may be main-
tained,through changes in production costs and sales (Brink-
man, 1987).In an analysis of the competitive performance of
the EU countries, Banterle finds that competitiveness char-
acterized by negative dynamics, even though have high sales
at the export markets (Banterle et al., 2007).
Trzeciak–Duval seeing this issue from a financial point
of view, emphasizes that a competitive environment in the
agricultural sector, needs credit for its development and the
farmers’ in transition economies facing especially difficul-
ties in obtaining access to credit (Trzeciak–Duval, 2003).
Blancard finds that, almost all farms seem to suffer from
credit constraints for financing their investments and this is
influential on farm performance in the long run (Blancard
et al., 2006).In his interdisciplinary core work on new in-
stitutional economics, by developing effective modes for
governing of agrarian sustainability, Bachev argues and find
links between the farm performance and a wide spectrum of
factors of institutional nature such as personal, dimensional,
natural, etc. with influence on sustainability in agriculture
and governance choice in transition economies (Bachev,
2006; Bachev, 2007; Bachev, 2012).Given that farm compet-
itiveness is often undefined and is studied through traditional
indicators of technical efficiency, productivity, profitability
etc., important aspects of farm competitiveness such as the
governance efficiency, the institutional environment or the
‘rules of game’ and potential of incentives for adaptation are
commonly ignored in the analyses (Bachev, 2010). In transi-
tion economies farm competitiveness among others is deter-
mined by characteristics such as farm organization and the
governance’s role (Curtiss, 2000).Colyersees competitive-
ness developments in the light of the government interven-
tions due to increasing environmental implications,which
has been proven to have an impact on the competitiveness of
the agricultural sector anywhere in the world (Colyer, 2004).
Lioutas finds that training programs and education could
improve both, productivity and labor condition for farmers’
smallholders (Lioutas et al., 2010; Nikolov et al., 2014). Pro-
fessional training of farmers’ as a government intervention
affects competitiveness of family farms and these effects can
be measured, proving that the farmers’ that participated in
this training achieved higher productivity and thus increased
their farms’ competitiveness (Vitunskienė, 2018).Agricul-
tural standards evolved over the course of many years and
were in essence codified publicly by regular accepted use,
but the last decade has seen dramatic changes and these de-
velopments are related with new requirements to export re-
quirements for size, color, safety, consistency, volume, pack-
aging, labels, etc., which affects the need for investments,
changes in the level of production, etc. (Giovannucci, 2008).
Restrictions, standards and subsidies of the most powerful
countries for their products, poor organization of producers,
weak communication structure, transport and infrastructure,
limited trade information, are some of the reasons for poor
34 Myslym Osmani, Rezear Kolaj, Petar Borisov and Ekaterina Arabska
market access (OECD, 2007). While the agricultural prod-
ucts may be objectively identical between EU countries and
farmer producers, the processes through which they were
produced may vary greatly and this is related with standards
of farm practice and processes, since they commonly trans-
late into on–farm constraints (Brouwer et al., 2000). Specific
sectors of agricultural production in Romania are less com-
petitive due to international standards and with the accession
of country to the European Union the competition between
these products will be much stronger (Chelmu, 2012).
The importance of information and access to such
information on the part of small–scale producers and
the poor has long been recognized (Marter, 2005). It is
commonly accepted that raising competitiveness could
be reached not only through huge investments, but also
through creation and distribution of knowledge and net-
working and information among stakeholders which are
of extreme importance for agricultural sector (Terziev et
al., 2015). Zimmer, finds that the main reasons of farm-
ers’ to not cultivate an agricultural crop is related with
the lack of information of farmers’ and extension services,
which followed by problems and poor economic condi-
tions (Zimmer et al., 2015). The lack of information, or
situations of asymmetric information, is rather the norm
in most developing countries and it is surprising that there
are so few empirical studies based on data from devel-
oping countries assessing the effects of improvements in
information (Svensson et al., 2008).At the international
level changes in the competitiveness of nations are re-
lated with farmers’ and their access in the international
markets (Anderson, 1995). One of the main questions is
how to improve farmers’ competitiveness, by addressing
their market access capabilityto improve the overall per-
formance of the farm (Biénabe et al., 2005).
An important issue is the lack of power and negotiat-
ing capacity of smallest-scale farmers’ in their relation-
ship with other agents and negotiating skills, power and
political representation are also critical for small–scale
farmers’ and unorganized (Biénabe et al., 2005). The
negotiation process between participants in agricultural
activities is related with different knowledge, values or
economic status (Petrescu–Mag et al., 2018).Wilcox finds
positive relation between farmers’ negotiation power ef-
ficacy and the information about market, suggesting that
the negotiating capacity of farmers’ is enhanced when
the prevailing prices are ‘known’ (Wilcox Jr. et al.,
2006).Most studies on competitiveness often make the
mistake by only considering the output side of the agri-
business system (‘from farm to table’) and thereby ig-
noring the possible impact the input sector could have on
the competitiveness (Kirsten, 1999). Due to the increased
competition on the enlarged Single European Market,
rationalization of input costs to increase farm efficiency
might be one of the farm strategies (Bojnec et al., 2007).
Gill discussing the issue of the competitiveness of agri-
culture, evidenced importance of prospects related with
market in terms of prices and their stability/instability and
the movements of domestic of agricultural and non–agri-
cultural prices within the country (Gill et al., 1996). To
be competitive a farm needs to use the best practice with
respect to technology, its internal organization and con-
nections to market actions (Sarris et al., 1999). Traditional
studies on competitiveness have been challenged by non–
standard approaches, since that they are based mainly on
comparative costs and market participation which are dis-
torted by subsidies especially for agricultural products,
and for this reason traditional approaches show inconsis-
tent results(Zylbersztajn et al., 2003).
Contrary to popular perceptions, farming is not exclu-
sively the domain of elderly farmers’, but rather occurs at
various stages in the life course in ways which often make
such activity ‘invisible” to farm surveys and agricultural
development policy (Woodsong, 1994). It is believed that as
a farmer ages and gains experience he or she becomes more
productive with improved managerial ability, but the pro-
ductivity may fall later in life (Tauer, 1994). Farmer’s age
is positively and very significantly related to earnings, be-
cause age’s importance captures a number of processes,and
it goes together with farming, marketing of products and
sales and management skills all improve with experience
(Galt, 2015).There is a positive corresponds between age
of farmers’,the productivity, and their participation in the
factor markets and sales (Gebreselassie, 2003).There is a
highly and positively interaction between farmer’s ability
to produce and sell more in a market with education lev-
els, and especially farmers’ who have secondary education
combined with other forms of education, are more likely
to sell more in the market (Sebbata et al., 2014). At the
imperfect market conditions and socioeconomic and insti-
tutional constraints, farmers’ households’ educational lev-
el it is positively related to production efficiency(Wang et
al., 1996). Examination on the research on the economic
benefits of education is limited ondata from urban sector,
although because of the agricultural sector´s massive size,
the intensity of use of trained manpower and rural develop-
ment requires a huge expansion of education at all levels
(Lockheed et al., 1980). Hamilton argues a broader role of
the farmers ‘education in access to credit and the agricul-
ture, to the marketing commodities, buying and selling and
factors of production (Hamilton, 1990).
Competitiveness between gures and metaphors; are farmers’ apple producers enough competitive?
Material and Methods
We use primary data, obtained by a special survey with
220 accidentally selected farmers of Dibra region. Major
variables for which data were collected are shown in Table 1
(Table 1 below).
The competitiveness of the farmers’ is proxied with the de-
gree of sales difficulties or sales problems, where serious sales
problems mean lower ability to compete, while farmers’ ne-
gotiation power is proxied by the degree of pressure that trad-
ers exert on farmers to sell at lower prices. Table 2 shows the
structure of the sample by gender, age, and level of education.
Males are dominant, with 62% of the sample, while farmers
with 8–year or secondary education make up almost 90% of
the sample. In terms of age, dominant are farmers above 34
years old. About 15% of farmers are above 64 years old.
In terms of methodology we use the grouping of individ-
uals according to one or several characteristics (variables),
statistical reports of the structure as well as descriptive sta-
Table 1. Variables, their measurement scale and operationalization
Variables Mea-
Acronym Categories/Values
1 Gender Nominal Gender 0 = Female, 1 = Male
2 Age Ratio Age Years
3 Education Nominal Education 0 = Primary, 1 = Secondary,
2 = Superior
4 Sales are a problem Ordinal Sale 1 = Absolutely disagree 2 = Disagree,
3 = Agree, 4 = Absolutely agree
0 = Disagree (Absolutely disagree or Disagree)
1 = Agree (Agree or Absolutely agree)
5 Production and marketing costs are a problem Ordinal Costs
6 Competition is a problem Ordinal Competition
7Lack of nancing is a problem Ordinal Finance
8 Lack of trainings is a problem Ordinal Training
9 State Support is problem Ordinal StateSup.
10 Production public assistance for standards is appropriate Ordinal ProdAssist.
11 Marketing public assistance is appropriate Ordinal MarketAssist.
12 Marketing information is appropriate Ordinal Information
13 Market access has improved Ordinal MarketAccess
14 There is no pressure from traders Ordinal Pressure
15 Wholesale market is functioning Ordinal Wholesale
Source: Data estimated by authors
Table 2. The structure of the sample by gender, age and education
Gender/Age Education Total
Primary 8-year school Secondary College University
Females 7 60 11 5 1 84
Under 24 3 1 1 5
25-34 4 2 1 1 8
35-49 1 18 5 3 27
50-64 2 25 3 30
Above 64 4 10 14
Males 7 74 51 5 137
Under 24 1 1 2
25-34 7 3 10
35-49 2 17 11 2 32
50-64 2 31 24 1 58
Above 64 3 18 12 2 35
Total 14 134 62 10 1 221
Source: Data estimated by authors
36 Myslym Osmani, Rezear Kolaj, Petar Borisov and Ekaterina Arabska
tistics (means, medians, standard deviation) graphical pre-
sentation, non–parametric correlation (rank correlation and
coefficient of association).
Rank correlation
Since in our case almost all variables are expressed in the
ordinal scale, then the degree of association between them
can be measured by rank correlation. One such indicator is
the Sperman’s correlation coefficient rs. If X and Y are the
two ordinary variables the Sperman’s coefficient is calculat-
ed by the formula:
Here d is the difference between the ranks of individuals
according to Y and X, while n is the volume of choice.
Another formula for calculating the Sperman’s coeffi-
cient is:
rs = –––––,
where a and b are the ranks of X and Y respectively. Sa and
Sb are the standard deviation of the ranks for X and Y respec-
tively, while Sab is the covariance between the ranks a and b.
With the condition that n>30, the Sperman’s coefficient
is tested by the normal Z test, initially calculating the actual
value based on the data:
Zf = rsn – 1
Then we calculate the probability P:
P = 2P(Z > Zf)
If P > α, where α is the significance level (usually 0.05),
then the hypothesis on the lack of correlation between the
two variables has no basis to be rejected.
Coefficient of association
The other two coefficients that can be used to measure
the degree of association between ordinary variables in the
case of 2x2 tables or groupings (between two ordinary vari-
ables with two categories 0 and 1 each) are the association
coefficient Ka or the contingency coefficient Kk. Let be the
2x2 table for two variables (no problems for sales and market
information are appropriate) as follows (Table 3):
Coefficient of association Ka in this case can be calculat-
ed by the formula:
ad – bc
Ka = –––––––
ad + bc
Here a, b, c and d are the absolute densities (number) of
individuals (cases) for each combination of the categories
of the two variables. The contingency coefficient Kk can be
calculated with the formula:
For more methodological details see Osmani
(2015),Keller (2018), Boslaugh (2013) and Elisseva et al.
(2004).Microsoft Excel and GRETL programs were used to
perform groupings, calculations and graphs.
Results and Discussion
The following Table 4 shows the main descriptive statis-
tics for some of the variables with interest. The most import-
ant problems that farmers of farmers’ have assessed are the
lack of state support, followed by lack of training and lack of
finances. Sales problems are rated at 2.96, which means that
sales problems are quite high, otherwise competitiveness is
rated at 1.04, which is quite low (calculation: 4-2.96 = 1.04).
The sales median shows that half of the farmers’ estimate
over 3 difficulties in sales. Standard deviation (SD) indicates
that farmers are more homogeneous in their responses to
sales problems, cost–related problems, and competition–re-
lated problems than to responses for other variables.
The following Figure 1shows the grouping of farmers’
according to their agreement with some major difficulties
Table 3. Example of a 2x2 grouping with ordinal vari-
No problems for
Market information is appropriate Amount
0 = Agree 1 = Disagree
0 = Agree a b a+b
1 = Disagree c d c+d
Amount a+c b+d n
Source: Data estimated by authors
Fig. 1. Farmers’ assessment of the first group of problems
Source: Data estimated by authors
Competitiveness between gures and metaphors; are farmers’ apple producers enough competitive?
that they assess as such. It is noted that in all cases, almost
80% or over 80% of farmers’ are unique in their attitude
about the main problematic. For example, over 84% of them
think that sales are characterized by serious problems and
difficulties. 85% of farmers’ think that the main difficulty re-
lated to sales problems are financial difficulties, about 81%
problems with competition, etc.
The following Figure 2 shows the grouping of farmers’
by their agreement with some other difficulties or shortcom-
As the data show, serious problems or shortcomings are also
their related to the support of the farmers’ for the production
standards and the support for the marketing of the product, not
forgetting the deficiencies related to the trade information, the
access to the markets the pressures that traders put on farmers’
to buy, mainly related to prices and quality but not only, etc.
The following Table 5 shows how the main problems
vary according to the main activity of the farm. We note that
the problem is generally more serious in the case of horticul-
ture and apples than in the case of vegetables. It seems that in
the case of fruits and apples in particular, problems in sales,
as well as lack of training are somewhat more problematic
than in the case of vegetables. The lack of finances seems to
be equally serious for both horticulture and vegetable.
Table 6 shows age-disaggregates estimates for the major
problems that apple farmers are facing. It is quite obvious
Table 4. Summary statistics
Variable Mean Median SD Min Max Variable Mean Median SD Min
Sale 2.96 3.00 0.704 1.00 4.00 Information 2.43 2.00 0.871 1.00
Costs 2.91 3.00 0.700 1.00 4.00 ProdAssist. 2.32 2.00 0.906 1.00
Competition 3.00 3.00 0.731 1.00 4.00 MarketAssist 2.12 2.00 0.878 1.00
StateSup 3.35 4.00 0.776 1.00 4.00 Wholesale 2.55 3.00 0.760 1.00
Finance 3.15 3.00 0.878 1.00 4.00 MarketAcces 2.35 2.00 0.747 1.00
Training 3.33 4.00 0.823 1.00 4.00
Source: Data estimated by authors
Fig. 2. Farmers’ assessment of the second group of
Source: Data estimated by authors
Table 5. Average ratingsof problems according to some activities
Sale Costs Competition Finance Training
Is apple main contribution?
0 = No 2.65 2.73 3.04 2.85 2.92
1 = Yes 3.00 2.94 3.00 3.20 3.40
Is fruit main contribution?
0 = No 2.66 2.79 2.94 2.85 2.91
1 = Yes 3.04 2.95 3.02 3.24 3.46
Is vegetable main contribution?
0 = No 2.97 2.91 3.09 3.09 3.39
1 = Yes 2.94 2.91 2.81 3.29 3.22
Total 2.96 2.91 3.00 3.15 3.34
Source: Data estimated by authors
Table 6. Assessment for problems of farmers’ according
to age
Age Sale Costs Competition Finance Training
30 years 2.75 2.92 2.88 2.46 3.25
42 years 2.79 2.76 2.84 3.25 3.46
55 years 3.14 2.93 3.08 3.21 3.29
65 years 2.98 3.11 3.18 3.27 3.32
Total 2.96 2.91 3.00 3.15 3.34
Source: Data estimated by authors
38 Myslym Osmani, Rezear Kolaj, Petar Borisov and Ekaterina Arabska
that older farmers are facing more sales problems than do
younger ones. Production and marketing costs, competition,
and lack of finance are also serious problems (Table 6).
The following Table 7 unveils the degree of association
between the sales variable and each of the other variables
of interest. The calculation of the association coefficient is
made possible after the 2x2 grouping of individuals (two
rows, two columns, or with 2 categories for each variable)
as follows (Table 7).
The association coefficients show a strong association
between the competitiveness of farms and problems with
cost, state support, problems with competition, lack of fi-
nance, training, etc.
The following Table 8 shows the ranking correlation co-
efficient (Sperman’s coefficient) between problems in sales
with variables or other problems identified by farmers’.
Thus, the main or primary factors that seem to have an
impact on competitiveness (sales problems) are production
and marketing costs, competition, the lack of state support,
and the lack of finance. Older farmers seem to face more
problems, while education, in general, seems to be neutral.
However, if we disaggregate the education in three levels
(0=Primary, 1=Secondary, 2=Superior), we found a signif-
icant negative relationship between the secondary level of
education only and the ability to compete, i.e., these farmers
tend to be less competitive.
Age and education generally result in factors with a pos-
itive effect but not significant on sales problems, although
as a trend older farmers’ and those with more education tend
to have more problems. However, a significant difference
in effect results between secondary education and its other
two categories taken together, where farmers’ with second-
ary education seem to have more difficulty with sales than
those with primary or higher education. Gender also is not
Farmers’ competitiveness is a key issue influencing the
sale of farm products, namely the income and standard of
living of farming families, and more. This study builds on
the need to assess the competitiveness of apple farmers’ and
identifying some factors of economic, demographic, and in-
stitutional character that affect it, currently unknown or not
systematically estimated.
Filling this knowledge gap could serve as a good basis
for orienting/indicating effective policies and measures to
Table 7. Association between sales and other variables
Variables Sale 0 = Disagree 1 = Agree Total Coe. of
Costs 0 (Disagree) 15 33 48 0.551
1 (Agree) 20 152 172
Competition 0 (Disagree) 15 27 42 0.629
1 (Agree) 20 158 178
Finance 0 (Disagree) 17 31 48 0.649
1 (Agree) 18 154 172
Training 0 (Disagree) 10 24 34 0.46
1 (Agree) 25 161 186
Market Assist 0 (Disagree) 29 122 151 0.428
1 (Agree) 6 63 69
Prod Assist 0 (Disagree) 24 124 148 0.035
1 (Agree) 11 61 72
Information 0 (Disagree) 30 105 135 0.641
1 (Agree) 5 80 85
Market Access 0 (Disagree) 18 118 136 -0.249
1 (Agree) 17 67 84
State Sup 0 (Disagree) 18 15 33 0.846
1 (Agree) 17 170 187
Wholesale 0 (Disagree) 21 73 94 0.394
1 (Agree) 14 112 126
Pressure 0 (Disagree) 20 115 135 -0.104
1 (Agree) 15 70 85
Total 35 185 220
Source: Data estimated by authors
Competitiveness between gures and metaphors; are farmers’ apple producers enough competitive?
increase the competitiveness of farmers’ and increase their
standard of living, increasing their role in the apple value
chain, and bringing price and quality benefits to consumers.
The results build on the data collected through a special ran-
dom survey of farmers’ in the studied region (Dibra). The
results indicate that the level of competitiveness of apple
farmers’ in the study area is quite low (1.04) on a scale rang-
ing from 1 to 4.
In a line with the hypotheses, the study demonstrated a
negative correlation between the ability to compete on one
side, and unfair competition, problems with production and
marketing costs, lack of finance including credit, and lack of
state support to farmers’ and this as we have put forward is
supported by an extensive literature. The institutional frame-
work, including the approach to credits, unfair competition,
and states support deserves attention. This industry during 30
years (approximately) of the country’s transition towards EU
membership had to take advantage of the effects of concentra-
tion and specialization and dynamics. Infact, the above insuf-
ficiency creates social effects for the region and especially for
the departure of people abroad, social cohesion, etc.
Regarding the age, data results indicates that older farm-
ers are facing more problems with sales, thus being less
competitive, this result also being in line with the research
hypothesis. The literature evidences both positive effects and
negative effects of the age on the farmers’ ability to compete.
Rosenberg (2017), taking under review census (COA, 1982–
2012), expresses concern about the increase in the number
of zero-sales farmers’ finding age–related links, where the
zero-sales farm rises dramatically with the rice of farmers’
age. This is related on the one hand to old age on the aver-
age of farmers’ who deals with this activity and also with
the effects of abandonment of the region by young people.
Moreover, the latter testifies to the loss of general working
skills in agriculture, as these skills are related to inheritance
the overestimated role of social capital, etc.
Contrary to the hypothesized associations, between the
ability to compete on one side, appropriate assistance for
farm production/marketing standards, and adequateness of
market information, on the other side, is verified a negative
association. However, we have pointed out the literature
highlights cases where higher international standards af-
fect negatively the ability of the local farmers’ to compete
(Chelmu, 2012).The education in general does not influence
the ability to compete, but farmers with secondary education
seem to be less competitive. There is not verified a signif-
icant and positive association between farmers’ ability to
compete on one side, improved market access, appropriate
functioning of the wholesale market, and no pressure exerted
on farmers’ by the traders as a proxy variable for farmers’
power of negotiation, and training.
It should be discussed carefully positive signs and
significant association with competitiveness in the case
of three variables: market information, product standard
assistance and marketing assistance. Formally, based on
these coefficients, we can state that those who estimate that
market information, production standards assistance, and
marketing assistance are all okay tend to think that sales
are a problem! This is not in line with logic or expectations
and can only be explained if we accept that these factors
are secondary or tertiary regarding the effects on compet-
itiveness. Otherwise, as an example, although commercial
information for farmers’ may be complete, if they have
problems with costs or finances, problems with sales will
be inevitable. If we refer more specifically to the market
information, Table 7 shows that there are 80 farmers’ who
have a problem with the market and who at the same time
report that the market information is in order; or there are
30 farmers’ who have no problem with the market but at
the same time report unacceptable state of market informa-
tion. So the positive sign of the three specific associations
mentioned above does not mean that there will be no sales
Table 8. Sperman’s coefficient of correlationbetween sales and the other variables
(Base hypothesis H0: No correlation)
Variable Spearman R Prob. H0Variable Spearman R Prob. Variable
Age 0.146 0.030 Refuted Prod Assis 0.247 0.000 Refuted
Education 0.098 0.146 Not refuted Market Assist 0.298 0.000 Refuted
Costs 0.515 0.000 Refuted Market Access 0.015 0.826 Not refuted
Competition 0.281 0.000 Refuted Wholesale 0.498 0.414 Not refuted
StateSup 0.292 0.000 Refuted Pressure 0.040 0.551 Not refuted
Finance 0.236 0.000 Refuted DEdu-1 0.149 0.027 Refuted
Training 0.083 0.219 Not refuted DEdu-2 -0.037 0.586 Not refuted
Information 0.396 0.000 Refuted Gender 0.088 0.192 Not refuted
Source: Data estimated by authors
40 Myslym Osmani, Rezear Kolaj, Petar Borisov and Ekaterina Arabska
problems when market information, help with production
standards and help with marketing are well valued by the
majority of farmers’, or does not mean that these problems
do not exist when there are no problems in sales, because
it is the main or primary factors that lead to changes in
Based on the above results, discussion and the arguments
presented, this study contributes to the increase of knowl-
edge about the competitiveness of the small apple farmers’in
Albania and some of the most important factors that deter-
mine it. Some limitations could however be outlined.
The ability to compete is a crucial issue which impacts
immensely on–farm sales.With higher ability to compete
farmers’ will have better access to markets, hence more op-
portunities to sell their products and realize higher income,
and improve farmers’ ‘households’ standard of living, pros-
pects for their children, and their role in and efficiency of the
apple value chain.
The study analyzes the situation and the most influential
factors for competitiveness, illustrating with a case study of
farmers’ apple-producers in the region of Dibra, northeastern
Albania, using statistical methods based on primary data col-
lected by a special survey. The analysis of data related to the
problems and difficulties of sales revealed that the competi-
tiveness of apple farmers’ is quite low. As a result, farmers’
sell at very low prices and part of the product fails to sell.
The most serious reasons for this low competitiveness that
the study revealed are unfair competition in the market main-
ly from imported products, significant production, and sales
costs, lack of financial support (such as input subsidies) from
the state, and very limited access to credit. The study did not
identify as statistically significant the market access, trade
information, pressures on farmers’ and training, but as the
data show a significant percentage of farmers’ is claiming
that training is a problem, that information is not adequate,
or that part of farmers’ are under pressure from traders to sell
at low prices.
Policy implications.The study uncovers good guidelines
to help farmers understand their opportunities to increase
their competitiveness and other relevant interested. Reduc-
ing unfair competition would be perhaps the major path to-
wards better farm ability to compete. Measures to do this
could include a wide range of subsidies including collective
action practices and farmers’ groups to reduce costs, infor-
mation providing to farmers’ about prices and quality stan-
dards of the imported apple and a new state legal framework
including traceability according to EU standards for agri–
food products to make sure they are safe and healthy for con-
sumers it is with importance on the demand side.
Providing subsidies for quality inputs to reduce produc-
tion/marketing costs and enhance productivity may effect
on the quality and level of prices of their products and also
the reputation and general capabilities negotiations of the
farmers’. Subsidies and credits on the other hand may im-
prove post–harvest operations and storage, with effects on
the quality standards as well as better overtime schedule of
sales operations, which would promote higher farmer’s ne-
gotiation power.
In the same direction providing of advice and support
for Good Agricultural Practices (GAP) would be effective
as literature highlights (Brouwer et al., 2000) etc., standards
of farm practice and processes have a crucial role to play, so
farmers’ should be supported and encouraged to use these
practices. These practices are one of the best product quali-
ty enhancers with a direct impact on the competitiveness of
farmers’.Access to new tech–knowledge remains crucial for
the progress of the sector and this is supported by an exten-
sive literature. Summarizing, an important trinomial is that
farmer decisions that involve success and/or potential failure
are related to the quality of extension services, policy–mak-
ing capacities, and supervision.
The much–needed promotion of forms of collective ac-
tion it cannot remain an issue that is discussed only in sem-
inars, we need to see the theories, findings from scientific
research tested and applied in practice. The farm organiza-
tions can contribute to the definition and the implementation
of new pathways of change in rural areas, providing several
benefits for individual with specific needs and local com-
munity (Lanfranchi et al., 2015).In Albania there is a lot of
potential to benefits from farmers’ in this regard and this
study is just one of the many cases that suggests. Collective
action among farmers’ themselves and among other actors in
the value chain would will reinforce the sustainability of the
economic system and also make possible quality advisory
services, quality and lower prices for inputs as well as stan-
dardization of on–farm cultivation practices and methods.
Thus, well–structured measures, including subsidies and tar-
geted advice to promote collective action, would also work
for higher farmers’ ability to compete.
Way forward. Good Agricultural Practices (GAP), price
stability in the domestic and international markets, produc-
tivity, and the effectiveness role of farm extension services
are important drivers or enhancers of the farmers’ ability to
compete. The access to new knowledge and new technol-
ogies is a prerequisite for raising competitiveness and im-
proving business environment (Arabskaet al., 2014) and it
goes hand in hand with the premises for the revitalization of
Competitiveness between gures and metaphors; are farmers’ apple producers enough competitive?
the sector. Thus, further research on these issues in the light
of new developmental dynamics would be a necessity and
highly recommended action to outline additional guidelines
in promoting farmers’ ability to compete.
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Received: May, 19, 2021; Accepted: June, 25, 2021; Published: September, 2021
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Risks management studies in the agri-food sector predominately focus on the technical methods and the capability to perceive, prevent, mitigate, and recover from diverse risks. In most economic publications the risks are usually studied as other commodity regulated by the market supply and demand, and the farmers “willingness to pay” for an insurance contract modeled. At the same time, the risk management analysis largely ignore a significant “human nature” based (bounded rationality, opportunism) risk, critical factors for the managerial choice such as the institutional environment and the transaction costs, and diversity of alternative (market, private, collective, public, hybrid) modes of risk management. This paper incorporates the interdisciplinary New Institutional Economics and presents a comprehensive framework for analyzing the risk management in the agri-food sector. First, it specifies the diverse (natural, technical, behavioral, economic, policy etc.) type of agri-food risks, and the (market, private, public and hybrid) modes of their management. Second, it defines the efficiency of risk management and identifies (personal, institutional, dimensional, technological, natural) factors of governance choice. Third, it presents stages in the analysis of risk management and for the improvement of public intervention in the risk governance. Fourth, it identifies the contemporary opportunities and challenges for the risk governance in the agri-food chain. Finally, it identifies, and assesses the efficiency and prospects of major modes for risk governance in the Bulgarian dairy sector.
In this article I develop a political economic understanding of community-supported agriculture (CSA). I first develop the relevance of three concepts—economic rents, self-exploitation, and social embeddedness—to CSA and then introduce a framework that relates CSA farmers’ earnings to the average rate of profit, economic rents, and self-exploitation. I then examine qualitative and quantitative data from a study of 54 CSAs in California's Central Valley and surrounding foothills to explain the wide range of farmers’ earnings in relation to the characteristics of production of CSAs, the social embeddedness of CSAs, and the farmers’ motivations and rationalities. Qualitative data from interviews are used to interpret the results of an ordinary least squares regression analysis showing that (1) farmers’ age, number of employees, and type of CSA strongly shape farmers' earnings; (2) the moral economy of CSA cuts both ways economically, allowing for the capture of economic rents but more often resulting in self-exploitation because of farmers’ strong sense of obligation to their members; and (3) farmers’ motivations are diverse, but tend toward low and moderate instrumentalism, meaning that earning an income is often not a high priority relative to other values. The conclusion recommends the need to recognize alternative rationalities but also to discuss and confront strong self-exploitation in alternative food networks because of the broader political economic context in which they exist.
Farmer productivity by age was estimated, allowing for differences because of efficiency and returns to scale. Using Census of Agriculture data, estimates vary by state, but returns to scale average 1.07. Efficiency increases average 4.5 percent every ten years of age, to the age interval 35 to 44, and then decreases at that same rate.
The view that nations compete against each other like big corporations has become pervasive among Western elites--many of whom are in the Clinton administration. As a practical matter, however, the doctrine of "competitiveness" is flatly wrong. The world's leading nations are not, to any important degree, in economic competition with each other. Nor can their major economic woes be attributed to "losing" on world markets. This is particularly true in the case of the United States. Yet Clinton's theorists of competitiveness--from Laura D'Andrea Tyson to Robert Reich to Ira Magaziner--make seemingly sophisticated arguments, most of which are supported by careless arithmetic and sloppy research. Competitiveness is a seductive idea, promising easy answers to complex problems. But the result of this obsession is misallocated resources, trade frictions and bad domestic economic policies.