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TITLE: Quantifying factors that influence implementation of QMS
(Quality Management Systems) in meat processing industry in Albania
using Ordinal Logistic Regression
By:
Doc. Ilir KAPAJ (principal investigator)
Agriculture University of Tirana, Faculty of Economy and Agribusiness, Dep. of
Agribusiness Management
e-mail: ilirkapaj@yahoo.com , ikapaj@ubt.edu.al
Tel: 00355 (0)68 40 13 722
Dr. Remzi Keco (collaborator)
Agriculture University of Tirana, Faculty of Economy and Agribusiness, Dep. of
Agribusiness Management
e-mail:, rkeco@ubt.edu.al
Tel: 00355 (0)69 20 95 456
Department Chair: Prof. Dr. Donika KERCINI
Department Chair: Prof. Dr. Kristaq PATA
Dean of the Faculty: Prof. Dr. Bahri MUSABELLIU
Tirana, August 28, 2010
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1. Introduction and problem statements (max 1 page)
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In the last decade quality has became of outmost importance to society. Consumers
have become more conscious of quality, and organizations are now judged more on
their overall quality performance instead of their financial performance alone. The
most drastic change in quality thinking is probably the change from productionoriented to consumer-oriented concepts. Moreover, integrative approaches, system
thinking, the focus on advanced technologies and belief in human capacities have had
a considerable impact on current quality management (Schiefer 2002)
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Quality has become a vital distinctive feature for competition in the world market
food products. To obtain a good quality end product, quality is more and more
managed along the whole food chain from the supplier of raw materials to the
consumption. Striving for quality is not a free choice. Consumer understanding of
food quality and the ultimate concern for health and food safety force actors in
agribusiness and food industry to use quality management as a strategic issue in
innovation and production (Luning, et al 2002).
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Although before the nineties there existed a good tradition, the current industry of the
meat processing is a relatively new industry in Albania, established mainly in these
last 15 years. Exploiting all the possibilities and the resources and overcoming the
difficulties faced during development, it has always managed to satisfy the
quantitative needs of the Albanian consumers.
Nowadays the most important and delicate problem related to meat processing
industry is the quality and safety of these products (avoiding elements in the content
of these products that damage and endanger the health). This problem is becoming
more sensitive as the meat industry is starting to prepare for introducing its products
in a larger and more organized way in the foreign markets, but firstly in the European
market.
In this study we are going to identify the factors that have an effect on implementing
quality management standards by meat processing sector in Albania and also to
quantify these effects.
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2. Objectives and research hypotheses (1/2 page)
Objectives of this research are:
Investigating level of implementing quality management standards in meat processing
sector in Albania, and which are the factors that influence implementation of these
standards.
How the different integrated quality management aspect are affected by different
factors belonging to internal and external environment of the organization (referring
to ordinal logistic regression analysis and quantitative measurement of these effects).
Within internal environment of the organization we thought to include factors that
deal with amount and quality of information from inside organization such as
“Number of computers in organization, Numbers of computers connected to internet,
etc. On the other hand with the term “External environment of the organization” we
are referring again to the amount, source and quality of information coming from
outside of the enterprise such as “Information from MoAFCP, Information from other
public and private institution, Information from markets (if enterprises collect data
regarding consumer’s preferences on quality etc.
Hypotheses: Willingness of meat processing enterprises to invest in implementing
quality management standards (GMP, ISO etc.) is affected largely by level of
information that they have regarding those standards.
According to Kapaj (2004) lack of information about these new practices and high
cost of implementation seems to be the main reasons for small and medium scale
meat processing enterprises not establishing the new practices (GMP, ISO standards).
For a few large scale enterprises lack of information and trained staff are the main
reasons for not applying these standards.
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3.
Literature review (max 1 page)
Food industry in Albania has to achieve the quality standards in order to be
competitive in future open markets (while aiming to enter in the EU countries). A
large number of enterprises in food industry suffer for lack of information in the field
of quality management and they need theoretical and practical training in this field
(Kapaj, 2004). Based on the fact that agriculture and food industry sector is the
largest contributor in the Albanian GDP, 23% of GDP in 2008 (INSTAT, 2009),
governmental policies in Albania aim further development of this sector.
Referring to a previous study (Kapaj, 2004) meat processing in Albania is dominated
by small-scale companies, partly industrial producers (54 well-established private
companies) and over 100 others operating as artisan ham & sausage producers. The
sector has noted increasing growth rates in terms of production, employment and
investment, even one of the most growing sectors in the agro-food processing
reaching 15% growth per year and with a current production value over Euro 55
million. Investments in the sector have increased in the recent years both on buildings
and technology-wise. Market share of domestic sausages and ham is estimated to be
over 90% with high import substitution norms in the recent years.
In new strategy for agricultural sector development from Ministry of Agriculture
Food and Consumer Protection in Albania is stated that meat consumption per capita
is also increasing, but still lagging behind the EU levels. The production is based
mainly on processing of imported raw materials, considering that livestock sector in
Albania is not developed at that stage to supply the industrial sector with the required
amount of raw materials. Slaughtering takes places mostly in farms, a few are located
in the main cities, but slaughterhouses by EU norms are lacking, hence a field of
investment. Slaughtered meat in Albania is preferred for fresh meat consumption.
Still, there are many farms increasing investments in both cattle and pig production
for industrial purposes, considering the increasing demand of the meat processing
industry. Packaging materials and equipments are also imported (MoFCP, 2008)
Retail chains of main meat processors are found all over the country, with Tirana the
most concentrated market, due to about 30% (MoAFCP, 2008) of the population
living in this area. The sector is strongly supported also by a growing retailing market
with new international brand hyper and supermarkets locating in the country. New
niche markets are developing in meat processing sector, such as the frog meat, for
which Albania has a fairly strong position and exporting currently to EU, as well as
snail. Very good prospects are noted for the poultry meat.
Under the certification process of quality management systems are some of meat
processing enterprises, while there is a need for product certification by 90% of
enterprises, and a need for certification of quality and safety management systems by
70% of meat processing enterprises; the readiness to invest in certification of products
is expressed by 25% and certification of management system by 35% of meat
enterprises in Albania (MoAFCP, 2008)
This research will consist in the identification of level of the implementation of these
quality standards in meat processing industry in Albania, problems that this industry
faces, and help to identify the incentive policies to support the managerial staff of
enterprises implementing successfully these quality management systems.
On the other hand policy-makers based on this scientific research can orient their
policies better and make them more effective towards meat industry and meat safety.
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4.
Methodology (max 1 page)
Talking about statistical analysis, first of all we have to make a clear and
distinguished classification of variables and define the relevant statistical analysis for
each variable measurement level. In this study, as described below in methodology
the researcher mostly will have nominal and ordinal measurement level for the
variables and if it is the case logistic regression and more specifically Ordinal
Logistic Regression will be applied for analysis.
The family of logistic regression models in this regard (in focus of this study)
receives a special attention. Ordinary logistic regression models, also called logit
models, apply with binary data (two-category responses) and assume a binomial
distribution. Generalizations of logistic regression apply with multicategory responses
and assume multinomial distribution (our case) (Agresti 2002:4). Logistic regression
derives its name from the logit transformation used with the dependent variable.
(Hair 2006:357).
In this research most of our data are going to be ordinal data that have more than two
categories. Multicategory logit models that deal with ordinal responses, assume that
at each combination of the levels of explanatory variables, the response counts for the
categories of Y have a multinominal distribution. This generalization of the binomial
applies when the number of response categories exceeds two (Agresti 1996:205).
The core point of all multivariate techniques or models is to find if there is any
association between dependent variables and independent variables, and if it is,
measure the strength of the relationship.
We will use the SPSS Ordinal Regression Procedure, or PLUM (Polytomous
Universal Model), which is an extension of the general linear model to ordinal
categorical data. We can specify five link functions as well as scaling parameters. The
procedure can be used to fit heteroscedastic probit and logit models (Norušis
2008:69).
The default link function for this procedure in SPSS is Logit f(x) = log(x / (1 – x)).
This is the default link function and is recommended when the dependent ordinal
variable has relatively equal categories (as in our case using Likert scale) as it offers
more interpretable parameter estimates, including odds ratios as measures of effect
size, and as use of other link functions often makes no substantive difference in
findings, the logit link function is by far the most utilized in ordinal regression.
According to Hair (2006) in terms of interpreting the coefficients of Ordinal Logistic
Regression positive coefficient increases the probability, whereas a negative value
decreases the predicted probability, of an event to occur (exp. Full willingness to
invest on QMS) because the original coefficients are expressed in terms of logit
values, where a value of 0.0 equates to an odds value of 1.0 and a probability of 0.5.
Thus, negative numbers relate odds less than 1.0 and probabilities less than 0.50.
We will consider as dependent variable two categorical variables measured in Likert
scale “Willingness to invest on ISO standards” and “Perception of companies about
level of competition” (high, level of competition leading to an immediate need for
quality improvement). As independent variables we will choose like “Level of
knowledge about ISO standards”, “Willingness to invest on training”, “Operational
markets”, “Ration Export/annual turnover”, “Level of compiling product technical
specification”, “Collaboration with R&D department within organization”, “Extent of
using internet in the company”, “Level of information provided by MoAFCP
regarding QMS”, “Level of information regarding QMS from other public and private
institutions” etc. According to Agresti (1996) the measurement scale of independent
variables in ordinal Logistic Regression can be of any type as it is in our case
(nominal, interval, ordinal and ratio scale). We will use dummy variable to model
firm size in our analysis.
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5. Data collection and administration (max 1 page)
Sample selection
Meat processing in Albania is dominated by small-scale companies, partly industrial
producers (54 well-established private companies) and over 100 others operating as
artisan ham & sausage producers. (MoAFCP, 2009). A stratified random sampling
will be the way of selecting the sample.
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Before stratified random sampling a pre-classification of meat processing enterprises
will be done. Based on the number of employees we will identify small, medium and
large scale enterprises. The idea behind pre-classification is to select a representative
sample from meat processing enterprises. We will use number of employees as a
criterion for pre- classification because we can not find sufficient information
regarding annual turnover of enterprises, or the share of enterprises in meat market
(no official data). The information about the number of employees is available in the
MoAFCP. The researcher will take a proportionate (relative to weight of each group
in the population) percentage of the enterprises in each group. On those three groups
of enterprises a random sampling will be applied and 30 enterprises will be selected.
Hosmer and Lemenshow (2000) suggested that we need to have at least 10 cases for
each parameter in Logistic Regression. In our case we are going to build logistic
models with three parameters (one dependent and three independent), so 30 cases will
be sufficient.
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Questionnaire design
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As survey instrument and to achieve the objectives of this study, a face to face
interview questionnaire will be utilized. The questionnaire will be a product of
experience, literature review and discussion with people with experience in the field
of questionnaire design. We think to compose the questionnaire in three section; the
first one will contain general question about enterprises, the second one will deal with
investigation of quality management system, implementation and willingness to
invest (measured in Likert scale) on this systems and the third section will deal with
ways of gathering and using the information (regarding quality management systems)
from internal and external environment of organization.
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Implementation of the survey and data collection
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Face to face interviews questionnaire were conducted for collecting the data.
According to Dillman (1978) face-to-face interviews survey method allow for the
possibility of obtaining somewhat more complete and accurate results than the other
survey methods, but only if interviewers are well-trained and consistent. The
researcher judges this method as appropriated once, even it is expensive in Albanian’
conditions. Using mailed questionnaires in the case of Albanian is impossible due to
the lack of network and communications skills via mail. A pre-contact will be done in
the beginning with managers or owners of the selected meat processing enterprises by
phone. The data and location of the face to face interview questionnaire will be
decided via phone calls. In order to ensure clarity reliable data all face-to-face
interviews questionnaire were done by pre-trained staff (master students). We also
plan to test the questionnaire in a small sample of enterprises in Tirana district.
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Data Analysis
Most questions in the questionnaire will be closed-ended. A code system will be
developed to easy the data entry process. The data will be entered into Microsoft’s
Excel spreadsheet program and then imported into SPSS. The accuracy of data entry
will be checked by frequency counts of each category. SPSS will be used to run
Ordinal Logistic Regression model.
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6. Expected results (1/2 page)
As meat enterprises in Albania expand their operational markets it is more likely that
they will have the full willingness to invest in quality management standards. The
logic behind this behavior makes sense, if markets become more competitive,
companies have to improve their quality to survive in that market.
Also we expect to quantify the statement that more information and knowledge
enterprises have about ISO standards, the more they will have the willingness to
invest on these standards.
Also we expect to find out that meat processing enterprises must apply client
technical specification, compile inter-operational specifications and have a good
collaboration between sectors in their organization, in order to enter in high
competitive markets.
What must be interesting in this context is that the effect of these factors to the overall
performance of the company will be addressed using Ordinal Logistic Regression.
When we talk about overall performance we mean various aspects of performance
like, “Annual turnover”, “Ratio Export/Annual turnover” etc.
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7. Table of objectives, activities, outputs and outcomes (1/2 page)
Table of objectives, activities, outputs and outcomes (1/2 page)
Objectives
Activities
Outputs
Outcomes
Literature review on
quality management
Reading the
Selecting relevant
Writing the
and information
literature
literature
literature
related to quality
Methodology about
logit models and more Logistic
Ordinal Logistic
Writing
specifically about
regression
Regression
methodology
logistic regression
Designing the
questionnaire on
Literature on
Selecting
Writing the
quality management
questionnaire
appropriate
questionnaire
in meat processing
design
question
enterprises
Face to face
interviews with
Collecting data in the
Filled
Securing primary
managers or
field
questionnaire
data
owners of
enterprises
Entering data
Data analysis using
Analyzing with
into spreadsheet
Results
software
SPSS
(excel, SPSS
Completed written Final research
Writing final research Writing the draft
research
completed
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8. Time line of activities (1/2 page)
Time
20-30 September
1-10 October
10/October – 10/November
10 - 20 November
21/November - 10/December
11/December - 15/January
Activity
Questionnaire design
Pre-testing the questionnaire
Primary data collection and entering in the excel
spreadsheet
Second data collection
Data analysis
Writing the final report
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9. Pitfalls (1/2 page)
Due to the fact that the sample will be widely spread geographically (all territory of
Albania) we might have to adjust the time schedule of activities, because the
interviewers have to travel long distances. Also in this context we might have to
extent the time schedule, because the interview date and place is very much
dependent on availability of managers or owners of the enterprises.
We also expect some contradictory answers from the respondents (I stated that from
my experience), which we have to adjust in accordance.
We plan to adjust these problems on the site (during the interview). We are going to
show the interviewers the possible contradictory answers from the respondents, show
them the section and specific questions where we might expect these kind of answers
and teach them some tips how to get rid of the contradiction, by asking again the
respondents.
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10. References
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Agresti, Alan. 2002. Categorical data analysis. Wiley series in probability and
statistics. 2nd ed. New York: Wiley-Interscience.
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Dillman, D. A., (1978). Mail and Telephone Surveys. The Total Design Method. New
York: Wiley.
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Hair, Joseph F. 2006. Multivariate data analysis. 6th ed. Upper Saddle River, N.J.:
Pearson Prentice Hall.
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Hosmer, David W., and Stanley Lemeshow. 2000a. Applied logistic regression.
Wiley series in probability and statistics. 2nd ed. New York: Wiley.
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INSTAT, (Institute of Statistics), (2009). Statistical Yearbook 2004. Tirana, Albania.
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Kapaj, I. (2004). Assessing the quality and safety of the meat processing industry in
Albania. Master theses. Stuttgart/ Germany
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Luning, L.A., Marcelis, W.J. and Jorgen, W.M.F., (2002). Food Quality Management:
a Techno Managerial Approach. Wageningen Pers, Wageningen, Netherlands.
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Ministry of Agriculture Food and Consumer Protection. 2009, . Database for
registered food and beverage enterprises in Albania. MoAFCP, Tirana.
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_________. 2008, . Database for registered food and beverage enterprises in Albania.
MoAFCP, Tirana.
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Norušis, M. J. 2008. SPSS 16.0 advanced statistical procedures companion. Upper
Saddle River, NJ: Prentice Hall.
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Schiefer, Gerhard. 2002. Quality management in agriculture and food : Management
principles, system requirements, and development directions. 2. Aufl. ed. Vol.
94,2. Bonn: ILB.
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11. Budget
Budget Items
1. Salary and Wages
-Wages for students
AHEED $
($20*30)
$600
FEA $
In-kind match $
$1000
2. Equipment
-Laptop for data input and
analysis
-Desk-top computer
3. Misc. Supplies
-Survey printing
-Telephone
-Office space
4. Other
-Software program (SPSS)
-Office package
5. Publishing
6. Travel Expenses
-Travel expenses for
survey/per diem
-Car use
7. Sub-total
8. Total
$600
$250
$100
$100
$150
$100
$300
$350
$700
$600
$3,000
-
$700
$150
$1,300
$5,000
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Note:
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Payment for questionnaires (data collection and entry): 30 questionnaires*$20 per questionnaire = $600
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Due to the fact that we will do a random sampling, the subject of the study (meat processing enterprises) can not be
specifically located yet (in terms of districts). For this reason we will calculate as per diem rate an average standard
for all over the country.
Payment for per diem (travel expenses)
3 students (10 questionnaires each)
3 st.* $20 (per diem-only meals)*5 days = $300
3 st.* $25 (hotel) * 4 nights = $300
TOTAL travel expenses
$600
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Short Bio of Collaborators
Doc. Ilir KAPAJ
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Ilir KAPAJ (2009), IFCN (International Farm Comparision Network), Dairy Report for Albania
country page (2009), published by IFCN Dairy Research Centre Kiel/Germnay www.ifcndairy.org
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Wine industry and development potentials in Korca region. Scientific Buletin, nr 13,
2006,Korca,Albania.
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“Problems and perspectives of the agricultural lands market in Albania”; The Annals Of “Valahia”
University Of Targoviste, Romania. PhD. Candidate Remzi Keco, PhD. Elvira Lleksina1, PhD.
Candidate Arben Kambo, Ardian Çerava, 2009.
“Weed flora and weed management in established olive groves in Albania”. B. Huqi, K. Dhima, I.
Vasilakoglou, R. Keco F.Sallaku Weed Biology and Management 9, Japan, 2009.
Ph.D. Expected to get an Ph.D degree on March 2010/ Hohenheim Stuttgart, Germany
Master degree: March 2002- September 2004
Skills and competencies: Agribusiness Management, Farm management and Rural Development,
Quality Management & Safety of Food Products, Firms Economics.
Scientific Publications:
KAPAJ. A. KAPAJ, I (2010), “Assesing the Comprative Advantage of Albanian Olive Oil
Production”, IFAMR International Food &Agribusiness Management Association, Volume 13,
issue 1, 2010, https://www.ifama.org/publications/chainletter/cmsdocs/9i1.pdf
Ilir KAPAJ (2008), IFCN (International Farm Comparision Network), Dairy Report for Albania
country page (2008), published by IFCN Dairy Research Centre Kiel/Germnay www.ifcndairy.org
Ilir KAPAJ (2007), IFCN (International Farm Comparision Network), Dairy Report for Albania
country page (2007), published by IFCN Dairy Research Centre Kiel/Germnay www.ifcndairy.org
Ilir KAPAJ (2006), IFCN (International Farm Comparision Network), Dairy Report for Albania
country page (2006), published by IFCN Dairy Research Centre Kiel/Germnay www.ifcndairy.org
Ilir KAPAJ (2006) Efekte socio-ekonomike të implemetimit të projektit të sekuestrimit të karbonit
(socio-economic efects of implementing carbon sequestration projects), Magazine of Albania
Agriculture(2006)
Ilir KAPAJ (2005): “Konkurueshmëria dhe avantazhet krahasuese të prodhimit të misrit në Shqipëri”,
Albania Agriculture , Tirana/Albania, September 2005.
Dr. Remzi KECO
Ph.D degree: March 2010
Master degree: June 2006
Skills and competencies: Agribusiness management; Farm management; Financial and Economic
Analysis Project management .
Scientific Publications:
Aspects of Developments in rural areas of Albania, Scientific Buletin, nr 11, 2005,Korca,Albania.
The Cooperation of Agricultural Services in the Trans-Boundary Regions, an Additional Possibility for
Environmental Friendly Agricultural Practices, Thessaloniki, Grecce December 2008.
Phytotoxicity of ten winter barley varieties and their competitive ability against corn poppy and ivyleaved speedwell Expl.Agric,Volume
44,Cambridge University Press; K. Dhima, I.Vasilakoglou, A.
Lithourgidis, E. Mecolari, R. Keco, I. Eleftherohorinos, 2008.
“The vertical integration in the industry of wine- What supporting policies shall be adapted”?.;
Mangment Agricol, Seria 1,Vol 9, Scientific Buletin, Romania. R. Keco; B. Musabelliu. 2009.
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