Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 DOI: 10.1515/orga-2015-0015 Multi-Criteria Assessment of Vegetable Production Business Alternatives Silvo Pozderec, Martina Bavec, Črtomir Rozman, Jožef Vinčec, Karmen Pažek University of Maribor, Faculty of Agriculture and Life Sciences, Pivola 10, 2311 Hoče, Slovenia. Corresponding author: kanTien.pazek@um.si Purpose: Organic and integrated production of vegetables are the two most common production systems in Slovenia. The study analyzed two production systems with different cultures as alternatives with purpose to find the most appropriate variants. Design/Methodology/Approach: The study based on the development and integration of developed specific technological-economic simulation models for the production of vegetables (salad, growing peppers, salad cucumbers, pickling cucumbers, round and cherry tomato) in greenhouse and multi-criteria decision analysis. The methodology of the study based on the DEX methodology and the analytical hierarchy process (AHP) of organic (ECO) and integrated production (IP) in greenhouse. Results: The evaluation results show that both cultivation methods of commercially attractive vegetables in greenhouse are variable. In the case of integrated production, the assessment of multi-criteria decision analysis EC and DEXi showed that salad (Donertie F1) proved to be the best possible alternative. In the case of organic production, the multi-criteria analysis assessment of pickling cucumbers (Harmony F1) is the best possible business alternative. Conclusion: For the further production planning process by decision maker is the ranking with Expert Choice (EC) more useful and precise, while the DEX evaluations are more descriptive. Keywords: simulation model; multi-criteria analysis; vegetable; greenhouse 1 Introduction Integrated decision support systems and costs studies for the cultivation of commercially attractive vegetables in greenhouse are not sufficiently explored, as can be seen from domestic and foreign literature. The preliminary information about expected costs and returns of the vegetable production in greenhouse is essential for further planning and conducting investments in greenhouses and the production of market-attractive vegetables in greenhouse. Based on a study of simulation models and the MCDA method carried out by Klajic (2000) and Skraba (2003), it is assumed that simulation modelling combined with MCDA methods could be useful applied for vegetable production decision support. In the field crop production, the modeling of sugar beet and its processing into sugar for purpose of decision support is presented by Rozman et al. (2014). The analysis system dynamics methodology was chosen to model impacts of regional sugar factory investment. Fur- ther, the model for decision - making in agriculture is presented by Cardin-Pedrosa and Alvarez-López (2012). The authors explain the process followed to generate the model used as a decision support tool for agricultural production planning in the most agrarian areas in Galicia. The model includes social, environmental and economic indicators developed using both monographic information and field data. Hayashi (2000) combined in agricultural resource management multi-attribute utility theory and goal programming method for solving multi-objective planning problems. The optimal input use condition in agricultural sector (water irrigation) is evaluating by multi-attribute utility and multi-attribute marginal utility by Gómez-Limón et al. (2004) and Riesgo and Gomez-Limon (2006). The similar problem is observed by Latinopoulos (2009). Pavlovic et al. (2011) emphasize the support by expert decisions for selection of hybrids in agriculture. The authors expose the amount of available data and the meth- Received: March 15, 2015; revised: May 27, 2015; accepted: June 21, 2015 203 Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 ods for describing performance of an individual cultivar. The data summarization process is often the major limitation associated with producers making a good decision. In this way, the AHP can be applied for assessing multifunctional performances of different agricultural systems in a comparative way to other multifunctional economic activities. Parra-Lopez et al. (2007) compare the multifunctional performance of alternative olive growing systems in Andalusia on the basis of the assessments of different groups of experts. Some examples of using the multi-criteria decision analysis for evaluation or classification of the most suitable sorts or cultivars can be found in literature (Bohanec et al., 2008, Jayakumar and Hari Ganesh, 2012, Mohamed et al., 2012, Dragincic et al., 2015). Hayashi (2000) states that the multi-criteria decision analysis in agriculture helps cope with the multitude of objectives and descriptive comments. Pavlovic et al. (2011) have developed a multifunctional decision making model called DEX-HOP for preliminary hop hybrid assessment. The research was done on common hop (Humulus lupulus, L.) since hop significantly contributes to the quality of flavour and aroma in beer. An overview of the use of multi-criteria decision analysis in the field of organic farming can be found in the study by Christensen et al. (2012). The authors assert that the production and usage of organic products affected the decision problems, characterised by different goals, namely whether the consumer, producer or politician was the main decision maker. Rozman et al. (2013) developed a model of system dynamics for the development of organic farming, which would support the government's decision-making process - a case study in Slovenia. Dragincic et al. (2015) used the methods of Simple Additive Weighting (SAW), AHP and Dong's et al. Cardinal consensus model to study the most appropriate variety of organic table grapes, which would affect the final production performance. The aim of the study is the development of technologic - simulation model for vegetable production in greenhouse and multi-criteria decision analysis for salad, growing peppers, salad cucumbers, pickling cucumbers, round and cherry tomato production. There are two emphasized goals: development of simulation model (i) and its application in combination with the DEX-i method and Analytical hierarchical process - AHP (Expert Choice (EC) software) on a presented vegetable production in greenhouse (ii). The research question that is followed in the paper is which the most suitable alternative by combining technological-economic simulation modelling and multi-criteria decision analysis in the cultivation of vegetables in greenhouse. 2 Methodology The essential concept of our study refers to the economics of integrated and organic production of six types of market-attractive vegetables (salad, growing peppers, salad cucumbers, pickling cucumbers, round and cherry tomato) in greenhouse. For this purpose, the first research phase included the development of individual technological-economic simulation models with pertaining calculations of total costs. These were practically acquired from the inventory of individual phases of the technological process of integrated and organic production of market-attractive vegetables in greenhouse. We are referring to the so called computer assisted deterministic technological-economic simulation models (Tamubula and Sinden, 2000). Multi-parameter decision-making, which is based on the decomposition of the main issue into smaller issues, was selected for the evaluation of production systems. The model is based on the DEX methodology (Bohanec et al., 2013) and the AHP analytical hierarchy process of organic and integrated vegetable production. The observed hierarchical problem structure include four main aspects, i.e criterion (the economic, developmental, technological and environmental criterion) which have an important effect on the individual vegetable production system in greenhouse. 2.1 The development of technological-economic simulation models For the purposes an integrated technological-economic deterministic simulation model that assesses the economic feasibility of production (Figure 1) were developed. The system comprises of interrelated mathematical-functional relations between technological and economic variables. By using designed individual models, the computer program calculates the technological parameters of a specific production, which forms the basis of the technological map. By calculating the total costs, data is automatically collected in a single developed simulation model and mathematical equations are performed which calculate specific economic parameters (revenues, financial result, break-even price and break-even point of production, cost price and the economic coefficient) depending on different input parameters (various inputs, prices, fertilizers, various products, areas, percentage of loss etc.). Model evaluated parameters represent the input data for the second phase of research work; development of a multi-criteria decision model based on the DEX method and the AHP analytical-hierarchy process of organic and integrated production of vegetables in greenhouse. 2.2 Multi-criteria decision model The DEX and AHP method are based on the process of restructuring an issue into smaller and less challenging sub-issues; that is it is based on the decomposition of the 204 Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 Figure 1: The structure of the developed simulation model main issue in the form of a hierarchy, where the structure of hierarchy is identical in both models. The differences between methods occur in measurement scales and in the methods of combining the criteria into the final result. The main issue is structured as a hierarchy, while the sub-issues or the interim concepts are illustrated with variables which we interconnect with a structure. The decision model for integrated and organic production of market-attractive vegetables in greenhouse is comprised of four main criteria on the primarily level and thirteen sub-criteria on the secondary level. The design of the decision model included a classical manual approach. The hierarchy of the decision model for integrated and organic production of six market-attractive vegetables in greenhouse is shown in Figure 2. 3 Results and discussion 3.1 Results of the simulation model for integrated and organic vegetable production in greenhouse The simulation model was developed on the basis of technological-economic data collected during the individual phases of the technological process of integrated and organic vegetable production in greenhouse. The model analysis has been performed in a greenhouse of one hectare for each individual vegetable. The calculation of individual parameters have been performed with the Microsoft Office Excel 2007 package which represents an electronic table that enables editing, automatic calculation and analysis of data. Using the developed specific model the computer program calculates the technological parameters of production which form the basis for the technological map with calculations of total costs (Figure 3). The developed model collects input data and performs mathematical equations which determine specific economic parameters (revenue, economic result, break-even price and point of production and the economic coefficient) depending on different input parameters (various inputs, prices, fertilizers, various products, areas, percentage of loss, etc.). All prices collected and included in the models are retail and wholesale prices with value added tax (VAT). To calculate the results we first had to gather the costs that occur during the year in the production of vegetables grown in an integrated and organic manner in greenhouse. The total revenue was calculated by multiplying the expected amount of produce of each individual production with the sales price of the product that was set according to realistic expectations. 205 Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 Figure 2: The hierarchy of the decision model for integrated and organic production of six market-attractive vegetables in green- 3.1.1 Economic analysis of integrated vegetable production In presented case the produced vegetables (growing peppers - Bianca F1, salad cucumbers - Darina F1, pickling tcucumbers - Harmony F1, round tomato - Amaneta F1, cherry tomato - Sakura F1 and salad - Donertie F1) were grown in five greenhouses. The production has taken place on five hectares (greenhouse 1/1 ha, greenhouse 2/1 ha, greenhouse 3/1 ha, greenhouse 4/1 ha, greenhouse 5/1 ha). The integrated production has been carried out according to the Rules on integrated production of vegetables (MKGP, 2010). As seen in Table 1, from economical point of view is the most suitable production of pickling cucumbers, followed by production of cherry and round tomato. Based on gained economic analysis is expected that ranking using both multi-criteria tool will be the same. 3.1.2 Economic analysis of organic vegetable production Organic vegetables (growing peppers - Vedrana F1, salad cucumbers - Dinero F1, pickling cucumbers - Harmony F1, round tomato - Rally F1, cherry tomato - Sakura F1 and salad - Noisette F1) were grown in five green houses. The production takes place on five hectares (greenhouse 1/1 ha, greenhouse 2/1 ha, greenhouse 3/1 ha, greenhouse 4/1 ha, greenhouse 5/1 ha). The organic production is carried out according to the Rules on organic production and processing of agricultural products and/or foods (MKGP, 2014). Compared to integrated production the economy coefficients by organic vegetable production are lower. The ranking of business alternatives is not equal (Table 1 and 2). Salad cucumbers and cherry tomato assess the same value of economy coefficient. The reason are higher sale price and quantity production in integrated production. Production of salad is in both observed alternatives on the last place (relationship between sale and break - even 206 a cs a. o a 3 o »9 S a, ^ 3 o a. o a a a, o a o = 3 o- 3 a' os a Salad cucumbers [produce ca. 300.000 kg/ha) Darin a F1 (80x40) /1 heap Costs Quantity Price/unit Total Varlablecosts Plants (piece) 24.000 0.24 5.760 Protective foil (kg) 530 2 1.160 Irrigation tubing T-tape (piece) 5 160 300 Ties for hanging plants (kg) 200 2.5 500 Clipsfor attaching (piece) 24.000 0.024 576 Packaging (piece) 40.000 0.75 30.000 Labels(piece) 40.000 0.009 360 Lime (kg) 2000 0.07 140 Organic 3:3:3 (kg] 700 0.225 153 Multicomp base 14:ll:234Me (kg) 350 0.77 270 Polyfeed ll:44:ll+Me (kg) 350 1.4 490 Polyfeed 16:S:324Me (kg) 200 1.5 300 Polyfeed 21:11:21+Me (kg) 200 1.5 300 Calciogreen 0:0:0:34 (kg) 250 3,2 2.050 Multi Ca 15:0:0:21 (kg) 1170 0,3 S 445 Multi K 13:0:46 (kg) 1000 1.2 1.200 Kendal (1) 23 13 364 Actiwave (1) 35 10 350 Megafol (1) 10 S SO Bumblebees (piece) 5 100 500 Soil analysis 1 150 150 Protective means 500 500 Total 46.451,60 € GROWING PEPPERS (IP) SALAD CUCUMBERS (IP) PICKLING CUCUMBERS (IP) a a- o = to o ] H 1 J K. L M ■ Produce 300.000 kg/ha Gross product 300.000 kg/ha Loss 0,00% Net product 300.000 kg Farm land 1 ha Sales price 0,55 £/kg COSTS €/ unit Quantity /ha € / ha Variable costs Plants (piece) 0.24 24.000 5.760 Protective foi 1 (kg) 2 580 1.160 Irrigation tubing T-tape (piece) 160 5 BOO Ties for hanging plants (kg) 2.5 200 500 Clips for attaching [piece) 0.024 24.000 576 Packaging (piece) 0.75 40.000 30.000 Labels (piece) 0,009 40.000 360 Fertilizers 5.352 Protective means 500 Biostimulator 794 Other material costs 650 Work costs - hired manual work 34.096 Contractual work 6.300 Potentially variable costs 44.500 Fixed costs and annual amortisation 7.S07 CHERRY TOMATO (IP) ROUND TOMATO (IP) SALAD (IP) iJT | T m m Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 Expected produce (t/ha) Sales price (€/ kg) Total cost (€) Revenue (€) Financial result (€) Break-even price of production (€/kg) Break-even point of production (kg) Cost price with subsidy (€/kg) Economy coefficient Growing peppers 150 0,85 106.219 127.500 21.281 0,71 124.963 0,71 1,20 Salad cucumbers 300 0,55 139.155 165.000 25.845 0,46 253.009 0,46 1,19 Pickling cucumbers 150 0,90 77.620 135.000 57.380 0,52 86.244 0,52 1,74 Cherry tomato 170 1,15 128.282 195.500 67.218 0,75 111.549 0,76 1,52 Round tomato 250 0,65 127.528 162.500 34.972 0,51 196.196 0,51 1,27 Salad 60 0,90 46.266 54.000 7.734 0,77 51.407 0,78 1,17 Expected produce (t/ ha) Sales price (€/kg) Total cost (€) Revenue (€) Financial result (€) Break-even price of production (€/kg) Break-even point of production (kg) Cost price with subsidy (€/kg) Economy coefficient Growing peppers 110 1,00 101.178 110.000 8.822 0,92 101.178 0,93 1,09 Salad cucumbers 200 0,75 122.768 150.000 27.232 0,61 163.691 0,62 1,22 Pickling cucumbers 90 1,50 100.606 135.000 34.394 1,12 67.071 1,13 1,34 Cherry tomato 120 1,20 118.137 144.000 25.863 0,98 98.447 0,99 1,22 Round tomato 150 0,90 114.106 135.000 20.894 0,76 126.784 0,77 1,18 Salad 35 1,20 40.202 42.000 1.798 1,15 33.502 1,18 1,04 Table 1: The economic analysis of integrated vegetable production Table 2: The economic analysis of organic vegetable production price). In the next chapter it is explained and presented the assessments of primary criteria and secondary sub-criteria of the developed multi-criteria decision model DEX and the AHP of individual vegetable productions alternatives in greenhouse. 3.2 Results of the DEX multi-criteria model 3.2.1 Results of the DEX multi-criteria model for integrated vegetable production According to the primary level of hierarchy of the DEX multi-criteria decision model, the assessment of integrat- ed vegetable production in greenhouses demonstrated that the best rated criterion was the "developmental criteria" (evaluated as excellent) and the "economic criteria" (evaluated as excellent) in the production of round tomatoes, and the "technological criteria" (evaluated as excellent) in the production of salad. The worst assessment was given to the "developmental criteria" (evaluated as bad) in the production of pickling cucumbers (Table 3). The final multi-criteria assessment of integrated vegetable production in greenhouse (Table 3) demonstrates that the production of growing peppers, salad cucumbers, cherry tomato, round tomato and salad is evaluated as good, while the production of pickling cucumbers is rated as acceptable. 208 Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 Table 3: The assessment of integrated vegetable production with the DEXi tool Option GROWING PEPPERS SALAD CUCUMBERS PICKLING CUCUMBERS CHERRY TOMATO ROUND TOMATO SALAD ASSESSMENT OF INTEGRATED VEGETABLE PRODUCTION good good acceptable good good good ECONOMIC CRITERION average average average average excellent average Financial result of production average average excellent excellent excellent average Produced quantity good high good good high average Market ways average excellent average bad excellent average DEVELOPMENT CRITERION average average bad average excellent excellent Relevance of production relevant potentially interesting potentially interesting potentially interesting very relevant very relevant Potential for creating new markets average excellent average bad excellent excellent Education of farmers average average bad bad average good Promotion of crops low low low good good good TECHNOLOGICAL CRITERION average average average average average excellent Sensitivity to diseases and vermin's average average average high low low Knowing the production technology average average average excellent excellent excellent Difficulty of the production technology high average average high high low ENVIROMENTAL CRITERION average average average average average average Protection of groundwater average average average average average bad Reduction of the use phytopharmaceuticals average average average average average high Possibilities of obtaining useful organism average good good good good bad 3.2.2 Results of the DEX multi-criteria model for organic vegetable production For organic vegetable production in greenhouses the best rated criteria proved to be the "developmental criteria" (evaluated as excellent) in the production of all types of vegetables, "environmental criteria" (evaluated as good) in all vegetables except salad and the "economic criteria" (evaluated as excellent) in the production of salad cucumbers. The worst assessment was given to the "technological criteria" (evaluated as bad) in the production of cherry tomatoes and the "economic criterion" (evaluated as bad) in the production of salad (Table 4). Further, the final assessment of organic vegetable production in greenhouses (Table 4) demonstrated that the production of growing peppers, salad cucumbers, pickling cucumbers and round tomatoes is evaluated as good, while the production of cherry tomatoes and salad is evaluated as acceptable. 3.3 Results of the AHP multi-criteria model 3.3.1 Results of the AHP multi-criteria model for integrated vegetable production The final assessment of integrated vegetable production in greenhouse (Figure 3) has demonstrated that the production of salad was evaluated as the best (EC = 0.253), followed by the production of round tomato (EC = 0.220), cherry tomato (EC = 0.163), growing peppers (EC = 0.125), salad cucumbers (EC = 0,121). 209 Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 As expected from the DEXi model results, the lowest evaluation was given to the production of pickling cucumbers (EC = 0.119). 3.3.2 Results of the AHP multi-criteria model for organic vegetable production The production of organic pickling cucumbers was evaluated as the best (EC = 0.215), followed by the production of growing peppers (EC = 0.201), round tomato (EC = 0.195), salad (EC = 0.179), salad cucumbers (EC = 0.112). Ats seen in previous figure, the lowest evaluation was given to the production of cherry tomato (EC = 0.098). However, as seen previous results there exist the differences by economical and multi - criteria assessment of vegetable production. 4 Conclusions For the purposes of our study we have developed an integrated technological-economic deterministic model, enabling the assessment of economic viability of six market-attractive vegetables (salad, growing peppers, salad cucumbers, pickling cucumbers, round and cherry tomato), produced in an integrated and organic manner in greenhouse. To help assess the production of vegetables in greenhouse we have developed a model based on the DEX method and the analytical hierarchy process (AHP) of Option GROWING PEPPERS SALAD CUCUMBERS PICKLING CUCUMBERS CHERRY TOMATO ROUND TOMATO SALAD ASSESSMENT OF INTEGRATED VEGETABLE PRODUCTION good good good acceptable good acceptable ECONOMIC CRITERION average average average average bad Financial result of production average excellent excellent excellent average bad Produced quantity good high good good high low Market ways excellent excellent excellent average excellent average DEVELOPMENT CRITERION excellent excellent excellent excellent excellent excellent Relevance of production Very relevant relevant Very relevant relevant Very relevant relevant Potential for creating new markets excellent average excellent average excellent average Education of farmers good average average average good good Promotion of crops high good high good high good TECHNOLOGICAL CRITERION average average average bad average average Sensitivity to diseases and vermin's average average average high average low Knowing the production technology average average average average average average Difficulty of the production technology high high high high High average ENVIROMENTAL CRITERION good good good good Good average Protection of groundwater high high high high high Good Reduction of the use phytopharmaceuticals high high high high high High Possibilities of obtaining useful organism good good good good good average Table 4: The assessment of organic vegetable production with the DEXi tool 210 Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 organic and integrated vegetable production. The assessment results demonstrate that both methods of producing market-attractive vegetables in greenhouse (integrated and organic production) are variable. In the case of integrated production the multi-criteria decision analysis assessment EC = 0.253 and DEXi evaluation = good showed that salad (Donertie F1) proved to be the best possible alternative. In the case of organic production the multi-criteria decision analysis assessment EC = 0.215 and DEXi evaluation = good showed that pickling cucumbers (Harmony F1) are the best alternative. In integrated vegetable production, the worst alternative proved to be the production of pickling cucumbers (Harmony F1), which received the multi-criteria decision analysis assessment EC = 0.119 and DEXi evaluation = acceptable. In organic production, the worst alternative proved to be cherry tomato (Sakura F1), which received the multi-criteria decision analysis assessment EC = 0.098 and DEXi evaluation = acceptable. Ranking alternatives (vegetables) with multi-criteria decision models DEX and AHP is basically the same. Further, unlike the DEXi decision model, where the criteria/sub-criteria are evaluated as the same in different alternatives, the Expert Choice Model also demonstrates more detailed differences in the calculation of total priority of a specific criterion/sub-criterion in individual alternatives. Therefore, ranking individual alternatives by using the AHP multi-criteria model is more accurate and makes it easier for the user to decide on an appropriate alternative. On the other site, the data availability required for used methodological approaches for defined alternatives can be a serious limitation in the planning process. However, the integrated system takes into consideration different independent objectives and enables ranking of different business alternatives. Further research could be made in combinations with the AHP resource allocation theory, where calculated priorities could be used for optimal allocation of business entrepreneurship resources at constrained investments; naturally, the AHP hierarchy should be changed correspondingly. The decision model should be also interrelated to the marketing informatio system (marketing attribute). ■jGoal: Assessment of integrated vegetable production Salad cucumbers Pickling cucumbers Cherry tomato Round tomato Salad Economic criterion (L: ,288) ^financial result of production (L: ,667) H produced quantity (L: ,111) m market ways (L: ,222) Environmental criterion (L: ,074) protection of groundwater (L: ,691) □ reduction of the use of phytopharmaceuticals (L: ,218) □ possibilities of obtaining useful organisms (L: ,091) Developmental criterion (L: ,249) * relevance of production (L: ,112) ■ potential for creating new markets (L: ,074) H education of farmers (L: ,475) ^ promotion of crops (L: ,339) "Technological criterion (L: ,389) □ sensitivity to diseases and vermins (L: ,085) knowing the production technology (L: ,644) □ difficutly of the production technology (L: ,271) Figure 3: Final assessment of integrated vegetable production with the AHP tool Growing peppers i ,125 ,121 ,119 ,163 ,220 ,253 Information Document 3Goal: Assessment of organic vegetable production Developmental criterion (L: ,249) □ relevance of production (L: ,095) □ potential for creating new markets (L: ,061) 3 education of farmers (L: ,500) □ promotion of crops (L: ,343) Economic criterion (L: ,288) ^financial result of production (L: ,667) □ produced quantity (L: ,111) 9 market ways (L: ,222) Environmental criterion (L: ,074) □ protection of groundwater (L: ,680) □ reduction of the use of phytopharmaceuticals (L: ,211) □ possibilities of obtaining useful organisms (L: ,109) b H Technological criterion (L: ,389) □ sensitivity to diseases and vermins (L: ,075) □ knowing the production technology (L: ,673) □ difficutly of the production technology (L: ,251) Pickling cucumbers Growing peppers Salad cucumbers Cherry tomato Round tomato Salad Figure 4: Final assessment of organic vegetable production with the AHP tool ,201 ,112 ,215 ,098 ,195 ,179 Information Document 211 Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 References Bohanec M., Rajkovic V., Bratko I., Zupan B. & Znidarsic, M. 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Multi-criteria policy scenario analysis for public regulation of irrigated agriculture. Agricultural Systems, 91(1-2), 1-28, http://dx.doi.org/10.1016/j.agsy.2006.01.005 Rozman Č., Škraba A., Pažek K. & Kljajic M. (2014). The development of sugar beet production and processing simulation model: a system dynamics approach to support decision-making processes. Organizacija, 47(2), 99-105, http://organizacija.fov.uni-mb.si/index.php/ organizacija/article/view/563 Rozman Č., Pažek K., Kljajic M., Bavec M., Turk J., Bav-ec F., Kofjač D. & Škraba A. (2013). The dynamic simulation of organic farming development scenarios - A case study in Slovenia. Computers and Electronics in Agriculture, 96, 163-172, http://dx.doi.org/10.1016/j. compag.2013.05.005 Škraba A., Kljajič M., & Leskovar R. (2003). Group exploration of system dynamics models - is there a place for a feedback loop in the decision process? System Dynamics Review, 19(3), 243-263. Tamubula I. & Sinden J.A. (2000). Sustainability and Economic Efficiency of Agroforestry Systems in Embu Distict, Kenya: An Application of Environmental Modelling. Environmental Modelling and Software, 15(1), 13-21. 212 Organizacija, Volume 48 Special Theme: Simulation Based Decision Making Number 3, August 2015 Silvo Pozderec is a PhD student of Agricultural Economics at Faculty of Agriculture and Life Sciences at University of Maribor. His research priorities are technological-economic simulation modelling and multi-parameter decision modelling in agriculture. Martina Bavec is full professor of vegetable and field crops and organic agriculture at the University of Maribor, Slovenia. She has been an advisor for vegetable production and organic farming, as well as the main supporter for establishing a national inspection and certification body for organic agriculture. She has led many national and international projects, edited the main national book about organic agriculture, and authored and co-authored 43 research papers, and numerous professional papers. She is a very active presenter of organic agriculture in the community and a key representative of the BSC, MSc, and PhD study programs of organic agriculture at the university where she teaches. She is the co-author of a book »Organic production and Use of Alternative Crops" published by Taylor and Francis CRC Press. From March 2012 to July 2013 she worked on Ministry of Agriculture and the Environment as general Director of Directorate for agriculture being responsible beside daily work also for preparation of draft for Rural development program and decisions basis for pillar I. Črtomir Rozman achieved his Ph.D. at University of Maribor, Faculty of Agriculture. He is active as Full Professor for Farm management in the Department for Agriculture Economics and Rural Development (Faculty of Agriculture and Life Sciences, University of Maribor). His research includes development of decision support systems for farm management (simulation modeling, multi-criteria decision analysis, machine learning) and economics of agricultural production. He is also involved in teaching activities as Head of Department and as thesis supervisor at post graduate study programs and multiple national and international research projects. He is author or coauthor of 67 scientific papers including 28 papers in journals with impact factor. Jožef Vinčec is a PhD student of Agricultural Economics at Faculty of Agriculture and Life Sciences at University of Maribor. His research priorities are Operational research in agriculture and simulation modelling. Karmen Pazek achieved her Ph.D. at University of Maribor, Faculty of Agriculture in 2006. She is active as Associated Professor for Farm management in the Department for Agriculture Economics and Rural Development on Faculty of Agriculture and Life Sciences, University of Maribor. Her research includes development of decision support tools and systems for farm management (simulation modeling, multi-criteria decision analysis, option models) and economics of agricultural production. She is involved in teaching activities as thesis supervisor at postgraduate study programs and involved in national and international research projects. She is author or coauthor of 45 scientific papers including 20 papers in journals with impact factor. Več-kriterijska ocena poslovnih alternativ pridelave zelenjave Namen: V Sloveniji sta ekološki in integriran način pridelave zelenjave med najpomembnejšimi proizvodnimi sistemi. Študija predstavlja analizo dveh proizvodnih sistemov, ki vključujeta pridelavo različnih zelenjadnic. Namen raziskave je več-kriterijska ocena najprimernejše poslovne alternative. Struktura/Metodologija/Pristop: Raziskava temelji na razvoju in povezavi specifičnih tehnološko-ekonomskih simu-lacijskih modelov za pridelavo zelenjave (solate, paprike, solatnih kumar, kumar za vlaganje, okroglega paradižnika in grozdastega paradižnika) v zaščitenem prostoru in več-kriterijski odločitveni analizi. Podlaga raziskavi je metodologija DEX in analitični hierarhični proces (AHP) za ekološko (EKO) in integrirano pridelave (IP) omenjenih zelenjadnic. Rezultati: Rezultati vrednotenja kažejo, da sta za pridelovalca spremenljiva oba načina pridelave tržno zanimivih zelenjadnic v zaščitenem prostoru. Pri integrirani pridelavi se je z oceno večkriterijske odločitvene analize EC in DEXi solata (Donertie F1) izkazala za najboljšo možno alternativo. Pri ekološki pridelavi so se kot najboljša možna alternativa izkazale kumare za vlaganje (Harmony F1). Zaključki: Za nosilca odločanja in lažje načrtovanje proizvodnje zelenjadnic v rastlinjaku je tako rangiranje na osnovi EC bolj natančno in koristno kot rangiranje s pomočjo DEXi orodja. Ključne besede: simulacijsko modeliranje, več-kriterijska analiza, zelenjava, rastlinjak 213