How to develop saffron business clusters in Iran

Como desenvolver clusters empresariais saffron no Irã

Abstract

The aim of the current research was to create a framework for the development of saffron commercial clusters in South Khorasan province. This research is quantitative and a questionnaire was used to conduct it. 987 managers, assistants and marketers of saffron processing workshops and saffron sales centers of saffron commercial clusters in South Khorasan constitute the statistical population of the research. 278 people were used as a sample population in the table of Karjesi and Morgan in 1970, and a questionnaire was used to collect the necessary data. The data were analyzed using descriptive and inferential statistical indices, structural equation analysis and SPSS and SEM-PLS software packages. The inferential findings of the research showed complete agreement between the theoretical and experimental constructs and the measured factors with the accepted theoretical models. The results of data analysis indicate that economic and social factors had a positive effect on the level of development at the 95% confidence level. On the other hand, in the economic variable, the item “commercialization of saffron product” is the first priority and the item “transportation, packaging, marketing costs of saffron product” is the last priority, and also in the variable of social factors, the item “innovation motivation for saffron product producers” “in the first priority and the item “riskiness of investment for saffron product” is in the last priority. In addition, the variables of the research model account for about 68% of the changes in the level of development of commercial clusters in South Khorasan.

Keywords:
modeling; development; business clusters; saffron; South Khorasan province

Resumo

O objetivo da pesquisa atual foi criar um quadro para o desenvolvimento de clusters comerciais de açafrão na província de Khorasan do Sul. Esta pesquisa é quantitativa e foi utilizado um questionário para realizá-la. Um total de 987 gerentes, assistentes e comerciantes de oficinas de processamento de açafrão e centros de vendas de açafrão de clusters comerciais de açafrão em Khorasan do Sul constituem a população estatística da pesquisa. Um total de 278 pessoas foram utilizadas como amostra populacional na tabela de Karjesi e Morgan em 1970, e um questionário foi usado para coletar os dados necessários. Os dados foram analisados por meio de índices estatísticos descritivos e inferenciais, análise de equações estruturais e pacotes de software SPSS e SEM-PLS. Os resultados inferenciais da pesquisa mostraram total concordância entre os construtos teóricos e experimentais e os fatores medidos com os modelos teóricos aceitos. Os resultados da análise dos dados indicam que os fatores econômicos e sociais tiveram um efeito positivo no nível de desenvolvimento em 95% de confiança. Por outro lado, na variável econômica, o item “comercialização do produto açafrão” é a primeira prioridade, e o item “custos de transporte, embalagem, comercialização do produto açafrão” é a última prioridade, e também na variável de fatores sociais, o item “motivação para a inovação dos produtores de produtos de açafrão” é a primeira prioridade e o item “risco de investimento no produto de açafrão” está na última prioridade. Além disso, as variáveis do modelo de pesquisa respondem por cerca de 68% das mudanças no nível de desenvolvimento dos clusters comerciais em Khorasan do Sul.

Palavras-chave:
modelagem; desenvolvimento; clusters comerciais; açafrão; província de Khorasan do Sul

1. Introduction

Today, in most countries of the world, especially developing countries, small and medium enterprises play a role in various economic, social, production and service dimensions. Despite the fact that these enterprises participate in more than 90% of economic activities, but due to cumbersome regulations and the lack of a comprehensive development strategy, they have not been able to allocate a significant share of the GDP (Medvedev, S. (2019).

A significant part of economic activities in the world is carried out by small and medium-sized companies, and governments always support these companies. Clusters as a business structures can play a role in economic development of countries (Wonglimpiyarat and Chandrachai, 2016).

One of the approaches that has been able to play a significant role in the development of small an medium industries based on the experiences of different countries is the development of business clusters. These clusters can play an important role in regional development Hwang et al. (2019).

A business cluster is an active group with a business orientation that is concentrated in one location, complement one another's efforts, and faces similar difficulties and possibilities (Musso and Francioni, 2015; ISIPO, 2015). Business units that are present in clusters benefit from a variety of factors, such as increased productivity, business specialization, cost reduction, access to common resources and benefits, market access, and shared information (Paraušić et al., 2013; Hoffmann et al., 2014). The advantages are the outcome of business connections and cooperation within the cluster as well as the infrastructure that is made available to enterprises working there (Pop Zan and Deangizan, 2008; Jin et al., 2012).

Small business enterprises such as clusters with the support of the government and universities can contribute to the economic development by strengthening competitiveness, developing innovation and providing opportunities for collective learning (Gureva et al., 2016).

The pattern of organizing small and medium enterprises, including business clusters, has been determined as one of the regional economic development strategies since three decades ago. The consequences of this strategy have been to improve the employment situation and increase per capita income based on the capabilities of these regions (Hakim and Perdana, 2017).

The role of business clusters in increasing competitiveness is undeniable. Export-oriented countries are trying to not only help increase productivity by developing industrial clusters, but also gain a larger share of world markets (Raines, 2017).

Hikmat et al. (2016) investigate the influence of individual characteristics, policy-making, infrastructural, economic, social, managerial, and educational factors on marketing innovation of date business clusters in the Khuzestan Province. Based on the results of this study, five variables of policy-making, educational, social, economic, and management factors interactively explained 83.3% of the changes in the marketing innovation of date business clusters.

1.1. Research background

Mollashahi et al. (2017) presented a study entitled “Effective factors on the success of small and medium-sized agricultural and horticultural businesses in Zabul city”. The results of the research showed that the agricultural work experience of the managers of these businesses, the amount of loan received for building the business, the educational level of the manager, the age of the manager, the number of workers employed in the business, the distance from the business to the city, and the amount of cultivated area had a significant effect on the success of these businesses.

Nazari et al. (2017) stated that one of the effective strategies for the economic development of clusters is to establish networks. In fact, most of the cluster are small and micro size enterprises, and they should try to overcome their limited financial resources and knowledge through network activities.

Paraušić et al. (2017) in examining the relationship between economic development and the cluster development indicated that the state of cluster development in national economies is different depending on the stage of economic development. It was concluded that clusters could improve economic development and national competitiveness, especially in emerging markets and developing economies.

Using empirical methods, Kashirskaya et al. (2019) presented guidelines for the formation and development of agro-ecological clusters for the production, processing and sale of organic products in agricultural regions of Russia. According to the results, the production and development of the domestic market of organic products in the form of organic agricultural clusters is one of the strategic solutions for the implementation of reforms in the agricultural sector.

Zeng et al. (2019) indicated that the formation of agricultural e-commerce clusters includes four processes of technology introduction, technology diffusion, quality crisis, and industrial agglomeration based on elements such as industry foundations, e-commerce platforms, network facilities, entrepreneurial talents, government regulations, and market demand. The results also show that such projects have positive implications for the development of the agricultural sector and related businesses.

Joffre et al. (2019) in a research about role clusting in adoption of aquaculture practices, concluded that the implementation of the clustering approach of shrimp farms in the Mekong Delta in Vietnam increases the role of farmers in the value chain. It was also reported that agricultural clusters have a positive effect on the adoption of aquaculture practices.

1.2. Role of the cluster approach

In a study about the role of the cluster approach in the development of regional agricultural complexes, the main factors affecting the activity of the meat cluster in the region have been identified. The results show that regional economic clustering has implication in the growth of production efficiency only through the formation of a regional cluster (Okutaeva et al., 2018).

A network model of cluster economy is presented based on the cooperation between small and medium enterprises and suppliers of agricultural raw materials, which allows all actors (business units) of the cluster to participate in the development and formulation of strategy in the cluster (Zharikov et al., 2018)

Madureira et al. (2018) in a research about agricultural clusters in the field of fruit production in Portugal, pointed out that these clusters can play an important role in the production of knowledge and innovation in areas where there are small farms.

Ramirez et al. (2018) by using network theory pointed out that the dynamics of local social capital has a significant impact on different forms of cluster development. It was also found out that by using mixed methods, the relationship between between networks and social capital can be expained (Ramirez et al., (2018).

In a study about using clustering to increase the share of farmers' markets in the local food economy and improve their management in California, results show that the existing clustering behavior in agricultural markets can strengthen the role of these markets in the local food economy. There is also a positive relationship between knowledge sharing (as a cluster activity) and financial activity integration among agricultural product sellers, which highlights an interesting dynamic that results from the temporary nature of these clusters (Kassai et al., 2018).

Based on the report by country’s management and planning organization, more than 40 percent of employrment in the country is depend upon SMEs One of the challenges facing the small and medium size enterprises in South Khorasan province, is how to improve the performance of these enterprises (Khatami Firouzabadi et al., 2019).

1.3. Coverage for this study

The South Khorasan is located in the eastern part of the country. The area of this province is 151,193 square kilometers, which is the third largest province in Iran (Figure 1). According to the 2015 census, its population is equal to 768,898 people, and in this respect, it is the 28th province of the country.

Figure 1
Map of South Khoirasan province.

Based on the report by the Ministry of Agriculture, more than 90% of the world production of saffron is produced in Iran, in nthe two provinces of Khorasan Razavi and South Khorasan.

Meanwhile, South Khorasan province ranks first in saffron production in Iran and the world, but its value creation share on this product is less than 10%. In fact, in the current structure, most of the saffron products are sold raw and are processed by other countries.

According to the Statistics and Information Technology Department of the Agricultural Jihad Organization of South Khorasan Province, there are about 16,807 hectares of saffron cultivation in the province, which produces 67 tons of saffron. However, according to the statistics of South Khorasan Province Customs Department (2018) only about 50 kg of saffron is directly exported from the borders of South Khorasan Province, which is a very significant figure (Table 1).

Table 1
The area under cultivation, the amount of production and the national ranking of agricultural products of the province in 2016.

Narcissus flower	Almonds	Pomegranate	Pistachio	Cotton	Saffron	Jujube	Barberry	Product name
3101	9602	4371	19822	7615	15782	3218	15562	Area hectares
18005600 Branch	5773	25163	15427	15230	54	5439	19095	Production amount tons
5	9	8	6	4	2	1	1	National rank

According to the information in the Table 2, the most cultivated area among the products is barberry, jujube, saffron, and cotton.

Table 2
Statistics of manufacturing clusters in South Khorasan, Iran.

Place of concentration of the introduced cluster: most of the villages of South Khorasan province

Estimated number of cluster units: more than 5000 manufacturing and processing companies

According to the information available in the province's databases, currently about 82,896 people are directly working in the saffron production sector in the South Khorasan Province. It was also reported that more than 5000 clusters are active in production and processing of saffron in this province.

The production and trade of saffron in our country has faced various ups and downs in recent decades, for example, the average production of 5 to 6 kilograms of product per hectare in the 50s to 60s dropped to less than 4 kilograms per decade. 70s to 80s shows the fact that the reasons for this lack of performance should be addressed, while in the last few years, the land under saffron cultivation has multiplied in areas with good quality land and plenty of water, but the reason for the lack of production is The truth has not been researched, although more and more precision to produce a product equal to the customer's demand has been the main concern of the producers, but the decrease in performance has always been compensated by increasing the area under cultivation and more resources have been spent to respond to the market's needs.

Based on the executive plan regarding the identification of production obstacles in South Khorasan province in 2017, it has been determined that more than 70% of the manufacturing and agricultural enterprises in the province have sufficient human resources and the problem of most of them is the provision of financial resources.

Perhaps the biggest problem in micro and small industries active in the production and sale of saffron products in the province (and even the country) is the lack of integrated structures for supply, production management, distribution and sales management. According to the statistics published by the customs office of South Khorasan province, despite the production of more than 50 tons of raw saffron in this province, only about 150 kilograms of export from the borders of the province have been recorded (Mirfardi et al., 2017).

According to the surveys conducted in the province, about 4 types of saffron enter the market, the price difference of which is nearly 2 times in other markets of the country. In fact, the added value of the raw product was 100% only due to the transfer to other provinces of the country, unfortunately, the farmers did not get a share of this profit and the local brokers and middlemen are the main stakeholders of this price increase. It should be noted that according to the statistics published by the Department of Industry, Mines and Trade, the increase in the value of the raw saffron product in the countries of origin of the export of this product is about 10 times, and again the farmers did not benefit from it and this profit went to the pockets of dealers. It can be According to the opinion of the development agents of the business clusters of the province and the academic community, one of the main reasons for the existence of such conflicts in the province is the lack of structured communication. Cluster design as well as its development can be used as an important tool in this field (South Khorasan Province Industrial Towns Company, 2013). This study aims to determine the factors that affect the development of cluster for saffron producers in South Khorasan Province, Iran.

1.4. Conceptual framework

In this research, according to the literature review, six factors affecting the development of cluster for saffron were extracted. Based on the conceptual model of the research, socio-cultural, educational, economic, technical, managerial, nvironmental and policymaking factors affected the development of business cluster for saffron (Figure 2).

Figure 2
Conceptual Framework.

The main purpose of this study was to identify the components of the optimal model for the development of business cluster for saffron in South Khorasan Province. The specific objective was to identify the educational, socio-cultural, economic, technical, policymaking, manageria; and environmental factors affecting the development of business cluster.

2. Materials and Methods

The present study is non-experimental in terms of the control of variables, and the method of data collection is survey type. This research, which was carried out using a questionnaire and in-person interviews, is quantitative in form, is deemed applicable research in terms of its objective, and is a kind of causal research. The 987 managers, assistants, and marketers of the saffron processing workshops and saffron sales outlets of the saffron business clusters in South Khorasan make up the statistical population of the study. 278 people were used as the sample population in Krejcie and Morgan's 1970 table (Krejcie and Morgan, 1970), and a questionnaire was used to gather the necessary data.

The validity of the data collection tool was evaluated by an expert panel (Mathew et al., 2011). In this way, a researcher-made questionnaire presented to the faculty members from the department of agricultural development, extension, and agricultural education, as well as researchers and experts who have opinions on saffron. They were asked to respond to the questionnaire's questions in writing. An updated questionnaire was created for reliability testing after obtaining feedback and addressing corrections.

For each questionnaire dimension, Cronbach's alpha coefficient was utilized to assess the questionnaire's reliability. The Cronbach's alpha scale has a flexible range from 0 to 1. The more closely the alpha coefficient approaches one, the more reliable the questionnaire is. In general, it can be argued that the reliability of the questionnaire is validated if the Cronbach's alpha on each dimension is more than 0.7 (Rajaei et al., 2011). Table 3 summarizes the reliability of the research questionnaire results. As can be observed, Cronbach's alpha coefficient exceeded 0.7 for all questionnaire dimensions.

Table 3
The results of the reliability of the main scales of the questionnaire applying Cronbach's alpha test.

Scales	Number of Items	Cronbach's Alpha Coefficient
Economic	9	0.713
Managerial	6	0.764
Educational	5	0.838
Socio-cultural	5	0.766
Technical	6	0.832
Political	10	0.780
Development	5	0.886

A comprehensive method for testing theories on the connections between observable and latent variables in structural equation modeling. Using correlational and non-experimental data, this method can be used to determine whether theoretical theories are acceptable in a certain community. Additionally, multivariate analysis is one of the most effective and useful techniques for analysis in the study of organizational issues, management, and social and behavioral sciences. In this study, the data was examined using SPSS₂₂ software after validation and reliability analysis, and structural equation modeling was performed using SEM-PLS software. The fit of the measurement model and the research structure was assessed using the chi-square indices ($X^2$), the Goodness of Fit Index (GFI), the None-Normed Fitness Index (NNFI), the Increasing Fitness Index (IFI), the Normed Fitness Index (NFI), the Comparative Fit Index (CFI), the Root Mean Square Error of Approximation (RMSEA), and the Standardized Root Mean Square Residual (SRMR). Furthermore, because there is no set threshold (criterion) for these indicators, the literature has suggested the following general guidelines: model fit is appropriate and acceptable if the value of $X^2$ is not significant, the values of the GFI, NNFI, IFI, NFI, and CFI indicators are higher than 0.9, the value of RMSEA is less than 0.8, and the value of SRMR is less than 1.0 (Lai et al., 2014).

3. Results and Discussion

3.1. Descriptive statistics

According to the research's findings based on the respondents' ages, the groups 51 years and older and less than 30 years had, respectively, the highest and lowest percentages. Male respondents made up the majority of the sample in terms of gender. For education, respondents with a bachelor's degree had the largest abundance of 138 (49.5%), while respondents with a diploma or less had the lowest abundance of 23 (8.5%). Additionally, managers had the largest abundance of 130 (46.8%) across all occupations, while salespeople had the lowest abundance of 27 (9.7%). Table 4 displays the results from the descriptive statistics.

Table 4
Description of the individual and professional characteristics of the sample under study.

Variables		Number of Sample	Percentage	Cumulative Percentage
Age (years)
	Less than 30	40	14.4	14.4
	Between 31 and 40	72	25.9	40.3
	Between 41 and 50	69	24.8	65.1
	More than 51	97	34.9	100.0
Education
	High school diploma or less	23	8.3	8.3
	Associate Degree	63	22.7	31.0
	Bachelor Degree	138	49.6	80.6
	Master Degree	54	19.4	100.0
	Ph.D.	0	0	100.0
Gender
	Male	243	87.4	87.4
	Female	35	12.6	100.0
Marital Status
	Married	244	87.8	87.8
	Single	34	12.2	100.0
Occupation
	Manager	130	46.8	46.8
	Marketer	66	23.7	70.5
	Employee	55	19.8	90.3
	Salesperson	27	9.7	100.0

3.2. The rate of saffron business clusters development

According to the respondents' rankings of the factors affecting the development of saffron business clusters in South Khorasan, the factor “production capacity of the Saffron business cluster” is ranked highest, while the factor “employment potential of the Saffron business cluster” is ranked lowest (See Table 5). The conditions of business clusters in South Khorasan are suitable, as evidenced by the assessment of the level of development of the business clusters there, which reveals that 87.8% of them have a reasonable level (Table 6 contains the relevant data).

Table 5
Prioritization of items based on South Khorasan’s level of saffron business cluster development.

Item	Average	Standard Deviation	Dispersion Coefficient	Priority
Production capacity of the Saffron business cluster	4.78	0.46	0.096	1
History of saffron business cluster-affiliated workshops activations	4.78	0.49	0.103	2
Export potential of the Saffron business cluster	4.68	0.53	0.113	3
Technology level in workshops connected to the saffron business cluster	4.29	0.56	0.131	4
The employment potential of the Saffron business cluster	4.46	0.59	0.132	5

Table 6
The South Khorasan province's level of saffron cluster business development.

Development Level	Number of Persons	Percentage	Cumulative Percentage
Very Inappropriate	0	0.0	0.0
Inappropriate	0	0.0	0.0
Relatively Appropriate	9	3.2	3.2
Appropriate	25	9.0	12.2
Totally Appropriate	244	87.8	100.0
Sum	278	100.0	-

3.3. Analysis of structural equations

In this section, a structural model was employed, and the results of its application are shown in Tables 7 and 8. This model was used by the causal effects in the conceptual model of the research to significantly study the effect of each of the main latent variables and also rank these variables based on their impact on the development of saffron business clusters.

Table 7
Standard estimates and significant level of path coefficients of items relating to the development of business clusters and social and educational subscales.

Factors		Symbol	Standardized Coefficient *	t-value	Result
Economic	Providing workshops connected to the saffron business cluster with facilities and bank loan terms	a1	0.572	1.977	Significant
	Retail costs and saffron product market volatility	a2	0.631	3.074	Significant
	Market changes and wholesale costs for saffron products	a3	0.550	2.655	Significant
	Transport, packaging, and marketing costs for saffron products	a4	0.512	2.544	Significant
	wages for all saffron-related jobs, from collection to packing	a5	0.633	3.578	Significant
	Commercialization of the saffron product	a6	0.830	6.102	Significant
	Saffron business cluster and network for product distribution	a7	0.811	5.077	Significant
	Government subsidies are given in the saffron industry in terms of money, credit, and support	a8	0.801	5.181	Significant
	Saffron industry policies for attracting capital	a9	0.778	4.939	Significant
Managerial	Innovativeness of workshop managers connected to the saffron industry cluster	b1	0.475	2.070	Significant
	Acquiring the required permits to expand the saffron business	b2	0.464	2.060	Significant
	Managers of workshops connected to the saffron industry cluster have a propensity to learn	b3	0.628	2.624	Significant
	In touch with workshop directors and administrators of relevant organizations	b4	0.789	2.468	Significant
	Innovation in the development of saffron business cluster strategy	b5	0.659	2.195	Significant
	Interaction between management and staff of Saffron Business Cluster affiliated workshops	b6	0.808	2.329	Significant
Political	Plans at the national and provincial levels in the saffron industry	c1	0.780	3.860	Significant
	Regulations and legislation (such as product export laws, etc.)	c2	0.883	6.301	Significant
	Bureaucracy or administrative bureaucracy (such as obtaining the necessary permits, etc.)	c3	0.895	6.309	Significant
	The implementation of market-wide competitive policies for saffron	c4	0.766	4.227	Significant
	Implementation of export incentives in the saffron market	c5	0.717	3.576	Significant
Socio-cultural	Cultural education regarding the position of saffron in the food basket for the home	d1	0.490	2.041	Significant
	Risky investment for saffron product	d2	0.348	1.983	Significant
	Inspiration for saffron producers to innovate	d3	0.864	2.159	Significant
	Acceptance of new products in the community as a culture (for example, saffron syrup, etc.)	d4	0.845	2.129	Significant
	Participation of members in the development of the saffron business cluster	d5	0.852	2.172	Significant
Technical	How much saffron is produced in the province	e1	0.740	2.258	Significant
	Acceptance of novel techniques from saffron cultivation to packaging	e2	0.672	2.247	Significant
	Having a stable financial strategy for the saffron product	e3	0.875	2.890	Significant
	Decreasing demand for water for Saffron onions	e4	0.341	2.080	Significant
	Saffron products' heat, insect, and disease resistance	e5	0.347	1.990	Significant
	Adaptability to the South Khorasan region's lands	e6	0.179	2.030	Significant
Educational	Workshops' state of expertise and training in marketing	f1	0.365	2.013	Significant
	Information obtained via radio and television and other forms of mass media	f2	0.433	2.423	Significant
	Using saffron industry experts as advisors and creating byproducts	f3	0.439	2.264	Significant
	Benefiting from experienced saffron merchants	f4	0.713	2.332	Significant
	Using online networks to market saffron-related products	f5	0.598	2.521	Significant
	Organizing exhibitions both at home and abroad to showcase saffron products	f6	0.589	2.525	Significant
	Entrepreneurial abilities of workshop managers connected to the saffron business cluster	f7	0.584	2.395	Significant
	Holding lectures and leading educational tours for example saffron farms	f8	0.843	2.180	Significant
	Holding specialized workshops and educating investors on the capacity of saffron	f9	0.588	2.060	Significant
	Correct knowledge of saffron export and production among cluster members	f10	0.811	1.980	Significant
Development	Production capacity of the saffron industry cluster	g1	0.641	5.100	Significant
	Potential for employment in the saffron business cluster	g2	0.766	7.690	Significant
	Export potential of saffron business cluster	g3	0.845	19.620	Significant
	History of saffron business-affiliated workshops activations	g4	0.767	8.183	Significant
	Technology level in the saffron business cluster's workshops	g5	0.827	8.233	Significant

• ^*
  The level of significance is reported in Figure 3.

Table 8
Results of the fitting model’s degree of compliance with the fitting indices.

Fitting Indices	Proposed Criteria	Value
Chi-Square / Degree of Freedom (relative chi-Square)	Less than 3	2.63
Comparative Fit Index (CFI)	Greater than or equal to 0.90	0.95
Goodness of Fit Index (GFI)	Greater than or equal to 0.90	0.92
Normed Fitness Index (NFI)	Greater than or equal to 0.90	0.94
None-Normed Fitness Index (NNFI)	Greater than or equal to 0.90	0.94
Increasing Fitness Index (IFI)	Greater than or equal to 0.90	0.96
Standardized Root Mean Square Residual (SRMR)	Less than 0.08	0.059
Root Mean Square Error of Approximation (RMSEA)	Less than or equal to 0.08	0.061

Standard estimates of path coefficients and latent variable variances are included in Table 7, which contains the study's final structural model. As can be observed, the variances of the independent and dependent variables are always significant, which is a justification for the model's validity. In general, the measurement error decreases as the shared variance between a latent variable and an observable variable increases. All standard path coefficients display the proper results, as indicated in Table 7. Additionally, Figure 3 depicts the structural equation that was calculated.

Figure 3
Structural equation model of research (***means significant at the level of 0.001, **means significant at the level of 0.01, *means significant at the level of 0.05).

The indicators of CFI, GFI, NFI, NNFI, and IFI are higher than the recommended value of 0.9 based on the findings of this study, which are presented in Table 8. The RMSEA had a value of 0.061, and the SRMR was 0.059. It can be argued that research variables such as socio-cultural and educational factors determining the degree of business cluster formation in South Khorasan associated with saffron give an effective model. The research's conclusions about the GFI revealed that, despite the suggested corrections, the estimated model still has an acceptable GFI.

A summary of the outcomes for testing the research hypotheses is shown in Table 9 in addition to the results above. The findings demonstrate that all research hypotheses were confirmed, indicating that the dependent variable was positively and significantly impacted by socio-economic, managerial, educational, socio-cultural, technical, and political factors. The educational and socio-cultural factors, when compared to other factors, had a stronger impact on the development of saffron business clusters in South Khorasan, according to the standard coefficient, which measures the strength of their effect. Additionally, the components already included in the research model have contributed to the explanation of around 68% of the variation in the amount of saffron-related business cluster development in South Khorasan.

Table 9
Conclusions from testing research hypotheses.

Hypotheses	Standardized Coefficients (direct effect)	t-value	Result
The level of development of South Khorasan's saffron-related business clusters is significantly influenced by economic factors.	0.114*	2.089	Confirmed
The level of development of South Khorasan's saffron-related business clusters is significantly influenced by managerial factors.	0.389**	7.109	Confirmed
The level of development of South Khorasan's saffron-related business clusters is significantly influenced by educational factors.	0.367**	5.684	Confirmed
The level of development of South Khorasan's saffron-related business clusters is significantly influenced by socio-cultural factors.	0.302**	4.738	Confirmed
The level of development of South Khorasan's saffron-related business clusters is significantly influenced by technical factors.	0.117*	2.414	Confirmed
The level of development of South Khorasan's saffron-related business clusters is significantly influenced by political factors.	0.298**	4.862	Confirmed

• The value of R-squared for all investigated hypotheses was 0.68.
• ^*
  Significant at 5% level;
• ^**
  Significant at 1% level.

4. Conclusions

The development of related industries is crucial and required to go along with the development of saffron production in South Khorasan. Saffron-related industries are referred to as complementary and conversion industries in the agricultural sector and have both a direct and indirect connection to the agricultural sector. Major saffron processing operations in rural areas are frequently domestic and tiny, making it difficult for them to compete with metropolitan industries. However, if these businesses can band together to enhance potential and income while lowering production costs, they will be able to do so. A business cluster is a dynamic group with a business focus that is geographically concentrated, cooperate and support one another's efforts and faces similar difficulties and possibilities. In this study, saffron processing business clusters in South Khorasan province were determined using the features of cluster identification (geographical focus, collaboration and competition between firms, and shared opportunities and problems between businesses).

The published reports demonstrated that from the distant past to the present, Great Khorasan has been regarded as the world's most significant saffron production location (Abrishami, 2001). Due to climatic factors and geographic positioning, South Khorasan has a significant competitive advantage in saffron farming both now and in the country's new divisions. It must be accepted without a shadow of a doubt that this province, both in terms of the reality that currently exists there and because of the potential for the development of saffron cultivation in it, is one of the centers of saffron cultivation and production today. Additionally, estimates indicate that the South Khorasan province produces 25% of the nation's saffron. Because of this, it should be regarded as an economic center for the cultivation, production, and related activities for the saffron crop, and efforts should be made to enhance the suitable marketing channels and the development of business clusters related to saffron. Given the significance of saffron to regional and national development as well as concerns about saffron marketing, the development model for saffron business clusters in South Khorasan province has been examined throughout this study.

The findings demonstrate the positive and significant influence that managerial, educational, socio-cultural, technical, and political factors have had on the dependent variable. The educational and socio-cultural factors, in comparison to other factors, had the biggest impact on the development of saffron business clusters in South Khorasan, according to the standard coefficient, which shows the intensity of the effect. Additionally, the combination of these factors has led to complicated problems that call for sophisticated solutions in the South Khorasan saffron manufacturing industry. The failure of agricultural extension to play its crucial roles in resolving pressing problems like saffron production and marketing will continue, as has been the case thus far, and it raises more and more doubts about the necessity of agricultural extension in saffron production and processing. As a result, to assist in resolving the fundamental problems facing the agricultural sector, particularly saffron production, it is necessary to coordinate all economic, socio-cultural, technical, managerial, and political activities due to the rapid changes and developments in society.

Due to the influence and significant role of the socio-cultural and educational factors on the development of saffron business clusters, it is imperative and advised to the connected organization to emphasize them. Besides that, it is recommended that the Jihad Agricultural Organization and the Province's Industry and Mining Organization give activists and the owners of saffron production and processing businesses the training they need in the processing of saffron products so that the value chain of saffron products takes place in the village and the resulting profit is distributed to the villagers.

Acknowledgements

The authors acknowledge the support provided by the Science and Research Branch, Islamic Azad University of Tehran, to conduct this research.

References

• ABRISHAMI, M.H., 2001. Saffron from ancient times to the present: the encyclopedia of production, trade and consumption Tehran: Amir Kabir Publishing Institute.
• GUREVA, M.A., LITVINENKO, I.L., SHICHIYAKH, R.A., KOLPAK, E.P. and NOVOSELOVA, N.N., 2016. Cluster-Management as a Technology for Increasing the Efficiency of Territory Resource Exploitation in a Region. International Journal of Economics and Financial Issues, vol. 6, no. 8S, pp. 143-147.
• HAKIM, L. and PERDANA, T., 2017. System Dynamics Modeling on Integrated Supply Chain Management of Potato Agribusiness Bandung: Bandung Islamic University. http://doi.org/10.29313/mimbar.v33i1.2092
  » http://doi.org/10.29313/mimbar.v33i1.2092
• HIKMAT, M., MIRDAMADI, S.M.M., HOSSEINI, S.J.F., SAMARI, D. and EBRAHIMPOUR, M., 2016. Investigating the influencing factors on the marketing innovation of date business cluster in Khuzestan province. Argos, vol. 10, no. 2, pp. 333-343.
• HOFFMANN, V.E., LOPES, G.S.C. and MEDEIROS, J.J., 2014. Knowledge transfer among the small businesses of a Brazilian cluster. Journal of Business Research, vol. 67, no. 5, pp. 856-864. http://doi.org/10.1016/j.jbusres.2013.07.004
  » http://doi.org/10.1016/j.jbusres.2013.07.004
• HWANG, A., BENTO, R.F., ARBAUGH, J., ASARTA, C.J., COCHRAN, J., FORNACIARI, C.J. and JONES, C., 2019. A cluster analysis of highly productive business and management education scholars. Journal of Education for Business, vol. 94, no. 1, pp. 21-30. http://doi.org/10.1080/08832323.2018.1502141
  » http://doi.org/10.1080/08832323.2018.1502141
• IRAN SMALL INDUSTRIES AND INDUSTRIAL PARKS ORGANIZATION – ISIPO, 2015 [viewed 14 October 2023]. South Khorasan Branch [online]. Available from: https://skhorasan.isipo.ir/index.jsp?siteid=1&fkeyid=&siteid=17&pageid=347&code=09
  » https://skhorasan.isipo.ir/index.jsp?siteid=1&fkeyid=&siteid=17&pageid=347&code=09
• JIN, X., WEBER, K. and BAUER, T., 2012. Impact of clusters on exhibition destination attractiveness: evidence from Mainland China. Tourism Management, vol. 33, no. 6, pp. 1429-1439. http://doi.org/10.1016/j.tourman.2012.01.005
  » http://doi.org/10.1016/j.tourman.2012.01.005
• JOFFRE, O.M., POORTVLIET, P.M. and KLERKX, L., 2019. To cluster or not to cluster farmers? Influences on network interactions, risk perceptions, and adoption of aquaculture practices. Agricultural Systems, vol. 173, pp. 151-160. http://doi.org/10.1016/j.agsy.2019.02.011
  » http://doi.org/10.1016/j.agsy.2019.02.011
• KASHIRSKAYA, L., VORONKOVA, O., SITNOV, A., SHICHIYAKH, R., KUDINOVA, M. and SYCHEVA, I., 2019. Rural Development through the Formation of Zonal Agro-Ecological Clusters. Journal of Environmental Management and Tourism, vol. 10, no. 3, pp. 651-659. http://doi.org/10.14505//jemt.v10.3(35).19
  » http://doi.org/10.14505//jemt.v10.3(35).19
• KASSAI, M., KASPAR, J., DEIF, A. and SMITH, H., 2018. Exploring farmers markets as a temporary cluster to improve local food economy. British Food Journal, vol. 120, no. 8, pp. 1844-1858. http://doi.org/10.1108/BFJ-03-2018-0169
  » http://doi.org/10.1108/BFJ-03-2018-0169
• KHATAMI FIROUZABADI, S.M.A., TABATABAEIAN, S.H. and DASHTI, M.A., 2019. Key success factors in the process of implementing advanced technologies in the industrial firms: pieces of evidence from the automotive industry in Iran. Journal of Technology Development Management, vol. 6, no. 4, pp. 89-126. http://doi.org/10.22104/jtdm.2019.3000.2013
  » http://doi.org/10.22104/jtdm.2019.3000.2013
• KREJCIE, R.V. and MORGAN, D.W., 1970. Determining sample size for research activities. Educational and Psychological Measurement, vol. 30, no. 3, pp. 607-610. http://doi.org/10.1177/001316447003000308
  » http://doi.org/10.1177/001316447003000308
• LAI, Y.-L., HSU, M.-S., LIN, F.-J., CHEN, Y.-M. and LIN, Y.-H., 2014. The effects of industry cluster knowledge management on innovation performance. Journal of Business Research, vol. 67, no. 5, pp. 734-739. http://doi.org/10.1016/j.jbusres.2013.11.036
  » http://doi.org/10.1016/j.jbusres.2013.11.036
• MADUREIRA, L., CRISTÓVÃO, A., FERREIRA, D. and KOEHNEN, T., 2018. Actors, roles and interactions in agricultural innovation networks: the case of the portuguese cluster of small fruits. In: International Symposium on New Metropolitan Perspectives
• MATHEW, S.N., FIELD, W.E. and FRENCH, B.F., 2011. Content validation using an expert panel: assessment process for assistive technology adopted by farmers with disabilities. Journal of Agricultural Safety and Health, vol. 17, no. 3, pp. 227-241. http://doi.org/10.13031/2013.38184 PMid:21919319.
  » http://doi.org/10.13031/2013.38184
• MEDVEDEV, S., 2019. Some features of forest cluster management. In: IOP Conference Series: Earth and Environmental Science IOP.
• MIRFARDI, A., AHMADI, S. and ROSTAMI, J., 2017. The investigation of the impact of the social capital aspects on the performance of agricultural and industrial cooperatives in Boyer-Ahmad County. Journal of Applied Sociology, vol. 28, no. 4, pp. 31-52. http://doi.org/10.22108/jas.2017.21704
  » http://doi.org/10.22108/jas.2017.21704
• MOLLASHAHI, G.A., ZARIFFIAN, S. and VALIOLLAH, S., 2017. Factors affecting success of small and medium agricultural and horticultural enterprises in Zabol city. Iranian Journal of Agricutural Economics and Development Research, vol. 46-2, no. 4, pp. 739-748.
• MUSSO, F. and FRANCIONI, B., 2015. Agri-food clusters, wine tourism and foreign markets: the role of local networks for SME’s internationalization. Procedia Economics and Finance, vol. 27, pp. 334-343. http://doi.org/10.1016/S2212-5671(15)01004-7
  » http://doi.org/10.1016/S2212-5671(15)01004-7
• NAZARI, M., HOSSEIN GHOLIPOUR, T., SOLEIMANI, G. and MOUSAVI NAQABI, M., 2017. Development of inter-enterprise networks Solution to exploit the unused capacity of small and medium-sized enterprises. Journal of Productivity Management, vol. 10, no. 40, pp. 7-47.
• OKUTAEVA, S., YESMAGULOVA, N. and KISHKO, N., 2018. Cluster approach to the development of regional agro-industrial complex based on the materials of Akmola region. Проблемы агрорынка, vol. 4, pp. 160-166.
• PARAUŠIĆ, V., CVIJANOVIĆ, J. and MIHAILOVIĆ, B., 2013. Market analysis of clusters in Serbian agribusiness. Ekonomika Poljoprivrede, vol. 60, no. 4, pp. 713-728.
• PARAUŠIĆ, V., DOMAZET, I. and SIMEUNOVIĆ, I., 2017. Analysis of the relationship between the stage of economic development and the state of cluster development. Argumenta Oeconomica, vol. 39, no. 2, pp. 279-306. http://doi.org/10.15611/aoe.2017.2.12
  » http://doi.org/10.15611/aoe.2017.2.12
• POP ZAN, A. and DEANGIZAN, S., 2008. Greenhouse cooperative cluster: a new approach in line employment of graduates of agricultural colleges. In: Proceedings of the 1st National Conference on Cooperatives and Agriculture, 2008, Tehran. Tehran: Tehran University.
• RAINES, P., 2017. Cluster policy–does it exist? Cluster development and policy London: Routledge. pp. 21-33. http://doi.org/10.4324/9781315196251-3
  » http://doi.org/10.4324/9781315196251-3
• RAJAEI, Y., YAGHOUBI, J. and DONYAEI, H., 2011. Assessing effective factors in development of entrepreneurship in agricultural cooperatives of Zanjan province. Procedia: Social and Behavioral Sciences, vol. 15, pp. 1521-1525. http://doi.org/10.1016/j.sbspro.2011.03.323
  » http://doi.org/10.1016/j.sbspro.2011.03.323
• RAMIREZ, M., BERNAL, P., CLARKE, I. and HERNANDEZ, I., 2018. The role of social networks in the inclusion of small-scale producers in agri-food developing clusters. Food Policy, vol. 77, pp. 59-70. http://doi.org/10.1016/j.foodpol.2018.04.005
  » http://doi.org/10.1016/j.foodpol.2018.04.005
• SOUTH KHORASAN PROVINCE CUSTOMS DEPARTMENT, 2018. South Khorasan: South Khorasan Province Customs Department.
• SOUTH KHORASAN PROVINCE INDUSTRIAL TOWNS COMPANY, 2013. Report on the status of saffron production in South Khorasan South Khorasan: South Khorasan Province Industrial Towns Company.
• WONGLIMPIYARAT, J. and CHANDRACHAI, A., 2016. Cluster management and research commercialisation. International Journal of Business Innovation and Research, vol. 11, no. 3, pp. 311-325. http://doi.org/10.1504/IJBIR.2016.078869
  » http://doi.org/10.1504/IJBIR.2016.078869
• ZENG, Y., GUO, H., YAO, Y. and HUANG, L., 2019. The formation of agricultural e‐commerce clusters: a case from China. Growth and Change, vol. 50, no. 4, pp. 1356-1374. http://doi.org/10.1111/grow.12327
  » http://doi.org/10.1111/grow.12327
• ZHARIKOV, R.V., BEZPALOV, V.V., LOCHAN, S.A., BARASHKIN, M.V. and ZHARIKOV, A.R., 2018. Economic security of regions as a criterion for formation and development of agricultural clusters by means of innovative technologies. Scientific Papers. Series Management, Economic, Engineering in Agriculture and Rural Development, vol. 18, no. 4, pp. 431-439.

Publication Dates

• Publication in this collection
  22 Nov 2024
• Date of issue
  2024

History

• Received
  14 Oct 2023
• Accepted
  25 Jan 2024