Effect of the Olive Value Chain on the Assets of Olive Orchard Owners in Rudbar County: the Application of Sustainable Livelihood Approach
Subject Areas : Education and training
Shahaboldin
Shokri
1
(عضو هئیت علمی دانشگاه آزاد اسلامی)
Yazdan
Habibi
2
(Science and Research Branch, Islamic Azad University)
Seyyed Mehdi
Mirdamadi
3
(دانشیار، دانشگاه آزاد اسلامی واحد علوم و تحقیقات، تهران، ایران)
Keywords: "sustainable livelihood", "livelihood assets", "value chain", "Rudbar County",
Abstract :
This descriptive-analytical research aimed to investigate the effects of the olive value chain on the assets of olive orchard owners in Rudbar County with the sustainable livelihood approach by the library and field method using a questionnaire. The content and face validity of the questionnaire were confirmed by a panel of experts after revision, and its general reliability was estimated at 0.97 by Cronbach’s alpha. The study site was Rudbar County. The statistical population was composed of 5053 olive orchard owners out of whom 604 people were sampled based on Bartlett’s table. Data were analyzed using the SPSS and LISREL software packages. According to the applied LISREL, the main findings were as follows: P-VALUE =0.000001, NNFI=0.907, CFI=0.910, RMSEA=0.036 and X^2/df =1.51, IFI =0.910 and PGFI =0.768. Results revealed that out of these five resources, social capital was the strongest one affecting respondents’ livelihoods in the study area (λ=1.02). The results revealed that the fit of the measurement model is appropriate and acceptable. Also, it can be said that capital assets influence livelihood outcomes significantly and positively, so the livelihood level will increase with increasing capital assets.
Effect of the olive value chain on the assets of olive orchard owners in Rudbar County: The application of sustainable livelihood approach
Abstract
This descriptive-analytical research aimed to investigate the effects of the olive value chain on the assets of olive orchard owners in Rudbar County with the sustainable livelihood approach by the library and field method using a questionnaire. The content and face validity of the questionnaire were confirmed by a panel of experts after revision, and its general reliability was estimated at 0.97 by Cronbach’s alpha. The study site was Rudbar County. The statistical population was composed of 5053 olive orchard owners out of whom 604 people were sampled based on Bartlett’s table. Data were analyzed using the SPSS and LISREL software packages. According to the applied LISREL, the main findings were as follows: P-VALUE =0.000001, NNFI=0.907, CFI=0.910, RMSEA=0.036 and 
/df =1.51, IFI =0.910 and PGFI =0.768. Results revealed that out of these five resources, social capital was the strongest one affecting respondents’ livelihoods in the study area (λ=1.02). The results revealed that the fit of the measurement model is appropriate and acceptable. Also, it can be said that capital assets influence livelihood outcomes significantly and positively, so the livelihood level will increase with increasing capital assets.
Keywords: sustainable livelihood, livelihood assets, value chain, Rudbar County
1 Introduction
Today, livelihood has gone beyond economic and income issues and turned into an important part of human life so that its stability is deeply effective in the stability of family life and welfare. The formation of an economic structure in rural areas has entailed certain issues, e.g., lower flexibility against short-term climatic fluctuations, volatility of crop prices at harvest time, crop marketing constraints, users’ dependence on off-village factors, overt and covert unemployment, the decline in capital return, the degradation of basic natural resources, the vulnerability of rural economy and instability of income sources, the lack of job security, the low level of life quality, and finally, unsustainable rural livelihood (Ahmadi et al., 2019).
Livelihood is usually investigated at the household level (Diniz et al., 2015) and can be defined as the combination of multiple assets and activities which contribute to the income of local residents (Su et al., 2019 ; Ellis, 2000 ). The focus on livelihood as an instrument of life quality and welfare is a new approach to selecting optimal development strategies in developing societies so that it can provide resources by which people can improve and enjoy their life (Asghari Saraskanrud et al., 2016: 313; Sadrmousavi et al., 2021: 194).
Achievement to sustainable livelihood needs adopting a strategy at different planning periods considering the internal and external conditions of rural communities because sustainable livelihood is a process-based activity that is made possible through the interaction and cooperation of institutions in charge of rural development and the establishment of coordinated connections among different components that are influential on sustainable livelihood in the long run, the accomplishment to which needs strategic planning and the identification of strategies (Sojasi Ghidari et al., 2016). Capitals and assets are among the most important components of a sustainable livelihood framework so that livelihood is supported by investment in the capabilities of the sustainable livelihood asset (Zenteno et al., 2013). According to Chambers, livelihood will be sustainable when it is resistant to stresses and shocks, capabilities and assets are maintained not only for the present but also for the future, and net benefits are created for the livelihood of others at the national and local levels in the short run and long run (Department for International Development, 2008). The sustainable livelihood approach has emerged as a new approach to rural development that aims to reduce or even eradicate rural poverty (Ariuon et al., 2012; Veisi and Nikkhah, 2019: 329). This approach entails integrates the concepts of welfare, security, and capability with the in-depth analysis of poverty, vulnerability, and resilience and entails the sustainability of natural resources. It encompasses human resources, technical assets, natural resources, social assets, and financial assets as vital indicators to measure livelihood security (Isazehi & Sharifzadeh, 2021; Sharifinia, 2021: 214; Shah et al., 2013; Subba et al., 2016).Based on the livelihood approach, livelihood capitals (physical, natural, human, financial, and social) are the basis for rural people’s capability and capacity for intervention in their social and personal destiny because these capitals determine and orient people’s and families’ perceptions, expectations, and activities in rural areas (Badko et al., 2020; Barimani et al., 2016).
The value chain is a general description of all activities performed for a crop from the initial inputs step to processing, delivery to the final market, and post-consumption disposal. The product moves at different steps, transactions occur among various stakeholders of the chain, money and information are exchanged, and added value is gradually generated (UNIDO, 2009). The value chain refers to a series of factors and related markets, which converts inputs and services to products with the features that consumers would like to buy (Andre Devaux et al., 2018). As a departure point, the value chain argues that the livelihood approach can complement the value chain by providing a full image of dynamics that influence people’s lives directly or indirectly. Therefore, the value chain analysis has been accompanied by the analysis of the livelihood approach, which is selected not only in terms of perspective but also in terms of methodology (Krap, 2012). The value chain analysis can also be used as a precious instrument to investigate the role of the value chain in accomplishing certain political goals, e.g., poverty alleviation, sustainable growth, and injustice reduction (Bellu, 2013). Any changes in the agricultural value chain have implications for farmers’ livelihood and their vulnerability (Fournier, 2019). Olive is a crop that is conventionally sold in both raw and processed forms. This economically important and highly valuable crop can be produced in different regions of Iran so that it is regarded as a strategic crop in some provinces (Chegini et al., 2015).
Given that Iran is among the 10 top countries in terms of horticultural production and has the third rank in terms of crop diversity, the horticultural sub-sector is specifically important. This sub-sector accounts for 25 percent of the added value, 30 percent of employment, and 80 percent of the exports of the agricultural sector (Ghasemi and Bakhshi Shadmehri, 2019). One of these crops is olive. The global cultivated area of olive orchards, distributed among 47 countries on five continents, amounts to over 11 million ha. Over 6.7 million families in the world possess olive trees – an average of 1.67 ha of olive orchard per family. However, 98 percent of the global olive harvest is related to the Mediterranean region (IOC1,2020). FAO (2021) reports that Spain is the leading olive producer in the world with a production rate of 8,256,550 tons per year.
In Iran, Rudbar County is one of the main olive-producing regions and hosts most olive processing factories in this country (Table 1). Indeed, 80 percent of Rudbar’s agricultural economy depends on the olive crop, and this county is the basis of the olive trade in Iran. The main olive cultivars in this county include ‘Zard’, ‘Roghani’, ‘Fishmi’, ‘Shenge’, ‘Marri’, and ‘Goluleh’ in the order of the cultivation area. Agriculture Jahad Organization of Guilan reported in 2020 that a total of 22,000 people in Rudbar County made living from olive production (Jahad Agriculture Organization of Guilan Province ( 2021).
Table 1 Information on the cultivation area, production rate, and yield of olives in Rudbar County in 2020-2021
Total cultivated area including dispersed trees (ha) | Total area | Production rate (t) |
| Yield | |||||||||||||||
Non-fertile |
| Fertile | |||||||||||||||||
Irrigated | Rain-fed | Total |
| Irrigated | Rain-fed | Total | Irrigated | Rain-fed | Total | Irrigated | Rainfed | ||||||||
230 | 2 | 232 |
| 8466 | 131 | 8597 | 8829 | 16304 | 325 | 16632 |
| 1926 | 2474 | ||||||
Source: ITC Center, Deputy of Planning and Economy, Ministry of Agriculture Jahad, 2021
Since the olive crop needs processing before marketing, it is regarded as a valuable industrial plant with added value. In addition to crop production at the farm, all marketing steps including harvesting, transportation, oil extraction, sales, and financial and credit institutions are somewhat involved in creating value for its crop (Chegini et al., 2015; Kheiri, 2007). The agricultural development programs in Iran show that such goals as increasing crop production and processing have always been considered by development policymakers and the supply of rural households’ livelihood has always been in priority (Sawari et al., 2018). Olive, which is the main crop in Rudbar County, has a desirable sale market across Iran. However, given the lack of the government’s support services in this region, the availability of a good sale market, and the possibility of regional branding for olives, it is necessary to conduct research on this crop in order to contribute to the value addition of this crop (Soleymani et al., 2020).
Therefore, given the role of the olive in the agricultural economy of this county, it seems necessary to develop the value chain of this crop. In this respect, it appears that the value chain of this crop can be improved by adopting proper strategies and policies. In total, the research investigated the dimensions and nature of the olive value chain in Rudbar and assessed the livelihood sustainability level of olive orchard owners using sustainable livelihood indices. This research tries to first investigate the different dimensions of the olive value chain and then their effect on capital assets and the livelihood level of olive orchard owners. It also provides solutions for improving the orchard owners’ livelihood level.The next section reviews the theoretical literature on the olive industry and the livelihood of olive orchard owners. Then, the research methodology and the structural model are explained. Finally, some concluding points and recommendations are presented.
1. International Olive Council
2 Literature Review
Presently, the research on the value chain of olive is of crucial significance for accomplishing the goals of the olive development project in Iran because it allows considering the potential of olive production units for increasing productivity and optimally using the resources and helping the income and livelihood of olive orchard owners in addition to studying their economy. Nonetheless, few studies, which are reviewed below, have partially addressed the olive value chain.
Pravakar et al. (2013) revealed that human capital (religious structure, family size, and literacy level), financial capital (credit source, employment, families’ annual income), physical capital (healthcare facilities and healthy drinking water sources), and social capital (education and social status of farmers) were effective in improving farmers’ livelihood. Also, Badko et al. (2020) found that differed in their livelihood assets and capital in human, financial, physical, natural, and social fields. They reported decreases in physical, financial, and natural assets and increases in social and human assets due to vulnerability in different fields in recent years. According to their results, the livelihood assets were not equally sustainable so that the financial and physical capitals were the most unsustainable assets and the social and human assets were the most sustainable assets in the studied villages with mean sustainability scores of 1.41, 2.46, 3.68, and 3.25, respectively. According to Aazami and Shanazi (2018), the Zarivar wetland was influential on the fivefold dimensions of livelihood including natural, human, physical, social, and financial assets of the families living in its margins so that it improved the components of each capital, enhancing their asset and livelihood levels of the people.
Aazami et al. (2018) reported that the study a confirmatory factor analysis and a structural equation model using the LISREL to measure different effects of agro-industry on sustainable livelihoods assets. The results revealed that out of these five resources, natural capital was the strongest one affecting respondents’ livelihoods in the study area (λ=0.90). The results showed that the measurement model fit Was appropriate and acceptable. Mchopa et al. (2021) reported a study that aimed to analyze the impact of sunflower value chain activities on livelihood sustainability potentials among households of smallholders The findings showed that most of the households had lower chances for livelihood sustainability (67.1%) while few households (12.5%) were categorized into high livelihood sustainability. It was concluded that the sunflower value chain had the potential for households’ livelihood sustainability unlike other socio-economic activities as it enabled smallholders to withstand livelihood shocks and stresses based on the generated household income.
García Tejada (2019) studied the olive production chain with a focus on small producers in Karavali province, Spain to improve their economic conditions from the beginning of the cropping season, harvest time, processing, and final marketing until crop delivery to consumers. Since olive production was a source of employment at all levels in the region, it was found that olive sales had very low income, so smallholders were financially weak and have a low organizational level. The research attempted to find solutions for improving smallholders’ income by analyzing the production chain and suggesting value production. In this respect, they proposed an improvement for the olive production chain for small olive producers, which would allow improving their income and life quality. Boudi et al. (2016) found that despite the value chain being profitable for all players, significant shortages and bottlenecks still weakened the general development of the value chain. The key bottlenecks for the improvement of productivity and added value were poor agriculture performance and institutional environment, as well as the issues related to the natural, structural, technological, and economic environment, lack of market transparency, market uncertainty, lack of quality control, absence of a monitoring system that was traceable throughout the chain, lack of certification and labeling, and almost total absence of organized structures around the crop. In this context, Soleymani et al. (2020) reported that the supply chain development strategies were close to competitive strategies and the most important competitive strategies included the extension of cultivating high-yielding and marketable cultivars, the extension of modern irrigation methods such as drip irrigation, the establishment of seedling production centers across the county to facilitate access to the seedlings of high-yielding cultivars, allocation of governmental lands with supportive facilities to increase the cultivation area, and the motivation of agriculture graduates to found mechanized orchards by supporting their plans. In a study on the factors related to the marketing behavior (selling type) of olive farmers in Tarom Township, Iran, Chegini et al. (2015) reported that the farmers supplied their crop to the market in three forms – green, broken, and canned – and their marketing behavior was significantly related to such variables as age, selling price, crop quantity and quality, orchard area, the number of extension classes attended, and their risk-taking.
Najafi et al. (2016) investigated the effect of different factors on improving olive orchard management in Tarom with an emphasis on bank facilities and found that bank facilities were influential on olive orchard management in the study site positively and significantly. Their results also revealed the positive and significant effect of management improvement on increasing olive production in this town. Additionally, management improvement would contribute to the expansion of olive orchards across the region. In a study on designing a closed-loop green supply chain for olive under risk conditions, Nazari Gooran et al. (2020) showed that the chain was profitable by 55417 billion USD. However, given the ratio of disposal cost to waste recycling profit (431.91), the olive supply chain performs poorly in waste recycling. This ratio would be reduced by 79 percent by modifying the chain. Also, there is no need for imports under risk conditions in this chain, and all market needs and demands of the exporting centers are satisfied without any sale loss through the chain. So, the productivity of the olive processing industries can be increased by equipping olive processing factories and founding processing factories for the waste of oil extraction and/or production of valuable products from the waste.
As has been mentioned in the literature, the olive value chain has diverse dimensions, which are each influenced by different factors. Demographic factors, economic factors, technical factors, infrastructural factors, institutional factors, policymaking factors, and marketing factors are linked with the value chain in some sense.
The results of the literature on the olive value chain show that olive orcharding, which has unique characteristics, has provided local people with a good source of income along with other activities. However, it is struggling with numerous unsolved gaps and problems in different parts. It seems that the adoption of the sustainable livelihood approach can partially answer these issues, making it unavoidable to conduct extensive research. Accordingly, this study is an attempt to explore the dimensions and contexts that constitute sustainable livelihood in the framework of the olive value chain (Figure 1) as a way to improve the livelihood of olive orchard owners.
Based on the findings of this study, changes in the access of olive growers to the assets can increase their ability to maintain and withstand crises. And in order for olive growers to achieve a strong and sustainable livelihood through olive production, they must have adequate access to these livelihood resources. According to the cases, the present study identifies the factors affecting the development of the olive value chain and its impact on the capital assets and livelihood results of Rudbar olive growers. Figure 1 depicts the primary research model.
پایداری نهادی |
Figure 1 The conceptual model of the research
3 Methodology
The research was an applied study conducted descriptively and analytically in which data were collected with a survey using a quantitative approach. The statistical population was composed of all olive orchard owners in Rudbar County who were registered in the Comprehensive Zonation System of Agriculture Jahad Organization and were available to online users. They amounted to 5053 people. The sample size was determined at 598 people based on the least sample size table of Bartlett et al. (2001). Since the questionnaires returned is fewer than the questionnaires distributed in most studies, the sample size was increased to 620 people to ensure attaining the minimum sample size required. Finally, 604 questionnaires were returned.
In the questionnaire, the Likert scale was used to measure the research variables, and for the validity of the questionnaire, a panel of experts including agricultural development, extension, and horticulture was used and their corrective views were considered. Finally, the content and face validity Was confirmed. Then, Cronbach's alpha was used to determine the reliability of the questionnaire. Data analysis was performed using SPSS24 and LISREL software and confirmatory factor analysis. The main data collection instrument was a self-designed questionnaire that was composed of 81 items to assess the olive value chain as the independent variable with five dimensions, livelihood assets as the mediating variable with five dimensions, and livelihood sustainability as the dependent variable with four dimensions.
Table 2 The results of Cronbach’s alpha for the research variables
Variable | Cronbach’s alpha |
Infrastructure | 0.803 |
Marketing and sale | 0.700 |
Policymaking and institutional | 0.767 |
Technical factors | 0.823 |
Economic factors | 0.766 |
Natural capital | 0.765 |
Human capital | 0.715 |
Social capital | 0.766 |
Physical capital | 0.744 |
Financial capital | 0.724 |
Welfare | 0.710 |
Income | 0.711 |
Food security | 0.713 |
Sustainability of natural resources | 0.712 |
Overall | 0.794 |
The appropriate value for Cronbach’s alpha is 0.7. Based on Table 2, it was found to have proper values for the criteria included in the latent variables, so it supports the reliability of the research. The sample size for the studied villages was estimated in proportion to the population size and using the proportional allocation method. Finally, the participants were selected by simple randomization. Table 3 presents the sample size in the studied villages.
Table 3 Distribution of the statistical sample of the research based on the important olive producing villages in Rudbar city
Region | District | Village | Olive orchard owners | Sample size |
Central | South Rostamabad | Shemam | 160 | 47 |
Joben | 171 | 48 | ||
Ganje | 94 | 28 | ||
Glavarz | 37 | 12 | ||
Keleshter | Telabar | 123 | 38 | |
Aliabad | 189 | 61 | ||
Nezamivand | 39 | 12 | ||
Torkneshin | 39 | 12 | ||
Pachenar | 65 | 19 | ||
Lushan | 600 | 186 | ||
Gharehtikan | 48 | 15 | ||
Rahmatabad and Blukat | Rahmatabad | Roodabad | 16 | 3 |
Kiaabad | 68 | 14 | ||
Nesfi | 187 | 36 | ||
Fishom | 57 | 12 | ||
Dashtevil | Seidan | 22 | 7 | |
Chelebar | 32 | 10 | ||
Amarlu | Jirandeh | Bivarzen | 33 | 9 |
Paroodbar | 44 | 12 | ||
Pakdeh | 60 | 18 | ||
Klishom | Layeh | 18 | 3 | |
Anbuh | 7 | 2 | ||
Total |
|
| 604 | |
(Source: Research findings)
A total of 604 people filled out the research instrument among which 97.7 percent (590 people) were male, and 2.3 percent (14 people) were women. Their average age was 47.95 years. The highest frequency was 160 people (26.5%) for the age range of 51-60 years. In terms of educational level, 10.4 percent were illiterate, and only 13.9 percent had a bachelor’s degree or higher. According to the results (Table 2), the highest number of family members employed in the orchard (76.8%) was one person, and in only 3.8 percent of the participants’ families, three members or higher were working in their respective orchards. Regarding the history of orchard establishment and olive tree production and cultivation, the studied olive orchard owners had 3-50 years of experience. The highest frequency was for the experience ranges of 11-20 years and 21-30 years (169 people, 28%) and the lowest for the range of >41 years with a frequency of 10 people (1.7%). It was also found that the mean experience was 22.12 years with a median of 20 years, a mode of 30 years, and a standard deviation of 11.05 years. More results are presented in Table 4.
Table 4 Distribution of the respondents based on their demographic and professional characteristics
Variable | Levels | Frequency | Percent | Other statistical indices |
Gender | Male | 590 | 97.7 | Mode = male |
Female | 14 | 2.3 |
| |
Age (years) | <30 | 61 | 10.1 | Mean = 47.95 |
31-40 | 115 | 19 | Mode = 44 | |
41-50 | 153 | 25.4 | SD = 11.99 | |
51-60 | 160 | 26.5 | Min = 26 | |
>61 | 115 | 19 | Max = 72 | |
No. of family members working in the orchard (persons) | 1 | 464 | 76.8 | Mean = 1.26 |
2 | 117 | 19.4 | SD = 0.52 | |
3 or higher | 23 | 3.8 | Mode = 1 | |
Educational level | Illiterate | 63 | 10.4 | Mode = diploma |
Elementary | 114 | 18.9 |
| |
Intermediate and under-diploma | 125 | 20.7 |
| |
Diploma | 186 | 30.8 |
| |
Associate degree | 32 | 5.3 |
| |
Bachelor’s degree or higher | 84 | 13.9 |
| |
History of activity (years) | ≤10 | 144 | 23.8 | Mean = 22.12 |
11-20 | 169 | 28 | Mode = 30 | |
21-30 | 169 | 28 | SD = 11.05 | |
31-40 | 112 | 18.5 | Min = 3 | |
≥41 | 10 | 1.7 | Max = 50 |
(Source: Research findings)
The livelihood levels of the olive orchard owners in Rudbar County were described using the method of Interval of Standard Deviation from the Mean (ISDM). The components determining the livelihood level from the persepective of people were ranked in terms of mean, standard deviation (SD), and coefficient ov ariations. Then, the mean and total standard deviation were determined (mean = 7.56; SD = 0.983).
In this method, the scores obtained are converted into four levels as follows:
A = weak A < Mean - SD
B = moderate Mean – SD < B < Mean
C = good Mean < C < Mean + SD
D = excellent Mean + SD < D
Table 5 The frequency distribution of the livelihood levels of olive orchard owners in Rudbar County based on the scores obtained
Cumulative percentage | Percentage | Frequency | Livelihood level | Score |
16.4 | 16.4 | 99 | Weak | < 6.577 |
49.5 | 33.1 | 200 | Moderate | 6.577-7.561 |
85.1 | 35.6 | 215 | Good | 7.561-8.544 |
100 | 14.9 | 90 | Excellent | >8.544 |
Mean = 7.561; SD = 0.983; Minimum = 4.62; Maximum = 9.85
Table 5 shows that 16.4% of the people were at the weak livelihood level, 33.1% were at the moderate livelihood level, 35.6% were at the good livelihood level, and 14.9% were at the excellent livelihood level.
3.1 The analysis of the effect of the olive value chain on the capital assets of olive orchard owners with the sustainable livelihood approach
Table 6 measurement model of value chain
Variable | Dimensions | Items | Symbol | Factor loading | t-statistic | Result |
Olive value chain | Economic factors | The amount of olive production per hectare | e1 | 0.59 | 16.41 | Confirmed |
Fluctuations of olive prices, especially at harvest time | e2 | 0.62 | Fix |
| ||
The low selling price of olives compared to production costs | e3 | 0.49 | 13.44 | Confirmed | ||
The high cost of obtaining inputs for olive production (such as fertilizers, pesticides, etc.) | e4 | 0.75 | 20.57 | Confirmed | ||
Failure to pay the price of olive products on time by buyers and increasing financial stress | e5 | 0.56 | 15.22 | Confirmed | ||
Lack of credit and facilities for olive orchard establishment | e6 | 0.59 | 16.24 | Confirmed | ||
The high cost of olive tree and crop insurance | e7 | 0.29 | 7.97 | Confirmed | ||
|
|
|
|
|
| |
Infrastructural factors | The amount of using suitable means of transportation to reach the olive orchard | z1 | 0.74 | 20.81 | Confirmed | |
The existence of suitable transportation roads in the village | z2 | 0.70 | 19.21 | Confirmed | ||
Access to olive grading and processing units in the region | z3 | 0.70 | 19.46 | Confirmed | ||
Establishment of direct olive supply stores by olive growers | z4 | 0.68 | Fix |
| ||
Having a warehouse suitable for storing or keeping olives | z5 | 0.55 | 14.85 | Confirmed | ||
|
|
|
|
|
| |
Marketing factors | Establishment of associations or cooperatives of olive growers to direct the olive market | b1 | 0.70 | Fix |
| |
Acquiring accounting and financial management skills | b2 | 0.49 | 8.52 | Confirmed | ||
Paying marketing expenses to make more profit | b3 | 0.54 | 9.40 | Confirmed | ||
Acquiring the necessary skills and abilities for marketing by olive orchard owners | b4 | 0.35 | 5.68 | Confirmed | ||
Awareness of olive orchard owners about the needs and demands of the market and customers | b5 | 0.61 | 11.61 | Confirmed | ||
Awareness of olive orchard owners about the status of olive production by competitors in other provinces | b6 | 0.22 | 3.43 | Confirmed | ||
Knowing new domestic or foreign markets to offer products to specific customers | b7 | 0.09 | 1.46 | Confirmed | ||
Attention to the capacity of local markets to earn money, especially for small owners | b8 | 0.67 | 12.32 | Confirmed | ||
Controlling intermediaries in the marketing process | b9 | 0.32 | 5.06 | Confirmed | ||
Ability to work with information and communication technologies, computers, and the Internet for crop sales | b10 | 0.15 | 2.39 |
| ||
|
|
|
|
|
| |
Policymaking and institutional factors | A lot of legal obstacles for receiving loans and credit facilities | s1 | 0.54 | 11.41 | Confirmed | |
The high bank interest rate and the lack of cooperation of the bank in repaying the bank facilities on an annual basis | s2 | 0.64 | 13.72 | Confirmed | ||
Subsidies (such as fertilizer subsidy) paid by the government to increase farmers' motivation to develop olive cultivation | s3 | 0.53 | 10.90 | Confirmed | ||
Guidance and consultations by relevant organizations | s4 | 0.66 | 14.92 | Confirmed | ||
The existence of supporting institutions (cooperatives) to prevent the abuse of olive growers by brokers and middlemen | s5 | 0.50 | 10.28 | Confirmed | ||
The existence of a trustee and a special program for the promotion and marketing of olive crop | s6 | 0.75 | Fix |
| ||
|
|
|
|
|
| |
Technical factors | Choosing the right land to build an olive garden | f1 | 0.54 | 16.92 | Confirmed | |
The number of times of watering the olive garden | f2 | 0.64 | 17.18 | Confirmed | ||
Selection of olive seedlings suitable for the region's climate to produce valuable and marketable crops | f3 | 0.53 | 8.37 | Confirmed | ||
Preparation of a suitable plan for planting trees to harvest with different machines | f4 | 0.66 | 10.21 | Confirmed | ||
Identification and control of pests, especially olive fly, psyllium, etc. | f5 | 0.50 | 12.43 | Confirmed | ||
Knowing the types of fertilizers and how to use them correctly | f6 | 0.75 | Fix |
| ||
Knowing the types of olive tree pruning and how to do it correctly | f7 | 0.54 | 18.81 | Confirmed | ||
Awareness of the types of olive products and how they are produced | f8 | 0.64 | 19.87 | Confirmed | ||
Awareness of the methods of reducing olive waste | f9 | 0.53 | 16.47 | Confirmed |
Table 7 measurement model of capital assets
Variable | Dimensions | Items | Symbol | Factor loading | t-statistic | Result |
Capital assets | Natural capital | The amount of olive production per hectare | St1 | 0.59 | 16.41 | Confirmed |
Reducing soil erosion and protecting it better | St2 | 0.62 | Fix |
| ||
Use of appropriate irrigation methods | St3 | 0.49 | 13.44 | Confirmed | ||
Implementation of collaborative environmental protection projects | St4 | 0.75 | 20.57 | Confirmed | ||
|
|
|
|
|
| |
Human capital | Helping to cover health and family health expenses | Se1 | 0.74 | 20.81 | Confirmed | |
Increasing gardening skills | Se2 | 0.70 | 19.21 | Confirmed | ||
Improving access to educational services | Se3 | 0.70 | 19.46 | Confirmed | ||
The possibility of employment for women and girls | Se4 | 0.68 | Fix |
| ||
|
|
|
|
|
| |
Social capital | The possibility of membership in organizations and cooperatives | Sg1 | 0.70 | Fix |
| |
Increasing job competition and household production | Sg2 | 0.49 | 8.52 | Confirmed | ||
Doing partnership economic activities with other orchard owners | Sg3 | 0.54 | 9.40 | Confirmed | ||
Willingness to help and help others financially | Sg4 | 0.35 | 5.68 | Confirmed | ||
Increasing local people’s trust in each other (within a group) | Sg5 | 0.61 | 11.61 | Confirmed | ||
|
|
|
|
|
| |
Physical capital | Easier access to the market and shopping center | Sf1 | 0.54 | 11.41 | Confirmed | |
Helping to develop communication ways | Sf2 | 0.64 | 13.72 | Confirmed | ||
Improvement and renovation of residence or household housing | Sf3 | 0.53 | 10.90 | Confirmed | ||
Increasing access to agricultural and horticultural equipment | Sf4 | 0.66 | 14.92 | Confirmed | ||
|
|
|
|
|
| |
Financial capital | Income stability | Sm1 | 0.54 | 16.92 | Confirmed | |
The possibility of creating various job fields and side incomes | Sm2 | 0.64 | 17.18 | Confirmed | ||
Using new technologies in crop production | Sm3 | 0.53 | 8.37 | Confirmed | ||
Increasing access to production inputs (fertilizers, poisons, etc.) | Sm4 | 0.66 | 10.21 | Confirmed |
Table 8 presents the results of the factor analysis of sustainable livelihood levels and the t-test.
Table 8. measurement model of livelihood levels
Variable | Dimensions | items | Symbol | Factor loading | t-statistic | Result |
Sustainable livelihood levels | Family welfare | Feeling satisfied with life | mr1 | 0.58 | Fix |
|
Improving the physical and mental health of the family | mr2 | 0.68 | 43.66 | Confirmed | ||
Improving living facilities |
| 0.66 | 43.09 | Confirmed | ||
Providing basic needs | mr3 | 0.49 | 35.12 | Confirmed | ||
Increasing income through garden products | mr4 | 0.68 | Fix |
| ||
Income generation | Increasing savings | md1 | 0.49 | 27.83 | Confirmed | |
Stabilizing the effects of production and price fluctuations on households | md2 | 0.78 | 39.35 | Confirmed | ||
Helping improve household nutrition | md3 | 0.72 | 46.46 | Confirmed | ||
Food security | Improving spatial and temporal access to food | ma1 | 0.72 | 45.74 | Confirmed | |
Reducing the level of conflicts and crime | ma2 | 0.56 | Fix |
| ||
Reducing the destruction and pollution of pastures and natural resources | ma3 | 0.66 | Fix |
| ||
Sustainable use of natural resources | Improving soil fertility and the possibility of increasing resource productivity | mp1 | 0.71 | 39.74 | Confirmed | |
Reviving and developing natural resources of the village | mp2 | 0.64 | 34.03 | Confirmed |
Table 9 Ranking of the effect of first-order indices on the formation of the second-order construct
Rank | Sig. | t-statistic | Factor loading | First-order indices |
3 | 0.0000 | 72.81 | 0.99 | Natural capital |
2 | 0.0000 | 64.29 | 1.01 | Human capital |
1 | 0.0000 | 57.82 | 1.02 | Social capital |
5 | 0.0000 | 75.76 | 0.98 | Physical capital |
4 | 0.0000 | 68.52 | 0.99 | Financial capital |
In the statistical section, the structural equation modeling (SEM) method was used in the Lisrel software package. In the measurement section, the relationship between the indicators, or the questionnaire items, and the constructs was examined. CFA was employed to check the extent to which the research constructs were consistent with the indicators selected for their measurement.
3.2 The structural model of the research
SEM is employed for two purposes: the measurment of phenomena and the study of the relationships between phenomena. This present research pursued both goals, including testing the (structural) hypotheses and studying the fit of the model. To test the research hypoteses, SEM was executed in the Lisrel (ver. 10) software package. Figure 2 displays the model along with the standard coefficients. Figure 3 displays the model in the significance state. Tables 9 and 10 present the model’s fit indices in the general sense and the results of hypotheses testing, respectively.
Figure 2 The structural model of the research along with standard coefficients
Figure 3 The structural model of the research along with the significance coefficients (t-test)
Table 10 The model fit indices in a broad sense
Status | Value reported | Proposed level | Index |
Suitable fit | 1.767 | (Acceptable fit) | χ2/df |
Suitable fit | 0.036 | ≤ 3 | RMSEA |
Unsuitable fit | 0.000001 | ≤ 0.08 | P-VALUE |
Unsuitable fit | 0.820 | ≥ 0.05 | GFI |
Unsuitable fit | 0.808 | ≥ 0.90 | AGFI |
Suitable fit | 0.907 | ≥ 0.90 | NNFI |
Unsuitable fit | 0.815 | ≥ 0.90 | NFI |
Suitable fit | 0.910 | ≥ 0.90 | CFI |
Suitable fit | 0.910 | ≥ 0.90 | IFI |
Suitable fit | 0.785 | ≥ 0.90 | PNFI |
Suitable fit | 0.768 | ≥ 0.50 | PGFI |
Suitable fit | 0.046 | ≥ 0.50 | RMR |
The results for the structural model’s goodness-of-fit indices in Table 10 reflect the fit of the model as the RMSEA value is smaller than 0.08, the NNFI, IFI, and CFI values are greater than 0.9, the PNFI and PGFI values are greater than 0.50. The GFI, AGFI, and NFI values are smaller than 0.9, showing unsuitable fit. However, since the other indices have proper values, the general fit of the structural model can be accepted.
Table 11 The results of the effect and signficance coefficients of the model hypotheses
Test result | Significance | Path factor | Path |
Confirmed | 2.13 | 0.30 | Capital assets à Livelihood level |
Confirmed | 9.53 | 0.98 | Value chain à Capital assets |
Confirmed | 3.28 | 0.70 | Value chain à Livelihood level |
4 Results
Based on the results, the livelihood of olive orchard owners in Rudbar County is at a relatively optimal level from the perspective of the respondents. Indeed, over 50% of the studied people described their livelihood level to be good and excellent, and only 16.4% assessed their livelihood status to be weak. According to the results obtained from Model 2 in Figure 3, if t-value is >2.58, the factor loadings are significant at the P = 0.01 level and if the t-value is 1.96-2.58, the factor loading is significant at the P = 0.05 level, supporting the null hypothesis regarding the significance of the role of the indicator (variable) on the formation of the target construct (factor), so the significance of the relationships (the research assumption) is accepted within second-order CFA (Todman & Dugard, 2007). The research used χ2, normed fit index (NFI), non-normed fit index (NNFI), incremental fit index (IFI), root mean square residual (RMR), goodness-of-fit index (GFI), adjusted goodnesss-of-fit index (AGFI), comparative fit index (CFI), and the very important of root mean square error of approximation (RMSEA).
The value of χ2/df was estimated at 1.76, reflecting the good fit of the model. Based on the values reported for the fit indices in Table 6, the measurement model of the effect of the value chain on the livelihood level of olive orchard owners in Rudbar exhibits a good fit. Table 8 presents the values for standardized factor loadings, standard error, and significance of the paths in this measurement model. Accordingly, it is observed that t-values are >1.96 for all indicators. It can, therefore, be said that all selected dimensions are accurate enough to measure the effect of the value chain on the livelihood level of olive orchard owners. Indeed, the results of CFA confirm the significance and fit of the model for measuring the effect of the olive value chain on the livelihood level within the five-fold capitals.
Then, the standardized path coefficient (λ) and its significance level were calculated for the five capital groups to rank them in terms of their effectiveness in the livelihood level of the olive orchard owners in Rudbar (Table 9). Standardized path coefficients represent the intensity of the relationship between first-order factors and the second-order factor. According to the results, social capital is the strongest index (λ = 1.02). Other capital groups were arranged in the order of human capital, natural capital, financial capital, and physical capital in terms of their importance in measuring the livelihood level of the olive orchard owners in Rudbar.
The results for testing hypothesis 1 showed that the standardized path coefficient between the two variables (the olive value chain and capital assets) was β = 0.98 and the coefficient of significance (t-statistic) between these two variables was t = 9.53 (which is >1.96), so this relationship is significant. So, H0 is refuted and H1 is supported. It can be concluded that the olive value chain affects capital assets significantly. This is in agreement with the results reported by Mchopa et al. (2021) and Tejada et al. (2019).
According to the results about hypothesis 2, the standardized path coefficient is β = 0.30 between the two variables including capital assets and the livelihood level of the orchard owners, and the coefficient of significance (t-statistic) is t = 2.13 (>1.96) between them, reflecting the significance of the relationship. So, H0 is refuted and H1 is supported, and it can be inferred that capital assets influence the livelihood level of the orchard owners significantly. This is consistent with the reports of Najafi et al. (2016), Pravakar et al. (2013), Badko et al. (2020), Aazami and Shanazi (2018), and Nazari Gooran et al. (2020).
Based on the results for hypothesis 3, the standardized path coefficient and the coefficient of significance (t-statistic) between the two variables of the olive value chain and the livelihood level were estimated at β = 0.7 and t = 3.28 (>1.96), showing that the relationship is statistically significant. So, H0 is rejected and H1 is supported, and it is found that the olive value chain has a significant effect on the livelihood level. Similar results have been reported by Mchopa et al. (2021) and Tejada et al. (2019).
5 Conclusions and Recommendations
Optimal use of resources and facilities to meet human needs, including increasing production, income, employment, and welfare, is one of the most important development goals in all countries.
The livelihood status of the olive orchard owners was studied in Rudbar County from the perspective of the respondents. The results show that the promotion and development of the value chain activities can increase livelihood assets and subsequently, livelihood outcomes. According to the results, the indicators selected for the research exhibited their significant effect on measuring capital assets (natural, human, social, physical, and financial) and the olive value chain in Rudbar County. So, the model has an appropriate structure given the significance of all dimensions of capital assets and their measurement indicators and acceptably fits the theoretical foundation of the research. It means that the component of capital assets has a positive effect on the livelihood of olive orchard owners.
Based on the results, olive production and processing create financial capital and improve the income of those employed in this job, which is, in turn, a way to improve livelihood, increase assets, enhance the welfare of olive orchard owners, and increase crop security and production. To increase income and further boost this activity, it is recommended to reduce power and water tariffs, subsidize inputs, help crop marketing, reduce wastage, and grant low-interest bank facilities.
The development of the business environment through the use of technologies required for the production and supply of new olive products in new and diverse packaging is one of the value chain needs of this product.
It is suggested that the necessary infrastructure be provided so that the crop can be marketed quickly. Also, the profession should be supported by providing facilities so that the physical capital of households is improved. Example measures include purchasing transportation equipment and processing equipment, creating a suitable road to access the garden, providing suitable housing, and providing more access to media and communication networks.
According to the results, it is suggested that by equipping olive processing plants and constructing processing plants for oil extraction waste, waste management be done in order to protect the environment and increase productivity in the field of olive processing industries.
Based on the results, the factors underpinning the olive value chain influence the components of the capital assets positively. So, given the positive and significant relationship of the assets and factors influencing the olive value chain with the livelihood of orchard owners and the valuable advantages of this activity including increased income, increased production, higher per capita consumption, and so on, it is recommended to resolve the barriers hindering the development of this economic activity as much as possible.
Despite the health benefits of olives, they are not a staple in Iran and our per capita consumption of olives is low compared to European countries. Considering that the use of the oil of this high-quality and nutritionally valuable product will improve health, it is suggested to take measures to include this crop in the food basket of Iranians.
The research focused on the effect of the olive value chain on the livelihood of olive orchard owners whereas their livelihood is influenced by numerous factors. So, it is recommended to scrutinize the research literature to derive and study the tools equivalent to other factors.
6 References
Aazami, M., & Shanazi, K. (2018). The impacts of Zarivar wetland on the livelihood assets of rural households. Geography and Development Iranian Journal, 16(51), 25-42. doi: 10.22111/gdij.2018.3848(In Persian)
Ahmadi, A., Motieee, H., Riyahi, V., & Halalian, H. (2019). Analysis of levels of sustainable livelihoods of villagers (Case study of villages in Saqez city). Journal of Rural Development Strategies, 6(1), 3-19. doi: 10.22048/rdsj.2019.140559.1747 (In Persian with an English Abstract)
Andre Devaux, Maximo Torero, Jason Donovan, Douglas Horton, (2018). "Agricultural innovation and inclusive value-chain development: a review", Journal of Agribusiness in Developing and Emerging Economies, Vol. 8 Issue: 1, pp.99-123
Ariuon, S., Sahneh, B., & Khajeh Shahkoohi, A. (2022). The role of greenhouse farming on the sustainable livelihood of rural families Case study: Daland Township, the City of Ramian. Human Geography Research, 54(1), 155-172. doi: 10.22059/jhgr.2020.307576.1008155. (In Persian)
Asghari Saraskanrud, S., Jalalian, H., Azizpur, F., & Asghari Saraskanrud, S. (2016). Choosing the optimized srtategy of sustainable livlihood faced with drought by using integrated model SWOT and TOPSIS Case study: Rural areas of central district of Hashtrood. Journal of Geographic Space, 16(55), 313-339. (In Persian)
Azizi. Jafar. (2008). Investigating the process of changes in efficiency and technology in Iran's olive industries. Journal of Agricultural Policy and Research. No.3.VOL.12.Pages: 43-60.
Azizi. Jafar. And Aref Eshghi. Taravat. (2011). The role of information and communication technology (ICT) in Iranian olive industrial cluster. Journal of Agricultural Science, 3(1), 228-240.
Badko, B., Ghasemi Siani, M., Ranjbaraki, A., Shambiati, M.H., & Shakiba, A. (2020). Assessing the livelihood capital of mountainous villages with a sustainable livelihood approach (Case study: Kouhshah Rural District, Ahmadi District -Hormozgan). Journal of the Geographical Studies of Mountainous Areas, 1 (3) :53-65. (In Persian with an English Abstract)
Barimani, F., Rasti, F.,Raeisi, I., & Mohammadzadeh, M. (2016). An analysis of geographical factors influencing household livelihood in rural residential areas: A case study of Qasr-e-qand County. Geography and Territorial Spatial Arrangement, 6(18), 85-96. doi: 10.22111/gaij.2016.2370(In Persian)
Bellu L. G., 2013. Value Chain Analysis for Policy Making: Methodological Guidelines and Country Cases for a Quantitative Approach. EASYPol Series 129, FAO.,166 pp
Boudi, Melkhire, Khaled Laoubi, and Fouad Chehat. "A value chain analysis for sustainable development of olive oil agro-industry: the case of Algeria." Journal of Agriculture and Environment for International Development (JAEID) 110.2 (2016): 267-292
Chegini, S., Shams, A., Gheidi, A., & Karami Dehkordi, E. (2015). Factors associated with the marketing behavior (selling type) of olive farmers in the Tarom Township. Journal of Rural Development Strategies, 2(3), 271-286. doi: 10.22048/rdsj.2015.15049 (In Persian with an English Abstract)
Department for International Development (DFID).(2008). Sustainable livelihoods guidance sheets, numbers*22 1–8. London: Department for International Development.
Diniz, F. H., Kok, K., Hoogstra-Klein, M. A., & Arts, B. (2015). Mapping future changes in livelihood security and environmental sustainability based on perceptions of small farmers in the Brazilian Amazon. Ecology and Society, 20(2).
Ellis, F. (2000). Rural livelihoods and diversity in developing countries. Oxford university press.
FAOSTAT statistical database, 2021. URL: www.faostat.fao.org
Fournier, A. (2019). Vulnerability and Livelihood Influences of Urban Agriculture and Fruit and Vegetable Value Chains in Lebanon (Doctoral dissertation, Université d'Ottawa/University of Ottawa
García Tejada, M. P. (2019). Diagnóstico de la cadena productiva del olivo para mejorar las condiciones económicas de los pequeños productores en el distrito de Bella Unión-provincia de Caravelí–región Arequipa.
International Olive Council, 2020. https://www.internationaloliveoil.org/
International Olive Oil Council, 2020. Available at: www.internationaloliveoil.org
Isazehi, A., & Sharifzadeh, M. (2021). An analysis of the status of rural sustainable livelihood assets in Saravan County. Journal of Space Economy & Rural Development, 10(36), 79-98. (In Persian)
Jahad Agriculture Organization of Guilan Province.(2021). Deputy of Planning and Economy, Horticultural crop production rate in Rudbar County. Available on http://jkgc.ir/.ir,: retrieved on October 3 , 2021.
Kheiri, S. (2007). An educational needs assessment of olive orchard owners regarding the improvement and development of olive orchards in Viarah Village, Rudbar County. Journal of Jahad (Agricultural Extension and Rural Development), 140, 129-277. (In Persian)
Krap, T. D. (2012). Markets and livelihoods. Bringing a livelihood perspective to the apple value chain in Jumla, Nepal (Master's thesis).
Mchopa, A. D., Jeckoniah, J. N., & Mgema, J. M. (2021). Smallholder Agriculture and Livelihood Sustainability Potentials among Rural Households: A Case of Sunflower Value Chain in Tanzania. Journal of Social Sciences, Business and Technology (JSSBT), 2(2), 1-10.
Najafi, H., & Karim, M., & Rangriz, H. (2016). The effect of different factors on improvement the management of olive orchards in Tarom County with emphasis on bank facilities. Eqtesad-E Keshavarzi Va Towse'e, 24(95), 107-121.
Nazari Gooran, A., Mojaverian, S., Pishvaee, M. (2020). Green closed-loop supply chain design of olive under risk conditions. Agricultural Economics and Development, 28(3), 31-63. doi: 10.30490/aead.2020.312856.1102
Pravakar, Pijush, et al. "Present status of fish farming and livelihood of fish farmers in Shahrasti upazila of Chandpur district, Bangladesh." American-Eurasian Journal of Agricultural and Environmental Science 13.3 (2013): 391-97.
Sadrmousavi, M.S., Aghayarihir, M., & Valaei, M. (2021). Affecting factors in poverty reduction in rural areas in Miandoab County. Journal of Space Economy & Rural Development, 9(34), 193-216. (In Persian)
Sawari, M., Shabanali Femi, H., Irvani, H., & Asadi, A. (2018). Developing a paradigm to ensure sustainability of smallholders’ livelihood in drought conditions in Kurdistan province. Journal of Spatial Analysis & Environmental Hazards, 5(2), 1-18. (In Persian)
Shah, K. U., Dulal, H. B., Johnson, C., & Baptiste, A. (2013). Understanding livelihood vulnerability to climate change: Applying the livelihood vulnerability index in Trinidad and Tobago. Geoforum, 47, 125-137.
Sharifinia, Z. (2021). Analysis of factors affecting livelihood sustainability in rural areas of Sari County. Journal of Space Economy & Rural Development, 10(35), 213-236. (In Persian)
Sojasi Ghidari, H., Sadeqlu, T., & Shakourifard, E. (2016). Measuring the livelihood properties in rural areas using a sustainable livelihood approach (Case study: Rural areas of Taybad County). Journal of Research and Rural Planning, 5(1), 197-215. doi: 10.22067/jrrp.v5i1.48257 (In Persian with an English Abstract)
Soleymani, T.S.M., Abdollahzadeh, G., & Sharifzadeh, M.S. (2020). Strategic planning for developing supply chain of olive in Roudbar County, Guilan Province. Journal of Entrepreneurial Strategies in Agriculture, 6 (12): 98-111. (In Persian with an English Abstract)
Su, Z., Aaron, J. R., Guan, Y., & Wang, H. (2019). Sustainable livelihood capital and strategy in rural tourism households: A seasonality perspective. Sustainability, 11(18), 4833.
Subba, S. A., Kushwaha, S., & Deleuran, L. C. (2016). Assessing the impact of a sustainable bio-intensive farming system and a conventional farming system on the livelihood and food security of farmers in the Udayapur District, Nepal. Nepalese Journal of Agricultural Sciences, 14, 249-260.
UNIDO., 2009b. Agro-value chain analysis and development: The UNIDO approach.Working paper, Vienna., 74 pp
United Nations Industrial Development Organization (UNIDO), International Fund for Agriculture Development, & Food and Agriculture Organization (FAO). (2008). The importance of agro industry for socio-economic development and poverty reduction. Paper presented at The Side-Event on How Agro-Industry Can Help Eradicate Poverty. New York, USA, 5–16 May 2008.
Veisi, F., & Nikkhah, C. (2019). Analysis of the role of tourism in sustainable livelihoods of rural households, Case Study: Oraman distrct in Sarvabad County. Geography and Planning, 22(66), 329-348. (In Persian)
Zenteno, M, Z., Pieter A., Jong, Wil de, Boot, René G.A (2013). Livelihood strategies and forest dependence: New insights from Bolivian forest communities”, Forest Policy and Economics.26:12-21, https://doi.org/10.1016/j.forpol.2012.09.011
