Masoud Hekmat Department of Agricultural Development, Science and Research Branch, Islamic Azad University, Tehran, Iran

Transcription

1 Studying the Effect of the Factors Affecting the Agricultural Business Marketing Innovation Clusters (Case Study: Date Business Cluster in Khuzestan Province) Masoud Hekmat Department of Agricultural Development, Science and Research Branch, Islamic Azad University, Tehran, Iran Seyed Mehdi Mirdamadi: Corresponding Author Associate Professor, Department of Agricultural Development, Science and Research Branch, Islamic Azad University, Tehran, Iran Seyed Jamal Farajollah Hosseini Associate Professor, Department of Agricultural Extension and Education, Science and Research Branch, Islamic Azad University, Tehran, Iran Davood Samari Associate Professor, Islamic Azad University, Karaj Branch, Karaj, Iran Mohsen Ebrahimpour Institute of Planning and Agricultural Economics Research, Tehran, Iran Abstract: Identifying the effect of the factors affecting the agricultural business marketing innovation clusters is the aim of this study. Regarding the nature of the subject, this study is quantitative and regarding the purpose, it is applied. In terms of methodology, it is descriptive-correlational and analytical, and causal-relational type regarding controlling the variables, and in terms of time, it is a review study. The study population includes all executives, assistants, and marketing staff of date production and processing workshops that are members of the date business cluster of Khuzestan. They are totally 67 workshops in which 392 people are employed in marketing. In this study, to determine the study population, random sampling method was used and the number of sample was selected in proportion to the village population. Using the table provided by Krejcie and Morgan (1970) and according to the number of people and volume of the study sample size, the study population was estimated as n=190. Dependent variable is marketing innovation aspects in date business cluster and independent variables are individual characteristics, policy factors, underlying factors, economic factors, social factors, management factors and educational factors. The results of stepwise regression showed that policy, educational, social, economic and management factors interactively explained 83.3 percent of the changes of the dependent variable of the study, as well as the results of the path analysis showed that educational-promoting factors, with overall impact, have the highest impact on the dependent variable and social factors with direct impact have least effect on the dependent variable. Keywords: Business cluster, Khuzestan, Dates, Marketing, and Innovation. 333

2 1- Introduction Today, in most countries of the world, small and medium enterprises play a key role in job creation and economic development of communities. Necessary studies on the potential of sustainable economic growth have not been fully articulated so far, often due to a specific set of problems and obstacles for small and medium enterprises (SMEs) related to their size and relations. These production units are not capable of receiving and capturing market opportunities that require large quantities, homogenous standards and regular supply individually. In this regard, their experience difficulties in achieving economies scale in the purchase and supply of inputs such as equipment, raw materials, financing, consulting services and so on acts as a deterrent (Scheer and Zallinger, 2007). One of the major factors that lead to failure to achieve the objectives of agricultural development and increased production and income of farmers in developing countries is the agricultural marketing system failure. Today, in most advanced countries, marketing of agricultural products is considered as one of the main economic sectors. Given the current world situation, the production has gotten out of traditional form and production for sale on the market is one of the main targets of the manufacturers. Market is the embodiment of all the activities of a producer to receive a profit from production. Thus, marketing campaign does not start from the beginning of harvest time, but from the time of decision to produce. In this regard, the marketing of agricultural products due to the specific characteristics of these products, which includes corruptibility, seasonality, and demand for all seasons, gets particular importance. One of the things that have always been discussed in the marketing of agricultural products in less developed countries, including Iran, is the difference between producer price that is the price the producer receives and the price that the consumer pays. However, it should not be assumed that this price difference is only in developing countries, it exists in developed countries as well. Nevertheless, here the difference between the higher prices is due to services such as packing, grading and converting the product while is in less developed countries little service is done on the product. One of the factors blamed for this difference in prices is mediating factor called speculators. This mediating factor has relatively a decisive role in prices partly due to control of the market and creating a monopoly that great profits is obtained (Mirzajani, 2011). Marketing is recognizing consumer behavior, measuring it, converting this information to planning production to meet the needs. In other words, marketing is a conscious effort to create an efficient allocation of resources and creating a kind of expertise in the market. Organizations must find their target market to better identify their needs to develop and provide products and services tailored to them. The base of marketing effort is to avoid wasting resources and different facilities. Marketing means segmenting or market regulation and determining products for the most appropriate markets (Mahdipoor, et al., 2005). Business clusters of agriculture could be the engine of national and regional economy, as well as the development of enterprises and production units in the form of cluster, due to increased cooperation and collaborative activities, will be more efficient. On the other hand, attention to the Agricultural Marketing business clusters and creating and deploying an innovative marketing system could increase the number of production units in the region, improve employment, boost exports, create links with other areas, and identify and access new markets. 334

3 One of the major concepts that are widely used in developing countries is development. Certainly when it comes to the development of countries and societies, one of its most important ways and perhaps the first ones to attract the minds of others is the employment status of the countries. Basically, development has a quality and all-round concept and includes all political, cultural, social and economic aspects. However, in most cases because of the important role of employment growth and job creation in the developing countries, the economic growth of developing countries is taken as synonymous to development (Hadadpour, 2012). This study seeks to identify factors influencing the innovation in marketing of date business cluster in Khuzestan, so that the products can be supplied to consumer markets in simple ways, and on the other the revenue of the producers of date could noticeably be increased through less role of intermediaries and speculators. Obviously, achieving these goals paves the way for the entry of others interested in production. Thus, the improvement of employment in the region would not be expected as far and will have economic development in the study area. Kafashpoor et al (2014) conducted a study as Effective factors on attracting new customers, loyal customers, and network marketing (Case study: the well-known food brands). The results of this study emphasize the importance of quality on customer satisfaction and loyalty, and the effect of both on the positive publicity of the customer (attracting new customers by previous customer. Saafi Sis et al (2014) carried out a study called The analysis of social capital actors and resources in the adoption of innovations by farmers for agricultural innovation system (research in Shabestar in East Azarbaijan province). The results showed that social capital of ideological leaders with impact factor of 0.821, government agricultural extension agents with impact factor 0.434, and farmers' family and colleagues with impact factor have the highest power to affect the behavior of agricultural innovation adoption by the farmer. Khamesi (2013) in a study titled Pathology of the development of industrial clusters in the Iran, case study of agricultural industrial cluster of Jouybar stated that according to the position of small and medium enterprises in the industrial development of communities and their valuable contribution in applying a great part of the work force highlight the attention to this sector. The results showed important indices for the development of industrial clusters such as the government and policymakers, investment, financial incentives, training and extension, infrastructure, knowledge and relationship with the university and culture. Ali Mirzaee and colleagues (2011) conducted a study titled Obstacles to the development of small and medium rural entrepreneurship enterprises as in Khuzestan (Case Study: date complementary industries). The results of the factor analysis showed that the holders have agreed on four factors: infrastructure, marketing, management and policy and overall explained 53.94% of the total variance. Moreira et al (2015) conducted a study called (Drivers of marketing innovation in companies in Portugal. The results showed that the financial support of the research and development of research activities within the company: the acquisition of machinery, software, and equipment, acquisition of foreign knowledge and performance of other producers affect marketing activities towards the tendency of companies to innovate in the marketing process. Mumtaz Baloch and Gopal Thapa (2014) conducted a study titled Agricultural Extension in Pakistan: access and content of date owners. Logistic regression analysis identified 5 variables out of 6 variables that had a significant effect on date owners access to extension services including age of household head, education of household head, number of palms owned 335

4 by the household head, the trees inherited and the percentage of dead trees. The majority of farmers were not satisfied with three main ways to promote public extension services provided by the authorities. In order to overcome this shortcoming, reviewing policy and advocacy planning largely eliminates the problem of agriculture. Ghanee (2014) conducted a study titled Status of Iranian date market and its ability to enter the EU market. The results showed that Europe date imports has allocated 10% of world imports to itself while its value is 30% of the total value of world exports. The results reflect the fact that any country wishing to enter EU market to export date to Europe, at first must be removed from their traditional state. However, with ups and downs in the export, Iran does not have a permanent and stable overseas market, but Iran has the opportunity to match its date in line with international standards in terms of quality and packaging and in this way achieve widespread markets. 2- Research Methodology Regarding the nature of the subject, this study is quantitative and regarding the purpose, it is applied. In terms of methodology, it is descriptive-correlational and analytical, and causalrelational type regarding controlling the variables, and in terms of time, it is a review study. The study population includes all executives, assistants, and marketing staff of date production and processing workshops that are members of the date business cluster of Khuzestan. They are totally 67 workshops in which 392 people are employed in marketing. In this study, to determine the study population, random sampling method was used and the number of sample was selected in proportion to the village population. Using the table provided by Krejcie and Morgan (1970) and according to the number of people and volume of the study sample size, the study population was estimated as n=190. Dependent variable is marketing innovation aspects in date business cluster, which includes three aspects: innovation activities, innovation management, and cultural factors. Independent variables in this study are in the following groups: Individual characteristics (age, sex, level of education, experience in the production and marketing of dates, marital status), policy factors, underlying factors, economic factors, social factors, management factors, and educational factors. In the statistical analysis to examine the relationship between variables based on their scale, correlation coefficient like Spearman and Pearson correlation coefficient are used and to study the differences between different groups on different levels of the dependent variable, tests such as Mann-Whitney test were used. To identify the combined effects of the independent variables on the dependent variable, enter regression method was used. To identify the major factors affecting the research, stepwise regression is used. The impact of low efficacy variables, removed in stepwise regression, was obtained from the difference between enter and stepwise regression. To identify the direct and indirect effects of independent variables on the dependent variable, path analysis was used. 3- Results The results obtained showed that 79.5% of the respondents with frequency of 151 were men and 20.5 were women with frequency of 39. In studying the marital status, it was found that 27.9% of the study population with 53 frequency were single and 72.1% with a frequency of 137 were married. The data showed that of the total of 190 staff members of the date business cluster associated with marketing activities regarding the age groups, 5.9% with a frequency of 11 subjects are 336

5 less than 20 years, 35.3% with a frequency of 67 people in the group of years, 43.6% with frequency of 83 are in age group, 11.6% with a frequency of 22 people in the group and 3.7% with a frequency of 7 persons are in 66 years and over group. The results showed that 4.7% of subjects with a frequency of 9 people in terms of education are illiterate, 10.5 percent with a frequency of 20 have elementary level studies, 17.4% with a frequency of 33 people have guidance school education, 20 percent with a frequency of 38 subjects have high school education, 25.3 percent with a frequency of 48 have a diploma, and 22.1% percent with a frequency of 42 have higher than diploma level of education.the results showed that 60% of subjects with a frequency of 114 in terms of experience in date production are in 1 to 5 years' experience, 19.5 percent with a frequency of 37 people are in group of 6 to 10 years, 8.4 percent with a frequency of 16 people are in from 11 to 15 years, 3.2% percent with a frequency of 6 people from 16 to 20 years, 7.3 percent with a frequency of 14 persons at 21 to 25 years of experience and 1.6% with a frequency of 3 subjects are in the group of 26 to 30 years of experience. The results showed that 76.8% of subjects with a frequency of 146 in terms of marketing experience of date are in group 1 to 10 years, 11.6% with a frequency of 22 are in the group of 11 to 20 years of experience, 10% with a frequency of 19 people in the group from 21 to 30 years and 1.6%, with a frequency of 3 subjects are in 31 to 40 years (table 1). Table 1. Distribution of individuals according to personal characteristics Variables frequency (n) Percent The cumulative percentage Gender Man Women Marital status Single Married Age Groups Less than to to to and over Education illiterate Elementary Guidance High school Diploma Higher than diploma The record in date production 1 to to to to to to

6 marketing innovation of date business clusters Row Studying the Effect of the Factors Affecting the Agricultural Business Marketing experience 1 to to to to To investigate the relationship between the variables according to the scale of each, it was attempted to calculate the correlation coefficients between them and examine the significance levels. The results showed that policy, infrastructure, social, economic, administrative, educational and promoting factors have a significant positive correlation at 99% level with the dependent variable (marketing innovation of date business clusters) and (Table 2). Table 2: Correlation between marketing innovation of date business clusters and independent variables The first variable The second variable Pearson correlation The significanc Variable Scale Variable Scale coefficient e level 1 Age Interval Ordinal The experience in Relative Ordinal marketing 3 Experience in dates Ordinal Factors policymakers Ordinal Ordinal 0.742** Infrastructure factors Ordinal Ordinal 0.741** Social factors Ordinal Ordinal 0.759** Economic factors Ordinal Ordinal 0.812** Management factors Ordinal Ordinal 0.790** Educationalpromotional Ordinal Ordinal 0.837** factors 10 Level of Education Ordinal Ordinal **P<0.01 *P<0.05 To compare the average rating is expressed in terms of the respondents in the study based on gender and difference between them Mann-Whitney test was used. Given the significance level obtained (0.662), it can be concluded that there is no significant difference in terms of gender in the average rating of respondents' idea. Moreover, to compare the rating average of respondents' comment based on marital status and their difference Mann-Whitney test was used. Given the significance level obtained (0.888), it can be concluded that there is no significant difference in the average ranking in terms gender (Table 3). Table 3: Comparing the average of respondents' views on aspects of marketing innovation of date business clusters based on gender and marital status Dependent variable Marketing Innovation of Date Business Cluster **P<0.01 *P<0.05 independent variable Group Frequency Average rating Gender Man Woman Marital Single status Married Value of U Significance level

7 - Stepwise multiple regression analysis In this method, the independent variables that have had significant role on the dependent variable enter the equation to determine the role of each of them on the dependent variable. So in order to analyze the role of the seven independent variable that have had a significant role on the dependent variable (aspects of marketing innovation of date business clusters), stepwise multiple regression analysis was used. Based on the results of the regression, political factors, educational factors, social factors, economic factors, and management factors were kept in the equation and interactively explained 83.3% of the dependent variable changes (aspects of marketing innovation of date business clusters). According to the results of Enter regression, two other independent variables (infrastructure factors and number of family members) that have significant roles on the dependent variable could explain only 0.3 percent of the dependent variable changes. Accordingly, 16.4 percent of the dependent variable changes are explained by other factors that were not considered in this study. To compare the effects of five independent variables in the regression model on the dependent variable, standardized beta coefficients were used that showed that independent variable educational factor has the greatest role in the field of marketing innovation. According to the regression coefficients and constants obtained from analysis of the stepwise multiple regression, regression model of the study was obtained as follows. It should be noted that independent variables that have nominal scale virtually entered the regression equation (Table 4 and 5). Table 4: Correlation coefficients of the variables affecting marketing innovation of date business clusters Step Model The Correlation Coefficient R Coefficient of Determination (R2) Adjusted Coefficient of Determination (R2Adj) 1 First step Second step Third Step Fourth Step Fifth Step Table 5: T value of variables affecting marketing innovation of date business clusters Predictor Variables Intercept Educational factors Economic factors Management factors Policymakers factors social factors Non-Standardized Coefficients Enter Coefficient The Standard Error Standardized Coefficients Beta Calculated T R= R = R 2 Adj=0.833 Sig F=0.000 Significance level

8 - Path analysis Path analysis is of multivariate techniques that in addition to studying direct effects of the independent variables on the dependent variable consider the indirect effects of these variables. Path analysis techniques are based on a set of multiple regression analysis based on the assumption of the relationships between independent and dependent variables. This method puts special emphasis on innovative use of visual diagram known as path diagram (Kalantari, 2012). Based on the results of multiple stepwise regression variables, policy making, economic, social, management and educational factors have had the greatest impact on the dependent variable interactively (aspects of marketing innovation of date business clusters) and based on the extent of impact each has entered a visual and an innovative diagram so that besides the direct impact of the independent variables on the dependent variable, their indirect impact is also evaluated (Table 6). After multiple analyses, path analysis graph of this study was presented as follows: Figure 1: Path Analysis Diagram Table 6: Total direct and indirect effects of independent variables on the dependent variable Independent variable Indirect Direct effects Total direct and indirect effects of each effects variable Educational- extension factors Management factors Economic factors Policymaking factors Social factors The results of path analysis showed that educational factors with indirect effect and direct effect and total impact has the maximum effectiveness on the dependent 340

9 variable (aspects of marketing innovation of date business clusters), management factors with indirect effect and direct effect and total impact , economic factors with indirect effect and direct effect and total impact , policy making factors with indirect effect and direct effect and total impact and social factors with direct effect on the dependent variable have interactively explained the dependent variable. 4- Discussion and conclusion Management factors have an impact on marketing innovation of date business clusters. This result is consistent with many studies such as Ali Mirzaee and colleagues (2011), Kafashpour and his colleagues (2014). It seems that the development of a strategic plan by the manager, getting advice from marketing experts by the manager and using specialists can pave the ground for marketing innovation in marketing innovation of date business clusters. Social factors have an impact on marketing innovation of date business clusters. This result is consistent with studies such as Ali Mirzaee and colleagues (2011), Moreira et al (2015). It seems that the improvement of date consumption culture in the community and considering the need of the consumer can provide the grounds for marketing innovation in date business clusters. Economic factors have an impact on marketing innovation of date business clusters. This result is consistent with different studies such as Khamesi (2013), Saafi Sis and colleagues (2014) and Ghane (2014). It seems that regulating the pricing of date, narrowing the gap between wholesale and retail prices, and creating financial incentives, price adjustment, and processing industry on the market could pave the ground for the creation of marketing innovation in dates business clusters. Policy making factors have an impact on marketing innovation of date business clusters. This result is consistent with different studies such as Sabour and colleagues (2013), Ali Mirzaee and colleagues (2011), and Moreira et al (2015). This result suggests that the adjustment of the agricultural sector in relation to the date and manner of its exports, improving marketing research and complementary industries and increasing the capacity of the Union of date in protecting the rights of its members can lead to innovation in date business clusters. Participating in educational-promotion courses has an impact on marketing innovation of date business clusters. This result is consistent with different studies such as Ali Mirzaee and colleagues (2011) and Mumtaz Baloch and Gopal Thapa (2014). This result suggests that holding educational courses for managers for familiarity with marketing firms, and specialized training programs for managers of enterprises, increasing advertising and marketing courses in innovative thinking can lead to innovation in date business clusters. - Suggestions From delving into research, particularly the analytical results, some suggestions on policymaking, educational-promotion, infrastructure, social, economic and management factors can be given as follows to promote innovation in the field of innovation in date business clusters. However, achieving some of these goals and improving educational programs to encourage authorities of business workshops in the field of innovation in date 341

10 business clusters should be considered by the authorities and other stakeholders of the agricultural sector so that in the field of marketing innovation, managers can improve their levels from lower and average levels. Today, to be able to survive in the face of diversification and changes in market and be able to make policies in the market, the agricultural workshops need market analysis and information. To this end, workshops should update their business processes using new technologies that are called business intelligence. Using business intelligence, businesses are able to develop information systems based on secret information to create a business insight to help them making faster and more reliable decisions. Development of business areas, leading and purposeful presence in the international environment and increasing the efficiency of the workshops are of the key functions. Since 84.7 percent of producers are less than 50 years old, and on the other hand over 60 percent of producers have less than 5 years experience of producing dates, it is recommended that dried fruits and dates union get help from people with experience and expertise in date production as consultants. Moreover, given that 92.9 percent of producers in terms of education are in diploma level or lower, it is recommended that higher education institutions (such as scientific-practical universities, centers for agricultural education, agriculture, etc.), as well as other courses that have been required for the regional market and created in these centers, make serious effort to establish the field of manufacturing and marketing of dates, because the dates is the most strategic crops of Khuzestan and has always had good exchange bringing for the country. The results showed that there is a significant positive relationship between management and marketing innovation of date business clusters. Therefore, it is recommended that managers and owners of workshops develop a strategic plan and an appropriate strategy of marketing along with obtaining advice from experts and using specialists increase their ability to innovate and while reducing production costs can be able to create new demand for production units. References: 1) Alimirzayi, A., Asadi, A., Tahmasebi, M. (2011). Obstacles to the development of small and medium enterprises, rural entrepreneurship in the province (Case Study: date complementary industries). Entrepreneurship Development, Issue XII, pp ) Ghane, S. (2014). Resume of Iran Date Market And Its Potential To Enter The Eu Market. Advances in Environmental Biology, Vol 8(9), Pp ) Hadadpour, k. (2012). Cooperation and its role in economic development. Official website of the Department of Cooperatives, Labour and Social Affairs of the Alborz province, available at: 4) Kafashpour, A., Kariznoei, A., Hoseini mogaddam, S. M. R. (2014). Factors affecting attract new customers, loyal customers, network marketing (Case study: the wellknown brands in the food industry). First National Conference on Marketing: Opportunities and Challenges, Mashhad, p. 1. 5) Krejcie, R. V., Morgan, D. W. (1970). Determining Sample Size for Research Activities, Educational and Psychological Measurement. 6) Khamesi, S. J. (2013). Pathology as the development of industrial clusters in the country, the agricultural industry cluster study streams. Dissertation, Department 342

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