Determinants of Performance of Innovative Integration Summer Flower Value Chain among Medium and Small-Scale Farmers Kenya.

Determinants of Performance of Innovative Integration Summer Flower Value Chain among Medium and Small-Scale Farmers Kenya.

Dennis Otieno

Murang’a University of Technology 

DOI: https://dx.doi.org/10.47772/IJRISS.2024.806173

Received: 10 October 2023; Revised: 22 February 2024; Accepted: 17 June 2024; Published: 16 July 2024

ABSTRACT

The floriculture industry has undergone significant changes due to evolving global consumption patterns. While previous studies have primarily focused on large-scale production, there is a growing need to understand the potential of small-scale flower production. This study aimed to address this gap by examining the drivers of summer flower production among small-scale flower producers. The research was guided by theories such as global value/supply chain theory, strategic management theory, institutional theory, and transaction cost theory. A mixed-method approach was employed to collect data from 217 medium and small-scale summer flower growers in Kenya. The study findings indicate that the agribusiness value chain has a positive impact on the performance of summer flower farmers. Additionally, partnerships play a crucial role in ensuring just-in-time delivery to direct market

Key words:  Markets; Performance; Flowers; Value Chain; Partnerships.

INTRODUCTION

Agriculture indeed plays a significant role in economic growth and poverty reduction in developing countries. Prioritizing agricultural investment can generate benefits that have a positive trickle-down effect on other sectors of the economy¹. Globalization has been a key driver of expansion and evolution in the agricultural input supply chain system¹². It has transformed the world from fragmented economies into a unified trading bloc, offering enormous opportunities while intensifying competition and increasing demand on market players¹. To capitalize on the emerging opportunities, farmers must transform and improve their performance¹.

However, the global market is dominated by commission-based or auction transactions, such as the Tele Flower Auction and direct selling through Flora Holland in the Netherlands, which serves as a major hub for flower trading in Europe and worldwide¹. These marketing approaches tend to favor large-scale farmers who dominate the markets¹.

Small-scale flower farmers face challenges due to their lower output levels, limited access to foreign exchange for purchasing necessary imported inputs, and high airfreight costs resulting from government taxes on aviation fuel¹. To remain competitive in the flower sector, small-scale farmers are adopting innovative measures. Traditional food production methods are being replaced by practices that resemble manufacturing processes, with increased coordination among farmers, processors, retailers, and other stakeholders in the value chain¹. These practices enhance the value of the commodity. To maximize returns and adapt to these changes, farmers should integrate innovative value-addition, horizontal coordination, and vertical coordination strategies. These approaches facilitate the flow of superior products and services between suppliers and end-users¹. lack of such approaches  created the gap that motivated this study to generate additional  knowledge to inform discourse on summer flower production. Further, the agribusiness value chain, innovation and strategic alliance aspects of the horticulture value chain remain unexplored.  In this context, this study analysed multiple variables that related strategic value chain integration and performance among small scale summer flower farmers.

General Objective

The general aim of this study was to assess the influence of agribusiness value chain on performance of small-scale summer flowers in Nyeri, Murang’a and Kiambu Counties, Kenya.

Specific Objectives

1. To determine the level of farmer decision making on agribusiness value addition in small and medium scale summer flowers in Nyeri, Murang’a and Kiambu Counties.
2. To determine effect of coordination agribusiness value chain cost reduction strategy on performance of small and medium scale summer flowers in Nyeri, Murang’a and Kiambu Counties.
3. To find out how strategic alliances influence performance of small and medium scale summer flowers in Nyeri, Murang’a and Kiambu Counties.

Research Questions

1. What is the level of farmer decision making on agribusiness value addition in small and medium scale summer flowers in Nyeri, Murang’a and Kiambu Counties?
2. What is the effect of coordination agribusiness value chain cost reduction strategy on performance of small and medium scale summer flowers in Nyeri, Murang’a and Kiambu Counties ?
3. What is the effect of strategic alliance on the  performance of small-scale summer flowers in Nyeri, Murang’a and Kiambu Counties?

MATERIALS AND METHODS

Research Design

The study you mentioned employed a mixed-method approach, combining qualitative and quantitative data collection methods. This approach allows for a comprehensive understanding of the research topic by capturing both descriptive and statistical information. Qualitative data was used to complement and validate the findings obtained from quantitative data. The primary data collection involved engaging with farmers, traders, and key informants in the industry. The target population for this study was small and medium-scale summer flower growers in Nyeri, Murang’a, and Kiambu Counties, which are the major growing areas for summer flowers in Kenya. According to the Kenya Flower Council (2019), there are 472 small-scale summer flower growers in these three counties.

The sample size for a research study is an important consideration to ensure that the findings are statistically significant and representative of the target population. According to Mugenda & Mugenda (2003), a sample size ranging from 10% to 30% of the target population is generally considered a good representation. Bartlett et al. (2001) suggest that a 5% margin of error is acceptable in such situations.

To calculate the sample size, you can use the formula for a finite population as proposed by Yamane (1967) and cited in Israel (1992). This formula takes into account the desired confidence level, alpha level, and the size of the target population. For example, if you aim for a 95% confidence level and a 0.05 alpha level, a sample size of 217 farmers can be selected using random stratified sampling techniques. These farmers will serve as the ultimate sampling units and provide the necessary survey information. It’s important to involve various stakeholders in the flower industry, including regulators, growers, exporters, consumers, input suppliers, service providers, and traders, to ensure a comprehensive understanding of the value chain¹.

n =       N/1+N(e²)

Where:

n= desired sample size

N= Population

e = margin of error at 5% (standard value of 0.05)

The sample size for the study is:

n =       472/(1+472(0.05²))

=217 respondents

Data Collection Instrument

The study you mentioned employed a mixed-method approach, combining qualitative and quantitative data collection methods. This approach allows for a comprehensive understanding of the research topic by capturing both descriptive and statistical information. Qualitative data was used to complement and validate the findings obtained from quantitative data. The primary data collection involved engaging with farmers, traders, and key informants in the industry. The target population for this study was small and medium-scale summer flower growers in Nyeri, Murang’a, and Kiambu Counties, which are the major growing areas for summer flowers in Kenya. According to the Kenya Flower Council (2019), there are 472 small-scale summer flower growers in these three counties.

The study utilized questionnaires to obtain data from respondents. The questionnaires were calibrated using a five-point Likert Scale, ranging from ‘strongly agree’ (SA) to ‘strongly disagree’ (SD). The questionnaires consisted of both close-ended and open-ended items. Additionally, interviews were conducted to collect information from value chain traders and key informants. Pre-testing was conducted to ensure the accuracy, clarity, and suitability of the research instrument. The pre-test involved 10 small and medium-scale summer flower farmers who were not part of the survey. Content validity was examined to ensure that the instruments addressed all the research questions. Based on the analysis of the pre-test results, the researcher made corrections, adjustments, and additions to some of the research instruments¹.

Data Processing and Analysis

The data collected was coded and entered into the computer and analyzed using descriptive statistics with the help of SPSS version 24. Specific grouping categories was generated to account for the variables being developed by the descriptive statistics.

The linear regression model below was used;

            Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ +ε

Where Y is the organizational performance, β₀ is constant and ε is the error term of the model.

X₁        =          Farm Decision making

X₂             =         Coordination

X₃            =          Strategic alliances

The analytical was as follows

Objective 1. This was based on descriptive data mainly frequencies, means mode

Objective 2.  Descriptive data was grouped into categories depending on the number of activities carried out by the farmers and partners.

Objective 3 Descriptive data was grouped into categories depending on innovation activities carried out by the farmers and partners.

Objective 4. Performance levels was based on data categories and was determined by data aggregation at the means of likert scale data coded for joint decision making, commitment, coordination and partnerships. Data was  analysed using linear regression and coefficient of determination was derived to show how these variables are related.

Ethical Considerations

In the study you mentioned, participants were informed about the purpose of the research before their engagement. This ensured that they could provide informed consent and did not feel coerced into participating. Confidentiality was maintained to protect the identities of the respondents, and their information was not disclosed in the research findings. These measures were taken to minimize the chances of physical or psychological harm to the participants resulting from their involvement in the research.

RESULTS AND DISCUSSION

Study Variables

The study variables in this section were measured using Likert scale ranging from “‘strongly disagree’ (1) to ‘strongly agree’ (5). The scores of disagreeing have been taken to represent a variable which had a mean score of 0 to 2.4 on the continuous Likert scale; (0≤ Mean<2.4). The scores of ‘Undecided have been taken to represent a variable with a mean score of 2.5 to 3.4 on the continuous Likert scale: (2.5≤Mean<3.4) and the score of both agree and strongly agree have been taken to represent a variable which had a mean score of 3.5 to 5.0 on a continuous Likert scale; (3.5≤ S.A. <5.0)”. A standard deviation of > 0.9 implies a significant difference on the impact of the variable among respondents.

 Farmer Decision Making on Agribusiness Value Addition in Summer Flower

The study sought to determine farmers decision making on agribusiness value addition in summer flower in Kenya. The findings are as shown in Table 1 below;

Table 1 Farmer Decision Making on Agribusiness Value Addition in Summer Flower

The respondents strongly agreed that they work with partner who are suppliers of raw materials (mean=4.57, SD=1.038), and that strategic partners monitor product quality at some point of the value chain (mean=4.51, SD=1.104). They agreed that they work with strategic business partners who conduct value-adding activities (mean=4.32, SD=1.097), they adopt innovation in their service delivery (mean=4.24, SD=1.188). Further, the respondents agreed that partners manage the cold-chain and maintains the integrity of the aesthetic value of the flower commodity (mean=4.15, SD=1.47), strategic partners monitor product quality along the entire value chain (mean=3.70,SD=1.219), alliance they have established contributes to export-readiness by packaging the cut flowers into bouquets  (mean=3.85, SD=  0.942), and that their export partners add value to production by sharing export market information (mean=3.69, SD=1.253).The respondents however were undecided on managing their our cold-chain and maintaining the integrity of the aesthetic value of the flower commodity (mean=3.48, SD=1.185), and on innovating new products frequently            (mean=3.48, SD=.862). Further, the respondents Disagreed that they package the cut flowers into bouquets for export-readiness (mean=2.54, SD=1.359).

Coordination Agribusiness Value Chain Cost Reduction Strategy

This section of the questionnaire sought to get rating from the respondents on coordination agribusiness value chain cost reduction strategy adopted by summer flowers small scale farmers.

The respondents were asked to indicate the extent to which they agreed with various factors that on cost reduction strategy adopted by summer flowers small scale farmers using a five Likert scale of 5= strongly agree 4= agree 3= undecided 2= disagree 1= strongly disagree.

The results are shown in Table 2 below:

Table 2 Coordination Agribusiness Value Chain Cost Reduction Strategy

From the findings, the respondents strongly agreed that they have a close customer contact (mean=4.69, SD=1.072) and that their business strategies are driven by goal of increasing customer value (mean=4.67, SD=1.234). They also strongly agreed that they periodically review their product development to plan a response to changes taking place in our business environment (mean=4.61, SD=1.184). The respondents agreed that their business processes are designed to produce a specific output for a particular customer or market (mean=4.35, SD=1.143), farmers have invested in large scale production (mean=4.05, SD=0.954), and that summer flowers use low-cost energy in production process (mean=4.13, SD=1.119), and that they do a lot of market research to introduce new products (mean=4.16, SD=0.996). However, the respondents were undecided whether the customer’s interest always come first, ahead of the owners’ (mean=3.42, SD=1.183) and on developing new products frequently (mean=3.30, SD=1.178).

Strategic Alliances along small scale summer flowers value chain farmers

This section of the questionnaire sought to get rating from the respondents on strategic alliances along small scale summer flowers value chain farmers.

The respondents were asked to indicate the extent to which they agreed with various factors on strategic alliances along small scale summer flowers value chain farmers using a five Likert scale of 5= strongly agree 4= agree 3= undecided 2= disagree 1= strongly disagree.

The results are shown in Table 3 below:

Table 3 Strategic Alliances along small scale summer flowers value chain farmers

 As shown in Table 3 above, majority of the respondents strongly agreed that partnerships ensure just-in time delivery to direct markets (mean=4.60, SD=.841), and that they have a close customer contact (mean=4.55, SD=0.91). Further, the respondents agreed that they work with strategic business partners who carry out value-adding activities (mean=4.27, SD=1.174), strategic partners monitor product quality at some point of the value chain (mean=4.31, SD=1.192), and that the export partners adds value to production by sharing export market information (mean=4.08, SD=1.279). However, the respondents were undecided whether strategic partners monitor product quality along the entire value chain (mean-=3.46, SD=1.205).

Agribusiness Value Chain and Performance of Summer Flowers Small Scale Farmers

This section of the questionnaire sought to get rating from the respondents on effect of agribusiness value chain on performance of summer flowers small scale farmers. The respondents were asked to indicate the extent to which they agreed with various factors on effect of agribusiness value chain on performance of summer flowers small scale farmers using a five Likert scale of 5= strongly agree 4= agree 3= undecided 2= disagree 1= strongly disagree. The results are shown in table 4 below:

Table 4 Agribusiness Value Chain and Performance of Summer Flowers Small Scale Farmers

From the findings in table 4 above, respondents strongly agreed that partnerships ensures just-in time delivery to direct markets (mean=4.72, SD=1.103), they strive to ensure just-in time delivery to direct markets (mean=4.69, SD=1.119), and that through alliances they maintain the consistency of demand and supply (mean=4.57, SD=1.274). Further, they agreed that it has led to increase in the customer retention in the firm’s performance (mean=4.36, SD=1.255), efficiency in serving customers performance (mean=4.36, SD=1.173), increased customer satisfaction performance (mean=4.24, SD=0.926), and that they have managed to cope with market demands and develop new products and services quickly (mean=4.22, SD=1.20). In addition, the respondents agreed that they maintain the consistency of demand and supply (mean=4.10, SD=1.277), increase the profits performance (mean=4.19, SD=1.262), increased return on investment performance (mean=4.09, SD=0.941), increase the sales volume performance (mean=4.06, SD=1.255), and also the  process of operation is frequently reviewed (mean=3.49, SD=0.893).

Multiple Regression Results

In order to determine how dependent and independent variables relate, the study conducted a multiple regression analysis. The regression analysis results were presented using regression model summary and beta coefficient tables.

The linear regression model below;

            Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ +ε

Where Y is the organizational performance, β₀ is constant and ε is the error term of the model.

X₁        =          Farm Decision making

X₂             =         Coordination

X₃            =          Strategic alliances

Model Summary

Coefficient of determination explains the extent to which changes in the dependent variable (performance of summer flowers small scale farmers) can be explained by the change in the independent variables or the percentage of variation in the dependent variable that is explained by all the independent variables.

From Table 5, the value of R² is 0.600, which means that 60.0% of the total variance in independent variables has been explained.

Table 5 Model Summary

Regression Analysis

The results in Table 6 reports how well the regression equation fits the data (i.e., predicts the dependent variable).

Table 6 Analysis of Variance

A null hypothesis states that there is no linear relationship between the variables. The F-test can be used to reject the null hypothesis of fail to reject it. F (4, 84) = 25.084 and df = 84, the test is highly significant (p = 0.000 < 0.05). Therefore, the null hypothesis is rejected, and we conclude that there is a linear relationship between the variables in our model and that the regression model is a good fit of the data.

Beta Coefficients

Table 7 presents the results of the test of unstandardized beta coefficients which indicates the equation of the linear model.

Table 7 Beta Coefficients

Farm decision making, coordination, strategic alliances have p-value of 0.021, 0.003, and 0.041 respectively. These p-values are statistically significant at 5% significant level. Therefore, these three independent variables have a positive influence on organizational performance. This implies that of summer flowers small scale farmers should concentrate more on strategic alliances (p value of 0.007), farm decision making (p value of 0.022), and coordination (p value of 0.019).

As presented in Table 7, all the coefficients are found to be positive suggesting that an increase of a unit of farm decision making, coordination, strategic alliances lead to an increase in performance of summer flowers small scale farmers. The higher the coefficient values of beta, the more influential the independent variable. As evident from the study, strategic alliances have the most influence on performance of summer flowers small scale farmers and coordination has the least influence.

SUMMARY OF FINDINGS

This study sought to find out the factors performance of business along the summer flower value chain among small-scale summer flowers farmers in Kenya. The study was guided by three objectives namely, to determine the level of farmer decision making on agribusiness value addition in small and medium scale summer flowers in Kenya, to determine effect of coordination agribusiness value chain cost reduction strategy on performance of small and medium scale summer flowers in Kenya, and to find out how strategic alliances influence performance of small and medium scale summer flowers in Kenya. Primary and secondary sources of data were used in this study where primary sources of data were collected by use of closed ended questionnaire after a pilot test had been conducted. The collected data was analysed using SPSS to compute both descriptive and inferential statistics including frequencies, charts, regression and correlation. The results were thereafter presented in form of tables, graphs and charts.

The research received a good response rate, which contributed towards gathering of sufficient data that could be generalized to represent the opinions of respondents in the performance of small and medium scale summer flowers in Kenya. In addition, the validity coefficient index of 0.82 and Cronbach was obtained therefore implying that the questionnaires were valid. Demographic information established that the majority of the respondents indicated that they were male, had diploma as their highest level of education. From the findings, farm decision making, coordination, strategic alliances positively influence performance of summer flowers small scale farmers.

All the coefficients were found to be positive, suggesting that an increase of a unit of farm decision making, coordination, strategic alliances leads to an increase in performance of summer flowers small scale farmers. The higher the coefficient values of beta, the more influential the independent variable. As evident from the study, strategic alliances have the most influence on performance of summer flowers small scale farmers and coordination has the least influence.

Farmer Decision Making on Agribusiness Value Addition in Summer Flower

The findings on farmer decision making on agribusiness value addition in summer flower shows that respondents strongly agreed that they work with partner who are suppliers of raw materials, and that strategic partners monitor product quality at some point of the value chain. They agreed that they work with strategic business partners who conduct value-adding activities, they adopt innovation in their service delivery. Further, the respondents agreed that partners manage the cold-chain and maintains the integrity of the aesthetic value of the flower commodity, strategic partners monitor product quality along the entire value chain, alliance they have established contributes to export-readiness by packaging the cut flowers into bouquets, and that their export partners add value to production by sharing export market information. The respondents however were undecided on managing their our cold-chain and maintaining the integrity of the aesthetic value of the flower commodity, and on innovating new products frequently. Further, the respondents disagreed that they package the cut flowers into bouquets for export-readiness.

The findings agree with the findings of Fonsah et al., (2017) who did a study on factors influencing Banana Agricultural Value Chain in Bangladesh. The assessment concentrated on the significant banana delivering territory of Bangladesh. The study builds up that the serious issues are absence of good agricultural practices, which influences the overall quality, conveyance, and marketing of this significant fruit. Overview results over the total banana value chain show an eagerness to embrace innovation and WTP more significant expenses for any assortment of great bananas. A breeding company develops new varieties of flowers (typically) in their home country and further exports it to Kenya for trials at their local premises. There is a clear need to conduct more research into Kenya’s flora to identify and potentially locally develop new indigenous flower varieties for commercialization (Bolo, Muthoka, Washisino, Mwai, & Kisongwo, 2006).

Based on the findings of the study, small and medium scale summer flowers farmers should work with partner who are suppliers of raw materials, and strategic partners who monitor product quality in all points of the value chain. The farmers should also adopt innovation in their service delivery and partners should manage the cold-chain and maintains the integrity of the aesthetic value of the flower commodity.

Coordination Agribusiness Value Chain Cost Reduction Strategy

The findings on coordination agribusiness value chain cost reduction strategy indicate that the farmers have a close customer contact and that their business strategies are driven by goal of increasing customer value. Periodically review of product development is performed to plan a response to changes taking place in business environment. The summer flower farmers design business processes to produce a specific output for a particular customer or market, farmers have invested in large scale production. Summer flowers use low-cost energy in production process and does a lot of market research to introduce new products.

The findings of the study agreed with the Reddy (2013), who posited that the concept of agricultural value chain includes the full range of activities and participants involved in moving agricultural products from input suppliers to farmer’s fields and ultimately to consumers. The idea of the value chain is based on the process view of organizations which emphasizes on seeing a manufacturing (or service) organization as a system, made up of subsystems each with inputs, transformation processes and outputs(Miller, 2012). According to Porter (1999), inputs, transformation processes, and outputs involve the acquisition and consumption of resources; money, labor, materials, equipment, buildings, land, administration and management.

From the findings of the study farmers should have close customer contact and establish business strategies which are driven by goal of increasing customer value. They should also periodically review product development to plan a response to changes taking place in business environment. The summer flower farmers should design business processes to produce a specific output for a particular customer or market.

Strategic Alliances along small scale summer flowers value chain farmers

The findings on strategic alliances along small scale summer flowers value chain farmers reveal that partnerships ensure just-in time delivery to direct markets, farmers have a close customer contact and work with strategic business partners who carry out value-adding activities. The strategic partners monitor product quality at some point of the value chain and the export partners adds value to production by sharing export market information.

The findings agrees with the findings of Krone (2017), who posited that management should decide on what level of partnership between the supply chain actors is proper for the supply chain links. The authors point out that there are so many interactions between different companies taking place across the supply chain that it is important to distinguish between the primary and supporting members. They define primary members of the supply chain as all those autonomous companies or strategic business units who carry out value-adding activities (operational and/or managerial) in the business processes designed to produce a specific output for a particular customer or market, while supporting members are companies that simply provide resources, knowledge, utilities, or assets for the primary members of the supply chain (Krone, 2017).

From the findings of the study, partnerships are key because it ensure just-in time delivery to direct markets. Farmers should have a close customer contact and work with strategic business partners who carry out value-adding activities. The strategic partners should monitor product quality at all points of the value chain and the export partners should frequently share export market information to adds value to production.

Agribusiness Value Chain and Performance of Summer Flowers Small Scale Farmers

The findings on agribusiness value chain and performance of summer flowers small scale farmers indicated that partnerships ensure just-in time delivery to direct markets and strive to ensure just-in time delivery to direct markets. Through alliances the farmers maintain the consistency of demand and supply. Agribusiness value chain leads to increase in the customer retention in the firm’s performance, efficiency in serving customers performance and increased customer satisfaction performance.

The findings agree with the findings of Cooper and Lybrand (2014) directed an investigation on 213 organizations in Pakistan to look at the effect of value chain examination on the net revenue of firms. The findings showed a solid connection between value chain examination and net revenue of the company. Their decisions bore witness to the theory that examination of the value chain can for sure lead to the appropriation of new techniques that can build an organization’s gainfulness. The investigation similarly shows that 57% of the respondents concurred that the value chain examination is a helpful system in creating methodologies that limiting the operative price of a trade. This eases the firm the chance of cost authority position in the business along these lines bringing about predominant execution (Akenbor& Okoye, 2011).

From the findings of the study agribusiness value chain has positive effect on performance of summer flowers farmers. Partnerships ensure just-in time delivery to direct markets and strive to ensure just-in time delivery to direct markets. Through alliances the farmers maintain the consistency of demand and supply.

CONCLUSION

The study concluded that the summer flowers small scale farmers have implemented agribusiness value addition. The farmers have built partnerships and collaborations with other players in the industry.

The study also concluded that the summer flower farmers have adopted collaboration as a cost reduction strategy. The farmer’s business strategies are driven by goal of increasing customer value. The farmers review their product development to plan a response to changes taking place in business environment. The summer flower farmers design business processes to produce a specific output for a particular customer or market, farmers have invested in large scale production. Summer flowers use low-cost energy in production process and does a lot of market research to introduce new products.

Further, the study concluded that the farmers have implemented strategic alliances along small scale summer flowers value chain farmers reveal that partnerships ensure just-in time delivery to direct markets, farmers have a close customer contact and work with strategic business partners who carry out value-adding activities. The strategic partners monitor product quality at some point of the value chain and the export partners adds value to production by sharing export market information.

RECOMMENDATIONS

The study concluded that farm decision making, coordination, strategic alliances were significantly affecting the performance of small-scale summer flowers. The study therefore recommends that in order to improve performance of small-scale summer flowers, the farmers should consider establishing strategic alliances, collaboration and informed decision making process in order to improve their performance. The study recommends that policy makers in horticultural industry should use the findings to improve the industry.

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