Abstract
Purpose
The approach to integrate concepts from different disciplines so as to solve the problems facing smallholder farmers has gained momentum in recent years. However, very little is known about how word-of-mouth (WOM) dimensions can be used in agricultural marketing to explain market participation among smallholder farmers. Therefore, this study investigates the perceived usefulness of WOM in explaining smallholder farmers’ market participation.
Design/methodology/approach
The cross-sectional design was carried out to survey a sample of 467 smallholder farmers. This study used partial least squares structural equation modelling (PLS-SEM) in SmartPLS 4 to test hypotheses.
Findings
The results revealed that WOM dimensions such as expertise differential, strong tie and trustworthiness among smallholder farmers significantly influence the WOM message delivery. Likewise, the findings suggest that WOM message delivery significantly influences market participation among smallholder farmers. Finally, it was revealed that WOM message delivery significantly mediates the relationship between WOM dimensions and market participation.
Practical implications
This study provides useful insights to smallholder farmers on how to use WOM dimensions to enhance more market participation in formal markets, especially through proper WOM message delivery.
Originality/value
The current study solves the problem of information asymmetry among smallholder farmers through WOM. It is perhaps the first study to establish the link between WOM dimensions and market participation among smallholder farmers in the context of developing countries.
Keywords
Citation
Ismail, I.J., Amani, D., Changalima, I.A. and Kazungu, I. (2024), "I share because I care! Smallholder farmers’ perceptions of the usefulness of word of mouth for their market participation decisions", IIM Ranchi Journal of Management Studies, Vol. 3 No. 1, pp. 39-53. https://doi.org/10.1108/IRJMS-11-2022-0104
Publisher
:Emerald Publishing Limited
Copyright © 2023, Ismail Juma Ismail, David Amani, Ismail Abdi Changalima and Isaac Kazungu
License
Published in IIM Ranchi Journal of Management Studies. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
In developing countries, majority of subsistence consumers including individuals and families are living in substandard houses and are considered to have limited access to better education, health care, minimal incomes generation and other resources (Weidner, Rosa, & Viswanathan, 2010). Smallholder farmers are considered to be among individuals who are still living in subsistence life, and if efforts are not taken to solve their challenges, they will continue to live below the poverty line. To smallholder farmers, agricultural commercialization is essential in transitioning from subsistence farming to market-oriented production so as to improve production and food security (Megerssa, Negash, Bekele, & Nemera, 2020). However, despite its potential benefits, subsistence concentration and limited market integration continue to be significant barriers to growth in the agricultural sector. Market participation is an important proxy for agricultural commercialization and has been shown to improve farmers’ welfare by increasing production for food and nutrition security (Hlatshwayo et al., 2022).
Unfortunately, smallholder farmers in developing countries still have low market participation rates and depend primarily on informal marketplaces due to a lack of formal market connections and limited access to agricultural marketing information (Bannor, Oppong-Kyeremeh, Kyire, Aryee, & Amponsah, 2022; Changalima & Ismail, 2022; Kyaw, Ahn, & Lee, 2018). Although extension officers in rural areas could play a key role in providing updated market information, they do not always provide sufficient support to smallholder farmers (Hlatshwayo et al., 2022). As a result, middlemen are often viewed as important marketing agents by smallholder farmers because they have access to potential market information and have direct contacts with traders and buyers, and they are more familiar with market operations (Ismail, Srinivas, & Tundui, 2015; Mapiye, Makombe, Molotsi, Dzama, & Mapiye, 2023). However, this information asymmetry can result in middlemen benefiting more than smallholder farmers, leading to smallholder farmers continuing to sell their crops at farm gates or in informal markets where prices are relatively low (Otekunrin, Momoh, & Ayinde, 2019).
Regardless of the market participation challenges facing smallholder farmers, selling at market place is regarded as a key motive for the improvement of their living standards. According to the motivation theories such as the Maslow's theory, people are motivated by the hierarchy of needs. To smallholder farmers, the motivation to sell at market place instead of selling at farm gate may be influenced by the need to generate income so as to fulfill the basic needs such as shelter, healthcare and food (Sebatta, Mugisha, Katungi, Kashaaru, & Kyomugisha, 2014). This is supported by the expectancy theory which suggests that individuals are motivated by beliefs that the efforts they provide can results to expected desired outcomes. Applying this theory to smallholder farmers, the theory suggests that smallholder’s market participation can be influenced farmer’s expectations that, selling at the official markets can be more beneficial and can provide more rewards than selling at farm gate. This is because of a perceived profitability, access to information and resources and a perceived effort-reward balance presented at official markets.
Additionally, understanding the motivations behind consumer choice behavior can promote more sustainable practices within the agricultural industry, leading to a more sustainable food system (Lazaroiu, Andronie, Uţă, & Hurloiu, 2019). Effective communication strategies such as branding can help customers inform other members of their social groups about the benefits of sustainably sourced foods (Majerova et al., 2020). Furthermore, customer satisfaction plays a crucial role in promoting positive recommendations for sustainable agricultural practices (Michalikova, Blazek, & Rydell, 2022). Access to market information can help smallholder farmers to reduce marketing costs as well as improving returns (Mushi, Mwaiseje, & Changalima, 2021; Muto & Yamano, 2009). Word of mouth (WOM) is regarded as one among the best marketing communication frameworks (Amani, 2022), because of its reliability in transmitting message from active customers of products to the other customers (Delafrooz, Rahmati, & Abdi, 2019; Sheu & Chu, 2017). Thus, by using similar WOM strategies, smallholder farmers can solve several marketing communication problems by sharing experiences about how to handle challenges related to marketing and hence make informative decisions.
However, regardless of the potentials presented in WOM (Balamoorthy & Chandra, 2023; Fang, Li, Zhang, & Ye, 2023; Huang, 2022), its application to smallholder marketing framework is limited. Therefore, smallholder farmers can leverage the WOM dimensions to improve the way they perceived usefulness of WOM messages for market participation. Thus, to fill the gap from other settings, this study offers a new theoretical perspective on how smallholder farmers can benefit from participating in formal markets by decreasing their reliance on middlemen and increasing their reliance on perceived usefulness of WOM. Additionally, the study explores how different WOM dimensions influence the delivery of WOM messages and how the delivery influence market participation among farmers. Finally, the study introduces WOM message delivery as a mediator in the relationship between WOM dimensions and market participation among smallholder farmers, providing a theoretical and empirical framework for increasing market participation rates through WOM. The rest of the paper is structured as follows; theoretical review and hypothesis development, research method, results, discussion and conclusion, implications, study limitations and further studies.
Theoretical review
Maslow’s theory and expectancy theory
The theoretical premise of this study posits that smallholder farmers' decision-making processes when choosing between formal and informal markets for selling their produce is driven by several theoretical underpinnings. The first theoretical thinking is that market participation among smallholder farmers is the outcome of their motivations to earn more income so as they can manage healthcare, food and shelter. This is supported by the Maslow's theory which suggests that people are motivated by the hierarchy of needs (Maslow & Lewis, 1987). This motivation theory focuses on the various levels of human needs and motivation. It is frequently depicted as a five-tiered pyramid, with each tier representing a different category of needs that individuals seek to fulfill in a hierarchical order. Recent research has demonstrated that the theory is useful in explaining aspects of decision-making in various settings (Mensah, Chen, Ntim, & Gabrah, 2023). We used this theory in our study because, in the context of smallholder farmers, the motivation to sell at the marketplace could stem from the need to generate income to meet basic needs such as healthcare and food, which aligns with Maslow's hierarchy of needs.
Similarly, market participation among smallholder farmers is the complex process which involves several expectations. According to the expectancy theory, individuals are always motivated to participate in any undertaking if they oversee the desired outcomes at the end of activities. This theory was proposed in 1960s by Victor Vroom and posits that people are motivated by beliefs that efforts may result into the desired outcomes (Vroom, 1964). Therefore, smallholder farmers' decisions to participate in the market may be affected by their expectations of greater rewards and benefits from selling at official markets rather than at the farm gate. For smallholder farmers to participate in markets, there must be expected rewards such as more profits and other benefits compares to selling at farm gate. The two theories have been used in our study as they are the motivational theories that may influence the decisions of smallholder farmers toward market participation. Thus, the study emphasizes the importance of utilizing these theories and leveraging WOM as an alternative source of information to help smallholder farmers make informed market participation.
Development of hypotheses
The study involved three main WOM dimensions; expertise differential, homophily, as well as the trustworthiness between the sender and receiver. Since, this study is among new initiatives in relating marketing concepts in agricultural practices, the study developed literature and hypothesis from other disciplines. The point of departure is that, proper development of WOM dimensions (independent variables) is perceived to have significant influence on the development WOM message delivery (mediating variable) and further influence the market participation of smallholder farmers (dependent variable).
Smallholder farmer’s expertise differential
The level of expertise of the sender of information is crucial in determining its effectiveness in bridging information gaps between smallholder farmers and middlemen. As noted by (Sweeney, Soutar, & Mazzarol, 2014), experts are likely to have more comprehensive and sufficient knowledge than non-experts, and this may influence how the receiver evaluates the relevance of the information conveyed in the message. In the context of smallholder farmers, seeking information from fellow smallholder farmers with more marketing experience can be an effective way to reduce exploitation from middlemen. This is because smallholder farmers who have prior experience with agricultural market operations are more likely to have more accurate and reliable information that can help inform market participation. Therefore, by leveraging WOM from experienced smallholder farmers, smallholder farmers can reduce information asymmetry and make more informed decisions.
Furthermore, the use of WOM to manage negative information has been noted in several studies, including the study by Ismail (2022) which highlighted the resistance of customers to negative information about local products. The study by Amani (2022) also showed that university students can use WOM to make risk decisions such as joining universities. Similarly, smallholder farmers can use WOM from their peers to reduce information gaps and make better market participation. Therefore, it is crucial to emphasize the importance of seeking information from reliable sources, such as experienced smallholder farmers, to reduce exploitation by middlemen and improve the effectiveness of WOM in agricultural marketing. It can be hypothesized that
Expertise differential among smallholder farmer’s influences WOM Message Delivery
Strong ties between smallholder farmers
The similarities, homophily and intimacy between senders and the receivers of the WOM may increase effectiveness of WOM message delivery (Amani, 2022). Theoretically, the communication between people works effective if they share some similarities (Kelman, 1961; Sweeney et al., 2014). According to Le, Dobele, and Robinson (2018), a strong tie between two parties is positively related with several outcomes such as a message quality. To smallholder farmers, the only means they can avoid exploitation from the middlemen is through developing a close and strong tie between themselves which can help them to share proper information about the availability of buyers and price in formal markets. Due to perceived similarity among smallholder farmers, those with enough prior experiences can help to share market information and increase the WOM message delivery. Therefore, one can hypothesize that.
Strong ties among smallholder farmer’s influences WOM message delivery
WOM trustworthiness between smallholder farmers
Trustworthiness has been document to be a degree to which receivers put confidence to the sender of the information (Ohanian, 1990). Trust is a paradigm in communication that has received much attention in several studies as it provides one among the best attributes in WOM message delivery (Amani, 2022; Ismail, 2022). A study by Ismail (2022) has noted that people always rely on information from friends whom they trust than information from people they don’t trust. In this way, if there are two choices, smallholder farmers will tend to believe more on WOM message from their fellow smallholder farmers than WOM messages from other sources such as middlemen. A study by Amani (2022) and Sweeney et al. (2014) documented that existing homophily is developed through a shared practices which creates a special atmosphere that can increase trust that can result into reliability of the WOM message delivery. Hence, it can be hypothesized that
Trustworthiness among smallholder farmer’s influences WOM Message Delivery
The role of WOM message delivery
Under a normal circumstance, the effectiveness of the message depends on the several factors of which the way of delivering it is considered to be a crucial factor. Particularly, past studies have noted that for the effective marketing communication to take part, there must be a sender, a receiver, message itself as well as proper message delivery (Amani, 2022; Ismail, 2022). Although there is WOM studies done in agriculture especially in market participation among smallholder farmers, experience from other disciplines suggests that message delivery is a subject of interest in the literature. This is because, the way messages are delivered provides a great affect to the receivers. Past studies have shown that if message is not delivered in a proper, easily, concise and clear way, it can result into negative outcomes, but if message is delivered in proper ways, it can efficiently be shared and hence increase engagement in any undertaking. Apart from that message delivery can be a potential mediator in the link between WOM dimensions and other market practices such as market participation. If the message delivery is accessible and clear, it can help to bridge the information gap through providing effectively and relevant information and knowledge to smallholder farmers for market participation. This allows less-experienced farmers to gain access to expertise-based insights, market trends and best practices that can enhance their understanding of market dynamics and improve their decision-making abilities.
Normally, message quality depends on how the message is delivered and how the information provided by the sender is perceived by the receivers (Sweeney, Soutar, & Mazzarol, 2008). Thus, a message with high quality delivery to smallholder farmers can play a critical role in increasing the impact of the message for market participation. Since homophily, expertise differential and trustworthiness influence WOM message delivery (Ismail & Changalima, 2022) and since WOM message delivery has several perceived usefulness (Amani, 2022), marketing participation decisions among smallholder farmers can be potentially and directly influenced by WOM message delivery as well as WOM message delivery can mediate the relationship between WOM dimensions and market participation. This study hypothesized that
WOM message delivery influences market participation among smallholder farmers.
WOM message delivery mediates the relationship between expertise differential and market participation among smallholder farmers.
WOM message delivery mediates the relationship between strong ties and market participation among smallholder farmers.
WOM Message delivery mediates the relationship between trustworthiness and market participation among smallholder farmers.
Conceptual framework
Figure 1 shows the variables and the relationships which have been developed from the literature review.
Research method
Research design and target population
This was a cross-sectional study. It was conducted in Dodoma region which is located in central part of Tanzania. Specifically, four villages; Mlembule, Njoge, Mwenzele and Makutupa were purposively selected based on the agricultural production level and the distance to the market places. In this study, the target population consisted of only smallholder farmers, with the head of households being used as the unit of inquiry. To ensure that only smallholder farmers were included in the study, households with farm sizes between 0.5 and 3.5 ha were selected as the inclusion criterion, as farms larger than 3.5 ha are not considered small holdings (Ismail, 2022).
Sampling procedures and data collection
In this study, village officials assisted in identifying smallholder farmer households in four villages. 603 households were involved due to the fact that this sample size met the requirements of a minimum sample size given the population size, confidence interval and margin of error. Thus, 603 smallholder farmers were randomly selected due to the fact that the finite sampling frame was available which included the list of households from the surveyed villages. A total of 603 questionnaires were initially distributed to smallholder farmer households and 467 (77.44% response rate) were collected by the end of the data collection period. While the final sample size may be considered small given the total population of smallholder farmers in Tanzania, partial least squares structural equation modelling (PLS-SEM) can still be effectively utilized (Hair, Risher, Sarstedt, & Ringle, 2019). According to the recommendation of G*Power program, a minimum sample size of 77 is required for a statistical power of 0.8, an effect size (f2) of 0.15, p = 0.05 and three predictors as parameters. As the total number of collected responses meets this recommendation, it is considered sufficient for the study. In this study, the sample size was 467 smallholder households.
Data analysis technique
This study used Smart PLS 4. This is a statistical tool used to examine data by applying a partial least square equation modeling (PLS-SEM). PLS -SEM has several advantages as suggested by (Farrukh, Meng, Sajid, & Shahzad, 2020; Hair, Sarstedt, & Ringle, 2019; Raza, Rather, Iqbal, & Bhutta, 2020). These advantages include its superiority in assessing mediation analysis and its ability to handle complex model (constructs and items) (Khan, 2023). It is also related with its suitability in predicting a group of complex equations simultaneously in the proposed models. Additionally, PLS-SEM is designed to have a high degree of predictive power and handle non-normal data (Arachchi & Samarasinghe, 2023). This is important for producing accurate representation of a sample to the population. Also, PLS-SEM can manage smaller sample sizes compared to covariance-based (CB)-SEM (Sumi & Ahmed, 2022). Finally, it is a statistical analytical tool which is considered to be the modern approach which can precisely measure the direct as well as indirect effects of latent constructs (Hair et al., 2019).
Measurement of variables
The design of the questionnaire used in this study depended on the items adopted from the previous studies. However, these items were modified to fit with smallholding agricultural practices in Tanzanian context. The measurement items for expertise (exp), strong tie (strg), trustworthiness (trust) and message delivery (womd) were adopted and modified from Ismail and Changalima (2022). Additionally, the measurement items for market participation (mrkp) were adopted and modified from Ismail (2022). Finally, all measurement items were captured using a format of a five-point Likert scale.
Results
Demographics of respondents
The results on demographics of respondents are presented in Table 1. These results show that the majority of smallholder farmers are males, comprising 302 individuals (64.7%), with ages falling between 29 to 39 (33%) and 40 to 50 (31.9%). Additionally, 344 farmers (73.7%) possess a secondary educational level. Regarding transportation facilities, a significant proportion of them, 411 farmers (88%), own a bicycle. Furthermore, 389 farmers (83.3%) are members of farm organizations. These findings imply that males constitute the majority of households included in the study and that they are of working age and have adequate education. Prior research in similar settings (Changalima & Ismail, 2022; Mahuwi & Israel, 2023) support the gender and age statistics but inconsistencies with the findings on the educational levels. It should be noted that smallholders’ age has crucial role in enhancing participation (Mchopa, Jeckoniah, Israel, & Changalima, 2020).
Measurement model
The measurement model was used to test the measurement qualities through construct reliability, discriminant validity and convergent validity as suggested by Hair et al. (2019). Table 2 shows that the values of composite reliability and Cronbach’s alpha for all constructs are greater than 0.7. This indicates that the reliability was achieved as values are above 0.7 (Tavakol & Dennick, 2011). Apart from that, the results of the measurement model show that, the average variance extracted (AVE) and show that, the factor loadings all items are greater than 0.5 and 0.7 respectively. This further indicates that, the convergent validity was attained. Correspondingly, the values of variance inflation factor (VIF) were less than 0.5, this means, there is no multicollinearity concerns in the data (Hair et al., 2019). On the other hand, the results in Table 3 show that the discriminant validity was achieved because the values for heterotrait-monotrait (HTMT) ratio were less than 0.85 (Henseler, Ringle, & Sarstedt, 2015). HTMT was selected because it measures the average correlations among the indicators across different constructs (Hair et al., 2019).
Structural model
The results indicate that R2 for mrkp is 0.404 and R2 for womd is 0.198. This suggests that the proportion of variance in mrkp is explained by 40.4% of womd and the proportion of variance in womd is explained by 19.8 % of WOM dimensions. Apart from that, this study involved seven hypotheses. Based on the results of the structural model in Table 4 and Figure 2, all seven hypotheses were tested to be significant. The results indicate that the first hypothesis (H1) was supported because of the significant influence of expertise differential on WOM message delivery (β = 0.112, p = 0.007). This suggests that, increasing expertise differential among smallholder farmers by 1 unit increases WOM message delivery by a factor of 0.112 (11.2%). Also, the second hypothesis (H2) was supported suggesting that strong ties between smallholder farmers significantly influences WOM message delivery (β = 0.171, p = 0.001). This also indicates that there is an assurance of increasing market participation by a factor of 0.171 (17.1%%) if strong ties between smallholder farmers is increased by 1 unit. Apart from that, the model results suggest that (H3) was supported. This is because trustworthiness was determined to significantly influence WOM message delivery (β = 0.345, p < 0.001). These results show that WOM message delivery can be increased by a factor of 0.345 (34.5%) if trustworthiness among smallholder farmers is increased by 1 unit.
Moreover, the study results suggest that WOM message delivery significantly influences market participation (β = 0.458, p < 0.001), hence (H4) was supported. This suggests that market participation can be increased by a factor of 0.458 (45.8%) if WOM message delivery is increased by 1 unit. Additionally, this study involved mediating effects. The results suggested that WOM message delivery significantly mediates the relationship between expertise differential and smallholder farmers' participation in the market (β = 0.051, p = 0.010), hence the H5 was supported. Similarly, the results explain that WOM message delivery mediates the relationship between strong ties and smallholder farmers' market participation (β = 0.078, p = 0.002), thus H6 was also supported. Furthermore, the results indicate that WOM message delivery mediates the relationship between trustworthiness and smallholder farmers' market participation (β = 0.158, p = 0.000). Therefore, H7 was supported.
Discussion and conclusion
This study examined the relationship between word-of-mouth (WOM) dimensions and market participation of smallholder farmers, with a focus on how WOM message delivery acts as a mediator. Generally, the findings are in line with motivation theories which suggest that for individuals to be engaged in any undertaken, they must be motivated by different factors. Learning from from motivation theories, smallholder farmers as key actors in existence of markets can be motivated to participate in market by the hierarchy of needs as well the expectations they have after participation. Therefore, they can utilize WOM dimensions so as to increase their chances to patriciate in the market so as to achieve their desired goals. Precisely, the findings showed that WOM dimensions significantly influence the delivery of WOM messages, which in turn has a significant influence on market participation among smallholder farmers. The study highlights the importance of leveraging WOM in agricultural marketing initiatives and prioritizing the development of relationships with experienced and knowledgeable smallholder farmers to facilitate effective delivery of WOM messages. These findings are in line with other previous studies on WOM (Amani, 2022; Ismail, 2022; Ismail & Changalima, 2022; Jain, Dixit, & Shukla, 2023) which suggested that WOM can be a crucial factor for reducing risks associated in marketing decisions. By prioritizing WOM dimensions, marketers and policymakers can ensure that WOM messages contribute positively to market participation behavior and promote greater inclusivity in agricultural markets. This also concurs with (Baker, Donthu, & Kumar, 2016) who noted that WOM effectiveness depends on the relationship developed between the sender and the receiver of the WOM message.
The study found that expertise and strong ties between smallholder farmers are important factors in delivering WOM messages effectively. Farmers with more knowledge and experience in market operations are better able to improve the means of delivering the message to inexperienced farmers. This findings match with (Abass et al., 2014; Amani, 2022) who suggested that, a sender of the message who is knowledgeable can be in a good position to properly deliver the WOM message to the receivers.
Similarly, farmers with strong emotional relationships, common interests and similar likes and dislikes are more likely to deliver the message in a positive way. These findings are consistent with previous research (Cooley & Parks-Yancy, 2019; Ismail, 2022) which suggested that individuals can more likely trust friends they know, especially during making purchase decisions suggesting that individuals with prior knowledge and subjective experiences can better comprehend the topic before exposing the information to others.
The findings also revealed that trustworthiness is important among smallholder farmers because it allows them to be more open to each other. Thus, if communication between them is built in a trustworthy manner, they can be more likely to find a proper way of delivering WOM message in appropriate way to benefit the relationship. These findings are supported by (Langlinais, Howard, & Houghton, 2022) who observed that effective communication can contribute to the development of trustworthiness among individuals. This highlights the importance of clear and effective communication, including WOM, in agricultural marketing initiatives, particularly in building trust among smallholder farmers and promoting their participation in formal markets. In most cases, trustworthiness among smallholder farmers is built on honest, reliability and sincere. Apart from that, increased market participation among smallholder farmers depends on how appropriate WOM message delivery was perceived to be usefulness. In this way, the approaches used to deliver the WOM messages can result to effectiveness of WOM to the smallholder farmers who receive the message from experienced smallholder farmers. The plausible explanation is that, recipient of the WOM message perceive the message to be effective if there is a strong tie as well as trust between smallholder farmers. In most cases, smallholder farmers tend to believe that the WOM message delivered to them is useful if they perceive the WOM message is capable of providing correct market information. Thus, from the smallholder farmer’s perspective, the WOM message is considered to be useful if it can induce persuasion for them to sell at market places instead of selling at farmgates.
The study found that all three dimensions of WOM have a significant impact on message delivery, which in turn affects market participation among smallholder farmers. Furthermore, the study revealed that WOM message delivery plays a critical mediating role in the relationship between WOM dimensions and market participation. The results suggest that the perceived usefulness of WOM messages is influenced by the way in which the dimensions of WOM are integrated and communicated to smallholder farmers. Therefore, enhancing WOM message delivery could potentially explain the linkage of expertise, strong ties and trustworthiness among smallholder farmers on market participation. This could, in turn, encourage less-experienced smallholder farmers to rely more on WOM information from experienced peers. The mediating role of WOM message delivery was also noted by Amani (2022), Ismail and Changalima (2022).
Theoretical implications
This study makes several significant contributions to the current literature by focusing on the influence of WOM dimensions on market participation among smallholder farmers in Tanzania, with the mediation of WOM message quality. Firstly, this study addresses the need to understand how WOM can be used to solve problems of information asymmetry in market participation among smallholder farmers. Secondly, the study provides a theoretical understanding of how WOM message delivery can mediate the relationship between WOM dimensions and market participation, highlighting the power of information from relatives and friends as a solution to misleading information from middlemen. Thirdly, this study fills a gap in the literature as previous studies on WOM have been mostly limited to other disciplines such as public procurement management (Ismail & Changalima, 2022), customer and marketing management (Ismail, 2022) and educational management (Amani, 2022), with little attention paid to smallholder farming and market participation. Lastly, this study contributes to the Maslow’ theory by postulating that smallholder farmers’ motivation to sell at marketplaces could stem from the need to generate income to fulfill their basic needs (shelter, healthcare, food), which aligns with the foundational level of Maslow's hierarchy. The study’s findings also support the expectancy theory which centers on that fact that that people are motivated by the belief that their efforts will lead to desired outcomes. Therefore, smallholder farmers’ decisions to participate in the market is influenced by their expectations of better rewards and benefits associated with selling at official markets as opposed to the farm gate.
Managerial implications
There are several important managerial insights that smallholder farmers should consider when planning to participate in formal markets. These insights are inextricably linked to the use of WOM information from other smallholder farmers, which is essential for ensuring proper and effective market participation. Smallholder farmers should engage more with farming groups and network linkages to increase information bases through interactions with experienced farmers who can provide reliable WOM in order to increase market participation. Furthermore, by understanding the benefits of WOM, smallholder farmers can avoid being exploited by middlemen and farm gate buyers. To ensure that WOM messages are effectively delivered and have a positive impact, smallholder farmers must improve their expertise, homophily and trustworthiness among themselves. This entails cultivating trusting relationships with friends and family, as recipients of the WOM message are more likely to believe information from these people. Smallholder farmers can better navigate the complexities of formal markets and improve their economic outcomes by taking these steps.
Study limitations and further studies
The study has some limitations, and future research can expand on it. Future studies can consider WOM message delivery as a moderator instead of a mediator in the relationship between WOM dimensions and market participation. Apart from that, this study used traditional WOM dimensions, future studies can look into electronic word of mouth (eWOM). This is because, the advancement of technology has affected how communication is done among smallholder farmers. Given that the current study was conducted in Tanzania, future researchers could improve it by broadening its geographical scope and involving smallholders from other countries. Also, involving smallholders from various regions within the country can provide more in-depth insights. Furthermore, future research may benefit from incorporating multigroup analysis, which would allow for a relevant examination of various countries or regions. Multigroup analysis can be conducted based on factors such as gender, the type of cultivated crops, or membership in farm organizations. Lastly, future studies may consider including other potential mediators and/or moderators to further enrich the current conceptual model. Exploring these additional variables can aid in capturing the complexities of the relationship when explaining market participation via WOM in the context of smallholder farmers.
Figures
Figure 1
The conceptual framework
Figure 2
The structural model – PLS algorithm
Demographics of respondents
| Characteristics | Category | Frequency | % |
|---|---|---|---|
| Gender | Female | 165 | 35.3 |
| Male | 302 | 64.7 | |
| Age | 18–28 | 54 | 11.6 |
| 29–39 | 154 | 33 | |
| 40–50 | 149 | 31.9 | |
| 51–61 | 58 | 12.4 | |
| 62+ | 52 | 11.1 | |
| Educational level | Primary | 75 | 16.1 |
| Secondary | 344 | 73.7 | |
| Diploma | 38 | 8.1 | |
| Degree | 10 | 2.1 | |
| Transportation facilities | Bicycle | 411 | 88 |
| Cart | 11 | 2.4 | |
| Automobile | 45 | 9.6 | |
| Membership in farm organization | Yes | 389 | 83.3 |
| No | 78 | 16.7 | |
| Total | 467 | 100 | |
Source(s): Table by authors
Construct and composite reliability
| Construct/item | VIF | Outer loadings | Cronbach’s alpha | Composite reliability | AVE |
|---|---|---|---|---|---|
| Expertise differential | 0.866 | 0.912 | 0.785 | ||
| exp1 | 2.120 | 0.895 | |||
| exp2 | 2.921 | 0.929 | |||
| exp3 | 2.202 | 0.831 | |||
| Strong ties | 0.840 | 0.841 | 0.676 | ||
| strg1 | 1.681 | 0.791 | |||
| strg2 | 1.904 | 0.813 | |||
| strg3 | 2.331 | 0.867 | |||
| strg4 | 1.839 | 0.815 | |||
| Trustworthiness | 0.844 | 0.853 | 0.680 | ||
| trust1 | 1.883 | 0.839 | |||
| trust2 | 1.789 | 0.786 | |||
| trust3 | 2.074 | 0.848 | |||
| trust4 | 1.941 | 0.824 | |||
| WOM message delivery | 0.894 | 0.895 | 0.760 | ||
| womd1 | 2.398 | 0.851 | |||
| womd2 | 2.789 | 0.869 | |||
| womd3 | 3.479 | 0.906 | |||
| womd4 | 2.681 | 0.860 | |||
| Market participation | 0.927 | 0.929 | 0.820 | ||
| mrkp1 | 2.651 | 0.884 | |||
| mrkp2 | 3.260 | 0.905 | |||
| mrkp3 | 4.841 | 0.935 | |||
| mrkp4 | 3.678 | 0.897 |
Source(s): Table by authors
Discriminant validity
| HTMT | |||||
|---|---|---|---|---|---|
| Construct | exp | mrkp | strg | trust | womd |
| exp | |||||
| mrkp | 0.183 | ||||
| strg | 0.058 | 0.334 | |||
| trust | 0.068 | 0.471 | 0.337 | ||
| womd | 0.136 | 0.636 | 0.312 | 0.454 | |
Source(s): Table by authors
Direct and indirect effects
| Direct effects | |||
|---|---|---|---|
| Relationship | Original sample (β) | T Statistics | p values |
| exp → mrkp | 0.097 | 2.756 | 0.006 |
| strg → mrkp | 0.110 | 2.839 | 0.005 |
| trust → mrkp | 0.207 | 4.222 | 0.000 |
| H1: exp → womd | 0.112 | 2.676 | 0.007 |
| H2: strg → womd | 0.171 | 3.467 | 0.001 |
| H3: trust → womd | 0.345 | 7.197 | 0.000 |
| H4: womd → mrkp | 0.458 | 9.549 | 0.000 |
| Mediating effects | |||||
|---|---|---|---|---|---|
| Relationship | Original sample (β) | T Statistics | p values | Lower limit CI | Upper limit CI |
| H5: exp → womd → mrkp | 0.051 | 2.574 | 0.010 | 0.015 | 0.092 |
| H6: strg → womd → mrkp | 0.078 | 3.153 | 0.002 | 0.031 | 0.128 |
| H7: trust → womd → mrkp | 0.158 | 6.272 | 0.000 | 0.111 | 0.211 |
Source: Table by authors
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