The interview revealed that most of the respondents relied only on memory (89 percent, see also Table I.2 and I.4 in Appendix I). The most commonly memorized information relates to yield, income, prices, costs and profit. Only 11 respondents in Sugihwaras (11.9 percent) and three respondents in Rejosari (4.2 percent) have ever kept production information in a farm record book. Not all, however, have
Although a memory-based recording system is common in developing countries (see IDS Workshop, 1989b), many (e.g. Biggs & Clay, 1980; Swift, 1979 cited in IDS Workshop, 1989b) argue that the system is unreliable and results in variations in decision making. Nevertheless, Ohlmer et al. (1998, p. 286) stated that farmers may not always rely on their memory for making decisions, because “farmers continually update their problem perceptions, ideas of options, plans and expectations when new
information is obtained”. Thus, farmers may have their own methods for keeping up
with the changes in their internal and external settings. This may come in the form of farmers’ information seeking and processing practices.
According to Errington (1986), farmers may access information from internal or external sources (e.g. family members or neighbouring farmers), verbal or written sources (e.g. discussion with extension officers or newspapers), or through direct observation. The information may come in the form of numbers, suggestions/
opinions, and experience. The importance of each source is mainly dependent on the decision to be made, the decision making phase, the characteristics of the farm/farm family/farmer, and decision making contexts (various studies summarized by Solano, Leon, Perez, & Herrero, 2001b; 2003).
In this study, the sources of information used by the respondents were traced using a list of possible information sources for the respondents to determine the intensity of usage, from 0 (never) to 4 (always). The list includes information sources related to farming techniques, loans, new technologies (new inputs and machinery), and product marketing (particularly market prices).
The results show that most respondents from Sugihwaras (78 percent) and Rejosari (80.3 percent) learned farming techniques from their family (see Table I.2 and I.4 in Appendix I). This may indicate knowledge has been passed through the generations. These respondents also appeared to exchange knowledge with their colleagues more often than with field extension workers (FEWs). Neighbouring farmers were also an important source of information about new inputs and machinery (in both villages). This was particularly evident for respondents from Rejosari (73.2 percent). This
shows the importance of farmer-to-farmer technology transfer. In contrast, family members, village leaders, farmer group meetings, input retailers, and extension officers had a minor role in providing information about new inputs.
Similar findings have also been found in other studies. For example, Solano et al. (2003) found that Costa Rican dairy farmers generally obtained information for decision making from their family. Asfaw and Admassie (2004) also showed the importance of information sharing among a farm household’s members in the case of chemical fertilizer adoption among smallholder farmers in Ethiopia. Some studies in developed countries (e.g. Blum, 1989; Ford & Babb, 1989; Henderson & Gomes, 1982; and Sutherland et al., 1996; all cited in Solano et al., 2003) also confirmed the importance of family as the source of information for seasonal planning as well as decision making related to financing and innovation. The studies by Ford and Babb, and Sutherland et al., also observed a central role of farmer colleagues as information sources for decision making. Other studies in developing countries also confirmed the influence of neighbours and village colleagues in farmers’ decisions related to new technologies (e.g. Case, 1992; Munshi, 2004; Pomp & Burger, 1995; Zhang, Fan, & Cai, 2002). Learning from neighbours, or other farmers, in the village may be the only source of innovation for semi-subsistence farmers in developing countries who usually have limited resources, skills and access to information. This is relevant for the respondents in Sugihwaras and Rejosari who, to some extent, still have semi- subsistence characteristics.
Solano et al. (2003) also indicated the importance of extension services as the source of information for the Costa Rican dairy farmers. This was relevant especially for farmers who sought information about new techniques, and/or who became more business-oriented with an income-maximizing goal (Solano et al., 2006). However, the relative access to extension services seems to determine whether the extension services are an important information source for farmers. For example, Sulaiman (2002) found a significant role of field extension workers (FEWs), government agencies (Assessment Institute for Agricultural Technology, AIAT) and farmer group leaders as innovation sources for small-scale farmers in tidal swamp agro-ecosystem
zones in South Sumatra Province of Indonesia. In contrast, the roles of the FEWs, researchers and farmer groups as a source of innovations for the respondents in this study appeared to be limited (12-37 percent).
The availability of extension services in Sugihwaras and Rejosari has been significantly decreasing for the last five years. Currently there are only two field extension workers (FEWs) available in the Deket District, and they have to assist farmers in 17 villages, including Sugihwaras and Rejosari. Both FEWs are
specialized in food crops; no FEWs are available for dealing with aquaculture. This explains the infrequent interaction between the respondents and the FEWs. Among the respondents, the ones from Rejosari seemed to interact with extension officers more frequently compared to the respondents from Sugihwaras (see Table I.2 and I.4 in Appendix I). Nevertheless, most of the respondents seemed to be familiar with the extension activities, including field training and demonstration plots, individual meetings, and group meetings. The latter were facilitated by the farmer groups in each village.
In the absence of extension services, farmer groups usually take a leading role. However, the Sugihwaras respondents’ farmer group (there are two farmer groups in Sugihwaras) seemed to be inactive as indicated by a high percentage of non-
participation rates (57.6 percent). Similar conditions occurred in Rejosari, but the farmers in this village still meet annually, at the beginning of each planting season, to decide water allocation as well as the amount of seed and fertilizer collectively purchased. This has brought many benefits for the farmers in Rejosari especially in terms of farm planning, problem solving, as well as in obtaining new information, knowledge and skills (see Table I.4 in Appendix I). The respondents from
Sugihwaras who participate in the farmer group also obtain similar benefits (see Table I.2 in Appendix I). Frequent absence from the village, mostly for off-farm jobs, is the main reason why respondents do not participate in a farmer group.
For farm credit, the respondents in both villages seemed to have limited access to credit information. Very few of them obtained information from banks and
cooperative offices (see Table I.2 and I.4 in Appendix I). This may suggest the respondents faced barriers in accessing credit, or the existing financial institutions in both villages were operating less than optimally. Many respondents had obtained credit from a cooperative, but the scheme was abolished in 2000 due to
mismanagement. The respondents from Sugihwaras seemed to use more diverse sources of credit information than the Rejosari respondents did.
The respondents’ reliance on intermediaries for marketing their products also indicates that intermediaries were the most important source of market information (77 percent of respondents in both villages). Many respondents in Rejosari also obtained information about the price of rice from a local warehouse. Only around 16 percent of Sugihwaras respondents, and 42 percent of Rejosari respondents, also obtained price information from local markets.
Overall, despite the heterogeneity of information sources used, the preferences seem to be dependent on the decision environment. In this study, the preferences of information sources also determined the respondents’ information processing practices. This relates to the level of interaction between the respondents and their significant others, and the respondents’ perceptions about the quantity and quality of information obtained from their significant others. The respondents’ information processing practices, particularly related to technology adoption, are presented next.
6.2.3.2 Information processing practices
When the respondents were asked about their reactions to information about a new technology, many of them stated “directly applied the technology” (37.3 and 35.2 percent of the respondents from Sugihwaras and Rejosari, respectively). At the same time, many of them also seek further information by asking their significant others, and/or observing other farmers who have applied the technology (Table I.2 and I.4 in Appendix I). These respondents will make decisions after they have sufficient information and/or feel more confident from observing their colleagues’ results.
Among the respondents’ significant others, their spouse appears to be the most frequent person involved in assessing new information for decision making (around 69 and 89 percent of the respondents from Sugihwaras and Rejosari, respectively). The roles of children, parents and extended family in the respondents’ decision making process, however, are more limited than the respondents’ spouse (Table I.2 and J.4 in Appendix I). This may indicate that the respondents view their spouse as the most trusted and closest person with whom they can share farm decision making.
Outside family, the respondents discuss new information and collaborate in decision making with neighbours and, to some extent, the head of the farmer group (see Table I.2 and I.4 in Appendix I). This confirms the previous findings that neighbours are the main source of information about new inputs and machinery. The roles of extension officers and village leaders are considered less important, which is consistent with previous findings.
When the respondents were asked about their main consideration when appraising a new technology, most of them answered “observable results” (64.9 and 84.3 percent of the respondents from Sugihwaras and Rejosari, respectively). They also indicated the importance of their “significant others’ opinion” (43.9 and 54.3 percent of the respondents from Sugihwaras and Rejosari, respectively). Other considerations include costs, profit, prices, specific features of the technology, and agro-climatic conditions (see Table I.2 and I.4 in Appendix I).
Overall, these findings show that the respondents perceive their significant others not only as the source of information, but also as role models who can give support when making decisions. This is also confirmed by the reasons behind the respondents’ preferences for their significant others. “Easy to meet” and “prompt responses” are among the most cited reasons by the respondents (47.3 and 59.7 percent of the respondents from Sugihwaras and Rejosari, respectively). The knowledge and experience of the respondents’ significant others are also important, especially when the respondents need to deal with farm planning and problem solving (see Table I.2 and I.4 in Appendix I). Nevertheless, only a few respondents perceived that the
discussion with their significant others would result in a more reliable decision about new technologies (5.1 and 5.7 percent of the respondents from Sugihwaras and Rejosari, respectively). This raises a question about the final decision maker.
The respondents appeared to have two choices regarding making the final decision of whether to adopt/delay/reject the technology. First, some involved others in making decisions as 54 percent and 89.7 percent of the respondents from Sugihwaras and Rejosari, respectively, preferred to have discussions and debate to find a mutually acceptable solution when they faced differences with their significant others (see Table I.2 and I.4 in Appendix I). Only a few acted passively when faced with a different opinion. Secondly, many respondents also preferred to be the sole decision maker, although they may listen to their significant others’ suggestions. Around 40.7 percent of respondents from Sugihwaras were not willing to share decision making with others, while some considered a consensus (23.7 percent). Similar patterns were also found in Rejosari (49.3 percent were not willing to share decision making). The most common people with whom the respondents shared their decisions were
colleagues (12 percent in Sugihwaras) and family members (20 percent in Rejosari).
Similar practices were also identified from studies in other countries. These studies (see Solano et al., 2001b, p. 182) found that individualistic decision making appears to be the most common phenomena in farming decision-making, regardless of gender and culture. For example, Solano et al. (2001b) found that dairy farmers in Costa Rica were in favour of making decisions by themselves, although their decisions appeared to be strongly influenced by others’ opinion, particularly from family members.
However, the influence of the farmer’s spouse and non-family significant others is determined by the nature of decisions to be made (Errington, 1986). This is evident in the case of financial/risky planning and decisions with certain requirements for information, and is influenced by decision period (short-, medium- or long-term) (Solano et al., 2001b). Asfaw and Admassie (2004) also found the role of family characteristics, particularly the level of education, and the decision environment,
affected the decision making process. This applies when the family acts as one decision entity.
Overall, the respondents exhibited different strategies for processing information about new technologies. These results, however, have not highlighted any
interrelationship between the respondents’ characteristics and their decision contexts that influenced their information practices. This could be achieved by applying the Theory of Planned Behaviour (TPB) where the respondents’ information processing approach could be explained through interlinking their perceptions with their
significant others’ opinions as well as their decision making setting. This actual analysis is in fact presented in Section 6.3.
6.2.4. Summary
From the background interview it was found that most of the respondents in
Sugihwaras and Rejosari were small-scale farmers. Most of them also had a limited level of education and obtained their farming knowledge and skills from their family as well as an exchange of knowledge with their neighbours. Their main commodities included paddy and milkfish with a yearly production level ranging from stable (Sugihwaras) to increasing (Rejosari). High production of paddy and milkfish in both villages, however, had not brought a higher income.
The introduction of “pandu”, which could probably produce higher returns, had not been as successful as might be expected as the respondents appeared to lack interest. One possible reason was that the respondents preferred to have a secure income, although this might not always mean a higher income. Many respondents also viewed prawn as a more risky product than milkfish, despite the higher market price. This perception might stem from (i) the decreasing production trend and prawn price, and (ii) the respondents’ lack of experience. The respondents’ inclination for a steadier income was also confirmed by their high reliance on marketing through
intermediaries. On one side, this attitude was reasonable since most of them were smallholder farmers. On the other side, such attitudes were inconsistent considering
that most respondents set a higher income as their main objective. In addition, the problems faced by the respondents were found to be relatively moderate. The respondents who showed a preference toward prawn culture usually had sufficient experience, lived in a village close to a water source, and/or had sufficient
resources/knowledge for dealing with the challenges.
The background interview also revealed the respondent’s approaches to information seeking. The respondents used different local sources when searching for certain types of information. They learned their farming skills from their family, but sought information about new inputs from their neighbours. Middlemen, local warehouse and local market people were also important sources of market information. Low utilization of external information sources on farm credit, however, reflected the existing barrier to credit in both villages. A similar situation was also identified in the case of obtaining information from extension services, which was mainly due to the limited number of field extension workers available for farmers in both villages.
The respondents were also asked about their information processing approach. Most of them relied on a mind-based farm recording system. When they were asked about their reaction to information about a new technology, two decision making
approaches were identified. Firstly, some respondents directly decided to implement the technology once they received relevant information. Alternatively, the respondents would search for further information and, at the same time, wait for an observable progress/result. The second approach seemed to be more common as the respondents indicated that their main consideration when appraising a new technology included “observable results” and “significant others’ opinion”. Other considerations included financial aspects, the characteristics of the technology and agro-climatic conditions. The respondents who chose the second approach discussed new information mostly with their spouse and, at the same time, learned from their neighbours. The latter might include passive observation of neighbours’ practices and/or an evening- informal discussion in a local coffee shop (in local terms, known as a “cangkruk”).
Despite the interaction with others, most of the respondents preferred making the final decision alone. This may suggest differences in the way the respondents and their significant others construe information about new technology. A bargaining process might also be involved in reaching a compromise, although this could not be proved using the background interview results. A framework that can integrate the
interrelationships between the respondents’ characteristics, their significant others and the decision making environment, hence, is clearly required. This is explained next.
6.3. Models of Planned Behaviour