An Integrated Conceptual Framework for ICT-based Market Information Source Adoption among Smallholder Farmers

The importance of ICTs for dissemination of information to farmers has been verified by extension practitioners, information and communication scholars, policy makers and development agencies. Information related to new seed varieties, production technologies, livestock breeds, vaccines, including weed and pest control, as well as relevant market information is constantly required by smallholder farmers. The identification of specific attributes among smallholder farmers which contributes to their adoption of a proposed ICT-based information source provides an important tool for developing interventions which address the information needs of farmers. Using a literature survey methodology, pertinent studies related to adoption of ICTs, farmers’ information source usage and relevant frameworks were identified, including applicable theories and models in technology adoption and information behaviour. In the proposed framework, the socio-economic characteristics of smallholder farmers were posited as key variables influencing smallholder farmers, within a farming system, to adopt ICT-based information sources. The framework contributes to discern the prospects of adopting ICT-based information sources by individual farmers within a farming system, and may also envisage other related welfare outcomes and market participation pathways among smallholder farmers. The review also addresses the paucity of conceptual discourse, while contributing to a growing pool of research on ICT in African agriculture.


INTRODUCTION
Information sources are vital and considered a pre-requisite for objective decision-making. It is agreed that information sources must be accurate, provide relevant and current information for it to be used frequently (Adereti, Fapojuwo and Onasanya, 2006;Kapoor, 2015). Other characteristics of a good information source include its cost-effectiveness, trustworthiness, usability, exhaustiveness and aggregation level (Acheampong et al., 2017). Information sources are important as they have contributory linkages to the utilization of information by farmers (Fawole, 2006), and determines whether the information is acted on or not. An understanding of preferred information source(s) among any group of farmers is pertinent in designing specific and targeted interventions (Babu et al., 2012), and it is for this reason that research has focussed on the source(s) of information available to smallholder farmers, same time, improving income and other welfare outcomes (Katengesa, 2012;Martey, 2014; Katengesa, Okello, Mensah and Jambo, 2014). Proponents of ICT-enabled market information sources such as Gwaka (2017) and Payne (2011), envisage ubiquitous information systems, capable of widespread distribution of market information and resulting in increased accessibility and participation of smallholder farmers in markets.
This review therefore aimed at outlining a conceptual framework which consolidates the factors leading to ICT-based information source adoption among smallholder farmers.

METHODOLOGY
The conceptual analysis and literature review approach was used. The review involved analysis of published resources from a search of available literature on the use of ICT-based sources among smallholder farmers, identification of relevant frameworks and empirical results from related studies. Using the EBSCO-host retrieval database, a basic search using relevant keywords produced a huge number of entries, which were further reduced by application of limiters, such as relevance, publication period and peer-reviewed journals.

REVIEW OF RELEVANT LITERATURE
Agriculture is, without doubt, an information sensitive sector (Deloitte, 2012), and Opara (2008) asserted that information use in agriculture has increasingly become important for effective decision making by farmers. There is a viewpoint which suggests that information is a public good that should be made widely and freely available (Pimentel and Franscisco, 2009;Ferris, Engoru and Kaganzi, 2008), therefore, farmers need to be connected to sources where they derive appropriate information (Manfre and Nordehn, 2014). Modern and widely available information and communication technologies (ICTs) are able to deliver relevant and timely information, facilitating informed decisions for utilising resources in the most productive and efficient mode. It is on this premise that Oladele (2011) declared that ICTs have become the gateway for agricultural information, due to the immensely optimistic perception among relevant stakeholders, such as extension agents, researchers and farmers, regarding its role.
Additionally, these ICT tools have the potential to not only transform agricultural systems, but also ensure prosperity of farm enterprises (Gwaka, 2017). Generally speaking, farmers are a group of active information-seekers and users, especially for their production and marketing decisions. There is scant literature on the information-source adoption attributes of farmers and its contribution to their decision-making processes (Just et al., 2002;McBride and Daberkow, 4 2003). Available studies primarily focus on the adoption of technology by farmers and not on the information sources influencing adoption (Velandia et al., 2009). Impressive growth in the application of information and communication technologies for marketing, production and services is acclaimed in the literature. The efficiency gains generated by farmers through the use of ICTs and subsequent transformations in agri-food production and processing systems have been noted (GODAN, 2018). The utility of ICTs in agricultural marketing and production value-chains have been highlighted by the World Bank (2011), and according to Tembo and Maumbe (2010), ICTs have become invaluable to the success of commercially oriented agricultural production. The efficacy of ICTs and its linkage to smallholder market participation is reiterated by Sibande, Barley and Davidova (2015), asserting that the receipt of market information from ICT-based media positively influenced market participation among smallholder farmers.
The imposing digital divide faced by smallholder farmers, especially in rural sub-Sahara African communities is a major cause for concern. This is because farmers lacking access to ICTs may experience digital poverty, increasing their risks which may also prevent them from adopting additional agriculture-based technologies Freeman and Mubichi, 2017). All of which reinforces their vulnerability to the acclaimed poverty trap (Barrett and Carter, 2013). This poverty limits access to information due to the costs involved in gathering information, and the remote rural environment where smallholder farmers reside is characterised by unequal and inequitable distribution of information (Magesa et al., 2014;Svensson and Yanagizawa, 2009). Khalil-Moghaddam and Khalia-Abadi (2013) declared that the identification of factors which foster adoption of ICTs is among the important challenges for alleviating a potential digital divide. They argued that availability-regarded as the existence of a system, worked towards reinforcing adoption attributes in the population and also affirmed the influence of certain socio-economic variables in the adoption of ICTs.
Research shows that individual characteristics are important indicators for technology adoption (Ali and Kumar, 2011;Oluwatayo, 2014), and to effectively incorporate ICTs, both the cultural context and specific characteristics of both adaptors and innovations must be taken into consideration (Kyem 2012). Individual attributes also influence the need for information, as well as the capacity to obtain and utilize such information (Israel and Wilson, 2006). While developing a model for computer uptake and use among farmers, Alvarez and Nuthall (2006) averred that farmer attributes such as enterprise objectives, personality, education, skills, Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 10 March 2020 doi:10.20944/preprints202003.0163.v1 current information management processes, and learning style were associated with their use of ICT-based information systems. Velandia et al. (2009) also posited that farmer's socioeconomic and demographic factors impact their preference regarding information-source usage.
This corroborates the position of Just et al. (2002), that different human capital attributes favour the use of different information sources. It also fits the narrative espoused within the economic approaches regarding decision-making (Agrilink, 2017), which assumes that decision-making processes are hinged on an internalized comparative analysis by the concerned person(s). Hill (2009) earlier reported that farmers, as individuals, have their preferred information sources which they utilise depending on the type of information sought. However, the reliance on the economic approach alone for decision-making ignores the complexities involved; as economic decisions are often embedded in specific technological pathways, institutional frameworks and socio-cognitive norms.
Due to this, social psychology theories such as Ajzen's (2005Ajzen's ( , 2011 Theory of Planned Behaviour which linked social norms and practical limitations, have found increased application in explaining farmers decision-making, and, in this instance, their informationseeking behaviour . In the context of smallholder farmers' decision-making, the theory suggests that the decision of the farmer to switch information sources, aimed at meeting a specific objective, is actively planned (Sutherland, 2010). The farmer has a clear motive in considering using the information source, thinks of the practicality of using the information source, and more importantly, the social implications of utilizing the proposed information source; which in this instance, is akin to a planned behaviour.
In their study of precision technology adoption among farmers, Velandia et al. (2009) postulated that farmers must make a decision regarding which information source to use from among the array of available sources. The importance of delineating information sources is highlighted by Adegbola and Gardebroek (2007), who found group differences in adoption technologies. Related to this, Somers and Stapleton (2013) proposed new integral systems framework of e-agricultural adoption aimed at initiating new avenues for research, theory and practice, which ultimately informs policy related to e-readiness among rural communities.
Following Valendia et al. (2009), the empirical approaches adopted suggest that the decision to use a particular information source is independent across information sources.
The need for models or frameworks that enhance our understanding of information sources preferred by farmers and how ICTs are linked must be considered an on-going endeavour. This is as a result of rapid changes in how information is generated and used. Such frameworks help with, developing new systems for information dissemination, addressing the need for understanding the target community before propagation of information (Msoffe and Ngulube, 2016), predicting the information-seeking behaviour of farmers (Mahindarathne and Min, 2018), placing emphasis on socio-economic factors in the technology adoption decisions

THEORETICAL UNDERPINNINGS
The review is anchored and draws from three widely used technology acceptance theories in  The model shown in Figure 1, indicates that a source (S), such as market actors, may originate a message (M) highlighting specific requirements of product, price and place. These messages are communicated using available channels (C), which may include ICT-enhanced tools, often used interchangeably when referring to information sources in the literature (Msoffe and Ngulube, 2017;Osei et al., 2016). These channels (sources) are considered worthy of researching to provide insight on how farmers receive (R) information (Isaya et al., 2016), and in this instance, the effect (E) is considered as their action or feedback to the market actors.
The Technology Acceptance Model (TAM) outlined in Davis et al. (1989) as adapted from the Theory of Reasoned Action, is an information systems theory which models technology acceptance and use. Its two most important pillars are the individuals' perceived usefulness and ease of use (Li, 2010). These two beliefs then lead to individual intention and actual behaviour. The focus of the theory is on the individual, whose relevant features can be identified using their personal characteristics. For this reason, Kim and Crowston (2011) have emphasized the importance of the individual user perspective in ICT adoption research, and encouraged Information Systems scholars to identify factors that influence individual users' adoption and use of ICTs.
The Unified Theory of Acceptance and Use of Technology (UTAUT) integrates the elements from eight technology acceptance models (Venkatesh et al., 2003), and is widely accepted and validated for technology adoption, but has been variously criticised for grouping and labelling a variety of items to represent single constructs. This representation of a single construct by different variables is problematic. For clarity and significance, Raaij and Schepers (2008) have argued for the inclusion of single variables that, in their view, moderate the key relationships within the model. These variables proposed to yield more significant coefficients, are primarily composed of personal features such as gender, age, and experience.
The Diffusion of Innovation (DOI) Theory of Rogers (1995), when used to study the adoption or use of ICT services is considered as a Technology Acceptance Model; emphasised in many studies including MacVaugh and Schiavone (2010), and Woosley and Ashia (2011). In line with this, Simin and Jankovic (2014) professed that the theory attempts to predict the behaviour of individuals and social groups, considering their individual characteristics and social relations, among others. Hence, Kapoor et al. (2013) reported that many researchers have utilized the theory to aid understanding of technology adoption. An advantage of the Diffusion of Innovation Theory, as asserted by Ituma-Aleke and Egwu (2014), is the provision of a contextual set driving the acceptance of a technological innovation, such as the use of ICTbased information sources.
The adoption approach which is relevant for our purpose, describes the adoption decisions of users through the application of different individual and social decision making theories, such as the Actor Network Theory (Callon, 1999), Technology Acceptance Model (Davis, 1989), Theory of Reasoned Action (Ajzen and Fishbein, 1980), the Theory of Planned Behaviour  (Ajzen, 1991) and the Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003).
Other relevant theories include the Uses and Gratifications Theory (Lin 1999

A Review Framework
Following the review of relevant theories and identification of associated concepts, a guiding framework for analysing the adoption of ICT-based market information sources among smallholder farmers in a particular farming system is presented in Figure 2. The framework  The purpose of the farm enterprise, household resources, farming practices and structure also play significant parts in the process of adopting the ICT-based information source for market participation. Finally, the adopting farmer has to overcome the access barriers for participating in markets, which includes distance to markets, poor rural infrastructure and transport systems, including inadequate information. In all these, the demographic characteristics of the farm household, social factors alongside other external variables affect the socio-economic environment within which the farmer operates, and invariably influences the outcome of the decision to adopt ICT-based market information sources for enhanced market participation.

Frameworks
Mwakaje (2010)  possible welfare outcomes (institutional involvement, quality of information and knowledge).

The importance of this framework lies in the division between intention (perceived usefulness)
and behaviour (level of usage) among users, which in this review, is aligned to the information need (perceived usefulness) and information-seeking behaviour (level of usage) of farmers.
Lubua and Kyobe (2019)  This agrees with many other studies that empirically confirmed the significant influence of the socio-economic characteristics of farmers in their adoption of ICTs for marketing and production decisions in specific farming systems (Nwafor, 2019;Waqas et al., 2015;Oluwatayo, 2014;Kyem, 2012;Bagchi & Udo, 2007). socio-economic characteristics, as central to understanding how individual smallholder farmers adopt ICT-based sources for obtaining market information.

An Integrated Conceptual Framework of ICT-based Information
The proposed emphasis on the socio-economic characteristics of farmers in ICT source use, as an influencing or independent variable is supported by key technology acceptance theories, and scholars such as Okello et al. (2014), Mwombe et al. (2013), Chirwa and Matita (2012), and Rahut et al. (2010). These authors submitted that important determinants of market participation and utilisation of ICTs relate to personal and farm-specific characteristics of farmers, and variables hypothesised to influence ICT use were selected among the personal features of farmer-respondents, such as their age, gender, level of education, farm size and income. These individual challenges are also highlighted by Fawole and Olajide (2012) as impeding factors in the adoption of ICTs among smallholder farmers. Worthy of note is the moderating effect of individual differences in a number of ICT adoption studies reported by Kim and Crowston (2011).
In support of this position, Hemmer et al. (2012) as well as Langat et al. (2016) established that the personal characteristics of information seekers influenced their selection and use of information sources. Furthermore, Mittal and Mehar (2015) reported that socio-economic factors were significantly associated with the information source relied upon by smallholder farmers; hence Olwande andMathenge (2011), andOmiti et al. (2009), highlight the effect of socio-economic characteristics, which are utilised as independent or influencing variables in the ICT-source adoption research.
In their study of factors driving ICT adoption in both developing and developed countries, Bagchi and Udo (2007) found that economic development measured as GDP, income and inequality, education or training, and the availability of infrastructure had significant relationships with the adoption of ICTs. These factors can be classified into personal features, such as education and income, and institutional factors including infrastructure and government regulations.
The review also draws from elements of the Quadratic Usage Framework, which highlights internal factors related to the user such as competency and personal values, as directly influencing their ability and motivation, which results in the usage of technology. These attributes drawn from various fields of study and relevant theories outlined in Table 1 were applied to highlight the personal characteristics of smallholder farmers in the development of an applicable framework. • Agriculture The framework specifically outlines the key variables which influence the adoption of ICTbased market information sources among smallholder farmers. These variables are conjectured to improve their use of ICT-based sources and continued participation in markets. In the framework outlined in Figure 3, the independent or explanatory variables consist of the personal, socio-capital and farm specific characteristics. These include age, gender, education level, income, farm size, income, membership of cooperative and household size. These personal or farm specific features (independent or explanatory variables) are then combined with instrumental variables like cost, convenience, ease of use, availability and timeliness, farming system, infrastructure, network connection, government regulations; and intervening variables like need, knowledge and perception. As proposed by Msuya et al. (2014), the framework needs to accommodate the influence of many varying personal and environmental factors, which could be functional in different permutations and directions. The combined influences of these factors determine whether farmers are aware or use ICT-based market information sources, and what market information they are able to receive. The access to market information hence has consequences for smallholder farmers' participation or non-participation in markets, and other identified possible welfare outcomes such as poverty alleviation.

CONCLUSION
The review process developed a conceptual framework for identifying pertinent factors in the adoption of ICT-based information sources among smallholder farmers, especially in sub-Sahara Africa. In the framework put out for peer-review and validation, the socio-economic characteristics of smallholder farmers such as their age, gender, level of education, membership of a cooperative, farm size, number of livestock owned, type of crop grown, an additional income source, among others, were posited as key variables in determining whether smallholder farmers in a farming system will adopt ICT-based information sources. Using a literature survey, pertinent studies related to adoption of ICTs, farmers' information source usage and relevant frameworks were identified, including applicable theories and models in technology adoption and information behaviour; all of which were used to construe the importance of personal features of smallholder farmers. It highlights the prevalent views, and support provided in the literature regarding the appropriateness of considering socio-economic features in adoption of ICT-based information sources among smallholder farmers.
Through identification of ICT-source adoption attributes among smallholder farmers, the framework demarcates the personal, socio-capital and farm-specific characteristics from other instrumental and intervening variables that apply uniformly to individual farmers within a farming system. When applied, the framework contributes to discern the prospects of adopting ICT-based information sources by individual farmers in the farming system. The possibility of identifying specific smallholder farmers, who are inclined to adopt a proposed ICT-based information source, provides an important tool for developing interventions which address the information needs of farmers. The framework may also be used to envisage related welfare outcomes and market participation pathways among smallholder farmers.