Intermediation Capabilities of Information and Communication Technologies (ICTs) in Ghana’s Agricultural Extension System Nyamwaya Munthali Thesis Supervisor, Postgraduate Studies Department, University of Lusaka https://orcid.org/0000-0001-9713-3632 Rico Lie Assistant Professor, Knowledge, Technology and Innovation Group, Wageningen University, The Netherlands https://orcid.org/0000-0003-4228-5107 Ron van Lammeren Associate Professor, Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, The Netherlands https://orcid.org/0000-0002-5062-882X Annemarie van Paassen Associate Professor, Knowledge, Technology and Innovation Group, Wageningen University, The Netherlands https://orcid.org/0000-0001-5341-3114 Richard Asare Country Representative, International Institute of Tropical Agriculture, Accra https://orcid.org/0000-0002-5557-9190 Cees Leeuwis Professor, Knowledge, Technology and Innovation Group, Wageningen University, The Netherlands https://orcid.org/0000-0003-1146-9413 Abstract Information and communication technologies (ICTs), specifically those that are digital and interactive, present opportunities for enhanced intermediation between actors in Ghana’s agricultural extension system. To understand these opportunities, this study investigates the capabilities of ICTs in support of seven forms of interme- diation in the context of agricultural extension: disseminating (information), retriev- ing (information), harvesting (information), matching (actors to services), networking (among actors), coordinating (actors), and co-creating (among actors). The study iden- tifies the types of ICTs currently functioning in Ghana’s agricultural system, and applies a Delphi-inspired research design to determine the consensus and dissensus of researchers, scientists, and practitioners about the potential of these ICTs to sup- AJIC Issue 28, 2021 1 Munthali et al. port each of the seven intermediation capabilities. The findings reveal that experts reached consensus that interactive voice response (IVR) technologies currently have the highest potential to support disseminating, retrieving, harvesting, and matching. Meanwhile, social media messaging (SMM) technologies are currently seen as high- ly capable of supporting coordinating and, to a lesser extent, co-creating, but no con- sensus is reached on the potential of any of the technologies to support networking. Keywords information and communication technology (ICT), agricultural innovation systems (AIS), ICT for agriculture (ICT4ag), agricultural extension, intermediation, inter- mediation capabilities, Ghana Acknowledgements This research was co-funded by the Wageningen University Interdisciplinary Re- search and Education Fund (INREF) and the Consultative Group on Internation- al Agricultural Research’s (CGIAR’s) Research Program on Maize (MAIZE). The research was further supported by the CGIAR donors,1 and by the Consortium for Improving Agriculture-based Livelihoods in Central Africa (CIALCA), which is funded by Belgian Directorate General for Development Cooperation and Human- itarian Aid (DGD). DOI: https://doi.org/10.23962/10539/32212 Recommended citation Munthali, N., Lie, R., Van Lammeren, R., Van Paassen, A., Asare, R., & Leeuwis, C. (2021). Intermediation capabilities of information and communication technologies (ICTs) in Ghana’s agricultural extension delivery. The African Journal of Information and Communication (AJIC), 28, 1-37. https://doi.org/10.23962/10539/32212 This article is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence: https://creativecommons.org/licenses/by/4.0 1 See https://www.cgiar.org/funders/ 2 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery 1. Introduction Agricultural productivity growth in Ghana, necessary to bridge the gap between potential and actual production of food and cash crops, is partly hampered by the prevailing approach to agricultural extension service delivery (Abdulai et al., 2020; Bua et al., 2020; McNamara et al., 2014; MOFA, 2007; World Bank, 2017). This approach is typified by extension largely focused on knowledge and technology transfer to farmers, rather than taking on broader roles (e.g., knowledge brokering, facilitating access to credit, and supporting market linkages) and serving a broader stakeholder base (Agyekumhene et al., 2018; Munthali et al., 2018). The narrow focus of this extension approach is problematic because farmers have multi-faceted production needs, and “improving food production […] is not just a matter of in- dividuals [farmers] receiving messages and adopting the right technologies [from scientists/researchers], but has much more to do with altering interdependencies and coordination between various actors” (Leeuwis, 2004, p. 18). More specifically, the prevailing extension approach fails to adequately coordinate the set of organisations2 that support value chain actors3 in emergent problem-solv- ing (e.g., with respect to climate change impacts), facilitating business linkages be- tween these actors, and facilitating the integration of scientific and other knowledges to produce appropriate knowledge and technology for value chain actors (Abdu-Ra- heem & Worth, 2016; Asiedu-Darko & Bekoe, 2014; McNamara et al., 2014). These drawbacks in the national extension system hamper production (Msuya & Wambura, 2016; Zwane, 2020). Since 1996, statements of national agricultural policy objectives in Ghana have con- sistently posited that reorganisation and improved coordination in the sector are key to agricultural development and climate change adaptation (DAES, 2011; Sigman, 2015; Sova et al., 2014; World Bank, 2017). Based on this policy direction, proposed structural changes in the Ghanaian extension service delivery system have included accommodating private extension organisations to meet the high demand for exten- sion services, value chain-focused interventions, and innovation platforms (Adekunle & Fatunbi, 2014; Agyekumhene et al., 2018; McNamara et al., 2014; Van Paassen et al., 2013). Thus, the extension ideology has broadened, since the 1990s, to include calls not only for top-down, one-size-fits-all approaches (i.e., training and visita- tion) but also for participatory and bottom-up approaches (e.g., farmer field schools) (DAES, 2011; Davis, 2008). The most recent Ghanaian extension framework is an 2 Research institutions, educational institutions, non-governmental organisations, development organisations, other government institutions, credit providers, weather service providers, transporters, and private extension service providers. 3 Farmers, input suppliers, processors, exporters, traders, retailers, wholesalers, packaging manufacturers, and other manufacturers. AJIC Issue 28, 2021 3 Munthali et al. integrated pluralistic extension system (Abdu-Raheem & Worth, 2016; Sigman, 2015). This approach envisages strengthened research–extension linkages, broader service delivery lines, and a larger number of service providers, with the intention of meeting the demand of farmers and other value chain actors for extension services. Ghana’s current extension ideology aligns with the agricultural innovation systems (AIS) perspective. With a view to fostering innovation in agriculture, the AIS per- spective focuses on influencing relationships between multiple actors and on the conditions (e.g., policies) that affect the actors’ (collective) operations (Klerkx & Leeuwis, 2008; Leeuwis, 2004; Swanson & Rajalahti, 2010). According to the AIS perspective, the focus on multiple actors’ relationships is necessary because: (1) in- novation occurs when interaction between diverse stakeholders is increased and open, resulting in improved knowledge exchange and access to appropriate knowl- edge and technology; and (2) innovation requires networking through which actors form partnerships that allow them to access business development opportunities and engage in collective action to respond to systemic challenges holistically (Koutsouris, 2012; Swanson & Rajalahti, 2010; World Bank, 2012). Extension approaches based on the AIS perspective involve three broad interme- diary roles: demand articulation, matching demand and supply, and innovation process management. Demand articulation involves the engagement of sector stakeholders in activities such as joint needs identification, participatory problem diagnosis and assessment, and making interdependencies explicit (Klerkx & Gildemacher, 2012). Matching demand and supply involves establishing sector contacts and developing mutually beneficial relationships—advice, credit, input, and market linkages (How- ells, 2006). Lastly, innovation process management comprises the creation of discus- sion and negotiation space for actors to coordinate and jointly mitigate constraints, maintain relationships, and engage in knowledge-sharing and integration or co-pro- duction for continuous innovation (Leeuwis, 2010; Vitos et al., 2013). Despite Ghana’s national agricultural policy direction transitioning to an AIS-based extension approach, barriers still stand in the way of both public and private ex- tension organisations on the path to facilitating this new direction. These factors include financial constraints (e.g., untimely and limited funding), human resource constraints (e.g., freezes in hiring staff, limited staff numbers), and skill set-related constraints (e.g., limited adaptation on the part of educational institutions to develop the facilitation capabilities of extension staff ) (MOFA, 2007; Obeng et al., 2019; Sova et al., 2014). 4 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery At the same time, Ghana is a key African player in the innovative use of digital information and communication technology (ICT) (GSMA, 2019). Digital ICTs are now central to most spheres of development (Sein et al., 2019; United Nations, 2020), as represented by the ICT for development (ICT4D) discipline, which is focused on “the application of any entity that processes or communicates digital data in order to deliver some part of the international development agenda in a developing country” (Heeks, 2017, p. 10). Among the key ICTs and ICT-enabled services har- nessed for developmental purposes are interactive voice response (IVR), short message service (SMS), unstructured supplementary service data (USSD), social media (e.g., WhatsApp, Facebook), and document and data management systems (e.g., Open Data Kit). Such ICTs and ICT-enabled services present new opportunities for con- nectivity and information sharing to enhance communication-related service delivery (Bell, 2015; Gershon & Bell, 2013). Therefore, these technologies are being explored by scientists, researchers, and development practitioners to respond to the limitations of classical approaches to extension and interaction in Ghana’s agricultural system (Cieslik et al., 2018; Fielke et al., 2020; Gakuru et al., 2009; MEST, n.d.; Qiang et al., 2012). Currently, there is limited literature assessing the capability of different types of ICTs to drive agricultural innovation processes (Fielke et al., 2020; Van Osch & Coursaris, 2013). One such rare study presents an assessment by European experts of the capability of social media and other web-based platforms to act as drivers of agri- cultural innovation (Hansen et al., 2014). The study finds that a number of the plat- forms (particularly social media) have high capacity to support the following specific social networking functions that support innovation: discussion (Facebook, NING, ERFALAND, and Yammer); networking (Facebook, LinkedIn, and NING); crowd- sourcing (ResearchGate and Crowdsourcing); cooperation (Yammer, ResearchGate, and Wikipedia); and co-production (ResearchGate and Wikipedia). However, the aforementioned European-focused study (Hansen et al., 2014) assesses forms of me- dia that are often not easily accessible in African agricultural contexts, where farmers are typically located in rural settings with limited access to the internet and to mo- bile devices that support internet services (Aker, 2011; Nyamekye, 2020). Thus, the opportunities for ICTs presented in the Hansen et al. (2014) study cannot be fully leveraged in many African agricultural systems. AJIC Issue 28, 2021 5 Munthali et al. In this study we seek to address a research gap through the identification of oppor- tunities for ICTs to support intermediation capabilities relevant to AIS-based exten- sion service delivery, in an African setting—specifically Ghana. The study identifies opportunities through a consensus-building exercise that captures the perspectives of scientists and researchers in the fields of communication, innovation, and develop- ment informatics; and practitioners of ICT for agriculture (ICT4Ag). 2. Conceptual context and analytical framework In this section we start by discussing bridging mechanisms as an overarching concept that incorporates the core concept of this study, which is intermediation capabilities. We highlight the possibility of ICTs functioning as bridging mechanisms and, in doing so, supporting extension organisations in facilitating AIS-based extension ser- vice delivery. We also outline the types of intermediation relevant to this facilitation process, and the intermediation capabilities that the ICTs may support. We conclude the section by stating the research questions. ICTs functioning as bridging mechanisms Farmers operate in multi-faceted production environments. Enhancing the perfor- mance of the Ghanaian agricultural sector, therefore, requires improved information (knowledge) flows among agricultural stakeholders and improved business linkages. The major stakeholders in the agricultural system are knowledge technology provid- ers and users. Their interaction and knowledge exchange need to be enhanced, along with that of other value chain actors who currently only have loose linkages (Adolwa et al., 2017; Asiedu-Darko, 2013; McNamara et al., 2014). The other main actors in the system are bridging organisations that are involved in facilitating interaction and linkages between stakeholders (Kilelu et al., 2011; World Bank, 2012). Bridging organisations are defined by Berkes et al. (2003) as organisations that provide an arena for knowledge co-production, trust-building, sense-making, learning, vertical and horizontal collaboration, and conflict resolution. From an innovation systems perspective, bridging organisations are regarded as in- termediaries, which are “persons or organisations that, from a relatively impartial third-party position, purposefully catalyse innovation through bringing together ac- tors and facilitating their interaction” (Klerkx & Gildemacher, 2012, p. 221). For many developing countries, it has been argued that agricultural bridging functions are best suited to, and easily assimilated by, public extension organisations, even 6 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery though other organisations (e.g., private extension organisations, non-governmental organisations (NGOs), farmer-based organisations, and research institutions) have been involved in the role (Kilelu et al., 2011). In the case of Ghana, for extension organisations to assimilate the bridging role in line with the AIS-based approach (Abdu-Raheem & Worth, 2016; Sigman, 2015), they “are required to expand their role from that of a one-to-one intermediary between research and farmers” to that which “creates many-to-many relationships to facilitate access to knowledge, skills, services, and goods from a wide range of organisations” (Kilelu et al., 2011, p. 89). However, various other actors in agricultural systems can also take on bridging func- tions. These include sector-focused networks, trade associations, special government programmes, consultants, input suppliers, and, with direct relevance to this study, ICTs (Kilelu et al., 2011; Klerkx & Gildemacher, 2012). ICTs can serve as bridging mechanisms (Hansen et al., 2014; World Bank, 2012), and can be leveraged by ex- tension organisations and other extension actors in support of functioning better as bridging organisations and engaging in AIS-based extension service delivery. Intermediation Hansen et al. (2014) assess the ability of social media and other ICT-enabled tools to drive agricultural innovation based on six “social network functions”: networking, cooperating, co-producing, crowdsourcing, discussing, and engaging. Using this frame- work, Hansen et al. (2014) engaged innovation systems experts to assess the extent to which different forms of social media and other web-based platforms (e.g., YouTube, ResearchGate, LinkedIn, Facebook, Twitter) support particular networking func- tions that may facilitate collaboration for sharing ideas and for mobilising knowledge and resources circulating in other arenas (Granovetter, 1973; Kaushik et al., 2018). In the African context, ICTs have been found to facilitate aspects of AIS-based ex- tension service delivery by enabling multiple actors to network and engage in joint needs identification, knowledge-sharing, and problem-solving to meet information needs in farming systems (Ajani, 2014; Fabregas et al., 2019; Munthali et al., 2018). Mobile applications have, for example, been recognised for their ability to improve value chain linkages (Ajani, 2014; Zwane, 2020), to build timely monitoring systems (e.g., with geo-referenced data) on environmental issues and production, and to pro- vide timely advice to enable farmers to respond to farming challenges (Gbangou et al., 2020; McCole et al., 2014). AJIC Issue 28, 2021 7 Munthali et al. That said, it is important to note that, in general, most studies of the role of ICTs in agricultural extension focus on the use of specific ICT tools (typically mobile apps) to provide market, technical, and weather information to farmers, rather than on ICTs’ impact, or potential impact, on the provision of AIS-based extension (Aker et al., 2016; Misaki et al., 2018). Furthermore, despite ICTs falling within the typology of intermediaries that can facilitate interaction and linkages between AIS actors to foster innovation, most studies of innovation intermediaries focus on the functioning and influence of other types of intermediaries, e.g., consultants targeting individual farmers and small and medium-sized enterprises (SMEs) in the agri-food sector; consultants targeting farmer collectives and agri-food SMEs; peer network brokers; education brokers; systemic intermediaries; and research councils (Kilelu et al., 2011; Kivimaa et al., 2019; Winch et al., 2007). Therefore, existing literature does not clar- ify which ICTs among those available in Ghana or other African countries are most capable of supporting the specific types of intermediation required to facilitate AIS- based extension service delivery activities in these contexts. Additionally, there has been little consideration of how experts, from the academically oriented to the more location-specific and practice-oriented, look at the potential of various kinds of ICTs to augment extension service delivery. To address these knowledge gaps, our study explored the views of communication and innovation scientists, development informatics researchers, and ICT4Ag prac- titioners on the current opportunities for ICTs to enhance intermediation functions within agricultural extension service delivery in Ghana. Analytical framework: Intermediation capabilities The framework we deployed in the study builds on the aforementioned social net- work functions framework of Hansen et al. (2014). Our framework modifies the Hansen et al. (2014) networking functions—engagement, discussion, crowdsourcing, networking, co-production and cooperation—by: • merging three overlapping functions (engagement, discussion, cooperation) into two broader functions (coordinating and co-creating); and • including additional functions (harvesting, matching, coordinating) relevant to facilitating AIS-based extension delivery. Overall, we broaden the work of Hansen et al. (2014) to reflect network- ing as well as communication functions relevant to facilitating AIS-based extension service delivery, and we refer to these functions collectively as 8 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery intermediation capabilities. The seven intermediation capabilities in our frame- work—disseminating (information), retrieving (information), harvesting (information), matching (actors to services), networking (among actors), coordinating (actors), and co-cre- ating (among actors)—are detailed below in Table 1. Table 1: Intermediation capabilities Intermediation capability Description Disseminating Enabling content to be spread widely, alerting or attracting the interest (information) of or raising the awareness of a large group of geographically dispersed actors Retrieving Enabling actors to retrieve information (e.g., price, weather) from a (information) central database or to retrieve documents out of a central repository Harvesting Enabling the gathering of feedback, ideas, and opinions through the (information) contributions of a large group of geographically dispersed actors e.g., crowdsourcing or polling Matching Enabling supply and demand linkages – actors are able to query, (actors to services) consult, or search information systems and connect to advice or services Networking Enabling contact between actors so that they make direct connections (among actors) and are able to interact to form new (business) relationships or reinforce existing relationships Facilitating virtual multi-actor engagement4 to provide open and live Coordinating communication channels that enable discussion for coordinated action (actors) e.g., acting together towards a common purpose or engaging in joint problem-solving Co-creating Facilitating a common working space for multiple actors to combine (among actors) and contribute contextual knowledge or information, and engage in document sharing and information storage towards a tangible output Source: Adapted from Hansen et al. (2014), with insights from Leeuwis (2004) and Howells (2006) Taking the intermediation capabilities listed in Table 2 as a reference, this study sought to answer the following research questions: • How do experts assess the extent to which different ICTs support specific intermediation capabilities? • What type of consensus or dissensus do experts reach over which ICTs can support which specific intermediation capabilities? • What factors are contributing to consensus and dissensus among experts about which ICTs can support which specific intermediation capabilities? 4 Multi-actor engagement in this study refers to virtually connecting and placing more than one actor in a virtual “room” and around a virtual “table” where they can engage in, or take advantage of, one- to-many and many-to-many communication (i.e., have a back-and-forth exchange/interaction). AJIC Issue 28, 2021 9 Munthali et al. 3. Methods In this section, we report on the scoping exercise that was conducted to identify the ICTs currently being used in the Ghanaian agricultural system. The outcomes of this scoping study provided the basis for engagement with experts on their views. The section also explains the set-up of the Delphi-inspired study, which was designed to establish experts’ consensus and dissensus with respect to the intermediation capabil- ities of the different types of ICTs that were identified through the scoping exercise. Scoping exercise We reviewed ICT4Ag literature on Ghana, and engaged with organisations rolling out ICT initiatives discovered in the literature, in order to identify the ICTs being used in the Ghanaian agricultural system (Aker et al., 2016; Gakuru et al., 2009; Qiang et al., 2012; World Bank, 2014). Through these scoping activities we devel- oped an inventory of ICT4Ag platforms (see Appendix). We then examined the inventory and were able to identify nine different types of ICTs in use (see Table 2). Table 2: Types of ICTs identified in Ghana’s agricultural system Minimum Type Interface Data Comm- Mobileformat unication device needed network needed short SMS SMS request message pull typing text one-to-one any phone 2G service (SMS) SMS SMS based push reading text one-to-many any phone 2G interactive IVR request- inbound based talking audio one-to-one any phone 2Gvoice and listening response (IVR) IVR request- outbound based talking audio one-to-many any phone 2Gand listening unstructured request- supplementary service data based typing text one-to-one any phone 2G (USSD) and reading social media messaging request- text, audio, (SMM) based typing pictorial, one-to-many smart phone 4Gand reading video text, audio, pictorial, data management data global (DaM) gathering navigation one-to-one or one-to-many smart phone 4Gsatellite system (GNSS) text, audio, document management document pictorial, (DoM) sharing video, one-to-many smart phone 4G GNSS spatial one-to-one or (Spa) mapping GNSS one-to-many smart phone 4G 10 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Deliver y Delphi-inspired expert consensus-building study Building on the scoping study, we developed an expert consensus-building method that was inspired by the Delphi study approach. A Delphi study is defined as “a method for systematic solicitation for judgements on a particular topic through a set of carefully designed sequential questionnaires interspersed with summarised infor- mation and feedback of opinions derived from earlier responses” (Chu & Hwang, 2008, p. 2828). It involves a “group facilitation technique, which is an iterative mul- tistage process, designed to transform opinion into group consensus” (Hasson et al., 2000, p. 1) among experts (Benitez-Capistros et al., 2014). Benitez-Capistros et al. (2014) define an expert as a person who is competent as an authority on particular facts. The content validity of the Delphi is enhanced by avoidance of data collection in a group setting where more dominant actors’ opinions may be captured (Hasson et al., 2000). Furthermore, Delphi data collection involves more than one round of questioning, which increases concurrent validity of the method (Hasson et al., 2000), and because consensus-building is the objective of the Delphi approach, the number of these rounds is undefined and dependent on when consensus emerges or increas- es among participants (Benitez-Capistros et al., 2014). According to Hasson et al. (2000) and Doria et al. (2009), acceptable majorities in a Delphi-derived consensus can range from a basic majority (50–59%) to a low (60–69%), medium (70–79%) or high (≥ 80%) majority. There are variations in the set-up of Delphi studies (Allen et al., 2019; Chu & Hwang, 2008). Our Delphi-inspired expert consensus-building method involved two rounds, and for each round the expert panel composition varied to fit a particu- lar purpose (see Figure 1). Figure 1: Summary of expert consensus-building method AJIC Issue 28, 2021 11 Munthali et al. First round: Honeycomb evaluation by internal panel of experts The first round involved a small internal panel composed of the research team: four experts in the domain of communication and innovation science. The experts each individually engaged in a honeycomb evaluation to assess the intermediation capa- bilities of the various ICTs (see example in Figure 2) and ranked the different ICTs in relation to the seven intermediation capabilities in our framework. The ranking was based on a Likert scale ranging from “0” (no capability to support) to “5” (strong capability to support). Based on the individual honeycomb evaluations, we calculated the average rank assigned by the experts to each type of technology for each type of intermediation capability. Figure 2: Example of honeycomb evaluation output (for “SMS push technology”) The aggregated and averaged results of the four internal experts’ honeycomb eval- uations were then presented to the entire internal panel to facilitate a convergence forum. The convergence forum gave the experts the opportunity to reflect on the ag- gregated results in relation to their individual responses, discuss areas of divergence, and ultimately reach agreement on the indicative intermediation capabilities of the different ICTs. The forum also enabled the experts to identify the significant results of the honeycomb evaluation from which 16 propositions were developed for the second round of the expert consensus-building method. 12 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Second round: Online survey of 11 external experts In the second round, the 16 propositions were packaged into a questionnaire for- mat, using a five-point Likert scale that ranged from “1” (strongly disagree) to “5” (strongly agree). The questionnaire was presented to a broader expert panel made up of Ghana-focused development informatics researchers and ICT4Ag practitioners. Potential respondents were identified from a list of invitees to a workshop convened in Accra, Ghana by the Environmental Virtual Observatories for Connective Action (EVOCA) research programme in April 2019, which targeted Ghanaian agricultur- al stakeholders. Additional researchers and practitioners were identified as poten- tial respondents through a search in the SCOPUS abstract and citation database of peer-reviewed research literature. The search was composed of two steps: (1) a search using the function “(mobile technology or ICT) AND (extension or agriculture) AND (Ghana)”; and (2) screening the articles captured in the search to establish whether they were on topic and, where applicable, to identify authors who could be invited to participate in the survey. In total, 22 potential respondents—13 researchers and nine ICT4Ag practitioners— were identified and sent an email invitation to engage in the study by completing the online questionnaire, which was administered via the web-based platform Google Forms. Of the invitees, 11 (five researchers and six practitioners—see Table 3) re- sponded to the questionnaire during the two-week period given for responses. Table 3: Eleven respondents Respondent’s Respondent’s organisation designation Researchers Centre for Agriculture and Bioscience International, Ghana junior researcher/project manager University for Development Studies, Ghana lecturer Wageningen University, The Netherlands PhD researcher (Ghana-focused) Council for Scientific and Industrial Research, Ghana junior researcher Kumasi Institute of Technology Energy and Environment, Ghana senior researcher Practitioners Esoko, Ghana senior manager Grameen Foundation, Ghana senior manager Farm Radio International, Ghana middle manager Maclear Technology, Ghana senior technical advisor Ministry of Food and Agriculture, Ghana district agricultural officer Ministry of Food and Agriculture, Ghana senior manager, extension directorate AJIC Issue 28, 2021 13 Munthali et al. For round two, the descriptive statistics analysed for each proposition included the mean (qi), the median (Q2), and the frequency of ranking for each point on the Likert scale. Based on these statistics, we determined whether there was positive consensus (agreement) or negative consensus (disagreement) about a proposition, or whether there was dissensus (varied ranking or polarisation) about a proposition. We considered three criteria to determine whether consensus was reached and to determine the direction of the consensus for each proposition (Table 4). These cri- teria were (1) the position of the mean on the Likert scale (Chu & Hwang, 2008); (2) the position of the mean in relation to the median in the data distribution (Chu & Hwang, 2008); and (3) the significance of the percentage of participants ranking a proposition on the Likert scale, ranging from low to medium to high to very high (Doria et al., 2009; Hasson et al., 2000). Table 4: Criteria determining consensus over a proposition Rule Positive consensus Dissensus Negative consensus 1 Position of mean qi > 3.5 2.5 > qi < 3.5 qi < 2.5 on Likert scale 2 Position of mean qi < Q2, Q2 < qi < Q3, qi > Q2, in relation to indicating there indicating there indicating there median of data is a right-skewed is a normal is a left-skewed distribution distribution distribution distribution 3 Position of very high consensus: low consensus: very high consensus: majority ranking ≥80% agree; 50–59% ≥80% disagree; on Likert scale high consensus: dis(agree) or high consensus: 70–79% agree; <60% dis(agree) 70–79% disagree; medium consensus: medium consensus: 60–69% agree 60–69% disagree 14 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Focus group discussion In addition to the expert consensus-building method, a focus group discussion was conducted to establish factors contributing to (positive or negative) consensus and dissensus (varying views or polarisation) over the propositions. The focus group dis- cussion took place during the EVOCA programme’s Ghana workshop. The work- shop attracted 19 participants and, as part of the workshop proceedings, the partic- ipants were selectively split into four working groups that each comprised all the categories of participants present at the event (mainly various kinds of technology users). One of the working groups comprised five workshop participants who took part in the focus group: two public extension staff members, two ICT-based NGO representatives, and a small-scale farmer. We presented the aggregated questionnaire results to the focus group, and they reflected on the results and engaged in an open discussion on whether or not they agreed with them in general, and why. The discus- sion was recorded to facilitate thematic analysis of the plausible factors contributing to consensus and dissensus on the propositions. 4. Findings First round of consensus-building The first round of the expert consensus-building, with the four-person internal pan- el of experts, collated views on the intermediation capability (high to low) of each ICT identified in the Ghanaian agricultural system (see Figure 3). In terms of the ICTs with a high capability to support intermediation capabilities (ranking > 3), the aggregated results of the honeycomb evaluation show that interactive voice response (IVR) outbound technologies were viewed as having very high capability to support disseminating, and IVR inbound technologies were viewed as having high capability to support retrieving. In addition, short message service (SMS) push technologies were seen as having a high capability to support disseminating, and unstructured supplementary service data (USSD) technologies were viewed as having a high capa- bility to support retrieving and matching. Furthermore, the aggregated results showed that social media messaging (SMM) technologies had a high capability to support harvesting and coordinating, and an intermediate capability to support all the other intermediation capabilities, excluding networking. AJIC Issue 28, 2021 15 Munthali et al. Figure 3: First round of consensus-building: Aggregated results of honeycomb evaluation (nine honeycomb images) 16 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery With respect to technologies found to have a low capability to support specific intermediation capabilities (ranking < 3), the panel of internal experts reached consensus that spatial (Spa) technologies generally had a low capability to support all the intermediation capabilities. The panel also reached consensus that SMS pull technologies, data management (DaM) technologies, and document management (DoM) technologies also did not rank highly (ranking > 3) in terms of their capability to support any intermediation. The assessment also found that all ICTs had a low capability to support networking. Second round of consensus-building Based on the aggregated results of the first round of consensus-building, the four- person internal expert panel developed a number of propositions, 16 of which (see Table 5) were used to develop the online survey questionnaire for the second round. AJIC Issue 28, 2021 17 Munthali et al. Table 5: The 16 propositions (P1 to P16) used in second round of consensus-building Intermediation capability Proposition P1 At present, among all the ICTs identified, IVR outbound technologies have the highest capability for disseminating information to rural farmers. Disseminating P2 At present IVR outbound technologies have higher capability than SMS (information) push technologies for disseminating information to rural farmers. P3 SMM technologies have high potential to facilitate disseminating information to rural farmers in the next 10 years. P4 At present, among all the ICTs identified, IVR inbound technologies have the highest capability for harvesting information from rural farmers. Harvesting P5 At present IVR inbound technologies have higher capability than USSD (information) technologies for harvesting information from rural farmers. P6 SMM technologies have higher potential than IVR inbound technologies for harvesting information from rural farmers in the next 10 years. P7 At present, among all the ICTs identified, IVR inbound technologies have the highest capability for allowing rural farmers to retrieve information. Retrieving P8 At present USSD technologies have the highest capability for rural farmers (information) to retrieve information than the other types of technologies. P9 SMM technologies have high potential for rural farmers to retrieve information in the next 10 years P10 At present, among all the ICTs identified, USSD technologies have the Matching (actors highest capability to match rural farmers to services. to services) P11 At present IVR inbound technologies have higher capability than USSD technologies to match rural farmers to services. P12 At present all the technologies identified have low capability to facilitate Networking networking between rural farmers and other agricultural stakeholders. (among actors) P13 SMM technologies have high potential to facilitate networking between rural farmers and other agricultural stakeholders in the next 10 years. Coordinating At present, among all the ICTs identified, SMM technologies have the (actors) P14 highest capability to facilitate coordination between rural farmers and other agricultural stakeholders. P15 At present SMM technologies have intermediate capability to facilitate co- Co-creating creating among rural farmers and other agricultural stakeholders. (among actors) P16 SMM technologies have high potential to facilitate co-creating among rural farmers and other agricultural stakeholders in the next 10 years. The propositions were also developed within a specific context to aid the panel of external experts in assessing which ICTs were likely to be best suited to facilitate cer- tain communication and networking functions in extension activities. The internal panel (more academic-oriented), therefore, required the external panel of respond- ents (more Ghana-specific and practice-oriented) to envision themselves as district extension staff tasked by the “Ministry of Agriculture – Headquarters” to qualify or disqualify the preliminary assessment of the current capability and future potential of specific ICTs to improve extension service delivery involving rural farmers. Experts’ consensus on propositions The results of round two showed that seven of the 16 propositions presented to the external experts were marked by positive consensus (Table 6). Additionally, the ques- 18 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery tionnaire results showed that there was no negative consensus among the external experts about any of the propositions. Table 6: Propositions associated with positive consensus Criteria for positive consensus Crit. 1 Crit. 2 Crit. 3 Type of ICT Proposition qi > 3.5 qi < Q2 (strongly) Agree % At present, [...] IVR inbound P4 technologies have the highest capability for harvesting 3.55 > 3.5 3.55 < 4 63.64 information from rural farmers. At present, [...] IVR inbound IVR P7 technologies have the highest inbound capability for rural farmers to 3.73 > 3.5 3.73 < 4 72.73 retrieve information. At present IVR inbound P11 technologies have higher capability than USSD technologies to match 3.73 > 3.5 37.3 < 4 81.82 rural farmers to services. At present, [...] IVR outbound P1 technologies have the highest capability for disseminating 3.64 > 3.5 3.64 < 4 72.73 information to rural farmers. IVR outbound At present IVR outbound technologies have higher capability P2 than SMS push technologies for 3.73 > 3.5 3.73 < 4 72.73 disseminating information to rural farmers At present, [...] SMM technologies have the highest capability to P14 facilitate coordination between 3.82 > 3.5 3.82 < 4 72.73 rural farmers and other agricultural SMM stakeholders. At present SMM technologies have P15 intermediate capability to facilitate co-creating among rural farmers 3.82 > 3.5 3.82 < 4 90.91 and other agricultural stakeholders. Abbreviations: qi = mean; Q2 = median As seen in Table 6, there was positive consensus among the experts that: • IVR inbound technologies currently have the highest capability for har- vesting information from farmers (P4), for supporting farmers in retrieving information (P7), and for matching farmers with advice and services (P11); • IVR outbound technologies currently have the highest capability for dissem- inating information to farmers (P1); and • SMM technologies currently have the highest capability to support coordi- nating between agricultural stakeholders (P14) including farmers, and inter- mediate-level capability to facilitate co-creating by these stakeholders (P15). AJIC Issue 28, 2021 19 Munthali et al. Experts’ dissensus over propositions The experts did not reach consensus on nine of the 16 propositions (Table 7). This dissensus was determined on the basis that the propositions failed to meet all three of the consensus criteria outlined earlier. Table 7: Propositions associated with dissensus Criteria for dissensus Crit. Crit. 2 Crit. 3 Type of 1 ICT Proposition 2.5 > Q2 qi < (strongly)qi < Disagree Neutral (strongly) < qi Q3 % Agree3.5 % % At present IVR inbound 2.5 > 4 > 3.36 18.18 27.27 54.55 technologies have higher 3.36 < 3.36 < 4 IVR capability than USSD 3.5 inbound P5 technologies for harvesting information from rural farmers. At present, [...] USSD 2.5 > 2 < 2.73 54.55 9.09 36.36 technologies have the 2.73 < 2.73 < 4 P8 highest capability for rural 3.5 farmers to retrieve infor- USSD mation. At present, [...] , USSD 2.5 > 2 < 2.73 54.55 9.09 36.36 P10 technologies have the 2.73 < 2.73 < 4highest capability to match 3.5 rural farmers to services. SMM technologies have 2.5 > 3 3 > 3.00 36.36 36.36 27.27 high potential to facilitate < 3.5 3.00 < P3 the dissemination of infor- 3.5 mation to rural farmers in the next 10 years. SMM technologies have 2.5 > 3 < 3.18 18.18 36.36 45.45 higher potential than IVR 3.18 < 3.18 < 4 P6 inbound technologies for 3.5harvesting information from rural farmers in the next 10 years. SMM technologies have 2.5 > 4 > 3.18 36.36 9.09 54.55 high potential for rural 3.18 < 3.18 < 4 SMM P9 farmers to retrieve in- 3.5formation in the next 10 years. SMM technologies have 2.5 > 3 < 3.27 36.36 18.18 45.45 high potential to facilitate 3.27 < 3.27 < 4 P13 networking between rural 3.5farmers and other agricul- tural stakeholders in the next 10 years. SMM technologies have 2.5 > 4 > 3.55 18.18 27.27 54.55 high potential to facilitate 3.55 > 3.55 < 4 P16 co-creating among rural 3.5farmers and other agricul- tural stakeholders in the next 10 years. At present all the tech- 2.5 > 2 < 2.55 54.55 0.00 45.45 nologies identified have 2.55 < 2.73 < 4 All P12 low capability to facilitate 3.5 networking between rural farmers and other agricul- tural stakeholders. Abbreviations: qi: mean; Q2: median; Q3: “middle” value in the second half of the rank-ordered data 20 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Specifically, as seen in Table 7, it was found that experts had varied views on: • whether IVR inbound technologies currently have a higher capability than USSD technologies to facilitate the harvesting of information from rural farmers (P5); • the current capability of USSD technologies to facilitate retrieving of in- formation by rural farmers (P8), or to facilitate matching of farmers with agricultural services (P10); • the current capability of all the technologies identified to support networking between rural farmers and other agricultural stakeholders (P12); • the future potential of SMM technologies to facilitate disseminating, har- vesting and retrieving information targeted at or involving farmers (P3, P6, P9); and • the future potential of SMM technologies to support networking and co-cre- ating between agricultural stakeholders (P13, P16). Focus group f indings: Factors contributing to consensus and dissensus Consensus on high capabilities of IVR technology The focus group discussion revealed two factors contributing to the external experts’ consensus on the high intermediation capabilities of IVR inbound and outbound technologies at present, as described above. One factor was that IVR technologies operate on basic and feature mobile phones (i.e., non-smart phones) that are acces- sible to rural Ghanaian farmers. The other factor was that IVR technologies, un- like SMS or USSD technologies, generate audio as opposed to textual content. This makes them more compatible with the generally low literacy levels of the farmers. In the words of one focus group participant: At the moment, IVR is known widely and used because it is programmed in a language that the end user understands. It does not involve text mes- sages and is available on any kind of phone. Consensus and dissensus on capabilities of SMM technology The focus group also established the reasons behind experts’ consensus on certain intermediation capabilities of SMM technologies and dissensus on other SMM ca- pabilities. The consensus on the high capability of SMM technologies to support co- ordinating between agricultural stakeholders, at present, was found in the focus group to be a result of the view that SMM technologies facilitate, to a greater extent than other ICTs, rapid and easy interaction and feedback. Another reason for the consen- sus on the high capability of SMM for coordinating, at present, was the assumption that most coordination functions involve service providers (e.g., extension agents) working together with lead farmers, i.e., with lead farmers who, because they have AJIC Issue 28, 2021 21 Munthali et al. higher literacy levels and greater financial means than the average farmers, are likely to have access to the smartphones necessary for the use of SMM technologies. Ac- cording to a focus group participant: Social media applications are the medium of swift information exchange and facilitation at the moment. […] because of the infiltration of cheap- er smartphones [...] most lead farmers have this platform [WhatsApp], which makes them easily organise meetings, and solicit for assistance and information from each [agricultural] actor when need be. Meanwhile, the consensus on SMM technologies’ current capability to support co-creating was that the capability is only at an intermediate level. On this point, it was found in the focus group that the experts took into consideration that many rural farmers currently lack access to smartphones that support the use of SMM technolo- gies, and also that the generally low levels of literacy of farmers affects their ability to engage intensively with or on SMM technologies. In relation to these challenges with farmers taking advantage of SMM technologies, some experts pointed to alternative communication mechanisms, such as face-to-face meetings, being more appropriate than SMM, at present, for facilitating co-creation involving rural Ghanaian farmers. Moving to the factors contributing to the dissensus regarding the future intermedi- ation capabilities of SMM in disseminating, retrieving, and harvesting information, the variation in views was found in the focus group to be due to different levels of optimism among the focus group participants on rural farmers’ future access to smartphones and the farmers’ future literacy levels. The more optimistic respondents were confident in farmers’ increased access to smartphones and increased literacy over the next 10 years. Representing the optimistic view, one focus group participant argued as follows: [...] but it [the situation] is not static. Maybe in 10 years the youth will become more active farmers and be more inclined to use WhatsApp. However, pessimistic views were also expressed. For example, one focus group re- spondent stated: [...] right now it has been tagged that you [farmers] need a lot of money to get a smartphone, let alone the [poor] internet connectivity within rural areas. 22 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Another focus group participant added an additional pessimistic view: I am not even looking at the costs of [mobile data] bundles. Let’s look at how old the active rural farmers will be and what their educational level will be. When you talk about the farmers now, most of them are within the range of 30–35 and they will be 40–50 in the next 10 years. In the next 10 years we will be dealing with the same crop of farmers. Therefore, I do not expect to see significant changes in relation to their adoption of such new technology [SMM technologies]. 5. Discussion and conclusion The starting point of this study was that ICTs have the capacity to respond to in- formation- and interaction-related needs in Ghana’s agricultural extension service delivery. Through the inputs of a total of 15 varied experts in two rounds, we assessed the capability of nine types of ICTs operating in Ghana to support specific com- munication and networking functions (intermediation capabilities) that are required to facilitate AIS-based extension service delivery. In this section we highlight the results, specifically instances of positive consensus and of dissensus, in experts’ views on the intermediation capabilities of the ICTs identified, and discuss these instances with reference to the reasoning provided by the focus group participants and in the context of existing literature. Based on this analysis and discussion we point out opportunities for specific ICTs to support certain communication and networking functions that are required to facilitate AIS-based extension service delivery, as well as alternative scenarios. Finally, this section reflects on the validity of the Delphi-in- spired research design and highlights potential areas for future research. Positive consensus over technologies’ intermediation capabilities Below we discuss and identify opportunities for IVR and SMM technologies to support intermediation. IVR technologies The results show that experts reached positive consensus on the high capability of IVR technologies to support disseminating, retrieving, and harvesting information, at present, and to support matching actors to services targeted at rural farmers, also at present. These findings are congruent with previous research pointing to IVR technology having great potential to reach farmers directly (Dittoh et al., 2013; Mc- Namara et al., 2014). It is clear that many scientists, researchers, and practitioners view IVR technologies as being appropriate for supporting these specific commu- nication functions involving rural communities. This is largely because, as found in our focus group discussion and also as argued in the literature, these technologies are audio-based and thus fit rural farmers’ literacy levels, and these technologies are supported by the low-cost basic and feature mobile phones that most rural farmers can readily access (Aker et al., 2016; Dittoh et al., 2013; Schmidt et al., 2010). AJIC Issue 28, 2021 23 Munthali et al. SMM technologies We also found that there was positive consensus among experts on the high capabil- ities of SMM technologies to support coordinating between farmers and other agri- cultural actors at present. Therefore, in this case, it is also clear that various experts, including Fabregas et al. (2019), see opportunities for SMM technologies to support the coordination of activities involving farmers and other agricultural actors. Fur- thermore, according to the focus group and other studies, the consensus reported is due to SMM technologies enabling speedy information dissemination and immedi- ate feedback (Bennett & Segerberg, 2012; Munthali et al., 2018; Stevens et al., 2016). However, despite the full spectrum of SMM technologies’ features, the study found that these technologies only have the potential to support a certain type of coordi- nating—not as defined in Table 2. The focus group reported that SMM technol- ogies tended to be used by lead farmers to interact with agricultural stakeholders (other than farmers) on a one-on-one basis. Specifically, focus group participants indicated that lead farmers use SMM technologies for speedy one-to-one communi- cation with these other agricultural stakeholders to support aspects of coordination (e.g., organising meetings)—as Martin and Hall (2011) also report—as opposed to using the technologies to facilitate many-to-many communication to support, for instance, multi-actor (stakeholder) knowledge exchange and joint problem-solving. The SMM technologies were not cited as having the potential to facilitate virtual, multi-actor open and live communication for coordinated action to solve emerging problem. Thus, there are indications that the possibilities of leveraging SMM tech- nologies’ ability to facilitate multi-actor discursive spaces are currently limited in Ghana’s extension practice. Last, various experts were of the collective view that at present SMM technologies have only intermediate capabilities to support co-creating involving rural farmers and other agricultural stakeholders. Thus, the experts saw SMM technology as currently having neither high nor low capability to support the co-creating function, which re- quires multi-actor engagement and many-to-many communication. The focus group participants provided insights into factors contributing to this survey outcome. Cer- tain focus group discussants were optimistic about farmers’ educational levels and smartphone access increasing in the near future, thus allowing farmers to engage with SMM technologies that have the technical capacity to support engagement and communication for co-creating. Other focus group participants held a pessimistic view on the matter. 24 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Dissensus over technologies’ intermediation capabilities Experts did not reach positive or negative consensus on a number of propositions. They had a mix of positive, neutral, and negative views on these propositions. We now discuss and identify these instances of dissensus in relation to intermediation via IVR, USSD, and SMM technologies. IVR technologies There was dissensus among the experts in our study on whether IVR inbound tech- nologies have a higher capability than USSD technologies to support harvesting, at present. At the same time, and as already mentioned, there was positive consen- sus among the experts that IVR inbound technologies have the highest capability, among all the technologies identified (including USSD), to support this communi- cation function. A plausible explanation for these inconsistent findings is that experts judged IVR inbound and USSD technologies, comparatively, as possessing equal technical abilities to support harvesting, but when explicitly asked which technology had the highest potential to retrieve information directly from farmers in the Ghana- ian context, they identified IVR inbound technologies. Moreover, the existing liter- ature, the analysis in the previous section on positive consensus, and the focus group inputs all point to a finding that IVR inbound technologies are best suited to support direct harvesting of information from Ghanaian rural farmers as these technologies support audio content and operate on basic mobile phones (Aker et al., 2016). USSD technologies We found that there was no consensus among experts regarding USSD technologies’ capability, at present, to support farmers in retrieving information or matching actors (farmers) to services over other ICTs. This dissensus was based on the competing pessimistic and optimistic views of experts on farmers’ literacy levels. Meanwhile, the focus group and the literature point to IVR technologies having higher capacity to support these communication functions in comparison to other technologies. For example, Perrier et al. (2015) state that IVR technology is better-suited than USSD to reach literacy-constrained audiences. SMM technologies There was also dissensus among experts on the future potential of SMM technol- ogies to support disseminating, harvesting, and retrieving targeted at rural farmers, or networking and co-creating involving rural farmers and other agricultural stake- holders. This outcome could be attributed to the competing and diverging views of experts, as already mentioned above, on the future dynamics of farmers' access to, and use of, the mobile smartphones that support these technologies. AJIC Issue 28, 2021 25 Munthali et al. For the networking function specifically, the findings above related to SMM tech- nologies—and the dissensus found on the propostion that all the technologies iden- tified have low capability to support networking at present—lead to the conclusion that it is unclear which ICTs are best suited to support the funct ion. Unlike the aforementioned findings on experts’ views on the possibility of leveraging SMM technologies to support networking in the Ghanaian context, the Hansen study (Hansen et al., 2014) found that social media currently has high potential, in the European context, to support networking and co-creating. The difference be- tween the Hansen at al. (2014) findings and those of this study point to two issues that require consideration. The first issue is that the findings of the European-fo- cused study could largely be influenced by the context—a context in which farmers have higher literacy levels and easier access to smartphones than farmers in most Af- rican countries (ITU, 2021). The second issue is that at present, as suggested by this study’s focus group participants, networking intermediation capabilities are likely to be best-supported, in contexts such as those found in Ghana, by alternative commu- nication mechanisms such as conventional face-to-face meetings, which remain rele- vant in the functioning of agricultural systems where intensive interaction is required (Leeuwis et al., 2018; Materia et al., 2015). Such communication mechanisms have been cited (Molony, 2006) as trusted social networking methods that, in the African context, are the most appropriate modes of interaction given the prevailing literacy levels and types of mobile phones owned in rural agricultural settings (Dittoh et al., 2013). Validity of the consensus-building method It is necessary to reflect on the validity of the expert consensus-building method that we applied in this study. In line with Delphi’s general principles, our consen- sus-building method included more than one round of individual responses by ex- perts (Hasson et al., 2000). However, our approach deviated from a typical Delphi in that it did not require that the same experts be involved in each of the two rounds. For our method, each set of experts was engaged for the distinct purpose of one round, so that we fostered concurrent validity by aggregating the views of a small group of experts in the first round and then presenting these views, for affirmation and/or refutation, to a broader expert panel in a following round. We developed this approach so as to allow the views of the internal expert panel (communication and innovation experts) to be subjected to assessment by experts who are more engaged than the internal panel with the Ghanaian context, and so as to be able to establish consensus and dissensus among a wide range of experts. Furthermore, a Delphi study is typically considered valid based on the input of 16 to 60 experts (Hasson et al., 2000). However, lower numbers of experts have been reported in other Delphi stud- ies (Benitez-Capistros et al., 2014). It is our view that the inputs of the 15 experts in this study provide valuable insights because the design of the consensus-building method fostered concurrence validity. 26 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Future research Opportunities for future research can be identified from this study. Further research could shed light on ICTs’ application and role in supporting broader (AIS-based) ex- tension service delivery. This study is an experts’ assessment of the intermediation ca- pabilities of technologies identified in Ghana and provides insights into how experts view specific ICTs’ potential to support communication and networking functions relevant to AIS-based extension service delivery. Going forward, empirical research is recommended to establish how the technologies practically support extension ac- tivities involved in AIS-based extension service delivery, in a variety of contexts. Based on the findings of this study and related literature, it is probable that certain ICTs can currently support certain AIS-based extension activities. IVR technologies may support the broadcasting of knowledge and early warning alerts to rural stake- holders as part of coordination efforts in problem-solving, and enable the stakehold- ers to retrieve knowledge and other information (e.g., on weather, prices) (Aker et al., 2016). IVR technologies could also match farmers with service providers and suppli- ers, as well as allow for the harvesting of information from farmers and other rural stakeholders (Viamo, 2020) as inputs for systemic problem diagnosis. On the other hand, the technologies identified do not seem to have the potential to support mul- ti-stakeholder engagement for collaborative problem diagnosis and problem-solving. This is based on two considerations: (1) this study found no clarity on whether any of the ICTs identified support the networking function; and (2) SMM technologies currently have the potential to largely support only one-to-one communication and coordination. Furthermore, given this study’s finding that SMM technologies have only an intermediate capability to support co-creating, it is therefore unclear whether these technologies can fully support the combining of knowledge to facilitate inno- vation among agricultural stakeholders in extension practice. References Abdu-Raheem, K. A., & Worth, S. H. (2016). Suggesting a new paradigm for agricultural extension policy: The case of West African countries. South African Journal of Agricultural Extension (SAJAE), 44(2), 216–230. https://doi.org/10.17159/2413-3221/2016/v44n2a425 Abdulai, I., Hoffmann, M. P., Jassogne, L., Asare, R., Graefe, S., Tao, H. H., Muilerman, S., Vaast, P., Van Asten, P., Läderach, P., & Rötter, R. P. (2020). Variations in yield gaps of smallholder cocoa systems and the main determining factors along a climate gradient in Ghana. Agricultural Systems, 181, 102812. https://doi.org/10.1016/j.agsy.2020.102812 Adekunle, A. A., & Fatunbi, A. O. (2014). A new theory of change in African agriculture. Middle-East Journal of Scientif ic Research, 21(7), 1083–1096. https://doi.org/10.5829/idosi.mejsr.2014.21.07.21564 AJIC Issue 28, 2021 27 Munthali et al. Adolwa, I. S., Schwarze, S., Bellwood-Howard, I., Schareika, N., & Buerkert, A. (2017). A comparative analysis of agricultural knowledge and innovation systems in Kenya and Ghana: Sustainable agricultural intensification in the rural–urban interface. Agriculture and Human Values, 34(2), 453–472. https://doi.org/10.1007/s10460-016-9725-0 Agyekumhene, C., De Vries, J. R., Van Paassen, A., Macnaghten, P., Schut, M., & Bregt, A. (2018). Digital platforms for smallholder credit access: The mediation of trust for cooperation in maize value chain financing. NJAS – Wageningen Journal of Life Sciences, 86–87( July), 77–88. https://doi.org/10.1016/j.njas.2018.06.001 Ajani, E. N. (2014). Promoting the use of information and communication technologies (ICTs) for agricultural transformation in sub-Saharan Africa: Implications for policy. Journal of Agricultural & Food Information, 15(1), 42–53. https://doi.org/10.1080/10496505.2013.858049 Aker, J. C. (2011). Dial “A” for agriculture: A review of information and communication technologies for agricultural extension in developing countries. Agricultural Economics, 42(6), 631–647. https://doi.org/10.1111/j.1574-0862.2011.00545.x Aker, J. C., Ghosh, I., & Burrell, J. (2016). The promise (and pitfalls) of ICT for agriculture initiatives. Agricultural Economics, 47, 35–48. https://doi.org/10.1111/agec.12301 Allen, T., Prosperi, P., Cogill, B., Padilla, M., & Peri, I. (2019). A Delphi approach to develop sustainable food system metrics. Social Indicators Research, 141(3), 1307–1339. https://doi.org/10.1007/s11205-018-1865-8 Asiedu-Darko, E. (2013). Agricultural extension delivery in Ghana: A case study of factors affecting it in Ashanti, Eastern and Northern regions of Ghana. Journal of Agricultural Extension and Rural Development, 5(2), 37–41. Asiedu-Darko, E., & Bekoe, S. (2014). ICTs as enablers in the dissemination of agricultural technologies: A study in the East Akim District, Eastern Ghana. Asian Journal of Agricultural Extension, Economics & Sociology, 3(3), 224–232. https://doi.org/10.9734/ajaees/2014/7661 Bell, M. (2015). Information and communication technologies for agricultural extension and advisory services: ICT – Powering behavior change for a brighter agricultural future. MEAS Discussion Paper. https://meas.illinois.edu/wp-content/uploads/2015/04/ Bell-2015-ICT-for-Brighter-Ag-Future-MEAS-Discussion-Paper.pdf Benitez-Capistros, F., Hugé, J., & Koedam, N. (2014). Environmental impacts on the Galapagos Islands: Identification of interactions, perceptions and steps ahead. Ecological Indicators, 38(2014), 113–123. https://doi.org/10.1016/j.ecolind.2013.10.019 Bennett, W. L., & Segerberg, A. (2012). The logic of connective action: Digital media and the personalization of contentious politics. Information, Communication & Society, 15(5), 739–768. https://doi.org/10.1080/1369118X.2012.670661 Berkes, F., Colding, J., & Folke, C. (2003). Navigating social-ecological systems: Building resilience for complexity and change. Cambridge University Press. Bua, S., El Mejahed, K., MacCarthy, D., Adogoba, D. S., Kissiedu, I. N., Atakora, W. K., Fosu, M., & Bindraban, P. S. (2020). Yield responses of maize to fertilizers in Ghana. In IFDC FERARI Research Report. https://www.ifdc.org/projects/ 28 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Chu, H. C., & Hwang, G. J. (2008). A Delphi-based approach to developing expert systems with the cooperation of multiple experts. Expert Systems with Applications, 34(4), 2826–2840. https://doi.org/10.1016/j.eswa.2007.05.034 Cieslik, K. J., Leeuwis, C., Dewulf, A. R. P. J., Lie, R., Werners, S. E., Van Wessel, M., Feindt, P., & Struik, P. C. (2018). Addressing socio-ecological development challenges in the digital age: Exploring the potential of Environmental Virtual Observatories for Connective Action (EVOCA). NJAS – Wageningen Journal of Life Sciences, 86– 87(2018), 2–11. https://doi.org/10.1016/j.njas.2018.07.006 Davis, K. E. (2008). Extension in Sub-Saharan Africa: Overview and assessment of past and current models, and future prospects. Journal of International Agricultural and Extension Education, 15(3), 15–28. Directorate of Agricultural Extension Services of Ghana (DAES). (2011). Agricultural extension approaches being implemented in Ghana. https://www.g-fras.org/en/reviews- assesments/item/949-agricultural-extension-approaches-being-implemented-in- ghana.html Dittoh, F., Van Aart, C., & De Boer, V. (2013). Voice-based marketing for agricultural products: A case study in rural Northern Ghana. In ICTD ‘13: Proceedings of the Sixth International Conference on Information and Communications Technologies and Development: Notes (Vol. 2) (pp. 21–24). https://doi.org/10.1145/2517899.2517924 Doria, M. de F., Boyd, E., Tompkins, E. L., & Adger, W. N. (2009). Using expert elicitation to define successful adaptation to climate change. Environmental Science and Policy, 12(7), 810–819. https://doi.org/10.1016/j.envsci.2009.04.001 Fabregas, R., Kremer, M., & Schilbach, F. (2019). Realizing the potential of digital development: The case of agricultural advice. Science, 366(6471), 1–9. https://doi.org/10.1126/science.aay3038 Fielke, S., Taylor, B., & Jakku, E. (2020). Digitalisation of agricultural knowledge and advice networks: A state-of-the-art review. Agricultural Systems, 180(2020), 1–11. https://doi.org/10.1016/j.agsy.2019.102763 Gakuru, M., Winters, K., & Stepman, F. (2009). Innovative farmer advisory services using ICT. https://www.w3.org/2008/10/MW4D_WS/papers/fara.pdf Gbangou, T., Ludwig, F., Van Slobbe, E., Greuell, W., & Kranjac-Berisavljevic, G. (2020). Rainfall and dry spell occurrence in Ghana: Trends and seasonal predictions with a dynamical and a statistical model. Theoretical and Applied Climatology, 141, 371–387. https://doi.org/10.1007/s00704-020-03212-5 Gershon, I., & Bell, J. A. (2013). Introduction: The newness of new media. Culture, Theory and Critique, 54(3), 259–264. https://doi.org/10.1080/14735784.2013.852732 Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78, 1360– 1380. https://doi.org/10.1086/225469 GSMA. (2019). 618 active tech hubs: The backbone of Africa’s tech ecosystem. Mobile Innovation. https://www.gsma.com/mobilefordevelopment/blog/618-active-tech-hubs-the- backbone-of-africas-tech-ecosystem/ Hansen, J. P., Jespersen, L. M., Brunori, G., Jensen, A. L., Holst, K., Mathiesen, C., Halberg, N., & Ankjær Rasmussen, I. (2014). ICT and social media as drivers of multi-actor innovation in agriculture. In World Congress on Computers in Agriculture and Natural Resources (pp. 1–8). https://doi.org/10.13140/2.1.3549.8242 AJIC Issue 28, 2021 29 Munthali et al. Hasson, F., Keeney, S., & McKenna, H. (2000). Research guidelines for the Delphi survey technique. Journal of Advanced Nursing, 32(4), 1008–1015. https://doi.org/10.1046/j.1365-2648.2000.t01-1-01567.x Heeks, R. (2017). Information and communication technology for development (ICT4D). Routledge. https://doi.org/10.4324/9781315652603 Howells, J. (2006). Intermediation and the role of intermediaries in innovation. Research Policy, 35(2006), 715–728. https://doi.org/10.1016/j.respol.2006.03.005 International Telecommunication Union (ITU). (2021). Connectivity in the least developed countries: Status report. Kaushik, P., Chowdhuy, A., Odame, H. H., & Van Passen, A. (2018). Social media for enhancing stakeholders’ innovation networks in Ontario, Canada. Journal of Agricultural & Food Information, 19(1), 1–23. https://doi.org/10.1080/10496505.2018.1430579 Kilelu, C. W., Klerkx, L., Leeuwis, C., & Hall, A. (2011). Beyond knowledge brokering: An exploratory study on innovation intermediaries in an evolving smallholder agricultural system in Kenya. Knowledge Management for Development Journal, 7(1), 84–108. https://doi.org/10.1080/19474199.2011.593859 Kivimaa, P., Boon, W., Hyysalo, S., & Klerkx, L. (2019). Towards a typology of intermediaries in sustainability transitions: A systematic review and a research agenda. Research Policy, 48(4), 1062–1075. https://doi.org/10.1016/j.respol.2018.10.006 Klerkx, L., & Gildemacher, P. (2012). The role of innovation brokers in agricultural innovation systems. In Agricultural innovation systems: An investment sourcebook (pp. 221–230). https://doi.org/10.1787/9789264167445-19-en Klerkx, L., & Leeuwis, C. (2008). Institutionalizing end-user demand steering in agricultural R&D: Farmer levy funding of R&D in the Netherlands. Research Ethics, 37(3), 460– 472. https://doi.org/10.1016/j.respol.2007.11.007 Koutsouris, A. (2012). Facilitating agricultural innovation systems: A critical realist approach. Studies in Agricultural Economics, 114, 64–70. https://doi.org/10.7896/j.1210 Leeuwis, C. (2004). Communication for rural innovation: Rethinking agricultural extension. Blackwell Science. http://www.modares.ac.ir/uploads/Agr.Oth. Lib.8.pdf#page=20&zoom=auto,-161,323 Leeuwis, C. (2010). Changing views of agricultural innovation: Implications for communicative intervention and science. In F. G. Palis, G. R. Singleton, M. C. Casimero, & B. Hardy (Eds.), Research to impact: Case studies for natural resource management for irrigated rice in Asia (pp. 15–32). International Rice Research Institute. Leeuwis, C., Cieslik, K. J., Aarts, M. N. C., Dewulf, A. R. P. J., Ludwig, F., Werners, S. E., & Struik, P. C. (2018). Reflections on the potential of virtual citizen science platforms to address collective action challenges: Lessons and implications for future research. NJAS – Wageningen Journal of Life Sciences, 86–87, 146–157. https://doi.org/10.1016/j.njas.2018.07.008 Martin, B. L., & Hall, H. (2011). Mobile phones and rural livelihoods: Diffusion, uses, and perceived impacts among farmers in rural Uganda. Information Technologies & International Development, 7(4), 17–34. 30 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Materia, V. C., Giarè, F., & Klerkx, L. (2015). Increasing knowledge flows between the agricultural research and advisory system in Italy: Combining virtual and non- virtual interaction in communities of practice. The Journal of Agricultural Education and Extension, 21(3), 203–218. https://doi.org/10.1080/1389224X.2014.928226 McCole, D., Culbertson, M. J., & McNamara, P. E. (2014). Addressing the challenges of extension and advisory services in Uganda: The Grameen Foundation’s Community Knowledge Worker Program. Journal of International Agricultural and Extension Education, 21(1), 6–18. https://doi.org/10.5191/jiaee.2014.20101 McNamara, P. E., Dale, J., Keane, J., & Ferguson, O. (2014). Strengthening pluralistic agricultural extension in Ghana. USAID and MEAS. MEST. (n.d.). https://meltwater.org/ Ministry of Food and Agriculture (MOFA). (2007). Food and Agriculture Sector Development Policy. Government of Ghana. Misaki, E., Gaiani, S., & Tedre, M. (2018). Challenges facing sub-Saharan small-scale farmers in accessing farming information through mobile phones: A systematic literature review. Electronic Journal of Information Systems in Developing Countries, 84(4), 1–12. https://doi.org/10.1002/isd2.12034 Molony, T. (2006). “I don’t trust the phone; It always lies”: Trust and information and communication technologies in Tanzanian micro- and small enterprises. Information Technologies and International Development, 3(4), 67–83. Msuya, C. P., & Wambura, R. M. (2016). Factors influencing extension service delivery in maize production by using agricultural innovation system in Morogoro and Dodoma Regions, Tanzania. South African Journal of Agricultural Extension (SAJAE), 44(2), 248–255. https://doi.org/10.17159/2413-3221/2016/v44n2a431 Munthali, N., Leeuwis, C., Van Paassen, A., Lie, R., Asare, R., Van Lammeren, R., & Schut, M. (2018). Innovation intermediation in a digital age: Comparing public and private new-ICT platforms for agricultural extension in Ghana. NJAS – Wageningen Journal of Life Sciences, 86–87, 64–76. https://doi.org/10.1016/j.njas.2018.05.001 Nyamekye, A. B. (2020). Towards a new generation of climate information systems: Information systems and actionable knowledge creation for adapative decision-making in rice farming systems in Ghana. Wageningen University and Research Centre. Obeng, F. K., Gumah, S., & Mintah, S. (2019). Farmers’ perceptions of information and communication technology (ICT) use in extension service delivery in Northern Region, Ghana. Ghana Journal of Science, Technology and Development, 6(1), 21–29. https://doi.org/10.47881/126.967x Perrier, T., Derenzi, B., & Anderson, R. (2015). USSD: The third universal app. Association for Computing Machinery Conference December 1-2, 13–21. https://doi.org/10.1145/2830629.2830645 Qiang, C. Z., Kuek, S. C., Dymond, A., & Esselaar, S. (2012). Mobile applications for agriculture and rural development. World Bank. Schmidt, C., Gorman, T. J., Gary, M. S., & Bayor, A. A. (2010). Impact of low-cost, on-demand, information access in a remote Ghanaian village. ACM International Conference Proceeding Series, 8(2), 85–100. https://doi.org/10.1145/2369220.2369261 AJIC Issue 28, 2021 31 Munthali et al. Sein, M. K., Thapa, D., Hatakka, M., & Sæbø, Ø. (2019). A holistic perspective on the theoretical foundations for ICT4D research. Information Technology for Development, 21(1), 7–25. https://doi.org/10.1080/02681102.2018.1503589 Sigman, V. (2015). Agricultural extension policy forum: Ghana. Report on the Policy Forum sponsored by Ghana Directorate of Agricultural Extension Services, Ministry of Food and Agriculture; Modernizing Extension and Advisory Services; and Agriculture Policy Support Project. Sova, C., Chaudhury, A., Nelson, W., & Nutsukpo, D. K. (2014). Climate change adaptation policy in Ghana: Priorities for the agriculture sector. Working Paper No. 68. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Stevens, T. M., Aarts, N., Termeer, C. J. A. M., & Dewulf, A. (2016). Social media as a new playing field for the governance of agro-food sustainability. Current Opinion in Environmental Sustainability, 18, 99–106. https://doi.org/10.1016/j.cosust.2015.11.010 Swanson, B. E., & Rajalahti, R. (2010). Strengthening agricultural extension and advisory systems: Procedures for assessing, transforming, and evaluating extension systems. Agriculture and Rural Development Discussion Paper No. 45. World Bank. https:// hdl.handle.net/10986/23993 United Nations. (2020). Sustainable Development Goal 9: Investing in ICT Access and Quality Education to Promote Lasting Peace. https://sdgs.un.org/ Van Osch, W., & Coursaris, C. (2013). Organizational social media: A comprehensive framework and research agenda. In 46th Hawaii International Conference on Systems Sciences (pp. 700–707). https://doi.org/10.1109/HICSS.2013.439 Van Paassen, A., Klerkx, L., Adu-Acheampong, R., Dembele, F., & Traore, M. (2013). Choice- making in facilitation of agricultural innovation platforms in different contexts in West Africa: Experiences from Benin, Ghana and Mali. Knowledge Management for Development Journal, 9(3), 79–94. Viamo. (2020). Mobile surveys. https://viamo.io/services/mobile-surveys/ Vitos, M., Lewis, J., Stevens, M., & Haklay, M. (2013). Making local knowledge matter: Supporting non-literate people to monitor poaching in Congo. Paper presented to 3rd ACM Symposium on Computing for Development, January 11-12, Bangalore. https://doi.org/10.1145/2442882.2442884 Winch, G. M., & Courtney, R. (2007). The organization of innovation brokers: An international review. Technology Analysis & Strategic Management, 19(6), 747–763. https://doi.org/10.1080/09537320701711223 World Bank. (2012). Agricultural innovation systems: An investment sourcebook. https://doi.org/10.1596/978-0-8213-8684-2 World Bank. (2014). Mobile at the base of the pyramid: Ghana, Mozambique, Nigeria, Zambia. World Bank. (2017). Ghana agriculture sector policy note: Transforming agriculture for economic growth, job creation and food security. Zwane, E. (2020). The role of agricultural innovation system in sustainable food security. South African Journal of Agricultural Extension, 48(1), 122–134. 32 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Appendix: Inventory of ICT4Ag platforms identified Platform, services Constituent ICTs E-agriculture https://www.e-agriculture.gov.gh/ IVR inbound DaM Direct to farmers: SMM o E-farm – farmer audio agricultural information library Spa o Call centre – access to subject matter specialists o Farmer engagement platform Extension provision: o Web portal – repository of value chain actors, service providers, and stakeholders; and dissemination of new technologies and agricultural current affairs o E-extension – to collect farmers’ geo, bio, and crop data; and digitise field and pest and disease monitoring reports o E-subsidy – electronic registration of farmers with GPS integration and unique ID generator to facilitate efficient fertiliser subsidy distribution AgroTech SmartEx DaM Trader and outgrower schemes: DoM o Farmer discovery and enrolment with GPS integration – farmer registration, Spa and records of farm practices and credit activities o Farmer management – protocol of agent routine tied to key crop growth stages of farm operations to deliver timely support o Value chain and service linkages – access to agribusiness service providers and value chain actors o Information and knowledge repository – collection of technical information on crop production, processing, and marketing o Monitoring, evaluation, and learning – analyse farmer data to learn their needs and requirements, and track their performance. Additonally, tracking of agents’ activities through a dashboard Esoko https://www.esoko.com/ SMS push IVR inbound Direct to farmers: IVR outboud o Market prices and weather SMS pull o Agronomic tips DoM o Buy and sell marketplace – reach agent through call centre, sorted by location, DaM commodity, quantity and grade, and place offer that is SMS to buyer(s) Spa o Farmer Helpline call centre – access to agri-extension experts, market prices, and weather forecasts Extension provision: o Knowledge plus – knowledge respository templates o Insyts – digitised reporting templates and real-time analytics o Real-time message alerts Business-to-business services – for government institutions, NGOs, social projects: o Buy-and-sell marketplace – reach agent through call centre and place offer that is sent to farmers via SMS o Targeted marketing messages, announcements, and alerts o Polling and feedback o Knowledge repository templates o Digitised reporting templates AJIC Issue 28, 2021 33 Munthali et al. mFarms https://www.mfarms.org/solutions/ SMS pull SMS push Direct to farmers: DaM o Commodity and agri-input prices IVR o Precision agriculture outbound o M-Xtension – provides good agricultural practices Spa o Farmer to market – facilitates linkage between farmers, and input and ouput markets through human agents To extension providers, agro-dealers, seed producers, off takers: o Field agent management – agent database development and service provision/ activity tracking o Farm-level monitoring – farmer database development with farm mapping and farming activity Business-to-business services – for NGOs, FBOs, agro-dealers, logistics or warehousing companies, aggregators, processing companies: o Targeted advertising and messaging with instant delivery reports and dashboards o Targeted short surveys and polling for organisations (NGOs, input suppliers, etc.) to track their performance o Warehousing, and stock and sales tracking systems o Loan management systems o Fleet management systems Plantwise https://www.plantwise.org/KnowledgeBank DoM DaM For plant health and protection institutions and extension providers: SMM o Plantwise factsheet – repository of crop-based pest and disease management Spa advice o Plantwise data collector – digitised “prescription form” to record farmers’ biodata, plant health problem diagnosis and prescriptions o Plantwise plant doctors’ platform – pest and disease alert and knowledge- sharing platform Scientific Animations Without Borders (SAWBO) https://sawbo-animations.org/home/ DoM For extension providers: o Video library – extension information accessible as 2D, 2.5D, and 3D animations with voice overlay Complete Farmer https://www.completefarmer.com/ DaM Spa For farmers: o Builds and manages farms for individuals and provides real-time monitoring sensor and drone feed data through an online dashboard QualiTrace https://www.facebook.com/QualiTrace/ USSD For input buyers: o Anti-counterfeiting solution – enabling input buyers to confirm the authenticity of farm inputs by dialling the barcode of the purchased product through a USSD application prompt Akokotakra https://akokotakra.com/app DaM Spa For farmers: o Mobile and web-based management system that enables poultry farmers to record, monitor, and track their operations 34 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Ghalani https://www.facebook.com/ghalaniapp/ DaM Spa For farmers and agri-businesses: o Electronic management of farm records TROTRO Tractor https://www.trotrotractor.com/ USSD IVR inbound For farmers: o land preparation, planting, spraying, threshing, shelling, and transportation services Ignitia Iska https://www.ignitia.se/ SMS push Direct to farmer: o Location-specific weather updates – daily, monthly, and seasonal rain forecasts Farmerline https://farmerline.co/ SMS push USSD Direct to farmers: IVR inbound o Weather forecasts IVR o Agronomy tips – customised to location (GPS) and production stage outbound o Market prices DaM o Market place – access to farm inputs, water, solar energy, and financial services Spa – aggregated demand for inputs (type and location) for Farmerline to supply goods Business-to-business – off takers, input dealers, global food companies, government institutions, research organisations, NGOs, financial institutions: o Polling and short surveys o Engagement platform – send customised bulk messages o Data collection, management, and analytics – including farm-level monitoring, field monitoring, farmer profiling, and farm mapping through delivery o Building credit history to access advanced financial services through a mobile money payment platform o Mobile payments and savings platform o Plant health and vegetation change monitoring using satellites Moringa https://moringaconnect.com/ DaM Spa Extension provision: o In-house electronic data collection form and analytics, paired with GIS mapping system to monitor plant growth and trace moringa trees from planting to processing MTN MoMo (e-wallet) https://mtn.com.gh/momo/ USSD Direct to farmers: Mobile banking – payments, loans and savings, micro insurance Business-to-business: o Mobile banking – payments, loans and savings, micro insurance VOTO Mobile (Viamo) https://viamo.io/services/information-sharing/ SMS push USSD Direct to farmers: IVR o Mass-messaging on good agricultural practices outbound o Mass-messaging on price information and weather forecasts DaM Business-to-business: Spa o Mobile data collection – track field activities, monitor disaster response, report on stock levels, measure attendance, follow-up on referrals o Polling priorities, needs, and feedback from farmers or stakeholders o Mass-messaging to advertise and inform farmers or stakeholders AJIC Issue 28, 2021 35 Munthali et al. Farm Radio International https://farmradio.org/ghana/ IVR outbound Direct to farmers: IVR inbound o Access to messages, alerts, radio programme segments, and ability to leave SMS pull audio message SMS push o Commodity-based farm tips For radio stations and businesses: o Conduct surveys using audio messages o Farmer feedback on radio broadcasts o Uliza polling – voting by beeping/flashing to two phone numbers desginated for a “yes” or “no” response – listeners use basic phone to vote on IVR system, view results and recording. Number announced on radio station – call number and answer with number or record, flash call back o Automated callback or SMS with market information Manobi Africa https://www.manobi.com DaM SMS push Direct to farmers: Spa o Listing and precise georeferencing of farming plots o Marketplace (offers and demands) between large and small producers, and traders, buyers, and importers o Real-time monitoring of prices of agricultural products in wholesale and retail markets o Epidemic alerts, weather forecasts, calculation yields Extension provision: o Data collection – digitised monitoring data on agricultural operations during crop production Business-to-business: o Collaborative platforms – facilitate multi-actor engagement for cooperatives, associations, etc. o Data collection – surveys and advanced monitoring and evaluation o Inventory management system CocoaLink https://www.hersheytrading.ch/en_us/good-business/creating-goodness/cocoa- SMS push sustainability/cocoa-link.html DaM DoM Direct to farmers: Spa o Farmers can send in (photo) inquiries directly to experts and other farmers IVR o Farmers receive weekly messages (farming practices, farm safety, child labour, outbound crop disease prevention, post-harvest production, and marketing) from COCOBOD o Digital access to educational content – planting tips, correct input usage, and descriptions of best practices Extension provision: o Electronic farmer data collection Farmforce https://farmforce.com/ SMS push DaM Out-grower schemes and NGO (groups or cooperatives or exporters) – agent Spa o Crop growth stage, pest scouting and monitoring results, bio-data, input usage, and recording or estimating harvests / yields o Manage micro-loans and perform audits o Historical information of where crop came from at supermarket level o Tracking specific produce through the value chain o Bulk messaging to field staff and farmers o Electronic (field audit) survey 36 The African Journal of Information and Communication (AJIC) Intermediation Capabilities of ICTs in Ghana’s Agricultural Extension Delivery Freedom Fone https://archive.flossmanuals.net/freedom-fone/what-does-freedom-fone-do SMS pull IVR Direct to farmers: outbound o Sharing audio information with an audience – educational dramas, market IVR inbound information, recorded radio programmes, or short news items For businesses: o Polling – enable audience to vote on an issue using their phone o Collect SMS feedback from audience – updates about specific news events, alerts, or time-critical information o Get your audience to leave audio messages to share their opinion on a particular topic or make reports in their own language (IVR inbound) SavaNet https://savanet-gh.org/?q=content/what-we-do Spa DaM Direct to farmers: o Farmer group linkage to extension agents, ICT professionals, and researchers etc. (conference using mobile phone and portable external speakers) o Farm area mapping and analysis o Soil testing and analysis o Record keeping o Market access and weather forecasts SyeComp https://syecomp.com Spa Business-to-business and service to NGOs: o Farmland surveying o Farm mapping o Certification support and traceability GeoTraceability SMS push Extension service provision: DaM o Tailored business plans – processing field data and agronomic practices Spa to generate appropriate recommendations for business plans Business-to-business or project services: o Survey design tools and electronic data collection o Mapping production areas and relevant infrastructure o Traceability tools o Tailored messages to targeted groups of producers o Interoperating data from multiple platforms and data sources onto one database o Cloud-based data management structure to securely store and recall unlimited amounts of data Anitrack and Animat https://gh.linkedin.com/company/anitrack SMS push DaM Direct to farmers: Spa o Anitrack: a web application that enables animal identification, and health tracking of livestock using sensors (wearable tracking devices around the neck of the animal) to monitor vitals such as temperature and report when necessary sensors go off – sending a message to a registered veterinarian o Animat: a website for livestock producers to place their stock online for buyers to see AJIC Issue 28, 2021 37