# Exploring the value of a multidimensional service innovation model for improving the design of digital agro-advisory services

Chloé Alexandre, Aurélie Toillier, Pim den Hertog, Sophie Mignon, Guy Faure

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Chloé Alexandre, Aurélie Toillier, Pim den Hertog, Sophie Mignon, Guy Faure. Exploring the value of a multidimensional service innovation model for improving the design of digital agro-advisory services. Journal of Agricultural Education and Extension, 2025, 21 p. 10.1080/1389224X.2025.2559593. hal-05480874

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Competence for Rural Innovation and Transformation

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# Exploring the value of a multidimensional service innovation model for improving the design of digital agro-advisory services

Chloé Alexandre, Aurélie Toillier, Pim den Hertog, Sophie Mignon & Guy Faure

**To cite this article:** Chloé Alexandre, Aurélie Toillier, Pim den Hertog, Sophie Mignon & Guy Faure (03 Oct 2025): Exploring the value of a multidimensional service innovation model for improving the design of digital agro-advisory services, The Journal of Agricultural Education and Extension, DOI: 10.1080/1389224X.2025.2559593

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# Exploring the value of a multidimensional service innovation model for improving the design of digital agro-advisory services

Chloé Alexandre<sup>a,b</sup>, Aurélie Toillier<sup>a,b</sup>, Pim den Hertog<sup>c</sup>, Sophie Mignon<sup>d</sup> and Guy Faure<sup>a,b</sup>

<sup>a</sup>CIRAD, UMR INNOVATION, Montpellier, France; <sup>b</sup>INNOVATION, Univ Montpellier, CIRAD, INRAE, Montpellier SupAgro, Montpellier, France; <sup>c</sup>Dialogic innovation and interaction, Utrecht, the Netherlands; <sup>d</sup>Montpellier Research in Management (MRM), Montpellier, France

## ABSTRACT

**Purpose:** This study explores the reasons for the unrealised potential of digital agro-advisory services in developing countries by analysing the difficulties encountered by advisory service providers who are digitalising their services.

**Design/Methodology/Approach:** We used a multidimensional model of service innovation to examine the changes that occurred in the advisory system as it underwent digitalisation and the manner in which a Burkinabe farmer organisation and their partners coped with these transformations. This model includes six dimensions that can be transformed during the service innovation process: the service concept, interactions with users, the partner network, the revenue model, the organisational delivery system, and the technological delivery system.

**Findings:** This study shows that the farmer organisation did not anticipate the multiple transformations implied by the digitalisation process. This had detrimental effects for the farmer organisation, including the disruption of its day-to-day activities, difficulties in ensuring the economic viability of the new digital advisory service, and an evolution of the advisory approach towards top-down supervision.

**Practical Implications:** This article highlights six dynamic capabilities that are essential for advisory service providers to successfully manage the development of a digital farm advisory service.

**Theoretical Implications:** Using a holistic model of service innovation is instrumental in comprehending the failures encountered by organisations developing digital agro-advisory services.

**Originality/Value:** This article adopts a new perspective to understand the failures of digital advisory services: the capabilities of advisory providers to holistically manage the digitalisation of their service.

## ARTICLE HISTORY

Received 23 January 2025
Accepted 8 August 2025

## KEYWORDS

Digitalisation;
multidimensional model of
service innovation; service
system; farmer organisation;
dynamic capabilities; Burkina
Faso

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# Introduction

Digital technologies are increasingly used in developing countries to inform and advise farmers (Aker, Ghosh, and Burrell 2016), but their full potential has not been fully tapped (Steinke et al. 2020). The promotion of digital technologies in developing countries has for a long time followed a linear process of technology transfer (Baelden and Van Audenhove 2015; Heeks 2002). As a result, the design processes for new information services remain too often ‘centred around specific technologies and informed by strong technological rationality’ (Steinke et al. 2020, 2), resulting in ‘design-reality gaps’ (Heeks 2002). In reaction, co-design approaches such as user-centred design (Bull et al. 2024; McGrath, Regan, and Russell 2024) or *ex ante* user readiness assessment (McCampbell et al. 2021) are put forward to better take into account the expectations and perspectives of users.

While such user-centred approaches are a major step forward in developing relevant digital agro-advisory services that are relevant for users, they tend to overlook the difficulties faced by agro-advisory service providers not only in designing, but also in developing and deploying digital agro-advisory services (Ortiz-Crespo et al. 2020). Digitalisation involves *the introduction of digital technological innovations into existing (organisational, industrial, societal) systems in such a way that changes how those systems operate* (Fielke, Taylor, and Jakku 2020, 1). The digitalisation of agro-advisory services can thus be seen as a service innovation process, which implies transformations at several levels. Such transformations can be a source of innovation, but they also constitute a disruption that service providers must be able to anticipate and manage, to avoid ending up weakened. We therefore assume that using a service innovation lens will help to identify the various transformations induced by digitalisation and the challenges it implies for agro-advisory service providers, therefore contributing to developing more viable services.

Due to the intangible and fuzzy nature of services, identifying the changes resulting in or generated by a service innovation – beyond transformations in physical objects – has been quite a challenge (Janssen et al. 2015). The model developed by Den Hertog, van der Aa, and de Jong (2010) seeks to fill this gap. It draws on the concept of ‘service system’, that can be described, following Spohrer et al. (2008) as a ‘*dynamic configuration of resources, including people, organisations, shared information (language, laws, measures, methods), and technology, all connected internally and externally to other service systems by value propositions*’.

Den Hertog, van der Aa, and de Jong’s (2010) model identifies six dimensions of a service system where changes can occur during a service innovation process: (1) the service concept, (2) user interactions, (3) partners, (4) the revenue model, (5) the organisational service delivery system and (6) the technological service delivery system. These dimensions are interconnected: a change in one dimension is likely to induce transformations in the whole service system (Den Hertog, van der Aa, and de Jong 2010). This model also identifies dynamic capabilities essential for service providers to manage these changes (Den Hertog, van der Aa, and de Jong 2010). According to this model, the service innovation process can be seen as a search process, during which organisations experiment with introducing changes in one or more dimensions (Janssen et al. 2015). However, service providers may
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have difficulties to manage these transformations, thus leading to failed innovation processes.

We therefore address the following question: How can a multidimensional conceptualisation of service innovation help to better grasp service providers difficulties to design, develop and deploy innovative digital agro-advisory services in developing countries?

In this paper, we explore the value of mobilising a multidimensional model of service innovation to analyse the various transformations (and associated challenges) that agro-advisory service providers must manage in order to digitalise their service.

# Material and methods

## Analytical framework

This section presents how a multidimensional model of service innovation can be used to explore how advisory service providers adjust to and undergo digital transformation. As mentioned above, Den Hertog, van der Aa, and de Jong (2010) built a model distinguishing six dimensions where service innovation can take place in a business: (1) a new service concept, (2) new customer (or user) interactions, (3) a new value system or new partners, (4) a new revenue model, (5) a new organisational service delivery system and (6) a new technological service delivery system.

The first dimension, ‘service concept’ or ‘service offering’ (Frei 2008) describes the value co-created by the service provider and the service user. Most service innovations are new ways to organise a solution to customers’ problems or needs, often achieved by combining elements of services existing individually or as part of broader services (Den Hertog, van der Aa, and de Jong 2010). For example, agro-advisory service providers can innovate by offering not only advice but a more integrated service offer, ranging from access to credit and inputs distribution to advice for agricultural products’ transformation and commercialisation.

The second dimension refers to ‘new interactions with users’.¹ Interactions between users and service providers are an important source of innovation (Den Hertog, van der Aa, and de Jong 2010). Innovation in user interactions can be induced by the use of novel technologies which transform the role users play in the creation of value, as extensively discussed by the literature on ‘customer-interface interactions’ (Den Hertog, van der Aa, and de Jong 2010). In the case of advisory services, interactions between service providers and farmers are crucial to produce specific solutions to farmers’ specific challenges (Cerf and Hemidy 1999; Ingram 2008). Such interactions can evolve by developing new interfaces, for example digital platforms and social media, both allowing bi-directional communication (Baumüller 2018; Munthali et al. 2018; 2021).

The third dimension ‘new partners’ reflects the fact that service innovations are increasingly developed by different partners, pooling complementary resources and knowledge (Chesbrough 2003) or ensuring different service functions which are combined to deliver the overall service (Chesbrough 2003). Service innovation success is often conditioned by partners’ ability to connect with networks of business partners, but also with users (Den Hertog, van der Aa, and de Jong 2010). This is also true for digital agro-advisory services, relying on inter-organisational partnerships, which
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include a wide variety of organisations to gather the resources and capacities necessary to develop the services and enable a continuous delivery (Alexandre, Toillier, and Mignon 2022; Kernecker, Busse, and Knierim 2021).

The fourth dimension refers to ‘new revenue models’. A revenue model is a part of the business model that explains different mechanisms of income generation and its sources. To turn new service concepts into successful innovations, service providers and their partners need to find appropriate revenue models, which can require considerable ingenuity (Chesbrough 2006; Johnson, Christensen, and Kagermann 2008; Paallysaho and Kuusisto 2008). Despite the diversity of funding sources (private or public funders, non-governmental organisations (NGOs), users) and mechanisms (direct invoicing, vouchers, competitive funds, subsidies), developing a viable business model for digital agro-advisory services remains a challenge in developing countries (Birner, Daum, and Pray 2021).

The fifth dimension refers to new ‘organisational service delivery systems’, i.e. new personnel, organisation and culture supporting the service delivery. This dimension makes it possible to identify changes in the organisational structure of the service organisation itself, its management approaches, interpersonal capabilities or team skills supporting the development of innovative services (Den Hertog, van der Aa, and de Jong 2010). Recent studies show for example that agricultural advisors are still questioning the specific skills and capacities that they would require to make the most of digitalisation (Ayre et al. 2019; Eastwood et al. 2019; Fielke, Taylor, and Jakku 2020; Klerkx, Jakku, and Labarthe 2019; Rijswijk, Klerkx, and Turner 2019).

Finally, the last dimension refers to new technologies used to deliver the service. In the case of digital agro-advisory services, examples of new technological solutions include call centres (Baumüller 2018; Ortiz-Crespo et al. 2020), decision support systems implemented as smartphone applications (Saito et al. 2015), digital platforms (Munthali et al. 2018), facilitation of farmer-to-farmer knowledge-sharing via participatory video (Van Mele 2011) or social networks (Mills et al. 2019; Omulo and Kumeh 2020).

This service innovation model puts forward that all dimensions are interconnected and should therefore be thought of in a systematic manner to ensure a coherent service innovation process. In this paper, we propose to use this model as an *ex post* analytical tool, to identify the transformations of the service system at two stages of the digitalisation process: during the international development project that enabled the development of the digital agro-advisory service (phase 1) and after its termination (phase 2). In both phases, we seek to identify the changes that were anticipated before the introduction of digital technologies (and thus implemented to adapt *for* digitalisation – cf first loop in Figure 1) and those that were not and happened as a result of the service digitalisation (and thus happened as an adaptation *to* digitalisation – cf second loop in Figure 1) We also seek to analyse the difficulties service providers met when implementing such changes.

## Methodology

To our knowledge, no studies have yet conducted a systemic analysis of the transformations undergone by advisory service providers in developing countries, during the digitalisation process of their service. We therefore conducted an exploratory case study (Yin
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<figure><img src="image_17.png" /><figcaption>**Figure 1.** Analytical framework. Source: authors, inspired from Den Hertog, van der Aa, and de Jong (2010).</figcaption></figure>
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2018) in Burkina Faso to produce new knowledge based on empirical evidence. Burkina Faso is a relevant country in which to conduct this case study, as it is characterised by a high demand for farm advisory services and a wide variety of existing DAAS (Tsan et al. 2019; Hien 2021).

## Case study description

The case study concerns a Burkinabe farmer organisation (FO) engaged in the production of organic cotton. This FO (subsequently referred to as the ‘Cotton FO’) digitalised its certification and advisory services for farmers over the course of a four-year international development project with an international NGO. However, the FO encountered difficulties during this process and the results did not fully meet its expectations.

The Cotton FO is a long-established and politically influential union of cooperatives. The organisation was established in 1998 and currently comprises over 9,000 cooperatives, which are grouped at the departmental, provincial and national levels (Coulibaly 2018). The FO has considerable financial resources, derived primarily from the sale of cotton (a principal cash crop in Burkina Faso) and its equity holdings in cotton companies. The FO employs approximately 150 individuals, including 15 technicians who oversee the organic and fair-trade cotton production programme at the FO’s headquarters and 35 advisors who work with organic cotton producers. The cotton FO initiated the development of the organic cotton programme in 2004 in collaboration with international non-governmental organisations and the national agronomic research centre of Burkina Faso.

The programme is based on two principal services: the agro-advisory service, which aims to train organic cotton producers in order to ensure compliance with organic production standards and to provide them with assistance in the management of their farms; and the certification service, which aims to collect data at different levels (plot, farm, producer group, national FO) that is necessary for the certification process. The cotton certification is based on an internal control system, whereby the FO is responsible for ensuring that the farmers adhere to the requisite organic and fair-trade production specifications. To this end, the FO initially devised a system of paper forms that enabled advisors to collate data from farmers.

Subsequently, the data were transcribed onto computers and analysed by technicians at the FO's headquarters. In 2015, the FO initiated the collaboration as part of a four-year international development project with the international NGO mentioned above. Among others, this project aimed at developing a digital platform to facilitate data collection, treatment and sharing for the advisory and certification services. The digital platform comprised two interfaces. The first, accessible on a digital tablet, enabled agricultural advisors to collect information from cotton farmers for the purpose of providing advice and facilitating certification of organic cotton. Information was gathered via a digital questionnaire. Aggregation and analysis of the data were conducted on a computer, with the second interface typically accessible to elected representatives of FOS and members of the NGO supporting them.

## Data collection and analysis

In order to trace the chronological transformations induced by and for digitalisation and their effects on the digital agro-advisory service system, a total of 44 interviews were
<figure><img src="image_19.png" /><figcaption>**Table 1.** List of interviewees. Source: authors.</figcaption></figure>

<table><thead><tr><th></th><th>Profile of interviewees</th><th>Number of interviews</th></tr></thead><tbody><tr><td rowspan="4">April to July 2018</td><td>Farmers</td><td>52</td></tr><tr><td>FO Elected representatives</td><td>3</td></tr><tr><td>FO Technicians</td><td>2</td></tr><tr><td>FO Advisors</td><td>19</td></tr><tr><td rowspan="2">August 2018 to December 2019</td><td>Farmers</td><td>10</td></tr><tr><td>FO Technicians</td><td>10</td></tr><tr><td>Total</td><td></td><td>96</td></tr></tbody></table>

carried out (see Table 1). From April to July 2018, interviews were conducted with elected representatives, technicians, advisors and farmers to ascertain the rationale behind the development of the new digital platform and the impact it has had on the roles and relationships between advisors and farmers. The term ‘technicians’ is used to refer to the technical team based at the FO’s headquarters. This team is responsible for a range of back-office functions, including the production of advisory curricula, training and management of advisors, accountability, communication, monitoring and evaluation, and so forth. Subsequently, from April 2018 to December 2019, we conducted interviews with FO technicians with the objective of identifying the transformations induced by digitalisation within the organisation and how the FO and its partners managed such changes and reacted to these transformations. To corroborate our findings, we also mobilised secondary data, including operational reports.

## Results

In this section, we present how the FO approached and managed the transformations induced for and by the digitalisation of its advisory service for organic cotton producers, first during its partnership with the NGO (phase 1, described in part 1); and then, after this partnership ended (phase 2, described in part 2).

### Transformations of the service system during the partnership between the FO and the NGO

The digitalisation process was initiated as part of an international development project, thereby effecting transformations in dimensions 3 (new partners) and 4 (new revenue model) (for an overview of the transformations of the service system during the partnership, see Figure 2).

The NGO proposed the development of a digital platform for the automated collection of data necessary for both the certification process and the monitoring of the project that funded the platform’s development. Some members of the FO expressed a preference for utilising the digital platform as a means of enhancing the advice provided to farmers. However, their opinions were not taken into account. The digital platform that was developed did not entirely align with the expectations of the FO as the information collected was not fed back to the producers to help them improve their agricultural practices. A technician of the FO interviewed explained: ‘*Currently, our system resembles surveys, the information collected is not fed back to the producers. The limitation of this scheme is that it is not participatory: we are simply creating a database for FO technicians*’
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<figure><img src="image_21.png" /><figcaption>**Figure 2.** Transformations of the service system during the international development project between the NGO and the FO. Source: authors.</figcaption></figure>
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and our partner. What is missing is individualised feedback to organic cotton producers'
The NGO and the FO thus found themselves in disagreement over the new service
concept to develop (dimension 1 of the service innovation model), which had not
been subjected to sufficient reflection.

The NGO selected the company to develop the platform and did not engage with the FO at any stage during the initial design process. The FO was not consulted with regard to the selection of hardware and software, nor was it involved in the design of the interfaces. 'Initially, we were not consulted. We faced a 'fait accompli'. The digital platform was already in place and there was no option but to use it' (Interview with a technician). The NGO provided the FO with two of its employees to deploy and use the digital platform, effectively altering the organisational delivery system (dimension 5).

Although the platform was primarily used for data collection to facilitate the certification process and project monitoring, the digital tablets employed for data collection from farmers were used by advisors during their visits to farmers, thereby signifying a technological transformation of the advisory service delivery (dimension 6 of the service innovation model).

This resulted in unforeseen consequences for the relationship between advisors and
farmers, as well as the advisory approach itself (dimension 2 of the service innovation
model). From the outset of the Organic Cotton programme, the responsibility for imple-
menting both the internal control system (for the fair-trade certification) and the advi-
sory service was borne by the advisors. The introduction of digital questionnaires led
to a shift in the mode of communication between farmers and advisors, which became
more akin to an interrogation. This resulted in the abandonment of a comprehensive
approach to understanding the reality of farmers. On average, advisors estimated that
they spent approximately 75% of their working time implementing the internal
control system, 20% on advisory activities, and 5% on other FO services, primarily
input distribution. Nevertheless, despite the limitations imposed by the NGO, some advi-
sors also used the digital tablets for advisory purposes. Some advisors downloaded docu-
ments from the internet (for example, technical production itineraries) or photographed
manuals for the purpose of self-training. Others employed their tablets to capture images
of farmers who had developed innovative production techniques, using these visual aids
during training sessions with other farmers. As one advisor observed, 'Sometimes farmers
are not sure to know important insects, I show them pictures I took with my tablet'. The
objective of the advisors was to enhance the farmers' knowledge, derived from a re-
appropriation of the FO's standard production recommendations, and to personalise
their training and discussions with farmers. Additionally, some advisors used photo-
graphs as a means of fostering stronger interpersonal connections with farmers. They
observed that this approach was particularly effective when farmers had achieved favour-
able cotton production outcomes. As a result of this approach, the advisor noted that the
farmer will often request to have a picture of their field displayed for other farmers.
Additionally, some advisors perceived that farmers exhibited greater trust in them due
to the real-time collection and synchronisation of data on digital tablets. The farmers
believed that the advisor could not alter the data collected once it had been recorded
on the digital questionnaire, despite this not being the case: 'I know that he can recall
everything I have said with the tablet. And he himself has put everything in there too
and he can't change it. So, no one can cheat' (interview with a farmer). This quotation
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demonstrates the limited understanding of the platform's functionality exhibited by farmers, which some advisors leveraged to encourage the adoption of specific practices: 'Sometimes, I tell a farmer that the tablet has told me that something is wrong when I see that the farmer wants to hide something. I walk around the plot and come back to him saying that the tablet is showing something wrong, and I ask him to explain it to me' (interview with an advisor).

## Transformations of the service system after the end of the partnership

The agro-advisory service system continued to evolve following the conclusion of the partnership between the cotton FO and the NGO (see Figure 3 for an overview). Upon the conclusion of the project, which spanned four years, the NGO was compelled to withdraw, resulting in the transfer of the digital platform to the FO. Henceforth, the FO assumed responsibility for the management of the digital service independently. However, neither the FO nor the NGO had formulated a comprehensive exit strategy for the partnership.

The FO was thus ill-prepared to engage with the firm that had developed the platform (dimension 3 of the service innovation model). Furthermore, the organisation encountered challenges in identifying a new, viable business model (dimension 4 of the service innovation model), given that the international development project accounted for approximately 80% of the organic cotton programme's costs. Upon the conclusion of the project, the FO was confronted with the challenge of sustaining these costs without having secured alternative sources of funding. From the perspective of the FO's accounting department, this posed a significant concern, as the FO's own resources would be insufficient to cover the operating costs of the digital platform, let alone the additional costs associated with the advisory and certification services: 'With the two or three years of crisis the cotton sector has gone through, our economic outlook is no longer good. Without external support, we will not be able to maintain in their current states the advisory and certification services, nor the digital platform' (interview with a FO technician).

Moreover, following the departure of the two employees provided by the NGO, the FO was compelled to rapidly develop new skills to manage the new services, thereby transforming once again the organisational service delivery system (dimension 5 of the service innovation model). The NGO provided training to FO members on how to manage the platform independently of its continued support. However, the training, which took place in the final months of the project, proved inadequate for the FO to assume responsibility for the new tool without difficulty. Consequently, the technicians of the FO's monitoring and evaluation department were tasked with the responsibility of managing the platform. The introduction of these new functions, coupled with the lack of familiarity of the other FO technicians with the platform, resulted in an increased workload for the monitoring and evaluation department, which found itself unable to cope. A member of the FO's department explained: 'All the technicians have been trained, but it is the monitoring and evaluation department that is called upon to provide support, which leaves us with insufficient time to complete our own tasks.' The remaining technicians allow only a week to resolve urgent issues, which frequently proves insufficient. This situation hinders our ability to progress with our own daily tasks. 'It is imperative that they learn to utilise this tool independently with minimal delay' (interview with a
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Phase 2:

Transformations of the service system after the international development project

<figure><img src="image_25.png" /><figcaption>**Figure 3.** Transformations of the service system after the international development project between the NGO and the FO. Source: authors.</figcaption></figure>
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technician). Notwithstanding the delayed integration of the novel digital platform, the monitoring and evaluation department enhanced its proficiency in digital technologies and acquired a more nuanced comprehension of the potential and constraints of emerging technologies: ‘*Our system not secure because the data are stored on the cloud and not on a server that is accessible only to the relevant parties and under their exclusive control. It is imperative that a more secure solution is devised that does not rely on cloud storage*’ (interview with a technician).

Furthermore, the digitalisation of their services enhanced the reputation of the cotton FO in the eyes of other FOs and even pivotal actors within the value chain, including cotton processing companies. Such companies sought the input of the FO in order to discuss the potential adoption of analogous technologies within their own organisations: ‘*There is a general trend towards digitalisation. The local cotton processing company approached us to ascertain whether they should adopt a similar approach, given the enhanced efficiency it would afford them. In the context of organic cotton, our organisation is at the vanguard of this field*’ (cotton FO technician).

Nevertheless, FO members considered that the potential of the digital platform and tablets could have been exploited to provide more effective advice to farmers. For instance, the functions and interface of the digital questionnaires could have been improved to facilitate more efficient data collection and analysis. The implementation of data sorting functions would have enabled advisors to access the information they required with greater expediency during their discussions with farmers. Furthermore, the advisory functions could have been enhanced by communicating to farmers the data stored on the platform, thus enabling them to adopt a reflexive view of their practices and improve them. Additionally, advisors highlighted the necessity to access digital training materials to reinforce their knowledge. Finally, some advisors expressed the desire to create an exchange platform to facilitate knowledge sharing between advisors, as well as with the FO's technical team.

## Discussion

Following the presentation of the contributions of the Den Hertog, van der Aa, and de Jong (2010) model of service innovation for the analysis of the digitalisation of agro-advisory services in developing countries, two potential applications of this model are discussed in order to assist innovative organisations in developing their reflexivity and in the management of the transformations of their service system.

### Contributions of a multidimensional model to the analysis of the digitalisation of agro-advisory services in developing countries

Despite the common perception that digital tools can enhance the relevance and performance of agro-advisory services in developing countries, a significant proportion of services continue to face challenges in meeting this demand and achieving long-term sustainability (Steinke et al. 2020). Consequently, studies have emphasised the necessity for the development of critical social science studies to enhance comprehension of the underlying causes of this observed ‘failure’ of digital agro-advisory services (Cieslik et al. 2018; Mann 2018). Although the scope of this case study is limited, it nonetheless
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contributes new knowledge to this issue by exploring novel perspectives. Indeed, previous studies have explored the reasons for these ‘failures’ by analysing the limitations of the design approach employed by service providers (Ortiz-Crespo et al. 2020) or by identifying the shortcomings of the regulatory frameworks governing digital use (Tsan et al. 2019). However, to the best of our knowledge, no studies have yet analysed the difficulties encountered by agro-advisory service providers during the digitalisation of their service in a systemic manner. Indeed, there is a paucity of detailed understanding of how service providers envisage and manage these transformations, particularly in developing countries (Klerkx, Jakku, and Labarthe 2019). The following three points, derived from the case study, contribute to a deeper understanding of this phenomenon.

**_The digitalisation of agro-advisory services remains predominantly technology-centric, with insufficient attention paid to the organisational components of the service system._**

This case study illustrates that the digitalisation of the agro-advisory service under examination is still predominantly influenced by a technology-centric approach to innovation. The digitalisation process was primarily conceived as the introduction of novel technologies, with minimal consideration given to the potential for other transformations within the service system, whether at the back- or front-office level. This lack of anticipation had deleterious effects on the service system, including a disruption of the service organisation's routine activities, difficulties in ensuring the economic viability of the digital agro-advisory service, and an evolution of the advisory approach that became more akin to supervision.

The findings of this case study are in alignment with the conclusions of Heeks (2002) and Masiero (2016), who have highlighted that the organisational dimensions are frequently overlooked during the development of digital agro-advisory services in developing countries. The case study also provides insights into the reasons why the majority of agro-advisory services in developing countries encounter difficulties in providing farmers with targeted information and in facilitating their learning processes (Alexandre 2023; Baumüller 2018). This case study illustrates that the introduction of digital tablets had not been considered by service providers in terms of its potential to transform the roles of agricultural advisers and their relationships with farmers.

**_An unanticipated change of partners with a significant impact on the service system_**

The case study also illustrates the challenges resulting from the withdrawal of the international NGO, subsequent to the conclusion of the international development project that linked it with the farmer organisation. The withdrawal of this partner resulted in a deficit of financial and human resources (two dimensions of the service innovation model), which was not foreseen by the partners. This lack of anticipation gives rise to questions regarding the service provider's capacity to maintain the new digital advisory service over time. This observation is not unique to the case study conducted in Burkina Faso. A number of studies have highlighted that digital advisory services in developing countries are primarily financed by international donors and developed as part of short-term development projects (typically between three and five years) that connect local providers with international organisations (Tsan et al. 2019). It thus appears essential for advisory service providers to more effectively anticipate and plan for the
<figure><img src="image_28.png" /></figure>

sustainability of these services in the absence of external support, particularly in terms of financial and human resources. This study lends support to the findings of Fee (2012), which emphasise the importance of developing an exit strategy for international development projects in advance. In this regard, the multidimensional model of service innovation proposed by Den Hertog, van der Aa, and de Jong (2010) could be employed to identify the various components of a service that an organisation must be able to integrate in order to ensure the sustainability of a new service.

**Difficulties in developing digital agro-advisory services due to lacking dynamic capabilities of service providers?**

Ultimately, this case study suggests that the mixed or inconclusive results of digital agro-advisory services in developing countries can be attributed to service providers' lack of dynamic capabilities, which are essential for successfully managing a service innovation process. Dynamic capabilities are defined as the organisational capabilities that enable the integration, construction and reconfiguration of internal and external competencies in order to address rapidly changing environments (Teece, Pisano, and Shuen 1997).

The multidimensional model of service innovation used for this case study was further enriched by Den Hertog, van der Aa, and de Jong (2010) and Janssen, Castaldi, and Alexiev (2016; 2018), who identified the dynamic capabilities necessary to manage the six dimensions of service innovation. These capabilities refer to the capability to signal user needs and technological options; to conceptualise; to (un)bundle; to co-produce and orchestrate; to scale and stretch; and to learn and adapt.

Nevertheless, verification of this hypothesis requires identifying the dynamic capabilities necessary for service innovation. The existing conceptual frameworks of dynamic capabilities for service innovation, as exemplified by the works of Agarwal and Selen (2009); Janssen, Castaldi, and Alexiev (2016) and Kindström, Kowalkowski, and Sandberg (2013), have been primarily developed on the basis of studies conducted in Northern countries. Yet, it is acknowledged that innovation capabilities are contingent upon the sector and context in which the innovative organisation operates (O'Connor 2008; Tidd 2001). It is thus necessary to identify the nature and constitutive elements of dynamic capabilities in the specific context of agro-advisory services in developing countries. Future studies could therefore aim to identify the micro-foundations, namely the ‘distinct skills, processes, procedures, organisational structures, decision rules, and disciplines’ that constitute dynamic capabilities (Teece 2007, 1319).

**Managerial contributions: potential uses of the multidimensional service innovation model**

In addition to the thematic contributions that the Den Hertog, van der Aa, and de Jong (2010) model can make to the analysis of agro-advisory services digitalisation, two potential uses for service providers wishing to engage in an innovation process are identified.

Firstly, the model can be employed *ex post* to analyse the various components of the system that have undergone transformation during the innovation process and to identify the effects (anticipated or unanticipated; positive or negative) of the alteration in one of the system's components. Such an *ex post* analysis can assist in enhancing the
<figure><img src="image_29.png" /></figure>

reflexivity of service providers, which is a pivotal competency for innovation (Sundbo and Fuglsang 2002).

Furthermore, the service innovation model can be employed *ex ante* (i.e. prior to initiating the process of service digitalisation) to assist service providers in questioning potential transformations of their service system and the resources that must be allocated to manage these transformations. In the case of the agro-advisory services under examination, it is evident that not all advisory providers possess the requisite resources and capabilities to engage in this process. As Charatsari et al. (2020, 5) observe, ‘*although the change-promoting character of agricultural digitalisation seems indisputable, not all extension and advisory organisations are able to alter themselves*’. In this respect, the model offers a valuable decision-making tool for service organisations to assess an innovation’s execution complexity (Tacy 2020).

## Policy implications

This study suggests several points for reflection which we submit to the institutions supporting the development and operation of digital agro-advisory services, whether national governments, international donors, or private companies.

- To move beyond a purely technology-centric approach, funders could use the multi-dimensional model presented above before allocating funds, to analyse how advisory service providers approach these different aspects (change in service concept, user interaction, partners, business model), and whether they have the human and financial resources to manage the organisational changes induced by digitalisation.

- This study shows that farmer organisations digitalising their advisory services may struggle to enforce their data rights, as highlighted also by McCampbell et al. (2021). Currently, data rights directives and regulations in Africa are highly fragmented (Ayamga et al. 2021). Two courses of action could be considered: developing harmonised and binding legal frameworks on data rights, and raising awareness among digital agro-advisory service providers and their partners about related requirements.

- Digital agro-advisory service providers may lack dynamic capabilities to manage service innovation. Programmes could be funded specifically to strengthen these capabilities, including anticipating user needs, managing partner networks, scaling innovations, and fostering organisational learning.

- Finally, this study suggests that short-term project cycles without sustainable funding or exit strategies often lead to the collapse of services once donors withdraw. This calls for a reflection on alternative funding models for digital agriculture, favouring realistic and locally-owned business models. Explicit exit strategies and long-term financial planning could also become mandatory components of donor-funded digital extension projects.

## Note

1. The original model uses the term ‘customer’. In this study, we prefer to use the term ‘user’ rather than ‘customer’ as the farmers that are involved in the co-production of agro-advisory services do not always pay for the service.
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## Notes on contributors

Chloé Alexandre (PhD management science) is junior scientist at Cirad, the Centre of International cooperation in Agricultural Research for Development (Cirad). Her research focuses on multi-actor collaboration and impact evaluation of innovation processes in the Global South. She is particularly interested in the management of power asymmetries in participatory processes. She has co-published research articles in international journals including *Innovations – Journal of Innovation Economics & Management* and *Agronomy for Sustainable Development*.

Aurelie Toillier is senior scientist at Cirad, Innovation and Development in Food and Agriculture lab. Her research topics are learning dynamics, innovation processes and support models leading to sustainable farming systems. She explores in particular collaborative learning, capacities to innovate and managerial oversights in open innovation settings in support of agro-ecological transitions in Southern countries. She is currently hosted at FAO for supporting the implementation of a worldwide programme aiming at developing capacities for national agricultural innovation systems. She has co-published research papers in international journals and several books and book chapter.

Pim den Hertog is one of the founding partners at Dialogic, a research-based consultancy in Utrecht (The Netherland). Pim originally graduated as an economic geographer at Utrecht University and obtained his PhD with a thesis titled 'Managing service innovation' from the University of Amsterdam. He developed the 6-dimensional model of service innovation as well as the related model on dynamic capabilities for managing service innovation and published extensively on both. He participated in and led numerous national and international studies on innovation policies, innovation governance, service innovation and service-innovation policies as well as monitoring and evaluation studies of individual innovation instruments and organizations.

Sophie Mignon is Full Professor of Management at the University of Montpellier and a member of the Montpellier Research in Management (MRM) laboratory. Her research focuses on sustainability, knowledge management—particularly the factors that facilitate knowledge capitalisation—organisational learning, and exploration processes as drivers of innovation. Her current work centres on management innovation. She has co-authored numerous research articles in international journals, as well as several books and book chapters.

Guy Faure is posted at the European Commission (DG INTPA) as expert supporting EU research and innovation programmes such as the DeSIRA initiative (Capacity4dev | Connecting the Development Community (europa.eu)) and participating in policy dialogue (UN FSS, One CGIAR, etc.). Previously he worked at CIRAD as director of a research unit 'innovation and development' leading research on advisory services, innovation support services and impact of research with the perspective to contribute to the agroecological transition of food systems.

## Disclosure statement

No potential conflict of interest was reported by the author(s).

## Funding

This work was supported by the French National Research Agency under the Investments for the Future Program, referred as ANR-16-CONV-0004.

## ORCID

Chloé Alexandre http://orcid.org/0000-0001-6457-5661
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