1 Introduction

Planning, design and management of welfare services are complex tasks with fundamental impact on societal well-being. These activities can involve at different levels in the three mentioned steps national governments or local administrations, not-for-profit companies and civic society organisations. Historically, the preferred standard approach in the field, alternative to a fully centralised institutional management, has been that of a public administration developing the first two (planning and design) phases and choosing with tender the best candidate organisation to manage the welfare service.

This approach is, however, criticised and considered suboptimal when acknowledging that local administrations and civic organisations have complementary non-overlapping experiences, information and competences. More specifically, if it is reasonable to assume that competences on a specific service grow with management experience, civic organisations with an established past record in the field are likely to possess original and, not unfrequently, superior information and competences vis-à-vis the public administrations. The standard procurement process involving only the public administration in the first two (planning and design) steps is therefore likely to lead to a poorly planned and designed welfare service.

The welfare improving potential of an alternative approach based on co-planning and co-programming can be understood from the recent judgement of the Italian Constitutional Court in response to an application from the President of the Council of Ministers questioning the constitutionality of Umbria Regional Law (No. 2 of 11 April 2019, Article 5(1)(b)) which, in connection with community cooperatives, sought to regulate the methods of implementation of the co-planning, co-design and accreditation provided for by Article 55 of the third-sector code. The government in its question alleged that the regional law encroached upon the exclusive legislative powers of the state under Article 117(2)(l) of the constitution insofar as it broadened the range of third-sector bodies, exhaustively defined by the national law, entitled to actively participate in the national planning of measures of social utility.

In the motivation of its judgement against the Umbria regional government and in support of third-sector bodies participation to co-planning and co-design, the court said that the latter “are representative of the 'solidarity society', they moreover often constitute a widespread local network of proximity and solidarity, sensitive in real time to the needs that stem from the social fabric. Thus, they are able to provide the public body with both valuable information (otherwise achievable in a longer time frame and with organisational costs at its own expense) and an important organisational and intervention capacity. That often produces positive effects, both in terms of saving resources and increasing the quality of services provided in favour of the “society of need”.

Having in mind the above-mentioned issues and events, our paper aims to provide an original contribution from an economic perspective to the literature of co-design and co-planning, developed mainly in the public management research. The field closer to ours with an established tradition in this literature investigates the role of co-production of welfare services intended as an innovative approach that overcomes the dichotomy between a public entity designing and delivering the service, on the supply side, and private end users of the service, on the demand side (Brudney 1983; Brudney and England 1983; Parks et al. 1981; Sharp 1980; Pestoff 2009). The main idea is that participation of end users to the production of the service can contribute to improve it incorporating in the design itself an improved knowledge of end users preferences and needs. This literature identified direct and indirect benefits of co-production. The intuitive direct benefit is the improvement in the quality of public services that better capture knowledge and preference of users (Bovaird 2007a, b; Ostrom 1999). The indirect benefit is the positive externality of improved citizenship (Levine 1984; Wilson 1981) and increased social capital (Sicilia 2016; Cahn and Gray 2012).

Starting from this point, however, other authors (Alford 2014; Bovaird 2007a, b) progressively develop the idea that co-production should not just consist in forms of consultation and/or involvement of individual customers/beneficiaries of the welfare service, but should be extended also to a broader range of actors including non-governmental partners. The idea of co-planning and co-design departs from this approach and extends it to a multilevel governance setting where civic society organisations having past experience in managing the welfare service cooperate with government actors in planning and designing the service. This evolved co-production approach tend to develop where welfare services are less centralised and standardised and in a favourable political scenario such as in the analysed examples of child care welfare services in Sweden (Pestoff 2009) or in housing policy Canada (Vaillancourt 2009).

Within this field, an approach closer to ours is that of Sicilia et al. (2016) who start from the limits of an approach planned and designed by the public sector only and focus on a more complex pattern of interactions between the public sector, non-governmental entities and citizens (end users) discussing a case study in Lombardy related to the management of services for autistic children. The Lombardy model included a first stage where the regional authority involved in a consultative way end user families with a survey to understand better their perspective and needs. In the second stage, the same regional authority promoted a tender identifying a series of projects where local health authorities were asked to collaborate with local non-governmental entities to design and manage the service. Sicilia et al. (2016) highlight that involvement of families in all phases of the process reinforced their trust in the institution and in the process itself. They also emphasise how this move to a “citizen-capability” approach (Sen 1993) from a “service-dominant” approach (Osborne et al. 2013) requires good coordination capacity of the public manager.

Our paper aims to provide an original contribution to this literature by providing for the first time to our knowledge a simple and general theoretical framework comparing four different models dealing with the interplay between local administration and civic society organisations in co-planning, co-design and management of social services. In our theoretical analysis, we outline pros and cons of the four models in terms of activation of intrinsic motivations, monetary incentives, enactment of effort and competences of complementary actors and respect of competition and anti-collusion and corruption rules. We as well provide a simulation of the comparative performance of the four different models according to parametric assumptions on coordination costs and marginal contribution of each involved actor. We finally discuss how the empirical evidence from four pioneeristic case studies complies with our benchmark model and outline some policy suggestions.

2 The model

Imagine a social environment populated by n actors (Xi i = 1,…,n) where one of them is a public administration (XPA) and the remaining n-1 are civic organisations with non-overlapping complementary information, competences and experiences in a given welfare service.

We assume that the path for developing the welfare service is made of three steps (planning, designing and managing). For planning, we mean a process starting from the inquiry on the needs of a given community living in a geographical area, followed by the definition of the services that can satisfy those needs. For designing, we mean the design of the service identified in the first step as crucial to satisfy local needs. In the standard non-co-planning approach, this second step coincides with the definition of the tender characteristics that will be used to identify the winning organisation which will manage the service. The third step consists of the management and operation of the welfare service.

We assume that the final value of the welfare service is given by the quality of each of the three steps (planning, designing and managing), with quality being in turn determined by information and effort provided by participants in each step.

More formally, the value of the welfare service is given by the difference between service revenues (Y), affected by positive contributions of participants to it, and service costs (C), affected by coordination problems depending on the number of non-governmental organisations participating to the process (k)

$$V = Y\left( {P,D,M} \right) - C\left( k \right)$$

where P, D and M stand for planning, designing and managing functions,

$$k = n - 1,\;P = g_{P} \left( {\Sigma_{i} X_{i} \left( {{\text{IEC}}_{i} ,e_{i} } \right)} \right),\;D = g_{D} \left( {\Sigma_{i} X_{i} \left( {{\text{IEC}}_{i} ,e_{i} } \right)} \right)\;{\text{and}}\;M = g_{M} \left( {\Sigma_{i} X_{i} \left( {{\text{IEC}}_{i} ,e_{i} } \right)} \right),$$

with the quality of each of the X actors being given by their respective information/experience/competence (IEC) set and effort (e).

We in turn assume that effort is a function of the non-governmental actor intrinsic motivations (IM) (Deci and Ryan 2000) and expected monetary rewards (mE) so that

$$e_{i} \left( {{\text{IM}}_{i} , \, m^{E} } \right)$$

with mE = (1/k)/M where M is the total amount of financial resources allotted to the given service that we conventionally normalise to one.

We as well assume that the effort provided by the governmental actor is the same in all cases (without making it necessary to discriminate about the relative value of the different forms) and is conventionally set to zero (ePA = 0).

2.1 The standard model without co-planning

The standard way of operating without co-planning includes a government planning and designing decision in the first two steps and the identification of the non-governmental organisation in charge of managing the service with a tender in the third step.

As a consequence, under the standard non-co-planning approach the value of the welfare service is

$$V = Y \, \left( {P,D,M} \right)$$

where P = gP(XPA), D = gD(XPA) and M = gM(Xi(W)(IECi(w), ei(w))),with i(W) indicating the organisation winning the tender and coordination costs being equal to zero since k = 1 and C(1) = 0.

2.2 The open co-planning model

In the open co-planning model, all actors participate to all stages (and, in a consultative way, to the first two planning and designing stages) knowing that they will be rewarded by having a role in the management stage. The amount of effort produced, stimulated by monetary incentives, is, however, limited by the fact that each of the n – 1 non-governmental actors will receive a small part of the reward cake in the last stage, with the expected monetary incentive falling as far as the number of participants grows. As well, some work of coordination of the n-1 actors is required, and therefore, control and sharing of resources are not equally distributed and remains opaque within the n – 1 network.

The final net value created in the open co-planning model is therefore

$$V = Y \, (g_{P} (\Sigma_{i} X_{i} \left( {{\text{IEC}}_{i} ,e_{i} } \right)), \, g_{D} (\Sigma_{i} X_{i} \left( {{\text{IEC}}_{i} ,e_{i} } \right)), \, g_{M} (\Sigma_{i} X_{i} \left( {{\text{IEC}}_{i} ,e_{i} } \right))) - C\left( k \right)$$

with k = n – 1 ei (IMi, mE) and mE being a negligibly small value since \({\text{lim}}_{{k \to \infty }} \;m^{E} = 0\)

The problem of this model is therefore that of incentives since effort stimulated by monetary reward tends to zero as far as k goes to infinity. In such case, the value of the welfare service will solely depend on intrinsic motivations. Hence, under the extreme case of k large enough and IM = 0, the model is dominated by the standard non-co-planning approach.

Note as well that, even in the open co-planning model, activity in step 3 (management of the welfare service) requires coordination and therefore some forms of hierarchy within the group of the n – 1 civic organisations. If coordination remains a public good, free riding will be the optimal strategy as far as k grows. The network of the civil society must have a structured organisation with a coordination committee to solve the problem. The problem of free riding can arise also in the third stage of management.

2.3 The upstream and downstream tender co-planning model

In the upstream and downstream tender co-planning model, the government selects with an open tender the winning organisation that will participate to the first two steps represented by the co-planning and co-designing activities. We assume that, if the tender is efficient, the government will select the best entity (but only one entity) in terms of information, experience, competences and effort. In such case competition, rules are met and the winning organisation is rewarded for its first- and second-stage activity. Co-planning and co-designing receives maximum effort and information from the tender winner, but obviously no contribution from the other excluded actors of the social environment.

The tender is also used to select the best organisation to manage the service in the third stage.

As a consequence, the total value produced is

$$V = Y \, \left( {X_{PA} , \, X_{i(w1)} \left( {{\text{IEC}}_{i(w1)} ,e_{i(w1)} } \right), \, X_{i(w1)} \left( {{\text{IEC}}_{i(w1)} ,e_{i(w1)} } \right), \, X_{i(W2)} \left( {{\text{IEC}}_{i(w2)} ,e_{i(w2)} } \right)} \right) - C\left( k \right)$$

where w1 and w2 indicate the two different identities of organisations working in the first two stages and in the third stage, respectively, and C(k) = 0 since also here k = 1

The total effort in the three steps is given by the effort of the non-governmental organisation winning the tender for the given stage plus that of the public administration. If the monetary incentive is important, the number of participants large enough and coordination costs are high, and the maximum effort of an individual winner at each stage is higher than the effort provided in the open co-planning model of Sect. 2.2. If the total number of non-governmental actors is low, their intrinsic motivations are high and coordination costs are low, the open co-planning model can be preferred, while the opposite occurs when intrinsic motivations are low.

2.4 The downstream tender co-planning model

In the downstream tender co-planning model, the first- and second-stage processes are open to everyone in a consultative way, while the selection of the service manager in the third stage is performed with a competitive tender. However, IEC and effort provided by each organisation are not optimal since their first- and second-stage roles are only consultative and they know that they will have only a limited probability of being winner in the third-stage tender.

The model is perfectly compatible with competition rules in this case since the managing actor in the third stage is selected with a tender.

The value created by this model will be

$$V = Y \, (g_{P} (\Sigma X_{i} \left( {{\text{IEC}}_{i} ,e_{i} } \right)), \, g_{P} (\Sigma X_{i} \left( {{\text{IEC}}_{i} ,e_{i} } \right)), \, X_{i(W)} \left( {{\text{IEC}}_{i(W)} ,e_{i(W)} } \right)) - C\left( k \right)$$

with k = n − 1 in the first two (co-planning and co-design) stages.

3 Comparative performance of the four models

A first tentative comparison of the four models is presented in Table 1. The open co-planning model is the best if the number of non-governmental actors is high, and intrinsic motivations are high and coordination costs are low. It has, however, problems of compatibility with procurement rules. Compatibility problems grow if there is a likelihood that some non-governmental actors will be excluded from participation.

Table 1 Comparative analysis of the four models
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The second model is the most consistent with procurement rules, but is much poorer in terms of activation of system skills.

The third model is compatible with procurement rules and more effective if participants to the first and second stage are in large number and intrinsically motivated, but remains dominated by the open model as far as increasing the number of actors to the final stage adds up to the quality of the service.

4 Simulation

To compare the effects of the four different models, we conveniently assume a unit contribution to the final output value of the service from each the three inputs: (1) IEC (information/experience/competence), (2) intrinsic motivations and (3) effort affected by monetary incentives.

We as well assume additivity within and between the three phases so that the final output value is the sum of actors’ contributions in the three (planning, designing and managing) stages. The crucial parameter for our simulation is the hypothesis on the marginal contribution of each actor to the venture. Under the most optimistic case of this benchmark scenario, we are assuming an orthogonal contribution where the marginal effect of each new actor has a 100 per cent weight (pure additivity).

Based on these parameters in our benchmark scenario with zero coordination costs, the advantage of involving non-governmental actors in the three phases is striking and the open model dominates the other three, followed by the downstream tender and the upstream/downstream tender model (Table 2). In the sensitivity analysis presented in Fig. 1, we see how this advantage falls as far as coordination costs grow. It is, however, only when coordination costs amount to above 70% of the benefits of adding new actors that the open model loses its leadership in favour of the upstream/downstream tender model.

Table 2 Welfare service values in the four models with zero coordination costs
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Fig. 1
figure 1

Comparative performance of the four models under changing coordination cost and orthogonal (100%) marginal contribution

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In the simulations that follow, we relax the assumption on pure additivity of the contribution of non-governmental actors and assume that each of them contributes only for an additional 50 per cent to the final outcome. The underlying and more realistic assumption is that there is partial overlap of information, competence and experiences among the different non-governmental actors. In this case, the open model loses its leadership just before coordination costs attain 60 per cent level (Fig. 2) while, under a more drastic scenario where the marginal contribution of each new actor is cut to one-third, the threshold level of coordination costs where the open model loses its leadership is just below 30 per cent (Fig. 3).

Fig. 2
figure 2

Comparative performance of the four models under changing coordination cost and (50%) marginal contribution

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Fig. 3
figure 3

Comparative performance of the four models under changing coordination cost and 33% marginal contribution

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The simulation is obviously very general, but gives the idea that the benefits of co-planning and co-designing can be eroded by two factors such as the limited marginal contribution of new participants in terms of non-overlapping knowledge and experiences and in terms of provided effort, on the one hand, and coordination costs of the team, on the other hand. We discuss more in depth how these coordination costs can be conceived and modelled in the section that follows.

5 Coordination costs

Without lack of generality, we can model coordination costs as the difference between the cooperative outcome and the Pareto dominated Nash equilibrium arising in typical social dilemmas such as the prisoner’s dilemma (for a classification of the different types see Daniel et al. 2005). The difference is always positive and obviously depends on the payoffs of the game. We as well know that in multiplayer prisoner’s dilemmas coordination becomes more difficult since the parametric interval of the prisoner’s dilemma gets larger with respect to the two bordering areas where the individual cost of choosing the cooperative strategy is too high or too low, and therefore, the dilemma disappears. To illustrate this point, Becchetti and Salustri (2019) consider a simultaneous two-player prisoner’s dilemma where players can choose between a cooperative and a non-cooperative strategyFootnote 1 and the choice of the cooperative strategy by one player creates an externality of (1/2)X in the other player, produces an intrinsic motivation benefit IM for the player adopting it and has the cost of C for each player so that the payoff matrix can be represented as follows.

  

Player 2

 
  

Cooperate

Do not cooperate

Player 1

Cooperate

X + IM-C, X + IM-C

(1/2)X + IM-C, (1/2)X

 

Do not cooperate

(1/2)X, (1/2)X + IM-C

0, 0

Under these assumptions, the dominant strategy for a “homo economicus” player that is a player maximising its own payoff is not cooperating and the Nash equilibrium is the pair of non-cooperation strategies yielding a payoff (0,0). Such equilibrium is dominated by the cooperative choice yielding X + IM-C in the interval in which cooperation costs are neither too low or too high—or (1/2)X + IM < C < X + IM).Footnote 2 This is because in such interval the NE outcome is dominated by the strategy pair where both players adopt the cooperative strategy yielding the following payoffs (X + IM-C, X + IM-C).

In this respect, coordination costs can be calculated as being the difference between the aggregate outcome in the cooperative and non-cooperative equilibrium that is 2(X + IM-C).

The interesting aspect of this kind of prisoner’s dilemma is that increasing the number of players not only makes the costs of non-cooperation higher, given that n(X + IM-C) is higher than 2(X + IM-C) when n > 2, but also extends the prisoner’s dilemma interval which becomes ((1/n)X + IM < C < X + IM). This implies that we are in the prisoner’s dilemma interval also for lower costs of cooperation.

6 Directions to overcome coordination costs: the role of networking alliances

The game-theoretical literature has formulated several proposals to solve the dilemma, thereby reducing coordination costs in our co-planning models where more than one non-governmental actor is involved. Among them is the pivotal role of a player signalling its reliability in choosing the cooperative strategy and paying a cost for it in the presence of non-cooperative choices of the other players. In an evolutionary perspective, the role of this player helps to converge to the cooperative equilibrium (Hilbe et al. 2014; Stewart and Plotkin 2013) and the pivotal player can win with its reputation the role of coordinator of large networks. The intuition of this solution is that trustworthiness is fundamental to solve the dilemma and the pivotal player by paying a cost and signalling its stance on the cooperative strategy even when other players do not cooperate builds a reputation of trustworthiness through game rounds. Alternative proposals to solve the dilemma relate to efficient punishment strategies for players deviating from the cooperative strategies. The simplest example can be tit-for-tat strategies that reduce the cost of punishment to a single period (Axelrod and Dion 1988). The limit of punishment strategies are that their credibility is limited when they are costly for punishers.

Other ways to foster cooperation are gift exchange strategies that trigger gratitude and reciprocity, thereby creating relational goods (Becchetti et al. 2012). In the presence of a high level of relational goods, the violation of the cooperative strategy involves the additional negative effect of the loss of the relational good, and therefore, the payoff matrix changes so that the set of cooperation strategies can become also the Nash equilibrium.

An experimented approach to reduce coordination costs is the creation of a memorandum of understanding undersigned by participants that can become a more binding “networking alliance”.

We can therefore define a networking alliance as a non-legally enforceable set of proposed tasks and strategies undersigned by the counterparts that indicate modalities of cooperation and make cooperation feasible and more likely, thereby helping to make the cooperative equilibrium an achievable focal point. The process followed to develop it starts by identifying the network of participants, their goals and the definition of win–win “multiwinner races” where all participants can benefit or not lose from the pact. More specifically, this implies the identification of areas of actions where the participation constraints of the different actors do not bind. To make an example of multiwinner races in study groups, cooperation is much more likely when studying for a university examination than when competing for a job offer for which only one vacancy is open. This is because in the first case an improved performance of the studying mate in the group does not reduce the likelihood of success of other mates as it occurs in the second example when they compete for a unique place. The ability of scrutinising objective functions of different non-governmental members to understand their payoffs and participation constraints in order to create multiwinner races (where gains are not univocally defined by monetary benefits but can also come from information/education achievement and or satisfaction of intrinsic motivations), and in making these two points compatible with the social goal of satisfaction of a given demand of welfare services, is a crucial point for the success of co-programming.

The networking alliance can be a useful instrument to pursue this goal.

A crucial issue when talking about a networking alliance is the difference between an alliance and a contract. The contract tries to regulate all possible contingencies, is enforceable for contingencies described in it and parties can be prosecuted for violations of its clauses, even though effectiveness of enforcement depends on the efficiency of the local justice. The problem of contracts is that they are typically incomplete (they cannot describe all possible states of affairs) and therefore cannot enforce respect of cooperation in all circumstances and in non-regulated “grey areas” of human interactions. A networking alliance does not try to regulate all possible contingencies while it indicates modalities of actions and goals to whom the parties should commit. It is effective whether parties stick to these modalities of action, thereby maintaining reciprocal trust. The alliance is therefore a coordination mechanism with the aim of stimulating mutual trust and therefore cooperating strategies if parties follow it, even though the same parties cannot be prosecuted for its violation.Footnote 3 This is why the networking alliance is more than a “cheap talk” whose impact on the likelihood of cooperative equilibria has also been demonstrated (Farrell 1987), can stimulate trust and trustworthiness and indicate the direction towards the focal point of the cooperative equilibrium, thereby significantly reducing coordination costs. The essential ingredients of a networking alliance are described in Table 3 in Appendix.

7 Discussion

Results of our simulations are obviously crucially influenced by model assumptions. The two main assumptions driving results are those on the marginal contribution of each new participating non-governmental actor, on the revenue side, and on the magnitude of coordination costs, on the cost side. This is why in Figs. 1, 2 and 3 we perform a sensitivity analysis on the relative dominance of the four different models when parametric values on these two assumptions (marginal contribution and coordination costs) vary.

The model without co-planning is dominated by the three co-planning models if planning and designing skills of the governmental actor are poor and can be significantly enriched by information, experience, competences and effort of non-governmental actors. This is always the case if we assume that designing and planning capacity is crucially influenced by managing experience and that non-governmental entities have superior managing experience than the governmental actor.

The benefits of co-programming are more clear if from the static uniperiodal approach of Sect. 5 we could move to a multiperiodal approach where welfare recipients needs and demand for welfare services evolve following a given law of motion, and information about it and about what is needed to satisfy it also evolves and is dispersed among members of the network. In such case, an open co-programming process, or at least the involvement of civic society actors by the local administration, is crucial to bridge the gaps between the evolution of the dynamics of local population needs and information and satisfaction of them (exactly as explained in the constitutional court judgement mentioned in Introduction), thereby creating more easily forms of social innovation (Vaillancourt 2009).

In a dynamic version of the model, we can as well assume that non-governmental actors participating to stage one acquire learning and networking skills. This increases their incentive to participate and their effort even when intrinsic motivations are low and the number of participants is high so that the expected monetary reward is low. The intertemporal perspective could therefore make the monetary incentive problem in the open model less binding.

Coordination problems in large networks can, however, arise in steps open to all non-governmental actors. If we assume that coordination costs are high, the open co-planning model does not work. More formally, if coordination costs are higher than the benefit of participating to the co-planning process, non-governmental actors decide not to participate to it. Coordination costs can be solved ex-ante if non-governmental actors have a form of coordinating structure or association with fixed charges and decision rules. The decisions of the coordinating team will not necessarily satisfy all members in the same way, but the coordination problem is solved.

In order to avoid violation of competition, the steps of the process open to participation must be open to all non-governmental actors. This is usually obtained with a “call of interest” addressed to all the potential actors for sitting at the first (co-planning) stage of the process. If this procedure is respected the limit of the open process is not violation of competition rules but lack of incentives that can lead some of the potential participants not to sit at the table.

We can wonder what are the policy measures that can address the trade-offs and dilemmas described in our theoretical framework. Ideally we would need something increasing participation of organisations of the civic society without increasing coordination costs. Imposing co-programming (that is, choice of at least one of the three co-programming models) can improve well-being if marginal benefits of participation are higher than costs of coordination, at the cost, however, of creating a trade-off between quality and timing. However, this point is not so clear-cut, since also the standard approach where the first two steps are entirely performed by the public administration can last for long. The issue of timing therefore can be properly solved by fixing deadlines to the process. In the presence of a clear advantage of participation over coordination costs, a policy measure imposing the choice of at least one of the three co-planning measures can be advisable.

8 A first exercise of classification of pioneering co-planning experiences into our taxonomy

The experience of co-planning is at its origins in Italy and it could be useful to try to reconnect the first qualified pioneering experiences with the models presented in our theory.

In this respect, our work can provide tools for the activity of the newly created observatory of co-planning good practices that can get inspiration by theoretical frameworks as ours to create a proper taxonomy of co-planning experiences in order to understand which models have more potential and are more likely to be replicable elsewhere.

To this purpose, we identify below four short case studies and classify them within our taxonomy presented in Table 1.

Standard no co-planning model

 

Patto di Rete e di Comunità® di Castegnato

The implementation process of the Community Network Pact of the Municipality of Castegnato was designed on the basis of a research carried out directly by the local administration (without any stakeholder participation) which identified urban regeneration and the development of youth sharing spaces as two crucial goals for local economic and social development

The definition of the object of intervention of the public administration was determined by the anticipation of the presumed latent requests from the beneficiaries of the intervention, more than from the satisfaction of requests directly expressed by community stakeholders

The starting point of the work was to search for the local creative abilities and to understand how the regeneration of an urban environment (identified by the local administration with a preliminary local mapping) could be capable to translate the creative contribution of young people, students and innovators in stable and effective local solutions

The extremely simplified work of this preliminary analysis from the local administration has led to the preparation of an action plan and a roadmap suitable for a closed and limited partnership where the only two invited participating organisations were NeXt Economia (a multistakeholder third level organisation) and a particularly active local Foundation (Cogeme) whose main activities were teaching soft skills and local redevelopment

The process has been formalised in a Community Network Pact that has taken on different characteristics in relation to the object of the regeneration (property or physical asset to be recovered and reactivated) and was left open to different time and context specific interpretations

On the basis of this experiment, three policy lessons can be drawn:

(1) there is an implicit and latent creativity in small municipalities, which does not express itself because it is fragmented and unidentified. Scouting through public calls for ideas open to young people, students and innovators can therefore be a booster of innovation;

(2) a strategic policy intervention on the management of public goods and those abandoned or to be revitalised can support the identification of the unique local characteristics (genius loci) on which to focus. If, on the other hand, intervention is just focused on asset regeneration, without a more comprehensive strategy also looking a projects involving human resources, the potential birth of ideas and projects is by far reduced;

(3) social and community innovation is made of strategic partnerships as well as open co-programming activities in which all local stakeholders are involved

 

Open co-planning model

 

Patto di Rete e di Comunità® di Gasperina

The overall process was originated by a not-for-profit entity, Il Sotterraneo who started a co-programming and co-designing programme at two different but intertwined levels

On the one hand, a preliminary investigation with the local public administration aimed at identifying the distinctive elements which prevented a participatory and inclusive policy aimed at the goal of local re-population in the last 5 years

On the other hand, a work of social investigation aimed at fostering the emergence of the distinctive features and drivers of the "decision to remain" (“restanza”) that could led could young people, the elderly and small local entrepreneurs to take the decision not to leave

The difficulty of the formally created Community Network Pact during the process was to link these two surveys which produced converging outcomes with a problem of false perception of the severity and emergency of the situation and a lack of awareness of the loss of traditions and crafts, which each year were reduced by 20% compared to the previous year

The co-programming worked at two speeds and at two levels (institutional and civil society), and led to the re-elaboration of the original problem (purely of a cultural nature) to a problem linked to the state of abandonment (of real estate and local relationships) by the families who had decided to stay and live in the buildings, and those who have decided to leave the territory at risk of depopulation

The work on social and environmental needs represented the most important part of the activity of the Gasperina Community Pact even if it required additional effort to mitigate the conflicts between the public administration and the local leading not-for-profit entity which represented an obstacle to the involvement and the participation of individual citizens

The absence of a significant number of companies and organisations participating to the planning activity created the problem of accelerating too much decision-making processes, thereby creating a bias towards the interests of a few participants

For this reason, the decision of setting up the Community Network Pact represented an element of cohesion necessary to include additional people and families within the network. The co-design process enabled the creation of the first project of Renewable Energy Community with social impact in Italy. The Renewable Energy Community will generate revenues that will help the process

In synthesis, the most important steps made possible the process where: (1) the identification of the operational strategy and sustainable development model of the community for the next 10 years (also going beyond the current administration in office and aggregating other 3 local administrative experiences); (2) the development of a participatory planning process for energy production and social sustainability of the community of Gasperina, linking the issue of abandoned buildings to the problem of energy poverty of some local families

 

Upstream and downstream tender co-planning model

 

Patto di Rete e di Comunità® di Montegiordano

The co-programming process started with an assessment of the integral sustainability of the Municipality and an in-depth study of the public policies implemented in the previous three years by the administration, in terms of the benefits perceived and generated within the community

With the input from the local administration, the process facilitator winner of the upstream tender held 14 individual meetings with some privileged witnesses of the local community, 4 multistakeholder focus groups with organisations and businesses that work or would like to work for the development of the Montegiordano area, and two co-planning meetings with the citizenship

From the multipurpose survey and the model of progressive Interdependence elaborated and implemented by the Local Community Development team, in addition to investigating the level of co-responsibility of citizens, two areas of intervention emerged related to local active ageing policies and tourist promotion of local excellences. These two strategic areas required the voluntary, active and responsible involvement of the recipients of support interventions by the public administration in the social and socio-health field, but they collide with the lack of local social animation structures, as well as a small presence of young participants

The element of co-responsibility was applied for the first time to the shared administration process by borrowing the concept of the Co-responsibility Educational Pact so far applied mainly within the world of formal education (regulatory reference: Decree of the President of the Republic 21 November 2007, n.235)

The activities developed in the area, and in particular those linked to the promotion of "Made In", were carried out with voluntary work of local stakeholders. The focus of the overall strategy was, on the one hand, on activating a generative welfare that rethinks services dedicated to the elderly population and develops active ageing indicators. On the other hand, on identifying the local excellences (the genius loci) in a cooperative key to support the flourishing of new tourist accommodation activities that can better connect the mountain and marine area of Montegiordano, which is a unique valuable characteristics of this geographical area, but also risks to create two distinct populations with separate specific interests. During the process it was deemed necessary to aggregate all the autonomous and informal social entrepreneurship formulas through a “community cooperative” legal entity born with the aim to strengthen the tourist and restaurant services of the two areas, as well as support the creation of new entrepreneurial activities

The open nature of the community and the participation of representatives of the non-profit and for-profit entities have ensured full sharing of the sustainable local development objectives, extending the field of intervention to neighbouring municipalities and actively involving the Union of Mountain Municipalities

The size of the local administration and its limited volunteer resources have made necessary

external support for the management of the various stages of co-programming and co-planning, placing a high risk on the continuation of the activities after the external intervention

 

Open co-planning model

 

Patto di Rete e di Comunità® di Siddi

The pact implemented within the Municipality of Siddi in Sardinia is represented by a grass-root co-programming process originated by the local youth council. The process started from the analysis of needs related to the development of community identity, through the implementation of the model of "Live in", experimented in other small Municipalities present at national level

The “Consulta” (local stakeholder assembly), together with other informal realities, represented the initial coordination group which made it possible to restrict the focus of interest of the Municipality to the sole shared management of a territorial community

The co-programming process turned out to be particularly complex due to the variety of interests represented in the coalition. An element of co-management of all the operational phases was included within the shared administration process, with roots in the multistakeholder partnership involved in the pact and entailing a complex and articulated civil society participation. The Community Pact of Siddi, in all its phases and by its nature, did not lend itself to being exercised at a single level, but was implemented in intergenerational dialogue and in the recognition, within the pact. Involvement and participation of voluntary organisations allowed to activate a mutual reinforcement mechanism with respect to the ability to mobilise the sustainable development strategies envisaged in the various interventions. The governance involved a rotation mechanism of coordination and loyal collaboration with thematic working groups that can co-manage development guidelines of the network for a limited period that varies according to the territories and a rotating mechanism that is managed with an assembly of the network to be included in the regulation of the Network and Community Agreement

The evaluation of the pact was also managed in a cooperative perspective, leading to the development of an impact co-evaluation model of the entire path implemented, through the verification and monitoring of the results. In particular, the impact of the network project was intended to improve the multidimensional well-being of the specific beneficiaries. To detect this change, a multidimensional well-being-oriented ex-ante and ex-post questionnaire was administered to the beneficiaries of the paths co-designed by the shared administration, aimed at investigating their conditions before and after the execution of the development idea of the community

The main risk factor in the process is represented by limits in the ability to generate economic value in the medium–long term for all the members of the pact

 

9 Conclusions

Welfare recipient needs evolve over time depending on their tastes and rapidly changing economic and social dynamics. In this complex framework, it is reasonable to assume that public administrations are imperfectly informed about them and that part of the related knowledge is captured by civil society organisations with experience and practices in the management of welfare services and daily contacts with service recipients.

This is why the recent literature (as well as institutions) has started to understand that the standard model where the public administration identifies the needs, plans and designs the service and, in a later step, identifies through procurement tenders the civil society organisation that can manage the service maximising its quality, is becoming obsolete.

In this paper, we provide three alternatives based on forms of total or partial co-planning and co-design such as (1) the open co-planning model where the public administration and a network of civic organisations cooperate in all of the three (planning, design and management) stages, (2) the upstream /downstream tender co-planning model where the public administration selects with a tender the civic society organisation that will work with her in all of the three stages and (3) the downstream tender co-planning model where the open cooperation approach works at the first two (planning and design) stages, while the management stage is executed by the organisation winning a tender.

With a theoretical framework we analyse pros and cons of the four different approaches identifying the key offsetting factors in the marginal contribution of each new participant (on the revenue side) and coordination costs (on the cost side). In the rest of the paper, we model more in-depth coordination costs using the standard game-theoretical approach of coordination failure in the prisoner’s dilemma and discuss some solutions to overcome it (cheap talks, pivotal players in an evolutionary perspective, punishment strategies, identification of proper win–win races). We finally identify in the definition of a “networking alliance” the intermediate approach between a contract and a fully rule-free solution that can increase the likelihood of cooperative equilibria.

In our final section, we examine data on the first pioneering co-planning experiences in Italy trying to classify them within our model taxonomy. We aim to create in this way an example of a process for a national observatory of co-planning experiences where the interplay of theories and experiences can lead to identify the best practices and co-planning models that can be disseminated and replicated with proper local adaptation in other parts of the country.

Our research aims to introduce, shed lights and stimulate researchers reflection around a new emerging topics. Further developments could investigate more in depth the issue from a dynamic perspective or model coordination costs with a different game-theoretical social dilemma perspective. The emergence and description of new co-planning and co-design best practices in the future can help to identify and discuss further potential solutions to the problem promoting further improvement in co-planning and quality of welfare services.