Preferences, Institutions, and Policy Makers: The Case of the New Institutionalization of Science, Technology, and Innovation Governance in Colombia

1 Introduction

Institutions are fundamental for establishing the rules of the game and the objectives to be achieved in regard to a country’s social, growth, and development needs. Institutions also define incentives for agents and interest groups, who adapt their behaviour accordingly and take into account existing and potential market failures. The advance of science, technology, and innovation (STI) requires the development of appropriate institutions that transform the individual or specific preferences of some interest groups into collective results that solve the problems of society. However, preferences for the means and strategies with which to carry out this function differ among policy-makers, scientists, decision-makers, investors, and citizens because the perceptions of and perspectives on STI vary between the generators and beneficiaries of knowledge.

According to one definition, an institution “specifies the players whose behaviour is bound by its rules; the actions the players must, may, must not, or may not take; the informational conditions under which they make choices; their timing; the impact of exogenous events; and the outcomes that are a consequence of these choices and events. The game form is transformed into a game when players are endowed with preferences over outcomes” (Shepsle, 2010). Regarding STI, it is important to determine adequate rules and requirements along the entire value chain to transform the dependence on other countries’ knowledge generation into inputs for a knowledge-based society. These elements are the key to new STI institutionalization, taking into account preferences, institutions, and policy-makers. This study aims to support the institutionalization of new STI policies and governance in Colombia initiated through the creation of the Ministry of Science, Technology, and Innovation (MSTI).

Institutions are fundamental for the success of countries. Acemoglu and Robinson (2013) demonstrated that the arbitrary rules implemented by extractive institutions destroy a country both politically and economically. In contrast, inclusive institutions strengthen economic growth and development in the long run through the rule of law, which is based on legality, constitutionality, judicial independence, rights, and duties. The rule of law, in turn, stimulates economic processes, business, and investment by ensuring legal security and predictability, the autonomy and transparency of the legal system, and the protection and guarantee of property. These precepts are fundamental for good governance and must be considered in the formulation of new institutions for STI. In particular, transparency, independence, and rules that allow research and development (R&D) investments in the private sector should be promoted as key elements in creating new knowledge, technologies, and innovation offering an adequate rate of return and improvements in productivity and competitiveness (Brown & Martinsson, 2018; Impact Task Force, 2021; Kenny, 2020). In this study, we aim to address the challenges of developing appropriate institutions in the Colombian context.

The formulation of STI policy requires different instruments and tools, providing direct help to researchers and innovators and refining the enabling environment for scientific and innovation activities that generate different forms of technological, social, and institutional innovations. These innovations range from the incremental to the radical and from low-tech to high-tech, which implies stakeholders, networks, and the situations that allow learning, technology development, and adoption and diffusion (Chaminade & Padilla-Perez, 2014; Cunningham et al., 2013).

The government can support STI by managing and promoting economic growth and the modernization of the state to strengthen efficiency and effectiveness through decentralization. This strategy implies greater independence and transparency in public management to orient STI towards sustainable development and the creation and distribution of knowledge. That said, out of 38 countries in the Organisation for Economic Co-operation and Development (OECD), 15% do not have an MSTI, and among Latin American countries, 61% do not have an MSTI.

This study aims to highlight the main factors that can affect the new institutionalization of STI governance in Colombia by considering the preferences and role of policy-makers in operating the new MSTI. By adopting an empirical strategy that treats different agents as policy-makers and their preferences as a functional form, this study considers the appropriate policies for promoting STI in all economic sectors, increasing investment, and delivering results. This policy emphasis is justified because STI can increase production factors, improve efficiency by optimally allocating these production factors, and boost innovation rates, all of which are recognized as main forces in economic growth and development (Bekhet & Latif, 2017; Zaman & Goschin, 2010).

Thus, by studying the preferences of different stakeholders, this article aims to investigate new STI institutions in Colombia considering the importance of the adequate formulation and application of governance institutions to promote development and growth based on knowledge and technological change.

Institutions are the focus because understanding institutions implies understanding the complex causation and combinations of factors that make it possible to promote appropriate STI policy and instruments. This topic has received limited attention from previous studies, especially in developing countries. Additionally, this study focuses on transitions achieved through the creation of the MSTI, which is in line with the United Nations Conference on Trade and Development (UNCTAD) (2019). According to UNCTAD STI policy strategy, instruments, processes, and governance require policy harmonization and strategic coherence between STI and many related policy improvement issues.

However, policy experimentation with new types of STI policies is necessary to guarantee compliance with current policies to meet global challenges, where institutions play an important role in addressing effective STI processes (OECD, 2022b; UNCTAD, 2019). Hence, this study performs a series of simulations to determine the factors that could influence new STI institutionalization in the Colombian context.

The main contributions and scope of this research are as follows: i) This analysis contributes to both knowledge and the literature by focusing on institutions and the significance of governance institution quality in promoting STI. ii) It attempts to capture the STI policy preferences of different stakeholders who promote development and economic growth in Colombia.

This article starts with a brief theoretical overview of institutions and preferences related to STI from a review of the theoretical and empirical literature. It then presents the literature review and continues with the data and methods used in this study. Next, the main results are discussed. Finally, tentative conclusions are drawn.

2 Literature Review

This section provides a literature review of two approaches, theoretical and empirical, to determine the importance and relationships between institutions and policy-makers within the STI framework.

3 Methods and Data

Regarding preferences and institutions, the most recent literature (Persson & Tabellini, 2000) includes, among the main stability factors, agents' level of knowledge of a particular issue and the good management and efficient allocation of scarce resources by policy-makers. The most general models represent preference functions considering the existence of two possible policy-makers in the context of resource management.

This study follows the indicators and variables proposed by the 2015 Frascati Manual developed by the OECD (2015) for investments in R&D that comprise creative and systematic work undertaken to increase the stock of knowledge – including knowledge of humankind, culture, and society – and to devise new applications of available knowledge. Three types of activities are covered: basic research, applied research, and experimental development.

According to Ricyt (2018), the Latin American context uses variable investments in science, technology, and innovation activities (STIAs). Such activities include innovation activities, scientific and technological services, support for scientific and technological training, R&D and administration, and other support activities. These two variables make it possible to assess simulations based on the differences between R&D and other STI investments, taking into account the fact that OECD countries measure only R&D. Additionally, the variables can be used to analyse two scenarios.

For simplicity, it is assumed here that there are three types of STI policy-makers who manage and control two decision variables: STIAs and topics related to R&D. One of these representative agents is a business maximizer of resources, i.e., a businessperson-entrepreneur. Another is a politician, and the last is a scientist, i.e. an academic manager and expert on STI issues. The characteristic equation of the preferences of the businessperson-entrepreneur has the following structure:

Regarding institutions, the recent literature includes various stability factors in the management of policies related to spending on STIAs and resources allocated for R&D in countries. The management of decisions is formalized based on the preferences and inclinations of each representative agent given the decision variables. Equation (1) defines the parameters and standard weights to determine the weight of the variables in each of the possible decisions of the businessperson. ʆ b represents the preferences of the businessperson-entrepreneur. In terms of probabilities, ½ represents the weight for the importance that each variable has in the decision of the representative agent. For the case of Ω , which represents investments in STIAs, this policy-maker gives an equal valuation to the difference between R&D resources ψ and the average that was assigned to that expense during the analysis period ψ ̅ .

For the scientist-manager, the preference is as follows:

Here, ʆ c represents the preferences of the scientist-manager, Ω represents investments in STIAs, ψ represents investments in R&D, ψ ̅ represents the mean rate of investment in R&D, and k is an adjustment parameter to avoid possible high deviations from the average of R&D spending. This parameter must be within the range 0 < k < 1 to allow adjustments. R&D spending is determined by the following expression:

Equation (3) shows the importance that spending on R&D should have for the preferences of policy-makers ψ . The variable ψ ̅ represents the average of the expenditures on R&D in the analysis period. The parameter β represents the adjustment to be made between the difference in spending on R&D activities Ω and the expected value for R&D spending Ω e in the following periods and the possible execution.

The model assumes that the control variables determined by STIAs and R&D are the main policy instruments for policy-makers in STI. It should also be assumed that in the short term, the policy-maker is elected, thereby representing different interests given the policy-maker’s preference function. In this way, the difference in the preferences of the two representative agents is specified by the functional forms set in equations (1) and (2) for the businessperson-entrepreneur and the scientist-manager, which allows us to establish the preferences that each representative agent has for STIAs or R&D.

Solving the main interactions determined by equations (1) and (3), the relevant equation is expressed as follows:

When solving, the relevant relationship is shown in equation (5):

Equation (5) tells us that the businessperson-entrepreneur is more interested in control over current and future STIAs. In this sense, the equation additionally warns that R&D may be given little consideration in governance by this policy-maker.

For the scientist-manager, solving the interactions given by equations (2) and (3), the following relationship is specified in equation (6):

The relevant relationship is shown in equation (7) as follows:

According to equation (7), which shows the different relationships for the scientist-manager, this representative agent is more concerned with the impact that the two variables, STIAs and R&D, may have on the economy as a whole, without loss of generality. This policy maker is interested in having an R&D rate that, to the greatest extent possible, does not deviate from its natural rate and that does not side-line the effects or implications of STIAs in regard to economic growth. The question is how to determine the optimal rates given the preferences of each policy-maker in terms of the contribution of each activity to growth.

The STIA rate for the businessperson-entrepreneur is determined based on equation (5) by solving with respect to the control variables. Carrying out the respective operations yields Ω b , which represents the optimum rate for the businessperson‒entrepreneur given her preferences.

When deriving with respect to Ω ,

By carrying out the respective operations, the optimal STIA spending rate is obtained for the businessperson:

The STIA rate for the scientist-manager is obtained based on equation (7) operating with respect to the control variables. Ω c represents the optimum rate for the scientist-manager given her preferences.

When deriving with respect to Ω ,

By operating and solving, the optimal STIA spending rate is determined for the scientist-manager:

Here, Ω p represents the optimum rate for the politician given her preferences, with the results appearing in terms of the effect of the main decision variable on the policy measures to be implemented.

Using the same assumptions for the preferences of each policy-maker, one can determine the main relationships and outcomes for the politician as a central planner.

This document uses the time series of STI spending generated by the Administrative Department of STI (Colciencias) from 1968 to 2018. We use data published by the National Planning Department, Cotte and Andrade, 2019, and the World Bank for Colombia to capture investments in STIAs and the R&D series. The variables used in the various techniques and the time periods were selected based on the availability and reliability of the available data. These data were the basis for making the projections and estimates for each scenario based on the preferences of policy-makers for a projected period of 19 years.

For the simulations and their respective projections, the time series are used to predict the behaviour and the main results. STIAs and R&D are taken as the main control variables, given that they are the main indicators that an MSTI would manage. The general structure in time series for predictions takes into account the following general structure (equation (10)):

The values of the past are taken into account to make the future predictions of each policy-maker based on the data of the previous institution that was in charge of managing the variables of STI, particularly those related to STIAs and experimental R&D.

The predictions of the following successive periods satisfy the following structure (equation (11)):

Therefore, the following is assumed (equation (12)):

Similarly, for the following successive periods (equation (13)),

4 Empirical Results and Discussion: Simulations for Policy Makers

To conduct the simulations, we follow the methods explained in the previous section based on equations (8) and (9). Additionally, the most recent and robust methodology developed by Cotte and Andrade (2019) is used. The different characteristics of the variables are analysed. Furthermore, the fluctuations in the time series are used as a study instrument, employing the trends, deviations, periodicity, duration, amplitude, variability, and general behaviour of the data reported by the Colombian Observatory of Science and Technology (2019).

Table 1 shows the main estimates for each of the central planners and their contribution to the decision variable in the management of STI policy. According to the simulations, the results show great variability in terms of the possible behaviour of the main control variable in reaction to the policy.

The simulations for the different policy-makers over 19 periods show that the variables STIAs and R&D, which are the variables to be managed by the businessperson, politician, and scientist-manager, lead to different results. Without loss of generality, the optimal results are obtained by the scientist-manager because she shows great interest in STIAs and the effective allocation of R&D resources. In contrast, the politicians and businessperson show negative results for some periods, generating losses and inefficiency in resource allocation. According to Brookes et al. (2017), the integration of science with the common good and society and the achievement of a more influential position for science require a scientific manager and leader to support change for the better worldwide.

Moreover, researchers with management and leadership skills aim to organize better projects. They also aim to more effectively complete the adequate transfer and application of project results and to establish appropriate strategies to promote new knowledge, technology, and innovation. Furthermore, they aim to foster innovation and collaboration among different stakeholders, such as those from the government, the productive sector, universities, society, and research centres. Finally, they aim to employ others from national and organizational contexts and motivate them to achieve project objectives (Jason & Macnaghten, 2011; Pozenel, 2018).

However, identifying a policy maker with a scientist-manager profile is not always possible because different power relations or political interests can influence the selection. Thus, it is important to establish the perspective and expected results of the new institutionalization and objectives of STI governance. This implies a good framework that includes (Pardo et al., 2019) adequate regulations and institutions, patterns of governance, interactions and patterns of negotiation between STI public institutions and stakeholders, new forms of self-governance (including new actors in helices four and five), independence, openness, and transparency through a participatory dialogue.

Figure 1 shows cyclical trends at the beginning of the analysis period. However, by the end, relative stability in the behaviour of the series emerges. These results indicate that based on the preferences of each policy-maker, stability should be considered within the optimal management of policies given the principles of independence and transparency and the effective allocation of resources for the entire system (ESCAP, 2018). Figure 1 shows the fluctuating trends for the variables of interest used for STIAs and R&D as one of the objectives of the preferences of each policy maker. Table 2 shows projections that, on average, yield the best result of 0.13 for the scientist-manager, with a minimum value of 0.09 and a maximum value of 0.2. For the businessperson‒entrepreneur, the results show an average of 0.01, with a minimum value of −0.02 and a maximum of 0.08. For the politician, the results show an average value of 0.02, with a minimum of −0.07 and a maximum of 0.15. The projections and their tendencies determine that the best results would be achieved by a policy-maker with an adequate technical profile and with the preferences of the scientist-manager.

Figure 1

Trends for policy-makers in STI. Source: Cotte and Andrade (2019).

Notably, the coordination and consensus among the different agents participating in this system in all scenarios are the best outcomes. That is, policies coordinated in all sectors are perhaps the first-best alternative. Moreover, optimality, given the scarcity of resources overall, would yield an efficient allocation and the best effects in the medium and long terms, considering the new institutional framework and possible institutional arrangements that could reduce uncertainty and transaction costs. Indeed, in modern theories of economic growth, such factors mark the difference between high-, medium- and low-income countries.

These results indicate the importance of the evolution of STI policies similar to those of countries such as China, Japan, the Republic of Korea, and Singapore, which are characterized by Epstein et al. (2007) as follows. i) These policies facilitate technology transfer and diffusion and generate qualified human resources in science and technology. ii) The scope and objectives of STI policy have gradually been extended from the stimulation of industrial development and economic growth objectives to innovation and social and environmental objectives for inclusive and sustainable growth. iii) These countries have prioritized frontier technology development as a policy objective, generating specific instruments and mechanisms to promote advances in this regard in fields such as the environment, digital infrastructure, and R&D. iv) Finally, public sector innovation is viewed as a tool for improving public service delivery and supporting the development of technological and innovation capabilities and markets through the adoption and promotion of new technologies with applications for managing human resources or deploying new regulatory frameworks. These elements are key to designing appropriate STI governance to promote development, equality, and growth. In particular, in emerging countries, this requires building innovation capabilities in the construction of their own development pathways to address economic, environmental, and social aspects based on knowledge, new technologies, and innovation.

To determine the reliability of the estimated projections, consistency, and sufficiency analyses are performed for the series. Consistency is a measure of the extent to which membership strength in the causal configuration is consistently equal to or less than membership in the outcome (Knott, 2018). Coverage applies to the proportion of the sum of the membership scores in an outcome that a particular configuration explains. In other words, coverage explains how many cases are covered by a sufficient configuration for a given outcome.

According to Licht (2015), the only way to maintain innovation in the productive sector or large knowledge-intensive industries is to invest in R&D. Such investment constitutes a good plan that will help firms produce their own technologies and innovations, potentially guaranteeing them a place as pioneers in their sectors. It will also allow firms to access better prices and new markets, secure a competitive advantage, and promote the effectiveness of R&D investments. Higher R&D enables higher profits, growth, and market value per unit of R&D investment. Conversely, when fewer companies invest in productive R&D, there is lower or negative innovation, which could drive lower growth in a country or region.

Another important point is the importance of public investment in R&D, considering the following (Cotte & Jimenez, 2019): i) R&D expenditure is a significant driver of competitiveness and productivity, which generates economic growth. ii) Government support for R&D reduces the costs of research and thus stimulates corporate R&D spending. iii) The public sector can help compensate for corporate R&D investment below the socially optimal level because the results of research and innovation can be used and are available to all firms and society as a whole. iv) Finally, it should be ensured that public expenditure does not decrease private investment in R&D. These elements are very important for achieving an effective STI policy that promotes public and private investment in R&D and STIAs. Such investment is fundamental for promoting growth, competitiveness, and development in the whole economy and benefits the population.

According to these results, in the new institutionalization of STI governance in Colombia, it is important for the new MSTI to analyse different stakeholders (UNCTAD, 2019). These include the following: i) The first is the research system, which represents the ability to learn and apply the knowledge required to build a local knowledge base. ii) Second, intermediary organizations compensate for a basic systemic failure in the connection with generators and users. iii) Third, the education system improves the quality of the human capital available to firms, governments, and research institutions and can change the needs of industries, workers, and consumers. iv) Fourth, civil society and citizens are fundamental for focusing STI policy on meeting social challenges. v) Fifth, the government is key to establishing a consensus on STI policy priorities, directing public resources to important areas, removing obstacles, designing and enforcing regulations and standards, and attempting to improve framework conditions through public policies. vi) Finally, firms and entrepreneurs have the ability to learn, absorb, innovate, and commercialize new knowledge and technologies with an innovative effect.

Moreover, new STI governance must include the following issues (UNCTAD, 2019): The first is a strategic reflection on costs and benefits. The second is a policy orientation towards structured application in the ongoing and planned policy processes in Colombia. The third is transformative change based on evidence. The fourth is being systemic. The fifth is being participatory to engage key government and non-governmental stakeholders from the country to guarantee that the analysis and recommendations are relevant and actionable. The sixth is being context-sensitive to ensure that the advantages and limitations of the local context are sufficiently considered. The seventh is being evidence-based to ensure the use of good quantitative and qualitative data relevant to the country's context. viii. Finally, the eighth is capacity building for consolidating existing and building new capacities of STI stakeholders with key roles in the STI system. The simulations performed in this study demonstrate the importance of these issues for contributing knowledge to solve the main challenges of the country.

The findings of this study are important as input for the analysis and evaluation of STI policy in Colombia, as it is newly institutionalized under the MSTI. An appropriate policy will allow the country to move from being a consumer to being a generator of STIs that suits the local requirements and the local context to solve economic, social, and environmental problems based on knowledge as a driver of growth, sustainable development, and progress.

5 Conclusions

This study analysed the new institutionalization of STI in Colombia and the role of policy-makers’ preferences with the aim of clarifying the prospects for improving STI governance in the country. It used qualitative and quantitative methods and determined the main factors that will affect the new institutionalization of STI governance in Colombia in terms of the preferences and role of policy-makers operating the new MSTI.

The results indicate that the new institutionalization of STI governance implies guaranteeing transparency, independence, and rules that promote and strengthen R&D investments, especially in the private sector. This can achieve the generation of new knowledge, technologies, innovation, entrepreneurship, and improvements in productivity and competitiveness as key elements in promoting economic growth and development.

The results from the simulations showed wide variability in the potential behaviour of the main variables in terms of the policy. Furthermore, the trends are cyclical, indicating that the optimal management of policies must be based on independence, transparency, and effective resource allocation.

The main implications of this study are related to the importance of STI in transforming the economy by generating greater growth and development in a knowledge-based society. In contrast, the limitations of this study are the need to analyse other factors and aspects that can affect STI governance and to evaluate the decision-making process based on differences in the profile, interest, and knowledge of policy-makers.

Regarding scientific policy and its implementation, this study shows the importance of public policy-makers considering decision variables for the efficient allocation of scarce R&D resources together with general STIAs in the context of improvements in the welfare of the population. Moreover, STI policy needs to analyse regional societal challenges and adjust competitiveness and innovation systems based on interregional requirements and gaps to decrease disparities in the country.

Modern theories addressing the growth and development of countries hold that the variables differentiating high-income from low-income countries include the adequate use and allocation of resources to R&D, incentives for science, increases in technology usage and the encouragement of innovation. These variables are fundamental for creating the conditions necessary to stimulate the growth of countries.

This work also shows the implications of implementing social policies related to economic agents’ preferences in terms of benefits from advances in STI for countries’ productivity [26], living conditions and, thus, the competitiveness of each region. Structural reforms and their implementation are essential for achieving a society that advances with the new industrial revolution based on the knowledge-generating economy, where the new institutionalization of STI can include the political economy of new advances in STI to increase and manage the globalized nature of STI and to determine power relations with stakeholders. These elements require further research to improve STI governance and establish the policy impacts to achieve objectives and effectively promote STI among different stakeholders in Colombia.