Similar to other developing countries [1
], Thailand is now facing challenges that arise from the growth of economies, populations, and urbanizations—that is, increased energy demand, environmental degradation, global warming effects, and municipal solid waste (MSW) generation and management problems. MSW management, in particular, has caused the country critical problems that required urgent resolution, such as rising MSW generation, the limited capacity of landfill sites, and environmental effects on surrounding areas. Compounding these issues is insecurity in Thailand’s energy sector given the country’s substantial dependency on imported fossil fuels and petroleum in serving national energy consumption demand. To illustrate, 60% of the total energy consumption in 2017 was satisfied through imported fuels, of which around 80% is made up for crude oil [2
]. Seeking alternative energy resources has thus been a crucial difficulty for the Thai government.
As reflected in global trends, one of the most potentially efficient approaches to satisfying energy demand and dealing with MSW management problems is the conversion of MSW into energy-from-waste (EFW) products [3
], which can be considered as a kind of bioenergy resources [4
]. EFW products can also be used as an environmentally friendly bioenergy resource for electricity, heat, and/or transport fuel generation [4
]. Similar to biomass, EFW product is regarded as a renewable and carbon-neutral energy resource used to replace and/or reduce usage of fossil fuels and coal, which are considered as the important sources of CO2
and NOx emission [5
]. Such products therefore play an important role in mitigating the emission of greenhouse gas (GHG) [6
For this reason, the government has promoted and implemented the conversion of MSW into EFW or waste-to-energy (WTE) products as a practical strategy for resolving national MSW management problems, reducing the burden imposed on landfill sites, fulfilling energy demand, and reducing CO2
production and global warming impacts. This strategy is part of Thailand’s 2015 Alternative Energy Development Plan (AEDP), which is the government’s initiative for minimizing reliance on imported energy and cultivating domestic alternative energy resources, especially EFW. At the end of the plan’s implementation in 2036, the proportion of renewable energy used in the country is forecast to increase to 30% final energy consumption, thereby replacing around 39,388 ktoe of fossil fuel utilization and reducing GHG emissions by around 140 million tCO2eq
]. Under the ultimate goals, 550 MW of electricity and 495 ktoe of heat would be accounted for by the achievement of EFW targets [9
The conversion of MSW into energy is gaining momentum as a preferred MSW management strategy in Thailand, and feed-in-tariffs (FiTs) for WTE-based electricity generation is supported by the government (Table 1
]. To date, however, the country has only 39 WTE plants with an electricity generation capacity of around 313 MW and three WTE incinerators with a heat generation capacity of approximately 47 ktoe [9
]. Achieving the EFW targets set forth in AEDP 2015 requires relevant organizations to cooperate with one another in establishing an appropriate and desirable FiT for heat generation from MSW. Through collaboration, these organizations can jointly support and encourage MSW-related development and investment.
Numerous efforts have been initiated to satisfy requirements for EFW development, especially the elimination of MSW management and EFW technology limitations, but such endeavors disregarded the importance of cooperation among relevant government organizations in sustainable and holistic EFW development and effective EFW policy formulation and implementation. In particular, energy policy creation and enactment in accordance with waste management directives is required given that government organizations involved in energy and waste management must cooperate to ensure the feasibility of EFW development and investment and to derive value from these projects. Unfortunately, such partnership has not arisen in the Thai context, with ineffective cooperation among governed institutions weakening and impeding EFW development in the country. Nevertheless, an optimistic outlook can be derived from Thai government organizations’ realization of the negative effects of their inability to cooperate and their efforts to deal with this obstacle. This impediment, as stated in AEDP, can be resolved by searching for a host that will support the advancement of EFW programs, fostering integrated cooperation among relevant agencies, and developing a database system for data sharing among such entities [11
]. The difficulty now is that Thai government organizations have not released analytical or research results on the causes of ineffective cooperation; nor have they provided details regarding the proposed improvements to collaboration or presented clearly defined steps in implementing these enhancements. This challenge points to the critical need for comprehensive explorations of the problem and systematic approaches to improving collaboration among government organizations.
Policy process generally involves different types of knowledge, actors, and activities, thus leading to situational overlaps, which inevitably drive activities in one circumstance to affect those occurring in another [13
]. To this end, effective cooperation among parties is necessary for a successful public policy process [9
]. As asserted by Edward [14
], disunity in organizations hinders the cooperation essential to the implementation of complex policies, especially those that require joint efforts from many parties. Inappropriate institutional arrangement is indicated as a factor influencing the lack of cooperation, which in turn, contributes to ineffective policy process [15
]. Hence, understanding among institutions is essential; such understanding refers to the shared concepts that govern the behavior of actors participating in a policy situations [13
Effective cooperation should be accorded priority because many policy-related tasks required different actors to interact collectively and help one another in managing difficulties. Cooperation is also a primary driver of good understanding among actors, which can increase policy effectiveness [16
] and encourage actors to share resources, information, and competencies to support enhanced decision making, interactions, and the achievement of mutual goals and policy outcomes [18
An important consideration in attempts to foster cooperation is that it is not a “simple behavior, nor even as specific pattern of behaviors. Rather, it is seen as a set of relations among behaviors and their consequences” [20
]. Cooperation has been defined in different ways, but explanations of the concept always revolve around the manner by which actors effectively work together. Examples are its definitions as “the alignment of incentives, or the extent to which partners are willing to work together” [21
] and “the organizations working together for the same goals, but maintain control of their individual resources” [22
]. Sometimes the term “cooperation” is used interchangeably with “coordination” and “collaboration” [23
]. Cooperation has likewise been elucidated as involving goal-directed behaviors, rewards for each participant, distributed responses, coordination, and social coordination, whose combination can augment the accuracy with which the types of cooperation transpiring among actors are classified [20
With respect to general relationships in society, individual actors are connected with others through four types of ties, namely, (1) similarities that include “spatial and temporal proximity as well as co-membership in groups and events and sharing socially significant attributes” (e.g., residing in the same location, belonging to the same race, or having the same attitude); (2) social relations conceptualized as continuous properties (e.g., friendship, kinship, or business partnership); (3) interactions viewed as “being facilitated by and occurring in the context of social relations (and vice-versa)” (e.g., providing advice and support, engaging in trade); and (4) flows described as “tangible and intangible things that are transmitted through interactions” (e.g., information or resources) [19
]. These ties can lead to cooperation that can occur tacitly without communication or explicit agreement given that the expectations of actors are merged; through negotiation; and through enforcement by a strong actor, provided that such actor also adjusts its own policies and endeavors to achieve mutual benefits [26
]. The decision of actors to cooperate with one another is influenced by various factors, such as the previous interactions of an individual actors [20
], the achievement of cooperation objectives in the past [30
], the effects of institutions [13
] and neighboring municipalities’ decisions [31
], and an actor’s willingness, intensives, self-interest, and opportunism [21
Because cooperation results from the decisions and actions of actors to work together, the patterns that underlie such collaboration are flexible. That is, cooperation can vary depending on the degree of interaction among actors as they jointly create values [33
]. Accordingly, researchers have been attempting to systematically classify cooperation to broaden our understanding of this behavior. Weber and Heidenreich [33
], for example, categorized cooperation in product development into vertical cooperation with suppliers and customers, horizontal cooperation with competitors, and institutional cooperation with university and research organizations. The authors also identified three stages of new product development on the basis of the actors involved in the industrial process: Concept development, product development, and implementation. Alimov [35
] classified cooperation among partners, from the perspective of regional economics, into cooperation in the political and security domains, in trade and economic activities, and in the development of culture and humanitarianism. In their study on cooperation among Indonesian government organizations to support the implementation of an e-government system, Nurdin, Stockdale, and Scheepers [36
] classified cooperation into vertical (within an organization) and horizontal (between different organizations) collaboration.
Effective cooperation among actors is necessary for successful collective work. To the best of our knowledge; however, a limited understanding has been achieved as to cooperation among government organizations and the conditions that are conducive to the effective development and implementation of public policy. To improve our grasp of such matters, this research delved into collaboration among Thai government organizations involved in the formulation and enactment of AEDP 2015 using the institutional analysis and development (IAD) framework. Analysis was directed specifically toward the effects of the institutions on the characteristics of policy situations, the manner by which the actors interact, and the factors that influence their decision to cooperate with one another in the policy process of interest.
The specific interactions of interest in this work were those occurring among core Thai government organizations involved in the development and implementation of the EFW targets stipulated in AEDP 2015. Data for the case study were extracted through document analysis and in-depth interviews with government staff. In this regard, the objectives of the study were to examine the intensity of cooperation among the actors and to analyze the factors and conditions that influence decisions of these actors to cooperate with one another.
To elevate our understanding of cooperation, we applied the concept of cooperation intensity, which is described as actor interactions that involve vigorous contribution to policy work and policy outcomes. The concept was further categorized into five levels to reinforce the novel contributions of this study. The levels at issue are reflected in (1) the pursuit of common goals and mutual benefits, (2) the pooling of resources, (3) the sharing of responsibilities, (4) the synchronization of activities, and (5) the monitoring of partners. This proposed hierarchy constitutes the implications of the research given its applicability as a reference in the assessment of current situations, the improvement of cooperation in a step-by-step manner, and the proposal of strategies for enhancing cooperation and, thereby, policy development and implementation.
The rest of the paper is organized as follows. Section 2
provides a brief background on the IAD framework, and Section 3
describes the methodology adopted in this work. Section 4
presents the results, Section 5
discusses the findings, and Section 6
concludes the paper.
2. Institutional Analysis and Development Framework
The IAD framework (Figure 1
) is an institutional approach generalized for institutional and collective action analyses [13
]. This framework was constructed on the basis of the effects of rules and norms that were determined from logical observations; it is useful in deriving a set of typical regulations that influence the different elements necessary for policy analysis [37
]. The framework also uncovers details of an action situation, thereby reinforcing our understanding of interactions among actors and the outcomes of such exchanges [39
The IAD framework is used to examine questions related to the effects of institutions on interesting events or situations. The framework is adopted primarily in analyzing what effects emerge from external variables, how decisions are made, and what actions are exercised [41
]. Its core analytical unit is the action arena, which is defined as a conceptual space where actors interact and experience the consequences of actions [13
]. The action arena comprises actors and action situations, which are influenced by exogenous variables (biophysical conditions, community attributes, and rules-in-use). The relationship between actors in an action arena that is subjected to constraints from exogenous variables are reflected through patterns of interaction [42
]. An action situation is constructed from the association among seven variables, which were explained by Ostrom, Gardner, and Walker [43
] as follows: When actors
participate in a given situation, they are assigned positions
and are required to decide among various actions
in light of information
made available to them. This information apprises actors of how actions are linked to potential outcomes
, the levels of control
that they can exercise over such linkages, and the costs and benefits
that come with actions and outcomes.
The above-mentioned variables are influenced by rules-in-use, which are the “shared understanding among those involved that refer to enforced prescriptions about what actions (or states of the world) are required, prohibited, or permitted” [44
]. Rules-in-use are consulted and applied by actors in action situations, thus reflecting that such regulations directly control the decisions and behaviors of actors [39
]. To facilitate analysis, the IAD framework classifies rules-in-use into seven types on the basis of the key influence that they exert on variables related to an action situation [13
]. These rules are presented in Table 2
The behaviors of actors who participate in a particular structure of action situations under the influence of exogenous variables constitute patterns of interaction that lead to an actual or predicted range of outcomes. Patterns of interaction are the characteristics of the internal structure that typifies an action situation and the conduct of actors in a resultant structure [13
These components and occurrences are discernible in policy development and implementation situations, wherein one of the actions required of actors is to work cooperatively. The decision of actors to collaborate and the intensity with which they execute this task directly influences the effectiveness of policy work. Understanding the factors that affect such decisions and behavior is therefore necessary in ascertaining ways to ensure effective cooperation in policy development and implementation.
In different countries, policies visibly exert a significant influence on the development of renewable energy and investment in this resource; therefore, active involvement and effective cooperation among relevant actors are the major precondition for the transition to renewable energy utilization [4
]. To this end, this study focused on the examination of cooperation among actors under a policy process as reflective of patterns of interaction that relate to the behaviors of actors and the consequences of such conduct on expected policy outcomes [20
]. Park, Srivastava, and Gnyawali [34
] classified the different degrees to which actors cooperate with their partners given that the extent of collaboration can vary depending on partners and period of time [33
]. This concept was adopted in the present study, this time to classify cooperation in the AEDP policy process, and the intensity of cooperation was defined as actor interactions that entail intensive contributions to policy works and outcomes. Correspondingly, five levels of cooperation intensity were conceptualized; collaboration through (1) the pursuit of common goals and mutual benefits, (2) the pooling of resources, (3) the sharing of responsibilities, (4) the synchronization of activities, and (5) the monitoring of partners. This cooperation hierarchy can be used as a guide in analyzing current and future (projected) cooperation and advancing enhanced collaboration.
We applied the proposed cooperation intensity levels to the case study (Table 9
) and found that the main gaps between ideal and actual interactions are (1) differences in perceptions of MSW problems and the prioritization of the solutions put forward by individual actors; (2) the actors’ commitment to the different solutions; (3) inconsistency among responsibilities, actions, and control over the outcomes of the actors; (4) the failure of the actors to clarify and synchronize related and duplicate policy activities; and (5) the unwillingness of the actors to undergo checking and monitoring.
This study likewise identified and scrutinized the variables that influence the gaps between ideal and actual cooperation in the case study. This objective was accomplished by probing into different cooperation intensity levels during the AEDP policy development and implementation on the basis of ideal action arena structures (Table 8
). The gap in cooperation intensity with respect to common goals and mutual benefits is caused by variances between ideal and actual actions. The actors do not clearly communicate individual views regarding MSW problems and solution directions. This deficient communication drives the actors to solve national MSW challenges in different ways, as reflected in the inconsistency of their derived goals. With regard to resource pooling, the actors also pursue divergent solutions, thereby affecting potential outcomes and causing difficulties in combining resources.
Before considering the variables that influence the gaps in the rest of the cooperation intensity levels, it should be noted that the actors do not have perfect information, which is the ideal variable in the action arena for shared responsibilities, synchronized activities, and partner monitoring. Information is a critical source of gaps because the actors are compelled to decide and act under inadequate information.
Gaps in shared responsibilities are caused by actions, potential outcomes, and control variables. In the case study, the actors do not implement effective actions in clarifying overlapped responsibilities and thus respond to varying policy targets. This affects the balance of control given that the MoEN is the sole agent responsible for the achievement of AEDP 2015 targets, whereas the MoI is the policy operator who oversees the selection of MSW treatment approaches. Additionally, activities are not synchronized because the actors neither plan for such integrating nor organize policy activities together. In the matter of partner monitoring, the Thai government experiences difficulty in accomplishing this aspect of cooperation given that action arena variables (i.e., actions, information, control, potential outcomes, and costs and benefits) have yet to be constructed. Currently, no effective monitoring system under Thai bureaucracy is in place, and the actors themselves are unwilling to undergo checking and monitoring because of the inflexibility, suspicion, and fault-finding to which actors resort when mistakes are made.
According to Smajgl, Leitch, and Lynam [75
], all action arenas are influenced by the rules-in-use. In the IAD framework, rules-in-use include both formal and informal rules that significantly impact an action arena [41
]. This study investigated aggregation, information, and scope rules that chiefly affect the actors’ decisions and consequent outcomes. The effects of these rules on action arena variables were used to explain the decisions, actions, and behaviors of the actors involved in the case study. Because all the actors are government organizations, formal rules are enacted as laws or regulations. Focus therefore, revolved around the informal rules that are molded by norms and behaviors [76
]. Informal rules can be combined with formal ones, which can then restrict how actors interact and make decisions.
In consideration of different rules under the category of information rules, the one that most essentially affects the information variable in the action arena is the shame-prone culture that discourages the disclosure of sensitive information [63
]. This rule prevents actors from acquiring perfect information, which is necessary for movement toward a higher cooperation intensity. Limited information affects actors’ decisions seeing as they are forced to decide with inadequate knowledge as a basis. Elevation to more intense cooperation is likewise impeded by the control variable that is governed by the rule on avoiding decisions that can cause conflicts, tensions, and, particularly, increased workload among actors [61
]. This rule is categorized as of aggregate type, specifying how actors decide over choices. When actors’ decision-making hinges on the desire to avoid conflicts, tensions, and increased workload, potential outcomes can be constrained. The potential outcome variable is controlled by scope rules. In the case study, the most important scope rule is path dependency. Given that the MoEN faces imperfect information and is constrained by the avoidance of conflicts, tensions, and increased workload for its partner, it is obligated to forecast potential outcomes on the basis of path dependency. Cooperation intensity in the case study is low; thus, predicting potential outcomes with past situations as basis is inevitable, although a higher cooperation intensity in the future might be deterred.
As patterns of cooperation are influenced by an action arena and variables in the action arena are influenced by rules-in-use, theoretically, changing the latter should result in a more appropriate internal action arena structure, which should improve the patterns of that underlie cooperation among Thai government organizations. For example, when actors make decisions, they should concern themselves with elevating the quality of national social welfare rather than devoting resources to circumventing conflicts, tensions, or increased employee workload. This does not mean, however, that actors should be aggressive and inflexible; rather, they should decide sincerely and reasonably for the benefit of the country. Moreover, adherence to the shame-prone culture should stop because it is a tremendous obstacle not only to advancement to more intense cooperation but also to the development of an entire policy process.
Notwithstanding the potential advantage of altering rules-in-use, especially informal ones, such strategy is not easy and takes time. In practice, adjusting some variables in an action arena can be more easily and more rapidly achieved. Actors evaluate situations differently, and they work under diverse conditions; an essential requirement, then, is to fine-tune understanding among actors. Consistent with this requirement, this research recommends obligating all actors to thoroughly communicate with their partners at every cooperation intensity as good understanding among actors, especially with regards to individual needs and limitations, is crucial to collaboration and improvements to cooperation intensity in the future. Because Thai government organizations evaluated their performance twice a year, the satisfaction of their partners with communication should be used as a performance criterion. As van Karnenbeek and Janssen-Jansen [76
] explained, informal rules are “the rules that are shaped by norms and behavior”. Therefore, when actors communicate intensively, they gradually become accustomed to this behavior, which slowly becomes the norm for them. Consequently, intensive communication during collaboration in a policy process can serve as the rules that drives the actions of government organizations in the future.
As Chenboonthai and Watanabe [64
] examined government organizations as actors in an action arena and explained that because actors value their own policy capacities (i.e., the conditions conducive to policy development and implementation) and those of others differently, they face difficulties in cooperating during policy works. In the present research, the effects of the internal structure of an action situation in an action arena on patterns of cooperation were investigated, along with the effects of the rules-in-use on the variables of the action situation. Ineffective cooperation is influenced not only by the different valuations of actor’s policy capacities, but also by inappropriate internal action arena structures, which might be controlled by rules-in-use. As a result, understanding the policy capacities of actors is potentially insufficient to advance effective cooperation, but it remains necessary to understand rules-in-use and the action situations that constrain actors.
Remedying ineffective cooperation among Thai government organizations is critical for effective policy development and implementation, but studies on cooperation under policy processes are limited. To fill this void, the current research expanded our grasp of Thai policy processes by casting light on cooperation from an institutional perspective; this orientation was adopted given that institutions affect the decisions made by actors—an influence that, in turn, impacts policy outcomes [13
]. The IAD framework was selected as the tool for carrying out the case study on collaboration among the MoEN, MoNRE, and MoI, which are involved in EFW target development and implementation under AEDP 2015. To add value to the research, we adopted the concept of cooperation intensity, which pertains to actors’ interactions that involve vigorous contribution to policy work and policy outcomes. We then categorized such intensity into five levels, which are reflected in collaboration through (1) the pursuit of common goals and mutual benefits, (2) the pooling of resources, (3) the sharing of responsibilities, (4) the synchronization of activities, and (5) the monitoring of partners. This cooperation hierarchy can be used as a guide in the analysis of current and future (projected) cooperative initiatives and the advancement of enhanced collaboration.
With the five levels of cooperation intensity as a basis, we found that the causes of ineffective cooperation are differences in perceptions of MSW problems and the prioritization of solutions put forward by the individual actors; the actors’ commitment to different solutions; the inconsistency among responsibilities, actions, and control over the outcomes of the actors; the failure of the actors to clarify and synchronize related and duplicate policy activities; and the unwillingness of the actors to undergo checking and monitoring. These causes, as determined from the IAD framework, stemmed from the effects of rules-in-use—especially informal information, aggregation, and scope rules—on the actors’ behaviors and decisions. Changing rules is not an easy task, and altering actors’ behaviors instantly is difficult to accomplish. To improve cooperation, we recommend obligating all actors to thoroughly communicate with their partners at every cooperation intensity level as good understanding among actors, particularly with regard to individual needs and limitations, is crucial to collaboration and improvements to cooperation intensity in the future. Because Thai government organizations evaluate their performance twice a year, the satisfaction of their partners with communication should be used as a performance criterion.
Similar to other studies, the present study is encumbered with certain limitations. First, our findings were obtained from an ex-post analysis characterized by a limited number of variables and constraints. Second, the proposed classification of cooperation intensity is a simplified one, when in reality, cooperation does not occur as systematically and as linearly as described in this research. The establishment of cooperation can proceed backward, in a combined fashion, or be disregarded altogether. It is hoped, however, that the lessons learned from the case study and the recommendations will benefit future research on policy development and implementation, especially in service of the next revision of AEDP 2015.
For further research, scholars can look into the effects of institutions that govern other patterns of interaction that affect effective policy development and implementation by actors. These patterns include negotiation, communication, and ignorance. Researchers can also investigate the evaluative criteria used in assessing the connections between cooperative behaviors and their outcomes.