Case study3

challenges

Article

Modeling Autonomous Decision-Making on
Energy and Environmental Management Using
Petri-Net: The Case Study of a Community in
Bandung, Indonesia

Niken Prilandita *, Benjamin McLellan and Tetsuo Tezuka

Graduate School of Energy Science, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan;
[email protected] (B.M.); [email protected] (T.T.)
* Correspondence: [email protected]; Tel.: +81-75-753-4739; Fax: +81-75-753-9189

Academic Editor: Palmiro Poltronieri
Received: 28 December 2015; Accepted: 5 April 2016; Published: 14 April 2016

Abstract: Autonomous decision-making in this study is defined as the process where decision-makers
have the freedom and ability to find problems, select goals, and make decisions for achieving the
selected problems/goals by themselves. Autonomous behavior is considered significant for achieving
decision implementation, especially in the context of energy and environmental management, where
multiple stakeholders are involved and each stakeholder holds valuable local information for making
decisions. This paper aims to build a structured process in modeling the autonomous decision-making.
A practical decision-making process in waste-to-energy conversion activities in a community in
Bandung, Indonesia, is selected as a case study. The decision-making process here is considered as
a discrete event system, which is then represented as a Petri-net model. First, the decision-making
process in the case study is decomposed into discrete events or decision-making stages, and the
stakeholders’ properties in each stage are extracted from the case study. Second, several stakeholder
properties that indicate autonomous behavior are identified as autonomous properties. Third,
presented is a method to develop the decision-making process as a Petri-net model. The model is
utilized for identifying the critical points for verifying the performance of the derived Petri-net.

Keywords: autonomy; decision-making; Petri-net; energy; environmental; community; Indonesia

1. Introduction

The recent global agenda and technological challenges for creating a more sustainable
environment have encouraged countries around the world to gradually shift towards sustainable
energy transitions. Upon the new global agreement of Sustainable Development Goals, every country
is now highly anticipated to direct their efforts towards realizing a more sustainable energy system and
environment [1]. From the technology side, the emergence of new technologies, such as smart grids
and source-centered renewable energies, have expanded the potential and requirements of energy
generation and management in ways that have not been available previously. These facts suggest that
the energy system is likely to become more distributed and localized, thus the decision-making and
policy-making process in the energy sector should be adjusted to follow this future tendency [2].

Most decisions made on energy and environmental management affect a large number of people
and, thus, are of public interest. Decision-making in this sector usually becomes complicated since
various interests need to be accommodated in the process. Moreover, once a consensus has been
successfully reached, it does not guarantee successful implementation. Various decision-making
approaches for reaching an easy consensus, as well as for achieving successful implementation,
have been proposed. Two common approaches in decision-making are with the centralized and the

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decentralized approaches [3,4]. The quest of balancing between the centralized and the decentralized
systems for decision-making is often an issue in organizational management. Easy access to
information with the advancement of information technology, the internet, and other means today,
have made the decision-making style in organizations lean towards a more decentralized style [5,6].
However, this approach may not be entirely applicable for cases in energy and environmental
management that occur in the public domain.

This study puts more focus on autonomy in decision-making processes regardless of whether they
are conducted under a centralized or a decentralized system. Two ways of understanding the concept
of autonomy are considered here. Firstly, autonomy in the political or public administration field,
which is often seen as one of the traits of a more decentralized system [4]. Secondly, as understood
in the current study, autonomy can be considered as a property of persons regardless of the systemic
context [7–9]. Therefore, we argue that autonomy can exist in both centralized and decentralized
approaches because autonomy is the property of each decision-maker.

The hypothesis of this study is that decisions made autonomously are more likely to achieve
successful outcomes. Autonomy in making decisions is believed to be related to an increase in quality
of life. Research from neuroscience has found that actively making decisions can boost pleasure and
increase the decision-makers’ happiness, satisfaction, and perceived control [10]. Furthermore, high
levels of happiness and satisfaction are causal influences on success and achievement, not the other
way around [11]. Simply stated, if a decision-maker has made an autonomous decision, without being
coerced or forced, it is considered more likely that the decision-maker will achieve the decision goal
and benefit from that.

Normatively, stakeholders’ autonomy in making decisions is important, though its important
role in decision-making may not been objectively examined [7]. The fact that we have not found
studies that objectively examined the role of autonomy in decision-making in energy-environmental
management showed that this theme has to date been insufficiently examined. We argue that the
recent global agenda and technological advances in the energy-environmental sector (e.g., smart-grid
technologies, decentralized energy, and market liberalization) expect decision-makers to become more
autonomous. This situation has created the necessity to develop a framework that can represent and
identify the role of stakeholders’ autonomy in the decision-making process. Such a framework would
consist of several elements employed for specific tasks, and is the purpose of the current research.
This paper discusses one of the important elements of the framework, a model that aims to represent,
analyze, and simulate the autonomous decision-making process.

The autonomous decision-making model in this paper is developed as a discrete event system,
and this paper presents the method to build such a model. The decision-making process is
decomposed into discrete events that we call decision-making stages. Afterwards, the properties
of stakeholders involved in each stage are identified; thus, the concept of a discrete event system
for autonomous decision-making is established. Petri-net is utilized to represent the discrete event
system of the autonomous decision-making process. Each decision-making stage, the stakeholders’
properties, and the state after decisions are made; corresponding to a small Petri-net model
consisting of a few transitions and places. The autonomous decision-making model is constructed
by combining all of these small Petri-net models of each event/stage. As an addition, we conducted
analysis of the Petri-net model’s behavior for identifying the stages which are indispensable for an
autonomous decision-making system. These stages are called the critical points in the autonomous
decision-making process.

2. The Definition of Autonomous Decision-Making

This section explains the definition of autonomous decision-making. The term, autonomous
decision-making is defined by dissecting it into the root words comprising it, which are “autonomy”
and “decision-making”. The development of the concept of autonomy as a political and personal
property is historically explained, followed by a brief explanation on various scopes of the

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decision-making process, and various types of energy decision-making. Based on this information, we
construct the definition of autonomous decision-making used in this study.

2.1. The Concept of Autonomy

The definition of autonomy has been through several changes throughout the course of history.
As mentioned above, there are at least two different concepts of autonomy explained in this paper.
Autonomy originated from the Greek words “auto” which means self, and “nomos” which means law.
This concept was firstly coined referring to the city states in ancient Greece that were self-governing.
Originally, autonomy was defined in a political manner, which was the right of the states (or city-states,
in that instance) to administer their own affairs [9]. In the context of public administration management,
territorial or local autonomy is the result of a decentralization process [12]. In the Indonesian context
for example, the of Decentralization number 22/1999, was the beginning of the country’s journey
towards a more decentralized political structure. This law has since become the legal basis for
providing more autonomy to local governments in making decisions regarding their own territory
and environment. The spirit of the law has had a side effect, however, in that it caused the Indonesian
people to gain greater awareness of autonomy, knowing that they had more freedom in choosing
among options. This has promoted decision-making processes to be performed more autonomously
in various levels of society’s hierarchical structure, including at the lower authority levels, such as
villages and sub-districts [13]. Looking at this fact, the term autonomy in Indonesia has gradually
become understood not only as the property of a state or territory, but also as a personal trait.

One of the most important moments in the history of the concept of autonomy was when the
definition of autonomy was transformed from the property of a state in the ancient Greek era, into a
property of persons during the Renaissance era [7,8]. Since then, the concept of autonomy has been
understood in both ways. However, autonomy in the majority of contemporary works is seen as a
property of persons, or personal autonomy [7]. Although the concept of autonomy mainly revolves
around these two definitions, the dimensions of autonomy are understood in many different ways,
depending on which field of study is viewing it. Mackenzie, for example, defined three dimensions
of autonomy, namely self-determination, self-governance, and self-authorization [14]. Other studies
focus on the self-directedness and resoluteness dimensions of autonomy [9]. Meanwhile, the computer
science and information technology fields view the ability to continuously learn or self-learning traits
in the emergence of autonomous machines or artificial intelligence as one of the most important
characteristics of autonomy [15].

2.2. Decision-Making Process

The definition of decision-making has been long established, and since decision-making is
understood as a process of making decisions, then the definitions mostly evolved on the scope
of the process. There are two predominately different views in decision theory regarding the extent
of the decision-making scope. Firstly, decision-making is defined as a process started by identifying
problems or goals, and ended after a decision has been made. One of the main supporters of this
concept was Herbert Simon (1960) [16]. Later, Huber (1980) expanded the concept of decision-making
by defining it as “the process through which a course of action is taken” [17], and the process by
which the decision is implemented is considered as part of the problem-solving process. Most of the
studies that defined the decision-making process came from the field of organizational management.
Meanwhile when decisions need to be made in the public domain, the decision-making process is often
regarded as the whole cycle from problem identification up to decision implementation and evaluation,
and then feeding-back to problem identification. This is known as a generic decision cycle [18], or a
planning process [19]. An example of a decision-making cycle is presented in Figure 1. In this study,
we investigate the decision-making process extended to the implementation stages.

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Figure 1. Example of a decision-making cycle [18,19].

2.3. Energy-Environmental Decision-Making at Various Stakeholder Levels

The following section explains decision-making in energy and environment by various

stakeholders, such as national government, local government (provincial/city/regency governments,

and formal agencies/bodies within these local governments), community, household and individual

(households and individuals are considered as a single decision-maker), and non-governmental

institutions (i.e., international and local NGOs, business or private sector stakeholders, media,

experts and academicians). As mentioned earlier, decision-making in energy and environmental

management often becomes complex because it occurs in the public domain and, therefore, various

stakeholders are involved in it. According to Sexton, et al. [20], the main stakeholders that are usually

involved in environment-related decision-making are national governments, regional or local

government bodies, business associations, environmental advocacy groups, community or

neighborhood groups, and affected or interested individuals. The relationships between these

stakeholders can be classified into two types of relationship, which are vertical (hierarchical) and

horizontal (parallel) relationships with each other [21,22]. Decision-making for individual

stakeholders and groups of stakeholders is influenced both by the structure of relationships and the

characteristics of the individual stakeholders.

Energy related decision-making and policy-making (We use the phrase “energy (and

environmental) decision-making and policy-making” or “decision-making in energy sector”

interchangeably in this paper because the research object is related with both energy and

environmental sector.) at the national level tends to occur in a top-down manner, following the

hierarchical structure of the country’s institutions. In the UK, for example, energy decision-making

functions have historically been performed mainly by the central government and large corporations

in the private sector. This situation began to change after the Localism Bill was stipulated in 2010

aiming to shift decision-making power from central governments to individuals, communities, and

local government [23,24]. Another example is from a developing country, Indonesia, where for more

than two decades since the first national energy policy was introduced in 1981, the key strategic

energy decisions and policies are made centrally by the national government [25]. The role of local

government in the energy sector was recognized after the promulgation of the Energy Act in 2007.

The act mandates each local government to formulate its own local energy masterplan, based on the

targets outlined by the national energy masterplan.

Recent experiences from both countries have shown that the local authorities are mandated and

expected to have more capacity in energy decision-making functions. The long period of centralized

energy decision-making experience in both countries has created a great challenge for the local

authorities to pick up the task. Lack of capacity of the local government with regards to energy

planning, and limited guidelines on how to formulate the masterplan itself, are some of the

Figure 1. Example of a decision-making cycle [18,19].

2.3. Energy-Environmental Decision-Making at Various Stakeholder Levels

The following section explains decision-making in energy and environment by various
stakeholders, such as national government, local government (provincial/city/regency governments,
and formal agencies/bodies within these local governments), community, household and individual
(households and individuals are considered as a single decision-maker), and non-governmental
institutions (i.e., international and local NGOs, business or private sector stakeholders, media, experts
and academicians). As mentioned earlier, decision-making in energy and environmental management
often becomes complex because it occurs in the public domain and, therefore, various stakeholders
are involved in it. According to Sexton, et al. [20], the main stakeholders that are usually involved in
environment-related decision-making are national governments, regional or local government bodies,
business associations, environmental advocacy groups, community or neighborhood groups, and
affected or interested individuals. The relationships between these stakeholders can be classified
into two types of relationship, which are vertical (hierarchical) and horizontal (parallel) relationships
with each other [21,22]. Decision-making for individual stakeholders and groups of stakeholders is
influenced both by the structure of relationships and the characteristics of the individual stakeholders.

Energy related decision-making and policy-making (We use the phrase “energy (and environmental)
decision-making and policy-making” or “decision-making in energy sector” interchangeably in this paper
because the research object is related with both energy and environmental sector.) at the national level
tends to occur in a top-down manner, following the hierarchical structure of the country’s institutions.
In the UK, for example, energy decision-making functions have historically been performed mainly by the
central government and large corporations in the private sector. This situation began to change after the
Localism Bill was stipulated in 2010 aiming to shift decision-making power from central governments to
individuals, communities, and local government [23,24]. Another example is from a developing country,
Indonesia, where for more than two decades since the first national energy policy was introduced in
1981, the key strategic energy decisions and policies are made centrally by the national government [25].
The role of local government in the energy sector was recognized after the promulgation of the Energy
Act in 2007. The act mandates each local government to formulate its own local energy masterplan,
based on the targets outlined by the national energy masterplan.

Recent experiences from both countries have shown that the local authorities are mandated
and expected to have more capacity in energy decision-making functions. The long period of
centralized energy decision-making experience in both countries has created a great challenge for
the local authorities to pick up the task. Lack of capacity of the local government with regards to
energy planning, and limited guidelines on how to formulate the masterplan itself, are some of
the challenges faced by the locals. Despite the limited capacity and experience, local governments
around the world have developed various energy-environmental measures and local action plans, as a

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form of participation in global initiatives such as the International Council for Local Environmental
Initiatives (ICLEI) and the Climate Alliance [26]. Aside from having a mandate to implement
energy-environmental measures at the local level, local authorities are also expected to involve and
nurture the community or grassroots levels in local energy initiatives [27].

Energy decision-making functions at the community level have been empirically observed in
North America [28–30]. Most of the decisions and measures taken are on climate change mitigation
planning, considered as the re-emergence of the energy planning efforts which increased after the oil
crisis in the 1970s, but later declined in the 1980s due to lower energy prices [28]. Although the number
of local actions for energy measures in USA were increased after 2006, all of the decision-making
processes identified were initially developed at the municipality level first [28]. The municipalities then
involved the community in their plans to reduce community-wide energy use and GHG emissions.
Although similar, the Canadian experience with its community energy management or community
energy planning program is slightly different from what happened in the USA. Observations of the
Community Energy Plans (CEPs) that emerged during 2003–2007 [29,30] have shown the potential
of community roles in formulating action plans specifically related to energy efficiency, energy
conservation, and application of renewable energies [30]. However, since CEP is part of a broader
commitment of the municipalities on forming local action plans for GHG reduction, the content of
the CEP is often written in accordance to what the municipality or municipal council needs [29].
These practices are somewhat different from what was conceived by Jaccard, et al. [31] as community
energy management.

The practices of energy related decision-making at the community level is also evident in European
countries, such as in the UK and Germany [27,32,33]. Often referred to as grassroots initiatives [27,34]
or community (renewable) energy [33,35], it is defined as projects where communities exhibit a high
degree of ownership and control, and collectively benefit from the outcomes [35]. The term community
in this literature is relatively broad, referring to a group of people who share the same geographical
location (neighborhood communities) or the same interest (non-governmental organizations) [33].
The recent practices of community energy in Europe are gradually shifting as part of socio-political
movements from the grassroots level [27] and, thus, they are more likely to be considered as bottom-up
initiatives when compared to the CEPs in North America.

Energy decision-making at the individual level is traditionally studied as a part of consumer
behavior studies which view the individual as the energy customer or end-user [36,37]. Individuals
as consumers make everyday decisions related to energy; therefore, they are becoming the target of
various energy measures [37], such as the behavior change programs in energy consumption and
energy technology adoption [38]. The high potential of new energy systems and technologies such as
renewable energy systems and smart grids have shifted the focus of individual energy decision-making.
In the light of these technologies, individuals’ energy decisions are not only shaped by the energy
system and policy, but can also shape the system [39]. The social foundation of smart grids consists
of “decentralized socio-technical networks that underpin the electricity consumption of groups of
consumers who are increasingly becoming autonomous” [40]. However, for effective technology
adoption, it is suggested to no longer view the individual solely as a consumer of energy, but also as a
citizen, part of a community or society [37].

From the research related with energy decision-making above, it is found that energy
decision-making functions occur at various stakeholder levels, and the decisions made by one
stakeholder may affect others in the total energy system. The challenge of shifting towards a more
localized and distributed energy system creates a need for every stakeholder not only to actively
participate in energy decision-making, but also to become more autonomous.

2.4. Definition of Autonomous Decision-Making

In this research, we put more focus on autonomy as the property of persons, not as a property of
the system or environment. This study considers that each decision-maker is seen as an autonomous

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system, or in other words, autonomy is a property of each stakeholder who participates in the
decision-making process. This means that every decision-maker or stakeholder has their own goal to
achieve and has the autonomy to decide by themselves. Thus, as mentioned earlier, this study views
that autonomy can exist in both centralized and decentralized approaches.

In light of this, we define the autonomous decision-making as the process where decision-makers
have the freedom and ability to find problems, select goals, and make decisions for achieving the
selected problems/goals by themselves in a responsible manner based on available information.
It follows that persons having the ability to self-determine, self-govern, show self-control, and
self-learning are persons who exhibit autonomous behavior. The definition for each autonomous
behavior used in this paper is presented in Table A1 in the Appendix.

3. Methodology for Modeling an Autonomous Decision-Making Process

The aim of this study is to develop the autonomous decision-making model for the energy
and environmental management process by using Petri-net. For this aim, an energy-environmental
management project in Indonesian community (Rukun Warga) is selected as a case study. The steps
performed for modeling in this paper are: (1) case selection and data collection; (2) decomposing
the decision-making process and extraction of the stakeholders’ properties; (3) identification of
stakeholders’ autonomous properties; and (4) modeling the decision-making process from the observed
case using Petri-net and analysis of the model.

3.1. Case Study Selection and Data Collection

This paper undertook one decision-making process as a case study to be modeled, and there is a
strong indication to select this particular case. The selected case study was included and investigated
along with other five community decision-making processes in our previous work [41]. These cases
were, in turn, selected from a broader set of around 20 case studies. The five cases were selected due to
their success in project implementation and the availability of detailed documentation and information.
Among the five cases, the community presented in this study was considered to have utilized both
centralized (top-down) and decentralized (bottom-up) decision-making approaches. Since we argued
that autonomous decision-making can occur under both approaches, by selecting this case we can
investigate and model autonomous decision-making under both approaches using the same case.
In addition to that, by using the same case study which exhibits two different decision-making
approaches over a period of time, the behavior change and improved capability of the community in
making decision were observed.

The model developed here is based on a case study of a practical decision-making process for a
waste management system project in a community in Bandung City, Indonesia. The waste management
technique utilized in the community project is a bio-digester installation to transform household waste
to energy (biogas). This case was selected because a considerable number of stakeholders were
involved in the activities with relatively even inputs to the project. Various stakeholders’ involvement
in a project is a rare occasion, especially when almost all stakeholders can contribute relatively evenly
in the project. This situation occurred because the project developed in two phases. The first phase
started as one project and then changed to another project after the first went through a stagnant phase.
The second phase achieved quite a successful outcome and is still in operation at the time of writing.
The stakeholders that were involved in each phase are different, which is one reason why there were
various stakeholder contributions. This unique situation is considered useful for understanding the
possible outcomes from various stakeholders’ engagement when the project changed course.

A thorough data collection is necessary for understanding the case study well. Information
about the community activities and decision-making process were collected using secondary and
primary sources. Various secondary records used were project reports, academic reports, journal
articles, newspaper articles, and web-based articles. Interviews, informal discussions, observation, and
demonstration of the biogas installation were also undertaken during site visits. The primary sources

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interviewed are the chief of the community, the former community chief, bio-digester operators, and
the recycling center operator.

3.2. Decomposing the Decision-Making Process and Extraction of the Stakeholders’ Properties

The decomposition of the case study is important for constructing the autonomous
decision-making model as a discrete event system. There are two steps involved in this decomposition,
which yield two major results that become the foundation of the discrete event system for modeling
autonomous decision-making. Firstly, the community decision-making process is decomposed into
decision-making stages. Secondly, the properties of each stakeholder involved in each stage are
identified. Utilizing the framework developed in our previous work [41], the decision-making process
is decomposed. Modified from Simon [16], Huber [17], and Petrie [18], the framework consists of four
important phases, namely: (1) problem finding; (2) knowledge and information; (3) consensus building;
and (4) decision and implementation (see Figure 2). The points or questions in each phase function as
guidance in decomposing decision-making stages and …