\r\n\tIn conclusion, this book is intended for Engineers for research in the domains of speech signals and ECG denoising and also in the domain of image denoising. Many mathematical tools can be used for speech enhancement, ECG Denoising, and Image Denoising. Among those tools, we can mention wavelets, Empirical Mode Decomposition, Total Variation Denoising, Non-Local Means (NLMS), Kalman Filtering, Wiener Filtering, Deep Learning, etc.
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1. Introduction
It is known that people have a tendency to play game [1]. It is essential to prepare enjoyable learning environments for people who are in need of new search for playing game and having fun. Gamification concept which appeals to users from every age has arised based on the idea of integrating structure of the games into education [2]. Although concept of game is too old, concept of gamification is a new concept. Gamification has become the most popular topic of the last few years [3, 4, 5].
Gamification approach which emerges as the new face of education in the information age is defined as the process of including users into game [6]. According to Bunchball, gamification refers to make the components and mechanics of game more enjoyable through non-play activities in order to generate behavior change among individuals [7]. While gamification approach is an appropriate method for obtaining positive outcomes in education and it leads students to adapt new behaviors through motivating them, making them to study more or learn new things; it also aims to keep people’s motivation high and facilitate attachment and certain behaviors [8]. Level completion, awarding, specialization, professional development which lead to addiction among individuals playing game are used for improvement in education. Therefore, using the system in games for instructional aims would both make instruction more enjoyable and allow individuals to change their behaviors [9].
It is necessary to look at the statistical data to understand why the concept of playing spreads so fast. The market size of the global gaming industry is 99.6 billion dollars by 2016. When the game revenues at the country level are examined by 2016, it is seen that China ranked first with 24.2 billion dollars, followed by the USA with 23.4 billion dollars and Japan with 12.4 billion dollars. Total Western Europe (Germany, France, England, Spain, Italy) totaling $ 17.3 billion in game revenues. The top five countries in the industry dominate about 70% of total gaming revenues. There is an annual income of $ 685 million to 16th in Turkey [10]. In Turkey there are more than 20 thousand internet cafe and is visited by 7.5 million active players each month here [11].
According to Game Designers, Developers, Producer and Publishers (OYUNDER), the average age of gamers in our country is 31 and there are more than 25 million active gamers. Every day, the average number of people playing on a daily basis is more than 10 million, and the average playing time is increasing all over the world [12]. about 30 million people in Turkey are active on the computer, playing digital games in the mobile phone or game console. Experts, an annual turnover of 600 million dollars in the sector in Turkey, said that the turnover of the world reached $ 100 billion [13].
Turkey Games Market Report 2016; Turkey 14.5 million young people (above the EU average) and 46 million online user than 80 million people is a developing country with a young population and it is one of the most valuable gaming market potential in EMEA [14]. In a study conducted in the United States, the average age of those playing in the last 12 years is 37 years. This rate shows that excitement about playing games on the computer is at an advanced level. In addition, 61% of senior executives who participated in the study stated that they were playing during working hours. Lastly, an international survey shows that the ratio of the total population of regular electronic game players is 66% in Germany, 57% in Mexico, 53% in Russia and 52% in England [15].
These figures and studies show us that people are conscious and willing to play. In fact, this enthusiasm is growing day by day and the new generation is a full-fledged player profile. From this point of view, the excitement and motivation resources that people show to play games can be put into life. These motivators, dynamics and processes can be used to generate behavioral changes in order to increase productivity in real life [16].
In recent years, it has been shown as a potential mechanism to enhance participatory participation through online work and practices that play games [17, 18, 19]. Firstly; it is done with points, graphics, level, competition etc. features. By adding features to otherwise ordinary tasks, it can create a more enjoyable and engaging experience for the user [20, 21, 22]. By using the features of the games, it is possible to make the testing experience less burdensome, thus reducing wear. In previous surveys, participants’ personal report surveys have found that playing experiences are usually more fun than their non-play counterparts [23, 24, 25, 26, 27].
In the cases where the method of play is preferred in education, game elements such as rewards, points, rosettes come first in the design phase. Therefore, there are arguments that playing is a system that is rewarded only for learning, and that this is a negative effect on the motivation of students who are engaged in such a process [28]. Two systematic investigations have recently been conducted, with gaming playing an impact on ‘online programs’ (mostly e-learning) [29] and web-based mental health interventions. Looyestyn and his colleagues have found that playing games on objective measures of events such as the use of the program, number of visits to the website and contributions is a big influence. In contrast, Brown and colleagues assessed the effect of gaming on loyalty to online mental health intervention, and they have found that most games play only one game item, rather than just light application of games, but have little effect on effectiveness [30].
According to Yilmaz and O’Connor, gamification studies aim to carry out human-human or human-computer interaction actively [31]. Accordingly, it is aimed to determine what to award at first, what kind of behavior is expected from individuals and more importantly what kind of options should be offered to maintain the system in a healthy way.
According to Gartner Hype cycle, although gamification has become popular in recent years and it has begun to be used for educational purposes, it shows a rapid growth in order to meet the requirements in this context [32]. When topics related with gamification keywords are examined, it is seen that search on examples related with gamification and gamification education are at a high level [33]. When trends in gamification concept are compared based on regions, it was figured out that Singapore and South Africa were emerged as the first countries [33]. Gamification is commonly used in these countries since it support occupational training toward adults. It is known that gamification method is used by institutional organizations in order to increase satisfaction and efficacy among workers and increase product and service quality in the organization [9].
When the literature is examined, it seen that gamification is used in many different areas including marketing [34, 35], health [3, 36], sustainability, journalism, entertainment [3] and education [3, 35, 36, 37, 38]. Gamification is taken really seriously in countries which frequently use technology. Professor Kevin Werbach from Pennsylvania University gives online education on gamification. This is lasting 10 weeks and it can be followed with Turkish subtitles. Certificate is also given at the end of education [39]. There are organizations in Turkey which realized the effect of gamification approach as well. The first gamification attempt named as “Gameatwork” was successful with the prepared web site. Gamification will be more prevalent when it is used in different areas and there will be various attempts when organizations continue to realize its effectiveness [40].
On the other hand, in education there are already processes like playground; students gain points when they achieve the desired learning goal, scores that they earn become grades, and at the end of the academic term they pass to the next level [28, 38]. Playing will allow students to have fun in the learning process [41, 42] or by giving the user an advantage in time management [43] motivation affects the positive direction. Although Samur is a new and popular method with a similar approach, when a limited number of studies conducted in the field of education are examined, it is generally stated that positive results are obtained in the processes involved in this method [44]. With a similar approach Buckley and Doyle are evaluating the fact that it provides individuals with the opportunity to experiment, make mistakes, gain experience and make sure that failure is not an end and that the individual can achieve his goal [28].
According to Landers and Callan, gamification application for the education of students or individuals who wants to develop themselves has not yet become prevalent enough [45]. Findings in the literature also support this notion. It is seen that there are limited number of studies examining achievement, motivation and views of students in gamification approach. Examining studies related with gamification approach and identifying trends in these studies constitute the problem of this study. Therefore, this study is expected to contribute to researchers for future research.
Main aim of this study is to examine the studies related with gamification in Web of Science database and identify trends in the area of gamification based on these studies.
2. Method
Content analysis method was used in this study to identify the trends in gamification research. According to Yildirim and Simsek, content analysis is conceptualizing the collected data at first, then organizing the concepts through using themes and interpretting themes [46]. Content analysis is commonly used with frequency analysis technic through digitizing the data. Content analysis is a scientific approach that enables to examine verbal, written and other materials in an objective and systematic way [47]. According to Cohen et al., content analysis is also described as the process of summarizing and describing the basic content of written information and the messages it contains [48]. Content analysis is a reusable, objective and systematic technique in which some words or chapters of a text are summarized under categories, depending on the rules [49].
This review was undertaken and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (S1 Appendix) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines for observational studies (S2 Appendix) [50]. In analyzing the research included in the study, PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyzes), which is both a critical and quality-guided guide, was used in combining the results of the evidence-based research. Coded information;
Distribution of Studies based on Years
Distribution of Publications based on Number of Authors
Distribution of Studies Based on Type of Publication
Distribution of Studies Based on Paradigms
Distribution of the Studies Based on Research Sample
Distribution of the Studies Based on the Environments
Distribution of the Studies Based on Theory/Model/Strategy
Distribution of Game Components, Dynamics and Mechanics
Distribution Based on Learning Area
It was decided that the researcher should read all the researchers found in the result of the research. Data collected in the research were first evaluated in MS Excel by entering into meta-analysis programs. Gamification keyword was scanned in full-texts in Web of Science database without year restriction and 313 studies were obtained by November 2015. Web of Science Categories; Computer Science Theory Methods (n = 101), Education Educational Research (n = 83), Engineering Electrical Electronic (n = 82), Computer Science Information Systems (n = 79), Computer Science Interdisciplinary Applications (n = 48). Letter to editor, book reviews and meeting abstract were not included in the research (papers excluded n = 20). Since the number of studies on gamification in Web of Science database increase day by day, the present study included studies published before December 2015 and therefore, 313 studies in total were examined. The flow diagram depicts the flow of information through an up-down approach throughout the different stages of the process. The system is treated first in general terms. Then, the processes in the internal structure of the system shape up to the relationship between the number of defined, included and excluded entries and the reasons for exclusion (refer to S1 Appendix) [50]. Analysis of studies was carried out based on the common views of researchers in order to ensure reliability and validity. In digitization process of the data, if a study included two or more dimensions, frequencies were calculated through covering every dimension separately. Data were interpreted after constituting tables.
Cohen’s kappa statistical technic was used to calculate the relationship between category classification carried out by researchers and high level of inter-rater reliability was obtained (.96). Distribution of the articles based on years is provided in Graph 1.
Graph 1.
Distribution of studies based on years.
As it can be seen in Graph 1, research in gamification area have begun in 2011 and increased through the years. Therefore, it is not possible to observe academic studies on gamification before 2011. Eighty-two studies were obtained in 2015 since studies including December 2015 might not be added into the system.
Number of authors in the studies is demonstrated in Table 1.
Author
n
3 authors
125
2 authors
79
1 author
71
4 authors
18
5 authors and above
20
Total
313
Table 1.
Distribution of publications based on number of authors.
As it can be seen in Table 1, articles have been mostly written by 3 authors (n = 125), 2 authors (n = 76) and 1 author (n = 71). It is seen that number of studies conducted by 4 or 5 authors are lower. Distribution of studies on gamification based on countries is provided in Table 2. Countries with less than 6 publications are not included in Table 2. All of them were shown under “other” category.
Country
n
Country
n
USA
51
Portugal
9
Spain
29
Japan
9
Germany
25
Finland
9
England
22
Romania
7
Korea
18
Austria
6
Australia
15
Holland
6
Canada
13
Greece
6
Brazil
11
Other
77
Total
313
Table 2.
Distribution of studies based on countries.
When studies in Web of Science are examined based on countries, it is seen that there are 39 different countries in which the studies were carried out. It was figured out that 51 of the studies were conducted in USA, 29 of them in Spain, 25 of them in Germany, 22 of them in England, 18 of them in Korea, 15 of them in Australia, 13 of them in Canada and 11 of them in Brazil.
It was determined that gamification is actively used in Australia, USA, India, Canada and Holland in 2013. Brazil and France followed this rapid development [51]. According to the results of Google Trends (2016) since January, it is seen that Singapore, South Africa, Holland, Denmark, Australia, Sweden and India are interested in gamification approach. This shows that studies might change based on countries throughout the years [33].
Distribution of studies based on type of publication is provided in Table 3.
Type of publication
n
%
Proceeding
164
52.4
Article
149
47.61
Total
313
100
Table 3.
Distribution of studies based on type of publication.
According to Table 3, number of proceedings (n = 164) presented in conferences with a rate of 52.4% is really high. Researchers explained that gamification concept has been the discussion topic of conferences since 2010 and this might be the reason for this result [52]. Karatas examined studies covering gamification approach for education and indicated that there are few number of master and doctorate thesis since this area is newly recognized [53] .
Distribution of studies based on paradigms is shown in Graph 2.
Graph 2.
Distribution of studies based on paradigms.
According to Graph 2, 163 studies used quantitative method. Studies using mixed methods are the second with 59 number of studies. Since it is a trend topic, it is seen that there are 28 review studies. In pedagogical terms, most of the researchers examined gamification approach especially on ensuring integration [54, 55]. This might be the reason for high number of review studies. Other studies also discussed environments in which gamification system could be integrated into a certain learning [56, 57, 58, 59].
3. Results
In this section, results related with studies on gamification area examined in line with the aims of the present research are provided with tables.
3.1. Distribution of the studies based on research sample
Distribution of the studies based on research sample is provided in Table 4.
Research sample
n
Adults
152
Students
95
Voluntary participants
21
Children
15
Customers
5
Writers/players
4
Patients
4
Civil servants
4
Library users
3
Teachers
3
Sportsmen
3
Twitter community
2
Managers
2
Total
313
Table 4.
Distribution of the studies based on research sample.
According to the results provided in Table 4, it is seen that studies related with gamification have mostly been conducted with adults. This result might be related with the fact that playing games is prevalent among adult population. Following the category of adults, students were the second category of research sample frequently used in the studies related with gamification. This result is consistent with other studies including undergraduate students as participants [60, 61]. Researchers need to have technical knowledge and knowledge on software and hardware for gamification and this might be the reason for including university students in the studies [53]. It is seen that voluntary participants (n = 21), customers (n = 5), writers and players (n = 4), patients (n = 4) and civil cervants (n = 4) constitute the research samples of the studies as well. Schouten et al. examined the users’ experiences and motivations toward gamification among individuals with low levels of literacy [62]. This study showed that individuals with low educational level are also included in the studies on gamification approach as participants.
3.2. Distribution of the studies based on the environments
Distribution of the studies based on the environment in which the studies were carried out is provided in Table 5.
Environments
n
Mobile environment
126
Online environment
91
Internet-based environment
32
Social media platform
25
Virtual environment
11
Game-based system
8
Online and offline platform
4
Real environment
3
Sustainable environments
3
Advertisements
2
Other
8
Total
313
Table 5.
Distribution of the studies based on the environments.
It is seen that mobile environments are the most frequently used environments (n = 126). Following mobile environments, online environments (n = 91), internet-based environments (n = 91) and social media platform (n = 25) are the most frequently used environments.
Educations including Microsoft Ribbon Hero which aims to teach office program in a funny way, ClassDojo which is game-supported class management application that can be used by parents and students [63], Duolingo and Lingualeo which is used for foreign language teaching [64], Kahoot which is used in question-answer activities in class through mobile devices [65], web design with Khan Academy which provides free learning materials throughout the world and programming languages continue to provide education through mobile devices. Almost all of these applications allow online access. In addition, these environments are preferred since they might ensure positive learning outcomes through selecting appropriate social gamification tools for contents which could be provided in social learning platforms [8].
3.3. Distribution of the studies based on theory/model/strategy
In this study, approaches, theories or models used in the studies are also examined and shown in Table 6.
Theoretical approaches
n
%
Motivation theory
131
41.86
Game design factors
86
27.48
Unspecified
44
14.06
Main characteristics of game learning
27
8.63
Learning theory
9
2.88
Flow theory
8
2.56
Technology acceptance model
3
0.96
Mechanics, dynamics, esthetics
3
0.96
Alternative learning-model
1
0.32
Self-determination theories
1
0.32
Total
313
100
Table 6.
Theoretical distribution of the studies.
It is seen that motivational theories are the most frequently used approach in the studies on gamification (n = 131; 41.86%). Other studies also frequently included motivational theories [66, 67, 68]. It was also revealed that there are many studies emphasizing game design factors (n = 86; 27.48%). There are also studies in which their theoretical structures are unspecified (n = 44; 14.06%). This might be because of the fact that this is a recent area. It is determined that motivational theories are important indicators for internal and external motivations of students in a course about gamification system provided to engineering students in order to reinforce their entrepreneurship [69].
3.4. Distribution of game components, dynamics and mechanics
Distribution of game components, dynamics and mechanics is provided in Table 7.
Game components
n
%
Goal-duty
105
25.06
Reward
101
24.11
Progression stick
52
12.42
Cup
35
8.36
Feedback
32
7.64
Success
19
4.54
Badge
12
2.87
Virtual goods
9
2.15
Experience
9
2.15
Leader board
8
1.91
Promotion
6
1.44
Score
6
1.44
Quiz
5
1.2
Cooperation
5
1.2
Sustainability
4
0.96
Difficulty
3
0.72
Event detection
3
0.72
Fantasy and control
2
0.48
Entertainment
2
0.48
Richness of data
1
0.24
Total
419
100
Table 7.
Distribution of game components, dynamics and mechanics.
As it can be seen in Table 7, the most frequently used game components used in the studies are goal-duty (n = 105; 25.06%), reward (n = 101; 24.11%) and progression sticks (n = 52; 12.42%). O’Donovan investigated distribution of individuals motivated through gamification based on game components. Results showed that individuals were mostly motivated through progression sticks [55]. Sari and Altun figured out that badges and cups earned by students motivate them to earn more rewards. It is stated that although students compete with each other in order to earn these components, in fact, they compete with themselves [70].
When positive outcomes of using gamification in learning environments are considered, it has been concluded that integration of game components into these designs will positively affect learners’ motivation [71].
3.5. Distribution based on learning area
Learning areas in which the studies have been conducted are also examined in this study and results are provided in Table 8.
According to the results, it is seen that learning areas are activated in mobile learning area (n = 91, 29.08%). These findings are expected since games can be used through mobile devices and adults prefer this area. Mobile learning which is used as a support for learning processes among contemporary methods arises as the first step of every learning approach today [72]. Results showed that there are varieties in terms of learning areas used in the studies. It is also seen that gamification applications are preferred in virtual environment, simulation and augmented reality learning areas (n = 59; 18.85%), public, service, food, transportation and health sector (n = 56; 17.9%). Different learning areas show that gamification concept could be used in all learning areas. Since gamification concept might differ from game to game, learning areas will also shape in every application.
4. Discussion and conclusion
Designers could view users’ experience in a wider context through gamification concept and constitute an effective learning environment with using motivational components in environments in which there is a competition, cooperation and social interaction [73]. Gamification will become more prevalent when it is begun to be used in different areas and there would be various attempts in this area when the potential of gamification is realized.
The present research is aimed to examine the studies conducted in the area of gamification. It was revealed that studies in the area of gamification have begun in 2011 and increased through the years. When studies in Web of Science database are examined based on countries, it is seen that studies have been conducted in 39 different countries. These countries were identified as USA, Spain, Germany, England and Korea. It was also indicated that gamification are actively used in Australia, USA, India, Canada and Holland. Brazil and France follow this rapid development [51]. When trends in gamification search in 2016 are examined, it was revealed that Singapore and South Africa are the first two countries [33]. This also shows that gamification approach would be a trend topic in different regions over time and different studies would be conducted in this area.
Furthermore, it was figured out that number of proceedings presented in conferences are higher when compared to other types of publication. Researchers indicated that gamification concept has been the discussion topic of conferences since 2010 and this might be the reason for this result [52]. It is expected that number of different types of publication for educational purposes would increase. It was revealed that there are 8 master thesis and 1 doctorate thesis in the area of gamification until January 2016 in YOK thesis center of Turkey [74]. It is considered that this rate will increase at the end of 2016.
According to the results, it is seen that quantitative studies are more preferred when compared to other type of research methods. Karatas indicated that there are insufficient number of quantitative and qualitative studies in the area of gamification [53]. It is expected that paradigms of the studies will become more salient. It is considered that studies examining game designs appropriate for gamification approach would be conducted more frequently in the future. In addition, it is expected that number of studies including achievement tests as quantitative studies will also increase.
When distribution based on research sample is examined, it is seen that studies related with gamification have mostly been conducted with adults. Since playing games is prevalent among adults, the accuracy of this result is accepted. Gokkaya revealed that since gamification supports learning at work as a practical solution for qualified personnel requirement, it is an ideal method for obtaining positive outcomes in especially adult education [9]. Following adults, students are also frequently included in the studies. This result is consistent with other studies including undergraduate students as participants [60, 61]. Diversity in research sample shows that gamification might be used in every age group and area.
Results showed that mobile environments are the most frequently used environments in the studies related with gamification. Gamification applications are supported by mobile devices and this might be the reason for these results. It is also seen that online, internet-based environments and social media platforms are also used in the studies. Educations including Microsoft Ribbon Hero which aims to teach office program in a funny way, ClassDojo which is game-supported class management application that can be used by parents and students [63], Duolingo and Lingualeo which is used for foreign language teaching [64], Kahoot which is used in question-answer activities in class through mobile devices [65], web design with Khan Academy which provides free learning materials throughout the world and programing languages continue to provide education through mobile devices. Almost all of these applications allow online access. These applications are commonly preferred since they allow users to share their status or scores in social media after activity. Therefore, it is essential to determine different activities which will affect success in online environments and integrate them into education environment.
It is seen that motivational theories are the most frequently used approach in the studies on gamification. Although it is known that motivational theories are mostly preferred, it must be also noted that gamification could include many different disciplines. Karatas indicated that future research would not only benefit from motivational theories, they might include different theories related with game, learning and behavioral sciences [53]. It can be said that gamification should be provided to students appropriate for their levels so they would not lose their motivations.
It is determined that the most frequently used game components in the studies are goal-duty, reward and progression sticks. O’Donovan investigated distribution of individuals motivated through gamification based on game components [55]. Results showed that individuals were mostly motivated through progression sticks. Reinforcing structure of game components might be the reason for this result. When positive outcomes of using gamification in learning environments are considered, it has been concluded that integration of game components into these designs would positively affect learners’ motivation [71]. When studies in the area of gamification increase, usage rates among game components would change. It is considered that different game components will be integrated into education based on learning environments and areas in future research. Applications might be prepared for lessons with advanced level of difficulty through providing rewards and scores.
Furthermore, results showed that learning area concentrates on mobile learning area. Results showed that there are varieties in terms of learning areas used in the studies. It is seen that gamification applications are also preferred in virtual environment, simulation and augmented reality learning areas, public, service, food, transportation and health sector. Although the number of studies are low, there are studies in learning areas such as science, food, interactive teaching, marketing, simulations, medicine and transportation. This shows that area of gamification is not limited to technology. Different learning areas show that gamification concept could be used in all learning areas. Karatas stated that gamification might be used in different learning areas. Since gamification concept might differ from game to game, learning areas would also be shaped in every application [53]. It is expected that appropriate designs for different learning areas would increase in future research.
This study will be a guide for researchers to integrate different game components into education environments, constitute independent learning areas and learning environments including different theories and conduct research in this area.
Supporting information
S1 Appendix. This is the completed PRISMA flow diagram.
S1 Appendix. Completed PRISMA Flow Diagram.
S2 Appendix. This is the completed PRISMA checklist.
S2 Appendix. Completed PRISMA checklist
Section/topic
#
Checklist item
Reported on page #
TITLE
Title
1
Identify the report as a systematic review, meta-analysis, or both.
1
ABSTRACT
Structured summary
2
Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number.
1
INTRODUCTION
Rationale
3
Describe the rationale for the review in the context of what is already known.
1, 2
Objectives
4
Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).
2, 3
METHODS
Protocol and registration
5
Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
NA
Eligibility criteria
6
Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.
3
Information sources
7
Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.
3, 4
Search
8
Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.
3, 4
Study selection
9
State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).
3, 4
Data collection process
10
Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.
3, 4
Data items
11
List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
3, 4
Risk of bias in individual studies
12
Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.
NR
Summary measures
13
State the principal summary measures (e.g., risk ratio, difference in means).
NR
Synthesis of results
14
Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I2) for each meta-analysis.
4
Risk of bias across studies
15
Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).
4
Additional analyses
16
Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.
4
RESULTS
Study selection
17
Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.
10, S1 Appendix
Study characteristics
18
For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
4, 5
Risk of bias within studies
19
Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12).
4, 5
Results of individual studies
20
For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.
4, 5
Synthesis of results
21
Present results of each meta-analysis done, including confidence intervals and measures of consistency.
4, 5
Risk of bias across studies
22
Present results of any assessment of risk of bias across studies (see Item 15).
NR
Additional analysis
23
Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]).
5–8
DISCUSSION
Summary of evidence
24
Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).
5–8
Limitations
25
Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).
4, 10 S1 Appendix
Conclusions
26
Provide a general interpretation of the results in the context of other evidence, and implications for future research.
8–10
FUNDING
Funding
27
Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review.
NA
From: Moher et al. [50]. For more information, visit: www.prisma-statement.org. NR: not reported. NA: not applicable.
\n',keywords:"gamification, education, content analysis",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/59668.pdf",chapterXML:"https://mts.intechopen.com/source/xml/59668.xml",downloadPdfUrl:"/chapter/pdf-download/59668",previewPdfUrl:"/chapter/pdf-preview/59668",totalDownloads:1785,totalViews:580,totalCrossrefCites:6,totalDimensionsCites:10,totalAltmetricsMentions:1,impactScore:9,impactScorePercentile:96,impactScoreQuartile:4,hasAltmetrics:1,dateSubmitted:"October 19th 2016",dateReviewed:"January 17th 2018",datePrePublished:null,datePublished:"June 20th 2018",dateFinished:"March 1st 2018",readingETA:"0",abstract:"Gamification has become the most popular topic of the last few years. Studies in gamification area are examined based on certain different criteria in this study and content analysis method was used in order to identify trends in this area. Web of Science were scanned through using gamification as keyword without year restriction. A total number of 313 studies were regarded as appropriate for the aim of the study and examined. It is seen that research in this area have begun in 2011 and increased every year. It is also seen that motivational theories are mostly preferred in the studies conducted in gamification area. It was determined that goal-duty, reward and progression sticks are the mostly used components as game components. It is seen that gamification applications are frequently preferred in virtual environment, simulation and augmented reality learning environments after mobile environments and in parallel with these, they are also preferred in learning areas such as public, service, food and health. Therefore, identifying different activities which could affect success in online environments, integrating these into education environment and provide these activities with theories appropriate for students’ ages for them not to lose their motivation are essential.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/59668",risUrl:"/chapter/ris/59668",book:{id:"5810",slug:"socialization-a-multidimensional-perspective"},signatures:"Senay Kocakoyun and Fezile Ozdamli",authors:[{id:"198755",title:"Associate Prof.",name:"Fezile",middleName:null,surname:"Ozdamli",fullName:"Fezile Ozdamli",slug:"fezile-ozdamli",email:"fezileozdamli@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Near East University",institutionURL:null,country:{name:"Cyprus"}}},{id:"199223",title:"MSc.",name:"Senay",middleName:null,surname:"Kocakoyun",fullName:"Senay Kocakoyun",slug:"senay-kocakoyun",email:"senaykocakoyun@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Istanbul Aydın University",institutionURL:null,country:{name:"Turkey"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Method",level:"1"},{id:"sec_3",title:"3. Results",level:"1"},{id:"sec_3_2",title:"3.1. Distribution of the studies based on research sample",level:"2"},{id:"sec_4_2",title:"3.2. Distribution of the studies based on the environments",level:"2"},{id:"sec_5_2",title:"3.3. Distribution of the studies based on theory/model/strategy",level:"2"},{id:"sec_6_2",title:"3.4. Distribution of game components, dynamics and mechanics",level:"2"},{id:"sec_7_2",title:"3.5. Distribution based on learning area",level:"2"},{id:"sec_9",title:"4. Discussion and conclusion",level:"1"},{id:"sec_9_2",title:"Supporting information",level:"2"}],chapterReferences:[{id:"B1",body:'McGonigal J. Reality is Broken: Why Games Make us Better and How They can Change the World. Penguin Publishing Group; 2011'},{id:"B2",body:'Hamari J, Koivisto J, Sarsa H. Does gamification work? A literature review of empirical studies on gamification. 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Journal of Research in Education and Teaching. 2015;16(3):125-130'},{id:"B72",body:'Calle-Martínez C, Rodriguez-Arancón P, Arús-Hita J. A scrutiny of the educational value of EFL mobile learning applications. Cypriot Journal of Educational Sciences. 2014;9(3):137-146'},{id:"B73",body:'Huber M, Hilty L. Gamification and sustainable consumption: overcoming the limitations of persuasive technologies. In: Hilty L, Aebischer B, editors. ICT Innovations for Sustain-ability. Cham: Springer International Publishing; 2015. pp. 367-385. DOI: https://doi.org/10.1007/978-3-319-09228-7_22'},{id:"B74",body:'YOK. 2016. Retrieved on January 16, 2016 from: https://tez.yok.gov.tr/UlusalTezMerkezi/tezSorguSonucYeni.jsp'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Senay Kocakoyun",address:"senaykocakoyun@aydin.edu.tr",affiliation:'
Anadolu BIL Vocational School of Higher Education, Computer Programming Department, Istanbul Aydin University, Turkey
Computer Education and Instructional Technology (CEIT) Department, Near East University, Northern Cyprus
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1. Introduction
Since its introduction during World War II most countries have come to view gross domestic product, or GDP, as their main measure of economic progress. Growth in GDP is widely seen as essential for advancing human welfare, even as the implications of this growth ever more clearly present us with existential threats, including a rapidly changing climate and dire impacts on biodiversity. With record growth have come record droughts and heatwaves. The last seven years, in fact, have been the warmest since records began in 1880 and last year, 2020, tied 2016 as the warmest year ever [1]. Wildfires across the planet are growing larger and more frequent and ever more evidence accumulates that ecosystems around the globe are collapsing [2, 3, 4, 5, 6, 7, 8, 9, 10].
Each day’s news it seems underscores the fact that there is a price to pay for our global obsession with growth and limits to what the biosphere can provide to an ever-larger global economy. As a result, the pressure for growth is increasingly being met with calls for greater sustainability. How these two things can be reconciled may be the most urgent and important challenge of our time.
This chapter will summarize the debate over the limits to economic growth beginning with a discussion of how growth is defined and why it is the focus of national economic policy. We will then review the connection between economic growth, sustainable development, and the conservation of biodiversity and examine issues surrounding the quest for sustainable development, including alternative measures of growth and alternatives to a focus on perpetual growth. We will end the chapter with a discussion of policies to help move the world onto a safer, saner trajectory focusing on the role that economic incentives can play in catalyzing necessary change and the importance of a commitment to cost-effectiveness in the design of policies to promote conservation action.
2. What growth means
The standard definition of economic growth is a sustained increase in a nation’s real (inflation adjusted) gross domestic product (GDP). GDP is the monetary value of all goods and services produced in a country each year. In recent years, real GDP growth in the U.S. has averaged around 2% which means that the economy doubles in size every 36 years [11].
2.1 Why grow?
Proponents of economic growth focus on its many benefits, including higher standards of living and the ability to devote more resources to things like health care and education. Increases in sanitation, nutrition, and longevity have all been possible due to economic growth. Since 1800, life expectancy has grown from less than 30 years to more than 70 with eradication of childhood disease and improvements in medicine and nutrition [12]. Vast changes in material abundance have also been possible due to economic growth allowing many the things that only the wealthy could aspire to in the past.
Though something we now take for granted economic growth is a very recent phenomenon. Widespread economic prosperity (as measured by GDP per capita) has only been achieved in the past couple hundred years and as shown in Figure 1, has only really taken off in the past 50 years [13].
Figure 1.
The history of Economic growth: GDP/capita, 1820–2018 [13].
The incidence of extreme poverty over this period has fallen dramatically, in rich countries and poor alike [14]. Since 1990 alone the number of people living in extreme poverty has fallen by more than 1 billion [15]. The reasons for this reduction are many but one essential element has been the increase in crop yields achieved due to massive public investments in modern agricultural research. According to IFPRI [16], the case of English wheat is typical. Whereas it took nearly a millennium for yields to go from 0.5 to 2.0 metric tons per hectare it took only 40 years to rise from 2.0 to 6.0 metric tons per hectare. Yield increases such as these for wheat, rice and other crops have led to unprecedented levels of food security for many developing countries, despite large and continuing increases in population [16].
2.2 The downsides to growth
Given its many benefits, it is little wonder that economic growth is a focus of global economic policy. Growth, however, has its costs. Environmental destruction and impacts on biodiversity are perhaps the most obvious, but there are also conflicts between economic growth and national security and international stability, and ultimately, economic sustainability itself.
Growing economies consume natural resources and produce wastes. This results in habitat loss, air and water pollution, climate disruption, and other environmental threats, threats which are becoming more apparent as economic activity encounters more and more limits. The depletion of groundwater and ocean fisheries are examples as are shortages of fresh water, and the global spread of toxic compounds such as mercury, chlorofluorocarbons, and greenhouse gases.
These conflicts are in part the result of the inescapable impact of an ever-growing human population. They are, however, exacerbated by market failures, including externalities and open-access resources, and in the case of biodiversity, the lack of markets altogether.
Externalities are the side-effects of commercial activities that impact third parties and are not reflected in the costs of production, and for this reason are “external” to the decision-making of both producers and consumers. Pollution from a factory is a negative externality. Intertemporal externalities (e.g., from climate change) impose costs on those in the future that are external to current generations. Externalities of all sorts undercut the ability of markets to produce sustainable outcomes.
Resources that are open to all without restriction, such as ocean fisheries, also invite unsustainable outcomes as is evidenced by the currently depleted state of the world’s open-access fisheries.
Biodiversity suffers from a third market failure, the fact that it is generally not traded in formal markets. Though the popular conception of overexploitation is of resources plundered by the forces of markets, the absence of a market can be equally problematic. Things with no price end up being treated as if they have no value. Such is the fate of endangered species, tropical rainforests, coral reefs, and indeed much of wild nature.
Environmental impacts, of course, are not unconnected to society at large. Things like climate change and the extinction crisis have economic impacts and these in turn can threaten national security and international stability. Such threats are often made worse by inequality. Not everyone benefits equally from growth and some have arguably not benefitted at all. The problem of growing inequality is certainly an issue in the U.S. where the nation’s top 10 percent now average more income than the bottom 90 percent [17]. But it is also clearly a problem globally. Sub-Saharan Africa is a case in point (see also, Figure 1). Although the poverty rate there has fallen in percentage terms since 1990, it has not fallen fast enough to keep pace with population growth [18]. As a result, the number of poor in that region continues to rise and now accounts for nearly two thirds of the world’s total population in extreme poverty [18].
Climate change, resource scarcity, and environmental degradation generally are certain to accentuate such inequalities in the future with unavoidable impacts on social unrest, national security, and international stability. The national security implications of these issues were starkly presented in a recent report commissioned by the U.S. Army [19]. According to the study, America could face a grim series of events triggered by climate change involving drought, disease, failure of the country’s power grid and a threat to the integrity of the military itself, all within the next two decades. The report also projects that sea level rise in the future is likely to “displace tens (if not hundreds) of millions of people, creating massive, enduring instability” and the potential for costly regional conflicts [19]. The report cites in particular the role that drought has played in sparking the civil war in Syria and the potential for tensions stemming from sea level rise and large-scale human displacement in Bangladesh.
All of the above issues have clear implications for economic sustainability – a healthy environment and international stability, after all, are the foundations for a healthy economy. We need healthy soils for agriculture, healthy oceans for fisheries, clean air and water and a stable political environment for international trade, all of which are threatened by unrestrained growth [20].
3. The quest for sustainable development
Increasing awareness of the limitations of growth has led to much discussion of sustainable development. This concept is most commonly associated with a report published by the World Commission on Environment and Development in 1987. In that report sustainable development is defined as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” [21]. Since the publication of this report, the idea of sustainable development has gained a solid footing in the popular imagination. An important landmark in this regard is the signing of the so-called Rio Declaration at the Earth Summit in 1992 in which 192 nations committed themselves to a detailed agenda for sustainable growth and development [22].
Despite its popularity, the precise meaning of sustainable development is somewhat elusive. From an economic perspective a simple definition might be that growth should proceed so long as the marginal benefits exceed the marginal costs (Figure 2). Marginal cost is the cost of a small increase in an activity and marginal benefit is the additional benefit from that increase. Figure 2 shows the marginal costs and benefits of growth in GDP. Since the benefits tend to decline and the costs to rise with additional GDP growth, the sweet spot is to grow until the marginal costs are exactly equal to the marginal benefits. Any increase in GDP up to this point is “economic growth” whereas growth in GDP past this point, where costs rise above benefits is uneconomic [20].
Figure 2.
Economic and uneconomic growth in GDP [20].
3.1 The problems with GDP
Such definitions are all well and good, but problems arise in discerning when and where costs begin to exceed benefits. This, in turn, is made more difficult by the way in which we measure growth. Ironically, GDP, our global standard measure of growth, was never intended as a measure of costs and benefits. Instead, it is simply a gross tally of market output with no distinction made between output that adds to well-being and output that diminishes it. Instead of separating costs from benefits GDP assumes that all monetary transactions by definition add to social welfare [23].
GDP also excludes everything that happens outside formal markets and therefore ignores many things that clearly benefit society such as volunteer work and unpaid work in households like childcare and elder care. Much of the value of environmental services is ignored as well.
As shown in Box 1, this method of accounting leads to some very counterintuitive results, including the fact that GDP increases with polluting activities and then again with clean-ups, crime and natural disasters are treated as economic gain, and the depletion of natural capital is treated as income [23].
The shortcomings of GDP are particularly significant with regard to biodiversity. As shown in Box 2, biodiversity underpins virtually all economic activity. Yet, it is not explicitly accounted for anywhere in GDP. In many cases, biodiversity is an unvalued input (e.g., crop and livestock genetics) into an output (food) whose value is counted in GDP. And while the connection between the two is clear in a general sense, the impact of added growth on the unvalued input is not. Worse, to the extent that further growth depletes the biodiversity we depend on it is counted as adding to national income. And since the benefits of avoiding the depletion of biodiversity often accrue to others (either in full or in part) there is little incentive for individuals or governments to invest in its conservation.
3.2 Moving beyond GDP
Faced with the obvious limitations of GDP, many countries are now looking for alternative ways of measuring social and economic health, including adjustments to measures like GDP and the development of alternative indicators.
GDP treats crime, divorce, and natural disasters as economic gain.
GDP counts all monetary transactions as positive. So, crime, divorce, and natural disasters, like fires and hurricanes, are all counted as economic progress.
GDP ignores the non-market economy of households and communities.
GDP ignores all activities that take place outside the market economy, including volunteer and home-based work such as childcare and elder care.
GDP treats the depletion of natural capital as income.
GDP treats the depletion of both natural and man-made capital as income rather than depreciation. So the more a country depletes its natural resources the more it adds to GDP.
GDP increases with polluting activities and then again with clean-ups.
GDP counts pollution as a double benefit to society by first including the economic activity that leads to pollution and then the cost of clean-ups.
GDP takes no account of income distribution.
GDP ignores income inequality. In the U.S. GDP has grown more than seven-fold since 1980 [24]. GDP presents this growth as a benefit to all, yet the country’s three richest men now own more wealth than the bottom half of the country combined [25].
3.2.1 GDP adjustments
A basic problem with GDP and other conventional measures is that they are measures of output, not welfare. A true measure of welfare would rise when societies are better off and decline when they are worse off [26]. One of the limitations of GDP as a welfare indicator is that it does not take account of the depletion of either natural or man-made capital. As a result, spending to replace worn-out machinery is treated as income even though it adds nothing to the existing stock of machinery. Similarly, consumption and pollution that depletes society’s store of natural capital is also incorrectly treated as income.
Box 2.
Biodiversity underpins Economic activity, human health and wellbeing.
Food Security and Global Nutrition – Food production depends on biodiversity for plant and animal varieties, pollination, pest control, and disease regulation [27]. Indigenous produce adapted to local conditions in countries around the world serve as a basis for improved plant varieties and as a buffer against a changing climate [28, 29].
Disease Regulation – Lowered biodiversity and habitat fragmentation can lead to increased disease transmission and higher healthcare costs [30, 31]. Medicinal plants and manufactured pharmaceuticals rely on biodiversity. The diversity of plants and animals is an essential source of molecular compounds needed for future drug discovery [32].
Business and Livelihoods – More than half the world’s GDP is moderately or highly dependent on nature, including nature-based tourism and recreational hunting and fishing [28, 33]. Fisheries, forestry and agriculture provide trillions of dollars annually in economic activity [34].
Protection and Replenishment – Biodiverse ecosystems provide natural buffers against storms and floods, water purification, soil formation and organic waste disposal [28]. Biodiversity underpins forests, grasslands, and agricultural systems essential for carbon storage and climate regulation [28].
The former limitation can be addressed by simply subtracting an estimate of capital depreciation from GDP. This is now done as a matter of course in many countries, including the U.S. in what is called net domestic product (NDP) [35]. Adjusting for GDP’s treatment of natural capital, however, is more complicated since there are uncertainties about precisely which cost items to deduct from GDP as well as how these items should be valued [36].
Nevertheless, in an effort to redress this shortcoming, economists have developed an alternative measure called the genuine progress indicator (GPI) which subtracts the value of natural capital used in production as well as the costs of negative externalities from GDP [37].
GPI also attempts to address other limitations of GDP by broadening the conventional accounting framework to include the benefits of volunteering and household labor as well as the impact of a variety of other factors, including crime, health care, income distribution, and leisure [37]. In effect, the GPI aims to serve as an indicator of sustainable welfare by focusing on the value of two basic things: activities that actually make us better off and those that are likely to be sustainable over the long term [37, 38].
Not surprisingly, GPI tells a rather different story than GDP of the recent history of economic growth. In an exhaustive study of the difference between the two indicators Kubiszewski, et al. [39] looked at 17 countries for which GPI data are available over the period 1950–2005. As shown in Figure 3, whereas GDP/capita rises continuously over this period, GPI/capita levels off in the late 1970s and begins to decrease slightly thereafter.
Figure 3.
GDP vs. GPI (genuine Progress indicator), 1950–2005 [39].
3.2.2 Alternative indices
Despite the theoretical appeal of the GPI, it too has limitations. Uncertainties about what costs and benefits to include and how they are valued tend to make these kinds on indices ill-defined. There are also unavoidable problems with trying to summarize how well a society or economy is doing using a single number.
These issues have given rise to specialized indices (e.g., of ecological health or happiness) as well as a dash-board approach involving selected indicators that allow societies to better track the things they really aspire to.
One specialized index (the Living Planet Index) measures the state of global biodiversity based on population trends of vertebrate species from around the world. As shown in Figure 4, the most recent index shows an average 68% decline in the abundance of 4,392 mammal, bird, fish, reptile, and amphibian species from 1970 to 2016 [40]. Some groups are doing much worse. Freshwater populations have declined by an average of 84%, with regional declines as high as 94% (in Latin America). These startling reductions underscore the extent to which GDP as a standalone indicator is masking the impacts of economic growth.
Figure 4.
The global living planet index (LPI) shows a 68% average decline between 1970 and 2016 [40].
An alternative to using a single index is the so-called dash-board approach, involving what are sometimes called sustainable development indicators. This approach seeks to go beyond measuring simply material wealth to focus on a broad range of indicators of the quality of life and environmental health.
One example of this approach is the Better Life Initiative [41] developed by the Organization for Economic Cooperation and Development (OECD), a group of 37 mostly rich countries. This initiative recommends 11 indicators that the OECD suggests as essential to well-being in terms of material living conditions (housing, income, jobs) and quality of life (community, education, environment, governance, health, life satisfaction, safety and work-life balance) [http://www.oecdbetterlifeindex.org/#/45555545544].
At present, these indicators – which have been developed for all 37 OECD member countries – reflect only current well-being but in the future the organization expects to complement these with indicators describing the sustainability of well-being over time.
3.2.3 Concepts over numbers
A common shortcoming of all the above indicators is complexity. One reason for the power of GDP, despite its flaws, is simplicity. Up is good, down is bad, and even though a single, modified index like the GPI shares in this advantage, its usefulness as a measure of progress (or peril) is much diminished if it is unlikely to be accepted as a standard.
In response to this dilemma, some have opted for advancing concepts rather than numbers to help inspire and guide in the development of policies that will ultimately be needed to move us in the right direction. Two ideas worth mentioning in this regard are the steady state economy and doughnut economics.
The idea of a steady state economy is most closely associated with the work of economist Herman Daly, one of the co-founders of the journal Ecological Economics. According to Daly, a steady state economy seeks to respect the bounds of sustainability by keeping GDP and resource use stable [42]. As measured by GDP, an economy is either growing, stable or in recession. Since neither economic growth nor recession is sustainable, a steady state economy is the only sustainable prospect and is therefore the “only appropriate policy goal for the sake of sustainability” [42].
Proponents of the steady state emphasize that it should not be confused with economic stagnation which, they say, is the result of a failed growth economy whereas a steady state economy seeks to balance the lack of traditional growth with efforts to distribute wealth so as to broaden economic security [43].
Doughnut economics, the creation of economist Kate Raworth, is in many ways a popularized version of Daly’s steady state economy. Both authors reject the idea that perpetual growth is a viable option and instead call for maximizing social welfare within the physical and ecological limits of the planet. According to Raworth, the goal of economic activity should be to “meet the needs of all” while respecting planetary boundaries [44]. Raworth uses a doughnut, i.e., a disc with a hole in the middle, as her visual framework in which the inner ring represents society’s social foundation and the outer ring its environmental ceiling (Figure 5). Between the two is what Raworth calls an “environmentally safe and socially just space in which humanity can thrive” [44].
Figure 5.
The doughnut of social and planetary boundaries [image credit: Kate Raworth and Christian Guthier] [44].
4. Policies to take us there
The above discussion of how we define and measure sustainability, of course, begs the question of how we get from here to there. Clearly, a part of the answer lies in the measures and definitions themselves. We cannot correct problems if our measures conceal them, and we will never achieve sustainability if we do not define it as an explicit objective.
Nevertheless, this still leaves the difficult work of developing policies to help promote more sustainable outcomes. Experience and the existence of market failures suggests that we cannot leave solutions to the market alone. That said, it would be a mistake to underate the potential for productively using market forces in our search for solutions. Policies based on economic incentives in particular offer an extremely powerful and effective set of options.
Two examples in areas that matter to biodiversity are conservation agreements and carbon pricing. Both illustrate how incentive-based policies can help provide simple, cost-effective, and scalable solutions to environmental problems.
4.1 Conservation agreements
Conservation agreements are performance-based agreements in which resource owners commit to a concrete conservation outcome – usually the protection of a particular habitat or species – in exchange for benefits designed to give them an ongoing incentive to conserve [45]. The type of benefits provided vary but can include technical assistance, support for social services, employment in resource protection, or direct cash payments.
One of the great advantages of this approach is that the terms of agreements are flexible and can therefore be tailored to a particular setting. This flexibility makes conservation agreements a very scalable approach that can be implemented on private and indigenous lands outside traditional protected areas as well as on lands managed by national governments. In addition, whereas the creation of a traditional park or protected area requires a long, complex political process, conservation agreements, as a market-based approach, make park creation more akin to a standard business transaction, and this, in turn, makes park creation much more rapid and efficient.
Since conservation agreements are a voluntary approach that addresses the underlying costs of conservation they are more politically acceptable than forced buyouts or eminent domain and are also often less expensive than other approaches since they focus on opportunity cost which in many cases is extremely low, particularly in developing countries [46].
Conservation agreements were first piloted in 2001 in the context of a timber concession in Guyana [45]. Since then, they have been implemented in a wide variety of settings in roughly 20 countries around the world [47]. Examples include agreements focused on particular species as well ecosystems such as coral reefs, mangroves, and in the Solomon Islands, the largest uninhabited island in the South Pacific [47, 48].
4.2 Pricing carbon
Carbon pricing is another example of an incentive-based policy that relates to biodiversity. While this approach does not target biodiversity directly, it is perhaps the most important single policy affecting all life on Earth. When it comes to conservation, and so much else, unless we effectively tackle climate change very little else will matter.
Although there are many ways of putting a price on carbon, by far the simplest and most effective is a tax imposed on fuel suppliers (e.g., oil and gas producers). Once taxed, fuel suppliers raise their prices and in this way the higher prices ripple through the whole economy. There is no way to evade the tax and there is nothing to monitor or enforce (other than whether energy producers pay their taxes). Across the economy the cost of energy-intensive goods and services would rise giving both businesses and consumers an incentive to conserve.
One of the many advantages of a carbon tax is that it ensures that emission reductions are achieved at least cost to society. The reason is that unlike regulations that require everyone to adopt a particular technology or reduce their emissions by a certain amount, carbon taxes allow for the fact that some entities can reduce their emissions at a lower cost than others. This flexibility offers the opportunity for substantial cost savings.
Regulations alone, for example, can be twice as expensive as a carbon tax per ton of carbon abated while reducing far fewer emissions [49]. Similarly, subsidies (e.g., for electric vehicles) are unavoidably wasteful since they cannot target those who will only be motivated to buy because of the subsidy. If a tax credit of $7,500 convinces only one in four people to buy a hybrid electric vehicle, for example, the effective cost of the incentive is four times the subsidy or $30,000 – more than the price of many plug-in hybrids [50]. Such subsidies also tend to disproportionately benefit high-income households and while hybrids themselves emit less carbon than conventional cars, if the source of power used to charge them comes from coal they will raise carbon emissions rather than reduce them [51].
In addition to being less expensive, carbon taxes have several other important advantages. To begin, the cost of the tax is clearly known ahead of time. If the cost varies, as is true with cap and trade – the program used in several U.S. states – it makes it difficult for business (and consumers) to plan and therefore undercuts incentives to make long-term investments in efficiency.
Other options for pricing carbon are also more administratively burdensome and less transparent and often address only a subset of emissions. Cap and trade, for example, typically covers only electric utilities, which in the U.S. leaves out nearly three-quarters of total carbon emissions [52].
Most carbon tax proposals also now involve offsetting rebates so they do not disadvantage the poor who spend a larger percentage of their income on energy. Many proposals, in fact, would leave the majority of households better off with the tax than without it. In effect, such a “tax” would pay people for doing the right thing.
An important adjunct to a carbon tax is a UN program called REDD – Reducing Deforestation and Forest Degradation. REDD is a global effort designed to break with historic trends of increasing deforestation and greenhouse gas emissions by offering countries a financial incentive for forest conservation [53]. Since deforestation is the second largest anthropogenic source carbon emissions any realistic plan for addressing climate change must include efforts to halt the loss of tropical forests [54].
REDD takes advantage of the fact that reducing emissions anywhere on the globe has the same beneficial impact on slowing climate change. Reducing emissions through REDD therefore offers a means for offsetting emissions of industries that have no other option for meeting their climate commitments. For this reason, airlines around the world who have committed to being net-zero emitters in coming decades are expected to be major future funders of forest conservation through REDD [55].
Happily, protecting tropical forests is one of the least cost ways of reducing carbon emissions [56, 57]. REDD therefore has the potential for simultaneously reducing the cost of fighting climate change while providing a powerful incentive for protecting biodiversity.
4.3 A lack of environmental support
Given their advantages for conservation one might well expect that the three policies discussed above would be popular with environmentalists. In fact, all three policies have faced significant environmental opposition. Conservation agreements have received a great deal of favorable media attention but apart from modest investments by the organization that first developed them, they have largely been ignored by the international conservation community. This is in part a reflection of the fact that “paying for conservation” is regarded by many as a foreign concept, or worse, a dangerous precedent that “commodifies” nature and risks making all conservation efforts more expensive.
But it also reflects an important underlying incentive that shapes the conservation establishment. After years of strong popular support, the budgets and staff of all the major international conservation organizations have grown to the point where conservation has become an extremely expensive undertaking, one that depends critically on continued success in fundraising. And that, in turn makes for resistance to changes in tactics that would funnel money away from existing staff (even to laudable objectives like providing resource owners with an ongoing incentive to conserve). In the language of economics, the opportunity cost of supporting this kind of incentive-based conservation is the funding not going to current operations.
Carbon taxes have suffered from a similar lack of support. Part of the problem in this case is that taxes in general are an unpopular approach. But they have also suffered from competing agendas and a basic lack of understanding as illustrated by the fate two carbon tax bills in the U.S. state of Washington. The first was a revenue neutral bill that included tax cuts and rebates to offset the impact of higher prices from the carbon tax. This bill was defeated by an unusual coalition of oil interests and environmentalists. The later felt that the money collected by the government should be used to offset the impact of the tax on the poor (even though that is exactly what the rebates would have done) and to fund investments affecting climate, communities, and racial equity [58].
To accommodate these concerns, the second bill included no offsetting rebates and instead called for using the tax revenue to support a dedicated fund focused on the environment and social justice. In addition, the bill called for reducing the carbon tax by half to lessen its impact on prices. In effect, these changes made the revised bill both more regressive and less effective in reducing carbon emissions. Despite these “improvements”, this bill was also defeated, this time by voters who objected to the added tax and the fact that it was being used to fund what the Seattle Times called a grab bag of “special interest payouts” [59].
The UN REDD program has also faced environmental objections, in this case based on concerns over the long-term security of emission reductions in developing countries and the fact that offsets allow polluters to avoid reducing their own emissions by paying for cheaper emission reductions elsewhere [60].
5. Summary and conclusion
The past two centuries of economic growth have provided the world with many benefits. Our lives are longer and healthier with more leisure and shorter workweeks. Childhood diseases that afflicted our parents are largely a thing of the past. The creative explosion of the last few decades has yielded advances in medicine, the arts, technology and more. All these things are the benefits of economic growth.
There are, however, downsides to economic growth that put our past progress and the future of life in jeopardy. Although global economic policy is still strongly wedded to growth in GDP there is increasing recognition that this is not a sustainable situation. Blindly promoting ever more growth without seeking to address market failures and impacts on the environment is clearly a prescription for trouble. The question is how to moderate these impacts while still maintaining a focus on advancing economic security and the quality of life.
Part of the answer to this question is in developing better indicators of how economic activity is affecting the things we care about. Having a global standard measure like GDP that ignores the value of nature and counts both pollution and clean up as progress is certain to steer us in the wrong direction. Dethroning GDP and work on replacements are worthy endeavors. Measures of impact, though, even at their best, are better at informing us of the need for change than in incentivizing specific changes. They still leave us with the hard work of developing appropriate policies for the future.
How we proceed in this regard will make a difference. Unconstrained markets are not likely to produce a happy ending, but this does not mean that we should ignore the potential for using markets and incentives in our search for solutions. The same forces that are driving us in the wrong direction can be harnessed and channeled in directions that will greatly enhance the potential for sustainable outcomes.
This is particularly true in the case of policies designed to address threats to biodiversity. Indeed, in the case of two important policies, carbon taxes and conservation agreements, ignoring this potential is likely to come at a price. Compared to a carbon tax, standards and subsidies could double the cost of dealing with climate change and rejecting the use of incentives in conservation agreements and REDD could jeopardize whether forests are saved at all.
The good news is that we have some extremely simple and powerful tools at our disposal. A single, small change in the tax code can reorient the entire economy away from carbon. And conservation agreements and REDD can be flexibly implemented almost everywhere they are needed. While funding these efforts will not be inexpensive there is ample global willingness and ability to pay for conservation and no shortage of those in a position to conserve who are willing to accept payment.
The challenges are great, but many of the tools needed to address them are at hand. We need only choose to put them to use.
\n',keywords:"Biological diversity, economic development, Sustainability, GDP, Genuine Progress Indicator, conservation agreements, carbon taxes",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/77935.pdf",chapterXML:"https://mts.intechopen.com/source/xml/77935.xml",downloadPdfUrl:"/chapter/pdf-download/77935",previewPdfUrl:"/chapter/pdf-preview/77935",totalDownloads:144,totalViews:0,totalCrossrefCites:0,dateSubmitted:"March 8th 2021",dateReviewed:"July 7th 2021",datePrePublished:"August 8th 2021",datePublished:null,dateFinished:"August 8th 2021",readingETA:"0",abstract:"A growing economy has long been regarded as important for social and economic progress. And indeed, much of what we value in society is the product of economic growth. It is becoming increasingly clear, however, that growth cannot continue forever and that there is a price to pay for our failure to chart a more sustainable path. This chapter examines the conflict between our global obsession with growth and the conservation of biological diversity. The chapter begins with a discussion of what growth means and why it is the focus of global economic policy. We then review the connection between economic growth, sustainable development and the conservation of biological diversity and examine issues surrounding the quest for sustainable development, including how growth is measured and why there is a need to develop alternatives measures of growth and alternatives to a focus on perpetual growth. The chapter concludes with a discussion of the role that economic incentives can play in helping to catalyze necessary change and the importance of a commitment to cost-effectiveness in the choice of policies to promote conservation action.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/77935",risUrl:"/chapter/ris/77935",signatures:"Richard E. 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The quest for sustainable development",level:"1"},{id:"sec_5_2",title:"3.1 The problems with GDP",level:"2"},{id:"sec_6_2",title:"3.2 Moving beyond GDP",level:"2"},{id:"sec_6_3",title:"3.2.1 GDP adjustments",level:"3"},{id:"sec_7_3",title:"3.2.2 Alternative indices",level:"3"},{id:"sec_8_3",title:"3.2.3 Concepts over numbers",level:"3"},{id:"sec_11",title:"4. Policies to take us there",level:"1"},{id:"sec_11_2",title:"4.1 Conservation agreements",level:"2"},{id:"sec_12_2",title:"4.2 Pricing carbon",level:"2"},{id:"sec_13_2",title:"4.3 A lack of environmental support",level:"2"},{id:"sec_15",title:"5. Summary and conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'NASA. 2020 Tied for Warmest Year on Record, NASA Analysis Shows [Internet]. 2020. [cited 2021 Jun 6]. https://www.nasa.gov/press-release/2020-tied-for-warmest-year-on-record-nasa-analysis-shows.'},{id:"B2",body:'Patel, Six Trends to Know about Fire Season in the Western U.S. [Internet]. 2019. 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Conservation agreements as a tool to generate direct incentives for biodiversity conservation. Biodiversity. 2010. (11):5-8.'},{id:"B47",body:'CI. What on Earth is a ‘Conservation Agreement’ [Internet]. Conservation International. 2021. [cited 2021 Jun 6]. https://www.conservation.org/blog/what-on-earth-is-a-conservation-agreement'},{id:"B48",body:'CAF. Conservation Agreement Fund [Internet]. 2021. [cited 2021 Jun 6]. https://conservationagreementfund.org/projects/'},{id:"B49",body:'Rossetti, P, Bosch, D, Goldbeck, D. Comparing effectiveness of climate regulations and a carbon tax [Internet]. Unpublished research report. American Action Forum, Washington, D.C.; 2018. [cited 2021 Jun 6]. Available from: https://www.americanactionforum.org/research/comparing-effectiveness-climate-regulations-carbon-tax-123/#ixzz6wCB4GgcU'},{id:"B50",body:'Metcalf, GE. On the economics of a carbon tax for the United States [Internet]. Brookings Institution. Brookings Papers on Economic Activity. 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