American Journal of Computer Science and Engineering Survey Open Access

Identifying and Prioritizing Gamification Success Factors in Online Marketing

Mohammad Zand^* Department of Computer Science, Kharazmi University, Tehran, Iran
^*Correspondence: Mohammad Zand, Department of Computer Science, Kharazmi University, Tehran, Iran, Email:

Received: 02-Jul-2024, Manuscript No. IPACSES-24-20863; Editor assigned: 04-Jul-2024, Pre QC No. IPACSES-24-20863 (PQ); Reviewed: 18-Jul-2024, QC No. IPACSES-24-20863; Revised: 11-Jan-2025, Manuscript No. IPACSES-24-20863 (R); Published: 18-Jan-2025, DOI: 10.36648/2349-7238.25.13.37

Keywords

Gamification; Online marketing; Success factors; Digital marketing strategies; Meta-synthesis; Motivational program

Introduction

The term gamification was coined by Nick Pelling in 2002, but it wasn't until the second half of 2010 that the term was widely used. Companies use gamification as a strategy to engage consumers and customers with interesting game-like mechanisms and incentives aimed at advertising, marketing, engagement and customer loyalty. More than 350 companies have launched large-scale gamification projects since 2010 and from 2012 to 2013 alone, consulting firms Deloitte, Accenture, NTTData and Capgemini began efforts to target Fortune 500 companies with gamification [1]. Gamification uses game design elements in non-game contexts to motivate consumer engagement. It has become popular in marketing activities, with leading companies increasingly integrating gamification in their strategies. The global gamification market was valued at $10.19 billion in 2020 and is estimated to reach $38.42 billion by 2026, aiming to provide economic, motivational and social benefit. A gamification is a new approach that is used in cases such as education, health and human resources in marketing and business and companies spend their resources on this and use experts for this [2]. Some of the benefits of using gamification in e-marketing include increasing site visits, increasing advertising effectiveness, increasing sales, obtaining background information from users, collecting primary data, etc. [3]. But this technology, like other new technologies, faces its problems, such as being new, lack of consensus among experts in the definition, weak design and successful implementation [4].

Nowadays, electronic (internet) marketing has become one of the most important categories [5]. Therefore, many businesses use the Internet and other electronic media in their marketing activities. Gamification is one of the new tools that can help improve and optimize the online marketing funnel, but the biggest problem that gamification projects face is in the field of implementation and design [6]. On the other hand, companies are facing a generation called the third-millennium generation, who have the greatest desire to use technology compared to their previous generations. This generation is the first large group of the geographic community whose biggest means of entertainment is games, so marketers who want to communicate with this generation should consider new approaches [7]. Gamification in online marketing has been found to influence consumer motivation and behavior and this impact can be sustained through effective planning [8]. Gamification is considered a hot and exciting topic for research due to its relative novelty and very fast growth [9].

Despite the high potential of gamification, currently, most companies do not implement it properly and cannot create the necessary motivation in their users [10]. 80% of gamification projects fail and do not succeed as they should. Gamification projects include the financial and time capital of companies and institutions and marketing, especially online marketing, is very important, so identifying the success factors of gamification helps to improve gamification projects. In recent years, this phenomenon is also a new issue in Iran and companies are looking for the optimal use of this technology, but many times, even using this trump card, they cannot succeed as they should. Implementation of gamification is important. It has a high target audience attraction and can lead to behavior change, development of communication, loyalty and an increase in visits to products or services. Therefore, the purpose of this research is to identify and rank the success factors of gamification in online marketing and provide a model for these factors through the examination of numerous gamification projects. Considering that not much research has been done on this topic in Iran, the results of this research can make an important contribution to the best possible implementation of gamification projects by gamification and marketing specialists to achieve maximum results with minimal resources. The lack of experience in the field of gamification implementation as well as its maintenance and sustainability, the lack of developed theories and the lack of a guiding model are issues that appear in the field of gamification. Also, one of the biggest challenges faced by gamification specialists is to keep players in the system for a long time attract them to the system and drive them towards loyalty. Therefore, the other importance of this research is from the point of view that it can introduce new dimensions of factors that can lead to the improvement of the gamification system and finally online marketing.

In the qualitative phase of the research, the main indicators related to gamification were extracted and coded by reviewing the literature and the meta-combination method. Then, the initial model of gamification success factors in online marketing was presented. In the quantitative phase, the presented model was assessed through questionnaires and using PLS software and the final framework was presented. The following questions have been answered in this research:

First question: What are the factors affecting the success of gamification in online marketing?

Second question: What structure does the structural pattern of the identified factors follow?

Third question: How much is the validity of the presented model?

Fourth question: What is the priority of the identified factors?

Materials and Methods

Gamification

Gamification utilizes game-based mechanics and game thinking to engage individuals, incite action, facilitate learning and address problems. Gamification is the use of game design elements and techniques in contexts other than games and the combination of game elements (points, badges, leaderboards) to motivate and engage users. It also includes three main parts: 1) Implemented motivational abilities, 2) Resulting psychological consequences and 3) Subsequent behavioral consequences. In defining gamification, they highlight the role of gamification in invoking the same psychological experiences that games (in general) do. Also, games should use gamification abilities. Gamification can be defined as the innovative use of game design elements to increase the interactivity of company products and services. Gamification increases customer value and can increase favorable consumption, loyalty and product patronage. In addition, it is defined as a process to enhance services with (motivational) capabilities to invoke more game experiences and behavioral outcomes. The gamification experience by customers can create a sense of pleasure, happiness and excitement while interacting with the company's activities such as shopping or checking the website. When customers experience a sense of pleasure, happiness and excitement in purchasing or interacting with the company, it forms a sense of attraction, creating an obsession in interacting with the brand. Therefore, they sometimes tend to buy things for no reason. Gamification offers positive effects; however, these effects largely depend on the context in which gamification is implemented and on the users who use it.

Gamification in Marketing

The concept of gamification and its mechanisms in non-game contexts has become a rapidly emerging method in marketing. Marketing inherently involves persuasion, motivation and manipulation, making gamification a great potential tool. Online marketing has utilized gamification to achieve various goals, including increased customer engagement, brand loyalty and desired user actions. A key motivation for gamification is to leverage game mechanics and elements in non-game contexts to capture customer engagement during product or service use. Understanding the customer experience allows organizations to create offerings with greater utility value compared to competitors, enabling them to outperform. Therefore, by researching these success factors, marketers can apply modern concepts like gamification. Considering the importance of gamification activities in online stores, successful online marketing strategies involve finding ways to increase brand appeal and value. Gamification not only values the customer's gaming and entertainment experience but also supports the creation of functional value. With the increasing use of websites for purchases, gamification elements influence both customer willingness to interact with marketers and their brand loyalty to products that use marketing gamification. Factors such as customer interaction with gamification and the gamified purchase experience positively affect both attitude toward gamification and brand loyalty. This study shows that marketing gamification, when used correctly, can be a powerful tool to attract and retain customers.

Advantages and Challenges of Gamification

Gamification is increasingly used as a design strategy when improving various behavioral outcomes in online retailing. Satisfaction has a positive and significant effect on brand love and in turn, on desirable consumer behaviors (i.e., brand loyalty, positive word of mouth and resistance to negative information). Gamification can provide numerous benefits such as increased user engagement, increased brand loyalty and improved customer behavior for online marketing campaigns. Gamification elements can make interactions with a brand more enjoyable and motivating and lead to more user engagement. Positive gamified experiences can strengthen brand loyalty and encourage repeat interactions and can be used to encourage desired customer behaviors such as product purchase, social sharing, or content creation. However, implementing gamification effectively requires careful consideration. Some potential challenges are poor design, extrinsic versus intrinsic motivation and a focus on mechanics over goals. Mechanisms that are poorly designed or not aligned with target audience preferences can backfire and lead to disengagement. Relying too much on extrinsic motivation (e.g., points, badges) can undermine intrinsic motivation (e.g., genuine interest) and prioritizing game elements over marketing goals can lead to a gamified experience which does not reach the desired results.

Factors Affecting the Success of Gamification in Online Marketing

Gamification should be aligned with clear marketing goals and seamlessly integrated into the user experience. It is also important to understand the basic game mechanics (scores, badges) and dynamics (reward systems, challenges). Gamification elements must be strategically selected and implemented to achieve specific marketing goals and adapting these elements to the target audience and marketing context is essential. Effective gamification contributes to the psychology and motivational factors of the user such as achievement, competition and social interaction. Identifying the motivations and preferences of the target audience is very important for designing gamified experiences because users must have a clear understanding of the goals and a sense of progress in the gamified experience. Rewards provided in the framework of gamification should also be considered valuable and relevant to the target audience.

To explain the theoretical background of the research questions, first the available sources and background were reviewed so that by mentioning the amount of knowledge development that has occurred so far, it is possible to develop and explain a clear theory in this research. Therefore, Table 1 is presented to check the relevant background.

Table 1: The summary of relevant studies.

While gamification has been a topic in previous research, there is still a noticeable gap in the existing body of knowledge related to gamification within the field of marketing. Within this framework, prior studies have explored this subject matter from various perspectives. Some studies have focused on the gamification and branding. While some studies have focused on gamification and motivation. We have other studies on gamification from different perspectives. For example, summarize the studies previously conducted on the use of gamification in education. Moreover, study gamification and customer experience in online retail and while, in their research, aimed to investigate how gamified CRM projects influence consumers’ favorability. However, limited studies have considered this concept from the perspective of gamification success factors in marketing and no research has been identified that has examined this concept. Based on this, the current research seeks to identified and prioritized gamification success factors in online marketing. By gathering, organizing and examining existing knowledge on the topic and presenting it in a structured manner, this review can also be useful for professionals who want to improve their understanding of gamification implementation.

Methodology

In this research, a descriptive approach, a combination of quantitative and qualitative methods is used to answer the research questions. In descriptive research, the researcher looks for the nature of the subject and wants to know how the phenomenon, variable, object or material is. The current research method is practical in terms of the type of goal because its results are provided to start-up businesses so that they can use its results for their business development. First, by reviewing the literature of articles related to gamification in the last 20 years and using the seven-stage meta-synthesis method of Sandlowski and Barroso, the main indicators related to gamification were extracted and coded. In the next step, the extracted codes were grouped according to the semantic affinity and concepts created in a similar category, and the initial model of online marketing gamification success factors was presented. The validity and reliability of the model extracted from the meta-synthesis method were examined through interviews with 8 experts in this field to remove indicators not related to gamification. Sandlowski and Barroso's seven-step meta-synthesis method, which is also called "exploratory synthesis analysis", is a structured framework for qualitative text analysis and concept extraction in meta-synthesis research. This method consists of seven steps as follows: Setting research questions, a systematic review of texts, searching and selecting sources, extracting information, analyzing and combining findings, quality control and presentation of findings. Finally, the framework of gamification success factors in online marketing was presented.

The method of collecting information in the first stage of library studies and its tool was a survey, where articles and books related to the research subject were studied inside and outside the country. In the next step, a field survey was used to determine the validity and reliability of the presented framework and its tools were a semi-structured interview and a closed questionnaire. In the library studies section, the review of gamification literature and its frameworks from the statistical community included all scientific and authoritative articles in scientific and specialized databases published in the last 20 years. Also, in the field section, the statistical population included all experts and practitioners in the field of gamification who had at least 4 years of executive work experience in this field or who owned at least one book or had articles in designing the marketing structure of organizations. The sampling method in the non-probability library section was targeted and the sample number was 79 articles and 8 books related to gamification and its frameworks. Also, the method of sampling in the field and determining the validity and reliability of the framework, non-probability judgment and the number of available samples were 8 experts in the field of gamification.

In the quantitative phase of the research, a Likert questionnaire was prepared using the indicators of the provided framework. The questionnaire was distributed among 100 people active in the gaming industry and then the validity of the designed model was measured by confirmatory factor analysis using the SmartPLS method. The sampling method in the quantitative stage was non-probability judgmental and the sample number was 100 gamification activists due to the limited number of experts familiar with this issue. The statistical population at this stage comprises all individuals who are experts in the field of gaming, possess comprehensive knowledge of game elements and have implemented these elements in various business contexts.

The validity of the designed model was evaluated using factor analysis and SmartPLS software. To validate the selection process of the referenced experts, three control factors were employed to determine the minimum criteria for the selection of each expert. In this way, if each option has at least two entry conditions, it is selected as an expert. Based on this, three criteria were considered for selection: At least 4 years of activity in the field of online marketing businesses, at least 4 years of activity in the field of game development and game design, etc., and publication of at least one valid article in the field of research keywords. Validation of the research model was used by several experts whose characteristics are shown in Table 2.

Table 2: Characteristics of experts.

Finding

In this research, using the seven-step meta-synthesis method of Sandelowski and Barroso, 79 foreign and Iranian authoritative articles and 8 specialized books related to the game and its patterns were examined during the last 20 years. By extracting and coding the main success indicators of the game, the first research question was answered. In the next step, the extracted codes were categorized based on the semantic relations and concepts created in a framework like the classification framework and the primary success factors of the game were presented. Next, by conducting semistructured interviews with 8 experts in the games and distributing semi-structured questionnaires among them, the validity and reliability of the model extracted from the metacombination method were examined and the second question was answered. Then the final template was distributed through a questionnaire to determine the importance and ranking of the factors identified by one hundred digital marketing experts and game designers, thus the third and fourth questions were also answered.

To analyze the data, the most famous Meta-Synthesis method, namely the seven-step Meta-Synthesis Method of Sandelowski and Barroso, was used, the steps of which are given below.

First Step: Organizing the Research Questions

To start meta-composite research, these questions must be answered first: 1) What are the indicators of the studied category? 2) What are the indicators of the studied category related to each other?

Second Step: Systematic Review of Texts

In this study, a comprehensive investigation was conducted on various databases, publications and search engines from both domestic and international sources, spanning the years 1991 to 2019. Various keywords have been used to search for research articles, such as success factors, marketing, online marketing and gamification. As a result, searching and checking databases, publications and different search engines using keywords 79 articles were found.

Third Step: Searching and Choosing Suitable Articles

To select suitable articles based on the observed algorithm, various parameters such as title, abstract, content, access, content and quality of the research method have been evaluated. In this step, the researcher rejects several articles in each review, which are not examined in the metacombination process. As soon as the articles are checked for suitability with the parameters of the study, in the next step the researcher must evaluate the methodological quality of the studies. The purpose of this step is to remove articles that the researcher does not trust in the presented findings. The Critical assessment skills program is a tool that is commonly used to assess the quality of primary qualitative research studies. This tool contains 10 questions that help you understand the concept of qualitative research. It also allows the researcher to determine the accuracy, validity and importance of qualitative research studies. These questions focus on the following: Research objectives, method logic, research design, sampling method, data collection, reflexivity (includes the relationship between the researcher and the participants), ethical considerations, accuracy of data analysis, clear expression of research findings and evaluation. At this stage, the researcher gives a small score to each of these questions and then creates a form. Therefore, he can collect the points he gives to each article and easily and briefly review the collection of articles and see the evaluation results. Based on the 50-point scale of the CASP rubric, the researcher proposes the following scoring and removes any article that is lower than the good score (less than 30): Poor (0-10), average (11-20), good (21 -30), very good (31-40), excellent (40-50). Based on the points given to each article, the minimum average score given to the articles was 23 and the maximum score was 45. To select suitable articles based on the algorithm seen in Figure 1. Various parameters such as title, abstract, content, access, content and quality of the research method have been evaluated.

Figure 1: Steps of extracting articles.

Fourth and Fifth Steps: Extraction of Results and Analysis and Synthesis of Qualitative Findings

The information from the articles in this research is classified into three parts: The components and indicators of the success factors of gaming, their frequency and the reference of each article. The results of this process are shown in Tables 3-9.

Table 3: Strategy dimension: Including four concepts and sixteen codes.

Table 4: Dimension of interactions: Including three concepts and ten codes.

Table 5: Psychological dimension: Including 3 concepts and 8 codes.

Table 6: Mechanical dimension: Including ten concepts and sixty-four codes.

Table 7: Measurement dimension: Including two concepts and four codes.

Table 8: Economic dimension: Including three concepts and six codes.

Table 9: Infrastructure dimension: Including one concept and four codes.

Sixth Step: Analysis

The designed table includes 7 categories, 26 themes and 112 codes. At this stage, a semi-structured interview was conducted with 8 experts in the ield of gaming, and the results of these interviews were determined by the validity and reliability of the categorization of the codes. The results of these interviews are detailed in Table 10.

Seventh Step: Control of Extracted Codes (Validity and Reliability)

In the meta-combination or thematic analysis method, to maintain the quality of the study, the following procedures were considered: Providing clear explanations for the options available in the research, using both electronic and manual search strategies to ind relevant articles, using quality control methods, using tools CASP to evaluate studies.

During the interview with the experts, three questions were asked

• What is your definition and opinion about gamification and its use in online marketing?

• What is your opinion about the categorization of the index? Do you approve of the presented factors?

• According to the questionnaire provided about success indicators in bioassay, if you have a specific indicator in mind, please describe it?

The first question of the interview was general, the answers of which were not used in the current research. To answer the second question of the interview, a half-game questionnaire was prepared and given to the experts to check the codes and indicators of the framework and agree or express their disagreement. In this study, some of the variables from the existing codes were not con irmed by the experts and were removed. In response to the third question, experts added 42 indicators to the indicators of gami ication in online marketing, and other experts con irmed the existence of 38 indicators identi ied in the success of gami ication and rejected the others.

Table 10: Indicators added by experts.

The presentation of content has been done in two aspects. The first aspect is the use of gamification success components and indicators in the past literature, which itself leads to the validity of the framework and the second aspect, the classification of categories and codes was presented to the experts through a semi-structured interview, which they confirmed the categorizations. To confirm the reliability, the technique of creating structured processes for the implementation and interpretation of convergent interviews has been used. As a result, the reliability of this framework has been proven through interviews and its interpretation.

Eighth Step: Presentat on of Findings

In this step, based on the study of previous research the extracted codes and the identification of the main indicators, the success factors of gamification were presented as shown in Figure 2.

Figure 2: Initial model.

Validity

After completing the stages of meta-combination methodology, a designed template, and semi-structured interviews were conducted with eight experts in the field of online marketing. In these interviews, all two levels of the model were examined and some of the variables were removed from it and new components were added to it. The validity of the current model was achieved through content validity.

Reliability

Kappa index has been used to measure the reliability of the designed model. In this way, someone else, without knowing how to integrate the codes and the created concepts, has tried to categorize the codes into concepts. Then, the concepts that we have presented in the research have been compared with the concepts presented by this person. Finally, according to the number of similar concepts and different concepts, the Kappa index has been calculated. The Kappa index luctuates between zero and one. The closer this criterion is to one, it indicates that there is more agreement between the raters. Kappa calculations are shown in Tables 11 and 12.

Table 11: Kappa calculation.

Table 12: Kappa calculation.

Random agreements=(A+B)/N × (A+C)/N × (C+D)/N × (B+D)/N

Random agreements=(21+2)/26 × (21+3)/26 × (3+0)/26 × (2 +0)/26=0.88 × 0.92 × 0.11 × 0.07=0.0062

K=(Random agreements-Observed agreements)/1-Random agreements=(0.807-0.0062)/(1-0.0062)=0.8/0.99=0.808

To measure validity, there are various methods and in this research, due to the fact that the variables of the research consist of several dimensions (components), the confirmatory factor analysis test has been used. In conducting factor analysis, it should be ensured whether the data in question is suitable for factor analysis or not. For this purpose, the KMO index and Bartlett test were used. Based on these two tests, the data are suitable for factor analysis when the KMO index is greater than (0.6) and close to one and the sig of the Bartlett test is less than (0.05). The results of these tests are presented in Table 13.

Table 13: KMO and Bartlett test for questionnaire questions.

After checking the measurement model, the structural model of the research should be checked and tested. The graphical output of the research model is shown in Figure 3.

Figure 3: Coefficients of the standard path of the research conceptual model.

The numbers written on the paths represent the coefficients of the path. For the "significance test" path coefficients were calculated using the bootstrapping method and the T-Student test values. In the T-Student test, if the value is greater than 1.96, the path coefficient is significant at the 0.05 level (Figure 4).

Figure 4: T-Student test results to check the significance of path coefficients.

The output of the software was used to check the hypotheses and test the significance of the path coefficients between the variables. Path coefficients and their significance results are given in Table 14.

Table 14: The results of structural model evaluation.

Finally, according to the results obtained in the previous sections, the final model of success factors in gamification in online marketing will be as follows (Figure 5).

Figure 5: Final model of the research.

Results and Discussion

Today, with the expansion of diverse production of products, the business environment becoming more competitive and the power of consumers, it can be said that the old methods of marketing and advertising cannot by themselves significantly help manufacturers and sellers in selling their products. Gaming is one of the newest tools that can act as a catalyst in today's business world. On the other hand, with the power of the digital space in the business world, we are witnessing the growth of businesses in the online space and the competition of different industries in this context. Therefore, companies can use online gaming to grow their business, but to be successful in this space and avoid possible failures in this space, they need to have a suitable model and the factors If they recognize the success in this space, then they can survive in the competitive environment and speed up and facilitate the stages of familiarization, loyalty and sales. Considering that the success factors have not been presented in an integrated and coherent manner in the research reviewed in this study the identification and ranking of these factors and its presentation in the form of a framework that can be used by business world activists were researched and presented.

This study specifically focuses on gamification, a technique gaining popularity for enhancing marketing strategies. By identifying and ranking the success factors of gamification in online marketing, this research provides valuable insights for businesses, especially those transitioning from traditional to online platforms.

The qualitative phase of the research utilized a comprehensive Meta-Synthesis Method to review relevant literature from the past two decades. This approach allows us to systematically extract and categorize the primary success factors of gamification. The qualitative analysis was further enriched by interviews with gamification experts, ensuring the reliability and validity of the proposed model. This iterative process of refinement, through expert feedback, underscored the dynamic nature of gamification and its adaptability across different marketing contexts.

In the quantitative phase, the validated model was rigorously tested through a survey administered to a diverse group of gamification specialists and digital marketing professionals. The use of SPSS and PLS software provided robust statistical validation, confirming the hierarchical importance of various dimensions of gamification. The strategy and economic dimensions emerged as the most critical, emphasizing the need for clear objectives and sustainable financial models in gamification initiatives. The prominence of the measurement dimension highlights the necessity of tracking and evaluating gamification efforts, while the psychology and mechanics dimensions underscore the importance of engaging and motivating users. The infrastructure dimension, though ranked lowest, remains essential for providing the necessary technological support.

In this section, in general, examples of the indicators obtained during the research are presented. Therefore, in the table below, according to the research conducted in the field of the research topic, the indicators obtained during the research are compared with the results of past research. Table 15 contains all the indicators that have been mentioned in books and articles and confirmed by this research.

Table 15: Indicators found from sources and confirmed by research.

Conclusion

This study presents a validated framework for the success factors of gamification in online marketing, offering valuable insights for businesses aiming to enhance their digital marketing strategies. The identification and ranking of these factors provide a clear roadmap for companies to follow, ensuring a structured and effective approach to gamification.

The emphasis on strategy and economic dimensions suggests that businesses should allocate sufficient resources and develop comprehensive plans to maximize the benefits of gamification. The importance of measurement highlights the need for continuous monitoring and evaluation to adapt strategies in response to user feedback and performance metrics. Understanding psychological aspects ensures that gamification efforts resonate with the target audience, fostering deeper engagement.

Future research could expand on this study by exploring the impact of gamification across different industries and cultural contexts, providing a broader perspective on its applicability and effectiveness. Additionally, examining the long-term effects of gamification on customer loyalty and business performance could offer further insights into the sustained benefits of this approach. In conclusion, this research underscores the potential of gamification as a powerful tool in online marketing. By carefully considering and implementing the identified success factors, businesses can significantly enhance their marketing efforts, driving greater engagement and achieving their strategic objectives.

Through the identification and ranking of success factors, this study provides valuable insights into the field of online marketers and provides a basis for understanding the research landscape surrounding the success factors of gamification in online marketing:

• A practical guide to running successful gamification campaigns.
• A framework for prioritizing resources and focusing on the most impactful elements.
• Insights into potential pitfalls to avoid when using gamification in online marketing.

Practical Implications

Since business environments, especially online businesses, are looking to use new tools to promote themselves, there is a need to provide a suitable gamification framework for consumer behavior science experts, gamification designers, marketing managers and business owners. be made According to the studies, the importance of strategy and economy is in the first place, so game designers and business owners should consider that without considering a correct strategy and considering financial and economic aspects. The project cannot implement the first steps of the design properly, so not only game designers but also marketing managers and business owners should participate in determining the strategy as well as financial and economic dimensions and not leave it to the game designer. Next, The measurement dimension is there, therefore, it is necessary to determine a correct structure to measure the gaming system and identify the strengths and weaknesses of the system to prevent the loss of financial and non-financial resources. In the following, it is necessary to pay attention to other dimensions, especially the mechanics, which can be changed in different projects according to their extent. Also, this research can help game designers, digital marketing managers, user experience designers and business owners to understand the dimensions of the issue and make appropriate games for their business, according to the goals of each business which can be effective, for example, to increase sales, brand awareness or advertising. The arrangement of mechanics can be changed.

Limitations And Suggestions For Future Research

This researcher's research has faced obstacles and limitations. Due to the lack of sources and the virginity of the research subject, it was not possible to write from multiple sources. The most important challenge was finding gamification experts due to the novelty of the topic. Due to the wide range of game mechanics and dynamics, it was not possible to measure all of them in the form of a thesis. Also, it was not possible to have easy access to statistical samples and spend a lot of time and money to access them and get the consent of experts to cooperate and complete the questionnaire. In addition to these, personal preferences and lack of detailed knowledge of the questionnaire questions may have influenced the results of the research findings. The level of loyalty and honesty of the respondents due to concern in clarifying their opinions or behavioral policy in response to the questions can also affect the research results.

Despite the limitations, it is recommended to investigate the success factors of gamification in other domains of knowledge management, such as human resources, organizational training and marketing tools like advertising, branding, sales and offline marketing. Furthermore, it is suggested to examine the success factors of gamification in social networks and the impact of gamification on habit formation in consumer behavior. Identifying and ranking the mechanics leading to success at each stage of the marketing funnel, as well as identifying and ranking the mechanics based on the demographics of target audiences and identifying and ranking the factors contributing to the failure of gamification in online marketing, can also be valuable topics for future research.

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