1. INTRODUCTION
Our global society is moving towards a knowledge-based society, which is a change that emphasizes using information, knowledge, and information technology as a driving factor instead of manual labor. This change has occurred in Thailand and cannot be avoided (Cheejaeng, 2008). At the same time, when stepping into the twenty-first century, people must continually learn and develop. Therefore, there must be a search for information and the use of information to help people solve problems and survive in modern society (Spink & Cole, 2006).
Business competition among enterprises is very intense. According to the report of the Global Competitiveness Index 2019/2020, a competitiveness assessment of 141 countries around the world, it was found that Singapore is the most competitive country in the world, and Thailand was the 40th. Innovation, knowledge, technological advancement, potential promotion, and infrastructure readiness were the main criteria used for evaluation (Schwab & Zahidi, 2020). These fundamental factors can indicate the ability to create innovations and manage or develop a country’s competitiveness through a process that uses knowledge as a production tool, drives economic growth, and creates jobs for the community, including competitive abilities.
Community Enterprise Promotion policy, under Thailand Policy Announcement 4.0, aims to promote and develop the Thai economy into a knowledge-based economy, especially the policy to promote community enterprises. This is an important initiative to constantly add value to the growth of business groups (Rao, 2015) by promoting the importance of supporting community enterprises to be ready for commercial business, advancing knowledge of entrepreneurship, and elevating collaborations between related agencies, among community-supporting enterprises.
The policy started by creating an exchange process of learning from outside sources, learning knowledge from a model community enterprise, and developing in an integrated way. The promotion and development process will result in the strength of the community enterprise groups and gaining of experience in developing their own business. This will have a long-term effect on the country’s economy. It is also the primary mechanism for revitalizing, fostering economic progress, and contributing to community employment (Office of Small and Medium Enterprises Promotion, 2013). It is a source of vocational training for different workers, where people can practice and learn from real work experience. People who would be interested in investing as new entrepreneurs in the community can gather new information and concepts, because the community enterprise group shares a common goal of creating and adding value to raw materials in the community and being able to leverage the use of existing local resources, to benefit and increase value. Examples include Kluay Sen community enterprise group, Barahombatik community enterprise group, and sweet salt community enterprise group.
Even though the Thai government has launched policy to promote and fully support community enterprises, which can be observed in enhancing community enterprises’ competitiveness in doing business, promoting knowledge-based skills, and supporting a concept of learning by doing, learning together, and surveying stakeholders’ perceptions regarding productivity, these goals aim to enhance and innovate capabilities as well as competitiveness and adaptation to highly dynamic knowledge-based enterprises (Office of Small and Medium Enterprises Promotion, 2013). Further studies related to community enterprise propulsion in the public and private sectors revealed that the government mainly supports the use of workshops regarding inspiring new entrepreneurs, business model canvases, company establishments, related regulations, and digital marketing. Most are long-term projects that take up to six months to complete. Even if the entrepreneurs have sufficient knowledge, they cannot start projects or develop a group of community enterprises immediately due to differences in the enabling factors of each group of enterprises, such as the physical and cultural characteristics of the environment, personal knowledge, and resources (Connell, 2007a).
Knowledge management (KM) is a concept that emphasizes learning from the knowledge of others. It is a learning process with ready-made best practices that can be applied to business. The best practices might involve exchanging knowledge in business management, sharing experiences, learning through business activities, sharing resources, and creating business bargaining power. In addition, KM benefits the business cycle as a tool for reducing risks in various areas. It also helps to induce managerial changes (National Science and Technology Development Agency, 2000).
Moreover, KM can enhance the effectiveness of strategies to enhance enterprise vision in roles of learning and knowledge, representing organizational success. It is an essential tool in creating a culture of enterprise groups, including a suitable culture of knowledge for promoting and creating awareness that enterprises have and can be used to add value to the products and services of the group (National Science and Technology Development Agency, 2000) to maintain competitiveness. It is also helpful in creating appropriate adaptations of knowledge tactics. This is consistent with a study of successful community enterprise groups called “Cafe Doitung,” which has a unique identity under the “From Local to Global” concept. A network of collaboration and integration of knowledge in the design of products and services for local people has been created; for example, a collaboration with Onitsuka Tiger brand presenting local hand-woven fabrics in the product design, and a collaboration with Cafe and Meal Muji, Tokyo, Japan promoting local coffee beans.
Additionally, KM is crucial in competitions among local community enterprise groups, leading to implementing knowledge strategies to create best practices, exchanging knowledge, and creating knowledge through the Professional Learning Center. Further, KM supports the knowledge creation process through knowledge bases and digital technology for monitoring, reviewing, and following up on the development of creative goods and services innovations, and the application of KM in operations and production, which involves the development of products and services and evaluation of entrepreneurial competencies and performance of community enterprise groups. This aligns with the community enterprise group for society under the brand Local Alike, a creative business that focuses on providing agricultural tourism for sustainability with the integration of digital technology. It is a media platform that connects tourists to the community with KM regarding tourism consulting, creating a learning network through social media, and managing knowledge of local wisdom in the community to develop careers, products, and services of high quality that meet tourism needs. From the studies mentioned above, it was found that KM and knowledge transfer processes are important to help community enterprise groups drive business growth, leading to further development and creating additional value for products and services, and fulfilling the learning process and sharing knowledge to raise the potential of doing business and strengthen the competitiveness of the organization.
Further, transferring knowledge between businesses to survive in the long term will lead to expansion and shift from a single operator to a network dependence, business alliance, or key partners in expanding the market base or group of customers. Therefore, implementing a KM approach through knowledge transfer between enterprises can reduce time. In particular, knowledge transfer in business processes can enhance the competitiveness of enterprises. However, the KM process cannot be successfully carried out without enabling factors that support the process, so the process of KM and business processes is necessary in order to rely on enabling factors that support such processes to be successful in business.
Pattani is one of the 14 provinces in the south of Thailand with a multicultural society, an economic structure that mainly depends on the agricultural sector, and a tendency to adjust to the service sector. Regarding business, it was found that Pattani province has registered 325 various businesses and 785 community enterprises, both currently in operation and no longer in operation as of April 15, 2022 (Community Enterprise Promotion Division, 2020). This is the third province in the southern region where community enterprises are growing. It is popular in line with the government’s Thailand 4.0 policy that supports and focuses on developing enterprises to create value that will lead to the economic development of people in the region and the country based on using knowledge as a driving force. Therefore, it is crucial and necessary to get support in order to generate an economic growth rate.
In light of the body of literature that has already been written about investigations into management procedures and knowledge transfer within community enterprise groups situated in the Pattani province and its environment, it is evident that there is a need for an investigation that thoroughly synthesizes and analyzes the interaction between facilitative determinants that influence the process of knowledge transfer and the operational facets of community enterprise groups. As a result, the researchers preferred carefully examining the variables in contexts similar to their own, such as community enterprise groups primarily involved in providing agricultural products and services, while outlining the procedural mechanisms used to produce optimal operational practices. This was done in order to find and fix any gaps in the previously mentioned knowledge and subject matter.
Regarding the importance of promoting and supporting the community enterprise groups of Pattani province mentioned above, it was found that they will be successful in the business process. It is essential to have a process of knowledge transfer between enterprise groups. In addition, KM and business processes are still necessary to be promoted and implemented effectively. Due to the nature of the area and the context of the establishment of each type of community enterprise, enterprise groups are similar but have different characteristics; that is, a multicultural society characterizes the context of Pattani province, and most of the people are Thai Muslims, followed by Thai Buddhists. Identifying which enabling factors will affect knowledge transfer and business processes is essential. Further, there are seaside, mountainous, and urban areas, so the physical environment, resources, and culture could facilitate behavioral expression in the knowledge transfer process and the business process of the enterprise group differently.
Therefore, the study of enabling factors affecting the knowledge transfer and business processes of community enterprise groups in Pattani province fills an urgent need to respond to the social context of whether Thailand will promote community enterprise groups in Pattani province to be adequately developed, and how the government might enhance and support community enterprises in order to comply with the policy of Thailand 4.0, especially in supporting startup enterprises to be ready to do commercial business in terms of having a ready-to-use knowledge set that can be applied to their business group and promoting knowledge of business ownership. This can be used as a guideline to promote and support community enterprise groups to develop rapidly and enhance competitiveness in a wide area. The results of this study will lead to a fast-learning pace of community enterprise groups, both at the Pattani provincial and regional levels, and it is expected that these findings can be applied to develop a set of knowledge regarding business models for community enterprises or relevant agencies such as the Provincial Chamber of Commerce, Science Park for Incubating Entrepreneurs, Social Enterprise Promotion Office, Government Entrepreneurship training unit, Office for the Promotion of Local Wisdom, and Community Enterprise to promote competency and raise the competitiveness of Pattani community enterprise groups.
2. OBJECTIVES
To study and confirm enabling factors affecting the knowledge transfer and business process of community enterprise groups in Pattani province.
3. RESEARCH HYPOTHESIS
H1: The communication process affects community enterprise groups’ knowledge transfer and business processes.
H2: Technology in business processes affects community enterprise groups’ knowledge transfer and business processes.
H3: The production process affects the knowledge transfer process and business processes of community enterprise groups.
H4: The exchange of experience affects the knowledge transfer and business processes of community enterprise groups.
H5: Regulations and administrative guidelines affect community enterprise groups’ knowledge transfer and business processes.
H6: Business plans affect community enterprise groups’ knowledge transfer and business processes.
H7: Reinforcement affects community enterprise groups’ knowledge transfer and business processes.
H8: Brainstorming is a factor affecting the knowledge transfer process and business processes of community enterprise groups.
4. LITERATURE REVIEW
4.1. Factors of Knowledge Management Success
Connell (2007b) has analyzed KM as comprised of two key components, which are sociocultural and organizational components and technological components, with a KM system (KMS) as a link between the two components. Moreover, there is integration between people, business processes, and technology, which corresponds to Ahmed et al. (2001) and Huggins and Johnston (2009), who both find that successful KM comes from five main components: people, process, information technology, communication technology, and cultural context. This is also consistent with Rapeepan et al. (2019), that the most successful factors of KM in business organizations are leadership, including being a leader in KM, followed by organizational strategies, organizational culture, networking, organization structure, and motivation. This is accordant to results from a study by Kewsuwun and Theppaya (2021), revealing that KM is a management process to increase the competitiveness of every organization. KM is the process of managing intangible knowledge assets. Therefore, KM is essential in helping formulate policies leading to learning organizations and high-performance organizations that can manage innovation and intellectual property within the organization. The process in different steps of KM must be consistent with the organization’s nature and the information technology infrastructure’s design to support the need for knowledge in business processes or activities. In addition, information technology can store information and knowledge of the organization or support the operational process. Thus, when an organization wants to bring knowledge or expertise to develop further products and services, innovation is called intellectual capital to help promote progress and strengthen business.
4.2. Knowledge Transfer
Knowledge transfer is a fundamental process in KM. Knowledge transfer can also determine the achievement of objectives and encourage individuals or employees in the organization to share knowledge among themselves. Knowledge will be limited if it is not shared. In contrast, when knowledge is transferred, it becomes more valuable and can be embedded more profoundly within the organization. Nowadays, knowledge transfer is increasingly used in the field of organizational development. It transfers knowledge from one person to different parts of the organization, leading to good performance. This is consistent with results from the synthesis of factors obtained from in-depth interviews with key informants of the community enterprise group. It was found that the KM process takes the form of discussions, group management guidelines, group business plans, and brainstorming within the enterprise group. This relationship illustrates the effect of the knowledge transfer process and business operations process of community enterprise groups in Pattani province. To be successful, it will require cooperation through face-to-face communication, technology, and virtual communities, leading to a knowledge-based community where people can learn and share knowledge and experiences (Kewsuwun & Theppaya, 2021). Therefore, knowledge transfer has become essential in developing organizational skills as a guideline for creating a competitive advantage.
In addition, disseminating knowledge to new sources intentionally or unintentionally results in more learning. However, knowledge also has a unique feature in which it can be inherited from one generation to the next and from one or more people. In such a manner, many people can review and prove knowledge. It is also investigated and adapted to suit the situation or the context (Desa & Kotha, 2006). Therefore, the researchers concluded that knowledge transfer consists of three components:
1. Transfer from person to person; namely, telling, teaching, practicing with each other, or observing others.
2. Transfer from individual to group; namely, teaching, telling, or being trained by an individual to a large number of people such as in class, training sessions, or lectures.
3. Transfer from group to group; namely, interaction of two different culture groups. They will transfer knowledge to each other.
From the above, the researchers concluded that knowledge transfer is a process to gain knowledge and seek to expand from a source to a new source, or convey it to people who can use it for the most significant benefit. That knowledge may be in the process of interpreting meaning, or there may be the use of technological media to help make the exchange process easier. This is intended to generate new ideas and innovations. Moreover, the results of the synthesis of factors obtained from review and in-depth interviews with key informants of the community enterprise groups show that the enabling factors regarding communication processes and technology used in business processes correlate and affect the knowledge transfer process and business process of community enterprise groups in Pattani province. This is because the communication process is the starting point for information exchange and KM within the enterprise group. The communication process leads to awareness and learning for promoting accurate understanding throughout the organization, from the policy to the operational level. It allows everyone in an organization to set visions, missions, and strategies together, leads the organization toward the goals set, and must be used in accordance with the basics of the organization in terms of structure, administrative system attitude, and values, including the culture of the personnel in the organization leading the organization to success (Marungrueng, 2019). As for the technology used in the business process, it is utilized to support the communication process to be convenient and fast and to facilitate contact thoroughly at all times. It is also a channel that helps distribute information and knowledge among people within the organization and consumers.
4.3. Integration of Knowledge Transfer of Community Enterprises
Knowledge embedded in a person is the best tool for a community enterprise. This tool will help expand the competency and efficiency of the community enterprise group. The inherent knowledge of the members of the enterprise is the knowledge that can be applied and used in real life. It is appropriate and meets the needs of the group members. In addition, creating an advantage in community enterprise groups is also gained by managing and transferring knowledge from member networks between the group of producers. This can be applied to exchange knowledge in many ways. In addition, knowing how to use technology in business processes that come from experience and sharing knowledge also contributes to the long-term success of enterprises.
According to studies regarding KM in Australia’s small and medium enterprises, Handzic (2006) found that the KM process in enterprise business groups consists of (1) raising awareness of KM, (2) connecting KM with business strategies, (3) exploring existing knowledge and other sources of knowledge, and (4) implementing KM processes. Additionally, the study’s results also indicated causes and effects that small and medium business managers need in order to implement the KM process in terms of knowledge transfer and sharing to use in their organizations. The nature of the process and context of knowledge requires organizations to prudently manage the knowledge within the organization for the benefit of the organization. However, KM requires systematic organizational management, so there is a need to raise awareness of KM, set the desired goals, and manage local resources and sources of knowledge exploration. Finally, KM will help enhance people’s potential and sustainably develop the organization long-term. This corresponds to Lee et al. (2005), who mention that implicit and explicit knowledge affect each other. Knowledge and innovation can be created as the organization’s most important assets.
Further, KM will help develop small and medium-sized businesses that cover community enterprises and household businesses in the future for sustainable business. McDermott (1999) reasoned that information technology tools alone do not affect KM changes and other factors—for example, trust or face-to-face contact. Businesses need workflow and collaboration in knowledge gathering and classifying knowledge for application in business, investment in learning and training, and increasing demand for infrastructure.
Integrating KM among enterprises in a dependent working environment could happen from persons with expertise in various work conditions as they get together to discuss, whether in the form of a face-to-face conversation or through communication technology. Creating a virtual community requires leaders and colleagues to engage in conversation, search, discover new things, and create innovations. There is a critical need for business KM to integrate KM concepts for value creation, which contains seven steps as follows:
1. Knowledge identification is utilized to establish a working group on KM that will hold working group meetings to indicate the necessary knowledge and information for members to exchange experiences.
2. Creating and acquiring necessary business knowledge and information. This step is utilized to organize meetings to seek knowledge on network development from inside and outside the organization. The working group will search for network development knowledge from various sources for explicit knowledge and interview experts in network development for tacit knowledge. The knowledge generation and management method involves all stakeholders exchanging knowledge and sharing values.
3. Organizing knowledge into a system is intended to organize meetings within a working group to systematically manage knowledge in network development and manage knowledge classification, to search and store the knowledge gained from the group or information that is beneficial to the organization.
4. Compiling and filtering knowledge is done to organize meetings of working groups and related persons to collect and scrutinize knowledge on network development, then inspect, compose, and update knowledge.
5. Accessing knowledge is done to organize working group meetings to find channels for accessing knowledge and reproducing knowledge data in various forms that are convenient and easily accessible, along with informing accessible channels for the target group and community enterprise network members. Knowledge transfer must be driven to achieve changes leading to the organization’s strategic plan, product differentiation, and organization management.
6. Exchanging and learning is accomplished to organize working group meetings to find ways to exchange knowledge and organize activities to transfer, using a knowledge exchange platform, symposium, or community of practice.
7. The learning process is deployed to organize working group meetings to find ways to apply knowledge as well as to encourage and support people to learn in the developed KMS and use it in practice. Following up and evaluating the learning outcomes of the community enterprise network will help users analyze and improve the community enterprise network to be more substantial and sustainable.
4.4. Business Process of Community Enterprise
The researchers followed Porter (1998)’s supply chain approach, which illustrates the activities of community enterprises. The main goal is to create value for products and services. In this regard, every process and activity must rely on knowledge transfer. Developing knowledge in operations among members within the enterprise group is strengthened to carry out various activities efficiently and create higher value (Mongkolnimitr et al., 2020). This process includes relationships from inbound logistics, which consists of preparing, purchasing, and providing raw materials or agricultural resources to the production process of goods or services for consumers. In the operation part, activities are linked to transforming the raw materials or agricultural resources of the production sectors to offer value that meet the needs of consumers, which may be produced by skilled labors or machinery. The last part of production consists of three sub-sections: (a) outbound logistics, which is an activity in which a group of enterprises brings goods and services obtained from production to deliver them to consumers; (b) marketing and sales, which is an activity in which a group of enterprises presents goods and services to consumers, to stimulate consumers in buying products and services, such as offering promotions and managing consumer relationships, and (c) service, which is an activity related to providing services to raise the service level and maintain the value of the enterprise group’s products and services, such as demonstrations and giving advice and product guarantees, along with satisfaction surveys in order to maintain the customer base.
5. RESEARCH METHODOLOGY
This study employed a mixed methods research design focusing on qualitative data, by conducting a survey of community enterprise entrepreneurs regarding attitude and opinion in enabling factors and confirming statistical data found with quantitative research to create mathematical prediction equations of contributing factors as follows.
5.1. Area of Study
The research area was in Pattani province, Thailand. Groups of community enterprises were selected based on products and services produced in Pattani province only.
5.2. Key Informant Selection to the Unit of Research
The researchers selected 30 key informants using specific methods from community enterprise groups registered with the Community Enterprise Promotion Division, Department of Agricultural Extension. The informants can coordinate research data collection using semi-structured interviews and are not in an at-risk area. Entrepreneurs are willing to provide access to business information. It also considers the conditions from which the business is operated, namely being an outstanding community enterprise group that is a successful model in business operations. Moreover, the researchers have set essential criteria for considering qualifications and conditions in selecting all three types of key informants in enterprise groups to enter the research process by classifying them. The 30 key informants were classified into (1) 10 businesses in the production sector, (2) 10 businesses in the trading sector, and (3) 10 businesses in the service sector.
Furthermore, the criteria to recruit the key informants are as follows: They must be community enterprise business groups in Pattani province. They must use technology or innovation to drive production service competition or add value to products and services, such as computers, tablets, mobile phones, Facebook, Line, Instagram, YouTube, or Twitter. The technology must also cover operating system programs, storing, production, and sales or finance systems, such as QR codes for payment, payment systems, or credit card machines. Their businesses must have (1) a continuous production process for products and services with the same quality and standards, (2) standards and quality that meet customer satisfaction, (3) products that are available from the local community and possess best management practices, (4) a network or business partners, and (5) a business model or clear business guidelines.
5.3. Research Instruments
The research instrument was a set of interview questions in the form of semi-structured interviews created by the researchers, which covered the research objectives and were divided into four components:
5.3.1. The R Program for Data Analysis
The R program for statistical computing was used to calculate statistics chi-square, Crammer’s V, variable correlation from in-depth interview data, and analyze factors that significantly affect knowledge transfer and business processes to create forecasting equations. The aim was to identify enabling factors affecting knowledge transfer and business processes of community enterprise groups in Pattani province using eight factors.
5.3.2. The Semi-Structured Interviews for Data Collection
Semi-structured interviews were divided into three parts:
Part 1, one item regarding the type of community enterprise.
Part 2, 11 items about the following issues: (1) use of technology and innovation in manufacturing products; (2) use of technology and innovation in business operations; (3) process of production of goods and services; (4) best practices in business KM; (5) network or business alliance; (6) processes in implementing a business plan; (7) guidelines and methods for managing enterprises; (8) customer success; (9) knowledge transfer success; (10) learning and development to promote competitive performance; and (11) ways to promote the sharing capacity of community enterprises. The reliability of this part was 0.91.
Part 3, 3 items according to the following issues: (1) creating contextual advantage; (2) causes affecting the business process of the community enterprise group; and (3) enabling factors affecting the knowledge transfer process and business processes of Pattani community enterprises. The reliability of this part was 0.87.
5.3.3. Non-Participant Observations
The observation method plays a crucial role in the researchers’ in-depth interview process. However, its purpose differs significantly from the observation typically associated with answering research objectives. In an in-depth interview, observation is a tool for gathering contextual information and enhancing understanding. Researchers observe non-verbal cues, body language, facial expressions, personalities (Phuthong, 2023), and environmental factors during the interview to gain insights into the participant’s emotional state and reactions, and the broader context of their responses. This observational aspect aids in data interpretation and provides valuable context, but its primary purpose is not to serve as a standalone method for answering research objectives. Instead, it complements the interview process, enriching the data collected and contributing to a more comprehensive analysis.
5.3.4. A Voice Recorder
To guarantee the accuracy of the data, informants’ interview responses were captured using a voice recorder. To make sure there were no discrepancies in the information obtained from the informants, both fieldnotes and recorded data were employed (Phuthong, 2023).
5.4. Construction and Evaluation of Research Tools
For constructing instruments for data collection and analysis of the enabling factors affecting the knowledge transfer process and business process of community enterprise groups in Pattani province, this study followed these methods and steps systematically (Kaewsuwan & Kajornkasirat, 2023):
5.4.1. Data Collection
The researchers collected various data from fulltext research, research papers, and related research on knowledge transfer in community enterprise, KM, business processes, and enabling factors affecting community enterprises, business alliances, and business models. This data covered the objectives the researchers determined and were applied in a semi-structured interview design.
5.4.2. Checking the Quality of Semi-Structured Interviews
Semi-structured interviews were among the research instruments that the researchers designed and implemented. Before being made available to experts, these tools underwent review, language editing, and formatting to guarantee their correctness, applicability, and thoroughness.
5.4.3. Using Sampling Techniques
The researchers was consulted by an expert to evaluate and scrutinize the semi-structured interview form using the instruments they had designed for the study. In addition, five specialists in KM, entrepreneurship, business, and research were chosen by the researchers to evaluate and confirm the precision and caliber of the research instruments and offer suggestions to guarantee content validity. Using purposive sampling techniques, the researchers applied the idea of taking into account the positions and credentials of the experts—that is, their experience, knowledge, competence, and experience in the field and area of study.
5.4.4. Content Validity
Using the evaluation results from the five experts, the researchers evaluated the quality of the research instruments. They calculated the fluency index between the research issue, query, definition, or item of congruence (IOC), and content validity after considering the expert’s remarks. According to the evaluation criteria, they assigned grades and generated scores (Kiranandana, 2007). The majority of the questionnaire’s components had IOCs between 0.6 and 1, suggesting that semi-structured interviews are a useful and efficient method for gathering data (Kiranandana, 2007).
5.4.5. Tryout and Reliability
On the advice of specialists, the researchers created research instruments. The tools were then tested on a sample of thirty community entrepreneurs, who were asked to provide feedback on the language and content to make sure it made sense and matched the goal of the study. The Cronbach α coefficient (Kiranandana, 2007) was then used to assess the results’ dependability. The results showed that the semi-structured interviews had a reliability score of 0.83.
5.5. Data Collection
The present study applied qualitative research to collect data and examine a social phenomenon, emphasizing data regarding insiders’ thoughts, perspectives, and opinions (Phuthong, 2023). The duration was six months (June to December 2022) for gathering primary and secondary data. The return rate of the semi-structured interviews accounted for 100%, and data were collected using the techniques outlined below.
5.5.1. Primary Data
Primary data were derived from semi-structured interviews recorded as field notes. The researchers interviewed until data and theoretical saturation were achieved. After that, the researchers analyzed the data simultaneously and summarized the initial concept based on the key informants’ interviews. The researchers collected and sorted data: 30 community enterprises were returned, and 100 percent of the distributed semi-structured interviews were conducted.
5.5.2. Secondary Data
Secondary data were retrieved from a review of research conceptual documents, academic textbooks, academic reports, reseach and academic journals, and previous research relevant topics on knowledge transfer in community enterprise, KM, business process, enabling factors affecting community enterprise, business alliances, and business models through search platforms such as the Scopus database, Prince of Songkla University (PSU) knowledge bank, and Thai Journals Online, the world’s largest abstract and citation databases. These offer hundreds of documents and articles from numerous national and international publishers with different titles, topics, and scopes (Phuthong, 2023). Additionally, meeting minutes, seminars, and pertinent organizations’ intranet systems may be included.
5.5.3. Field Data Observations
The researchers arranged for face-to-face interviews with key informants, and observational field data was initiated. In order to get the informants to cooperate in the data collection, the researchers assured them of their anonymity and confidentiality and described the purpose of the data collection and utilization. The researchers requested authorization to record audio before beginning the in-depth interviews, and they then started gathering data using the interview guide. After data regarding the informants’ demographic characteristics were collected, the researchers asked questions about knowledge transfer in community enterprise, KM, business processes, the context of community enterprise, and enabling factors affecting community enterprise, business alliances, and business models. This process continued until data saturation was achieved. The researchers then ended the in-depth interviews. The researchers noted prominent issues during the in-depth interviews and observed the informants’ behaviors, gestures, and facial expressions (Phuthong, 2023). The interviews lasted from 45 minutes to 1 hour.
5.5.4. Protection of the Rights of Human Subjects
The research ethics committee of PSU approved this study involving human subjects (approval code number: PSU IRB 2022-LL-HUSO 020 [Internal] under the Belmont Report on July 12, 2022). The first page of the semi-structured interviews had an information sheet, and only those participants who signed an informed permission form stating their willingness to participate in the study had their data gathered. After that, the study’s data were thoroughly examined as group data that had been anonymised for scholarly purposes exclusively.
5.6. Data Analysis and Statistics
The researchers analyzed the data using the mixed methods design as follows:
5.6.1. Content Analysis and Classification Approach
The researchers used frequency to address the enabling factors from key informants. The analysis methods included content analysis and the classification approach, and they were used to determine the degree of correlation of the variables. The data set was on the nominal scale (Kiranandana, 2007).
5.6.2. Descriptive Statistics
The researchers analyzed the basic information regarding types of community enterprise groups and their enabling factors using descriptive statistics with frequency, percentage, mean, and standard deviation (Kiranandana, 2007) and presented the analysis results in tabular format with descriptions.
5.6.3. Correlation Analysis
The researchers analyzed data on the relationships among enabling factors using inferential statistics and chi-square (X2), to test the relationship between two variables by organizing data types in frequency at a statistical significance level of 0.05. The R program, statistical computing, was used to test independence, to analyze the relationship between two variables, and to create forecasting equations and mathematical models.
However, when it was found that the variables were related, the magnitude of the correlation was tested using the Phi statistic by considering Cramer’s V (Vanichbuncha, 2002) to consider the magnitude and direction of the relationship between variables at the nominal scale. Frequencies were obtained from in-depth interviews (Wijitwanna, 2022) according to the criteria for interpretation of the size of the correlation coefficient (Wongrattana, 1998) below.
A correlation coefficient value of 0.91-1.00 represents a very high correlation.
A correlation coefficient value of 0.71-0.90 represents a high correlation.
A correlation coefficient value of 0.31-0.70 represents a moderate relationship.
A correlation coefficient value of 0.01-0.30 represents a low correlation.
A correlation coefficient value of 0.00 represents no relevance.
This can be applied to test the hypotheses as follows:
(H0) Enabling factors (communication, technology used in business processes, production processes, exchange of experience, regulations and management guidelines, business plans, reinforcement, and brainstorming) had no relationship with the knowledge transfer process and business processes of community enterprise groups in Pattani province.
(H1) Enabling factors (communication, technology used in business processes, production processes, exchange of experience, regulations and management guidelines, business plans, reinforcement, and brainstorming) were related to the knowledge transfer and business processes of community enterprise groups in Pattani province.
5.6.4. Enabling Factors Analysis
Correlation was analyzed between the independent variables enabling factors and dependent variables with mean and standard deviation (Kiranandana, 2007) using the R project for statistical computing.
5.6.5. Symbols Used in Data Analysis
n represents the number of community enterprises in the sample.
represents the mean value.
X2 represents the chi-square value.
p-value represents the test value of the relationship between enabling factors.
Α represents significant value.
Crammer’s V represents the independence test of the two variables in case the data has a nominal level of measurement according to the in-depth interviews.
X1 represents the communication process.
X2 represents the technology usage.
X3 represents the production process.
X4 represents the exchange of experience.
X5 represents the regulations and administrative guidelines.
X6 represents the business plans.
X7 represents the reinforcement.
X8 represents the brainstorming.
6. RESULTS
6.1. Hypothesis Testing
Hypothesis testing is utilized to analyze the relationship between facilitating factors affecting knowledge transfer and business processes. Considering the p-value that is less than or equal to 0.05 is a statistical significance determination. The results of the research hypothesis testing the researchers can be presented in Table 1 as follows.
Table 1 shows that hypotheses 1 to 4 were rejected. The results of the hypothesis testing could be explained as follows:
The 1st hypothesis test revealed that the communication process was not related to the knowledge transfer and business processes of community enterprise groups.
The 2nd hypothesis test revealed that the technology used in the business process was unrelated to community enterprise groups’ knowledge transfer and business processes.
The 3rd hypothesis test revealed that the production process was unrelated to community enterprise groups’ knowledge transfer and business processes.
The 4th hypothesis test revealed that the experience exchange was unrelated to community enterprise groups’ knowledge transfer and business processes.
In this regard, the results of the correlation showed that hypotheses 5 to 8 were accepted, which can be shown as follows:
Table 1
Summary of hypothesis testing results
| Hypothesis | X2 test significance | p-value | Cramer’s V | Test results |
|---|---|---|---|---|
| H1 Enabling factors in the communication process → knowledge transfer process and business processes of community enterprise groups | 2.857 | 0.240 | 0.309 | Reject H1 accept H0 |
| H2 Enabling factors in technology used in business processes → knowledge transfer process and business processes of community enterprise groups | 4.286 | 0.117 | 0.378 | Reject H1 accept H0 |
| H3 Enabling factors in the production process → knowledge transfer process and business processes of community enterprise groups | 4.038 | 0.133 | 0.367 | Reject H1 accept H0 |
| H4 Enabling factors in experience exchange → knowledge transfer process and business processes of community enterprise groups | 1.920 | 0.383 | 0.253 | Reject H1 accept H0 |
| H5 Enabling factors in regulations and administrative guidelines → knowledge transfer process and business processes of community enterprise groups | 8.750 | 0.013a) | 0.540 | Accept H1 reject H0 |
| H6 Enabling factors in business plans → knowledge transfer process and business processes of community enterprise groups | 6.240 | 0.044a) | 0.456 | Accept H1 reject H0 |
| H7 Enabling factors in reinforcement → knowledge transfer process and business processes of community enterprise groups | 0.271 | 0.038a) | 0.873 | Accept H1 reject H0 |
| H8 Enabling factors in brainstorming → knowledge transfer process and business processes of community enterprise groups | 6.240 | 0.044a) | 0.456 | Accept H1 reject H0 |
6.1.1. Hypothesis 5, the Enabling Factors in Regulating Administrative Guidelines Related to Community Enterprise Groups’ Knowledge Transfer and Business Processes
According to Table 2, it was found that service-type community enterprises expressed their opinions toward the regulations and administrative guidelines, with an enabling factor of 41.67%, followed by opinions from production-type community enterprises about regulations and administrative guidelines, with an enabling factor of 37.50%. However, the Chi-square test results at significance level (α) 0.05 showed that the p-value was 0.013, less than the α. Therefore, hypothesis H1 is accepted. When considering the variables’ correlation level using Cramer’s V, it was 0.540, indicating that the regulations and administrative guidelines enabling factor had a moderate relationship with the knowledge transfer and business process of the community enterprise group with a significance level of 0.05.
Table 2
Relationship between facilitating factors in regulations and administrative guidelines, knowledge transfer processes, and business processes of community enterprise groups (own data processing)
| Type of group community enterprise | Regulations and administrative guidelines enabling factor (X5) | |
|---|---|---|
| Frequency | (%) | |
| Production | 9 | 37.50 |
| Trading | 5 | 20.83 |
| Services | 10 | 41.67 |
| Total frequency | 24 | 100.00 |
6.1.2. Hypothesis 6, Enabling Factors Related to Community Enterprise Groups’ Knowledge Transfer and Business Processes in Business Plans
Table 3 shows that service-type community enterprises expressed their opinions toward the business plan enabling factor at 80.00%, followed by distribution-type community enterprises that showed opinions about the business plan enabling factor at 20.00%. Chi-Square test results at significance level (α) 0.05 showed that the p-value was 0.044, less than the value α. Therefore, hypothesis H1 is accepted. When considering the level of correlation of the variables using Cramer’s V, it was 0.456, showing that the business plan enabling factor had a moderate relationship with the knowledge transfer process and the business process of the community enterprise group, with a significance level of 0.05.
Table 3
Relationship between enabling factors in business plans related to knowledge transfer process and business processes of community enterprise groups (own data processing)
| Type of group community enterprise | Business plan enabling factor (X6) | |
|---|---|---|
| Frequency | (%) | |
| Production | 4 | 80.00 |
| Trading | 1 | 20.00 |
| Services | 0 | 0.00 |
| Total frequency | 5 | 100.00 |
6.1.3. Hypothesis 7, Enabling Factors in Reinforcement Related to Community Enterprise Groups’ Knowledge Transfer and Business Processes
According to Table 4, it was found that the production type of community enterprises expressed their opinions toward the reinforcement enabling factor at 38.46%, followed by distribution and service-type community enterprises that showed the same opinions about the reinforcement enabling factor at 30.77%. Chi-square test results at significance level (α) 0.05 showed that the p-value was 0.038, less than the value α. Therefore, hypothesis H1 is accepted. When considering the level of correlation of the variables using Cramer’s V, it was 0.873, showing that the reinforcement enabling factors correlated with the knowledge transfer process and business process of the community enterprise group, with a significance level of 0.05.
Table 4
Relationship between enabling factors in reinforcement related to knowledge transfer process and business processes of community enterprise groups (own data processing)
| Type of group community enterprise | Reinforcement enabling factor (X7) | |
|---|---|---|
| Frequency | (%) | |
| Production | 5 | 38.46 |
| Trading | 4 | 30.77 |
| Services | 4 | 30.77 |
| Total frequency | 13 | 100.00 |
6.1.4. Hypothesis 8, Enabling Factors in Brainstorming Related to Community Enterprise Groups’ Knowledge Transfer and Business Processes
According to Table 5, it was found that community enterprises in the service type expressed their opinions toward the brainstorming enabling factor at 40.00%, followed by production-type community enterprises that showed opinions about the brainstorming enabling factor at 36.00%. However, the Chi-square test results at significance level (α) 0.05 showed that the p-value was 0.044, less than the value α. Therefore, hypothesis H1 is accepted. When considering the level of correlation of the variables using Cramer’s V, it was 0.456, showing that the brainstorming enabling factor had a moderate relationship with the knowledge transfer process and the business process of the community enterprise group, with a significance level of 0.05.
Table 5
Relationship between brainstorming enabling factors and community enterprises’ knowledge transfer process and business processes (own data processing)
| Type of group community enterprise | Brainstorming enabling factor (X8) | |
|---|---|---|
| Frequency | (%) | |
| Production | 9 | 36.00 |
| Trading | 6 | 24.00 |
| Services | 10 | 40.00 |
| Total frequency | 25 | 100.00 |
6.1.5. Testing of the Relationship between Enabling Factors Affecting the Knowledge Transfer Process and the Business Process by Considering the Overall Picture of the Community Enterprise Group
Table 6 demonstrates the opinions of the community enterprise group determined by the frequency of answering issues in an in-depth interview. The results of analyzing and testing the relationship between enabling factors, considering the overall picture of community enterprise groups in Pattani province, revealed an overview of all eight enabling factors using the Chi-square test at significance level (α) 0.05 that the value p-value was 0.011, which was less than α. Therefore, hypothesis H1 is accepted, that is, enabling factors regarding the communication process, technology used in business processes, production process, exchange of experience, regulations and management guidelines, business plans, reinforcement, and brainstorming are related to the knowledge transfer process and business processes of community enterprise groups in Pattani province. When considering the level of correlation of the variables with Cramer’s V, it was 0.965, showing that all eight enabling factors related to the knowledge transfer process and the business process of the community enterprise group at a very high level with statistical significance at the level of 0.05.
Table 6
Relationship of opinions on enabling by considering overall picture of community enterprise groups in pattani province (own data processing)
| Community enterprise/enabling factors | Community enterprise | |
|---|---|---|
| Frequency | (%) | |
| Communication process | 22 | 73.30 |
| Technologies usage | 28 | 93.30 |
| Production process | 27 | 90.00 |
| Exchange of experience | 26 | 86.70 |
| Regulations and administrative guidelines | 24 | 80.00 |
| Business plan | 7 | 23.30 |
| Reinforcement | 14 | 46.70 |
| Brainstorming | 25 | 83.30 |
6.2. Correlation Analysis between Community Enterprise Groups’ Enabling Factors, Knowledge Transfer Process, and Business Process
Fig. 2 summarizes the correlation analysis of community enterprise groups’ enabling factors, knowledge transfer, and business processes. It can be concluded that there is a high correlation between the technologies usage enabling factor (X2), exchange of experience enabling factor (X4), and regulations and administrative guidelines enabling factor (X5) with the knowledge transfer and business process of community enterprise groups. The correlation between the communication process enabling factor (X1), production process enabling factor (X3), business plan enabling factor (X6), reinforcement enabling factor (X7), and brainstorming enabling factor (X8) with the knowledge transfer process and business process of community enterprise groups were found to be at a low level.
Fig. 2
Correlation analysis between enabling factors, knowledge transfer process, and business process of community enterprise groups (own data processing).
6.3. Analysis Results of Enabling Factors Affecting Knowledge Transfer and Business Process of Community Enterprise Groups in Pattani Province of Forecasting Equations and Mathematical Models
Table 7 confirms enabling factors affecting the knowledge transfer process of the community enterprise group with multiple regression. It was found that regulations and administrative guidelines (X5), business plans (X6), reinforcement (X7), and brainstorming (X8) had a positive effect on the knowledge transfer and business process of the community enterprise. These four an enabling factors can predict knowledge transfer and business processes with a statistical significance of 0.05, and account for 67% of the variance. The business plans (X6) had the most significant effect (β=0.208), followed by reinforcement (X7) (β=0.121).
Table 7
Multiple regression analysis of factors affecting community enterprise group’s knowledge transfer and business processes
| Community enterprise/enabling factors | B (raw score) | Standard error of b | Beta (standard score) | T | p-value |
|---|---|---|---|---|---|
| Regulations and administrative guidelines (X5) | -0.299 | 1.151 | -0.069 | 3.414a) | 0.026 |
| Business plans (X6) | 0.709 | 0.763 | 0.208 | -2.603b) | 0.076 |
| Reinforcement (X7) | 0.301 | 0.539 | 0.121 | 2.929a) | 0.052 |
| Brainstorming (X8) | -0.050 | 0.790 | -0.017 | 5.825a) | 0.041 |
| Constant (b) | 15.057 | 4.411 | -2.064c) | 0.002 |
The correlation of knowledge transfer and business process of community enterprise with the regressors (X5, X6, X7, X8) was equal to 0.282, and the standard error of the estimate (SEest)was equal to 0.095. The raw score model was as follows:
The forecasting equation for the knowledge transfer and business process of community enterprise in the standard score model was as follows:
7. CONCLUSION AND DISCUSSION
7.1. Conclusion
The results of the hypothesis testing in finding the relationship between the enabling factors and knowledge transfer and the business process of the community enterprise group showed that all eight enabling factors affected knowledge transfer and the business processes at a very high level. By considering the classification of community enterprise groups in Pattani province, it was found that there were four enabling factors related to the knowledge transfer and business process of community enterprises in Pattani province: The reinforcement and the regulations and administrative guidelines were the factors with the highest correlation, and business plans and brainstorming were the second correlation factors.
In contrast, the communication process, technology used in business, production process, and the exchange of experiences did not affect the knowledge transfer and business processes of the community enterprise group in Pattani province. The entrepreneurs may not pay attention to the abovementioned factors since they might be complicated to implement with other equipment and in production. In addition, there may be a slight emphasis on the exchange of experience since each party performs tasks under their responsibility only. As a result, such factors did not affect the knowledge transfer and the business process of the community enterprise group.
The mathematical scores from Table 7 presenting multiple regression analyses and showing statistical significance explain the knowledge transfer process of the community enterprise group with positive results. The two factors with the highest predictive values are the business plans and the reinforcement. These factors are at a high level since they are fundamental enabling factors in organizational management for operation and lead to a learning community for competitive advantage. According to KM concepts is utilized to find ways to exchange knowledge, problem-solve, plan, design, and organize activities using a knowledge exchange platform via a symposium or community of practice.
7.2. Discussion
The results of enabling factors affecting knowledge transfer and business processes of the Pattani community enterprise groups can be discussed as follows:
7.2.1. Overview of Hypothesis Testing
From the hypothesis testing, it was found that all eight enabling factors could affect and relate to the knowledge transfer process and the business process of the community enterprise group at a very high level. This may be because most entrepreneurs see that today’s society is a knowledge-based society where data, information, knowledge, and innovation are essential. Nowadays, digital technology plays a significant role and has also become a tool that helps support work and daily life and can be applied in various activities (Srijamdee & Pholphirul, 2020). Moreover, when considering the eight enabling factors, each is a part of the business process tools, such as the five forces, value chains, and business model canvas; so, they correspond to the constituents of the eight enabling factors. In addition, it was found that each factor was carried out by bringing digital technology to support operations within the organization, reducing workload and increasing speed in performing tasks and activities. This also resulted in the management system and services to owners or users operating efficiently and effectively regarding human resources and funding (Jarusen, 2021). The relationship of all eight enabling factors indicated that the knowledge transfer process, business process, exchanging of experiences, and brainstorming of members within the community enterprise group must rely on the communication process and technology used in business processes.
In modern times, eight factors are used as tools for both communications among group members and business partners or as a medium to create a space to communicate with customers through online channels. Furthermore, digital technology also relates to information and knowledge existing within and outside the enterprise group. That is, the information and knowledge available within the group are used as a medium for coordinating, discussing, consulting, or exchanging experiences with each other. This is consistent with the research of Chiu et al. (2011), Cheung and Lee (2010), and Lin and Lu (2011), who pointed out that digital technology can be used as a medium to exchange information via social media sites, which can result in individual or group learning. It is also an important factor in increasing the sharing of knowledge.
On the contrary, digital technology is a knowledge-seeking tool in social networking if information and knowledge are available outside of groups (Abed, 2022). Management, regulations, administrative guidelines, business plans, and reinforcement are consistent with the community enterprise promotion policy to promote and develop the Thai economy into a knowledge-based economy. The policy recognizes the importance of promoting knowledge of entrepreneurship in terms of regulations, laws, business plans, operational standards, systematic exchange of learning from external learning sources, knowledge transfer from model community enterprises, and development in an integrated manner. This will result in a robust community enterprise group as well as greater experience in developing members’ businesses. These eight enabling factors link the knowledge transfer and the business processes of the community enterprise group, strengthen bonds among alliances and business plans, and demonstrate good practices for enterprise groups (Chiriac & Frykedal, 2022; Liu et al., 2013).
8. SUGGESTIONS
Two suggestions can be made based on the findings on the construction of enabling factors for community enterprise.
8.1. Theoretical Guideline Suggestions
Findings from the analysis of the relationship between factors affecting knowledge transfer and business process, based on the opinions of community enterprise entrepreneurs, showed that most of them shared opinions about the factors that came from experience and experience. At the same time, exchanging knowledge and business processes among entrepreneurs must rely on areas that may cover physical, virtual, or conceptual spaces. They may use it to create new knowledge and facilitate sharing knowledge transfers between group members or allies to gain advantages in developing competition among community enterprises. To encourage community enterprise entrepreneurs to be able to conduct business processes and transfer knowledge to each other efficiently, they should see the importance of the area for sharing knowledge and experiences within the group.
8.2. Applications and Further Studies
The results of analyzing and confirming the enabling factors found that four factors related to and affected the transfer of knowledge process based on the types of community enterprise groups in Pattani province, including production groups, service groups, and distribution groups. The four factors are reinforcement, regulations and administrative guidelines, business models, and brainstorming. As a result, agencies that support community enterprise groups in regard to competitiveness, quality enhancement, and value at the provincial, regional, and national levels, such as the Provincial Chamber of Commerce, Science Park for Incubating Entrepreneurs, Social Enterprise Promotion Office, Government Entrepreneurship training unit, and Community Enterprise and Provincial Commercial Offices should pay more attention to and focus on promoting such factors.
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