Next Article in Journal
An Eco-Driving Strategy Considering Phase-Switch-Based Bus Lane Sharing
Previous Article in Journal
A Time Series Forecast of COVID-19 Infections, Recoveries and Fatalities in Nigeria
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Smart Co-Operative Management Framework Based on an EA Concept for Sustainable Development

by
Anassaya Chawviang
,
Supaporn Kiattisin
,
Montree Thirasakthana
and
Theeraya Mayakul
*
Information Technology Management, Faculty of Engineering, Mahidol University, Nakorn Pathom 73170, Thailand
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(9), 7328; https://doi.org/10.3390/su15097328
Submission received: 28 February 2023 / Revised: 16 April 2023 / Accepted: 25 April 2023 / Published: 28 April 2023

Abstract

:
A smart co-operative management framework aims to apply ICT to provide better services and increase management efficiency. The findings of previous studies suggest that the framework is suitable for any co-operative organization that uses information technology to improve its services, management, and governance. Therefore, this paper has applied a smart co-operative management conceptual model to a smart co-operative management framework. It is a smart co-operative management concept that complies with strategic management for responding to technological disruption. A smart co-operative management framework combines business and technology to align the concept to establish efficiency and governance in co-operative management. This paper presents a smart co-operative management framework based on the EA concept for sustainable development in co-operative management. This framework was developed through a smart co-operative conceptual model, comprehensive literature review, and requirement analysis based on the conceptual framework consisting of five layers: business, application, data and information, infrastructure and technology, and governance. Content validity was used for evaluation. This framework demonstrates that technology could enhance the co-operative sector through the layers of applications, data, and information supported by infrastructure and technology. This study shows the framework for sustainable development co-operatives in the co-operative sector. It also creates value through enterprise architecture (EA) and the smart co-operative management concept.

1. Introduction

A co-operative is a type of significant financial institution that is typically established by individuals working in the same area, country, province, or career. Co-operatives are formed to provide their members with financing, products, and services. According to the literature, at least 12% of the global population is a member of a co-operative [1]. Co-operatives are classified into six categories: agricultural, consumer, credit union, housing, insurance, and worker [2]. In the meantime, disruptive technology has substantially impacted co-operative enterprises, altering member behavior and increasing market competition. In order to successfully serve their members, co-operatives must modify their business processes. A co-operative is also an important institution that assists its members in living a better life, following their vision and co-operative principles.
Co-operatives are distinguished from other business enterprises in that a voluntary alliance of citizens effectively fulfills the financial needs of its members through a jointly owned and properly regulated co-operative [3,4,5], and members participate in policy formation and decision-making with equal voting rights [6,7]. Co-operative values are founded on self-help, self-responsibility, democracy, equality, fairness, and solidarity [8,9]. Co-operatives can contribute to sustainable development and operations for the benefit of their members and the community through democratically approved policies [10]. Consequently, co-operatives are crucial in providing benefits [11] and fostering co-operative ideals in their members [12]. In addition, the decision-making processes and associated member benefit outcomes have been studied [13,14]. Although co-operatives receive income from various sources [15], profit maximization is not their objective [3]. Co-operative objectives are designed to maximize member benefits while reducing variations in revenues and expenses, such as in-service markets, economic growth, consumer products, and the enhancement of their members’ life quality [16,17]. Co-operatives can engage in any economic activity and operate in any economic sector. Therefore, they must comply with applicable laws [18], and co-operative regulations must be validated by all parties involved. Currently, the value of co-operative businesses has increased. However, the performance of co-operatives has been hindered by governance problems such as financial scandals, the neglect of democracy, poor management, administrative power monopolies, and restrictions on member participation [19]. The second point is that balancing the interests of members is an emerging source of conflict because members who save want a high dividend rate on their savings, while members who borrow want a low lending rate [17]. Therefore, information technology is critical in enabling a rise in engagement, organizational democracy, and the efficiency of management decisions [20].
Smart co-operatives use information and communication technology to enhance their performance, quality of service, and management. By integrating the co-operative business process model with information and communication technologies, co-operative businesses have developed inventive ways to provide for their members. Therefore, information and communication technologies (ICTs) and other technologies are critical in enabling smart governance with the collaboration and participation of all various stakeholder groups in decision-making [21,22,23]. Enhancing collaboration, participation, and community empowerment [24] ensures transparency and confidence in co-operative management. Hence, information and communication technologies (ICTs) are crucial in the smart co-operative and governance framework. The framework’s design prioritizes the openness and efficacy of management processes. It refers to smart co-operative management concepts, smart members, smart economy, and smart governance [25]. The organization’s policy mission and objectives align with the co-operative’s core principles. In addition, the concept of a smart co-operative (SC) serves as the “road map” for the co-operative system. The SC framework makes business processes and governance more efficient.
Applying technology for co-operative solutions has become more cost-effective, transparent, and productive. Consequently, effective IT governance enhances productivity and the quality of services directly while improving overall management and efficiency [26]. As a result, IT governance is related to organizational structures and procedures, ensuring that ICT facilitates and pushes organizational goals and strategies [27,28]. The Control Objectives for Information and Related Technologies (COBIT) and the Information Technology Infrastructure Library (ITIL) are two prevalent standards concerning the IT framework. However, neither of these perspectives applies to co-operative organizations.
Technology has positively impacted individuals and co-operatives, increasing service quality, eliminating communication barriers between stakeholders, and enhancing cost savings [28,29]. For instance, cloud computing provides users with online data control and access, enabling them to exchange information via this platform [29]. The platform facilitates the convenience of co-operative activity and administration. New technologies make valuable information more available and accessible, improving member and regulator regulation. Its techniques include risk management [30]. Consequently, it is interesting to examine how ICTs could enable governance and establish accessibility and integrity in the co-operative system. Co-operatives are expected to fulfill the co-operative objectives.
Smart co-operatives are related to the strategy that implements intelligent technologies [31]. Many co-operatives in Thailand have implemented enterprise resource planning (ERP) to help their members manage business transactions and comply with the regulatory activities. This smart co-operative strategy is the consequence of technological disruptions directly relating to consistency, accuracy, visibility, efficiency, and sustainability. Improving participation through digital technology is a challenging goal [32]. In smart co-operatives, processes and strategies are enhanced through ICT, which creates an effective co-operative system and facilitates processes. The problems members encounter in attaining services should be fixed and these procedures should be improved.
Therefore, the research question is, “What are the components of an enterprise architecture for smart co-operative management?” This research question led to the development of a conceptual framework for smart co-operative management. An expert panel is expected to evaluate the framework using a quantitative evaluation method to ensure the framework’s content validity. We conducted the research protocol without technological bias and universal implications. These experts determined the framework’s completeness and business–IT alignment. In the Introduction, we thoroughly discussed the smart co-operative framework for sustainable development, which focuses on five layers: infrastructure and technology, data and information, applications, business, and governance. In the Literature Review and Methodology sections, we discuss how the data were collected using a semi-structured questionnaire to determine what makes a smart co-operative able to quantify expert opinions and how the content validity index (CVI) was used to ensure the framework fit. The Results, Discussion, and Conclusion sections present the framework for smart co-operatives, designed to enable all sizes and sorts.

2. Literature Review

2.1. Smart Co-Operative Management Concept

Based on the previous study, the conceptual model of a smart co-operative has shown the significant contributions of this research in looking at how the critical parts of a smart co-operative affect each other [33]. The data demonstrated that, without improving their management and services, it is hard to guide the long-term growth of co-operatives (co-ops) in a good way. For example, the process is digitized; however, it is not satisfied. The process is still duplicated, takes a long time, and is unavailable. Hence, smart co-ops must combine co-operative principles, business models, and information communication technology (ICT) to build values and governance. ICT is currently essential in facilitating this process. This was discovered as the primary goal and accomplishment in co-operatives regarding the co-operative enterprise. Based on the available data, this study suggests the smart co-operative concept, which divides its essential components into three dimensions and integrates ICT to support and advance each dimension: smart member, smart economy, and smart governance.
Members are encouraged to participate using ICT to increase member involvement, knowledge management, and communication to ensure the sustainable development of co-operatives. Knowledge is essential for enhancing services and performance [19,34,35]. An information system (IS) that supports administration and communication related to teaching and learning processes, organizes, and distributes educational materials. The most popular approach for accessing resources on computers, laptops, smartphones, and tablets is e-learning. E-learning offers many advantages over traditional learning methods. The development and improvement of decision-making processes in various activities that influence co-operatives depend heavily on the engagement of members [27,34,36,37]. To trade information and give information to policymakers, members should also interact and communicate with one another [35,38]. Communication is crucial in raising awareness and understanding among members and administrations [39]. The smart economy should support co-operative management and services. ICT is critical for promoting member collaboration, value proposition, and value co-creation. These perform well for quality management and co-operative services. According to the research, the collaboration of many stakeholders in carrying out policies and action plans can ensure the quality and improvement of the decision-making process [27,31,40,41]. Contributing value propositions through value co-creation in co-operative businesses, services, and digital business models can benefit customers and other stakeholders [42,43,44,45]. In order to satisfy members’ needs and gain a competitive advantage, the value proposition concept should consider the needs of all stakeholders [46,47,48,49]. Furthermore, ICT-enabled services improve service quality, increase service delivery efficiency, and raise members’ standards of living [38,50].
Smart governance uses technology to support government operations, laws, and regulations. In previous research, co-operatives were governed by a democratic system to benefit their members [3,4,5,11]. A co-operative operation influences several stakeholders. Regulations, monitoring, assessment, and corporate governance are crucial to improving transparency and confidence in co-operatives. New innovative and government channels are proposed, such as e-governance and e-democracy, including procedures such as e-voting [38,51,52], to promote democratic decision-making processes and improve transparency in governance [12,32,53,54]. Decision-making processes can be enhanced by involving stakeholders in monitoring co-operative management [27,34,36]. In order to improve and ensure efficient management and avoid any instances of risk, a governance system leads to monitoring and managing the quality of information [6,55,56]. The success of engaging and inspiring members is influenced by corporate governance, which is a key factor in ownership feelings [12]. ICT also plays a vital role in enhancing data quality, information exchange, integration, and monitoring, significantly improving decision-making accuracy and efficacy [22,57,58,59]. Additionally, IT governance is essential for smart governance and increasing effectiveness, efficiency, and transparency [60,61,62,63]. The suggested model is displayed in Figure 1.

2.2. Enterprise Architecture (EA)

Enterprise architecture (EA) is a strategic tool used to close the communication gap between business and IT stakeholders. It describes an enterprise’s goal from an integrated business and IT perspective. Employing EA has a many benefits, including assisting businesses in better aligning their IT and business strategies [64]. The EA model, a framework for ensuring alignment between business and IT strategies and operating model guiding principles, is well-known worldwide [65]. Enterprise architecture can also help businesses improve efficiency, agility, timely supply of products and services, revenue expansion, and cost reduction. EA benefits come from effective EA procedures and proper use of EA services and products. A significant component of the process is also involved in both social and cultural aspects. From the first day, when thorough knowledge begins to develop, through the final years, when quantified results materialize, organizations can benefit from EA [66]. The results show that enterprise architecture was adopted and implemented in many ways [67]. Implementing EA results leads to re-engineering projects that require significant IT investments in the long term [68]. As a result, many organizations, including federal, state, and local governments, have adopted EA, which links business and information technology (IT) to help the enterprise achieve its goals. Additionally, EA incorporates the organizational processes supported by IT, such as planning, analysis, designing, and management-level decision-making, and it improves the knowledge of many stakeholders. Enterprise architecture development should be carried out in two stages: an architectural stage and an engineering stage. The architectural stage starts with a general requirement and synthesizes distant possible plans, from which the “user” selects one. This decided TO-BE architecture delivers a solid specification for technological development. The engineering stage starts with the selected future architecture and creates an optimized enterprise design and a staged transition plan. The as-is and to-be enterprise design states are transferred in the transition plan. Enterprise engineering design evolves in response to new technologies and requirements. EA development is staged to provide early management investment and minimize risk. Even though the architectural stage does not cost much, it is necessary for it to be effective [69]. There are many EA frameworks available; the well-accepted ones include the following.

2.2.1. The ZACHMAN Framework

The Zachman Framework is one of the famous EA frameworks [70]. The Zachman Framework is a schema, or a synthesis, of two traditional classification schemes that have existed for a long time. It provides the basic architecture and descriptive representation of perceptual criteria. It is split into two sections: communication interrogatives to address the six what, how, when, who, where, and why questions, and reification transformations to address the same issues. The framework is a logical ontology and allows the user to figure out how to reach the required structure. It is not a methodology because it does not suggest a specific way to attain, manage, or analyze the data it represents [71]. Since the dawn of the information age, business has evolved and become more complex. In the information age, enterprise architecture determines whether a company will survive. The Zachman Framework is an important part of creating enterprise architecture as a framework for the operation of the enterprise [71].

2.2.2. The Open Group Architecture Framework (TOGAF)

According to the Open Group, the world’s most well-known and reliable enterprise architecture standard is TOGAF. Many corporations implement it. There are two critical elements: the architecture development method (ADM) and the architecture content framework (ACF) [64]. The TOGAF standard is a method and framework for enterprise architecture that the best organizations in the world use to improve the productivity of their organizations. It is the most well-known and trustworthy enterprise architecture standard, guaranteeing standardization, procedures, and communication among enterprise architecture specialists. It provides a systematic methodology and supports enterprise architecture adoption, production, use, and maintenance resources. The descriptive deliverables of each exercise phase have been fundamentally prioritized in the proposed TOGAF, which focuses more on the creativity, assessment, and elaboration stages [72].
The Open Group Architecture Framework (TOGAF) provides structures, such as a checklist and guidelines, for establishing an EA plan that emphasizes an organization’s key components. The four fundamental levels are business, data, applications, and technology architecture. Business connects governance, business strategy, organization, and process. Business is a domain that includes transformation. The application layer is sometimes called the “system blueprint”, and the business goal must be in sync. Utilizing these is necessary while working with essential business services. There are logical and physical architectures in the data model. The technical domain provides a detailed description of the selected technologies. Hardware and software for the IT infrastructure are offered [72].

2.2.3. The Federal Enterprise Architecture Framework (FEAF)

EA frameworks are differentiable based on their applied purposes [70]. Therefore, the Federal Enterprise Architecture Framework (FEAF) was developed around the architectural principles suitable for an organization’s policies and procedures. The enterprise architecture (EA) process and the implementation of the architecture are both regulated by specific principles. It is separated into business, data, application, and technological architectures. The guide is adaptive and adaptable to fulfill individual requirements. The United States federal government also uses the federal enterprise architecture framework (FEAF) to facilitate information sharing and interoperability. Furthermore, some challenges involving EA components, including monitoring, performance measurement, risk management, and regulatory compliance, require consideration [64].

2.3. Proposed Framework

The conceptual framework for smart co-operative management comprises infrastructure and technology, data and information, application, business, and governance. It combines smart members, smart economy, smart governance, co-operative principles, and IT governance. The framework promotes stakeholder engagement, satisfaction, and involvement through accessible e-commerce, e-services, e-administration, and e-governance with accessible data. ICT is essential for effective management, and enterprise architecture was added to the framework. The smart co-operative management framework was proposed as follows.

2.3.1. Business

The business layer is the primary layer of the co-operative that aims to serve and provide the members with products and services. Therefore, this layer is the initial layer of the co-operative management framework. All operations of co-operatives must follow the co-operative principles (CPs). Co-operative principles (CPs) are administrative guidelines that directly and indirectly affect the performance of co-operatives [9]. CPs are responsible for directing the co-operative’s delivery to members, promoting governance, creating transparency, and improving member life quality [33]. The regulations should align with the CPs and address governance and security concerns. The business layer focuses on co-operative service and management, such as cost benefits and cost-effectiveness.

2.3.2. Application

In the last 20 years, electronic platforms employing new technologies have quickly expanded throughout developed nations [73]. Therefore, the application layer has a role in enabling co-operative services, management, and governance. This layer supports services that are required to carry out business and governance. E-services are a critical way to improve client interaction with the service, enhancing the overall customer experience [57]. This enables all stakeholders to collaborate on providing services. Additionally, the application facilitates communication between co-operative members and management by making information more accessible, improving the relationship. E-learning has been proven to replace traditional learning methods in recent global lockdowns due to the COVID-19 pandemic. It has many advantages over conventional learning methods, such as wider accessibility of learning material and fast communication [74]. The core business of the smart co-operative is derived from the e-banking, e-commerce, and e-service concepts. E-banking enables users to access accounts; conduct business; or attain information about finances, goods, and services using a public or private network, including the Internet [75].

2.3.3. Data and Information

Digital disruption has allowed all information to be digitized, including co-operative information. Previous research has found that transforming big data can improve management efficiency [76]. The business transaction records and member data are required for systematic data processes. Moreover, IT enhances the capabilities of members to participate in co-operative systems with accurate data [33]. While permitting a two-way communication channel and data management, it should be adopted to ensure data quality and interoperability. The data sources are from two service channels: online self-service and desk service. Online self-service refers to business transactions made by members, whereas desk service refers to business transactions made by co-operative staff when members request service onsite. Hence, to eliminate the error data, IT can use application controls, which are input, processing, and output controls, to ensure that data are accurate and complete. The outcomes of information quality are completeness, accuracy, and consistency [77] and, when information is properly distributed, it promotes data accuracy and integrity [78].
The data and information layer was taken into consideration by the researcher after developing the conceptual framework. The conceptual framework developed the key data for the co-operative information system, which includes members, loans, deposits, trading, human resources, assets, finance, and accounting. Data standards must ensure data quality and openness while promoting the integration and meaningful use of data and information. The data governance framework is the most widely adopted standard for establishing a continuous process for developing and improving policies and standards for data management [79]. This is shown as the business of a smart co-operative flow in Figure 2.

2.3.4. Infrastructure and Technology

The infrastructure and technology must support a connected environment. Transmission control protocol/internet protocol (TCP/IP) is a set of recently introduced communication protocols used by the Internet that allows the massive computer network to establish and close connections with other computers in different locations [80]. Wireless networks have become basic infrastructures and cloud technology has been widely adopted in many organizations, with the ability to effectively identify hidden connections [81]. A data center is a secure physical and storage infrastructure facility that provides servers, storage subsystems, networking switches, routers, firewalls, cabling, and physical racks to facilitate co-operative business and applications. Moreover, the Internet of Things (IoT) and cloud computing are two distinct technologies that have the potential to be disruptive and enable a wide range of applications [82]. Currently, blockchain technology can secure governance by offering immutability in stored records and ensuring transparency in lending operations [83]. Additionally, blockchain technology can increase transparency, traceability, and security [84]. Furthermore, big data analytics (BDA) assists a company in making productive and efficient decisions [85] and provides new insights and influences on the results of efficiency improvements [67]. Application programming interface (API) is an automation, data accessibility, and risk mitigation tool that builds automation work, establishes data resource connections, controls data access, and creates value by connecting different software to exchange information between and within organizations [86]. Robotic process automation (RPA) is a technology that reduces costs and improves performance in routine tasks [87,88]. AI and data analytics are becoming robust processes to help organizations make informed and data-driven decisions [89]. Additionally, digital signature technology is a cryptographic opera that combines an electronic signature with the data used to verify the signature process [90]. Digital signatures are legally valid cryptographic primitives used for contract verification, notarization, authentication, and encryption. These are important to facilitate and improve co-operative business processes.

2.3.5. Governance

The final layer is governance, including the control, regulation, and standard for the business and technology. It is adopted by data governance, COBIT, and ITIL to promote data quality, data security, interoperability, risk management, and service improvement. Smart governance and IT security are essential for a smart co-operative organization to function properly. Data governance, COBIT, and ITIL frameworks ensure good quality services, efficient management, and transparency. However, they can be vulnerable to online crimes such as hacking, spyware, ransomware, phishing, and website spoofing [75]. The primary obstacle to using e-service channels is protecting the system’s security. Moreover, security is very important to the user when making electronic business transactions [91]. Therefore, the governance layer is an important component of the smart co-operative management framework. It focuses on monitoring, data analytics, and the tracking system. Various systems or applications in the system must integrate the data by sharing them within the network infrastructure. Data sharing promotes integrity and consistency and reduces the amount of duplicated data [92]. Data governance is a component of smart governance that emphasizes efficient data exchange, integration, sharing, and retrieval. Access control, privacy, and security risks are often mentioned, especially when considering sensitive private data [93]. Hence, the governance layer is the activity to control both business processes and ICT to ensure participation and transparent decision-making processes for all stakeholders in a smart co-operative.

3. Methodology

In this section, the research process is described. Qualitative and quantitative methods were used. The study expanded on the smart co-operative management conceptual model. Refer to the smart co-operative framework, which is a digital co-operative system. The purpose is to redesign the conceptual framework for co-operative organizations in relation to sustainable development with smart concepts, business models, and guidelines or IT standards to support information technology capabilities for smart co-operatives. In order to achieve the desired result according to the suggested framework and to support the framework’s design assumptions, it is crucial to identify the appropriate research methodology. This is the reason it is emphasized in this paper. The smart co-operative framework’s research methodology is illustrated in Figure 3.
The major task of this step is to determine which components of the conceptual model will be used to create the core framework that will serve as the system design for the smart co-operative framework. First, the Open Group Architecture Framework (TOGAF) is initiated to map the conceptual model component in the core enterprise architecture framework. These can be divided into four categories: business, technology, applications, and data and information. These are the co-operative principles while incorporating an important IT function. The entities will be clarified and named in the framework’s information flow. The business and information flow of the framework will be divided into four tiers based on TOGAF, COBIT, and IT governance.
The goal of framework design based on enterprise architecture was to establish a strong, effective, and well-aligned enterprise architecture that fits the organization’s goals. This approach relied significantly on TOGAF, expert evaluations, and the CVI (content validity index). By utilizing these tools to create and assess the framework, it was possible to identify any gaps or potential improvement areas. CVI is a method that may have to be used to perform the acceptance of a framework component and ensure that the framework is consistent with the organization’s broader innovation strategy [36,65,94].

3.1. Smart Co-Operative Management Conceptual Framework

The long-term growth of co-operatives while making improvements to their management and services is our key consideration. Smart co-operatives must combine co-operative principles, business models, and ICT in order to build co-operative values, co-operative businesses, and co-operative governance [31]. The development and improvement of decision-making processes in various activities that influence co-operatives depend on the engagement of members. The participation of members is encouraged by the aspect of smart members. ICT is important in encouraging member involvement, knowledge management, and communication [19,27,34,35,36,37,38,39]. ICT is critical for promoting member collaboration, value proposition, and value co-creation. The value proposition concept should consider the needs of all stakeholders. ICT-enabled services improve service quality, increase service delivery efficiency, and raise members’ standard of living [27,38,40,41,42,43,44,45,46,47,48,49,50]. Several stakeholders influence a co-operative operation to improve transparency and confidence in co-operatives [21,38,51]; regulations, monitoring, assessment, and corporate governance are crucial components [95]. Smart governance involves using ICT to develop new channels for improving governance [96], which are e-governance and e-democracy [23]. Hence, the transformation of core services and information services is the goal of implementing the enterprise architecture [36].

3.2. Evidence-Based Review

This step summarized the components as well as the factors that are relevant to EA. The framework will ensure the alignment between business and IT strategies. EA incorporates the organizational processes supported by IT, such as planning, analysis, designing, and management-level decision-making. Smart governance uses technology to improve monitoring, process control, decision-making, democracy, and transparency. It is separated into business, data, application, and technological architectures. The framework is flexible and meets the user’s needs.
The Zachman Framework provides the basic architecture, relationship, and descriptive representation of perceptual criteria. Therefore, the researchers developed an assumption that was split into two sections: communication interrogatives to address the six what, how, when, who, where, and why questions. The output identified the stakeholder relations, data, procedures, and business understanding. Then, TOGAF is used for content analysis and to create the framework. TOGAF is the most well-known and trustworthy enterprise architecture standard. It guarantees standardization, procedures, and communication among enterprise architecture specialists. TOGAF provides a systematized architecture development methodology and supporting resources that address the steps of adoption, production, use, and maintenance. Moreover, TOGAF provides structures, such as a checklist and a guideline, for establishing an EA plan. The four fundamental levels are business, data, applications, and technology architecture. The technical domain provides a detailed description of the selected technologies [72]. We conclude the components and factors in Table 1.

3.3. Analysis and Mapping

This stage involves transforming the smart co-operative conceptual model into a conceptual framework. We finalized the main layer of the smart co-operative management framework, which includes infrastructure and technology, data and information, applications, and business. However, the business includes smart members, smart governance, smart economy, and co-operative principles. IT security is applied to all components according to the standard of security by design.
The business process and service in this framework are essential, along with smart members as the roles of co-operative members. The co-operative organization has evolved into a digital firm, and the objective is to promote stakeholder engagement, satisfaction, and involvement through accessible e-commerce, e-services, e-administration, and e-governance with accessible data. The electronic (e) indicates that the process requires the application in order to improve, allowing accessible and convenient service. The IT governance framework and the EA framework are incorporated into the smart governance dimension. Figure 4 illustrates the transformation of a smart co-operative conceptual model into a conceptual framework.

3.4. Framework Design and Development

The researcher contributed a framework with critical success factors derived from the smart co-operative management conceptual framework combined with enterprise architecture (EA). The smart co-operative management conceptual framework was followed by analysis and mapping, consisting of the ten key factors following the conceptual model. The transition from the conceptual model to the conceptual framework, as demonstrated in Figure 4, is from a smart co-operative management conceptual model to a conceptual framework. This phase was divided into five layers, which are business, application, data and information, infrastructure and technology, and governance, as shown in Table 2.
In summary, the framework is proposed. The smart co-operative management framework aims to improve co-operative business processes, service quality, and efficiency management by using information and communication technology (ICT). First, an electronic platform will be implemented to aid the service channel. Data and information concern members, loans, deposits, trading, human resources, assets, and finance and accounting. Governance is embedded into every process and function of the co-operative and encourages data security, interoperability, quality, risk management, and service enhancement. This framework can help ensure high-quality services, effective management, and transparency in the co-operative.

3.5. Conceptual Framework Validation

This section focuses on the final stages of developing the smart co-operative conceptual framework. After conducting the confirmatory factor analysis and conceptual model design, the framework is evaluated by a panel of experts. The experts are specialists in the co-operative and information technology fields; they have varied degrees of experience in co-operative management, regulation, and information technology, and use experienced international standard and co-operative principles as a guideline or a framework for all co-operative operations, as shown in Table 3. Therefore, the experience of experts is justified for validating the framework and reflects the international implication for potentially generalizing the framework globally. The item-content validity index (I-CVI) is used to measure the level of agreement on the validity of each component of the framework. Previous studies have shown that a panel of five to ten experts is preferable [94], but using more than ten experts is generally not essential [101]. The nine experts were chosen based on their qualifications and experience in co-operative and technology management. To ensure content validity, the expert panel used content validity index (CVI) as a quantitative evaluation method to assess the framework’s completeness. Experts evaluated each layer and the overall framework using semi-closed-ended questions with two answers: “agree” or “disagree”, as well as providing suggestions for improvement.

3.5.1. Data Collection

In the situation of the COVID-19 pandemic, the researcher found that the online questionnaire was an effective tool for collecting data. Using an online channel that allowed access to the respondents, the researcher provided online forms and virtual meetings as online channels to access respondents. The data were collected using expert opinion questionnaires on the suitability and completeness of the framework for implementation, as shown in Figure 5. The framework was designed based on previous research on the conceptual model of smart co-operative management [33]. The questionnaires included semi-closed-ended questions with two answers: “agree” or “disagree”, which the respondents could choose. If experts do not agree, they can provide suggestions for improvement.

3.5.2. Content Validity Index (CVI)

The context and content validity of the smart co-operative management framework was evaluated by agreement index experts. The validity test results of the experts in the final round are shown in Table 3, where “Y” denotes expert agreement and “N” denotes expert disagreement. Two items on the semi-closed-ended questions with the responses were included in the I-CVI calculation to determine the relationship and agreement by item. The experts evaluated each item based on their judgment and expertise. The acceptable I-CVI value is 0.78 or higher when the number of experts is 6 to 10 [102,103], and Kappa (k*) must be greater than 0.8 in order to meet the requirements [104]. For calculating I-CVI, the following equation is used:
I - CVI = A N ,
where “A” is the number of experts who agreed.
The following is the formula and the criteria: multi-rater Kappa statistics support the value of Kappa (k*), a Kappa statistic, as it is more likely to be regarded as the validity factor by experts [105]. There are three possible interpretations: exceptional (k* > 0.74), decent (k* = 0.60–0.74), and fair (k* = 0.40–0.59) [102,103]. The following formulas apply to the value of Kappa (k*):
k * = ( I - CVI   -   P c ) ( 1   -   P c ) ,  
and
P c = [ N ! A ! ( N   -   A ) ! ] 0 . 5 N ,
where “N” is the number of experts [103].

4. Results

Experts completed the evaluation and a panel debate was held to complete the framework. The co-operative and technological fields are areas of expertise for BA specialists. This result (Table 4) shows that five layers (L1–L5), including the overall framework completeness agreement (CF), were excellent. All four layers (business, application, data and information, infrastructure and technology, and governance) are extremely valid and necessary for the framework (Kappa > 0.8) [104]. The framework is entirely consistent with co-operative principles and its efficiency and governance in co-operative management have been established. The framework also promotes governance and transparency. Although successfully establishing the component of the information-sharing process and flow has proven difficult, it still has significant value and is an indicator of system effectiveness. Infrastructure and technology are accepted to support other layers and drive the co-operative business to transform into a smart co-operative. These content experts determine the framework’s completeness as follows.
This validation was completely agreed upon in the second round. The final agreement of nine experts’ responses to a specific expert survey on this proposed framework revealed a consensus of 100% agreement, indicating that this framework is highly applicable as a smart co-operative management framework for executing the digitalized transformation. The framework of smart co-operative management is based on infrastructure and technology, data and information, applications, business, and governance, which combine with a smart economy, smart members, smart governance, co-operative principles, and IT security. The framework aims to foster stakeholder engagement, satisfaction, and involvement through accessible e-commerce, e-services, e-administration, and e-governance with accessible data. The co-operative organization has gradually transformed into a digital organization and ICT is essential for efficient administration. The suggested framework is displayed in Figure 5.

4.1. Business

The business layer is designed to improve co-operative service, management, and governance. It consists of a core operation and a support operation. The core operations are membership, lending, depositing, and trading. An electronic platform is implemented to aid the service channel, allowing members and management to access the products and services more easily. The operation supports promoting the decision-making, governing, and promotion processes. Core business is the first place to initiate digital transformation. Hence, it provides the quality of goods and services, while support for business consists of three parts: administration, knowledge and information, and participation. These activities facilitate management efficiency in co-operatives and facilitate activities for human resource development and communication efficiency. These activities improved the co-operative’s governance and collaboration efficiency.

4.2. Application

The application layer of smart co-operative management is divided into two groups: core functions and support functions. Core functions are support functions, such as e-management, e-monitoring, and e-risk management, while support functions are administrative functions, knowledge and information, and participation. These activities facilitate administration, communication, government, human resource development, and communication efficiency. They also facilitate voting, referenda, meetings, and collaboration activities, which improve the co-operative’s governance and collaboration efficiency.

4.3. Data and Information

The data and information layer is the third layer of the smart co-operative management framework. Data governance is an important part of smart governance, focusing on effective data exchange, integration, sharing, and retrieval. It is powered by a co-operative information architecture and includes information about members, loans, deposits, trading, human resources, assets, and finance and accounting. Privacy must be a concern when data are managed throughout the data life cycle. Co-operative interoperable infrastructure seeks to provide an efficient connection while also ensuring the integrity and openness of the data. Data governance also facilitates data management, assists with the interoperability goal, and describes the data structure and messages delivered and received across a TCP/IP network. Moreover, security, including access control, complies with the standards and regulations.

4.4. Infrastructure and Technology

The infrastructure and technology are connected through co-operative businesses, applications, and stakeholders. Transmission control protocol/internet protocol (TCP/IP) and wireless networks, the Internet of Things (IoT), cloud computing, and blockchain are technologies that support applications. Big data analytics (BDA) and application programming interface (API) are important technologies that can improve efficiency, security, and governance. Data analytics and artificial intelligence (AI) are effective tools for assisting co-operatives in making data-driven decisions. Robotic process automation (RPA) is a technology that aims to minimize costs and increase efficiency in routine tasks. The digital signature is a cryptographic operation that combines an electronic signature with the data used to verify the signature process to ensure security and compliance. The virtual private network (VPN) is an important technology that uses a virtual connection to transport data packets from a private network to remote locations. These are important for facilitating and controlling all smart co-operative management system functions. Finally, the technology investment must show the business value to deliver the IT government.

4.5. Governance

The last important layer of the smart co-operative management framework is governance. Co-operative principles, corporate governance, data governance, IT governance, COBIT, and ITIL are the most important components of a smart co-operative management framework. It embeds core functions, support functions, and information management to encourage data security, interoperability, quality, risk management, and service enhancement. Smart governance and IT security are integrated within the governance layer, with technology for governance and regulation being key elements. IT governance, including data governance, COBIT, and ITIL frameworks, should govern all layers of the smart co-operative framework, including traditional and electronic processes. This layer can help ensure high-quality services, effective management, and transparency in the co-operative.

5. Discussion

The need to enhance co-operative services and management is a significant challenge in successfully guiding the sustainable development of co-operatives. This section discusses and presents a smart co-operative management framework based on the findings from the Results section, showing the main contributions of this research in examining the impact of the framework of the smart co-operative. In order to promote co-operative values, co-operative business, and co-operative governance in smart co-operatives, it is essential to integrate co-operative principles, business models, and technology. Information technology is currently very important in facilitating this process. In terms of co-operative enterprise, it was discovered to be the primary goal and achievement of co-operatives. In order to encourage and support efficiency and governance in co-operative management, this study suggests a smart co-operative architecture separated into five layers based on the EA idea.
The business layer is the main layer that focuses on co-operative services and management. Its mission is to serve and provide products and services to its members. The business layer consists of a core operation and a support operation. The core operations are lending, depositing, and trading. The electronic platform could enable members and management to access the products and services more easily than the desktop channel. Therefore, this framework transforms the existing channel into an electronic channel. However, all operations of co-operatives must follow the co-operative principles (CPs). The co-operative service includes both the members and management, including related stakeholders. The support operation supports the decision-making, governing, and promoting processes. This layer is designed to improve co-operative business processes, service quality, and efficiency management with information and communication technology (ICT).
The application layer of smart co-operative management is designed to support the co-operative business by adopting new technology for enhancing and improving member services and co-operative management with support for core and support functions. These layers facilitate all business functions, both core activities and support activities. All applications facilitated co-operative business to enable governance and efficiency in the co-operative [33,98].
The data and information come from the two service channels: online self-service and desk service. When information is properly distributed, it promotes data accuracy and integrity [92]. The co-operative information architecture has significantly driven the smart co-operative system. Interoperable, co-operative information aims to offer an effective link while simultaneously guaranteeing data quality and openness [99]. Data management is made easier by data governance, which also helps with the interoperability objective. Security, privacy, and access control concerns are often raised, especially regarding sensitive personal data [93,106].
The infrastructure and technology layer consists of important technologies such as transmission control protocol/internet protocol (TCP/IP), wireless networks, the Internet of Things (IoT), cloud computing, blockchain, big data, application programming interface (API), artificial intelligence (AI), virtual private networks (VPNs), and robotic process automation (RPA). This layer facilitates all layers that enable efficiency and governance in co-operative management [33].
The governance layer is an extremely important component of the smart co-operative management framework. It focuses on monitoring, data analytics, and the tracking system. The primary obstacle to using e-service channels is protecting the system’s security. Many processes use technology to promote integrity and consistency and reduce the amount of duplicate data [97]. In addition, this layer has been designed for the entire governance, which helped to enhance direct democracy, decision-making, monitoring, controlling, and transparency in the co-operative sector [33].

6. Conclusions

In this study, we successfully developed the enterprise architecture framework for smart co-operative management. The EA framework was designed as the target architecture because it is based on the smart concept and on co-operative businesses, as well as on their related co-operative principles. The core components were determined through a literature review, and a smart co-operative management conceptual model is classified as a smart member, smart economy, and smart governance that transforms into a smart co-operative enterprise architecture framework that consists of five layers (business, application, data and information, infrastructure and technology, and governance). The components were confirmed and validated for the framework using qualitative and quantitative methods. This framework provides the basis for management, support, and accomplishing goals set through governance. First, the business layer emphasizes providing quality services and efficient management through collaborative business processes [99]. Second, the application layer intends to assist the business layer by making it easier to access products and services. Third, the data and information layer focusses on the support application layer to facilitate co-operative business processes. Fourth, the infrastructure and technology layer is fundamental to a smart co-operative management framework that supports all layers [100]. Finally, the governance layer addresses all of the framework’s purposes for governing through the framework, including both business processes and information technologies (ITs) to fulfill the framework’s requirements for good governance and business continuity. Therefore, this framework facilitates and governs smart co-operatives to accomplish business efficiency and effective governance for sustainable development [33].

Author Contributions

Conceptualization, A.C., S.K. and T.M.; Methodology, A.C., M.T. and T.M.; Validation, A.C.; Formal analysis, A.C.; Investigation, A.C.; Resources, A.C.; Writing—original draft, A.C.; Writing—review & editing, S.K., M.T. and T.M.; Visualization, T.M.; Supervision, S.K., M.T. and T.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. International Cooperative Alliance. What Is a Cooperative? Available online: https://www.ica.coop/en/cooperatives/ (accessed on 25 November 2022).
  2. Types of Cooperatives. Available online: https://www.gov.mb.ca/jec/busdev/coop/types.html (accessed on 4 December 2022).
  3. Becchetti, L.; Ciciretti, R.; Paolantonio, A. The cooperative bank difference before and after the global financial crisis. J. Int. Money Financ. 2016, 69, 224–246. [Google Scholar] [CrossRef]
  4. Ji, C.; Jia, F.; Xu, X. Agricultural co-operative sustainability: Evidence from four Chinese pig production co-operatives. J. Clean. Prod. 2018, 197, 1095–1107. [Google Scholar] [CrossRef]
  5. Nelson, T.; Nelson, D.; Huybrechts, B.; Dufays, F.; O’Shea, N.; Trasciani, G. Emergent identity formation and the co-operative: Theory building in relation to alternative organizational forms. Entrep. Reg. Dev. 2016, 28, 286–309. [Google Scholar] [CrossRef]
  6. Benson, T. Building good management practices in Ethiopian agricultural cooperatives through regular financial audits. J. Co-Oper. Organ. Manag. 2014, 2, 72–82. [Google Scholar] [CrossRef]
  7. Luo, J.; Guo, H.; Jia, F. Technological innovation in agricultural co-operatives in China: Implications for agro-food innovation policies. Food Policy 2017, 73, 19–33. [Google Scholar] [CrossRef]
  8. Ruostesaari, M.-L.; Troberg, E. Differences in social responsibility toward youth—A case study based comparison of cooperatives and corporations. J. Co-Oper. Organ. Manag. 2016, 4, 42–51. [Google Scholar] [CrossRef]
  9. Guzmán, C.; Santos, F.J.; Barroso, M.D.L.O. Analysing the links between cooperative principles, entrepreneurial orientation and performance. Small Bus. Econ. 2019, 55, 1075–1089. [Google Scholar] [CrossRef]
  10. Alves, W.; Ferreira, P.; Araújo, M. Mining co-operatives: A model to establish a network for sustainability. J. Co-Oper. Organ. Manag. 2019, 7, 51–63. [Google Scholar] [CrossRef]
  11. Iliopoulos, C.; Värnik, R.; Filippi, M.; Võlli, L.; Laaneväli-Vinokurov, K. Organizational design in Estonian agricultural cooperatives. J. Co-Oper. Organ. Manag. 2019, 7, 100093. [Google Scholar] [CrossRef]
  12. Borgström, M. Effective co-operative governance: A practitioner’s perspective. J. Co-Oper. Organ. Manag. 2013, 1, 49–50. [Google Scholar] [CrossRef]
  13. Gupta, C. The co-operative model as a ‘living experiment in democracy’. J. Co-Oper. Organ. Manag. 2014, 2, 98–107. [Google Scholar] [CrossRef]
  14. Hooks, T.; McCarthy, O.; Power, C.; Macken-Walsh, Á. A co-operative business approach in a values-based supply chain: A case study of a beef co-operative. J. Co-Oper. Organ. Manag. 2017, 5, 65–72. [Google Scholar] [CrossRef]
  15. Pokharel, K.P.; Archer, D.W.; Featherstone, A.M. The Impact of Size and Specialization on the Financial Performance of Agricultural Cooperatives. J. Co-Oper. Organ. Manag. 2020, 8, 100108. [Google Scholar] [CrossRef]
  16. Juga, J.; Juntunen, J. Antecedents of retail patronage in cooperative retail context. J. Co-Oper. Organ. Manag. 2018, 6, 94–99. [Google Scholar] [CrossRef]
  17. McKillop, D.; French, D.; Quinn, B.; Sobiech, A.L.; Wilson, J.O.S. Cooperative financial institutions: A review of the literature. Int. Rev. Financ. Anal. 2020, 71, 101520. [Google Scholar] [CrossRef]
  18. Kurimoto. Cooperative Law Japan; Springer: Berlin/Heidelberg, Germany, 2013. [Google Scholar]
  19. Chareonwongsak, K. Enhancing board motivation for competitive performance of Thailand’s co-operatives. J. Co-Oper. Organ. Manag. 2017, 5, 1–13. [Google Scholar] [CrossRef]
  20. Pereira, G.V.; Parycek, P.; Falco, E.; Kleinhans, R. Smart governance in the context of smart cities: A literature review. Inf. Polity 2018, 23, 143–162. [Google Scholar] [CrossRef]
  21. Garcia Alonso, L.-D.C. Technology Helps, People Make: A Smart City Governance Framework Grounded in Deliberative Democracy. Public Adm. Inf. Technol. 2016, 11, 333–347. [Google Scholar]
  22. Bolívar, M.P.R. Governance Models and Outcomes to Foster Public Value Creation in Smart Cities. In Proceedings of the 18th Annual International Conference on Digital Government Research, Staten Island, NY, USA, 7–9 June 2017. [Google Scholar]
  23. Oliveira, T.A.; Oliver, M.; Ramalhinho, H. Challenges for Connecting Citizens and Smart Cities: ICT, E-Governance and Blockchain. Sustainability 2020, 12, 2926. [Google Scholar] [CrossRef]
  24. Rose, J.; Persson, J.S.; Heeager, L.T. How e-Government managers prioritise rival value positions: The efficiency imperative. Inf. Polity 2015, 20, 35–59. [Google Scholar] [CrossRef]
  25. Koltay, T. Data governance, data literacy and the management of data quality. IFLA J. 2016, 42, 303–312. [Google Scholar] [CrossRef]
  26. Nachrowi, E.; Nurhadryani, Y.; Sukoco, H. Evaluation of Governance and Management of Information Technology Services Using Cobit 2019 and ITIL 4. Resti J. (Syst. Eng. Inf. Technol.) 2020, 4, 734–774. [Google Scholar] [CrossRef]
  27. Reis, L.C.D.; Ferreira, S.B.L.; Bernardini, F.C.; Cappelli, C. Towards a COBIT5 approach to ICT governance requirements in smart cities. In Proceedings of the 13th International Conference on Theory and Practice of Electronic Governance, Athens, Greece, 23–25 September 2020. [Google Scholar]
  28. Falconer, M. Smart City Framework A Systematic Process for Enabling Smart+Connected Communities. Cisco Internet Bus. Solut. Group (IBSG) 2012, 12, 2–10. [Google Scholar]
  29. Hon, W.K.; Millard, C. Banking in the cloud: Part 3—Contractual issues. Comput. Law Secur. Rev. 2018, 34, 595–614. [Google Scholar] [CrossRef]
  30. Arnold, V.; Benford, T.; Canada, J.; Sutton, S.G. Leveraging integrated information systems to enhance strategic flexibility and performance: The enabling role of enterprise risk management. Int. J. Account. Inf. Syst. 2015, 19, 1–16. [Google Scholar] [CrossRef]
  31. Meijer, A.; Bolívar, M.P.R. Governing the smart city: A review of the literature on smart urban governance. Int. Rev. Adm. Sci. 2015, 82, 392–408. [Google Scholar] [CrossRef]
  32. Stratu-Strelet, D.; Gil-Gómez, H.; Oltra-Badenes, R.; Oltra-Gutierrez, J.V. Critical factors in the institutionalization of e-participation in e-government in Europe: Technology or leadership? Technol. Forecast. Soc. Chang. 2021, 164, 120489. [Google Scholar] [CrossRef]
  33. Chawviang, A.; Kiattisin, S. Sustainable Development: Smart Co-Operative Management Framework. Sustainability 2022, 14, 3641. [Google Scholar] [CrossRef]
  34. Reed, M.S.; Vella, S.; Challies, E.; De Vente, J.; Frewer, L.; Hohenwallner-Ries, D.; Huber, T.; Neumann, R.K.; Oughton, E.A.; Del Ceno, J.S.; et al. A theory of participation: What makes stakeholder and public engagement in environmental management work? Restor. Ecol. 2018, 26, S7–S17. [Google Scholar] [CrossRef]
  35. Yobe, C.L.; Ferrer, S.R.D.; Mudhara, M. Measuring the financial efficiency of agricultural cooperatives in South Africa: An application of the Simar–Wilson methodology. Agrekon 2020, 59, 269–286. [Google Scholar] [CrossRef]
  36. Thirasakthana, M.; Kiattisin, S. Sustainable Government Enterprise Architecture Framework. Sustainability 2021, 13, 879. [Google Scholar] [CrossRef]
  37. Liang, Q.; Hendrikse, G.; Huang, Z.; Xu, X. Governance Structure of Chinese Farmer Cooperatives: Evidence From Zhejiang Province. Agribusiness 2015, 31, 198–214. [Google Scholar] [CrossRef]
  38. Anggraeni, M.; Gupta, J.; Verrest, H.J.L.M. Cost and value of stakeholders participation: A systematic literature review. Environ. Sci. Policy 2019, 101, 364–373. [Google Scholar] [CrossRef]
  39. Neirotti, P.; De Marco, A.; Cagliano, A.C.; Mangano, G.; Scorrano, F. Current trends in Smart City initiatives: Some stylised facts. Cities 2014, 38, 25–36. [Google Scholar] [CrossRef]
  40. Verdegay, J.L.; Rodríguez, Z. A new decision support system for knowledge management in archaeological activities. Knowl. Based Syst. 2020, 187, 104843. [Google Scholar] [CrossRef]
  41. Jiang, H.; Geertman, S.; Witte, P. Avoiding the planning support system pitfalls? What smart governance can learn from the planning support system implementation gap. Environ. Plan. B Urban Anal. City Sci. 2020, 47, 1343–1360. [Google Scholar] [CrossRef]
  42. Pérez González, D.; Díaz Díaz, R. Public services provided with ICT in the smart city environment: The case of Spanish cities. J. Univers. Comput. Sci. 2015, 21, 248–267. [Google Scholar]
  43. Payne, A.; Frow, P.; Eggert, A. The customer value proposition: Evolution, development, and application in marketing. J. Acad. Mark. Sci. 2017, 45, 467–489. [Google Scholar] [CrossRef]
  44. Bocken, N.; Short, S.; Rana, P.; Evans, S. A value mapping tool for sustainable business modelling. Corp. Gov. Int. J. Bus. Soc. 2013, 13, 482–497. [Google Scholar] [CrossRef]
  45. Baldassarre, B.; Calabretta, G.; Bocken, N.M.P.; Jaskiewicz, T. Bridging sustainable business model innovation and user-driven innovation: A process for sustainable value proposition design. J. Clean. Prod. 2017, 147, 175–186. [Google Scholar] [CrossRef]
  46. Carvalho, J.M.S.; Jonker, J. Creating a Balanced Value Proposition: Exploring the Advanced Business Creation Model. J. Appl. Manag. Entrep. 2015, 20, 49–64. [Google Scholar] [CrossRef]
  47. Voorberg, W.H.; Bekkers, V.J.J.M.; Tummers, L.G. A Systematic Review of Co-Creation and Co-Production: Embarking on the social innovation journey. Public Manag. Rev. 2014, 17, 1333–1357. [Google Scholar] [CrossRef]
  48. Osborne, S.P.; Radnor, Z.; Strokosch, K. Co-Production and the Co-Creation of Value in Public Services: A suitable case for treatment? Public Manag. Rev. 2016, 18, 639–653. [Google Scholar] [CrossRef]
  49. Hamidi, F.; Gharneh, N.S.; Khajeheian, D. A Conceptual Framework for Value Co-Creation in Service Enterprises (Case of Tourism Agencies). Sustainability 2019, 12, 213. [Google Scholar] [CrossRef]
  50. Sebhatu, K.T.; Gezahegn, T.W.; Berhanu, T.; Maertens, M.; Van Passel, S.; D’Haese, M. Conflict, fraud, and distrust in Ethiopian agricultural cooperatives. J. Co-Oper. Organ. Manag. 2020, 8, 100106. [Google Scholar] [CrossRef]
  51. Walravens, N. Mobile Business and the Smart City: Developing a Business Model Framework to Include Public Design Parameters for Mobile City Services. J. Theor. Appl. Electron. Commer. Res. 2012, 7, 21–22. [Google Scholar] [CrossRef]
  52. Bolívar, M.P.R.; Meijer, A.J. Smart Governance: Using a Literature Review and Empirical Analysis to Build a Research Model. Soc. Sci. Comput. Rev. 2016, 34, 673–692. [Google Scholar] [CrossRef]
  53. Cronemberger, F.; Gil-Garcia, J.R. Big Data and Analytics as Strategies to Generate Public Value in Smart Cities: Proposing an Integrative Framework. In Setting Foundations for the Creation of Public Value in Smart Cities (Public Administration and Information Technology; Springer: Cham, Switzerland, 2019; pp. 247–267. [Google Scholar]
  54. Barns, S. Smart cities and urban data platforms: Designing interfaces for smart governance. City Cult. Soc. 2018, 12, 5–12. [Google Scholar] [CrossRef]
  55. Kozłowski, Ł. Cooperative banks, the internet and market discipline. J. Co-Oper. Organ. Manag. 2016, 4, 76–84. [Google Scholar] [CrossRef]
  56. Manita, R.; Elommal, N.; Baudier, P.; Hikkerova, L. The digital transformation of external audit and its impact on corporate governance. Technol. Forecast. Soc. Chang. 2019, 150, 119751. [Google Scholar] [CrossRef]
  57. Barrett, M.; Davidson, E.; Prabhu, J.; Vargo, S.L. Service innovation in the digital age: Key contributions and future directions. MIS Q. 2015, 39, 135–154. [Google Scholar] [CrossRef]
  58. Díaz-Díaz, R.; Pérez-González, D. Implementation of Social Media Concepts for e-Government. J. Organ. End User Comput. 2016, 28, 104–121. [Google Scholar] [CrossRef]
  59. Gervasi, O.; Murgante, B.; Misra, S.; Stankova, E.; Torre, C.M.; Rocha, A.M.A.; Taniar, D.; Apduhan, B.O.; Tarantino, E.; Ryu, Y. (Eds.) Computational Science and Its Applications—ICCSA 2018. In Proceedings of the 18th International Conference, Melbourne, VIC, Australia, 2–5 July 2018. Part III. [Google Scholar]
  60. Ben Yahia, N.; Eljaoued, W.; Ben Saoud, N.B.; Colomo-Palacios, R. Towards sustainable collaborative networks for smart cities co-governance. Int. J. Inf. Manag. 2021, 56, 102037. [Google Scholar] [CrossRef]
  61. Reddick, C.G.; Chatfield, A.T.; Jaramillo, P.A. Public opinion on National Security Agency surveillance programs: A multi-method approach. Gov. Inf. Q. 2015, 32, 129–141. [Google Scholar] [CrossRef]
  62. Abraham, R.; Schneider, J.; vom Brocke, J. Data governance: A conceptual framework, structured review, and research agenda. Int. J. Inf. Manag. 2019, 49, 424–438. [Google Scholar] [CrossRef]
  63. Merino, J.; Caballero, I.; Rivas, B.; Serrano, M.; Piattini, M. A Data Quality in Use model for Big Data. Future Gener. Comput. Syst. 2016, 63, 123–130. [Google Scholar] [CrossRef]
  64. Kotusev, S. TOGAF-based Enterprise Architecture Practice: An Exploratory Case Study. Commun. Assoc. Inf. Syst. 2018, 43, 321–359. [Google Scholar] [CrossRef]
  65. Mayakul, T.; Kiattisin, S.; Prasad, R. A Sustainable Medical Tourism FrameworkBased on the Enterprise ArchitectureDesign: The Case in Thailand. J. Green Eng. 2018, 8, 359–388. [Google Scholar] [CrossRef]
  66. Niemi, E.; Pekkola, S. The Benefits of Enterprise Architecture in Organizational Transformation. Bus. Inf. Syst. Eng. 2019, 62, 585–597. [Google Scholar] [CrossRef]
  67. Gong, Y.; Janssen, M. Roles and Capabilities of Enterprise Architecture in Big Data Analytics Technology Adoption and Implementation. J. Theor. Appl. Electron. Commer. Res. 2021, 16, 37–51. [Google Scholar] [CrossRef]
  68. Ilin, I.V.; Levina, A.I.; Dubgorn, A.S.; Abran, A. Investment Models for Enterprise Architecture (EA) and IT Architecture Projects within the Open Innovation Concept. J. Open Innov. Technol. Mark. Complex. 2021, 7, 69. [Google Scholar] [CrossRef]
  69. Alex Pavlak, P. Enterprise Architecture: Lessoins from classical architecture. J. Enterp. Archit. 2006, 2, 20–27. [Google Scholar]
  70. Rachmaniah, M.; Suroso, A.I.; Syukur, M.; Hermadi, I. Enterprise Architecture for Smart Enterprise System. Int. J. Adv. Comput. Sci. Appl. 2022, 13, 10. [Google Scholar] [CrossRef]
  71. Zachman, J.A. The Concise Definition of the Zachman Framework by: John A. Zachman. Available online: https://www.zachman.com/16-zachman/the-zachman-framework/35-the-concise-definition (accessed on 25 November 2008).
  72. The Open Group. The TOGAF® Standard, Version 9.2 Overview. 2022. Available online: https://www.opengroup.org/togaf-standard-version-92-overview (accessed on 1 February 2023).
  73. Blanc, D.L. E-Participation: A Quick Overview of Recent Qualitative Trends; Department of Economic and Social Affairs, United Nations: New York, NY, USA, 2020; Volume 163, pp. 1–22. [Google Scholar]
  74. Alam, M.M.; Ahmad, N.; Naveed, Q.N.; Patel, A.; Abohashrh, M.; Khaleel, M.A. E-Learning Services to Achieve Sustainable Learning and Academic Performance: An Empirical Study. Sustainability 2021, 13, 2653. [Google Scholar] [CrossRef]
  75. Chaimaa, B.; Najib, E.; Rachid, H. E-banking Overview: Concepts, Challenges and Solutions. Wirel. Pers. Commun. 2020, 117, 1059–1078. [Google Scholar] [CrossRef]
  76. Lnenicka, M.; Komarkova, J. Developing a government enterprise architecture framework to support the requirements of big and open linked data with the use of cloud computing. Int. J. Inf. Manag. 2019, 46, 124–141. [Google Scholar] [CrossRef]
  77. Bradford, M.; Henderson, D.; Baxter, R.J.; Navarro, P. Using generalized audit software to detect material misstatements, control deficiencies and fraud. Manag. Audit. J. 2020, 35, 521–547. [Google Scholar] [CrossRef]
  78. Jak, D. Implementation of Computer Assisted Audit Techniques in Application Controls Testing. Manag. Inf. Syst. 2009, 4, 9–12. [Google Scholar]
  79. Alhassan, I.; Sammon, D.; Daly, M. Data governance activities: An analysis of the literature. J. Decis. Syst. 2016, 25, 64–75. [Google Scholar] [CrossRef]
  80. Morgan, E.L. Implementing TCP/IP Communications with HyperCard. Inf. Technol. Libr. 1992, 11, 12. [Google Scholar]
  81. Shen, Y.; Huang, L.; Lu, X.; Yang, W. A novel comprehensive steganalysis of transmission control protocol/Internet protocol covert channels based on protocol behaviors and support vector machine. Secur. Commun. Netw. 2015, 8, 1279–1290. [Google Scholar] [CrossRef]
  82. Botta, A.; de Donato, W.; Persico, V.; Pescapé, A. Integration of Cloud computing and Internet of Things: A survey. Future Gener. Comput. Syst. 2016, 56, 684–700. [Google Scholar] [CrossRef]
  83. Patel, S.B.; Bhattacharya, P.; Tanwar, S.; Kumar, N. KiRTi: A Blockchain-Based Credit Recommender System for Financial Institutions. IEEE Trans. Netw. Sci. Eng. 2021, 8, 1044–1054. [Google Scholar] [CrossRef]
  84. Polas, M.R.H.; Jahanshahi, A.A.; Kabir, A.I.; Sohel-Uz-Zaman, A.S.M.; Osman, A.R.; Karim, R. Artificial Intelligence, Blockchain Technology, and Risk-Taking Behavior in the 4.0IR Metaverse Era: Evidence from Bangladesh-Based SMEs. J. Open Innov. Technol. Mark. Complex. 2022, 8, 168. [Google Scholar] [CrossRef]
  85. Shamim, S.; Zeng, J.; Shariq, S.M.; Khan, Z. Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Inf. Manag. 2019, 56, 103135. [Google Scholar] [CrossRef]
  86. Ofoeda, J.; Boateng, R.; Effah, J. Application Programming Interface (API) Research. Int. J. Enterp. Inf. Syst. 2019, 15, 76–95. [Google Scholar] [CrossRef]
  87. Aguirre, S.; Rodriguez, A. Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study. In Applied Computer Sciences in Engineering; Communications in Computer and Information Science; Springer: Berlin/Heidelberg, Germany, 2017; pp. 65–71. [Google Scholar]
  88. Huang, F.; Vasarhelyi, M.A. Applying robotic process automation (RPA) in auditing: A framework. Int. J. Account. Inf. Syst. 2019, 35, 100433. [Google Scholar] [CrossRef]
  89. Janssen, M.; Brous, P.; Estevez, E.; Barbosa, L.S.; Janowski, T. Data governance: Organizing data for trustworthy Artificial Intelligence. Gov. Inf. Q. 2020, 37, 101493. [Google Scholar] [CrossRef]
  90. Fang, W.; Chen, W.; Zhang, W.; Pei, J.; Gao, W.; Wang, G. Digital signature scheme for information non-repudiation in blockchain: A state of the art review. EURASIP J. Wirel. Commun. Netw. 2020, 2020, 56. [Google Scholar] [CrossRef]
  91. Sánchez-Torres, J.A.; Canada, F.-J.A.; Sandoval, A.V.; Alzate, J.-A.S. E-banking in Colombia: Factors favouring its acceptance, online trust and government support. Int. J. Bank Mark. 2018, 36, 170–183. [Google Scholar] [CrossRef]
  92. Shen, M.; Duan, J.; Zhu, L.; Zhang, J.; Du, X.; Guizani, M. Blockchain-Based Incentives for Secure and Collaborative Data Sharing in Multiple Clouds. IEEE J. Sel. Areas Commun. 2020, 38, 1229–1241. [Google Scholar] [CrossRef]
  93. Mutimukwe, C.; Kolkowska, E.; Grönlund, Å. Information privacy in e-service: Effect of organizational privacy assurances on individual privacy concerns, perceptions, trust and self-disclosure behavior. Gov. Inf. Q. 2020, 37, 101413. [Google Scholar] [CrossRef]
  94. Gilbert, G.E.; Prion, S. Making Sense of Methods and Measurement Lawshe’s Content Validity Index. Clin. Simul. Nurs. 2016, 12, 2. [Google Scholar] [CrossRef]
  95. Lin, R.; Xie, Z.; Hao, Y.; Wang, J. Improving high-tech enterprise innovation in big data environment: A combinative view of internal and external governance. Int. J. Inf. Manag. 2020, 50, 575–585. [Google Scholar] [CrossRef]
  96. Scholl, H.J.; AlAwadhi, S. Creating Smart Governance: The key to radical ICT overhaul at the City of Munich. Inf. Polity 2016, 21, 21–42. [Google Scholar] [CrossRef]
  97. Surbakti, F.P.S.; Wang, W.; Indulska, M.; Sadiq, S. Factors influencing effective use of big data: A research framework. Inf. Manag. 2020, 57, 103146. [Google Scholar] [CrossRef]
  98. Angelidou, M.; Psaltoglou, A.; Komninos, N.; Kakderi, C.; Tsarchopoulos, P.; Panori, A. Enhancing sustainable urban development through smart city applications. J. Sci. Technol. Policy Manag. 2017, 9, 146–169. [Google Scholar] [CrossRef]
  99. Dwivedi, Y.K.; Janssen, M.; Slade, E.L.; Rana, N.P.; Weerakkody, V.; Millard, J.; Hidders, J.; Snijders, D. Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling. Inf. Syst. Front. 2016, 19, 197–212. [Google Scholar] [CrossRef]
  100. Pan, Y.; Tian, Y.; Liu, X.; Gu, D.; Hua, G. Urban Big Data and the Development of City Intelligence. Engineering 2016, 2, 171–178. [Google Scholar] [CrossRef]
  101. Lynn, M.R. Determination and Quantification Of Content Validity. Nurs. Res. 1986, 35, 382–386. [Google Scholar] [CrossRef]
  102. Almanasreh, E.; Moles, R.; Chen, T.F. Evaluation of methods used for estimating content validity. Res. Soc. Adm. Pharm. 2019, 15, 214–221. [Google Scholar] [CrossRef] [PubMed]
  103. Pookkaman, W.; Samanchuen, T. An Innovation Framework of Medical Organic Cannabis Traceability in Digital Supply Chain. J. Open Innov. Technol. Mark. Complex. 2022, 8, 196. [Google Scholar] [CrossRef]
  104. Holey, E.A.; Feeley, J.L.; Dixon, J.; Whittaker, V.J. An exploration of the use of simple statistics to measure consensus and stability in Delphi studies. BMC Med. Res. Methodol. 2007, 7, 52. [Google Scholar] [CrossRef] [PubMed]
  105. Wynd, C.A.; Schmidt, B.; Schaefer, M.A. Two quantitative approaches for estimating content validity. West. J. Nurs. Res. 2003, 25, 508–518. [Google Scholar] [CrossRef]
  106. Subahi, A.; Theodorakopoulos, G. Detecting IoT User Behavior and Sensitive Information in Encrypted IoT-App Traffic. Sensors 2019, 19, 4777. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Smart co-operative conceptual model.
Figure 1. Smart co-operative conceptual model.
Sustainability 15 07328 g001
Figure 2. The co-operative information sharing process and flow.
Figure 2. The co-operative information sharing process and flow.
Sustainability 15 07328 g002
Figure 3. Research methodology.
Figure 3. Research methodology.
Sustainability 15 07328 g003
Figure 4. Transformation of a smart co-operative conceptual model into a conceptual framework.
Figure 4. Transformation of a smart co-operative conceptual model into a conceptual framework.
Sustainability 15 07328 g004
Figure 5. A smart co-operative management framework based on the EA concept.
Figure 5. A smart co-operative management framework based on the EA concept.
Sustainability 15 07328 g005
Table 1. The selected factors are based on our literature review.
Table 1. The selected factors are based on our literature review.
LayersReferences
GovernanceMeijer and Bolívar 2015 [31], Reddick, Chatfield et al. 2015 [84], Al-Ruithe, Benkhelifa et al. 2016 [3], Bolívar and Meijer 2016 [52], Merino, Caballero et al. 2016 [63], Botta, de Donato et al. 2016 [82], Díaz-Díaz and Pérez-González 2016 [58], Koltay 2016 [25], Bolívar 2017 [22], Barns 2018 [54], Pereira, Parycek et al. 2018 [20], Sánchez-Torres, Canada et al. 2018 [91], Reed, Vella et al. 2018 [34], Abraham, Schneider et al. 2019 [62], Blanc 2020 [73], Fang, Chen et al. 2020 [90], Jiang, Geertman et al. 2020 [41], Manita, Elommal et al. 2020 [56], Mutimukwe, Kolkowska et al. 2020 [93], Reis, Ferreira et al. 2020 [27], Shen, Duan et al. 2020 [92], Alam, Ahmad et al. 2021 [74], Ben Yahia, Eljaoued et al. 2021 [60], Stratu-Strelet, Gil-Gómez et al. 2021 [32], Chawviang and Kiattisin 2022 [33], Malaivongs, Kiattisin et al. 2022 [97]
BusinessBorgström 2013 [12], Benson 2014 [6], Voorberg, Bekkers et al. 2014 [47], Rose, Persson et al. 2015 [24], Garcia Alonso 2016 [21], Kozłowski 2016 [55], Nelson, Nelson et al. 2016 [5], Osborne, Radnor et al. 2016 [48], Baldassarre, Calabretta et al. 2017 [45], Chareonwongsak 2017 [19], Payne, Frow et al. 2017 [43], Hooks, McCarthy et al. 2017 [14], Shamim, Zeng et al. 2019 [85], McKillop, French et al. 2020 [17], Mutimukwe, Kolkowska et al. 2020 [93], Sebhatu, Gezahegn et al. 2020 [50], Alam, Ahmad et al. 2021 [74], Chawviang and Kiattisin 2022 [33]
ApplicationArnold, Benford et al. 2015 [30], Rose, Persson et al. 2015 [24], Díaz-Díaz and Pérez-González 2016 [58], Angelidou, Psaltoglou et al. 2017 [98], Blanc 2020 [73], Manita, Elommal et al. 2020 [56], Mutimukwe, Kolkowska et al. 2020 [93], Alam, Ahmad et al. 2021 [74], Patel, Bhattacharya et al. 2021 [83], Chawviang and Kiattisin 2022 [33]
Data and InformationElizabeth Davidson 2015 [57], Díaz-Díaz and Pérez-González 2016 [58], Merino, Caballero et al. 2016 [63], Koltay 2016 [25], Bolívar 2017 [22], Osvaldo Gervasi 2018 [59], Shamim, Zeng et al. 2019 [85], Shen, Bradford, Henderson et al. 2020 [81], Shen, Duan et al. 2020 [92], Chawviang and Kiattisin 2022 [33]
Infrastructure and TechnologyMorgan 1992 [80], Hon, Rose, Persson et al. 2015 [24], Shen, Huang et al. 2015 [81], Hon, Garcia Alonso 2016 [21], Millard et al. 2016 [99], Pan, Tian et al. 2016 [100], Aguirre and Rodriguez 2017 [87], Hon and Millard 2018 [29], Huang and Vasarhelyi 2019 [88], Ofoeda, Boateng et al. 2019 [86], Shamim, Zeng et al. 2019 [85], Janssen, Brous et al. 2020 [89], Lin, Xie et al. 2020 [95], Manita, Elommal et al. 2020 [56], Oliveira, Oliver et al. 2020 [23], Shen, Duan et al. 2020 [92], Wang, Fang, Chen et al. 2020 [90], Gong and Janssen 2021 [67], Patel, Bhattacharya et al. 2021 [83], Stratu-Strelet, Gil-Gómez et al. 2021 [32], Afshar Jahanshahi et al. 2022 [84], Chawviang and Kiattisin 2022 [33], Polas, Afshar Jahanshahi et al. 2022 [84]
Table 2. Result of the mapping layer analysis.
Table 2. Result of the mapping layer analysis.
LayerDefinitionComponents
BusinessThe business layer had core and support functions. Membership, trading, lending, and depositing were crucial. Promoting, controlling, and supporting decision-making. To ensure that members and management could access products and services, an electronic platform would be established. This framework changed the channel. The business of the co-operative was separated into two sessions. To begin, the core function was the provision of goods and services, which included membership, lending, depositing, and trading. Finally, the support function was divided into three components: administration, knowledge and information, and participation.
ApplicationSmart co-operative management applied modern technology to core and support tasks to improve member service and management. Administration, knowledge and information, and involvement assist the co-operative core business.Core functions are e-member, e-lending, e-deposit, and e-commerce, and the support functions are as follows:
1. These apps aided human resource development and co-operative communication.
2. E-voting, e-referenda, e-meetings, and e-collaboration comprised the participation app.
3. All support services included administration, communication, and government
Data and InformationThe collaboration of the third component of the smart co-operative management framework, which was enabled by a co-operative information architecture, required data standards.The co-operative information system contained data regarding members, loans, deposits, trading, human resources, assets, finances, and accounting.
Infrastructure and TechnologyInfrastructure, technology, and applications co-operate. These technologies enabled smart co-operative management.A secure information system was supported by technologies such as TCP/IP, wireless networks, IoT, cloud computing, blockchain, data centers, big data analytics, application programming interface (API), data analytics, AI, RPA, digital signature, virtual private network (VPN), and others.
GovernanceThe final important layer of the smart co-operative management framework is governance. It is embedded in every process and function of a smart co-operative, such as business processes: core function, support function, and information management.Co-operative principles, corporate governance, data governance, IT governance, COBIT, and ITIL are all used in the framework. Using the framework, data security, interoperability, quality, risk management, and service improvement were all improved.
Table 3. Experts’ background and characteristics.
Table 3. Experts’ background and characteristics.
ExpertsType of ExpertProfessional RoleExperience
Expert 1Co-operative managementCo-operative policy and decision-maker>10 Years
Expert 2Co-operative managementCo-operative policy and decision-maker>10 Years
Expert 3Enterprise architectureCo-operative regulator (co-operative
auditing department)
>20 Years
Expert 4Co-operative informaticsCo-operative regulator (co-operative
auditing department)
>10 Years
Expert 5Co-operative managementCo-operative regulator (co-operative promotion department)>20 Years
Expert 6Co-operative innovationCo-operative regulator (co-operative promotion department)>10 Years
Expert 7IT AuditingCo-operative regulator (co-operative
auditing department)
>20 Years
Expert 8IT managementCo-operative regulator (co-operative
auditing department)
>10 Years
Expert 9Data protection officer (DPO)Enterprise architecture, banking system>15 Years
Table 4. Agreement index calculation of a smart co-operative management framework.
Table 4. Agreement index calculation of a smart co-operative management framework.
LayersE 1E 2E 3E 4E 5E 6E 7E 8E 9Agreement NumberI-CVI k * Evaluation
Business (L1)YYYYYYYYY91.001.00Excellent
Application (L2)YYYYYYYYY91.001.00Excellent
Data and Information (L3)YYYYYYYYY91.001.00Excellent
Infrastructure and Technology (L4)YYYYYYYYY91.001.00Excellent
Governance (L5)YYYYYYYYY91.001.00Excellent
Completeness of Framework (CF)YYYYYYYYY91.001.00Excellent
Agreement number666666666S-CVI/Ave1.00
Agreement proportion1.001.001.001.001.001.001.001.001.00S-CVI/UA1.00
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chawviang, A.; Kiattisin, S.; Thirasakthana, M.; Mayakul, T. A Smart Co-Operative Management Framework Based on an EA Concept for Sustainable Development. Sustainability 2023, 15, 7328. https://doi.org/10.3390/su15097328

AMA Style

Chawviang A, Kiattisin S, Thirasakthana M, Mayakul T. A Smart Co-Operative Management Framework Based on an EA Concept for Sustainable Development. Sustainability. 2023; 15(9):7328. https://doi.org/10.3390/su15097328

Chicago/Turabian Style

Chawviang, Anassaya, Supaporn Kiattisin, Montree Thirasakthana, and Theeraya Mayakul. 2023. "A Smart Co-Operative Management Framework Based on an EA Concept for Sustainable Development" Sustainability 15, no. 9: 7328. https://doi.org/10.3390/su15097328

APA Style

Chawviang, A., Kiattisin, S., Thirasakthana, M., & Mayakul, T. (2023). A Smart Co-Operative Management Framework Based on an EA Concept for Sustainable Development. Sustainability, 15(9), 7328. https://doi.org/10.3390/su15097328

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop