Open innovation in developing an early standardization of battery swapping according to the Indonesian national standard for electric motorcycle applications

Sutopo, Wahyudi et al. Article Open innovation in developing an early standardization of battery swapping according to the Indonesian national standard for electric motorcycle applications Journal of Open Innovation: Technology, Market, and Complexity Provided in Cooperation with: Society of Open Innovation: Technology, Market, and Complexity (SOItmC) Suggested Citation: Sutopo, Wahyudi et al. (2022) : Open innovation in developing an early standardization of battery swapping according to the Indonesian national standard for electric motorcycle applications, Journal of Open Innovation: Technology, Market, and Complexity, ISSN 2199-8531, MDPI, Basel, Vol. 8, Iss. 4, pp. 1-23, https://doi.org/10.3390/joitmc8040219 This Version is available at: https://hdl.handle.net/10419/274520 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Citation: Sutopo, W.; Prianjani, D.; Fahma, F.; Pujiyanto, E.; Rasli, A.; Kowang, T.O. Open Innovation in Developing an Early Standardization of Battery Swapping According to the Indonesian National Standard for Electric Motorcycle Applications. J. Open Innov. Technol. Mark. Complex. 2022,8, 219. https://doi.org/ 10.3390/joitmc8040219 Received: 6 November 2022 Accepted: 13 December 2022 Published: 15 December 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Journal of Open Innovation: Technology, Market, and Complexity Article Open Innovation in Developing an Early Standardization of Battery Swapping According to the Indonesian National Standard for Electric Motorcycle Applications Wahyudi Sutopo 1,* , Dana Prianjani 2, Fakhrina Fahma 3, Eko Pujiyanto 2, Amran Rasli 4 and Tan Owee Kowang 5 1University Centre of Excellence for Electrical Energy Storage Technology, Universitas Sebelas Maret, Surakarta 57126, Indonesia 2Master Program of Industrial Engineering Department, Faculty of Engineering, Universitas Sebelas Maret, Surakarta 57126, Indonesia 3Research Group Industrial Engineering and Techno-Economic, Department of Industrial Engineering, Faculty of Engineering, Universitas Sebelas Maret, Surakarta 57126, Indonesia 4Faculty of Business and Management, Inti International University, Nilai 71800, Malaysia 5Azman Hashim International Business School, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia *Correspondence: [email protected] Abstract: This research aims to achieve early standardization for battery swapping in line with domestic capabilities and global standards, and to protect Indonesian battery swap stakeholders. By distributing questionnaires to 190 respondents, the Framework for Analysis, Comparison, and Testing of Standards (FACTS) approach was used to analyze stakeholder needs, compare global standards regarding battery swaps, and validate the Indonesian National Standard (SNI) framework. An open innovation approach was considered to integrate a FACTS approach with open participation, mutual understanding, and consensus to generate parameters. Therefore, characteristics of open participation, mutual understanding, and consensus were identified using FACTS to catalyze market needs as well as stakeholder needs. The relationship between SNI implementation variables, national uniqueness, and stakeholder needs was predicted using structural equation modeling (SEM). We found that the proposed constructs—i.e., electromagnetic compatibility, equipment construction requirements, marking and instruction, and protection against electric shock—positively affect SNI implementation. Meanwhile, the SNI implementation, national uniqueness, and stakeholder protection positively affect SNI acceptance. Therefore, SNI acceptance can be obtained by considering SNI implementation, national uniqueness, and stakeholder protection. The findings of this study can be used to develop an SNI battery swap test that is globally competitive, has national characteristics, and considers domestic capabilities when developing the SNI documentation. Keywords: battery swap; early standardization; FACTS; global competitiveness; open innovation; SEM 1. Introduction Motorcycles are oil-fueled motor vehicles with the highest use percentage among Indonesian citizens from an economic standpoint [ 1 ]. There is a sufficiently strong potential to convert from oil-fueled motorcycles to electric motorcycles in Indonesia because of the high number of motorcycle enthusiasts. Activities to immediately implement electric vehicle programs in Indonesia are supported by political, economic, technological, and social factors [ 2 ]. The Indonesian government has issued regulations for accelerating batterybased electric motor vehicle programs for road transportation. The government attempts to provide a foundation, direction, and legal certainty to encourage energy conservation in the transportation sector. As a result, this demonstrates the country’s readiness to accelerate the transition from fossil-fueled to electric vehicles [3]. J. Open Innov. Technol. Mark. Complex. 2022,8, 219. https://doi.org/10.3390/joitmc8040219 https://www.mdpi.com/journal/joitmc J. Open Innov. Technol. Mark. Complex. 2022,8, 219 2 of 23 Battery swapping, also known as battery-as-a-service, allows electric vehicles’ owners to exchange discharged batteries for charged ones at swapping stations. Battery swapping, like most commodities, has its own supply chain system, from suppliers, orders, mass production, distribution, marketing, and service, to consumers [ 2 ]. However, battery swap testing standards must be developed before the technology can be mass-produced and used as a driving force for electric motorcycles. The early supply chain of the battery swap—i.e., the product development stage, which includes planning, design, development, and pre-production—must be considered in the development of standardization [ 4 ]. As the supervisor, developer, and coordinator of activities in the field of standardization, the national standardization body has authority over the process of developing these standards [ 5 ]. Each process of developing battery swap products—including planning, design, development, and pre-production—must follow the standard development process, which includes the formulation and setting of standard activities. Every use of a particular product must focus on consumer protection [ 6 ]. Consumer protection is required by the law to support the conversion of oil-fueled motorcycles to electric motorcycles. A standard can be used to provide such protection. Due to the unavailability of an Indonesian National Standard for battery swap product safety and performance, battery swap research for national electric motorcycles may lack a minimum level of quality and reference. As a result, product test standards must be used as a reference. Consumers can be assured that their products are appropriate in terms of performance, safety, and production by using product test standard processes in certifications or product standard labels [ 6 ]. Furthermore, Indonesia’s diverse natural conditions and its citizens’ distinct habits necessitate national uniqueness. In Indonesia, battery swapping is a new technology with broad applicability. Over time, the lifecycle of a new technology may be more or less similar to that of other innovations. Depending on the technology’s market adoption, it may or may not follow the diffusion of innovation [ 7 ]. In this case, knowing when and how to apply standards successfully requires understanding of the battery swap lifecycle. A new technology’s lifecycle is divided into four stages: invention, growth, maturity, and decline [ 8 ]. The invention phase is when the technology is first developed. It has a slow initial growth rate as experiments, research, and development on battery swaps and electric vehicles are carried out during this phase [ 9 – 14 ]. The second phase, known as the growth phase, is characterized by steady and rapid growth as the technology improves. This phenomenon occurs when the battery swap technology is widely used and developed [ 15 – 20 ]. At the maturity phase, the technology is mature, relatively stable, and has competitive implementations in the market. This phase is critical, as the compatibility of the technology is of high priority, and there would be a loss in market share unless compatibility is embraced [ 7 ]. The real challenge is to bring battery swap technology to market and keep it from dying in the valley of death. As a result, strategies for accelerating the commercialization of this new technology are required [ 21 ]. Therefore, it is necessary to introduce standards during the maturity phase to strengthen the technological innovation to cross the valley of death, emerge in the market, and avoid being trapped in the decline phase. This study employed the FACTS approach, which can be applied to develop and implement standards as per the recommendations of the National Institute of Standards and Technology [ 22 ]. Various standards—such as battery cell standards, battery modules, battery management, and battery-powered wheelchairs—have been developed [ 23 – 26 ]. Standardization and open innovation have similar characteristics [27]. Open innovation is a topic of innovation that is increasingly being discussed. Open innovation refers to the process carried out by companies to find new technologies, innovations, research, and products externally [ 28 ]. The aim of open innovation is to tap into the R&D community, even outside the industry, in order to align the pace of internal research and innovation with external developments. Open innovation is a systematic approach to innovation management that exploits internal advantages and capabilities while inte- J. Open Innov. Technol. Mark. Complex. 2022,8, 219 3 of 23 grating external opportunities and sources from industry, government, universities, and society [29]. The open innovation approach was considered to integrate a FACTS approach through the interaction of inbound and outbound processes. Thus, the knowledge, experience, and needs of stakeholders can be captured in deliverable standards. In developing standards, the FACTS approach considers all relevant stakeholders’ interests that represent transparency and open participation. As a result, the consensus principle in standardization allows interested parties to express their viewpoints and be accommodated accordingly. This paper outlines a comprehensive strategy for establishing an early standardization for battery swaps in electric motorcycle applications. This research aims to develop an SNI for battery swap testing that is globally competitive, has a national character, and is within domestic capabilities using FACTS and SEM methods. The FACTS method was employed to create a globally competitive standard framework for battery swapping, while the SEM method was applied to determine which construct models can support acceptance of standard implementation so that battery swap stakeholders in Indonesia can implement the standard. 2. Literature Review 2.1. FACTS and SEM Approach The FACTS method has been used to develop various other standards, such as for battery cells, battery modules, battery management, and wheelchairs [23–26]. The FACTS approach considers the interests of all relevant stakeholders; this approach also provides a framework for analyzing, comparing, and testing standards by structuring information through the Zachman framework. The Zachman framework is used to obtain information using the 5W1H questions (Who? What? When? Where? Why? How?). However, the FACTS method cannot determine which indicators or constructs should be the priority to be included in the standard. As a result, the SEM approach is applied to determine the relationships between constructs and indicators to identify which construct models support the adoption of standards early in the commercialization process. SEM is a multivariate statistical technique that combines factor analysis and regression analysis to investigate the relationships between variables in a model, either between indicators and their constructs or between the constructs themselves [ 30 , 31 ]. Latent variables are also known as unobserved variables, constructs, and latent constructs. Manifest variables are also known as observed, measured, and indicators. SEM combines two statistical methods: psychological factor analysis and simultaneous equation modeling developed in econometrics [32]. There have been many studies using the SEM method. SEM is a powerful tool that has been utilized to explore the public acceptance, especially towards environmental sustainability [ 33 – 35 ]. Previous studies have also researched the acceptance and purchase of electric vehicles using the SEM method [ 36 , 37 ]. Other research on the development of the TAM model as an indicator of electric taxi acceptance can also be carried out using SEM [38]. Table 1shows the position of this research compared to the existing literature. J. Open Innov. Technol. Mark. Complex. 2022,8, 219 4 of 23 Table 1. State of the art of this study’s field. Authors Study Object Number of Constructs Number of Indicators FACTS SEM Prianjani et al. [25] LiFEPO4battery cell standard 3 15 X- Aristyawati et al. [23] LiFEPO4battery module standard 6 - X- Rahmawatie et al. [26] LIFEPO4battery management system standard 4 14 X- Pratiwi et al. [24] Manual wheelchair standard 7 - X- Nosi et al. [37] The intensity of e-car purchases by millennials 6 34 - X Prianjani et al. [39]Conceptual model framework standardization and testing battery swapping in Indonesia 4 - X- Wang et al. [40] Public acceptance of electric vehicles 12 43 - X Globisch et al. [38]Using the TAM model as an SEM indicator of electric taxi acceptance 11 - - X Zhao et al. [41] Consumers’ acceptance of electric vehicles 6 27 - X Adu-Gyamfi et al. [42]Investigating the adoption intention for battery swap technology for electric vehicles 7 27 - X Gulzari et al. [43]A young consumer electric vehicle rental behavioral model 7 27 - X This study Development of battery swap testing standards using FACTS and SEM methods 7 58 X X 2.2. Open Innovation Dynamics Innovation is one of the important elements that drive the success, sustainability, and competitive advantage of a company. Various innovation models continue to be developed to make it easier for companies to innovate, such as the open innovation model. The dynamics of open innovation continue to evolve over time. There have been many studies on models that can be applied to manage product development in the context of open innovation. The main key to the success of open innovation is choosing the right partners so that economic performance and sustainability performance of innovation can be met simultaneously [ 44 ]. In addition, an effective open strategy can be implemented to achieve the desired competitive advantage from innovation management activities [ 45 ]. In open innovation, there are roles for government, industry, society, and universities in the innovation ecosystem to form dynamic micro-relationships that can then evolve into macro dynamics [ 46 ]. Furthermore, Yun et al. [ 47 ] explored the role of culture in driving the dynamics of open innovation, where open innovation is influenced by three-dimensional interactions, namely, entrepreneurship, intrapreneurship, and organizational entrepreneurship. There is a correlation between the types of networks that lead to collaboration and the types of innovation activities pursued and innovation outcomes realized [48]. Universities, which in this study are parties that actively carry out product research and development, have a large impact as a result of their engagement in open innovation. The administration of a university can target open innovation interactions and foster the emergence of specific university–industry relationships by providing professional assistance [ 49 ]. Universities can serve as a reliable intermediary to facilitate collaboration between multiple parties in a secure environment [50,51]. Innovation capabilities and market outcomes from open innovation depend on the strategy implemented. This can affect changes in the innovation efficiency curves resulting from the use of open innovation business models. Open innovation strategies appear in a variety of ways; hence, their effects are similarly diverse [ 52 ]. Therefore, strategic management of open innovation is vital for addressing dynamic capabilities as they relate to the right time to use open innovation. Thus, the positive and constraining aspects of open innovation in various circumstances can be identified [53]. J. Open Innov. Technol. Mark. Complex. 2022,8, 219 5 of 23 3. Research Methodology This study began with data collected from various sources and direct observation. We reviewed international battery swap standards for electric motorcycle applications, stakeholder requirements, standard technique adoption procedures, and SNI writing procedures. The interaction between standardization and open innovation was considered in the form of interactions between inbound and outbound processes. Inbound processes, which consider knowledge, experience, and stakeholders’ needs, were utilized with the FACTS steps. Meanwhile, outbound processes, which consider deliverable standards that meet the current and future needs of stakeholders, were utilized for the SEM approach. The experiment was carried out at the battery swap mini-plant of the university, where battery swap components, battery cells, and battery modules are available to be installed on electric motorcycles. This study uses variance-based SEM to develop exploratory SNI design models for electric motorcycle battery swap tests based on first-generation TAM theory [ 54 ]. The SNI battery test framework, which is the output of the FACTS approach, is the latent construct in developing the dependent variable of this study, i.e., perceived ease of use. This study is a continuation of previous research, where we developed the initial framework [ 39 ]. The initial framework used sequential mixed methods [55] and is illustrated in Figure 1. J. Open Innov. Technol. Mark. Complex. 2022, 8, x FOR PEER REVIEW 5 of 22 which consider knowledge, experience, and stakeholders’ needs, were utilized with the FACTS steps. Meanwhile, outbound processes, which consider deliverable standards that meet the current and future needs of stakeholders, were utilized for the SEM approach. The experiment was carried out at the battery swap mini-plant of the university, where battery swap components, battery cells, and battery modules are available to be installed on electric motorcycles. This study uses variance-based SEM to develop exploratory SNI design models for electric motorcycle battery swap tests based on first-generation TAM theory [54]. The SNI battery test framework, which is the output of the FACTS approach, is the latent construct in developing the dependent variable of this study, i.e., perceived ease of use. This study is a continuation of previous research, where we developed the initial framework [39]. The initial framework used sequential mixed methods [55] and is illustrated in Figure 1. Figure 1. Sequential mixed methodology of the study. 3.1. FACTS Approach The SNI framework was built using the FACTS approach, implemented in four stages. Stakeholders’ requirements were analyzed based on the perspectives and opinions of the stakeholders, such as the government, battery swap R&D, battery swap laboratories, battery swap factories, electric motorcycle factories, and electric motorcycle users (i.e., people who have ridden an electric motorcycle). In the second stage, technical analysis was performed by converting stakeholders’ opinions into technical language. A comparison of standards was made in the third stage by analyzing the similarities and differences in the reference standard. The Zachman framework was used to identify gaps and overlaps between the reference standard and the technical specifications of stakeholder requirements at this stage. The reference standard was IEC 62840-2:2016, containing the standard battery swap requirements for electric vehicles [56]. This standard was chosen because no international standards for the battery swap test were available. The comparison of stakeholder requirements and reference standards is shown in Table 2. Figure 1. Sequential mixed methodology of the study. 3.1. FACTS Approach The SNI framework was built using the FACTS approach, implemented in four stages. Stakeholders’ requirements were analyzed based on the perspectives and opinions of the stakeholders, such as the government, battery swap R&D, battery swap laboratories, battery swap factories, electric motorcycle factories, and electric motorcycle users (i.e., people who have ridden an electric motorcycle). In the second stage, technical analysis was performed by converting stakeholders’ opinions into technical language. A comparison of standards was made in the third stage by analyzing the similarities and differences in the reference standard. The Zachman framework was used to identify gaps and overlaps between the reference standard and the technical specifications of J. Open Innov. Technol. Mark. Complex. 2022,8, 219 6 of 23 stakeholder requirements at this stage. The reference standard was IEC 62840-2:2016, containing the standard battery swap requirements for electric vehicles [ 56 ]. This standard was chosen because no international standards for the battery swap test were available. The comparison of stakeholder requirements and reference standards is shown in Table 2. Table 2. Standard comparison. Stakeholder Requirements Standard Reference (Adopted from IEC 62840-2:2016) Protection against electric shock Chapter 7 Equipment constructional requirements Chapter 8 Electromagnetic compatibility Chapter 9 Marking and instruction Chapter 10 Based on an analysis of the similarities and differences in the reference standards, we subsequently conducted standard testing and verification of any testing standards that could meet the requirements of battery swap stakeholders for electric motorcycle applications in the final stage. The output of the FACTS approach was used to develop a questionnaire to create the SNI framework from the SEM analysis. 3.2. SEM Approach SEM was used for the second stage of data processing. Domestic capacity was recapitulated based on the FACTS output to implement the proposed SNI for battery swap testing. This information was then used as the input for SEM. First, based on the problem or research hypothesis, a structural model (i.e., outer model) of the relationships between latent variables in the partial least squares was created. Then, a measurement model (i.e., inner model) was created to determine whether the indicator was reflective or formative. The path diagram was then created based on the outcomes of the external and internal model designs. Subsequently, estimation of parameters was carried out by iteration. The goodness of fit was measured to ensure the validity of the model. Finally, hypothesis testing was performed. 3.2.1. Structural Model Four latent variables (i.e., constructs) were used in the model, namely, SNI implementation, stakeholder protection, national uniqueness, and SNI acceptance. The SNI implementation variable was obtained from data processing using the FACTS method, resulting in a non-equivalent adopted SNI based on IEC 62840-2: 2016. The stakeholder protection variable was generated from a literature review conducted previously. In addition, the national uniqueness variable was based on 10 goals of standardization [ 57 ]. Finally, the SNI acceptance variable was the outcome of this study. The exogenous latent variables identified were national uniqueness, stakeholder protection, electric shock protection, equipment constructional requirements, electromagnetic compatibility, and marking and instruction. Meanwhile, the endogenous latent variables were the SNI implementation and its success. Figure 2depicts the structural model and variable direction based on TAM [ 54 ]. 3.2.2. Measurement Model The measurement model emphasizes the relationships among measured (i.e., observed) variables underlying the latent variables. In this study, all constructs have reflective indicators, which measure each construct. For each construct, a measurement model was developed and consisted of the following aspects: • Manifest variable (indicator), which is denoted by X for indicators related to exogenous constructs or Y for indicators related to endogenous constructs; • Loading factor ( λ ), which represents the direct correlation between construct and indicator; J. Open Innov. Technol. Mark. Complex. 2022,8, 219 7 of 23 •Latent variable or construct (ξ); • Measurement error, which is denoted by δ for error related to exogenous constructs or εfor error related to endogenous constructs. J. Open Innov. Technol. Mark. Complex. 2022, 8, x FOR PEER REVIEW 6 of 22 Table 2. Standard comparison. Stakeholder Requirements Standard Reference (Adopted from IEC 62840-2: 2016) Protection against electric shock Chapter 7 Equipment constructional requirements Chapter 8 Electromagnetic compatibility Chapter 9 Marking and instruction Chapter 10 Based on an analysis of the similarities and differences in the reference standards, we subsequently conducted standard testing and verification of any testing standards that could meet the requirements of battery swap stakeholders for electric motorcycle applications in the final stage. The output of the FACTS approach was used to develop a questionnaire to create the SNI framework from the SEM analysis. 3.2. SEM Approach SEM was used for the second stage of data processing. Domestic capacity was recapitulated based on the FACTS output to implement the proposed SNI for battery swap testing. This information was then used as the input for SEM. First, based on the problem or research hypothesis, a structural model (i.e., outer model) of the relationships between latent variables in the partial least squares was created. Then, a measurement model (i.e., inner model) was created to determine whether the indicator was reflective or formative. The path diagram was then created based on the outcomes of the external and internal model designs. Subsequently, estimation of parameters was carried out by iteration. The goodness of fit was measured to ensure the validity of the model. Finally, hypothesis testing was performed. 3.2.1. Structural Model Four latent variables (i.e., constructs) were used in the model, namely, SNI implementation, stakeholder protection, national uniqueness, and SNI acceptance. The SNI implementation variable was obtained from data processing using the FACTS method, resulting in a non-equivalent adopted SNI based on IEC 62840-2: 2016. The stakeholder protection variable was generated from a literature review conducted previously. In addition, the national uniqueness variable was based on 10 goals of standardization [57]. Finally, the SNI acceptance variable was the outcome of this study. The exogenous latent variables identified were national uniqueness, stakeholder protection, electric shock protection, equipment constructional requirements, electromagnetic compatibility, and marking and instruction. Meanwhile, the endogenous latent variables were the SNI implementation and its success. Figure 2 depicts the structural model and variable direction based on TAM [54]. Figure 2. Structural model. Figure 2. Structural model. The residual regression value on endogenous latent variables denoted by ζ also contributes to the model. The regression coefficient between exogenous latent variables and endogenous latent variables is denoted by γ , while the relationship between two endogenous variables is denoted by β . Table 3presents the proposed constructs and indicators in the SEM model, while Table 4shows the measurement model for each construct. On the other hand, Figure 3shows the path diagram of the SEM model. Table 3. The construct and indicators in the SEM model. Construct Indicators Code National uniqueness Conformity to standardization goals A1 Exchangeability A2 Diversity control A3 Compatibility A4 Increased empowerment of resources A5 Communication A6 Security, safety, and health A7 Environmental conservation A8 Technology transfer A9 Reducing trade barriers A10 Protection of stakeholders Protecting the government B1 Protecting battery swap R&D B2 Protecting battery swap laboratories B3 Protecting the battery swap industry B4 Protecting the electric motor industry B5 Protecting electric vehicle users B6 J. Open Innov. Technol. Mark. Complex. 2022,8, 219 8 of 23 Table 3. Cont. Construct Indicators Code Protection against electric shock Standard contains protection against electric shock C1 Standard contains constructional equipment requirements C2 Standard contains electromagnetic compatibility C3 Standard contains marking and instruction C4 Protection against direct and indirect contact C5 Protection for power supply equipment C6 SBS charging equipment protection C7 Direct contact C8 Protection in battery enclosure C9 Protection regulations on coupler C10 Protective measures on energy with high voltage C11 Protective measures for unexpected events C12 Control signals on the shielding conductors C13 Additional protection C14 Manual reset of circuit breakers, residual current devices, and other equipment C15 Protection of persons in accordance with standard C16 Compliance of telecommunications network with standard C17 Equipment constructional requirements Compliance with standard C18 Switch C19 Contactor C20 Circuit breakers C21 Relay C22 Electrical measurements C23 Clearances and creepage distance C24 Resistance against mechanical, electrical, thermal, and environmental stresses C25 Minimum level of protection against mechanical impact C26 Material flammability and resistance against effects of solvents or liquids, vibration, and shock C27 Protective coating on the exposed surface in corrosion test C28 Enclosure stability in dry heat test C29 External parts of insulating material and parts are subject to heat and fire tests. C30 Ball pressure test C31 Resistance to tracking C32 Resistance to solar radiation C33 J. Open Innov. Technol. Mark. Complex. 2022,8, 219 15 of 23 Table 10 shows the relationship between the variables stated in the hypothesis. The path coefficient values range from − 1 to +1. A path coefficient value close to +1 indicates a strong positive relationship between the variables, while a path coefficient value close to − 1 indicates a strong negative relationship. The generated path coefficients are presented in Table 8. Table 10. Path coefficients. Hypothesis Path Path Coefficient H1 Electromagnetic compatibility →SNI implementation −0.218 H2 Equipment constructional requirements →SNI implementation 0.513 H3 Marking and instruction →SNI implementation 0.244 H4 Protection against electric shock →SNI implementation 0.384 H5 SNI implementation →SNI acceptance 0.143 H6 National uniqueness →SNI acceptance 0.473 H7 Stakeholder protection →SNI acceptance 0.109 The coefficient of determination (R 2 ) is used to show the predictive power of the path model. The value of R 2 ranges from 0 to 1. The value of R 2 , which is close to 1, indicates that the prediction accuracy is getting stronger. Table 11 shows the coefficients of determination for the inner model in this study. Table 11. Coefficients of determination. R2R2Adjusted Accuracy SNI implementation 0.664 0.657 Strong SNI acceptance 0.340 0.329 Medium The effect size f 2 can be used to determine the effect of an exogenous variable on the related endogenous variable. Table 12 presents the f2values for each path. Table 12. Path coefficients. Hypothesis Path f2Effect Size H1 Electromagnetic compatibility →SNI implementation 0.121 Medium H2 Equipment constructional requirements →SNI implementation 0.513 Large H3 Marking and instruction →SNI implementation 0.168 Medium H4 Protection against electric shock →SNI implementation 0.283 Large H5 SNI implementation →SNI acceptance 0.019 Small H6 National uniqueness →SNI implementation 0.301 Large H7 Stakeholder protection →SNI acceptance 0.010 Small The predictive relevance Q 2 aims to see how well the path model can predict the original observed value. The assessment Q 2 value is determined using the stipulation that if the value of Q 2 is more significant than zero, then a particular endogenous construct has predictive relevance. The predictive relevance values for the model are presented in Table 13. J. Open Innov. Technol. Mark. Complex. 2022,8, 219 16 of 23 Table 13. Predictive relevance. Latent Variable SSO SSE Q2= (1 −SSE/SSO) Electromagnetic compatibility 190,000 190,000 0 Equipment constructional requirements 760,000 760,000 0 SNI implementation 380,000 174,968 0.540 SNI acceptance 380,000 317,710 0.164 National uniqueness 950,000 950,000 0 Marking and instruction 380,000 380,000 0 Stakeholder protection 570,000 570,000 0 Protection against electric shock 760,000 760,000 0 The value effect size q 2 is obtained by comparing the Q 2 value when all exogenous variables are involved in the path model analysis with the Q 2 value when one of the exogenous variables is omitted in the path model analysis. The q 2 value in this study is determined as follows: q2= Q2 complete −Q2 ommited 1−Q2 complete = 0.719 −0.180 1−0.719 =1.922 4.3. Hypothesis Test Hypothesis testing in this study uses a significance level of 0.15. The proposed hypothesis has a positive direction. Therefore, the test conducted is a one-tailed test with the number of variables (k) = 8 and the number of respondents (n) = 190 [ 62 ]. A hypothesis is accepted if the following conditions are met: • The path coefficient is in the same direction as the proposed hypothesis, which is positive for a hypothesis that says “has a positive influence” or negative for a hypothesis that says “has a negative influence”. •t-Value ≥t-table. The results of the hypothesis testing are presented in Table 14. Table 14. Hypothesis test. Hypothesis Path Path Coefficient t-Value t-Table Decision H1 Electromagnetic compatibility has a positive effect on SNI implementation −0.218 4.237 1.042 Accepted H2 Equipment constructional requirements have a positive effect on SNI implementation 0.513 9.315 1.042 Accepted H3 Marking and instruction have a positive effect on SNI implementation 0.244 3.097 1.042 Accepted H4 Protection against electric shock has a positive effect on SNI implementation 0.384 7.479 1.042 Accepted H5 SNI implementation has a positive effect on SNI acceptance 0.143 1.636 1.042 Accepted H6 National uniqueness has a positive effect on SNI acceptance 0.473 5.755 1.042 Accepted H7 Stakeholder protection has a positive effect on SNI acceptance 0.109 1.123 1.042 Accepted J. Open Innov. Technol. Mark. Complex. 2022,8, 219 17 of 23 5. Discussions 5.1. SEM outer Model Analysis 5.1.1. Convergent Validity of Indicators Convergent validity is a measure that shows how much the indicator has a positive correlation with other indicators of the same construct. For research indicators that are still newly developed and have not been tested, the minimum value of outer loading is 0.5 or more [ 58 ], so that indicators with an outer loading of less than 0.5 will be removed. Removal of indicators with an extreme loading value of less than 0.5 is carried out gradually, starting from the smallest outer loading value. Every time an indicator is removed, the outer loading value is rechecked until the outer loading indicator is more than 0.5. In the SEM model with reflective indicators, the direction of the causality is from the latent variable to the indicator, which means that the latent variable determines the indicators, so all reflective indicators must have a high correlation with the latent variables. Because all indicators must have a high correlation, reducing the indicator should not change the meaning of the latent variable. An outer loading value of 0.5 or more means that the indicator has a 50% contribution to building its latent variable’s constructor [59]. In the latent construct of national uniqueness, five indicators were removed: A1, A2, A4, A9, and A10. • A1 (Battery swap components, such as battery cells, modules, and packs, must have passed the safety test) A1 has the purpose represented by A7, which contains “test standards for swap battery products which aim to ensure safety and health for users of swap battery products”. Therefore, if A1 is removed, it does not change the meaning of the construct of national uniqueness. • A2 (Standard dimensions of swapped batteries’ size, voltage, and electric current are required at all battery swap charging stations throughout Indonesia to produce equivalent performance and power without making changes or adjustments.) The A2 indicator has the intent and purpose represented by the A5 indicator, which contains “the use of swap batteries to reduce the waste of resources (time, people, and capital)”. Reduced waste of resources when using swapped batteries can be obtained if the minimum standard is implemented; hence, there are no significant differences between battery swap brands. The differences between battery swap brands can directly affect consumers and disrupt the supply chain’s flow [ 2 ]. Therefore, if A2 is removed, it does not change the meaning of the construct of national uniqueness. • A4 (Process suitability of swapped batteries for concurrent use with other relevant products without creating unnecessary interactions) The purpose of the A4 indicator can be represented by A3, which contains the “application of standard dimensions of size, voltage and electric current of swap batteries to all battery swap stations to minimize unnecessary differences”. Applying the minimum specifications for swapped batteries can minimize the differences that can harm consumers if there is more than one battery swap brand that consumers can use [63]. Three indicators were removed in the latent construct of stakeholder protection because B2, B3, and B5 can represent them, and each stakeholder can represent more than one perspective [22]. The removed indicators were as follows: • B1 (The application of the battery swap test standard is expected to protect the interests of the government) • B4 (The application of the battery swap test standard is expected to protect the interests of battery swap manufacturers) • B6 (The application of the battery swap test standard is expected to protect the interests of electric motorcycle users) Meanwhile, two indicators were removed in the latent construct of SNI implementation. These indicators included C1.2 (Battery test standards contain equipment construc- J. Open Innov. Technol. Mark. Complex. 2022,8, 219 18 of 23 tional requirements) and C1.3 (Battery test standards contain electromagnetic compatibility). The question for C1.2 and C1.3 is a question of redundancy that contains the effects of the equipment constructional requirements and electromagnetic compatibility constructs on the SNI implementation construct, which can be calculated during model analysis in SEM. Therefore, the elimination of C1.2 and C1.3 does not affect the meaning of the SNI implementation construct. Furthermore, we removed several indicators from the remaining constructs. The elimination of these indicators was based on the survey conducted at the lithium battery R&D center in Indonesia. This elimination indicates that battery swap stakeholders in Indonesia have not completely fulfilled the requirements stated in these indicators. However, several requirements can be fulfilled, but the stakeholders have not followed the reference standard rules. For example, C2.1 was removed because stakeholders in Indonesia have developed a battery that is safe against electric shock but is not compliant with IEC 60204-1:2016. C2.3 was removed because stakeholders have developed a battery that protects SBS charging equipment but is not compliant with IEC 61851-23:2014. Table 15 shows the reference standards that stakeholders have not fulfilled for each removed indicator. Table 15. Unfulfilled reference standards. Construct Removed Indicators Standards Protection against electric shock C2.1 IEC 60204-1:2016 C2.3 IEC 61851-23:2014 C2.5 IPXXB C2.6 IPXXB C2.7 IEC 60364-4-41: 2005+AMD: 2017 CSV C2.8 IEC 60364-4-41:2005 C2.11, C2.12 IEC 60364 series, IEC 60479 series, IEC TR 60755:2017, IEC 61008 series, IEC 61009 series, IEC 60947-2 Equipment constructional requirements C3.1 IEC 61439-1:2011 C3.2 IEC 60947-3:2008+AMD1:2012+AMD2:2015 CSV C3.3 IEC 60947-4-1:2018 C3.9 IEC 62262:2002 C3.12 IEC 61439-1:2011 C3.13 IEC 60695-2-11 C3.14 IEC 60695-10-2 C3.15 IEC 60112:2003+AMD1:2009 CSV C3.16 IEC 61439-1:2011 Electromagnetic compatibility C4.1 IEC 61000 series, IEC 61851-21-2:2018 5.1.2. Convergent Validity of Constructs A construct is valid if its Cronbach’s alpha value is above 0.5 for new untested instruments [ 58 ]. In this study, all constructs had values above 0.5. Therefore, it can be said that all constructs are valid. 5.1.3. Discriminant Validity Discriminant validity shows that a construct is different from other constructs, is unique, and captures phenomena not captured by other constructs. Discriminant validity at the construct level was determined by comparing the √AVE value of a construct with the construct’s correlation with other constructs. The √AVE value for each construct must be greater than the correlation value between constructs and other constructs. This assessment J. Open Innov. Technol. Mark. Complex. 2022,8, 219 19 of 23 is based on the Fornell–Larcker criteria [ 58 ]. In this study, the √AVE value of a construct had the most significant value compared to the correlation values between constructs and other constructs. Thus, this research can be considered valid. 5.2. SEM inner Model Analysis 5.2.1. Collinearity Assessment Collinearity assessment uses the provision that if the VIF value is more than five, then latent variable collinearity occurs. This study found no collinearity assessment with a VIF value below five. 5.2.2. Path Value and Significance The path value and significance test the significance level of a path coefficient via the bootstrap procedure. The minimum path coefficient value is 0.2, and it is ideally greater than 0.3 to indicate a meaningful relationship [ 60 ]. In this study, the path coefficient value for the electromagnetic compatibility towards SNI implementation was negative. 5.2.3. Coefficient of Determination The coefficient of determination is a value indicating the variance of the endogenous product caused by all of the exogenous variables connected to it. Chin [ 60 ] stated that the value of R 2 is high, medium, and small if it is 0.67, 0.33, and 0.19, respectively. The R 2 value used is the adjusted R 2 value for the model’s number of predictors. The R 2 value of SNI implementation was 0.657, categorized as vital, while the R 2 value of the SNI acceptance variable was 0.329, categorized as moderate. 5.2.4. Effect Size f2 The effect size f 2 was used to evaluate the SEM structural model. In this research, the relationships with a significant influence when an exogenous variable is removed were the relationships of equipment constructional requirements with SNI implementation and of protection against electric shock with SNI implementation. The relationships with moderate influence were the relationships of electromagnetic compatibility with SNI implementation and of marking and instruction with SNI implementation. The relationships with little influence were those of SNI implementation with SNI acceptance and of stakeholder protection with SNI acceptance. 5.2.5. Predictive Relevance When the SEM path model shows predictive relevance, the path model can accurately predict data that are not used in evaluating the model. This study has a predictive relevance of 0.540 to the SNI implementation variable and of 0.180 to the SNI acceptance. 5.2.6. Effect Size q2 Effect size q 2 was used to determine the exogenous effect on the Q 2 value of endogenous variables. In this study, the q 2 value was 0.1922, meaning that removing one of the exogenous variables in the pathway model has moderate predictive relevance for certain endogenous constructs. 5.2.7. Hypothesis Test A hypothesis test was conducted by comparing the t-table and t-value. The research hypothesis is accepted if the t-value is greater than the t-table. In this study, all hypotheses were accepted. 5.3. Policy Implications The findings and outputs obtained from this research can be used as a policy brief for the development of standards and to support the provision of recommendations and options in formulating policies related to the charging and exchange infrastructure for J. Open Innov. Technol. Mark. Complex. 2022,8, 219 20 of 23 electric vehicle batteries. The results of this study can provide input for the draft SNI battery swap concept to the technical committee in charge of developing the SNI. Thus, this study can be used as a basis for considering the selection of standard parameters and is expected to support the effectiveness of standard development until the SNI is officially formulated . This research is consistent with the principles of SNI formulation, namely, openness and consensus. It involves interested parties in the standardization of electric vehicles, including the government, battery swap R&D, battery swap laboratories, battery swap manufacturers, electric motorcycle manufacturers, and electric motorcycle users. We are open to these stakeholders so that they know about the SNI development program, and we provide equal opportunities for them to participate in the formulation of this SNI by exploring their opinions and needs related to battery swap standards and accommodating their needs in determining standard parameters. With this participation, the parties involved become aware of the importance of the current problem, so it is expected that in the future they would be willing to adopt the SNI that has been formulated and participate in the success of the electric vehicle acceleration program in Indonesia. Thus, this research supports the climate for developing electric vehicle policies and encourages the acceptance of the SNI in the community. The dynamics of open innovation are an important aspect to pay attention to in early standardization. The engagement of various parties—such as industry, government, society, academics, and developers—comprises the interaction required in developing a standard battery swap. The engagement of stakeholders can enhance the effectiveness and capability of the early standardization process. Therefore, it can better facilitate the product development process of battery swaps. 6. Conclusions An SNI for battery testing that is globally competitive was designed through data processing with the FACTS method, referring to international standards, namely, the IEC 62840-2: 2016 standard regarding Electric Vehicle Battery Swap Systems–Part 2: Safety Requirements. Test variables in the SNI battery test include protection against electric shock, equipment constructional requirements, electromagnetic compatibility, and marking and instruction. The SNI for battery swap testing was designed through data processing validation using SEM. The proposed constructs—i.e., electromagnetic compatibility, equipment construction requirements, marking and instruction, and protection against electric shock—positively affect SNI implementation. Meanwhile, the SNI implementation, national uniqueness, and stakeholder protection positively affect SNI acceptance. Therefore, it can be said that SNI acceptance can be obtained by considering SNI implementation, national identity, and stakeholder protection. An SEM model was designed for formal acceptance through the development of the technology acceptance model (TAM), which considers the variables of perceived ease of use, perceived usefulness, and attitudes towards use. The validation results using SEM indicate that all hypotheses were accepted. Because all of the hypotheses were proven correct, the research framework that was developed by applying FACTS and SEM can be used for early standardization. This means that the standardization of each process should accompany the development of battery swap products . Standardization as a catalyst of open innovation has shown through analysis that implementation, national uniqueness, and stakeholder protection positively affect SNI acceptance. The open innovation approach was considered to integrate a FACTS and SEM approach to generate significant parameters of swappable battery standards. Further research of open innovation and standardization will be more complex not only for swappable batteries, but also for smart connected products. Thus, interoperability of standardization is a crucial area for further study. J. Open Innov. Technol. Mark. Complex. 2022,8, 219 21 of 23 Author Contributions: Conceptualization, W.S. and F.F.; methodology, W.S., D.P. and E.P.; software, D.P.; validation, W.S., D.P. and F.F.; formal analysis, D.P.; data curation, D.P.; writing—original draft preparation, W.S., D.P., A.R. and T.O.K.; writing—review and editing, W.S., D.P., A.R. and T.O.K.; supervision, W.S. and E.P.; project administration, W.S. and F.F.; funding acquisition, W.S. All authors have read and agreed to the published version of the manuscript. Funding: This research was partially supported by the LPPM (Institute for Research and Community Service) Universitas Sebelas Maret under the “Program Flagship Prioritas Riset Nasional Untuk Perguruan Tinggi” Program FY 2021 (Contract no.: 2883/UN27.22/PT.01.03/2021). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. 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