Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms

Kimseng, Tieng; Javed, Amna; Chawalit Jeenanunta; Kohda, Youji Article Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms Journal of Open Innovation: Technology, Market, and Complexity Provided in Cooperation with: Society of Open Innovation: Technology, Market, and Complexity (SOItmC) Suggested Citation: Kimseng, Tieng; Javed, Amna; Chawalit Jeenanunta; Kohda, Youji (2020) : Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms, Journal of Open Innovation: Technology, Market, and Complexity, ISSN 2199-8531, MDPI, Basel, Vol. 6, Iss. 2, pp. 1-20, https://doi.org/10.3390/joitmc6020038 This Version is available at: https://hdl.handle.net/10419/241412 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. 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/ Journal of Open Innovation: Technology, Market, and Complexity Article Applications of Fuzzy Logic to Reconfigure Human Resource Management Practices for Promoting Product Innovation in Formal and Non-Formal R&D Firms Tieng Kimseng 1,2,* , Amna Javed 1, Chawalit Jeenanunta 2,* and Youji Kohda 1,* 1School of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1211, Japan; [email protected] 2 School of Management Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12120, Thailand *Correspondence: [email protected] (T.K.); [email protected] (C.J.); [email protected] (Y.K.) Received: 7 May 2020; Accepted: 15 May 2020; Published: 18 May 2020   Abstract: Human resource management (HRM) practices for promoting innovation tend to vary from one context to another. This leads us to investigate the configurations of internal HRM practices and supply chain collaborations that help firms to achieve high levels of product innovation or cause firms to achieve low levels of product innovation in formal R&D firms—firms which have actively engaged in systematic innovation, have established an R&D department, and/or have allocated budgets for R&D intention—and non-formal R&D firms. The data were collected during the period December 2016–February 2017 from manufacturing firms located in the Bangkok metropolitan area, Thailand. In total, 87 respondents were included for an empirical fuzzy-set qualitative comparative analysis. The results indicate that, first, formal and non-formal R&D firms achieve high levels of product innovation by adopting internal HRM practices or collaborating with customers/suppliers. They also can achieve high levels of product innovation if they adopt both simultaneously. Second, formal R&D firms achieve high levels of product innovation if they adopt R&D personnel development; otherwise, they need to collaborate with customers and suppliers to achieve high levels of product innovation. Finally, miss-adopting R&D personnel development causes formal and non-formal firms to achieve lows levels of product innovation. Keywords: internal HRM practices; supply chain collaboration; product innovation; technological capabilities; fuzzy-set qualitative comparative analysis 1. Introduction Human resource management (HRM) practices for promoting innovation have been extensively studied across continents, countries, and industries. In Asia, researchers from, e.g., Thailand [ 1 ], India [ 2 ], Laos [ 3 ], Vietnam [ 4 ], Japan [ 5 ], Philippine [ 6 ], Singapore [ 7 ], Indonesia [ 8 ], and Malaysia [ 9 ], identified various HRM practices in the manufacturing industry. These qualitative studies proved that firms mainly realized how critical HRM practices are in creating values for promoting innovation and maintaining sustainable survival and growth in today’s fast-changing business environment. In a quantitative study, researchers mainly adopt conventional methods, e.g., regression, correlations, mediators, and moderators, to study the effects or relationships of causal conditions on outcomes. For instance, Glaister Karacay, Demirbag et al. [ 10 ] defined HRM practices as, i.e., training and development, recruitment and selection, workforce planning, and performance appraisal; these are used as causal conditions to study their effects on firm performance. Ueki [ 11 ] studied the roles of top management, J. Open Innov. Technol. Mark. Complex. 2020,6, 38; doi:10.3390/joitmc6020038 www.mdpi.com/journal/joitmc J. Open Innov. Technol. Mark. Complex. 2020,6, 38 2 of 20 internal HRM practices, and customer relationships in promoting innovation in non-formal R&D firms. Zhang, Edgar [ 12 ] studied relationships between HRM practices and innovation and identified whether innovation is a mechanism of HRM practices and firm performance. Results from these studies may not fully represent and explain what happens in the workplace, where different configurations of HRM practices are related differently for promoting innovation. Researchers, moreover, mainly stated various best HRM practices, but are they really the best for all contexts? For example, Gill and Wong [ 13 ] highlighted five best practices of Japanese management styles, i.e., lifetime employment, seniority systems, house unions, consensual decision making, and quality control circles. These practices helped the Japanese firms to successfully manage, expand, and introduce their organizations into global markets. Among these practices, house unions, consensual decision making, and quality control circles are transferable to Singapore, but lifetime employment and seniority systems are problematic to adopt because of cultural differences [ 13 ]. This shows that HRM practices tend to vary from one context to another, where a single best practice of HRM practices in one context may cause problems in another context if the top management entirely adopts those practices without understanding the contexts of business operations and the cultures, norms, and values of local employees [ 14 ]. Jørgensen and Becker [ 15 ] stated that there is no one set of best HRM practices for promoting innovation, and that the best HRM practices should align with the context of the business operation (e.g., emerging or developed economies) and firm capabilities (e.g., formal R&D firms—firms which have actively engaged in systematic innovation, have established an R&D department, and/or have allocated budgets for R&D intention—or non-R&D firms). Hence, it is worth finding the best fit of HRM practices in accordance with our own context rather than adopting the best practices from an outside context [14]. The literature review mainly focuses on factors positively related to an outcome. For example, Ueki [ 11 ] proved that HRM practices help firms to achieve more process innovation, customer relationships help firms to promote product innovation, and the top management contributes to promote product innovation when she/he maintains relationships with engineers. However, are there any configurations that cause firms to have low levels of product innovation? This leads us to investigate the configurations of internal HRM practices and supply chain collaboration that help firms to achieve high levels of innovation and cause firms to have low levels of product innovation in formal and non-formal R&D firms using a fuzzy-set qualitative comparative analysis. The remainder of this paper is organized as follows. Section 2presents the literature review. Then, the methodology is presented in Section 3. Section 4presents the results and discussions. Conclusions are recapped in Section 5. Then, the practical implications, limitations, and further studies are summarized in Section 6. 2. Literature Review 2.1. Internal HRM Practices Internal HRM practices refer to a firm’s activities in utilizing internal resources to create new knowledge for promoting innovation. Researchers mainly defined internal HRM practices based on their experiences and the context of studies, because understanding practices in accordance with the context is critical in making sense of what happened and providing appropriate solutions for problem solving [ 16 ]. For instance, Zhang, Edgar [ 12 ] defined HRM practices as (i) hiring and evaluating employees based on their abilities, skills, and performances; (ii) encouraging employees to engage in decision-making for problem-solving; (iii) offering special training to employees to enhance their knowledge; and (iv) providing flexible strategies and organizational environments to enable employees to develop critical thinking, specific abilities, and skills. These HRM practices were defined differently in the works of (1) Fey, Björkman [ 17 ], where HRM practices consisted of incentive systems, job security, employee training, career planning, decentralization, internal promotion, and complaint resolution systems; (2) Glaister, Karacay [ 10 ], where HRM practices consisted of training and development, J. Open Innov. Technol. Mark. Complex. 2020,6, 38 3 of 20 recruitment and selection, workforce planning, and performance appraisal; and (3) Shipton, Fay [18], where HRM practices consisted of recruitment and selection, induction, appraisal, and training. From the Thai manufacturing context, Jeenanunta, Rittippant [ 1 ] highlighted three stages of HRM practices: (i) recruitment and selection, (ii) training and development, and (iii) retention and compensation. Across these three stages, Jeenanunta, Rittippant [ 1 ] highlighted various internal HRM practices, i.e., (i) Thai Oil adopts knowledge sharing, cross-functional operation, job rotation, innovation contest, and R&D personnel development; (ii) SCG Chemicals adopts learning by doing, knowledge transferred across firms, idea time sessions; (iii) PTT Global Green Chemicals engages employees with voluntary tasks, adopts cross-functional teams, conducts in-house training, and sends employees to train outside the company. These companies stated that these practices help to improve employee capabilities, make them ready for new task assignment, and change their mindset toward innovation. These practices help to foster learning and form a coherent system to facilitate the emergence of innovation at individual, team, and organizational levels [ 19 ]. Hence, this study focuses on in-house training [ 20 ], engineer rotation [ 21 ], R&D personnel development [ 22 ], and quality control circles [23] as the key causal conditions of internal HRM practices. 2.1.1. In-House Training In-house training helps to improve and enhance employee capabilities for assigned jobs so that they are able to promote innovation. In-house training needs to be conducted regularly for the knowledge acquisition of newly recruited employees and knowledge upgrading of current employees so that they are ready for task assignment [ 8 ]. In-house training not only focusses on teaching new things to employees, but also on updating their knowledge to follow what is happening in today’s fast-changing society [ 24 ]. In-house training helps employees to fully utilize their knowledge through, i.e., socialization, externalization, combination, and internalization, with co-workers at individual, team, or organizational levels [ 25 ]. The literature shows that investing in in-house training helps firms to enhance human capital firstly and organizational performance secondly [ 26 , 27 ]. Sobanke, Adegbite [ 20 ] highlighted the critical roles of in-house training for technical staffin accumulating firm technological capabilities. There are various practices which are defined for in-house training. For example, Norasingh and Southammavong [ 3 ] defined on-the-job training, attending training with customers, learning-by-doing, and field trips as in-house training. Similarly, Binh and Linh [ 4 ] defined in-house training as new staffrecruitment and training through production management. 2.1.2. Engineer Rotation Engineers are the key resources in helping an organization to deal with technical tasks which ordinary employees are mainly incapable of. Firms without engineers are mainly small firms with low technological capabilities where they do not have adequate resources to acquire engineers or do not require the roles of engineers in their organization because tasks mainly can be accomplished by ordinary employees. However, when there are transitions, e.g., upgrading from non-formal to formal R&D firms or expanding from 100% locally-owned to joint venture firms, firms mostly recruit engineers to deal with complex tasks. To make the roles of engineers even more critical, firms need to constantly check the capabilities of newly recruited and current engineers. This process helps firms to achieve the highest potential from every engineer. Hence, firms can enhance and improve engineer capabilities through engineer rotation practices. These practices help engineers to integrate their knowledge with the organizational knowledge as well as the supply chain partners’ knowledge. 2.1.3. R&D Personnel Development Small and medium-sized enterprises (SMEs) mainly do not classify the roles of engineers and R&D personnel, but large firms often do. R&D personnel are one of the main resources, like engineers, but R&D personnel tend to be allocated for promoting innovation [ 1 ]. Mohan [ 9 ] mentioned that firms provide technical and competency certification and soft skills training programs throughout the year J. Open Innov. Technol. Mark. Complex. 2020,6, 38 4 of 20 to enhance the competency skills of every employee; this is specifically designed for developing R&D personnel. Thus, the capabilities of R&D personnel can be enhanced through various practices, e.g., small group activities among R&D personnel, regular meetings to discuss problems/solutions among R&D personnel, and development of personnel in charge of R&D. 2.1.4. Quality Control Circles Quality control circles are defined as small group activities where firms organize for space sharing—i.e., physical, virtual, and/or mental space—among their colleagues. The quality control circles intend to involve everyone in an organization to co-create new knowledge; Japanese firms believe that participation, cooperation, and collaboration through various circles can strengthen the vigor and efficiency of business operations [ 23 ]. The quality control circles benefit firms in various ways, e.g., in developing and producing low-cost products, improving the efficiency of existing equipment through modifications of plant layouts and work procedures, developing employee capabilities, and improving organizational performance [ 23 ]. Besides Japan, the quality control circles are also transferred through the investment of Japanese firms to other countries. Local firms, which are the suppliers of Japanese firms, are required to adopt the quality control circles. Toyota, for example, has adopted and exported quality control circles during the expansion of the production plants to Thailand. During its business operation, Toyota required local suppliers, e.g., Thai Summit, to adopt quality control circles. These practices are considered as one of the minimum criteria to be a Toyota supplier. Toyota believed that these practices improved local supplier capabilities to match the firm’s standards. The quality control circles, moreover, are rooted in local suppliers through Toyota’s supplier network; this network motivates suppliers to participate and share knowledge openly, prevents members from free-riding, and transfers tacit and explicit knowledge effectively and efficiently [28]. 2.2. Supply Chain Collaboration Besides internal HRM practices, firms also need to collaborate with external partners, e.g., customers, suppliers, competitors, consultants, R&D institutes, and universities. These help firms with knowledge acquisition, knowledge transfer, and knowledge co-creation, which are invisible and embedded outside an organization [ 29 , 30 ]. The importance of external partners can be found in various studies, e.g., (1) intra-firm and external networks positively affect firm innovation, and intra-firm networks are moderators between external networks and firm innovation [ 31 ]; (2) family member involvement reduces collaboration with vertical partners [ 32 ]; (3) firms with domestic collaboration tend to have more foreign partner collaboration, and this may provide firms opportunities to access novel knowledge which does not exist domestically [ 33 ]; (4) collaboration with firms in various countries helps firms to acquire varieties of scientific and technological knowledge to improve the firm absorptive capacity [ 29 ]; and (5) vertical collaboration helps firms to engage in innovation and optimize core competency, whereas horizontal collaboration helps firms to identify new opportunities in a new market [34]. Firms understand how critical collaboration is. It, for example, pools knowledge for problem-solving, creates places for knowledge sharing and integration, increases choices for decision making, and enhances learning within and across an organization [ 14 ]. However, not every firm is able to expose their organization to every external partner, because this requires firms to have adequate capabilities in human resources, financial capital, and experienced top management. Local firms in emerging economies, especially SMEs, have limited financial resources, low technological capabilities, insufficient infrastructure, and low managerial skills [ 35 ]. They may be incapable or not ready to collaborate with external partners, specifically with universities, research centers, consultants, and competitors. Most SMEs are only able to collaborate with suppliers to set up plants and improve current systems and with customers to improve products to match standard requirements. This is because customers and suppliers are upstream and downstream partners of the supply chain to help firms to achieve, align, and mobilize resources effectively and efficiently for promoting innovation [ 36 ]. Stock, J. Open Innov. Technol. Mark. Complex. 2020,6, 38 5 of 20 Greis [ 37 ] stated that supply chain collaboration is highly linked with the collaboration of firms and suppliers and customers across extensive enterprises. Therefore, this study considers only customer and supplier collaboration, because they mostly collaborate with firms in emerging economies. Customer and supplier collaboration are mainly studied together. For example, (1) customers are important for product innovation, whereas suppliers are important for process innovation [ 38 ]; (2) supplier collaboration helps firms to achieve radical innovation, whereas customer collaboration helps firms to achieve incremental innovation [ 39 ]; (3) collaboration with one partner (e.g., customers) increases the likelihood of collaboration with a different partner (e.g., suppliers) [ 33 ]. Researchers also studied customer and supplier collaboration separately, e.g., (1) customer collaboration enables firms to refine R&D direction and enhance internal competencies by assisting in product design, technology, project management, and prototype assessment [ 40 – 42 ]; (2) relationships between supplier collaboration and innovation novelty might depend on the stages of supplier involvement (predesign or commercialization stage) [ 43 ] and the innovation capabilities of suppliers [ 44 ]; (3) supplier collaboration has strong relationships with radical product innovation rather than incremental [ 45 – 47 ]. Researchers highlight how critical supply chain collaboration is, but studying supply chain collaboration without considering internal HRM practices may lead to biased conclusions. For example, if firms have adequate internal capabilities, they may not collaborate with suppliers; they just need to collaborate with customers to acquire new knowledge for promoting innovation. Therefore, studying supply chain collaboration in combination with internal HRM practices helps us to gain new insight and knowledge on sources for promoting innovation in formal and non-formal R&D firms. 2.3. Firm Technological Capabilities Firms mainly adopt HRM practices based on their own capabilities. Large firms tend to have stronger capabilities and resources to invest in R&D [ 48 , 49 ], and they possess innovative advantages over smaller firms in terms of heterogeneous R&D activities [ 50 ]. Arnold, Bell [ 51 ] defined four phases of firm technological capabilities—technology use and operation, technology acquisition and assimilation, technology upgrading and reverse engineering, and R&D. These technological capabilities range from fundamental to the highest phases of technology use. In their studies, they define the states of firms for each phase of firm technological capabilities, but they do not identify HRM practices for promoting innovation. Then, Jeenanunta, Rittippant [ 1 ] identified types of HRM practices needed to upgrade the firm technological capabilities in each phase as (i) adopting training with joint venture partners and collaborating with suppliers for plant set up and operation; (ii) having specific recruitment and training packages; (iii) using cross-functional and project-based teams for promoting innovation; and (iv) acquiring R&D gurus, e.g., highly qualified personnel with Masters degrees and PhDs. Tsuji, Ueki [ 52 ] and Intarakumnerd [ 53 ] grouped these capabilities as formal and non-formal R&D firms. Formal R&D firms are organizations with systematic and organized activities—e.g., they have engaged in systematic innovation, have established an R&D department, and/or have allocated budgets for R&D for promoting innovation and improving the firm’s performance [54]. Whereas, non-formal R&D is a process of collecting, processing, and applying information for problem-solving [ 55 ]. Non-formal practices, e.g., designs, the utilization of advanced machinery, and training, are critical for promoting innovation, especially in low and medium technological industries [ 56 ]. Tsuji, Ueki [ 52 ] stated that formal R&D firms promote product innovation by cross-functional teams of production, engineering, marketing, and information technological usage, whereas non-formal R&D firms promote product innovation by HRM programs for employees, group awards for new suggestions, and ISO9000. Therefore, formal and non-formal R&D are the key indicators to define a firm’s technological capabilities. From this study, they are defined as firms that have and have not allocated some portion of their budgets for an R&D purpose. J. Open Innov. Technol. Mark. Complex. 2020,6, 38 6 of 20 2.4. Product Innovation Innovation is defined as changes in the products/services of a firm or the way that the firm produces them, changes in business models, improvements in management techniques, and modifications in the organizational structure [ 57 ]. Then, it is redefined as processes of exploration (i.e., inventing new knowledge) and exploitation (i.e., reusing existing knowledge in new contexts) [ 14 ], or processes of the development and implementation of existing ideas in a new context or new ideas on an existing context [ 58 ]. Innovation is highly context-oriented, so what works in one context may not be applicable in another context [ 59 ]. This highly depends on firm sizes, financial capitals, human resources, strategies and manufacturing capabilities, absorptive capacities, and collaboration levels with supply chain partners. Thus, innovative firms utilize existing knowledge/technologies or explore entirely new knowledge/technologies. They need to learn how to unlearn outdated practices and learn how to relearn new practices so that they can improve firm competency and drive innovation. There are various types of innovation—e.g., product, process, packaging, organizational, position, and commercial [ 60 ]—but only product innovation is investigated in this study, because manufacturing firms mainly embed their innovative ideas in products. Product innovation is a process of improving existing products or introducing a completely new product [ 61 , 62 ]. Aminullah, Hermawati [ 8 ] mentioned that SMEs tend to achieve product innovation at a very basic phase—e.g., diverging from their own recipe and improving existing products through trial-and-error— whereas vertical-integrated firms and global-oriented large firms tend to achieve the highest phase of product innovation, e.g., the development of a new product based on existing technology and new technology through conducting their own R&D and/or collaborating with supply chain partners, universities, and/or research centers. Mangematin and Mandran [ 60 ] defined three features of product innovation—(i) improving existing products; (ii) producing products which are new to a firm, but had already existed in a market; and (iii) producing products which are new to a market. Similarly, Tsuji, Ueki [ 52 ], Tsuji, Idota [ 63 ], and Ogawa, Ueki [ 64 ] categorized product innovation as (i) redesigning packaging or significantly changing the appearance design, (ii) significantly improving existing products, (iii) producing new products based on existing technologies, and (iv) producing new products based on new technologies. This classification is adopted in this study because it shows various types of product innovation with different levels of difficulties. From the literature review, this study investigates configurations of HRM practices, i.e., internal HRM practices and supply chain collaborations, that lead firms to achieve high levels and cause firms to achieve low levels for each type of product innovation in formal and non-formal R&D firms, as presented in Figure 1. J. Open Innov. Technol. Mark. Complex. 2020, 6, x FOR PEER REVIEW 7 of 21 Figure 1. Theoretical model. 3. Methodology 3.1. Sample and Data Collection This empirical study is motivated by in-depth case studies with Thai manufacturing firms [1]. An intensive literature review of HRM practices for promoting innovation was conducted. Combining knowledge from case studies and the literature review, a questionnaire—i.e., (1) profile of an establishment to provide the basic information of firms, (2) achievement for upgrading various types of product innovation, (3) internal HRM practices to promote product innovation, and (4) customer and supplier collaboration—was designed for data collection. The designed questionnaire was checked and commented on by three academic professors, who specialized in promoting innovation, for the questionnaire validation. The questionnaire was distributed to firms located in the Bangkok metropolitan area, Thailand, because this area is a center of economics and the main gateway for national and international trade [65]. This area has major industrial zones and factories for data collection, and it is larger than other cities in Thailand. A list of 1200 firms was sampled on December 3rd, 2016, from firms that registered their business in the database of the Department of Industrial Works, Ministry of Industry, Thailand [66]. Each questionnaire was distributed to respondents who were expected to be key people in managerial positions, e.g., presidents, chief executive officers, directors, managers, heads of departments, or group leaders. The questionnaires were distributed and collected from December 2016 to February 2017. There were three means of data collection, i.e., email, post-office, and walk-in; the return rate for each mean was 2.08%, 2.67%, and 100%, respectively. In total, there were 209 respondents, which was equivalent to 17.42%. 3.2. Data Cleaning There are three steps for data cleaning. First, the respondents who did not respond to the R&D expenditure were excluded from this analysis because we could not categorize whether they belonged to formal or non-formal R&D firms. Second, respondents were asked whether firms had product innovation in the last two years. If their response was “Yes”, they were required to answer each type of product innovation; otherwise, they went to the next questions without responding to each type of product innovation. Third, the data from respondents were analyzed by using a fuzzy- Figure 1. Theoretical model. J. Open Innov. Technol. Mark. Complex. 2020,6, 38 7 of 20 3. Methodology 3.1. Sample and Data Collection This empirical study is motivated by in-depth case studies with Thai manufacturing firms [ 1 ]. An intensive literature review of HRM practices for promoting innovation was conducted. Combining knowledge from case studies and the literature review, a questionnaire—i.e., (1) profile of an establishment to provide the basic information of firms, (2) achievement for upgrading various types of product innovation, (3) internal HRM practices to promote product innovation, and (4) customer and supplier collaboration—was designed for data collection. The designed questionnaire was checked and commented on by three academic professors, who specialized in promoting innovation, for the questionnaire validation. The questionnaire was distributed to firms located in the Bangkok metropolitan area, Thailand, because this area is a center of economics and the main gateway for national and international trade [ 65 ]. This area has major industrial zones and factories for data collection, and it is larger than other cities in Thailand. A list of 1200 firms was sampled on December 3rd, 2016, from firms that registered their business in the database of the Department of Industrial Works, Ministry of Industry, Thailand [ 66 ]. Each questionnaire was distributed to respondents who were expected to be key people in managerial positions, e.g., presidents, chief executive officers, directors, managers, heads of departments, or group leaders. The questionnaires were distributed and collected from December 2016 to February 2017. There were three means of data collection, i.e., email, post-office, and walk-in; the return rate for each mean was 2.08%, 2.67%, and 100%, respectively. In total, there were 209 respondents, which was equivalent to 17.42%. 3.2. Data Cleaning There are three steps for data cleaning. First, the respondents who did not respond to the R&D expenditure were excluded from this analysis because we could not categorize whether they belonged to formal or non-formal R&D firms. Second, respondents were asked whether firms had product innovation in the last two years. If their response was “Yes”, they were required to answer each type of product innovation; otherwise, they went to the next questions without responding to each type of product innovation. Third, the data from respondents were analyzed by using a fuzzy-set qualitative comparative analysis (fs/QCA) [ 67 ]. This method cannot deal with missing data, so the respondents that had missing data on causal conditions and outcomes were removed. Across these three steps, 9, 68, and 45 respondents were removed from steps 1, 2, and 3, respectively. Therefore, only 87 respondents were included for further empirical fs/QCA. 3.3. fs/QCA Fuzzy-set is defined as “a class of object with a continuum grades of membership, characterized by a membership function assigned to each object and ranged from zero to one” [ 68 ]. Ragin [ 69 ] introduced the fuzzy-set qualitative comparative analysis (fs/QCA) to deal with continuous and interval variables with causal complexity. Researchers who adopted fs/QCA believed that this technique combines the strengths of qualitative and quantitative approaches and that it is also the bridge between case-oriented and variables-oriented research. This is because fs/QCA does not analyze causal conditions in order to explain an outcome, but to explain how causal conditions combine in the complexity to generate an outcome [ 70 ]. There are various benefits of fs/QCA compared to conventional methods. For example, (1) fs/QCA can deal with equifinality, so it is able to explain various configurations that lead to a single outcome [ 71 ]; (2) fs/QCA can deal with asymmetry, so the presence or absence of a causal condition of an outcome requires different explanations [ 71 ]; and (3) fs/QCA can be analyzed with a small set of data [72]. Therefore, fs/QCA was adopted in this study. J. Open Innov. Technol. Mark. Complex. 2020,6, 38 8 of 20 3.3.1. Causal Conditions and Outcomes The causal conditions, i.e., internal HRM practices and supply chain collaboration, were achieved from parts 3 and 4, respectively. They were measured by using the dichotomous scale, where 0 =“No” and 1 =“Yes”. The outcome, i.e., product innovation, was achieved from part 2 and measured using the three-point Likert scale [ 52 , 73 ], where 0 =“Not Tried Yet”, 1 =“Tried”, and 2 =“Achieved”. Details of the causal conditions and outcomes are presented in Table 1. The Cronbach’s alpha coefficient of the causal conditions in formal and non-formal R&D firms are presented in the last two columns to test the reliability of the constructed variables. The Cronbach’s alpha coefficient ranges from 0.727 to 0.920, so each constructed variable exceeded the threshold value of 0.7 [ 74 ]; they can be grouped together for a further empirical fs/QCA. Table 1. Cronbach’s alpha of causal conditions and outcomes. Internal HRM Practices, Supply Chain Collaboration, and Product Innovation Formal (38) Non-Formal (49) In-house training (it) •Employees develop training courses without help from outside. 0.808 0.781 •Employees develop training materials without help from outside. •Employees serve as trainers/lecturers for training courses. •Firms have an in-house training facility/center. Engineer rotation (er) •Firms have rotational programs for engineers to rotate around various roles in a department. 0.757 0.797 •Firms have rotational programs for engineers to rotate around various departments. •Firms have career path programs for engineers to develop leaders of innovative activities. •Firms have external secondment programs to give opportunities for engineers to work in other firms. R&D personnel development (pd) • Firms conduct small group activities among R&D personnel. 0.832 0.92 •R&D personnel have regular meetings to discuss problems/solutions. •Firms develop personnel in charge of R&D. Quality control circles (qcc) • Firms have systems to disseminate successful experiences of quality control circles across the firm. 0.782 0.777 •Firms have systems to learn from successful experiences of quality control circles with customers/suppliers. Customer collaboration (cc) •The main customer dispatches personnel to the firm. 0.759 0.807 •Firms provide training to the main customer. •Firms receive training from the main customer. •Firms design a new product or service with the main customer. •Firms’ engineers obtain new technologies and knowledge through training/learning from customers. •Firms ask advice from/co-operate with foreign-owned (MNC/JV) customers. • Firms’ engineers communicate directly with the engineers of customers. Supplier collaboration (sc) •The main supplier dispatches personnel to the firm. 0.727 0.783 •Firms provide training to the main supplier. •Firms receive training from the main supplier. •Firms design a new product or service with the main supplier. •Firms’ engineers obtain new technologies and knowledge through training/learning from suppliers. •Firms ask advice from/co-operate with foreign-owned (MNC/JV) suppliers. • Firms’ engineers communicate directly with the engineers of suppliers. Product innovation •Redesigning packaging or significantly changing appearance design. (pdi1) •Significantly improving current products. (pdi2) •Producing new products based on existing technologies. (pdi3) •Producing new products based on new technologies. (pdi4) J. Open Innov. Technol. Mark. Complex. 2020,6, 38 15 of 20 somehow leads firms to achieve high levels low levels of product innovation. This does not mean that they are not important for promoting product innovation, but R&D personnel development tends to be more critical in the Thai manufacturing context. Formal R&D firms result in low levels of product innovation if they just adopt quality control circles, customer collaboration, and supplier collaboration without in-house training, engineer rotation, and R&D personnel development. Whereas, non-formal R&D firms result in low levels of product innovation if they just adopt in-house training without R&D personnel development, even with or without customer and supplier collaboration. Across these two groups, both groups proved that an absence of R&D personnel development causes firms to result in low levels of product innovation. Mani [ 2 ] specifically highlighted how critical R&D personnel development is in upgrading human resources capabilities and promoting innovation, but he did not mention that missing out on adopting R&D personnel development may cause firms to result in low levels of product innovation. 5. Conclusions The sources of knowledge for promoting innovation tend to vary from one context to another. This led us to conduct an empirical study to identify the configurations of internal HRM practices and supply chain collaboration that lead firms to achieve high levels and cause firms to result in low levels for each type of product innovation in formal and non-formal R&D firms. The data were collected during the period December 2016–February 2017 from manufacturing firms located in the Bangkok metropolitan area. The target respondents were the key people in managerial positions—e.g., presidents, chief executive officers, directors, managers, heads of departments, and group leaders—because they have adequate knowledge for answering our questionnaire. In total, 87 respondents were included for an empirical fuzzy-set quality comparative analysis. The results provide various configurations with the following commonality across formal and non-formal R&D firms. First, formal and non-formal R&D firms can achieve high levels of product innovation by adopting internal HRM practices or collaborating with supply chain partners, and these highly depend on their capabilities. Formal and non-formal R&D firms also achieve high levels of product innovation if they adopt both simultaneously. Second, formal R&D firms achieve high levels of product innovation if there is the presence of R&D personnel development. If firms do not have R&D personnel development, they need to collaborate with customers and suppliers to achieve high levels of product innovation. However, non-formal R&D firms do not show the critical role of R&D personnel development, since it is present in and also absent from configurations to achieve high levels of product innovation. Finally, formal R&D firms result in low levels of product innovation if they just adopt quality control circles, customer collaboration, and supplier collaboration, without adopting in-house training, engineer rotation, and R&D personnel development. Whereas, non-formal R&D firms result in low levels of product innovation if they just adopt in-house training with the absence of R&D personnel development, even when there is the presence or absence of customer and supplier collaboration. Across these two groups, the results prove that missing out on adopting R&D personnel development causes firms to result in low levels of product innovation. Therefore, various configurations lead firms to achieve high levels and cause firms to result in low levels for promoting product innovation in formal and non-formal R&D firms. These configurations may not be the best HRM practices for promoting product innovation, but they are the best fits in the Thai manufacturing context. 6. Practical Implication, Limitations, and Further Studies Firms mainly adopt HRM practices based on their own capabilities. Large firms tend to have stronger capabilities to invest in formal R&D [ 48 , 49 ] and possess innovative advantages over smaller firms in terms of heterogeneous R&D activities [ 50 ]. Therefore, top management needs to realize their firm technological capabilities, whether it is formal or non-formal R&D [ 52 , 53 ], such that they can adopt appropriate HRM practices in accordance with the firm technological capabilities to promote J. Open Innov. Technol. Mark. Complex. 2020,6, 38 16 of 20 product innovation. The results from this study show that R&D personnel development helps formal R&D firms to achieve product innovation, whereas quality control circles do not. This is different from non-formal R&D firms, where there is not enough evidence to prove the importance of R&D personnel development, but quality control circles somehow help non-formal R&D firms to achieve product innovation. Additionally, the results show that collaboration with customers and suppliers is the best configuration for promoting product innovation in formal R&D forms, but these collaborations seem to be less significant if they in are non-formal R&D firms. Therefore, any types of HRM practices are beneficial in their own ways to promote product innovation if the top management is able to identify related complementary HRM practices. There are three main limitations; first, the results may only represent manufacturing firms in emerging economies, e.g., Thailand, because firms in these countries mainly have low internal capabilities and adopt top-down management systems for promoting innovation. This may be different from developed nations—e.g., Japan, the US, or EU countries—where firms mainly have high capabilities and may adopt bottom-up or middle-up-down management systems for promoting innovation. Second, a fuzzy-set quality comparative analysis was used to identify the configurations of causal conditions that achieve high levels and low levels of outcomes. These configurations were identified in accordance with the provided causal conditions and outcomes. Thus, the results in this study are limited to the internal HRM practices and supply chain collaboration presented in this research. Additional causal conditions may lead to variations in configurations for promoting product innovation. Third, firms may share the same configurations to achieve high levels and low levels of product innovation. These conflicts can be solved by making assumptions about complex solutions to achieve intermediate and parsimonious solutions. However, this study presents only complex solutions, and we mainly make conclusions on the conditions presented in every configuration for achieving high levels low levels of each type of product innovation. For further studies, first, this study could be conducted in the context of firms located in developed countries where local firms have high capabilities in human and financial capital. Results may provide us with different perspectives on the significance of internal HRM practices and supply chain collaboration for promoting product innovation in formal and non-formal R&D firms. Second, this research can also be expanded to countries that adopt bottom-up and middle-up-down management systems for promoting innovation. This is because different management systems lead firms to adopt different practices for creating knowledge and promoting innovation. Besides giving information on the manufacturing industry in emerging economies, this study can be expanded to study practices for promoting product innovation in the service and agricultural industries. In addition, other types of innovation—e.g., process, technological, marketing, and position innovation—can be investigated because different practices may be required to achieve these innovations. Author Contributions: Conceptualization, T.K., C.J., and Y.K.; methodology, T.K., C.J., and Y.K.; software, T.K.; validation, T.K., C.J., A.J., and Y.K.; investigation, T.K., A.J., and Y.K.; data collection, T.K. and C.J.; writing—original draft preparation, T.K.; writing—review and editing, T.K., C.J., A.J., and Y.K.; supervision, C.J., A.J., and Y.K. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Acknowledgments: This research was supported by the Economic Research Institute for ASEAN and East Asia (ERIA), and the Logistics and Supply Chain Systems Engineering Research Unit and Centre for Demonstration and Technology Transfer of Industry 4.0 (LogEn i4.0). It is also partially supported by the Sirindhorn International Institute of Technology (SIIT), Thammasat University (TU) and the Japan Advanced Institute of Science and Technology (JAIST). The authors would like to express our thankfulness to Dr. Masatsugu Tsuji, President of Kobe International University and Dr. Yasushi Ueki, a researcher from the Institute of Developing Economies and Japan External Trade Organization (IDE-JETRO) for providing valuable and useful guidelines on the designed questionnaire. Conflicts of Interest: The authors declare no conflict of interest. J. Open Innov. Technol. Mark. Complex. 2020,6, 38 17 of 20 References 1. Jeenanunta, C.; Rittippant, N.; Chongphaisal, P.; Hamada, R.; Intalar, N.; Tieng, K.; Chumnumporn, K. Human resource development for technological capabilities upgrading and innovation in production networks: A case study in Thailand. Asian J. Technol. Innov. 2017,25, 330–344. [CrossRef] 2. Mani, S. Human resource management and co-ordination for innovation activities—Cases from India’s automotive industry. Asian J. Technol. Innov. 2017,25, 228–245. [CrossRef] 3. Norasingh, X.; Southammavong, P. Firm-level human resource management and innovation activities in production networks: A case study of Lao handicraft firms. Asian J. Technol. Innov. 2017 ,25, 288–309. [CrossRef] 4. Binh, T.T.C.; Linh, N.M. Human resource management for innovation in Vietnam’s electronics industry. Asian J. Technol. Innov. 2017,25, 345–366. [CrossRef] 5. Tsuji, M.; Shigeno, H.; Ueki, Y.; Idota, H.; Bunno, T. Characterizing R&D and HRD in the innovation process of Japanese SMEs: Analysis based on field study. Asian J. Technol. Innov. 2017,25, 367–385. 6. Del Prado, F.L.E.; Rosellon, M.A.D. Developing technological capability through human resource management: Case study from the Philippines. Asian J. Technol. Innov. 2017,25, 310–329. [CrossRef] 7. Tsang, E.W.K. The knowledge transfer and learning aspects of international HRM: An empirical study of Singapore MNCs. Int. Bus. Rev. 1999,8, 591–609. [CrossRef] 8. Aminullah, E.; Hermawati, W.; Fizzanty, T.; Soesanto, Q.M.B. Managing human capital for innovative activities in Indonesian herbal medicine firms. Asian J. Technol. Innov. 2017,25, 268–287. [CrossRef] 9. Mohan, A.V. Human resource management and coordination for innovation activities: Gleanings from Malaysian cases. Asian J. Technol. Innov. 2017,25, 246–267. [CrossRef] 10. Glaister, A.J.; Karacay, G.; Demirbag, M.; Tatoglu, E. HRM and performance—The role of talent management as a transmission mechanism in an emerging market context. Hum. Resour. Manag. J. 2018 ,28, 148–166. [CrossRef] 11. Ueki, Y. The roles of top management characteristics, human resource management and customer relationships in innovations: An exploratory analysis. Asian J. Technol. Innov. 2017,25, 206–227. [CrossRef] 12. Zhang, J.A.; Edgar, F.; Geare, A.; O’Kane, C. The interactive effects of entrepreneurial orientation and capability-based HRM on firm performance: The mediating role of innovation ambidexterity. Ind. Mark. Manag. 2016,59, 131–143. [CrossRef] 13. Gill, R.; Wong, A. The cross-cultural transfer of management practices: The case of Japanese human resource management practices in Singapore. Int. J. Hum. Resour. Manag. 1998,9, 116–135. [CrossRef] 14. Newell, S.; Robertson, M.; Scarbrough, H.; Swan, J. Human resource management and knowledge work. In Managing Knowledge Work and Innovation; Palgrave Macmillan: London, UK, 2009. 15. Jørgensen, F.; Becker, K. The role of HRM in facilitating team ambidexterity. Hum. Resour. Manag. J. 2017 ,27, 264–280. [CrossRef] 16. Cooke, F.L. Concepts, contexts, and mindsets: Putting human resource management research in perspectives. Hum. Resour. Manag. J. 2018,28, 1–13. [CrossRef] 17. Fey, C.F.; Björkman, I.; Pavlovskaya, A. The effect of human resource management practices on firm performance in Russia. Int. J. Hum. Resour. Manag. 2011,11, 1–18. [CrossRef] 18. Shipton, H.; Fay, D.; West, M.; Patterson, M.; Birdi, K. Managing people to promote innovation. Creat. Innov. Manag. 2005,14, 118–128. [CrossRef] 19. Lin, C.-H.; Sanders, K. HRM and innovation: A multi-level organisational learning perspective. Hum. Resour. Manag. J. 2017,27, 300–317. [CrossRef] 20. Sobanke, V.; Adegbite, S.; Ilori, M.; Egbetokun, A. Determinants of technological capability of firms in a developing country. Procedia Eng. 2014,69, 991–1000. [CrossRef] 21. Li, X.; Wang, J.; Liu, X. Can locally-recruited R&D personnel significantly contribute to multinational subsidiary innovation in an emerging economy? Int. Bus. Rev. 2013,22, 639–651. 22. Gonz á lez, X.; Miles-Touya, D.; Paz ó , C. R&D, worker training and innovation: Firm-level evidence. Ind. Innov. 2016,23, 694–712. 23. Watanabe, S. The Japanese quality control circle: Why it works. Int. Labour Rev. 1991,130, 57–80. 24. Pfeffer, J. Competitive Advantage through People: Unleashing the Power of the Work Force; Harvard Business School Press: Boston, MA, USA, 1994. J. Open Innov. Technol. Mark. Complex. 2020,6, 38 18 of 20 25. Nonaka, I.; Takeuchi, H. The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation; Oxford University Press: Oxford, UK, 1995. 26. Delaney, J.T.; Huselid, M.A. The impact of human resource management practices on perceptions of organizational performance. Acad. Manag. J. 1996,39, 949–969. 27. Koch, M.J.; McGrath, R.G. Improving labor productivity: Human resource management policies do matter. Strateg. Manag. J. 1996,17, 335–354. [CrossRef] 28. Dyer, J.H.; Nobeoka, K. Creating and managing a high-performance knowledge-sharing network: The Toyota case. Strateg. Manag. J. 2000,21, 345–367. [CrossRef] 29. Kafouros, M.I.; Forsans, N. The role of open innovation in emerging economies: Do companies profit from the scientific knowledge of others? J. World Bus. 2012,47, 362–370. [CrossRef] 30. OECD. Thailand: Innovation profile. In Innovation in Southeast Asia; OECD Publishing: Paris, France, 2013. 31. Ren, S.; Wang, L.; Yang, W.; Wei, F. The effect of external network competence and intrafirm networks on a firm’s innovation performance: The moderating influence of relational governance. Innovation 2013 ,15, 17–34. [CrossRef] 32. Pellegrini, L.; Lazzarotti, V. How governance mechanisms in family firms impact open innovation choices: A fuzzy logic approach. Creat. Innov. Manag. 2019,28, 486–500. [CrossRef] 33. Hsieh, W.L.; Ganotakis, P.; Kafouros, M.; Wang, C. Foreign and domestic collaboration, product innovation novelty, and firm growth. J. Prod. Innov. Manag. 2018,35, 652–672. [CrossRef] 34. Ahn, J.M.; Kim, D.-B.; Moon, S. Determinants of innovation collaboration selection: A comparative analysis of Korea and Germany. Innovation 2017,19, 125–145. [CrossRef] 35. Sudhir Kumar, R.; Bala Subrahmanya, M.H. Influence of subcontracting on innovation and economic performance of SMEs in Indian automobile industry. Technovation 2010,30, 558–569. [CrossRef] 36. Bullinger, H.-J.; Auernhammer, K.; Gomeringer, A. Managing innovation networks in the knowledge-driven economy. Int. J. Prod. Res. 2004,42, 3337–3353. [CrossRef] 37. Stock, G.N.; Greis, N.P.; Kasarda, J.D. Enterprise logistics and supply chain structure: The role of fit. J. Oper. Manag. 2000,18, 531–547. [CrossRef] 38. Reichstein, T.; Salter, A.J.; Gann, D.M. Break on through: Sources and determinants of product and process innovation among UK construction firms. Ind. Innov. 2008,15, 601–625. [CrossRef] 39. Yunus, E.N. Leveraging supply chain collaboration in pursuing radical innovation. Int. J. Innov. Sci. 2018 ,10, 350–370. [CrossRef] 40. Lawson, B.; Krause, D.; Potter, A. Improving supplier new product development performance: The role of supplier development. J. Prod. Innov. Manag. 2015,32, 777–792. [CrossRef] 41. Menguc, B.; Auh, S.; Yannopoulos, P. Customer and supplier involvement in design: The moderating role of incremental and radical innovation capability. J. Prod. Innov. Manag. 2014,31, 313–328. [CrossRef] 42. Tsai, K.-H. Collaborative networks and product innovation performance: Toward a contingency perspective. Res. Policy 2009,38, 765–778. [CrossRef] 43. Song, M.; Thieme, J. The role of suppliers in market intelligence gathering for radical and incremental innovation. J. Prod. Innov. Manag. 2009,26, 43–57. [CrossRef] 44. Kibbeling, M.; Van Der Bij, H.; Van Weele, A. Market orientation and innovativeness in supply chains: Supplier’s impact on customer satisfaction. J. Prod. Innov. Manag. 2013,30, 500–515. [CrossRef] 45. Amara, N.; Landry, R. Sources of information as determinants of novelty of innovation in manufacturing firms: Evidence from the 1999 statistics Canada innovation survey. Technovation 2005 ,25, 245–259. [CrossRef] 46. Freel, M.S.; Harrison, R.T. Innovation and cooperation in the small firm sector: Evidence from ‘Northern Britain’. Reg. Stud. 2006,40, 289–305. [CrossRef] 47. Harhoff, D.; Mueller, E.; Van Reenen, J. What are the channels for technology sourcing? Panel data evidence from German companies. J. Econ. Manag. Strategy 2014,23, 204–224. 48. Intarakumnerd, P.; Chairatana, P.-A.; Tangchitpiboon, T. National innovation system in less successful developing countries: The case of Thailand. Res. Policy 2002,31, 1445–1457. [CrossRef] 49. Petsas, I.; Giannikos, C. Process versus product innovation in multiproduct firms. Int. J. Bus. Econ. 2005 ,4, 231–248. 50. Choi, J.; Lee, J. Firm size and compositions of R&D expenditures: Evidence from a panel of R&D performing manufacturing firms. Ind. Innov. 2018,25, 459–481. J. Open Innov. Technol. Mark. Complex. 2020,6, 38 19 of 20 51. Arnold, E.; Bell, M.; Bessant, J.; Brimble, P. Enhancing policy and institutional support for industrial technology development in Thailand. In The Overall Policy Framework and the Development of the Industrial Innovation System; SPRU-Science and Technology Policy Research: Bangkok, Thailand, 2000. 52. Tsuji, M.; Ueki, Y.; Shigeno, H.; Idota, H.; Bunno, T. R&D and non-R&D in the innovation process among firms in ASEAN countries. Eur. J. Manag. Bus. Econ. 2018,27, 198–214. 53. Intarakumnerd, P. Human resource management and coordination for innovative activities in production networks in Asia: A synthesis. Asian J. Technol. Innov. 2017,25, 199–205. [CrossRef] 54. OECD. Frascati manual 2015: Guidelines for collecting and reporting data on research and experimental development. In The Measurement of Scientific, Technological and Innovation Activities; OECD Publishing: Paris, France, 2015. 55. Kleinknecht, A. Measuring R&D in small firms: How much are we missing? J. Ind. Econ. 1987,36, 253–256. 56. Santamar í a, L.; Nieto, M.J.; Barge-Gil, A. Beyond formal R&D: Taking advantage of other sources of innovation in low- and medium-technology industries. Res. Policy 2009,38, 507–517. 57. Schumpeter, J.A. Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest and the Business Cycle; Harvard University Press: Cambridge, MA, USA, 1934. 58. Van de Ven, A.H. Central problems in the management of innovation. Manag. Sci. 1986 ,32, 590–607. [CrossRef] 59. Swan, J.; Newell, S.; Robertson, M. The illusion of ‘best practice’ in information systems for operations management. Eur. J. Inf. Syst. 1999,8, 284–293. [CrossRef] 60. Mangematin, V.; Mandran, N. Do non-R&D intensive industries benefit of spillovers from public research? The case of the agro-food industry. In Innovation and Firm Performance. Econometric Explorations of Survey Data; Kleinknecht, A., Monhen, P., Eds.; Palgrave: London, UK, 2001. 61. Rogers, M. The Definition and Measurement of Innovation; Melbourne Institute of Applied Economic and Social Research: Parkville, Victoria, Australia, 1998; Volume 98. 62. Saha, S. Firm’s objective function and product and process R&D. Econ. Model. 2014,36, 484–494. 63. Tsuji, M.; Idota, H.; Ueki, Y.; Bunno, T. Innovation process of natural-resource-based firms in four ASEAN economies: An SEM approach. STI Policy Manag. J. 2017,2, 1–14. [CrossRef] 64. Ogawa, M.; Ueki, Y.; Idota, H.; Bunno, T.; Tsuji, M. Internal innovation capacity and external linkages in firms of ASEAN economies focusing on endogeneity. J. STI Policy Manag. 2018,3, 97–117. [CrossRef] 65. NESDB; OPM. The Twelfth National Economic and Social Development Plan: Thailand (2017–2021); Office of the National Economic and Social Development Board and Office of the Prime Minister: Bangkok, Thailand, 2017. 66. MOI. List of Firms Categorized by Location. 2015. Available online: http://www2.diw.go.th/factory/tumbol. asp (accessed on 3 December 2016). 67. Ragin, C.C.; Davey, S. Fuzzy-Aet/Qaulitative Compartive Analysis 3.0; Department of Sociology, University of California: Irvine, CA, USA, 2016. 68. Zadeh, L.A. Fuzzy sets. Inf. Control 1965,8, 338–353. [CrossRef] 69. Ragin, C.C. Redesigning Social Inquiry: Fuzzy Sets and Beyond; University of Chicago Press: Chicago, IL, USA, 2008. 70. T ó th, Z.; Thiesbrummel, C.; Henneberg, S.C.; Naud é , P. Understanding configurations of relational attractiveness of the customer firm using fuzzy set QCA. J. Bus. Res. 2015,68, 723–734. [CrossRef] 71. Fiss, P.C. A set-theoretic approach to organizational configurations. Acad. Manag. Rev. 2007 ,32, 1180–1198. [CrossRef] 72. Ragin, C.C.; Rihoux, B. Qualitative Comparative Analysis (QCA): State of the Art and Prospects. In Proceedings of the Annual Meeting of the American Political Science Association, Chicago, IL, USA, 2–5 September 2004. 73. Ueki, Y.; Tsuji, M. The roles of ICTs in product innovation in Southeast Asia. In Proceedings of the 5th Multidisciplinary International Social Networks Conference, Saint-Etienne, France, 16 July 2018. 74. Nunnally, J.C. Psychometric Theory, 2nd ed.; McGraw-Hill: New York, NY, USA, 1978. 75. Hsiao, Y.-H.; Chen, L.-F.; Chang, C.-C.; Chiu, F.-H. Configurational path to customer satisfaction and stickiness for a restaurant chain using fuzzy set qualitative comparative analysis. J. Bus. Res. 2016 ,69, 2939–2949. [CrossRef] J. Open Innov. Technol. Mark. Complex. 2020,6, 38 20 of 20 76. Scaringella, L.; Burtschell, F. The challenges of radical innovation in Iran: Knowledge transfer and absorptive capacity highlights-Evidence from a joint venture in the construction sector. Technol. Forecast. Soc. Chang. 2017,122, 151–169. [CrossRef] 77. Kafouros, M.I.; Buckley, P.J.; Sharp, J.A.; Wang, C. The role of internationalisation in explaining innovation performance. Technovation 2008,28, 63–74. [CrossRef] © 2020 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 (http://creativecommons.org/licenses/by/4.0/).