影響手機電子廠商使用RoHS的製程材料關鍵要素分析

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(1)國立臺灣師範大學工業教育學系碩士論文指導教授：郭金國博士. 影響手機電子廠商使用 RoHS 的製程材料關鍵要素分析 A Derivation of Key Success Factors for Influencing the Adoption of RoHS Process Materials by Mobile Phone Manufacturers. 研究生：吳志昭中華民國 107 年 8 月.

(2) 摘要隨著全球暖化日趨嚴重，以及消費者對環境保護與綠色消費意識的日漸重視，因此，在全球環保意識的提升、綠色技術的持續發展以及各國對環境保護的重視與要求，產品的生產製造，必須兼具環保；本研究將導入技術背景、組織背景及外在環境背景(Technological context, Organizational context and Environmental context, TOE) 模式，針對我國手機廠商使用「危害物質禁用指令」（RoHS；Restriction of the use of certain hazardous substance in electrical and electronic equipment）的製程材料關鍵要素進行分析，並探討如何導入適當的技術策略，以提升企業的競爭力。本研究將以偏最小平方結構方程模型(Partial Least Squares Structural Equation Modeling, PLS-SEM)檢定 TOE 模式之假設顯著，並以本國手機製造廠商之專業經理人為樣本，實證本研究架構之可行性。實證研究的結果，將可作為政府單位訂定倡導科技業導入 RoHS 製程材料環保政策之用。. 關鍵字：RoHS、製程材料、影響因素、綠色製造、TOE模式. i.

(3) Abstract The global warming is increasingly serious, as well as consumer environmental protection and green consumer awareness of the awakening, therefore, in the global awareness of environmental protection, green technology, sustainable development and national environmental protection and the requirements of the product in the manufacturing requirements, must meet the technical and environmental protection of the production environment; this study explores the adoption of Restriction of the use of certain hazardous substance in electrical and electronic equipment (RoHS) in terms of Taiwan's mobile electronics manufacturers for understanding the adopting behaviors of firms to use the "Hazardous Substances Directive", and further analyzes the key factors of the process material under the RoHS directive and how to use the appropriate technical strategy to enhance the competitiveness of the enterprise through the previous target specification. In this study, the PLS-SEM method will be utilized to confirm the hypothesized relationships based on TOE model. The proposed model and empirical results can serve as the basis to define the environmental protection policy to promote the RoHS materials.. Keywords: RoHS, Process material, Influencing factors, Green manufacturing, TOE. ii.

(4) Table of Contents 摘要 .................................................................................................................. i Abstract ............................................................................................................ ii Table of Contents ............................................................................................ iii List of Table ..................................................................................................... v List of Figure .................................................................................................. vi Chapter 1 Introduction ..................................................................................... 1 1.1. Research Backgrounds and Motivations ......................................... 1. 1.2. Research Purposes .......................................................................... 3. 1.3. Research Scope .............................................................................. 3. 1.4. Research Limitations ...................................................................... 4. 1.5. Research Process ............................................................................ 5. Chapter 2 Literature review .............................................................................. 7 2.1. Sustainability.................................................................................. 7. 2.2. Green Manufacturing ..................................................................... 8. 2.3. The TOE Framework .................................................................... 10. 2.3.1 Technological Background (TB) .................................................. 10 2.3.2 Organizational Background (OB) ................................................. 12 2.3.3 Environmental Background (EB) ................................................. 13 2.4. Factors Influencing the Adoption of Green Process Materials....... 14. Chapter 3 Research Method ........................................................................... 17 3.1. Partial Least Squares based Structural Equation Model (PLS-SEM)...................................................................... 17. Chapter 4 Empirical Study ............................................................................. 21 4.1. Data Collection and Analysis ........................................................ 21 iii.

(5) 4.2. Descriptive Statistics .................................................................... 22. 4.3. Measurement Model Assessment .................................................. 23. 4.4 Structural Model Assessment ............................................................ 25 Chapter 5 Discussion...................................................................................... 29 Chapter 6 Conclusion ..................................................................................... 33 References ..................................................................................................... 35 Appendix ....................................................................................................... 41. iv.

(6) List of Table Table 4-1 Reliability analysis of TOE dimension………..………..………24 Table 4-2 RoHS PMF facet convergence validity…………………..…..…25 Table 4-3 Hypothesis verification results………….………………………27. v.

(7) List of Figure Figure 1-1 Rsesarch Process ........................................................................... 05 Figure 3-1 The PLS path modelling example.................................................. 18 Figure 4-1 Path relationship diagram………………………………………….26. vi.

(8) Chapter 1 Introduction 1.1 Research Backgrounds and Motivations With the increase of global attentions in environmental sustainability, many countries have put lots of interests in green practices as the key factors to realize sustainability (Co-operation & O.F.E., 2009). In order to achieve sustainable development targets, conventional green solutions are based the concepts of “end-of-pipe” for reducing extant adverse impacts of environments. Under such situations, many firms might be passive to use the green solutions for avoiding the harms for environment instead of employing proactive measures to reduce sources of waste or pollution (Hsu, Choon Tan, Hanim Mohamad Zailani, & Jayaraman, 2013). However, solely emphasizing on how to promote environmental sustainability towards to level of firms may lead to negative impacts on whole supply chain (Cousins, Lamming, & Bowen, 2004). For reducing the sources of wastes of pollutions, firms have leveraged the open actions by which the green initiatives will be expanded beyond the level of firms to entire supply chain, including multi-organizations and up-down streams (Vachon & Klassen, 2006). In order to thoroughly carry out the green solutions in supply chain, it is necessary to introduce a green supply chain in initial stage of production process instead of solely utilizing end-of-pipe approach in later stages. Such introduction of green supply chain in early stage will be beneficial for facilitation of environmental sustainability and, further enhancement of economic and technical performance of value chain within industries (Carter & Rogers, 2008; Weng, Chen, & Chen, 2015).. 1.

(9) In recent years, the international community has been continuously promoting the green supply chain. Governments have successively formulated environmental protection laws and regulations to require manufacturing manufacturers. The EU promulgated the “Restriction of the Use of Certain Hazardous Substance in Electrical and electronic equipment” (RoHS) in which the products must follow the relevant regulations before they can be marketed in order to safeguard the safety of consumers and reduce environmental risks. Facing various tests and industries in terms of environment, it is a major challenge. Its influence covers the terminal industries such as electronics and automobiles, and it also has a structural impact on the upstream products, materials and raw materials industries. Due to the continuous improvement of information technology, new products have been introduced one after another, and the global physical resource changes have taken shape. Therefore, with the promotion of global awareness of environmental protection, the continuous development of green technologies and the emphasis and requirements of environmental protection in various countries, it is necessary to meet both the technical and environmental protection requirements for the production and manufacturing of products. In the process of developing design and production manufacturing to integrate environmental considerations, the procurement of raw materials have to be follow the regulatory requirements of environment (Brewer & Arnette, 2017), the entire product life cycle must be environmentally friendly design, therefore, in the product life of the various stages of the process, from the raw material mining, manufacturing to use, waste recycling, must be friendly to the environment. This research discusses the key successful factors being faced by domestic handset electronics manufacturers under the trend of RoHS directives and ex2.

(10) plores the ways in which mobile phone electronics manufacturers respond to the challenging environment. It also analyzes the key elements of handset electronics manufacturers' process materials and how to apply appropriate technical strategies.. 1.2 Research Purposes In accordance with the research background and motivations discussed above, this research aims to explore the key factors of the process materials that affect the use of RoHS for handset electronics manufacturers. The purpose of this study is summarized for the following three points: (1) Find out the key factors affecting adoption of RoHS for handset electronics manufacturers; (2) Examine the potential causal influential relations between key factors; (3) Provide an analytical model and empirical results that can be served as the basis to define the environmental protection policy to promote the RoHS materials.. 1.3 Research Scope The development and design of mobile electronic technology products aims to make our daily life more convenient and enhance the quality of our life. However, under the guidance of its leading-edge science and technology products, this research aims to build a manufacturing process that affects the use of RoHS by handset electronics manufacturers. The hope is that both science and technology and environmental protection are both a production and development environment; therefore, their motivation for research is that, in consideration of the ever-increasing international protection and emphasis on the environment and the scientific and technological living environment in which modern people are seeking convenience, science and technology products are 3.

(11) easy In the light of the changes of the times, the quick replacement resulted in the shortening of the cycle of the product life cycle. In order to enable the technological products to achieve the environmental protection, the mobile phones during the design and production have to rely on a green point of view for protecting the environment. Making a green assessment at all stages of manufacturing not only can provide the positive contributions for environmental protection, but also can meet the future technology products face replacement cycle of rapid life cycle. Hence this study will affect the handset electronics manufacturers use of RoHS process materials, the key factors in providing RoHS process materials direction, the scope of the study is divided into the following stages according to the viewpoint of their handset electronics manufacturers and the relative importance of the key factors of their green standards at each stage of handset electronics manufacturers: (1) RoHS process material technology, (2) raw material procurement reliability, (3) manufacturing safety, (4) the use of the applicability, (5) cost-benefit relevance.. 1.4 Research Limitations Due to an environmental directive adopted by the EU 2003 (RoHS), there are still many companies that are just importing and marketing green products. As far as the current market share of green products is still to be strengthened, the research limits in a relatively complete series of proprietary products cannot be obtained as a green product evaluation criteria for the relevance of research; would like to cell phone electronics manufacturers as a case, the relevant RoHS environmental directives literature discussion, as the basis for the evaluation of mobile phone manufacturers guidelines. 4.

(12) 1.5 Research Process In this research, in addition to above-mentioned sections, the operation process regarding the implementation of research can be split into several steps. First, the key factors will be collected from the literature review. These key factors will be used to design a questionnaire for experts’ survey. Then, the PLS-SEM will be utilized to confirm the hypothesized relationships proposed from this research. Finally, the empirical results and conclusions will be proposed. The research process is illustrated in Figure 1-1.. Figure 1-1 Research Process.. 5.

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(14) Chapter 2 Literature review This section is composed of following sections. The literature on Sustainability is illustrated in Section 2.1. Section 2.2 briefly discusses the green manufacturing. Section 2.3 introduces an important model, the TOE framework. Section 2.4 finally depicts the factors based TOE model to the adoption of green process materials.. 2.1 Sustainability Transforming the society and economy to sustainability can be one of critical difficulties in this era (Dyball, Brown, & Keen, 2007). Sustainability involves in many different scopes. Hence, it is hard to define a simple method to realize it. To achieve sustainability, a novel thinking, a new vision, a new dream, and a unique technique will be indispensable (Ben-Eli, 2004). The final purpose of building up the sustainability can be understood as a well-interaction system where people, technology, society, and the economy can communicate each other (Ben-Eli, 2006). Such interactive system stands for a special type of dynamic equilibrium in whole environment. Given this dynamic equilibrium, sustainable development and sustainability are meaningfully defined accordingly (Ben-Eli, 2006). In general, the sustainability is defined as a concept emphasizing on cross-generational equity. Although this concept has been fully and clearly explained, it is really difficult to achieve. Apparently, this is because the needs in the future cannot be completely defined now. Hence, the definition of sustaina7.

(15) bility according to Ben-Eli (2006) is depicted as a dynamic equilibrium of interactive system has to exist in which individuals and the tolerability of environment will be equilibrium, based on this, the individuals can promote development of society, technology and economy without negative impacts on the tolerability of the environment. As the above definitions for sustainability, realizing sustainability can be a significant challenge. Albeit difficult, sustainability is still a goal that countries and firms are actively chasing, since sustainable development will be favorable for our environment and future life. For manufacturing industries, developing technological products with green solutions is inevitable. Therefore, introducing the green solutions in productions and development at early stage is essential and important.. 2.2 Green Manufacturing Manufacturing firms living in this era are meaningful as they are able to be the crucial roles for promotion of environmental ecosystem instead of being the ones who make disasters to environment. In facilitating the environmental protection, market factors and government regulations are two critical drivers for green manufacturing. These two important drivers also provide tremendous risks for those who are making pollutions for environment. Generally speaking, developing green manufacturing may be accompanied with large cost and expenses. However, cleaner production, energy conservation, and the reduction of waste and pollution, in fact, can even offer more business opportunities for firms. That is, taking into consideration above green solutions will reduce risks and costs in business operating (Melnyk, Sroufe, Montabon, & Hinds, 2001). 8.

(16) Treating wastes and pollutions are often considered as passive actions restricted in law and regulations. In fact, there still seems to have other reasons influencing firms to adopt green solutions. For instances, the cost is increasing in disposing of hazardous materials. The pressure is increasing from market resistance to harmful products. The human’s consciousness of environmental sustainability is burgeoning. The wastes and pollutions can be classified into several categories depending on the green manufacturing system in general: (1) hazardous materials; (2) solid wastes; (3) greenhouse gases; (4) energy and; (5) water usage. Similar to lean production, green manufacturing also has a set of measures for reducing the pollutions and wastes. By means of these measures, the reduction of wastes can be effectively treated in process of green manufacturing. A comprehensive system in green manufacturing will influence each of aspects thorough the whole units including management, marketing, R&D, customers’ relationship, production and etc. Nevertheless, very few firms have expanded green system to such boundary where all of units will be connected and interacted each other for implementing the green measures. Based on the literature, most of firms only adopt the green measures and solutions in the manufacturing production and work their way upward and outward over time (Scallon & Sten, 1996). In this research, the key factors influencing RoHS materials adoption in mobile phone production will be focused.. 9.

(17) 2.3 The TOE Framework The technology–organization–environment (TOE) model is presented by Tornatzky, Fleischer, and Chakrabarti (1990) who depicted the innovation as a process where the innovation development is always affected through engineers, entrepreneurs and users. TOE offers a useful theoretical framework in analyzing how are the factors related to technology, organization, and environment affecting firms to adopt the novel innovations and particular technologies. These three important drivers are respectively the Technological Background (TB), the Organizational Background (OB), and the Environmental Background (EB). In order to develop the analytical framework of this research, TOE model will be taken refer and possible factors will be further selected and determined from this model. The TOE model and related hypotheses will be discussed in subsequent sections. 2.3.1 Technological Background (TB) The Technology Background (TB) indicates that the features of related technology will affect the diffusion of particular technologies (Tornatzky et al., 1990). More specifically, TB is composed of existing technologies that are being used and those available technologies form external place including market and other organizations. The extant technologies of companies are crucial in the process of determining adopting other new technologies, since existing technologies can be seen as a benchmark and limitation for those new technologies. Firms can base on the comparison of different technologies to conduct technological change (Xu, Ou, & Fan, 2017). Potential innovation, which currently does not be used, will also impact the innovation development at firms’ 10.

(18) level. These potential innovations can be split two forms: defining the limitation of possible innovations and modifying present innovations by observing different extant innovations. Besides, it is definitely for firms to discover innovations from the external organizations. To sum up, innovations can also be categorized into three types, including incremental, synthetic and discontinuous types (Tushman & Nadler, 1986). As discussion of TB, the technological innovations of firms and organizations can be influenced based on internal and external technologies. TB includes many of characteristics affecting firms to adoption of technology. For example, technology readiness can be one of important criteria being comprised in the TB aspect. For mobile phone manufacturers, determining to adopt RoHS materials in production process may need to consider many technological factors relevant to the use of prohibited materials. These factors may influence firms or organizations performances such as financial performance. To follow the green regulations and promote green manufacturing to meet the future production trend, adopting RoHS may be necessary for firms. If the firms understand the related technology knowledge of RoHS in production and environment protection more, they will be more willing to adopt RoHS for production. Therefore, firms with higher level of technology-related background are better determined for the adoption of the RoHS process materials. Thus, H1: TB will positively influence the adoption of RoHS process materials.. 11.

(19) 2.3.2 Organizational Background (OB) The Organizational Background is defined based on the resources available to help the particular technology adoption (Lippert & Govindarajulu, 2006). A great number of scholars have explored the relationships between OB and technology adoption (Lippert & Govindarajulu, 2006). In these relationships, there are two important relations, including top management support and particular technology knowledge and experiences, can be used to examine particular technology adoption. Theses two critical criteria have also been verified the effectiveness to affect the information technology adoption (Jia, Guo, & Barnes, 2017). However, there still are many factors influencing firms’ technology adoption. For examples, the criteria of firm size often being leveraged to investigate the IT adoption. Based on the past literature review, the larger of firm size, the greater of intention to adopt particular technology. The firm scope often can also be utilized as independent variable to analyze the adoption of IT. Moreover, competiveness pressure and regulatory may also influence the technology adoption (Lippert & Govindarajulu, 2006). The top management support always plays a big role influencing enterprise’ decision-making process (Ahani, Rahim, & Nilashi, 2017). Management support is also found to have impact on organizational learning, knowledge management and technology sourcing. Given these influential relations, the competitive advantages may further be enhanced. Moreover, technology-related knowledge and experience is a determinant affecting technology adoption. According to the previous studies on technology adoption, employees having sufficient technology usage experience can maximize the productivity. Adopting particular materials to produce electronics devices can also be re12.

(20) garded as a kind of technology adoption. This is because firms have to consider whether the materials adoption will impact organizational performance. From organizational perspective, taking possible factors into account to determine the adoption of the materials in production is also very important in decision making. In lights of above discussions, the adoption of RoHS materials for production process may be capable of being affected organization-based factors. Therefore, this study proposes a hypothesized relationship: H2: OB will positively influence the adoption of RoHS process materials. 2.3.3 Environmental Background (EB) In accordance with the scope of TOE model, the Environmental Background (EB) represents that firms can do business activities under some specific conditions (Ahani et al., 2017). These specific conditions include several factors that will influence certain technology adoption. For example, competitive pressure, which refers the degree of pressure from competitors in the market, can significantly influence the technology adoption (Oliveira & Martins, 2011). The competitive pressure sometimes can also force firms to make some changes in production and design. For instance, on the basis of competitive pressures, firms may need to make pricing and competitive evaluation when they decide to launch new products to the market. In short, competitive pressures may lead to environmental uncertainties and raise the necessity of technology adoption. If firms would like to adopt a new materials that will be applied into production, evaluating competitors’ strength and weakness and pricing for new products will be necessary. Give the assessment and analysis, firms can make response in time to determine if they should use process materials for producing new electronics devices. 13.

(21) Moreover, expectation of market trend is another important factor influencing technology adoption. If process materials adoption is believed to be the manufacturing industry’s trends, then most firms will be more willing to adopt it. Those rivals who decided not to participate the contest risk being left behind, and may be disadvantaged to their competitors (Yee-Loong Chong & Ooi, 2008). Therefore, based on above illustration regarding to EB and technology adoption, this research hypothesizes that: H3: EB will positively influence the adoption of RoHS process materials.. 2.4 Factors Influencing the Adoption of Green Process Materials In this section, author would like to explore the factors that affect the adoption of green process materials. Therefore, author will review the relevant literature in the past and understand the key factors in the relevant research for further reference. With the accelerated adoption of technology products, the short life expectancy of products, and the substantial growth of global electronics wastes, green product design is indispensable as the global emphasis on environmental protection is emphasized. From green design to evaluation of a variety of raw materials and process technologies as well as to plan the relevant environmental issues, all of measures are to achieve the least environmental impacts at the minimal cost (Lin, 2011). Material selection is an important part of product design. The green performance of the product is mainly reflected by the performance of the material. Thus, the material choice in green design is crucial. Material selection is the 14.

(22) key and foundation of sustainable development. Material selection, not only to consider the use of performance, process performance and economic principles, but also environmental factors should be considered to achieve the environmental coordination of materials and materials performance, cost and harmony between the unities. Material engineers and product engineers should devote themselves to the design, production and use of environmentally friendly new materials to protect the environment, conserve resources and energy (Wang, 2001). The factors can be derived from the seven primary concepts: capacity barriers, cultural and social resistance, lack of incentives for promoting green building, inadequate cost data for green buildings, inadequate information regarding the financial and economic benefits and opportunities of green buildings, limited range of green products and materials and delays in obtaining certification and permits for green buildings (SIMPEH, 2015). By taking advantage of these concepts, related measurement items based TOE framework for question survey will be developed.. 15.

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(24) Chapter 3 Research Method This chapter will illustrate the research method of this study and shows the analytical architecture. This section will introduce the Partial Least Squares based Structural Equation Model (PLS-SEM).. 3.1 Partial Least Squares based Structural Equation Model (PLS-SEM) SEM has become one of significant research techniques for examining causal relationship frameworks with latent variables. SEM is also broadly applied into various research domains such as consumers’ satisfaction, marketing management and firms’ image. In general, SEM based analytical tools can be split into two different forms: covariance based SEM (CB-SEM) and principal component based SEM (PLS-SEM). PLS-SEM is constructed based on the repetition approach that maximizes the explained variance of endogenous constructs (Fornell & Bookstein, 1982). PLS-SEM not only can be used to test the relationship between variables, but also this method can be utilized to develop a conceptual predicting model. Comparing to the CB-SEM, PLS-SEM has more advantages, including relatively small data set for use the analysis, non-normal data set, and formatively measured dimensions. On the basis of the above advantages of PLS, PLS thus can be regarded as an alternative technique replacing of CB-SEM to conduct analyses. A brief illustration of PLS-SEM path modeling is presented in Figure 3-1. Based on Figure 3-1, the two types of models including formative and reflective models are depicted. Meanwhile, the outer model and inner model will also be introduced. 17.

(25) Figure 3-1 The PLS path modeling example. Note. Henseler, Ringle, and Sinkovics (2009).. Here, the related models used to constitute PLS-SEM path modeling will be explained in more detail. First, the outer model, which is also called measurement model that has to treat the relationship between a latent variable and responding observed variables, can be described as: The reflective form: xab = a 0ab + a ab X a + errorab. (1). The formative form: X a = a 0a + a ab xab + errora. (2). The symbol of a ab represents the factor loadings, the. stands for the inter-. cept value, and the error term means the residuals. For simplicity, above two forms are constructed in terms of concept of regression specification and can be further rewritten as: 18.

(26) The reflective form: E  xab X a   0ab   ab X a. (3). The formative form: E  X a xab    0a   ab xab. (4). In addition to outer models, inner models, which refers to structural model, can be used to explain model effect, as shown below: X a  0  i a ai X i  errora. (5). After briefly introduction, the model evaluation will be further explained. Since the PLS path modeling technique to SEM does not require the assumption of distribution. In order to rationally evaluate the model fit, some indicators have to be leveraged for testing model performance. Therefore, several indicators often being used to adopted and followed, as shown below: (1) Reliability indicators The reliability indicator aims to examine the internal consistency based on corresponding dimensions. Mostly, two significant evaluation criteria, consisting of Cronbach’s alpha and composite reliability, are employed to test model fit. (2) Validity indicators The validity indicators can be divided into two categories: convergent validity and discriminant validity. More specifically, the purpose of convergent validity is to assess the appropriateness of items and its belonging dimension. In general, if the item’s loading exceeds 0.5, which means that these items have convergent validity. The purpose of discriminant validity is to explore the level of dissimilarity between dimensions. Based on the evaluation criteria, average variance extracted (AVE) exceeding 0.5 will be regarded as the acceptable in validity examination. (3) Structural model performance 19.

(27) The evaluation indicator of R-squares is one of most important criteria for structural model assessment. This indicator represents the assessment of explained variance of a latent variable with respect to its whole variance. In addition, path coefficients are also important need to be examined and tested based on their algebraic sign, statistical significance and magnitude. All in all, similar to CB-SEM, PLS path modeling is also a robustness statistical method that can be applied into causality confirmation and theoretic model development. In recent years, there are more and more scholars who have attempted to adopt PLS-SEM as analytical tools for their studies. In accordance with their studies, reflective model is broadly utilized versus formative model. This result indicates that PLS-SEM can effectively deal with influential relationships and this method can be replaced of CB-SEM for path modeling research. Given above-mentioned reasons, PLS-SEM will be used here for confirming hypothesized influential relationships.. 20.

(28) Chapter 4 Empirical Study 4.1 Data Collection and Analysis To perform this study, a questionnaire was first developed for investigating the adoption of RoHS process materials by mobile phone manufacturers. The data collection was carried out in November 2017. To measure the adoption of RoHS process materials by mobile phone firms, the feasible measurement items were collected and adapted from the prior literature. After the confirmation for the measurement items by experts, a final questionnaire is finished. All of the items were measured using a 5-point Likert-type scale. The research instrument had 20 questions that could be answered on a Likert scale of 5 points, with a note corresponding to the degree of agreement with assertions for which 5 was “very much”, and 1 was “not at all”. A total of 150 questionnaires were sent via e-mail to senior top directors serving in mobile phone industry in Taiwan, and all of questionnaires were returned with response rate of 100%. In this investigation, the assessment construct and measurement items were evaluated the appropriateness by experts’ opinions in order to obtain the validity for the use of research. Then, the identified constructs were utilized to subsequent analyses. In this research, the Partial Least Squares (PLS) method, a statistical analysis technique based on the Structural Equation Modeling (SEM), was employed to validate the proposed framework with empirical case and to examine the hypothesized relationships among the identified constructs. PLS-SEM is an extensively accepted approach to gauge the applicability of theoretical model with empirical data (Götz, Liehr-Gobbers, & Krafft, 2010). Besides, a PLS method including reflective and 21.

(29) formative models does not require a normal distribution, as opposed to covariance-based approaches, which requires a normal distribution (Henseler, Ringle, & Sarstedt, 2012). To conduct the research, one of the well-known software applications for PLS-SEM, namely SmartPLS software 3.2.7, was used to deal with collected data. In the following sections, the descriptive statistics analysis, measurement model assessment, and structural model assessment are presented, respectively.. 4.2 Descriptive Statistics This study used SPSS 23 for descriptive statistic analysis. The analytical results are shown below: (1) The male ratio is 13 higher than that of females, accounting for 68.6% of the sample, while 11 females account for 31.4% of the sample. (2) The age group is mainly 31-40 years old, a total of 20 people, accounting for 60.0% of the sample number, followed by 51-60 years old, a total of 7 people, accounting for 20.0%. (3) The industry has a total of 27 manufacturing industries, accounting for 77.1% of the total number of samples. (4) The company has the largest number of employees, 100 to 500, accounting for 51.4% of the sample, followed by 17.1% for the following 100. (5) Since its establishment, the company has been the largest in 21~30 years, accounting for 45.7% of the sample, followed by 22.9% in 21~30 years. (6) The work department has the largest number of production departments, a total of 16 people, accounting for 45.7% of the sample, followed by 11 research and development departments. (7) The degree of education is the largest in universities (including spe22.

(30) cialists), with a total of 24 students, accounting for 68.6% of the sample. (8) Personal income is 25-100 million NT dollars, accounting for 71.4% of the sample.. 4.3 Measurement Model Assessment The measurement model was assessed in terms of item loadings, construct reliability, and convergent and discriminant validity. In general, the measurement model is assessed according to following indicators by Fornell and Larcker (1981). The item loading should be exceeding 0.5. Construct reliability should be more than 0.8. Discriminant validity stands for each item correlates weakly with all the constructs besides its theoretically related constructs, was evaluated by using the square root of the average variance extracted from each construct was higher than the inter-construct correlation (Trinchera, 2008). More specifically, the average variance extracted (AVE) by each construct for checking the discriminant validity should exceed the amount of measurement error variance (AVE > 0.5). As shown in Table 4-1, all of the AVE and CR values for constructs were satisfactory, with composite reliabilities at 0.875 or more and AVE values at 0.636 and above. Further, as suggested by Nunnally (2010), Cronbach’s alpha values should be higher than 0.70. The t-values indicate that identified items are significant, suggesting good construct validity. The Cronbach’s alpha of each construct obtained from this research ranged from 0.812 to 0.968 met the guidance. Thus, the measurement items used in this research converged on the same latent construct and demonstrated internal consistency. In this study, Cronbach's α value was used to examine the consistency of the various facet items of the key elements of the RoHS process materials, which are summa23.

(31) rized in Table 4-1. Moreover, the discriminant analysis and correlation between constructs is presented in Table 4-2.. Table 4-1 Convergent validity and reliability measurement Constructs. Items. loadings. t-value. CR. Technology back- TB1. 0.934. 65.486. 0.968 0.864. 0.968. ground (TB). TB2. 0.931. 54.747. TB3. 0.940. 76.745. TB4. 0.950. 81.998. TB5. 0.932. 57.478. TB6. 0.887. 27.385. OB1. 0.800. 19.452. 0.875 0.657. 0.912. background (OB) OB2. 0.847. 21.792. OB3. 0.860. 23.611. OB4. 0.869. 32.852. OB5. 0.790. 19.732. OB6. 0.734. 13.995. OB7. 0.767. 12.564. EB1. 0.799. 21.267. 0.930 0.636. 0.812. background (EB) EB2. 0.794. 23.298. EB3. 0.827. 24.406. EB4. 0.771. 14.337. process RoHSA1. 0.901. 39.226. 0.901 0.753. 0.836. materials adoption RoHSA2. 0.832. 26.033. (RoHS_RMF). 0.869. 26.930. Organizational. Environmental. RoHS. RoHSA3. 24. AVE. Alpha.

(32) Table 4-2 Correlations between constructs (square root of AVE on diagonal) Constructs. TB. OB. EB. RoHS. Technology background (TB). 0.798. Organizational background (OB). 0.650 0.811. Environmental background (EB). 0.593 0.766 0.868. RoHS process materials adoption (RoHS_RMF). 0.465 0.708 0.639 0.929. 4.4 Structural Model Assessment Based the measurement model assessment, it offered evidence of reliability and validity, the structural model was then examined to evaluate the hypothesized relationships among the constructs in the proposed framework (Hair Jr, Hult, Ringle, & Sarstedt, 2016). In PLS-SEM method, the primary indicator for the assessment of the structural model is the variance explained. R2 values of 0.19, 0.33, or 0.67 for endogenous latent constructs of the structural model are illustrated as weak, moderate or substantial (Chin, 1998). As depicted in Table 4-3 and Figure 4-1, the model explains 62% of variance (R2) for RoHS adoption. As such, the proposed model can be assumed to sufficiently reflect the adoption of RoHS process materials by mobile phone manufacturers. To test whether path coefficients differ significantly from zero, t-values were calculated using bootstrapping. The non-parametric bootstrapping procedure was applied with 150 cases, 5000 subsamples and individual sign changes (Hair Jr et al., 2016). The analysis revealed that all of hypothesized relationships in the proposed model are statistically significant. Table 4-3 displays the results of the hypothesis testing. Hypothesis 1, which assumes direct positive rela25.

(33) tionship between technology background (TB) and RoHS process materials adoption (RoHS_RMF). ( b = 0.192,t = 1.993, p < 0.05) ,. has been verified. Or-. ganizational background (OB) has positive and significant impacts on HoRS process materials adoption (RoHS_RMF). ( b = 0.524,t = 5.264, p < 0.001) .. In. hypothesis 3, Environmental background (OB) has been demonstrated the positively significant influence on RoHS process materials adoption (RoHS_RMF). ( b = 0.163,t = 2.273, p < 0.05) .. Figure 4-1 Path relationship diagram. 26.

(34) Table 4-3 Result of hypothesis testing. Hypotheses. Path coefficients t-value Supported?. H1: TB ® RoHS_RMF. 0.192*. 1.993. Yes. H2: OB ® RoHS_RMF. 0.524***. 5.264. Yes. H3: EB ® RoHS_RMF. 0.163*. 2.273. Yes. Note: *Significant at p < 0.05. **Significant at p < 0.01. ***Significant at p < 0.001. 27.

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(36) Chapter 5 Discussion This research draws on a TOE theoretical framework to explore the adopting behavior in RoHS process materials by mobile phone manufacturers. The adopting behavior can be analyzed through three main constructs, including technological, organizational, and environmental backgrounds. To examine the potential relationships between these three main constructs and adopting behavior, PLS-SEM method is introduced to deal with such issue. After the empirical analyses by PLS-SEM, the results have been demonstrated the validity of proposed framework. In the following, the theoretical and managerial implications will be presented. This research contributes to a stream of TOE literature with empirical validation. A significant amount of past research has investigated the factors influencing sustainable manufacturing (Aboelmaged, 2018) and technology adoption (Ooi, Lee, Tan, Hew, & Hew, 2018; Tajudeen, Jaafar, & Ainin, 2018). Following the extant literature, this paper extends the generalizability of prior studies in TOE framework to investigate RoHS process materials adoption. First, according to empirical findings, organizational background (OB) construct was found to be a more important factor than technology background (TB) and environmental background (EB) factors in RoHS process materials adoption (RoHS_RMF). In path relationships confirmation, the path relationship between environmental background (EB) and RoHS process materials adoption (RoHS_RMF) has been confirmed the positive significance. Four items, comprising of pricing evaluation of competitive products, manufacturing cost, market analysis, and corporation goals, are used to measure the environmental background (EB). The path relationship (EB ® RoHS_RMF) result is con29.

(37) sistent with previous research in which the environmental background factors has a positive influence on technology adoption (Ghobakhloo, Hong, Sabouri, & Zulkifli, 2012). In the adoption of RoHS process materials, the environmental factors, such as pricing evaluation and manufacturing cost factors, always play a key role influencing the consideration of decision-making from top administrators. In addition, the environmental background (EB) has been verified the significance on various IT adoption issues (Ahani et al., 2017; Jia et al., 2017). Thus, the significance of environment background (EB) in the RoHS process materials adoption is emphasized. Second, technological background (TB) has been found the significance effect on adoption of RoHS process materials. This result is also line with the study by Chong and Chan (2012) who used TOE model to explore the technology adoption and has found that the technological background factor has a positive impact on technology adoption. The result also showed that firms should follow the rule of RoHS adoption in which the materials of Pb, Hg, and Cd need to be prohibited in the production process. Finally, this research provides empirical evidence that the organizational background (OB) is positively related to RoHS process materials adoption. The findings can be found in other technology adoption studies (Ahani et al., 2017; Oliveira, Thomas, & Espadanal, 2014). To measure organizational background (OB), seven items consisting of service life of equipment, maintenance of equipment, safety inspection, employee education, understanding of the international regulations, and follow the regulations of green production. Of these items, employee education has the highest loading values with 0.869. This implies that education for related RoHS adoption in production will be relatively important comparing to other items. 30.

(38) In sum, this research has offered the empirical evidence and validated framework to examine the relationships between three main constructs from TOE model and RoHS process materials adoption. Based on the research findings, technological, organizational and environmental backgrounds can positively affect the adoption of RoHS process materials. Comparing to previous research focusing on the information technology adoption, the proposed framework provides an insight where the process materials adoption by mobile phone firms is heighted. Such perspective to current theoretical model can offer a better understanding of process materials adoption in manufacturing industry.. 31.

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(40) Chapter 6 Conclusions This study aims at Taiwanese mobile phone manufacturers to sample the use of hazardous substances in mobile phone manufacturers. This study is mainly to analyze the key factors affecting the use of RoHS process technology for mobile phone electronics manufacturers based on the TOE model. By using three critical constructs, including "Technological context", Organizational context (Environmental context) and "Environment context", the potential influential relations can be hypothesized and further be confirmed with RoHS process materials adoption. In order to confirm these path relations and validate the proposed model, collected data are analyzed by PLS-SEM approach. This paper discusses the key factors affecting the process materials of mobile phone electronics manufacturers using RoHS, and use Smart PLS software as a tool for SEM analysis. The empirical model has been verified the effectiveness in this research and the proposed model explains the key factors affecting the process materials used by mobile phone electronics manufacturers to use RoHS based on good predicting rate of 62%. In addition, the path coefficient analysis significantly affects the key factors of mobile phone electronics manufacturers using RoHS process materials: the organizational background (5.264) is more significant followed by environmental background (2.273) and technological background (1.993). This result can also be used as a basis for future research on process materials using RoHS in mobile phone electronics manufacturers. In addition to above contributions, there are several limitations existing in this research. First, this study used TOE model based there main constructs to explore the adopting behavior of RoHS. In the future, related studies can further 33.

(41) extend TOE model by incorporating different constructs such as safety and privacy constructs. Second, the model does not explore the interference variables in the process materials used by mobile phone electronics manufacturers using RoHS, such as gender, age, and the company’s industry. Finally, this model needs to be further examined and validated in different countries and similar product production for the generalizability and robustness.. 34.

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(48) Appendix 影響手機電子廠商使用 RoHS 的製程材料關鍵因素問卷各位企業先進，您好本問卷主要是了解手機電子廠商使用 RoHS 的製程材料關鍵因素，希望藉由您寶貴的經驗，幫助我們從事此學術之研究。您所填寫的資料僅供本學術研究使用，絕不會對外公開，敬請安心填答。非常感謝您撥冗填寫此份問卷。敬祝身體健康萬事如意國立臺灣師範大學工業教育研究所科技應用管理碩士在職專班指導教授：郭金國博士研究生：吳志昭敬上. 第一部份：基本資料（僅作為本研究之用，絕不作其他用途）以下問題請您依據您個人的真實感覺在適當的內打勾，共 2 頁。性別： (1)  男 (2)  女年齡： (1)  18 ~ 30 歲 (2)  31 ~ 40 歲 (3)  41 ~ 50 歲 (4)  51 ~ 60 歲 (5)  60 歲以上貴公司所屬產業別：(1) 製造業 (2) 資訊業 (3) 金融業 (4) 塑膠業 (5) 化工業 (6) 光電業 (7) 其他業貴公司的員工人數：(1) 100 人以下 (2) 100~500 人 (3)501~1000 人 (4)  1001~5000 人 (5)  501~5001 人以上貴公司成立至今已幾年：(1) 10 年以下 (2) 11~20 年 (3)21~30 年 (4) 31~40 年 (5) 41~50 年 (6) 51 年以上請問您的工作部門：(1) 生產 (2) 銷售 (3) 研發 (4) 人事 (5) 財務 7. 請問您教育程度： (1) 高中職 (2) 大專院校 (3) 研究所(含)以上 8. 請問您的年薪收入大約：(1)  60 萬元以下 (2)  61~100 萬元 (3)  101~200 萬元 (4)  201 萬元以上 41.

(49) 第二部份:目前手機電子廠使用 RoHS 的製程材料包括: RoHS 的製程技術、. 1 公司能做到不含鉛(Pb)的材料生產技術. 非常非不不常同同普同同意意通意意 1 2 3 4 5. 2 公司能做到不含汞(Hg)的材料生產技術. 1 2 3 4 5. 3 公司能做到不含鎘(Cd))的材料生產技術. 1 2 3 4 5. 4 公司能做到不含六價鉻(Cr VI)的材料生產技術. 1 2 3 4 5. 5 公司能做不到含多溴聯苯 (PBB)的材料生產技術. 1 2 3 4 5. 您們公司認為 RoHS 製程材料產生效益的看法。 (技術背景). 6 公司能做到不含多溴二苯醚 (PBDE)的材料生產 1 2 3 4 5 技術您們公司採用 RoHS 製程時，所需投入各項準備程度的問項。 (組織背景) 1 我們的生產設備有使用期限的規範. 1 2 3 4 5. 2 我們的生產設備有定期保養. 1 2 3 4 5. 3 我們的生產設備有定期安全檢查. 1 2 3 4 5. 4 我們的生產線相關人員皆要接受各安全教育訓練 1 2 3 4 5 與講座 5 我們公司隨時掌握與了解國際公約規範. 1 2 3 4 5. 6 我們公司對於綠色製程理念相當認同. 1 2 3 4 5. 7 我們公司對環保規章相當重視. 1 2 3 4 5. 您們公司競爭對手及合作廠商採用 RoHS 製程的相關問項。 (環境背景) 1 競爭者的產品定價有做過評估報告. 1 2 3 4 5. 2 有系統的估算過公司的製造成本. 1 2 3 4 5. 3 有評估過企業的文化定位與目標需求. 1 2 3 4 5. 4 有做市場的問卷調查及需求評估. 1 2 3 4 5. 貴公司使用 RoHS 製程材料因素。 1 市場能提供符合 RoHS 規範材料. 1 2 3 4 5. 2 公司內部對綠色環保有一致性的共識. 1 2 3 4 5. 3 客戶對產品要求必需符合 RoHS 規範. 1 2 3 4 5. 原物料採購、生產製造安全、使用適應性、成本利益相關性等。. 作答完畢，請再檢查一次，是否每題皆有作答，感謝您！ 42.

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