Abstract
The worldwide machine tool market is anticipated to reach a value of USD 68.9 billion by 2021, from USD 65.6 billion in 2020. This projection is based on the progressive production drop within the car industry, which is the largest customer of machine devices, and supply chain disruption. The machine tool industry in Taiwan faces a severe challenge and has been unobtrusively experiencing an inner reshuffling and innovative transformation. The developing strategic alliances reflect a basic endeavor by numerous firms to improve their specialized capabilities. This study applied the DEMATEL, a suitable method for gathering group knowledge to form a structural model and visualize the casual relationship between subsystems through a casual diagram, revealing that the causal relationships between measurement criteria and the proposed model can provide a viable assessment of the alliance with satisfactory criteria that fit the decision-makers requirements, especially when the assessment criteria are various and interrelated. Financial resources were the strongest factor within the strategic behavior dimension (D1), whereas the minimize manufacturing cost was the foremost basic determinant in the cost perspective (D2). The specialists also demonstrated that obtaining dominant technology was a determinative component within organizational learning (D3). This paper offers proposals for government authorities to plan a machine tools industry strategy for Taiwan and for companies to formulate business directions for long-run advancement.
1. Introduction
Machine tools are utilized in numerous manufacturing industries, such as cars, aviation, hardware, and precision engineering. Persistent growth in these businesses, together with the investigation of modern oil and gas areas, is the essential driver for further development. In addition, the consolidation of three-dimensional (3D) printing innovation has recently helped to minimize the cost of materials used for creating these products. Furthermore, many manufacturers are devising innovative ways to deal with the predicted supply chain disturbance within the worldwide machine tools industry. The global machine tool market is dominated by exceedingly huge number of local and territorial players. The industry players are centering on promoting unused items as per the growing industry needs as a key procedure to reinforce their market impact and better serve the needs of shoppers.
Taiwan, the world’s fourth-largest machine tool exporter after Germany, Japan, and Italy, is becoming a major global player as its manufacturing capabilities are continuously progressing [1, 2]. Machine tools are the central apparatus for basic and accurate machining [3–6], especially for the aviation, defense, and vehicle industries, as well as for general equipment, metal machining, and electronics businesses. Machine tools not only create metal parts for industries, such as vehicles, aviation, defense, apparatus, molding, hardware, and generators, but they also produce common metal components for an assortment of equipment, and consequently, they are in some cases called the “Mother of Machines” [7–10]. Within the modern semiconductor and panel industries, machine tools play a crucial role in the business of components and consumables.
The broad utilization of machine devices is significant in the modern world. Taiwan traded USD 1.213 billion worth of machine apparatus within the first 4 months of 2011, which indicates a 59.9% year-on-year development according to the Taiwan Machine Device Establishment (TMTF). Of this total, metal-cutting machine instruments accounted for USD 980.35 million, up by 67.1%, and metal-forming machine apparatuses for USD 233.06 million, up by 35.3% [1, 11]. According to the Information Handling Office of the Taiwan Machine Device and Components Industry Affiliation (TMBA), the trade value of different industries in Taiwan, such as the machine device components, ordering heads or other machine device parts, metal-cutting instrument parts and accessories, metal-shaping machine device parts and accessories, ball screws, and ball or roller straight slides, from January to December 2019 was USD 1.391 billion, which declined by 27.7% from the same period of the previous year. Furthermore, compared with the third quarter of 2019, the fourth quarter of 2019 was down by 2.2% [1, 11].
Within the last few decades, there have been momentous changes in strategic alliance [12–14]. With progressively fierce worldwide competition, companies must research ways of reinforcing their competitiveness. A strategic alliance can involve great uncertainty and opportunities, requiring high capital expenditure for improvement through complicated innovation. With the ever-increasing speed of unions, there is now a need for a more efficient strategy to discover and assess the potential union partners [15–18]. Successfully building a strategic alliance requires an understanding of the basic variables for shaping coalitions [19, 20]. A comprehension of the issues related to unions will improve the efficiency of these organizations, providing a valuable method for selecting suitable key partners [12, 20, 21]. This paper employed the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to consider the key influencing factors in a strategic alliance pattern evaluation model for Taiwan’s machine tool industry. This work illustrates a decision-making strategy for selecting the most suitable partner organization [22, 23], proposing a novel hybrid strategy to manage the issue of different interdependence and input measurements within the strategic alliance pattern problem [24, 25]. This proposed hybrid strategy provides a much stronger understanding of the interrelationship among the assessment measurements and devises a method for collaboration on key design issues to improve the decision-making quality [26–30].
Initially, we present a multicriteria model comprising different measurements [31, 32]. The components that impact the strategic alliance design choice are so complicated that passive knowledge is more dependable than apparent information when making a choice [28, 29, 33–36]. This paper demonstrates an integrated multiple criteria decision-making (MCDM) technique that is more appropriate for national defense and forces budget planning. A DEMATEL method was employed to clarify the intertwined subcriteria interrelationships in the complex structural hierarchy of strategic alliance pattern strategy factors for Taiwan’s machine tool industry. A novel hybrid method was proposed to cope with the various interdependence and feedback dimensions’ problem in the strategic alliance pattern strategy factors for Taiwan’s machine tool industry, providing a better understanding of the interrelationship among the evaluation and selection dimensions and solving a complex interacting strategic alliance pattern strategy factors for Taiwan’s machine tool industry issue to enhance decision-making quality. The DEMATEL strategy adopts passive expert interviews and opinions [30, 37–39], employing fewer assets and centers on the driving figure within the framework and the development plan, thereby allowing selection of the ideal collaboration design. Considering the effect of a causal relationship can help to assess the significance of the influential factors more sensibly, and utilize fewer assets when understanding a complicated issue. Identifying causal connections between the impacting variables can give the organization the desired decision-making data [40–44]. Subsequently, we illustrate that the various DEMATEL criteria assessment methods are more effective than the conventional strategy, providing specialists with an important instrument [45–51].
This paper considers the strategic alliance pattern evaluation model for Taiwan’s machine tool industry and is organized as follows: Section 2 summarizes the assessment criteria for determining the strategic alliance pattern, Section 3 presents the DEMATEL technique, and Section 4 presents the questionnaire design, which incorporates the investigative system, analysis method, test results, and the observational findings. The concluding comments are given in Section 5.
2. Literature Review
With Asia being the world’s largest car-making region, the machine tool industry is anticipated to recover quickly with speculations in innovations, such as chip-making equipment expected to develop. The field is likely to see an increased demand for innovations with 5G communication and manufacturing advances. Issues with the materials supply have influenced machine instrument producers, with the major providers of machine components prioritizing large companies over SMEs during the recuperation. Taiwan is poised to become a greater worldwide player as its manufacturing capabilities become progressively modernized trading with nations such as China, India, Malaysia, Vietnam, and Turkey [1, 4, 52].
Due to the worldwide impact of the American financial crisis, the machine tool industry in Taiwan faces an exceptional challenge, thus it has been experiencing an inner reshuffling and mechanical transformation. As competition increases, the utilization of a predominant competition methodology is imperative for success. This paper presents an in-depth investigation of Taiwan’s machine tool industry after the financial emergency and provides a methodology for the industry to improve its competitive advantage with a solid competition technique and to increase profitability through differentiation within the postfinancial emergency period [53–55].
Fruitful commercial unions are a basic component of numerous businesses allowing firms to (1) overcome an asset limitation, (2) reduce exchange costs, (3) procure modern specialized and administration abilities, (4) construct client dependability by improving reputation, and (5) gain a competitive advantage and showcase this position. It is exceptionally difficult for machine tool companies to increase investment in R&D because they need adequate assets, such as capital, R&D faculties, and hardware [4, 17, 20]. Hence, forming commercial unions with other companies may be a viable way for them to obtain the essential strategies and help [13, 16]. Herein, we present a DEMATEL model to support key organization alliance decisions [56–59] to distinguish the persuasive components in a business union based on past research and to identify the research gaps.
Global automakers are running out of materials and are closing down; consequently, this year’s machine tool sales are expected to decline by more than 10% [1, 11]. The expanding number of business unions reflects a basic endeavor by firms to improve their specialized capabilities. This section examines the components utilized in previous assessment strategies, as well as the outcomes of this analysis. The following section recognizes the key strategic alliance pattern selection and identifies the research gaps.
2.1. Strategic Behavior Measurement
The rise of modern innovative divisions and the developing mechanical links are vital in business, so strategic behavior theory can be applied to this dimension. Strategic behavior has been formally modeled by game theory [60–63], typically postulating the rationality of players (i.e., participants to a strategic interaction), meaning that they act appropriately to obtain their goals and have consistent expectations of others’ behaviors [62, 63]. Strategic behavior involves decisions that consider the possible reactions of others. Economists have found that many examples of strategic behavior can be understood by relying on the core concepts of incentives and information. Behaving strategically means that each player must try to determine what the other player is likely to do. Rollback is crucial for strategic behavior, as thinking strategically means looking into the future to predict how others will behave, then using that information to make decisions. The emergence of new technology sectors and the growing technological convergence between sectors have also played an important role [64, 65]. Firms need to interact as they do not possess all the required and strategic alliances improve a firm's ability to obtain the necessary resources. Strategic behavior is evident in efforts to gain market power by blocking potential competition and discouraging the entry of other firms [60, 63]. Enterprises establish alliances for strategic objectives such as maximizing profit and possible cooperation, engaging in tactical practices including increasing the market share, having market access, redacting R&D time-span, and market defense [66, 67]. In addition, new firms and the older established firms develop a symbiotic relationship as suppliers and buyers when it is mutually beneficial. A strategic alliance as a strategy is viewed from the perspective of reduction of a firm’s risk exposure in terms of environmental uncertainty [66, 67]. The high-technology new firms have extensively used strategic alliances to gain access to knowledge, resources, and capabilities such as human and financial resources [62–64], combining these assets and capabilities to form and keep up the competition, thus maximizing the benefits [65, 66]. Firms ought to form alliances because a single firm cannot have all the required assets, and strategic alliances increase their capacity to obtain such assets.
2.2. Corporate Reputation
Taiwan’s machine tool industry comprises corporate brands even though the local market is relatively small. Strategic alliances, such as cooperation with major international manufacturers, to promote Taiwan’s machine tool brands internationally will promote the competitiveness of the industry [4, 5]. However, entering a new market is an expensive and time-consuming process [3], but forming strategic alliances with an established company with a good reputation can help create a favorable brand image and efficient distribution networks. Even established reputable companies need to introduce new brands to the market [63, 64]. The opportunity to grow market size with a partnership presents the opportunity to increase brand awareness, a key element of business success [65, 66]. Most firms are competent in some areas and lack expertise in other areas, so strategic alliances allow ready access to their lacking knowledge and expertise, which can be also used for other projects and purposes. Since a learning organization is a growing organization, a strategic alliance can improve the alliances’ performance. Nonetheless, the direct effect is not clearly explained by the existing theory, thus future research is required to investigate this relationship [65–67]. When a partner meets the positive expectations of the other party due to its corporate reputation, it reduces the perceived relational risk, generating trust that the partner will not act opportunistically. Corporate reputation has recently become of significant interest for financiers [67], as it is a vital intangible resource that empowers firms to establish client connections [68, 69]. Corporate reputation influences whether clients choose to purchase services when they cannot survey the quality before buying, thus it is vital for companies with overwhelmingly intangible assets [70, 71]. A great reputation is expected to lead to better representative recruitment/retention, more favorable assessment by reviewers and the media, superior connections with controlling offices, effective bartering apparatus with source/vendor/partner/distributor systems, and a more saleable brand [71].
2.3. Market Expansion
Taiwan’s high-tech products and equipment have a very important position in the global market [11], with Taiwan’s machine tool equipment ranking fourth in the world. However, this industry faces fierce competition from global competitors. As the machine tool equipment market expands, the global competitiveness of Taiwan’s machine tool industry can be maintained and enhanced. Entering foreign markets confers benefits such as economies of scale and scope in marketing and distribution [62, 63], but the cost of entering an international market may be beyond the capabilities of a single firm; hence, a strategic alliance with an international firm will benefit a rapid entry while keeping costs down. Choosing a strategic partnership as the entry mode may overcome the remaining obstacles, which could include entrenched competition and hostile government regulations [69]. Entering a strategic alliance will automatically increase brand awareness in an entirely new market that the franchise business has not had the resources to reach beforehand. In most cases of franchising alliances, a partner will be a business that offers a completely different set of services to a market that is similar to its own, allowing the business to increase its market size with little impact on the franchise business. A strategic alliance gives access to new markets that would not have been possible for either company alone [70, 71], for instance, companies going global often work with a trusted local partner to get an advantage in an emerging market. A strategic alliance should combine the best both companies have to offer, which can be a deeper understanding of the product, sales, or marketing knowledge, or even just more hands on deck to increase the speed to market. The market development stage is the period when a company surveys the current markets and market share [72, 73] and requires gauging the modern delivery capabilities in the current markets, as well as the potential unexploited markets for existing items. These assessments incorporate elective businesses and geographic regions. Moreover, market expansion distinguishes between elective innovation and extra employments for items, determines any changes within the market conditions, and measures the relative costs for diversifying into the target markets [48, 74].
2.4. Financial Resources
High-tech industries and equipment research and development require numerous resources [7, 8], of which, financial resources are key. If Taiwan’s machine tool industry wants to maintain competitiveness in the global market as well as high-quality products, rapid access to the global market is key, so finding a suitable partner to share the financial resources is important [9, 10]. Hence, financial resources are a common rationale for undertaking a cooperative arrangement. Indeed, when a market has opened up, or there is much uncertainty and instability in a particular market, sharing risks becomes particularly important [72, 73]. The competitive nature of businesses makes it difficult for a business to enter a new market or launch a new product, so forming a strategic alliance can reduce or control the risks. Capital markets do not often provide funds to those firms which are involved in new but risky projects [74], as the banker has limited control over the borrower's activity if there is insufficient collateral. However, other firms which appreciate the value of these risky projects may not be restrained in the same way. Consequently, collaborative arrangements in which one partner provides financial resources to another partner are common [75–77]. Strategic alliances are voluntary cooperative interfirm agreements for competitive advantage for the partners, that is, firms attempt to find the optimal resource boundary through which the value of their resources is better realized than through other resource combinations. The difference between the two perspectives is sometimes reflected in the competing research hypotheses derived from the two theories. For example, transaction-cost theorists suggest that whether or not partner firms are in the same industry will affect the choice of joint venture or acquisition. Strategic alliances allow access to other firms’ resources to garner otherwise unavailable competitive advantages and values to the firm [72–74]. Firms may use alliances or mergers/acquisitions to obtain valuable resources that are essential for competitive advantage. In the international arena, multinational companies may enter foreign markets by acquiring a local company, also seeking their resources, such as local facilities, knowledge, and connections, by forming strategic alliances [74]. Financial assets refer to how a business/company is financed, and monetary assets are money reserves that fill the shortage arising from the timing gap between a company’s cash receipts and cash payments [75, 76]. They are provided by various speculators (shareholders, banks, and/or obligation holders) in exchange for compensation (profits, interface, and/or capital gains) [77, 78].
2.5. Cost Perspective on Strategic Alliances
Another reason for forming alliances is to decrease costs, permitting firms to realize ideal decision-making with lower costs. Transaction cost theory can be applied to this dimension which is overall probably the most used theoretical underpinning [79–82]. Firms will choose transactions that economize coordination costs. As information and communication technology continues rapid cost-performance improvement, the unit cost of coordinating transactions will approach zero, thus enabling the design of innovative coordination transactions to fit new business needs. This refers to the transaction cost paid by the buyer involved in the transaction [79, 80]. The perceived costs of developing collaborative relationships go beyond those associated with developing and implementing contractual relationships [82, 83], affecting partner evaluation in relational exchanges because they are temporal. The cost concept comes from the cost-benefit pattern based on behavioral decision theory [84, 85], and the cost-benefit pattern illustrates that an individual’s behavior is influenced by their perception. The perceived ease of use and perceived usefulness could be regarded as benefits, while perceived cost and perceived risk are perceived as costs. In choosing a mobile payment system for small payments, the cost includes the transaction price, registration fee, or cost for a new device if one is needed to use the system, as well as the health hazards [82–85]. Firms are combined to oversee and minimize their costs and/or dangers. Strategic alliances of this sort are an approach for adjusting to a dubious environment—an internal tool by which the firm minimizes its exposure to cost vulnerabilities, increases sales, shares the cost of innovation, and avoids repeating mistakes. This can diminish the production costs and advertising costs, thereby reducing administration costs.
2.6. Minimize R&D Cost
High-tech research and development are costly involving labor and time costs [4–6]. In the current rapidly changing and highly competitive global machine tool industry, how to share resources, thereby reducing research and development costs for innovative and creative machine tool products to rapidly enter the market is an important consideration for industry experts. Strategic alliances are developed and propagated as formalized interorganizational relationships, particularly among companies in international business systems. Partners may not have sufficient R&D resources to cover the costs [79, 80]. More importantly, unexpected accounting costs may increase substantially in dynamic environments due to the high unpredictability and velocity, and sourcing from partners is an effective way to manage such sharp cost fluctuations. Sourcing cash from partners, for example, is a frequently used option for firms in high-tech industries [81, 82]. As accounting costs are specified in numbers, both parties’ responsibilities and obligations in sharing these costs can be precisely defined in partnership contracts, that is, transaction costs for such sharing are minimal. Strategic alliances are becoming an important form of business activity in many industries, particularly as companies are competing in a global field. Strategic alliances are not a panacea for every company and situation [82–84]; however, they can help companies to improve their competitive positioning, gain entry to new markets, supplement critical skills, and share the risk and cost of major development projects. Strategic alliances are agreements between two or more independent companies to cooperate in the manufacturing, development, or sale of products and services, or other business objectives [85]. Research and development costs refer to the spending required to create an innovative product [86, 87]. This incorporates the investigation stage that decides the practicality of the venture and the strategies for continuing, as well as all the planning and production stages required to provide a working item. The R&D costs require finding up-to-date information and incorporating it into a plan for a modern item and are more often investigated than spent in reality [88]. However, two classes of costs are important in R&D exercises and are capitalized: (1) materials and hardware and (2) funding acquired from others [89, 90].
2.7. Minimize Manufacturing Cost
The production and manufacturing of machine tools require manpower and land costs [5, 6], thus, Taiwan’s machine tool industry is actively looking for partners to increase the scale of production, thereby reducing production costs and gaining a competitive market advantage. Therefore, reducing production costs is an important consideration for the machine tool industry. Williamson [79] refers to this as asset specificity, meaning that assets can be highly specific for a transaction, leading to higher transaction costs. Distribution agreements can force a similar situation, as certain industries are connected to high economies of scale leading to fewer potential distributors. The trade of knowledge can also be impaired by transaction costs, due to the buyer’s uncertainty regarding the nature of knowledge. General manufacturing costs are different from firm-specific costs [82–84]. Environmental dynamism provides a flow of opportunities that typically is fast, complex, ambiguous, and unpredictable. Firms may not have sufficient general resources under their direct control to exploit these opportunities. Direct control over abundant general resources results in inflexibility which makes firms inefficient to manage the complexities and ambiguity. Strategic alliances enable these firms to access external general resources. Through joint ventures in foreign countries, for example, partners can access local production infrastructure and low-cost labor [88–90]. Sharing general resources rather than owning them provides important strategic benefits, such as loose coupling, ambidexterity, and improvisation, which increase firms’ learning speed and responsiveness to manage environmental dynamism. More importantly, sharing general resources reduces investment manufacturing costs, the total assets that are specifically utilized for preparing a product. In some equations, the manufacturing cost incorporates the costs related to buying raw materials, as well as labor costs, equipment operation, and the common overheads for running the production office [91, 92].
2.8. Minimize Marketing Cost
The machine tool industry is a B to B industry structure. When the machine tool industry wants to invest overseas and form strategic alliances, it must find a partner with a high corporate brand value. The high-quality products combined with the high brand equity of partners will accelerate the entry of Taiwan’s machine tool industry into the international market. Interfirm cooperative agreements are broadly defined as explicit interactions between two or more firms, such as the autonomy and identity of the parties are, at least, partly preserved [92, 93]. Thus, they differ from mergers, acquisitions, and other integration operations, nevertheless, they represent a means of achieving external growth based on the development of a new product or process technology and/or the commercialization of a new market [94]. Transaction cost theory deals with the question of economic organization by focusing on the transaction as the unit of analysis: “A transaction occurs when a good or service is transferred across a technologically separable interface. One stage of activity terminates and another begins” [79]. The theory postulates that particular forms of economic organization will result from the attempt to reduce transaction costs and refers to these forms of economic organization as governance structures. To better understand transaction cost theory in regards to alliance formation, it is important to understand the transaction costs in environments that could favor alliance formation [92]. The full marketing cost is related to conveying the product or service to clients [93, 94]. The marketing cost may combine costs related to trading the title of items to a client, putting stock in delivery centers pending movement, promoting the stock or brands being sold, or distributing them to outlets [95].
2.9. Organizational Learning Perspective on Strategic Alliances
Organizational learning alludes to “the natural change mechanism for accomplishing the particular objectives of an organization” [12, 14]. Learning the most current information and innovation is the fourth measurement for setting up a strategic alliance, and organizational learning theory can be applied to this dimension. Organizational learning theory is concerned with how learning takes place in organizations. It focuses on collective learning but takes into account the proposition that organizations do not perform the actions that produce the learning, rather individual members of the organization behave in ways that lead to it, although organizations can create conditions that facilitate such learning [96, 97]. The concept of organizational learning recognizes that this is affected by the context of the organization and its culture and is concerned with the development of new knowledge or insights that have the potential to influence behavior. It has been defined as a process of “Coordinated systems change, with mechanisms built-in for individuals and groups to access, build and use organizational memory, structure and culture to develop long-term organizational capacity” [98, 99]. Organizational learning takes place within the wide institutional context of interorganizational relationships and “refers broadly to an organization’s acquisition of understanding, know-how, techniques, and practices of any kind and by any means” [100, 101]. The theory of organizational learning focuses on the creation of knowledge and the use of that knowledge within an organization. Key aspects of organizational learning theory are that learning happens when people interact while identifying and solving problems [100, 102].
Organizational learning is a buzzword used to describe the process of transferring knowledge within an organization [98]. As the business gains experience, it should improve over time, creating a broad base of knowledge and covering all topics that could improve the business. Obviously, this is the smallest learning community—a community of just one. When an individual worker learns new skills or ideas, productivity and performance generally improve [100]. To maximize the benefit of this individual learning to the organization, the worker who learns the new skill must share it with coworkers [101, 102], otherwise, that skill leaves with the worker [99–102]. From the point of view of organizational learning theory, within the information economy and mechanical expansion, companies must build up an information base. Subsequently, the goal of organizational learning methodology unions is to memorize important knowledge and abilities of the organizations through participation to set up their genuine center capabilities and esteem creation strategies. The workforce can learn from the partner by conducting joint mechanical improvement, a common learning strategy for an organization. Acquiring the most recent innovation alludes to the abilities learned and innovation procured by the central firm from a partner [15, 16]. Product patent is an exclusive business model that a government offers a creator for a constrained period. To secure the assets vital for survival and to gain a competitive advantage, firms seek product patents to distinguish themselves from the environment and other firms. The final category incorporates ideas related to speeding up development using other companies’ assets and improving production mechanisms [17, 19].
Organizational learning is important for all companies, as the creation, retention, and transfer of knowledge within the organization will strengthen the organization as a whole [97, 98]. The theory of organizational learning focuses on the creation of knowledge and the use of that knowledge within an organization. An organization that embraces the lessons that can be learned from failure and study its processes contains more knowledge about best practices and will be much more able to adapt. Huber (1991) identifies four organizational learning processes: (1) obtain knowledge and technology; (2) distribution of information and management system; (3) information interpretation, and (4) organizational memory, as the process of information sharing, is the transition from the individual to the collective level, building organizational memory [100]. The processes of organizational learning involve knowledge acquisition, creation, refinement, storage, transfer, sharing, and utilization. The organizational learning function in the organization operates these processes, develops methodologies and systems to support them, and motivates people to participate in them. The goals of organizational learning are the leveraging and improvement of the organization’s knowledge assets to effectuate better management knowledge practices, improved organizational behaviors, better decisions, and improved organizational performance.
2.10. Obtain Dominant Technology
In the machine tool industry, the acquisition of key technologies is very important, so strategic alliance partners with such technologies should be identified to allow Taiwanese machine tool companies to quickly enter overseas markets [8, 9]. Organizational learning includes creating, retaining, and transferring knowledge and has implications for the performance and competitiveness of organizations. Organizational learning and knowledge management innovation are context-specific, influencing SMEs’ technological capability effectively [101, 102]. The effects of organizational learning were not only curvilinear but also differential across management system innovation adoption and implementation. While organizational learning from external noncompeting suppliers such as consultancies has been studied (Gaimon et al. 2017), future research is needed to link member/task networks in emerging phenomena such as crowdsourcing where organizations outsource their tasks to external entities or individuals for activities such as idea generation. Property-based resources are legal properties owned by firms, including financial capital, physical resources, and human resources [98, 99]. Owners enjoy clear property rights to these resources, or rights to use the resources, so that they cannot be taken away without the owners’ consent. Thus, property-based resources cannot be easily obtained because they are legally protected through property rights in such forms as patents, contracts, and deeds of ownership [101]. Since others cannot take property-based resources away, alliance partners will not be overly concerned about unintended transfers of these resources. With the right alliance, partners can outpace the competition with new solutions that are a complete package for their customers. These alliances are creative and revolutionary, dramatically changing the market landscape. Moreover, new social media technologies provide organizations the opportunities to obtain external feedback for improving existing products and services as well as introducing new ones. Obtaining and adapting to new dominant technology is more challenging for established organizations because of the relative rigidities of routines and tools [102]. As imaging transitioned from analog to digital in the 1990s, Polaroid kept up with the new technologies to develop digital imaging. However, outdated beliefs at the individual and team levels created organizational inertia that inhibited Polaroid from successfully adapting these new dominant technologies. The definition of a dominant technology has advanced from being a broad and conceivably redundant term to one that is more specific so that a dominant technology is considered prevailing when more than 50% of the products in an item category utilize the innovation [103, 104]. By including “in an item category,” the definition avoids the possibility that diverse prevailing plans arise from totally different item categories or specialties at the same time. Furthermore, no distinction will be made between locally or universally dominant designs [105, 106]. Partners may share property-based and knowledge-based resources through licensing/franchising, joint ventures, or R&D consortia [104].
2.11. Obtain Patent Protection
In the machine tool industry development, the acquisition of key technologies is very important, but at the same time, it is necessary to find a partner who is willing to protect the common intellectual property rights [6]. This is also an important consideration for overseas investment in the machine tool industry that requires substantial intellectual property rights. If Taiwan’s machine tool industry wants to enter the overseas market, it needs to cooperate with companies that own intellectual property rights. Our conceptual framework also combines organizational learning theory and patent protection, allowing us to integrate insights from prior research to identify opportunities for action that social media may provide for organizational learning and to develop an understanding of how patent protection allows organizations to learn for and from each other, drawing upon open resources and processes and opening effects. Innovation opportunities can be leveraged if they are supported by effective patenting strategies, balancing protection, and disclosure [107]. Not everything that can be protected should be, and patents can and should foster rather than hinder collaboration. To identify attractive opportunities, organizations must systematically manage their explicit and implicit knowledge assets, finding ways to share, combine, disseminate, and maintain this unique type of capital. Jeon (2019) shows that patent protection is optimal under symmetric information, whereas this is not so if the licensor has private information. Furthermore, social welfare under asymmetric information is higher than that under symmetric information for most patent protection levels, yet the latter dominates the former in the presence of an optimal policy for each regime. We think that patent protection is optimal under symmetric cooperation, whereas this is not so in the presence of information asymmetry [108, 109]. Since firms get a free ride on the innovation led by the upstream firm, the government should apportion the surplus to the innovator by protecting patent rights [107, 108]. A patent is a form of possession that an innovator may be given for an innovation or product [107–110]. Comparable to a trademark or copyright, a patent can include intellectual property possession; however, patent protection can be more troublesome to obtain and maintain. Unlike copyrights, which are set up the moment an individual creates a unique work, a patent must be formally recorded with a nation’s government [111, 112]. Each nation has distinct arrangements and methods regarding licenses, and a creator must get a patent and ensure patent security in numerous nations independently. Patent security is the legitimate security granted to the proprietor of a patent over their intellectual property and the strategies by which they can seek redress against somebody who encroaches upon the patent [113, 114]. This sort of security ordinarily depends on the nation in which an individual possesses a patent and how somebody can bring legal action against a company or individual who abuses their patent [108].
2.12. Improve Management System
Organizational learning is defined as “the process of change in individual and shared thought and action, which is affected by and embedded in the institutions of the organization.” [109, 110]. Organizational learning theory emphasizes the continuous process of change that enables an organization to thrive and adapt to its environment. This process is strategic in that it spans not only the individuals and groups within an organization but also the organizational management system as a whole [111, 112]. The management system involves the planning, organizing, motivating, and controlling of people, processes, and systems in the organization to ensure that its knowledge-related assets are improved and effectively employed. There are various ways to conceptualize the relationship between the management system and organizational learning [112–114]. The management system may be conducted across multiple organizations, such as with suppliers, partners, and customers, especially for the machine tool industry. Such management system activities rely on communications networks and systems and aim to improve knowledge, knowledge-related practices, organizational behaviors and decisions, and organizational performance. Management system focuses on knowledge processes, such as knowledge creation, acquisition, refinement, storage, transfer, sharing, and utilization, that support organizational processes involving innovation, individual learning, collective learning, and collaborative decision-making [115, 116]. When confronted with reductions in financing, rising costs, global competition for restricted assets, and a demand for higher-quality results, organizations are under pressure to function more successfully [115, 116].
Since the strategic alliance pattern is generally unknown outside firms and reserves are not adequate for workshops, we utilized semistructured interviews with specialists to decide the basic system for the survey [117–119]. The machine tool market will see an increase in automation and remote operation through the Internet of Things (IoT) development. Machine checking frameworks will be set up to permit the checking of inaccessible CNC machines. From the literature review, we collected usable measurements and criteria to be utilized when assessing and selecting a key collaboration design for the Taiwanese machine tool industry. We then interviewed specialists to screen the reasonable measurements and criteria based on the literature review [57, 120] and summarized these to build an assessment with 4 measurements and 14 criteria [121–123].
Four experts were interviewed, specialists in the machine tool industry and an academic in the mechanical research field, who were knowledgeable about the machine instrument industry and are specifically or by implication included in the machine tool industry (see Table 1). The interviews were conducted in their workplaces in Taichung City and Changhua City in Taiwan.
The following sections provide information regarding the specialists and their organizations and summarize and classify the experts’ opinions into four categories for the ensuing survey. In addition to developing the survey, the specialists provided their professional information and involvement in strategic alliances, as well as a mechanical point of view.
After meeting the specialists and investigating the literature, a system was developed including three measurements and 12 assessment criteria as shown in Figure 1. The aforementioned theoretical models contributed to our understanding of the evaluation of the strategic alliance pattern evaluation model. These studies examined a set of potentially relevant factors based on the past literature and discuss the gaps to recall knowledge and open a discussion. This presentation is based on a report distributed to the experts before the interview. We wanted the experts to have a common understanding of the results before evaluating the wealth management bank. This analysis was conducted asynchronously with the experts, and empirical data were collected from several key experts in different industries.
The evaluation model contributes to our understanding of strategic alliance patterns, with a set of possibly pertinent variables for strategic alliance pattern choice. We present a multicriteria model comprising the preferences of various dimensions, then introduce a tool, DEMATEL, to analyze the critical factors in a strategic alliance pattern evaluation model for Taiwan’s machine tool industry. The judgment of decision-makers is often given as set values, which is an inadequate reflection of the vagueness in the real world; hence, DEMATEL was applied to address this issue. This study regards the evaluation index system for strategic alliance pattern evaluation model for Taiwan’s machine tool industry as a system that includes causal relationships between the influencing factors, which is a new way to solve that problem. First, the factors that influence the strategic alliance pattern evaluation model for Taiwan’s machine tool industry are so complicated that recessive knowledge is more reliable than evident knowledge to make a decision. The DEMATEL methodology can exploit recessive knowledge, such as expert experiences and instincts, using the least resource devotion and focusing on the core driving factor in the system and the improvement direction, on which we can choose the optimal strategic alliance pattern evaluation model. Considering the impact of a causal relationship can more reasonably assess the importance of influencing factors and use the least resource devotion to solve a complicated problem when there are causal relationships between the influencing factors, which effectively and accurately provides the organization with the required decision-making information. In addition, it is apparent that there is a research gap regarding the multicriteria investigation of strategic alliance pattern design determination and in creating an understanding of the cause/effect relationship of complex social science issues.
The DEMATEL information analysis method was used to effectively integrate the knowledge of experts and help to develop a strategy by directly comparing the interrelationships of the key factors. The relations and the strength of influence among the key factors were obtained from the complex problems. DEMATEL turned the relations among the criteria into a clear structural model and dealt with a series of interrelations among the criteria. This paper discusses the key strategic alliance pattern evaluation factors; however, due to the high complexity and the interrelations in the numerous factors with limited resources, we had to allocate resources to the most critical key factors. This was in line with the DEMATEL characteristics; therefore, this analysis method was adopted to achieve the study goal.
3. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) Method
DEMATEL helped to develop a strategy by directly comparing the interrelationships of the key factors from the problem. The relations and the strength of influence among the key factors were obtained from the complex problems. DEMATEL turned the relations among the criteria into a clear structural model and dealt with a series of interrelations among the criteria. This paper discusses the strategic alliance pattern strategy factors for Taiwan’s machine tool industry. However, because of the high complexity and the interrelations in the numerous factors, with limited resources, we had to allocate resources to the most critical key factors. All of the above was in line with the DEMATEL characteristics. Therefore, we adopted this analysis method to achieve the goal of this study. We outline this novel crossover assessment to prepare an observational case study of the Taiwanese machine tool industry. There are four steps required in this procedure. The primary step is to build the assessment based on Section 2’s literature review and the expert interviews from Section 3.
We obtained three measurements and nine criteria appropriate for the assessment of a key collaboration design for the Taiwanese machine tool industry. The following step is to recognize the interrelationships among the measurements within the assessment, by applying the DEMATEL strategy. DEMATEL has been adopted in numerous scholarly fields, such as industrial research. The numerical concepts are borrowed from Liou et al. [37] and Wu [41]. The DEMATEL procedure is described as follows:(1)Define the quality factor characteristics and establish an evaluation scale. The assessment scale for causal relations is built and a pairwise comparison of the quality variables is conducted [41, 42, 124]. We referred to the scale proposed by Chang et al. [124] and Büyüközkan et al. [13], and employed 0, 1, 2, 3, and 4 as the five levels of estimation.(2)Obtain interdependent data for all factors using the expert opinion method. The pairwise comparisons between any two components are conducted, given as scores of 0 to 4, meaning “No influence (0),” “Low influence (1),” “Medium influence (2),” “High influence (3),” and “Very high influence (4)” [125, 126].(3)Calculate the arithmetic mean matrix. Assume that the number of factors is , and the value is from professionals who judge the factors based on the 0, 1, 2, 3, and 4 five-level evaluation scale: and (i = 1, 2, 3,…, n; j = 1, 2, 3,…, n) represent the influence degree of factor on factor . Then, sum up and average all from experts [126]. The formula is given as follows to calculate the arithmetic mean matrix.(4)Analyze the consistency. The purpose of this study is to make the expert questionnaire highly valid. This step mainly checks that the expert questionnaire is consistent. We applied Tsai et al.’s [127] research to analyze the consistency of expert questionnaires. Tsai et al. [127] mentioned that the consistency ratio is less than the significance level—the threshold is generally set to α = 5%. We also adopted the Tsai et al. [127] research equation to calculate the average gap ratio in consensus (%) is following equation: where represents the number of criteria and represents the number of experts.(5)Calculate the causal matrix. The causal connection network and the total-relation lattice outline the interrelated effect in each calculation; the equation is shown below [128–130]. The normalized direct-relation lattice can be obtained as .(6)Utilize the causal matrix. Let , the quality of the given y, be calculated for the direct/indirect network , and i, j = 1, 2,…, n [56]. Combine these columns with the columns of the direct/indirect matrix (T); the equation is given as follows. This incorporates the direct and indirect effect, which is the degree of the direct and indirect effect on the other variables. Once the normalized direct-relation is obtained, the total-relation matrix can be calculated, where it ought to be guaranteed that the convergence of . The total-relation lattice is shown as equations (3) and (4) [128–130].(7)Causal diagram.
The causal graph is delineated in a two-dimensional design, where the full is the horizontal axis, and the contrasting is the vertical axis. This representation can rearrange the complex causal relation into an effective visual structure, which helps us easily understand the issues [115]. When is positive and found above the x hub, the quality calculation m is placed as a type of cause, but in case is negative and found below the x axis, the quality figure is regarded as a result [128–130].
This paper identified and analyzed the critical strategic alliance pattern evaluation factors. A DEMATEL method was applied to analyze and classify these factors to help decision-makers to explore the causal relationships among the identified factors. DEMATEL designs and arranges the structural model of a system with expert knowledge and is a rigorous tool to describe the structures of complex relations. This method will determine the interactions between factors according to their specific characteristics and transform the causality of the factors into a systematic structural model. An empirical study is presented to illustrate how strategic alliance pattern evaluation was applied to enhance their advantage in the following section.
4. Empirical Results and Discussions
European, American, Japanese, and South Korean car manufacturing plants have ceased work due to a lack of car components. The demand equipment is not me. In particular, the trade of the machine tools industry was seriously harmed in the first half of this year. The development of machine apparatus sales this year is weak, being perhaps 10% to 15% lower than last year. As expressed previously, the aim of this study was to determine the factors influencing to the Taiwanese machine tools industry. Based on the experts’ comments made, we created an ideal strategic alliance design based on the hybrid MCDM, to indicate the connections between the assessment criteria, and to define a methodology for selecting organizations to collaborate with. This research topic is a complex and multifactor theme. Therefore, this research not only read traditional literature reviews to understand the strategic alliances factors but also applies the expert interview method. The expert interview method and the literature discussion are integrated into a strategic alliance evaluation framework. Then we continue to apply the DEMATEL expert questionnaire method which solve and analyze complex expert ideas. The research method of this article will continue to apply the DEMATEL research method, and the expert's ideas can be deduced by scientific methods and mathematical models to obtain highly valuable and constructive research conclusions.
This article presents a framework strategy for supporting choices that concern strategic alliances in Taiwan’s machine tool industry. To structure and establish the parameters of this framework, the expert information from individuals is required. This research is extremely professional and complex. Therefore, this research invites highly professional and practical-experience persons to participate in this research. After obtaining the raw data for this research, careful mathematical derivation and calculation are required to obtain the most accurate research results. It takes a lot of time for the research data to be obtained until the research is published. The research data are absolutely credible and correct. This proposed strategy can provide an improved understanding of the interrelationship among the assessment and determination measurements and reveal a complex connection between the factors in collaboration choice, which can upgrade the quality of decision-making.
4.1. Research Data Validation and Robustness
We construct the assessment model using the literature review and interviews with specialists. In order to determine the suitable dimensions and criteria for each dimension, this research interviewed experts to screen for the suitable dimensions and criteria based on our literature review. This research then summarized and constructed an evaluation model with three dimensions and nine criteria that are most suitable. In the sections that follow, this paper describes the organizations where experts are working and the interview themes that provide basic information, summarizes the experts’ main opinions about all themes and then classifies these opinions into three categories that can be adopted as the structural framework for the subsequent questionnaire. In addition to replying to the questionnaire in constructing this evaluation and selection model, the experts also provided their professional knowledge and experience. We interviewed these experts in their offices rather than off-site in Taichung City and Changhua City in Taiwan. The research questionnaire was validated through a survey of 21 respondents. These respondents comprised academic researchers, including professors, industrial experts based in Taiwan. They validated the survey questions and proposed changes in case of ambiguities—this ensured clarity of communication and logic. Furthermore, the content validity and the construct validity for the survey questions were ensured. The internal consistency of the data was assessed using the Cronbach’s alpha test, where for checking the reliability of the questionnaire, the value of alpha greater than 0.7 are acceptable. Cronbach’s alpha value was calculated to determine the internal consistency between the respondent’s opinions related to the influence of criteria on each other. The Cronbach’s alpha value was determined to be 0.793, which is well above the acceptable limits of 0.7. This verifies the consistency and hence the reliability of the data for the analyses conducted in this study.
The research also applied Tsai et al. [127] research to analyze the consistency of expert questionnaires. Tsai et al. [127] mentioned that the consistency ratio is less than the significance level—the threshold is generally set to α = 5% [127]. The consistency threshold was set to 0.05; values smaller than 0.05 indicate response consistency. The results showed that the overall value was 0.006093. The values of strategic behavior dimension, cost dimension, and organizational learning dimension were 0.005982541, 0.005619726, and 0.005619726, respectively. All values were smaller than the threshold, indicating that the responses were consistent [127].
The observational data were collected in the spring of 2012 using a survey, which was conducted following the expert interviews. The survey was sent to 30 experts. Nine respondents did not complete the survey not completely, and thus, their responses were not utilized. The assessment of utilizing the DEMATEL strategy was based on these 21 experts’ conclusions. As there were three measurements, the 13 3 × 3 matrix is as follows:
We then conducted a collected pairwise comparison and produced the preparatory normal causal matrix.
On the premise of the causal matrix, we obtained the normal causal matrix:
Once the normalized direct-relation was obtained, the total-relation network was calculated.
We then created the causal graph, as shown in Figure 2. Table 2 presents the direct and indirect impacts of three first-level measurements. The digraph of these three measurements is delineated in Figure 2. Table 2 shows that strategic behavior and organizational learning were the net causes, while the cost measurement was the net effect, according to the values. From Figure 2, it is obvious that the organizational learning measurement is the foremost basic measurement. In addition, the cost measurement was influenced by itself, as well as by strategic behavior and organizational learning.
Table 3 summarizes both the direct and the indirect impacts of the criteria for the three diverse measurements. The causal connections among the three second-level criteria of the strategic behavior measurement are delineated in Figure 3. Figure 4 shows the causal connections among the three second-level criteria of the cost measurement. The causal connections among the three second-level organizational learning measurement criteria are presented in Figure 5.
Figure 3 indicates that financial resources were the net cause, while corporate reputation and market expansion were the net effects, according to the values. From Figure 3, it is evident that financial resources is the foremost basic model. In addition, corporate reputation and market expansion were influenced by financial resources.
Figure 4 delineates that the criteria of minimize R&D cost and minimize manufacturing cost were the net causes, while minimize marketing cost was the net effect, based on the values. From Figure 4, it is evident that minimize manufacturing cost is the foremost basic cause. In addition, minimize marketing cost was influenced by the criteria of minimize R&D cost and minimize manufacturing cost.
Figure 5 portrays that obtain dominant technology and improve management system were the net causes, while obtain patent protection was the net effect, according to the values. From Figure 5, it is obvious that obtain dominant technology is foremost basic cause. Additionally, obtain patent protection was influenced by obtain dominant technology and improve management system.
In this experimental study, we attempted to identify the major components of strategic alliance pattern determination. We utilized the Taiwanese machine tool industry as our case study. On the premise of the observational findings, we concluded the taking after with a few administrative implications. The experts believed that financial resources was the strongest factor in the strategic alliance design determination within the strategic behavior measurement (D1). In the cost measurement (D2), we found that the minimize R&D cost was the foremost basic determinant of collaborations. The specialists also demonstrated that obtaining dominant technology was a determinative component for Taiwan’s machine tool industry, within the organizational learning measurement (D3).
In this experimental study, we attempted to identify the major components of strategic alliance pattern evaluation. We utilized the machine tool as our case study. On the premise of the observational findings, we concluded the taking after with a few administrative implications. The experts believed that financial resources was the strongest factor within the strategic behavior dimension (D1). In the cost perspective (D2), we found that the minimize manufacturing cost was the foremost basic determinant. The specialists also demonstrated that obtain dominant technology was a determinative component within the organizational learning (D3). The following selection tried to illustrate the proposed crossover strategy, which provides insight and proposals for assessing strategic alliance pattern.
5. Concluding Remarks
The Taiwanese machine tools industry has been suspended since the suspension of client manufacturing plants, and orders and shipments have plummeted. Specifically, the majority of clients of the machine tools industry are from the car industry. This wave of worldwide car manufacturing plants has been forced to suspend operations since the breakdown in supply of local car components. The declining demand for equipment is even more influential.
This study focused on the experiences of selected machine tool companies, located in Taiwan, in utilizing strategic alliances to overcome challenges and obstacles to scaling up, by promoting unsold/new items and developing their advertising scope [131]. This study found from the past research that the key factors of a successful industrial strategic alliance include technical aspects, capability aspects, trust, and so on. Shaikh and Levina [132] chose the open-development framework to create measurements around making decision. They construct a show of alliance partner selection and consider with open development communities. Haider and Mariotti [133] offer a longitudinal investigation of the forms of organization in organization collaboration portfolios. They concluded that strategic partners to pursue and which knowledge requirements to prioritize. This study learned that the successful industrial strategic alliance must be conducted the perspective of organizational open learning and innovation to success. Therefore, the organizational learning aspect was also integrated into the research framework in this research framework. This study also found that many previous studies on strategic alliances pointed out that for a successful strategic alliance, multiple dimensions and multiple factors must be considered. Young et al. [134] conducted a meeting of directors of private firms from the two biggest and most deliberately imperative move economies approximately key union accomplices about strategic alliance partners [135]. Hyder and Eriksson [136] analyse a union between two multinational companies from the same geological locale based on thought processes, assets, competitive advantage, believe, and execution. O’Dwyer and O’Flynn [137] tended to inquire about on key organization collaboration arrangement and proposed an intelligent model forecasting collaboration arrangement evaluation. Demirtas [138] embraced AHP strategy to assess the center competencies for strategic outsourcing model. Demirtas [138] pointed out that technological perspective played the most important role. Krammer [139] indicated that complementarity of corporate and technological diversification strategies drive exploitation alliances.
From the above past research, we can understand that a successful strategic alliance model not only considers a single aspect but must have an overall structure and thinking. This concept is completely consistent with this research model. From the past literature, we understand the importance of strategic alliances for industrial transformation and process, especially in the fast-changing industrial environment, how to integrate resources and diversify risks through strategic alliances.
The results demonstrated that the “strategic behavior” measurement’s impact is one of the foremost critical concerns. Within the commercial union, one sees that firms are spurred to obtain information, as this implies holding or procuring particular competencies; in this manner, they maximize their capacity to adjust to their environment. Firms adapt to a competitive environment by looking for particular information, which can be obtained by permitting agreements, or by gaining organizational or specialized information from key people. To maximize the success rate of a strategic alliance, the selecting party must assess each target enterprise’s money-related situation based on a rigorous examination of the potential target ventures. Meanwhile, the selecting party ought to thoroughly investigate the target enterprise’s sales philosophy and the essential factors that influence their decisions. As few firms are self-sufficient in particular assets, they establish alliances to combine the assets that they require to maintain or improve their current position. Deficiency in one or more strategic resources will constrain collaboration, as a measured approach to reduce instability and manage dependency. The resource dependency theory implies that companies adjust or respond to their environment.
R&D costs are likely to be one of the foremost concerns when considering for a strategic alliance. In numerous cases, the innovation required for industrial purposes is accessible within the commercial center, usually at a high price. In case the market development rate is moderate or slow, in-house or contracted R&D may be the best way to achieve innovation.
Moreover, when observation shows that the manufacturing cost is expanding, the company will frequently start to examine the status of each significant figure and decide where the increase started. The rise may be due to wage increases in the labor market, a change in the cost of raw materials, or the purchase of unused hardware that can be utilized straightforwardly within the manufacturing process. Knowing the cause of the increase can indicate whether the increment might be a brief one that will be counterbalanced by higher generation in a short period of time, or if a few activities must be undertaken to address the cause of the increment.
The conclusions obtained in this research are provided to the experts who completed the questionnaire in this research for reference. After this research process, an expert symposium will be held to discuss the research conclusions of this research. In this expert symposium, the experts not only confirm the correctness of their research conclusions but also hope can provide its research conclusions to relevant government units, so that relevant government units can refer to this research conclusion carefully when formulating policies. This research will conduct detailed and careful expert interview methods. We will continue the research conclusions for in-depth interviews and conduct interviews with more government representatives, industry representatives, and academic representatives to help Taiwan’s machine tool industry to upgrade and rebuild the industry.
Furthermore, the findings demonstrated that the dominant technology is a key factor for choosing a strategic alliance. In order for a company to extend its chance of achieving dominance with its plan, it should quickly deliver its innovation or item, and should promote the generation of complementary merchandise.
This investigation revealed that when strategists are considering how to drive or move forward the partner organization together, they must take into consideration the key persuasive variables and their impacts upon the other indirect measurements. Generally, enacting persuasive factors can more effortlessly result in the anticipated advancement, whereas indirect components can have limited ability to invigorate the continual development of these partnerships. This shows that the “strategic behavior dimension” is the causal measurement which unequivocally coordinates the influencers in all the other measurements. According to the interaction between the major competencies of the DEMATEL strategy, supervisors can viably choose a cost-saving method and viably increase the competitive advantage of the strategic alliance. This helps the financial specialists to diminish the obstructions and obtain much data from various powerful components, utilizing expert information. This research focuses on the analysis and research of Taiwan's machine tool industry. Under the impact of the new crown epidemic, Taiwan's machine tool industry has seen a significant decline. This study hopes to develop a strategic alliance evaluation model to enable Taiwan’s machine tool industry to cooperate and strategy alliance to enhance its competitiveness and competitive advantage. The conclusions of this research are in line with the suggestions of industry experts. This research will also provide the research results to Taiwan’s Ministry of Economic Affairs and the Ministry of National Development for reference. We hoped that when formulating strategic policies, they can provide the most efficient and fastest way for the machine tool industry.
These findings will support future research, as a useful reference for analysts to build strategic alliance models. As with any experimental study, this research has certain limitations. First, the observational information was collected in only one industry. Different businesses can have striking contrasts, and the research results may vary from one industry to another. Second, the technique used in this study, DEMATEL, presents impediments in terms of the small number of test measures. Furthermore, this paper will provide a step-by-step methodology to evaluate the selection of strategic alliance pattern evaluation model for Taiwan’s machine tool industry. This selection problem can be considered as multicriteria decision-making problem (MCDM) and we developed a computer-based group decision support system, an integrated analytic network process (ANP) and Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR)-based methodology along with a mechanism for determining the fuzzy linguistic value of each attribute. Thus, future research can be conducted to test the appropriate variables identified in this study, by utilizing different strategies and more up-to-date or geographically diverse data.
Data Availability
The data used to support the findings of this study are included within the article.
Conflicts of Interest
The author declares no conflicts of interest.