The Selection of Strategic Alliance in IC Packaging and Testing Industry with DEA Resampling Comparative Evaluation

Merger and acquisition (M&A) cases and the speed of horizontal integration have increased rapidly in the integrated circuit (IC) packaging and testing industry. Therefore, cooperation with suitable strategic alliance partner is a vital success factor for enterprises. This study proposes a “comparative evaluation” model that searches out appropriate strategic alliances on the basis of the resampling model acquired via data envelopment analysis (DEA). The realistic public data of 20 companies was collected from 2015 to 2019 in the IC packaging and testing industry. The super slacks-based measure model was used to evaluate the performance before alliance in the period from 2015 to 2019. The resampling past–present–future model was used to forecast the performance in 2020–2024. Afterward, a future strategic alliance for comparative evaluation of efficiency was established. The results of the alliance were divided into the groups “ineffective” and “effective”. The results show that 11 companies in the “effective” group achieved both improvements and 8 companies in the “ineffective” group achieved only unilateral improvements. The comparison model describes the efficiency of both sides simultaneously, not only from the perspective of the target but also from the perspective of the partner company. The evaluation model proposed in the study enables enterprises to find suitable alliance partners.

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Partner selection in market-driven strategic alliances

South African Journal of Business Management ◽

10.4102/sajbm.v28i3.794 ◽

1997 ◽

Vol 28 (3) ◽

pp. 97-104 ◽

Cited By ~ 3

Author(s):

Saul Klein ◽

Chekitan Dev

Keyword(s):

Strategic Alliances ◽

Customer Value ◽

Strategic Alliance ◽

Multiple Choice ◽

Partner Selection ◽

Alliance Partner ◽

One Stop ◽

Market Driven ◽

Alliance Partners

How should one select a strategic alliance partner? An answer to this question is provided by extending the literature on symbiotic marketing and focussing attention on market-driven strategic alliances. Such alliances are defined as long-term inter-firm co-operative relationships that add value for the customer. Value is created by providing the advantages of multiple choice purchase options coupled with the convenience of seamless, one-stop-shopping. This means paying attention to customers and competitors in selecting alliance partners. Market-driven strategic alliances are posited to be more successful when usage and firm complementarity levels are correctly matched with the alliance strategy being pursued.

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A Hybrid MCDM Model for Evaluating Strategic Alliance Partners in the Green Biopharmaceutical Industry

Sustainability ◽

10.3390/su11154065 ◽

2019 ◽

Vol 11 (15) ◽

pp. 4065 ◽

Cited By ~ 7

Author(s):

Chang ◽

Liou ◽

Keyword(s):

Strategic Alliances ◽

Strategic Alliance ◽

Selection Process ◽

Rapid Change ◽

Fuzzy Topsis ◽

Small Sample ◽

Biopharmaceutical Industry ◽

Aspiration Level ◽

Alliance Partner ◽

Alliance Partners

Since the rise of strategic alliances which play such an important role in industry today, the biopharmaceutical industry worldwide has entered an era of rapid change and collaborative thinking. The strategic alliance is one of the most important strategies for the green biopharmaceutical industry. Member organizations in these alliances work together to create more advantageous biotechnologies based on environmental protection to achieve mutual benefits. In the past, there have been only a few studies discussing partner evaluations and the selection process for the green biopharmaceutical industry, so the criteria or indicators are still not complete. Therefore, this study proposes a novel multi-criteria decision-making (MCDM) framework for strategic alliance partner evaluation that combines the best-worst method (BWM) and the fuzzy TOPSIS technique based on the concept of aspiration level (called fuzzy TOPSIS-AL) to evaluate the performance and priority rankings of strategic alliance partners. The BWM overcomes the shortcomings of small sample sizes and streamlines the number of conventional pairwise comparisons needed. The fuzzy TOPSIS-AL technique introduces the concept of the aspiration level, thereby leading to more reasonable suggestions for improvement. In addition, data from a multinational green biopharmaceutical company survey are utilized to demonstrate the validity and applicability of the proposed model.

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Confidence Interval Based Fuzzy Evaluation Model for an Integrated-Circuit Packaging Molding Process

Applied Sciences ◽

10.3390/app9132623 ◽

2019 ◽

Vol 9 (13) ◽

pp. 2623 ◽

Cited By ~ 7

Author(s):

Chun-Ming Yang ◽

Kuo-Ping Lin ◽

Kuen-Suan Chen

Keyword(s):

Confidence Interval ◽

Integrated Circuit ◽

Evaluation Model ◽

Measurement Data ◽

Electronics Industry ◽

Green Economy ◽

Fuzzy Evaluation ◽

Molding Process ◽

Ic Packaging ◽

Fuzzy Evaluation Model

The electronics industry in Taiwan has achieved a complete information and communication technology chain with a firm position in the global electronics industry. The integrated-circuit (IC) packaging industry chain adopts a professional division of labor model, and each process (including wafer dicing, die bonding, wire bonding, molding, and other subsequent processes) must have enhanced process capabilities to ensure the quality of the final product. Increasing quality can also lower the chances of waste and rework, lengthen product lifespan, and reduce maintenance, which means fewer resources invested, less pollution and damage to the environment, and smaller social losses. This contributes to the creation of a green process. This paper developed a complete quality evaluation model for the IC packaging molding process from the perspective of a green economy. The Six Sigma quality index (SSQI), which can fully reflect process yield and quality levels, is selected as a primary evaluation tool in this study. Since this index contains unknown parameters, a confidence interval based fuzzy evaluation model is proposed to increase estimation accuracy and overcome the issue of uncertainties in measurement data. Finally, a numerical example is given to illustrate the applicability and effectiveness of the proposed method.

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Resource and Risk Management in the Strategic Alliance Making Process

Journal of Management ◽

10.1177/014920639802400103 ◽

1998 ◽

Vol 24 (1) ◽

pp. 21-42 ◽

Cited By ~ 88

Author(s):

T. K. Das ◽

Bing-Sheng Teng

Keyword(s):

Strategic Alliances ◽

Strategic Alliance ◽

Interactive Effects ◽

Future Research ◽

Research Directions ◽

Managerial Implications ◽

Future Research Directions ◽

Alliance Partners ◽

And Performance ◽

Relational Risk

Resource-based and risk-based views of strategic alliances have not been adequately reflected in the literature. This paper identifies four types of critical resources that the partners bring to an alliance: financial, technological, physical, and managerial resource. It also suggests two basic types of risk in strategic alliances: relational risk and performance risk. The alliance making process is examined in terms of the interactive effects of resource and risk on the orientations and objectives of the prospective alliance partners. Managerial implications are discussed and future research directions indicated in the form of propositions for empirical testing.

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Collaborative Entrepreneurship for Continuous Innovation: A Strategic Alliance Perspective

10.5772/intechopen.93868 ◽

2020 ◽

Author(s):

Ribin Seo

Keyword(s):

Strategic Alliances ◽

Strategic Alliance ◽

Integrative Approach ◽

Interorganizational Learning ◽

Dynamic Interactions ◽

Resource Pooling ◽

Collaborative Advantage ◽

Continuous Innovation ◽

Alliance Partners ◽

Collaborative Entrepreneurship

Strategic alliances act as a platform to implement collaborative entrepreneurship while exposing a range of challenges. By capitalizing on entrepreneurial opportunities for continuous innovation, alliance partners can promote the productive utilization of resource-pooling systems and facilitate innovation processes for value co-creation. Simultaneously, the heterogeneity of partners in terms of different motivations and interests interferes with the advancement of collaborative entrepreneurship for resource exchange and orchestration. The objective of this paper is thus to explore how to deal with the potential coordination issues that can make an alliance vulnerable and its returns diminished through a preliminary integrative approach to the interface between collaborative entrepreneurship and strategic alliances. From this approach, three elements that can contribute to leverage values of collaborative entrepreneurship for continuous innovation are identified: social capital, entrepreneurial orientation, and interorganizational learning. Based on the discussion about the functions of each element in the context of alliance partners’ dynamic interactions, a model of analysis on collaborative entrepreneurship for continuous innovation is proposed. Hence, this chapter contributes to a better understanding of how firms can enact collaborative entrepreneurship productively to gain greater benefit from the alliance configuration for collaborative advantage.

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Strategic Alliances & Customer Impact: A Case Study Of Community Hospitals

Journal of Business & Economics Research (JBER) ◽

10.19030/jber.v8i9.755 ◽

2010 ◽

Vol 8 (9) ◽

Cited By ~ 1

Author(s):

Mary Helen McSweeney-Feld ◽

Suzanne Discenza ◽

George L. De Feis

Keyword(s):

Social Structure ◽

Strategic Alliances ◽

Strategic Alliance ◽

Font Size ◽

The Social ◽

Formal Relationship ◽

Alliance Partners ◽

The Relationship

A strategic alliance (SA) is a mutually beneficial long-term formal relationship formed between two or more parties to pursue a set of agreed upon goals or to meet a critical business need while remaining independent organizations.  It is a synergistic arrangement whereby two or more organizations agree to cooperate in the carrying out of a business activity where each brings different strengths and capabilities to the arrangement.  The social structure of alliances has been considered previously (Gulati 1995, et al.), so instead of discussing the social structure relative to alliance partners, this paper looks at the relationship between the dyad alliance entity and its customer(s).  This newer aspect is particularly important when there are differences in trust and culture to consider (Das & Teng 1998) between alliance partners.  Other considerations include authority, governance and structure, conflict, and the make-up of the strategic alliance, its partners, and the customer(s).

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Accounting Quality and Alliance Contract Provisions

The Accounting Review ◽

10.2308/tar-2017-0623 ◽

2020 ◽

Author(s):

Rui Ge ◽

Yuan Ji ◽

Henock Louis

Keyword(s):

Bargaining Power ◽

Strategic Alliance ◽

Market Value ◽

Accounting Quality ◽

Net Benefit ◽

Bankruptcy Risk ◽

Alliance Partner ◽

Accounting Numbers ◽

Alliance Partners

We show that the number of governance provisions imposed on a firm by a strategic alliance partner decreases with the firm's accounting quality. This effect is weaker when the firm has greater bargaining power and stronger when the alliance project is riskier. Moreover, the net benefit to an alliance partner of imposing an additional governance provision on its counterparty apparently increases when the counterparty accounting quality is low, resulting in an enhancement of the partner's market value and a reduction in its bankruptcy risk. Furthermore, alliance partners adopt fewer provisions based on their counterparties' accounting numbers when the counterparties' accounting quality is poor.

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The international context of cooperation: culture and institutions

Cooperative Strategy ◽

10.1093/oso/9780198814634.003.0021 ◽

2019 ◽

pp. 447-483

Author(s):

John Child ◽

David Faulkner ◽

Stephen Tallman ◽

Linda Hsieh

Keyword(s):

Interest Groups ◽

Strategic Alliance ◽

Joint Venture ◽

Institutional Environment ◽

National Context ◽

International Context ◽

Alliance Partner ◽

Cooperative Strategies ◽

Country Differences ◽

Alliance Partners

Chapter 21 examines ways in which the national context of alliances is relevant to cooperative strategies. It focuses on two salient contextual features. One is national culture. The other is the institutional environment, which particularly refers to governments and interest groups such as NGOs. National context is consequential for alliances in several ways. The context from which international alliance partners originate encourages each of them to internalize a particular set of norms and practices. So, if there is a substantial difference (“distance”) between those contexts, misunderstanding and friction can readily arise between the partners. Additionally, it may be problematic for an alliance partner to build sympathetic and constructive relationships with governmental bodies and interest groups in the host country location of the alliance unit (such as a joint venture), if that location is culturally and institutionally distant from the partner’s domestic environment. The chapter considers “distance” arising from country differences and how it can be highly consequential for the management and ultimate viability of an international strategic alliance.

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Learning and Knowledge Transfer in Strategic Alliances: A Social Exchange View

Organization Studies ◽

10.1177/0170840605050874 ◽

2005 ◽

Vol 26 (3) ◽

pp. 415-441 ◽

Cited By ~ 274

Author(s):

Senthil K. Muthusamy ◽

Margaret A. White

Keyword(s):

Knowledge Transfer ◽

Social Exchange ◽

Strategic Alliances ◽

Social Exchange Theory ◽

Strategic Alliance ◽

Mutual Influence ◽

Empirical Examination ◽

Social Exchanges ◽

Exchange Processes ◽

Alliance Partners

Although social interactions and exchanges between partners are emphasized as imperative for alliance success, comprehensive examination of how social exchanges facilitate learning and knowledge transfer in strategic alliances is lacking. Drawing on social exchange theory, we examined the effects of social exchange processes between alliance partners on the extent of learning and knowledge transfer in a strategic alliance. An empirical examination of data collected from alliance managers of 144 strategic alliances revealed that social exchanges such as reciprocal commitment, trust, and mutual influence between partners are positively related to learning and knowledge transfer in strategic alliances.

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A Study of the Strategic Alliance for EMS Industry: The Application of a Hybrid DEA and GM (1, 1) Approach

The Scientific World JOURNAL ◽

10.1155/2015/948793 ◽

2015 ◽

Vol 2015 ◽

pp. 1-14 ◽

Cited By ~ 3

Author(s):

Chia Nan Wang ◽

Nhu Ty Nguyen ◽

Thanh Tuyen Tran ◽

Bui Bich Huong

Keyword(s):

Strategic Alliances ◽

Manufacturing Industry ◽

Strategic Alliance ◽

Critical Factor ◽

Data Envelopment ◽

Electronic Manufacturing ◽

Target Company ◽

Alliance Partners ◽

The Right ◽

Realistic Data

Choosing a partner is a critical factor for success in international strategic alliances, although criteria for partner selection vary between developed and transitional markets. This study aims to develop effective methods to assist enterprise to measure the firms’ operation efficiency, find out the candidate priority under several different inputs and outputs, and forecast the values of those variables in the future. The methodologies are constructed by the concepts of Data Envelopment Analysis (DEA) and grey model (GM). Realistic data in four consecutive years (2009–2012) a total of 20 companies of the Electronic Manufacturing Service (EMS) industry that went public are completely collected. This paper tries to help target company—DMU1—to find the right alliance partners. By our proposed approach, the results show the priority in the recent years. The research study is hopefully of interest to managers who are in manufacturing industry in general and EMS enterprises in particular.

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