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Merger and acquisitions (M&A) is a process of restructuring two or more companies into one, a process that occurs frequently in many companies. Previous studies on M&A mainly paid attention to the potential gains from a merger, while ignored the problem of how to select the partners to merge. This paper aims to select the best partner from different candidates for a given company to merge.

Each company's historical data are used to identify each company's own production technology. With resources change, each company's new operation is restricted by its own production technology. Then, a 0–1 integer programming is proposed to select the best partner for M&A.

The banking industry involving 27 China's commercial banks is given to verify the applicability of our proposed model. The study shows the best partner selection for each bank company.

On the theoretical side, the study uses each company's own historical data to construct its own production technology to compressively reflect the production change after M&A. On the practical side, the study uses the proposed model to help the 27 commercial banks in China to select their best merger partner.

The Malaysian government is rushing banks to merge. The Central Bank has decided that there must be only 10 banks instead of a current total of 20. As a result, the local banks were being forced to merge with other banks. The problem lies in the non‐existence of a systematic means of identifying potential merger partner(s). This study thus, proposes to use the concept of the Transportation Algorithm to select potential merger partners for Malaysian banks, which would maximize the net worth of the merged entity. The methodology employed in this paper may not yield the best merger partner(s) but it should at least narrow down the choices to a select few where together with other rigorous financial, technical, strategic and even qualitative analysis may be used to determine the ultimate merger partner(s).

The purpose of the study is to examine the use of management controls by a public partner to minimise risks associated with a public-private partnership (PPP) in a developing country.

Using case study method, management controls used in a power project formed as a PPP are examined based on data gathered from semi-structured interviews and documentary analysis.

The study reveals that the public partner of the PPP used multiple controls depending on the nature of risks in different phases of the project. While bureaucratic control was the predominantly used control pattern throughout the three phases (namely, selecting, building and operating) of the PPP, trust-based controls also played an important role. Market controls on the other hand played, somewhat, a nominal role, particularly in the selecting phase of the project. The study also highlights the problematic nature of forming PPPs in developing countries despite the various benefits associated with such organisational arrangements. Additionally, the study provides insights into how certain contextual features of developing countries affect the way in which controls are applied.

The insights provided in this paper would be beneficial to policy makers, in developing countries in particular, when making decisions in relation to implementation, management and risk control of PPPs.

This study makes an original contribution to the existing literature on PPPs by examining the way in which management controls are used to minimise risk in a PPP in a developing country.

Selecting suitable and competent partners is an important prerequisite to improve the performance of collaborative product innovation (CPI). The purpose of this paper is to propose an integrated multi-criteria approach and a decision optimization model of partner selection for CPI from the perspective of knowledge collaboration.

First, the criteria for partner selection are presented, considering comprehensively the knowledge matching degree of the candidates, the knowledge collaborative performance among the candidates, and the overall expected revenue of the CPI alliance. Then, a quantitative method based on the vector space model and the synergetic matrix method is proposed to obtain a comprehensive performance of candidates. Furthermore, a multi-objective optimization model is developed to select desirable partners. Considering the model is a NP-hard problem, a non-dominated sorting genetic algorithm II is developed to solve the multi-objective optimization model of partner selection.

A real case is analyzed to verify the feasibility and validity of the proposed model. The findings show that the proposed model can efficiently select excellent partners with the desired comprehensive attributes for the formation of a CPI alliance.

Theoretically, a novel method and approach to partner selection for CPI alliances from a knowledge collaboration perspective is proposed in this study. In practice, this paper also provides companies with a decision support and reference for partner selection in CPI alliances establishment.

The purpose of this paper is to establish a mechanism for partner selection via adapting relative weights of criteria according to the priority of motivations for establishing strategic alliance.

The analytic network process (ANP) approach derived from the idea of the Markov chain is employed to deal with this dynamic situation and to establish a partner selection mechanism. With this approach, the priority of motivations and the relative importance of criteria are determined simultaneously.

Although choosing an appropriate partner is an important variable influencing success of alliance, attempts to identify a universal list of criteria and their corresponding relative importance which enterprises should employ when seeking a proper partner would be futile since the objectives of forging alliances vary depending on specific motivations. Based on this iterative review approach proposed in this paper, a proper weight setting for these criteria is available and will comply with the original motivation for establishing the strategic alliance. This is essential for selecting an appropriate partner for establishing an alliance that matches the original motivation.

The limitation of this research is the neglect of the possible inner dependence among criteria and sub‐criteria, although that can be coped with by choosing them properly.

The content of motivations and criteria as well as their priority and weightings may vary with different kinds of alliances or situations. The partner evaluation and selection mechanism proposed in this paper can meet different situations by adapting the relative weights of criteria and attributes according to the relationship between the criteria and motivations for every particular situation, thus enabling decision‐makers to think more comprehensively before conducting a selection process. If the priority of the motivations obtained from the mechanism is consistent with that set initially, the relative weights of these criteria can then be employed to evaluate the candidate partners in the selection mechanism. If it is not, the decision maker should reconsider the weighting process or measure again the relative weights for the criteria before conducting the evaluation and selection processes to avoid selecting an inappropriate partner that runs contrary to the original motivations.

The emphasis is on the interdependence between motivations and criteria for partner selection. This paper systematically deals with the interdependence of these two factors. Based on this iterative review approach proposed in this paper, a proper weight setting for these criteria is available and will comply with the original motivation for establishing the strategic alliance.

The purpose of this paper is to apply a mathematical method of formal concept analysis (FCA) to facilitate evaluation of potential partners, and to select the most appropriate partner for horizontal strategic alliances. Horizontal collaboration between ship design firms is important in relation to business cyclicality in the industry. The workload in ship design firms drops during the troughs of the shipbuilding cycle and increases dramatically during the peaks of the cycle.

The proposed method of partnership selection applies FCA, which is based on mathematical lattice theory. FCA allows firms to evaluate and select the best suitable partners for horizontal interfirm cooperation from several possible candidate firms. Utilization of FCA allows a firm to visually analyze a potential partner for a horizontal strategic alliance.

The contribution of this study to the literature is twofold. First, it contributes to the literature on the application of FCA in management field. Second, this study contributes to the partner selection literature. The contribution of the study is an alternative quantitative method for partner selection based on FCA. FCA compliments qualitative approaches in the process of alternatives evaluation and decision‐making regarding partner selection for horizontal collaboration.

Practitioners from ship design firms can use the FCA tool to facilitate decision‐making relating to the screening of potential partners for horizontal cooperation with regard to pre‐specified selected criteria.

FCA has been marginally applied to aid managerial decision making. The FCA tool is valuable for practitioners from ship design firms to manage the selection of partners for horizontal collaboration. The FCA tool is associated with numerous advantages, notably, relative simplicity and versatility of visual analysis when compared with other mathematical approaches such as the analytic hierarchy process, the analytic network process, optimization modeling, and fuzzy set logic.

The purpose of this paper is to develop a meta-model that systematically aggregates and organizes research on “partner selection” in interorganizational relationships (IORs), which is scattered across several disciplines, to help future researchers explore various aspects of this control mechanism in a more consistent manner. This paper also aims at critically reviewing each aspect of this control mechanism examined in the prior literature and identifying important research trends.

This paper conducts a comprehensive review and in-depth analysis of the key theoretical and empirical research findings on partner selection in IORs by identifying 172 papers across 46 journals that specifically discuss this control mechanism. A meta-model approach is adopted to review and identify the shortcomings in extant research and provide guidance to future researchers on exploring unanswered research questions. Moreover, maps are constructed using the Luft and Shields’s (2003) approach to graphically present the causal-model forms examined in this topic area.

This meta-model shows how the research on partner selection in IORs is scattered across different disciplines, resulting in its inconsistent evolution with researchers, in many cases, not being able to effectively synthesize contributions from fields that are not their own or not closely allied. The causal-model forms also enable rapid tracing of what has been researched.

There has been considerable research on control mechanisms in IORs till date. However, “partner selection,” which is an important control mechanism, has received little attention and is often neglected. To the best of the author’s knowledge, this paper is the first to develop a meta-model to consolidate knowledge on this topic that is important for further advancement of research.

The purpose of this paper is to provide insights on the franchise partner recruitment process and decision‐making criteria used to select partners. It aims to investigate the process and parameters considered by franchisees in selecting potential international hotel organizations as partners. The success of such choices influences growth of the firms and consequently affecting industry and economy.

In‐depth semi‐structured interviews with owners, directors, vice presidents and mangers of the franchisee organizations were deployed.

Findings suggest that partner selection is a multidimensional activity involving several key stages. Indian franchisees use profitability, brand name, operations support as decision‐making criteria while selecting their partners.

Differences occur at various stages of partner selection. A proper understanding of partner selection dynamics and careful consideration of criteria's like culture, organizational values, pricing, experience, etc. would result in a better building of relationship.

The paper highlights the complexity of the process and the decision‐making criteria from a franchisee's perspective. From a practical perspective, it could be of value to future and existing international hotel chains using franchising as a mode of expansion.

The purpose of this exploratory study is to examine the partner selection criteria reported by maritime firms in Norway. The study aims to analyze how a maritime firm's competitive advantage can be enhanced by the selection of the right partner with reference to a strategic alliance.

A multiple‐case study methodology was used. Archival, survey and interview data were explored relating to the partner selection process reported by Norwegian maritime firms. Primary data were gathered from semi‐structured personal interviews with managers of Norwegian maritime firms.

Case study evidence suggests that the strategic alliances were successful when partners had been carefully selected. As detected elsewhere, successful alliances were associated with partners that had managed to build trustful and honest relationships, had common strategic goals, and partners that supplied resources and competencies. Notably, it was detected that cyclicality in the maritime industry shaped the partner selection process. Trust between partners was used as mechanism to reduce uncertainty relating to the strategic alliance process. Firms seeking long‐term alliances selected partners with substantial capital and financial stability to survive a market's downturn, as well as the resources required for expansion during a recession.

Presented findings have implications for practitioners, especially for managers of shipping firms, banks, shipyards, producers of ship equipment, ship design firms, and ship brokers. Practitioners need to be aware that the rationale for inter‐firm collaboration change over time, and motives are linked to the phase of the maritime cycle. Inter‐firm collaboration provides competitive advantage benefits to firms and collaboration can protect as well as create jobs and can create wealth in maritime communities.

A novel conceptual contribution is the exploration of links between maritime industrial cyclicality and the partner selection process relating to strategic alliances. The study also adds to debates relating to the profiles of internationalizing smaller firms.

The purpose of this paper is to examine the following research question in partner selection decisions in business-to-business strategic partnerships/collaborations literature: How do inertia and uncertainty affect partner selection? Explicitly, the paper analyzes how inertia of previous alliance selection routines and uncertainty of entire market movement shape firms’ preferences regarding exploratory partner selection (i.e. selecting new partners who never collaborate with the focal firm).

Grounded on inter-firm partnerships, partner selection and network theory literature, the study empirically tests a fine-grained sample of 511 open-end funds initiated by 61 fund management firms in China. To do so, it runs Tobit regression for main analysis and applies a variety of sensitivity analyses to check the robustness.

Results show that inertia in previous partner selection has a negative effect on exploration. Importantly, these inertial forces impact domestic firms but not international firms. Market uncertainty also affects exploratory partner selection: short-term market uncertainty encourages exploration, whereas long-term uncertainty inhibits it. These effects also depend on firms’ type: long-term market uncertainty has a negative effect on exploration for international firms but not for domestic firms. Both types of firms exhibit a stronger tendency toward exploration when they encounter short-term uncertainty. However, this inclination is stronger in international firms.

Earlier research has examined how inertia affects exploitation but largely overlooked its effect on exploration. A critical examination of firm and environment level factors provides a deeper understanding of why and when firms have inconsistent preferences for specific partner selection strategies. Thus, this study offers a unique perspective for understanding firms’ exploratory partner selection by focusing on two important characteristics of focal firms: one internal (inertia) and one external (market uncertainty) in nature.