Cooperation and compliance in non-equity alliances

Gudergan, Siegfried P.; Devinney, Timothy M.; Ellis, Rob

doi:10.1016/j.jbusres.2015.10.051

Cited by 12 publications

(4 citation statements)

References 37 publications

(38 reference statements)

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“…Therefore, combining the quality of DCE data with the analysis features of PLS-SEM represents a useful approach to assess discrete choices and specifically, when the underlying decision making-irrespective of whether rational, optimizing or pragmatic, heuristic-requires understanding of relative attribute impacts rather than attribute level effects. Moreover, although not explored in this article, DCM, which that employs PLS-SEM to DCE data, provides a basis when, for example, incorporating latent class analyses methods to reveal differences in decision-making as it applies to managers themselves (Lin et al 2016) and a variety of their stakeholders such as alliance partners (e.g., Gudergan et al 2016) or customers (e.g., Mathies et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice

Hair

Ringle

Gudergan

et al. 2018

Bus Res

Self Cite

316

336

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Commonly used discrete choice model analyses (e.g., probit, logit and multinomial logit models) draw on the estimation of importance weights that apply to different attribute levels. But directly estimating the importance weights of the attribute as a whole, rather than of distinct attribute levels, is challenging. This article substantiates the usefulness of partial least squares structural equation modeling (PLS-SEM) for the analysis of stated preference data generated through choice experiments in discrete choice modeling. This ability of PLS-SEM to directly estimate the importance weights for attributes as a whole, rather than for the & Christian M. Ringle

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Section: Introductionmentioning

confidence: 99%

Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice

Hair

Ringle

Gudergan

et al. 2018

Bus Res

Self Cite

316

336

View full text Add to dashboard Cite

show abstract

“…Achieving a common goal is the basis of cooperation [18]. Business managers should build credibility [11] and accountability and enhance compliance in individual interactions with their stakeholders in their environment and outside of that environment [9,19,20]. Individual learning skills in cooperation action are important for full cooperation for some payoff [21,22].…”

Section: Theoretical Reviewmentioning

confidence: 99%

Through Synergy in Cooperation towards Sustainable Business Strategy Management

2022

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In our research we have focused our effort on answering one major question: could theory about synergy effects help to strengthen the cooperation between organizations to achieve more sustainable business? In order to do that, we set up three main research domains: (1) synergies and synergy effects; (2) cooperation and the cooperation environment; and (3) strategic management. From the methodological point of view, besides literature review, we combined content analysis of relevant internet sources (both quantitative and qualitative) and sociological survey in the years 2014 to 2018. The results show us strong connections between the effective usage of cooperation and synergy effect in strategic management and market competitiveness. They also show as that certain way of strategic cooperation between organizations could be significantly beneficial towards business sustainability. In our paper we present data from our research, our main significant findings, and also recommendations and tools for utilizing them in practice.

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“…The crucial issues to be considered in the planning and governing of an alliance include (1) equity distribution, (2) term of agreement, and (3) relationship management [45]. The partners' insights into risk, namely, uncertainty about the external environment's changes, trust, and level of profit-sharing, reflect the factors that lead to the alliance's efforts [77]. Each method for forming an R&D alliance can be explained as a firm's arrangements to minimize all efforts necessary to develop successful products.…”

Section: Types Of Randd Alliancesmentioning

confidence: 99%

Strategies for Heterogeneous R&D Alliances of In Vitro Diagnostics Firms in Rapidly Catching-Up Economies

Huang

Tung

2020

IJERPH

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Most developed countries already have high-quality in vitro diagnostic (IVD) techniques for diseases, but developing countries often do not have access to these technologies and cannot afford them. Enabling firms to leverage external resources to optimize their research and development (R&D) performance has become one of the most critical issues for small and medium-sized late-coming IVD firms. R&D alliances, especially heterogeneous alliances, are necessary for releasing the resource limitations of late-coming small and medium-sized enterprises (SMEs) and reaching the metaoptimum of the R&D performances. However, to the authors’ knowledge, a few, if any, previous studies have investigated the key success factors and strategies of heterogeneous alliances in the IVD industry. Therefore, the authors aim to define the critical factors for evaluating and selecting strategies for heterogeneous alliances in the IVD industry. A Decision-Making Trial and Evaluation Laboratory (DEMATEL)-based analytic network process (DANP) was proposed to prioritize the weights associated with the evaluation criteria. Then, a heterogeneous R&D alliance strategy was derived from the compromise ranking based on the modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. An empirical study of major Taiwanese IVD firms’ evaluation and selection of heterogeneous R&D alliance strategies will be used to reveal the practicability of the analytic framework. Based on the analytic results, the joint venture strategy is the most suitable heterogeneous R&D alliance strategy for IVD firms in rapidly catching-up economies. These results can serve as the basis for heterogeneous R&D alliance strategy definitions in the IVD industry in the future.

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Cooperation and compliance in non-equity alliances

Cited by 12 publications

References 37 publications

Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice

Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice

Through Synergy in Cooperation towards Sustainable Business Strategy Management

Strategies for Heterogeneous R&D Alliances of In Vitro Diagnostics Firms in Rapidly Catching-Up Economies

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