Development of dyadic relationships between competitors within multi-actor alliances

Santos, José Novais; Baptista, Cristina Sales

doi:10.1108/jbim-10-2019-0460

Cited by 4 publications

(4 citation statements)

References 69 publications

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“…Participating subjects form complex interactions in value exchange, which will change dynamically with the evolution of the design process (Santos and Baptista 2021). To maximize their expected benefits, subjects will spontaneously form loosely connected small groups in the form of competition or cooperation (Wang et al 2017).…”

Section: Collective Intelligence Designmentioning

confidence: 99%

Ecological evolution analysis in collective intelligence design

Guo

Wang

et al. 2022

Preprint

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The transition from conventional design has been hastened by the development of network platforms, and innovative design dependent on social resources has emerged as a new design paradigm. The concept of collective intelligent design (CID) can be compared to a design ecosystem, in which members are constantly interacting with one another to advance the design process. The system will vary as the design evolves organically. How to assess the system's evolving state is the foundation of system optimization. To characterize the evolution of the CID system, this study proposed a matching network-based ecological network model and specified a comprehensive evaluation index for analyzing the evolutionary state. The model's validity is confirmed by an examination of Zhubajie (ZBJ), China's largest CID platform. The results demonstrate the ecological model developed in this study can capture the evolution essence of the ZBJ, and evaluation indicators demonstrate the ZBJ has been relatively mature. While the individuals' relationships are growing more distant, the engagement is becoming more effective. Additionally, the platform's sustainability has diminished while its resilience to external hazards has improved. Stakeholders may benefit from these ideas as they attempt to enhance the design process.

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Section: Collective Intelligence Designmentioning

confidence: 99%

Ecological evolution analysis in collective intelligence design

Guo

Wang

et al. 2022

Preprint

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“…It is also important to develop partner-specific relationship models, e.g. for competitors who must cooperate within a network through the stages of alliances from co-existence through development and dissolution (Santos and Baptista, 2020). Despite obvious challenges, alliance performance and productivity can be enhanced with prior alliance experience, inter-partner learning, knowledge internalisation, transfer and absorptive capacity (Ranjan and Read, 2021).…”

Section: Analysis Of Alliance Literature On Tccm Themesmentioning

confidence: 99%

“…, 2021; de Man and Roijakkers, 2009), knowledge and other resources, alliance management (Hansen et al. , 2010), alliances with competitors (Santos and Baptista, 2020) and innovation (Spieth et al. , 2021), to name a few.…”

Section: Introductionmentioning

confidence: 99%

“…The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/1755-425X.htm knowledge and other resources, alliance management (Hansen et al, 2010), alliances with competitors (Santos and Baptista, 2020) and innovation (Spieth et al, 2021), to name a few. There is, therefore, a need to synthesise and analyse key insights from this vast and dispersed extant literature so that it can be applied in the field.…”

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confidence: 99%

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Dyadic, network and ecosystem alliances: systematic literature review and research agenda

Krishna

2022

JSMA

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PurposeLiterature on strategic alliances (SAs) is large, diverse and growing. It needs synthesis and analysis for application and further research. Authors have also underlined the need for studies covering differences in structuring, situational application and management of alliances. This systematic literature review aims to cover dyadic, network and ecosystem (DNE) alliances with theory, context, characteristics and methodology (TCCM) methodology covering the life cycle stages of an alliance (pre-formation, formation and management) to uncover insights which inform practice and guide further research on this important subject.Design/methodology/approachThis paper follows systematic literature review (SLR) methodology for research design and article selection and TCCM methodology for analysis. It also analyses the literature on DNE alliances using a nine-box matrix with DNE alliance forming one axis and three alliance lifecycle stages of pre-formation (alliance objectives), formation (alliance design and operationalisation) and post formation (alliance management) stages along the other axis.FindingsAnalysis indicates focus on individual firms and their own customer value proposition (CVP) in the dyadic and network alliances. Industries with fast-paced technological change benefit from loosely coupled alliances. Social context and social exchanges leading to collaboration and collective strengths mark network alliances, with a focus on knowledge creation and dissemination. Ecosystems focus on a collective CVP, which guides alliance behaviour. Ecosystem leadership guides this purpose through governance for sustained competitiveness. Negative consequences (dark side) of alliances can be mitigated by careful design, formation and management of DNE alliances.Research limitations/implicationsWhile literature has focussed on static view of alliances in their industry or social context, this literature review analyses alliances along the dyadic, network and ecosystem typology, thus providing a new lens to study alliances. The review also recognises that alliances evolve over their life-cycle stages and observes their progression through their lifecycle stages aids for fuller comprehension of their behaviour. Areas for future research in structuring, leadership, value co-creation and technological change set an agenda for future research.Practical implicationsDynamic managerial capabilities are drivers of alliance performance. The analysis using the nine-box matrix allows managers to better appreciate the options that exist and the consequences of their actions. Situating their alliance in the appropriate box can allow managers better plan, operationalise and manage their own alliances.Originality/valueThis systematic review compares and contrasts DNE alliances in extant literature and through their lifecycle stages. Insights from TCCM analysis and the nine-box matrix provide unique contribution to both theory and practice in this large and growing domain.

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Buyer–supplier interactions in business services: variety in relational interfaces

2022

Self Cite

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Business services have become a considerable share of many firms' external resources. Several service typologies have been proposed. This study explores the underlying dynamic of interaction patterns in business services through the lens of relational interfaces. Five exploratory case studies show the presence of variety in the buyer-supplier interfaces. Thus, the relevance of the interaction patterns to increasing a firm's productivity or innovativeness may require an assessment of this variety in relational interfaces.

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Development of dyadic relationships between competitors within multi-actor alliances

Cited by 4 publications

References 69 publications

Ecological evolution analysis in collective intelligence design

Ecological evolution analysis in collective intelligence design

Dyadic, network and ecosystem alliances: systematic literature review and research agenda

Buyer–supplier interactions in business services: variety in relational interfaces

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