Are distrust relationships beneficial for group performance? The influence of the scope of distrust on the emergence of collective intelligence

Massari, Giovanni Francesco; Giannoccaro, Ilaria; Carbone, Giuseppe

doi:10.1016/j.ijpe.2018.12.005

Cited by 24 publications

(23 citation statements)

References 78 publications

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“…For example, smaller groups can make better decisions and be more resilient (Kao & Couzin, 2019;Giannoccaro et al 2018), while less well-connected networks can promote collective performance on complex problems (Derex & Boyd, 2016;Lazer & Friedman, 2007;Mason et al, 2008). Interdependence of group members in terms of payoffs and shared information further affects collective performance (Gonzalez & Martin, 2011;Gonzalez et al, , 2015Martin et al, 2014;Massari et al 2019;Moisan et al, 2018;). Measures of node centrality such as betweenness predict the spread of information in societies (Banerjee et al, 2013).…”

Section: Social Environmentsmentioning

confidence: 99%

“…Our call echoes, on the collective level, Herbert Simon's earlier call to go beyond studying outcomes of rational thought in relatively simple, static problem situations (Simon, 1976(Simon, , 1978, and move towards better understanding of multi-scale interactions that can drive collective trajectories in sometimes unexpected directions. For example, early success can make a team more tightly interconnected over time (Mullen & Cooper, 1994) -in turn impairing its performance on further complex tasks where diversity of opinions is needed for success (Gonzalez et al, 2015;Massari et al 2019). Increased cooperation in social networks can support the formation of more long-range social ties, which can create the conditions for the collapse of cooperation (Akçay, 2018).…”

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confidence: 99%

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Beyond collective intelligence: Collective adaptation

Galešić¹,

Barkoczi²,

Berdahl³

et al. 2022

Preprint

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We develop a conceptual framework for studying collective adaptation: the process of iterative co-adaptation of cognitive strategies, social environments, and problem structures. Going beyond searching for “intelligent” collectives, we integrate research from different disciplines to show how collective adaptation perspective can help explain why similar collectives can follow very different and sometimes counter-intuitive trajectories. We further discuss how this perspective explains why successful collectives appear to have a general collective intelligence factor, why collectives rarely optimize their behaviour for a single problem, why their behaviours can appear myopic, and why playful exploration of alternative social systems can be useful. We describe different approaches for the study of collective adaptation, including computational models inspired by evolution and statistical physics. The framework of collective adaptation enables the integration and formalization of knowledge about human collective phenomena and opens doors to a rigorous transdisciplinary pursuit of important outstanding questions about human sociality.

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Section: Social Environmentsmentioning

confidence: 99%

mentioning

confidence: 99%

Beyond collective intelligence: Collective adaptation

Galešić¹,

Barkoczi²,

Berdahl³

et al. 2022

Preprint

Self Cite

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“…The historical average demand is μ, which is public information available to all supply chain members. Because foreign supplier i's trust level determines her relative confidence in the Chinese manufacturer's soft orders, we assume that T i ð0 < T i < 1Þ is an indicator of foreign supplier i's trust ( € Ozer et al, 2011). In the sequence of events (Figure 1), the manufacturer makes decisions before selling season.…”

Section: Silk Road Economic Belt Countriesmentioning

confidence: 99%

“…For example, China's factory gate pricing declined for more than three years from 2017, which reflects the price volatility in industrial practice (Chen and Reuters, 2019). In the production decision process, the manufacturer takes market price as an exogenous variable (similar assumptions by Scheele et al, 2018;€ Ozer et al, 2018) which will be determined in the selling season and decides production options. In OBOR cooperation, suppliers' distrust enlarges pressure in negotiation (Du, 2016;Massari et al, 2019).…”

Section: Silk Road Economic Belt Countriesmentioning

confidence: 99%

“…In the production decision process, the manufacturer takes market price as an exogenous variable (similar assumptions by Scheele et al, 2018;€ Ozer et al, 2018) which will be determined in the selling season and decides production options. In OBOR cooperation, suppliers' distrust enlarges pressure in negotiation (Du, 2016;Massari et al, 2019). As a result, the manufacture is able to strategically make concessions in reactions, including selling price, buy-back guarantee or quantity discount, to ensure sufficient supply.…”

Section: Silk Road Economic Belt Countriesmentioning

confidence: 99%

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Trust-based cooperation in Silk Road Economic Belt countries: strategical ordering in the assembly supply chain

Yue

Chen

et al. 2020

IJLM

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PurposeThis paper's purpose is to suggest that manufacturers strategically place soft orders for assembly materials with suppliers in Silk Road Economic Belt countries who probably doubt the realization of the soft orders placed.Design/methodology/approachFirst, a two-stage Stackelberg competition is constructed, taking into account the supplier's trust level in formulating the decision process in the assembly supply chain. The authors then provide a buyback contract to coordinate the supply chain, in which the manufacturer obtains enough supplies by sharing some of the perceived risks of not fully trusted suppliers. Furthermore, the authors conduct a numerical study to investigate the influence of trust under a decentralized case and a buyback contract.FindingsThe authors found that all supply chain partners in Silk Road Economic Belt countries experience potential losses due to not fully trusting certain conditions. The study also shows that, in Silk Road Economic Belt countries, operating under a buyback contract is better than being without one in terms of assembly supply chain performance.Research limitations/implicationsOn the one hand, the authors only consider the asymmetry of demand information without considering that of cost structure information. On the other hand, a natural extension of the paper is to integrate single-period transactions into the multi-period transaction problem setting. As all these issues require substantial effort, the authors reserve them for future exploration.Originality/valueDoing business with not-fully-trustworthy partners in Silk Road Economic Belt countries is risky, and this study reveals how trust works in global cooperation and with strategic reactions in situations of partial trust.

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Collective Intelligence and the Geopolitical Crossroads in Central-Eastern Europe. Review of the Selected Research Methods

Olszowski

Chmielowski²

2019

Internet Science

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Are distrust relationships beneficial for group performance? The influence of the scope of distrust on the emergence of collective intelligence

Cited by 24 publications

References 78 publications

Beyond collective intelligence: Collective adaptation

Beyond collective intelligence: Collective adaptation

Trust-based cooperation in Silk Road Economic Belt countries: strategical ordering in the assembly supply chain

Collective Intelligence and the Geopolitical Crossroads in Central-Eastern Europe. Review of the Selected Research Methods

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