Why Bitcoin Will Fail to Scale?

Bitcoin falls dramatically short of the scale provided by banks for payments. Currently, its ledger grows by the addition of blocks of ∼2,000 transactions every 10 minutes. Intuitively, one would expect that increasing the block capacity would solve this scaling problem. However, we show that increasing the block capacity would be futile. We analyze strategic interactions of miners, who are heterogeneous in their power over block addition, and users, who are heterogeneous in the value of their transactions, using a game-theoretic model. We show that a capacity increase can facilitate large miners to tacitly collude—artificially reversing back the capacity via strategically adding partially filled blocks in order to extract economic rents. This strategic partial filling crowds out low-value payments. Collusion is sustained if the smallest colluding miner has a share of block addition power above a lower bound. We provide empirical evidence of such strategic partial filling of blocks by large miners of Bitcoin. We show that a protocol design intervention can breach the lower bound and eliminate collusion. However, this also makes the system less secure. On the one hand, collusion crowds out low-value payments; on the other hand, if collusion is suppressed, security threatens high-value payments. As a result, it is untenable to include a range of payments with vastly different outside options, willingness to bear security risk, and delay onto a single chain. Thus, we show economic limits to the scalability of Bitcoin. Under these economic limits, collusive rent extraction acts as an effective mechanism to invest in platform security and build responsiveness to demand shocks. These traits are otherwise hard to attain in a disintermediated setting owing to the high cost of consensus. This paper was accepted by Kartik Hosanagar, information systems.

Coordination mechanisms for digital and sustainable textile supply chain

PurposeSupply chain network is complicated to manage due to the involvement of a number of agents. Formation of virtual organization using Industry 4.0 (I4.0) is an approach to improve the efficiency and effectiveness and to overcome the complexities of the channel. However, the task of managing the channel further becomes complicated after incorporating sustainability into the supply chain. To fill this gap, this paper focuses on designing of mechanism and demonstration of I4.0-based virtual organization to coordinate sustainable supply chain.Design/methodology/approachIn this paper, we model and compare I4.0-based virtual organization models using four other traditional contracts with centralized supply chain. The non-cooperative game theoretic approach has been used for the analysis of models.FindingsOur game-theoretic analysis shows that investment in I4.0 and sustainable innovation are beneficial for the overall supply chain. Our results show that linear two-part tariff contract and I4.0-based virtual organization model can perfectly coordinated with the supply chain.Research limitations/implicationsThis study consider deterministic model settings with full information game. Therefore researchers are encouraged to study I4.0-based coordination models under information asymmetry and uncertain situations.Practical implicationsThe paper includes implications for the development of I4.0-based coordination model to tackle the problems of channel coordination.Originality/valueThis study proposes I4.0-based game-theoretic model for the sustainable supply chain coordination.

Ride-Hailing Platforms: Competition and Autonomous Vehicles

Problem definition: Ride-hailing platforms, which are currently struggling with profitability, view autonomous vehicles (AVs) as important to their long-term profitability and prospects. Are competing platforms helped or harmed by platforms’ obtaining access to AVs? Are the humans who participate on the platforms—driver-workers and rider-consumers (hereafter, agents)—collectively helped or harmed by the platforms’ access to AVs? How do the conditions under which access to AVs reduces platform profits, agent welfare, and social welfare depend on the AV ownership structure (i.e., whether platforms or individuals own AVs)? Academic/practical relevance: AVs have the potential to transform the economics of ride-hailing, with welfare consequences for platforms, agents, and society. Methodology: We employ a game-theoretic model that captures platforms’ price, wage, and AV fleet size decisions. Results: We characterize necessary and sufficient conditions under which platforms’ access to AVs reduces platform profit, agent welfare, and social welfare. The structural effect of access to AVs on agent welfare is robust regardless of AV ownership; agent welfare decreases if and only if the AV cost is high. In contrast, the structural effect of access to AVs on platform profit depends on who owns AVs. The necessary and sufficient condition under which access to AVs decreases platform profit is high AV cost under platform-owned AVs and low AV cost under individually owned AVs. Similarly, the structural effect of access to AVs on social welfare depends on who owns AVs. Access to individually owned AVs increases social welfare; in contrast, access to platform-owned AVs decreases social welfare—if and only if the AV cost is high. Managerial implications: Our results provide guidance to platforms, labor and consumer advocates, and governmental entities regarding regulatory and public policy decisions affecting the ease with which platforms obtain access to AVs.

Influence of committed volunteers on helping behavior in emergency evacuations

We study how the presence of committed volunteers influences the collective helping behavior in emergency evacuation scenarios. In this study, committed volunteers do not change their decision to help injured persons, implying that other evacuees may adapt their helping behavior through strategic interactions. An evolutionary game theoretic model is developed which is then coupled to a pedestrian movement model to examine the collective helping behavior in evacuations. By systematically controlling the number of committed volunteers and payoff parameters, we have characterized and summarized various collective helping behaviors in phase diagrams. From our numerical simulations, we observe that the existence of committed volunteers can promote cooperation but adding additional committed volunteers is effective only above a minimum number of committed volunteers. This study also highlights that the evolution of collective helping behavior is strongly affected by the evacuation process.

The evolution of partner specificity in mutualisms

Mutualistic species vary in their level of partner specificity, which has important evolutionary, ecological, and management implications. Yet, the evolutionary mechanisms which underpin partner specificity are not fully understood. Most work on specialization focuses on the trade-off between generalism and specialism, where specialists receive more benefits from preferred partners at the expense of benefits from non-preferred partners, while generalists receive similar benefits from all partners. Because all mutualisms involve some degree of both cooperation and conflict between partners, we highlight that specialization to a mutualistic partner can be cooperative, increasing benefit to a focal species and a partner, or antagonistic, increasing resource extraction by a focal species from a partner. We devise an evolutionary game theoretic model to assess the evolutionary dynamics of cooperative specialization, antagonistic specialization, and generalism. Our model shows that cooperative specialization leads to bistability: stable equilibria with a specialist host and its preferred partner excluding all others. We also show that under cooperative specialization with spatial effects, generalists can thrive at the boundaries between differing specialist patches. Under antagonistic specialization, generalism is evolutionarily stable. We provide predictions for how a cooperation-antagonism continuum may determine the patterns of partner specificity that develop within mutualistic relationships.

Development of approaches to innovation transfer and intellectual property management to ensure enterprise competitiveness

The work deals with the problems of innovation transfer and intellectual property management at enterprises. An approach reasoning the choice of innovations and the type of their transfer at an enterprise has been developed, which increases the efficiency of innovation processes. For this purpose, the essence of the category “innovation transfer” regarding the micro-level was clarified and determined according to the sources of innovations. A set-theoretic model of innovation selection based on evaluating the essence of innovations, their generators (suppliers) and implementation conditions has been developed. For such an assessment, a set of criteria has been proposed, a number of the most essential conditions for introducing innovations at an enterprise have been identified, and an optimization model for the efficiency of the innovation development process has been developed. They allow making an informed choice of innovations in accordance with the needs of the enterprise. Evaluation criteria for the innovative potential are proposed and their essence is determined. Testing of the evaluation confirmed the possibility of using the proposed criteria. A model of innovation transfer, which presents the main processes and participants in the transfer of external and internal innovations has been developed, which allows enterprises to ensure a high level of organization and implementation of the transfer. Given the direct relationship between the transfer of innovations and intellectual property, an approach to improving intellectual property management at the enterprise is proposed. A number of principles of intellectual property management have been determined. The stages of intellectual property management at the enterprise are proposed as a set of specific actions determining all processes directly or indirectly related to such management, as well as those responsible for these processes and resource provision.

Awareness Growth and Belief Revision

The problem of awareness growth, also known as the problem of new hypotheses, is a persistent challenge to Bayesian theories of rational belief and decision making. Cases of awareness growth include coming to consider a completely new possibility (called expansion), or coming to consider finer distinctions through the introduction of a new partition (called refinement). Recent work has centred on Reverse Bayesianism, a proposal for rational awareness growth due to Karni and Vierø. This essay develops a "Reserve Bayesian" position and defends it against two challenges. The first, due to Anna Mahtani, says that Reverse Bayesian approaches yield the wrong result in cases where the growth of awareness constitutes an expansion relative to one partition, but a refinement relative to a different partition. The second, due to Steele and Stefánsson, says that Reverse Bayesian approaches cannot deal with new propositions that are evidentially relevant to old propositions. I argue that these challenges confuse questions of belief revision with questions of awareness change. Mahtani’s cases reveal that the change of awareness itself requires a model which specifies how propositions in the agent’s old algebra are identified with propositions in the new algebra. I introduce a lattice-theoretic model for this purpose, which resolves Mahtani’s problem cases and some of Steele and Stefánsson’s cases. Applying my model of awareness change, then Reverse Bayesianism, and then a generalised belief revision procedure, resolves Steele and Stefánsson’s remaining cases. In demonstrating this, I introduce a simple and general model of belief revision in the face of new information about previously unknown propositions.