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A critical issue in the design of routing protocols for wireless sensor networks is the efficient utilization of resources such as scarce bandwidth and limited energy supply. Many routing schemes proposed in the literature try to minimize the energy consumed in routing or maximize the lifetime of the sensor network without taking into consideration limited capacities of nodes and wireless links. This can lead to congestion, increased delay, packet losses and ultimately to retransmission of packets, which will waste considerable amount of energy. This paper presents a Minimum‐cost Capacity‐constrained Routing (MCCR) protocol which minimize the total energy consumed in routing while guaranteeing that the total load on each sensor node and on each wireless link does not exceed its capacity. The protocol is derived from polynomial‐time minimum‐cost flow algorithms. Therefore protocol is simple and scalable. The paper improves the routing protocol in (1) to incorporate integrality, node capacity and link capacity constraints. This improved protocol is called Maximum Lifetime Capacity‐constrained Routing (MLCR). The objective of MLCR protocol is to maximize the time until the first battery drains its energy subject to the node capacity and link capacity constraints. A strongly polynomial time algorithm is proposed for a special case of MLCR problem when the energy consumed in transmission by a sensor node is constant. Simulations are performed to analyzed the performance of the proposed protocols.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

The aim of this paper is to contribute to a greater understanding of non-profit organization (NPO) management control systems (MCS) and accountability in organizations providing support service for capacity constrained service users. Specifically, the paper examines the role of MCS and accountability in supporting mission realization in NPOs providing services to people with intellectual disabilities and reflects on this in the context of the COVID-19 pandemic.

The research comprised a case study of four NPOs providing services to people with intellectual disabilities in Ireland conducted prior to the global COVID-19 pandemic. The study probed management's perceptions of stakeholders and examined the manner in which the design and use of MCS and accountability processes supported mission realization.

Service users were regarded as the least powerful stakeholder and consequently the least attended to in terms of MCS and accountability processes. The absence of relational and dialogical accountability with service users is not only central to maintaining this power asymmetry but also poses a threat to mission realization. These deficits can be addressed through the integration and monitoring of internal advocacy activities into MCS and accountability processes, which, on reflection, may also mitigate some of the negative consequences for service users of isolation from external support networks in times of crisis.

This research has opened up an area for enquiry – internal advocacy – heretofore not addressed in the management accounting literature, opening up a novel vein for future research. Such research could further examine the role of internal advocacy, drawing from and adding to the research in other support service domains. A number of objectives and questions might be considered: (1) probing the level of management recognition of the role of direct engagement in advocacy activities in supporting service user agency; (2) identifying with service users and management the nature and attributes of effective advocacy activities and practices; (3) questioning how such advocacy activities and practices might be reflected in MCS; (4) identifying what service user stakeholders regard as effective accountability to them in relation to their needs and objectives; and (5) assessing the impact on service user experience and on NPO mission realization of internal advocacy activities and the monitoring and review thereof through MCS. These suggestions for future research draw attention to aspects of support service delivery that have the potential to be profoundly influential on service outcomes.

A performance management model reflecting the identified need to incorporate internal advocacy mechanisms into organizational management control systems is proposed in an effort to increase accountability of NPOs to their core mission stakeholder – service users. This model may be of value to NPO management as they move from a medical-model of care to a rights-based model for service delivery in care settings.

The paper reflects the importance of listening to the voice of vulnerable service users in NPO care settings and proposes a mechanism for embedding internal advocacy in formal management control systems and accountability processes.

In proposing an “agency” supportive relational and dialogical accountability logic for such organizations, underpinned by “internal advocacy”, this research provides theoretical and practical insights for accountability processes and the design of MCS. The findings contribute empirically, not just to the NPO management and MCS literature but also to understanding the relational interaction of service users with service organizations, and what this means in supporting service user objectives and realization of organizational mission.

The paper proposes multi‐sourcing models for optimal order allocation in newsvendor setting under supply disruption with stochastic demand where suppliers are capacity constrained.

Mathematical models are constructed to describe the stochastic single period two echelon supply chain. We first investigate the uncapacitated suppliers’ problem. Then capacity constraint is included in the model to study the effect on sourcing decision. A numerical example and its solution are included to illustrate the solution procedure. We find the solution using traditional optimization approach, genetic algorithm and simulation optimization approach.

The models capture the impact of disruption risk on optimal sourcing decision. When demand is highly uncertain the order should be place with the lowest cost suppliers in case of uncapacitated problem; whereas, it is to be appropriately split among a set of low‐cost suppliers in case of capacitated problem. Simulation optimization found to be the best solution approach for such problem.

The model is applicable for a single period short‐life cycle product.

The models can be utilized for any number of suppliers. The numerical study illustrates the impact of probability of disruption, its consequences and cost of purchase on sourcing decisions.

The ability to detect disturbances quickly as they arise in a supply chain helps to manage them efficiently and effectively. The purpose of this paper is to demonstrate the feasibility of automatically and therefore quickly detecting a specific disturbance, which is constrained capacity at a supply chain echelon.

Different supply chain echelons of a simulated four echelon supply chain were individually capacity constrained to assess their impacts on the profiles of system variables, and to develop a signature that related the profiles to the echelon location of the capacity constraint. A review of disturbance detection techniques across various domains formed the basis for considering the signature-based technique.

The signature for detecting a capacity constrained echelon was found to be based on cluster profiles of shipping and net inventory variables for that echelon as well as other echelons in a supply chain, where the variables are represented as spectra.

Detection of disturbances in a supply chain including that of constrained capacity at an echelon has seen limited research where this study makes a contribution.

The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side and demand-side constraints exhibited in the US vaccine rollout.

A queuing framework that operates under two distinct regimes is formulated to analyze service rates that represent system capacity to vaccinate (under the first regime) and hesitancy-induced throughput (under the second regime). These supply- and hesitancy-constrained regimes form the focus of the present paper, as the former reflects the inherent ability of the nation in its various jurisdictions to mobilize, whereas the latter reflects a critical area for public policy to protect the population’s overall health and safety.

The two-regime framework analysis provides insights into the capacity to vaccinate and hesitancy-constrained demand, which is found to vary across the country primarily by politics and region. The framework also allows analysis of the end-to-end supply chain, where it is found that the ability to vaccinate was likely constrained by last-mile administration issues, rather than the capacity of the manufacturing and transportation steps of the supply chain.

This study presents a new framework to consider end-to-end supply chains as dynamic systems that exhibit different regimes because of unique supply- and demand-side characteristics and estimate rollout capacity and underlying determinants at the national, state and county levels.

A comprehensive review of the literature for the problem of lot‐size scheduling (serial and assembly) considering the uncapacitated problem and complicated capacitated assembly manufacturing structure. Analyses the different solution techniques and findings for each product set.

Mechanisms to adjust planned lead times based on current work loads are desirable for time‐phased planning systems. This paper investigates the use of exponentially smoothed order flow time feedback in setting planned lead times dynamically. The system studied is a supply chain with capacity‐constrained processing stations and transit times between stations. Lot sizes are based on the minimization of flow times using queuing approximations. Both seasonal and level demand patterns with uncertainty are considered. Since both dependent and independent demands are assumed at each station, customer delivery performance depends on the distribution of inventory along the supply chain. Results show that dynamic planned lead time setting can be used effectively to control delivery performance along the supply chain. Performance is also influenced significantly by appropriate lot size selection.

This paper investigates tourism distribution channels in a small island destination with capacity constraints and contributes to understanding distribution in an emerging economy. Using the case of Fernando de Noronha in Brazil, the structures and factors underlying channel choice behaviour of tourism suppliers and intermediaries were investigated.

41 in-depth interviews were conducted with the private sector (tourism suppliers based on Fernando de Noronha and intermediaries, based on the island as well as mainland Brazil) as well as governmental organisations. A stratified purposeful sample was taken to select suppliers and data were examined based on thematic analysis.

Both direct and indirect distribution channels are used, with limited airline tickets influencing the suppliers' choice of channels in this small island and capacity-constrained destination. Many suppliers focused on relationships with destination-based ground operators. These local intermediaries are important and extremely relevant to small island destinations building an effective business network to connect the destination to geographically distant markets and intermediaries.

Limitations include the absence of air and cruise operators as interviewees.

The paper provides a comprehensive representation of the structures and analysis of tourism distribution channels in fragile small island destinations, specifically, in an emerging country context. This includes emphasising previously unexplored indirect channels of cruise ship operators and supplier's associations.