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Innovation management in the healthcare sector has undergone significant evolutions over the last decades. These evolutions have been investigated from a variety of perspectives: clusters, ecosystems of innovation, digital ecosystems and regional ecosystems, but the dynamics of networks have seldom been analyzed under the lenses of entrepreneurial ecosystems (EEs). As identified by Cao and Shi (2020), the literature is silent about the organization of resource allocation systems for network orchestration in EEs. This article investigates these elements in the healthcare sector. It discusses the strategic role played by entrepreneurial support organizations (ESOs) in resource allocation and elaborates on the distinction between sponsored and nonsponsored ESOs in EEs. ESOs are active in network orchestration. The literature explains that ESOs lift organizational, institutional and cultural barriers, and support entrepreneurs' access to cognitive and technological resources. However, allocation models are not yet discussed. Therefore, our research questions are as follows: What is the resource allocation model in healthcare-related EEs? What is the role played by sponsored and nonsponsored ESOs as regards resource allocation to support the emergence and development of EEs in the healthcare sector?

The article offers an explanatory, exploratory, and theory-building investigation. The research design offers an abductive research protocol and multi-level analysis of seven (sponsored and nonsponsored) ESOs active in French healthcare ecosystems. Field research elaborates on semi-structured interviews collected between 2016 and 2022.

This article shows explicit complementarities between top-down and bottom-up resource allocation approaches supported by ESOs in the healthcare sector. Despite explicit originalities in each approach, no network orchestration model prevails. Multi-polar coordination is the rule. Entrepreneurs' access to critical technological and cognitive resources is based on resource allocation modalities that differ for sponsored versus nonsponsored ESOs. Emerging from field research, this research also shows that sponsored and nonsponsored ESOs manage their roles in different ways because they confront original issues about organizational legitimacy.

Beyond the results listed above, the main originalities of the paper relate to the instantiation of multi-level analysis operated during field research and to the confrontation between sponsored versus nonsponsored ESOs in the domain of healthcare-related innovation management. This research shows that ESOs have practical relevance because they build original routes for resource allocation and network orchestration in EEs. Each ESO category (sponsored versus nonsponsored) provides original support for resource allocation. The ESO's legitimacy is inferred either from the sponsor or the services delivered to end-users. This research leads to propositions for future research and recommendations for practitioners: ESO managers, entrepreneurs, and policymakers.

The basic assumption in strategic management is that consistently high performing companies are able to adapt effectively to external shocks. While adaptation of allocation of resources and its constraints have been investigated, it is important to also consider the allocation of attention. Therefore, this study seeks to examine the differences in the patterns in the allocation of resources and attention in a comparative case study with focus on Southwest Airlines. This study illustrates that the comparison of the patterns of allocation of resource and attention is very promising for the explanation of consistent superior performance.

This paper analyzes Federal Aviation Administration and American Transport Association data in order to determine actual resource allocation. Moreover, textual analysis of annual reports serves as basis for examining the patterns of allocation of attention.

The results of this paper reveal a striking divergence of allocation of resources and attention (particularly attention to differentiation) for Southwest Airlines – the consistently high performing firm in the US airline industry.

The major limitation of the current study is the fact that it is a single industry study. It would be very interesting to replicate this study in other industries.

This study shows the importance of allocation of attention for firm performance. This is particularly relevant for resource intensive industries such as the airline industry where organizational inertia makes it hard to move resources fast. Yet, attention appears to have a great potential for firm performance and can be changed more easily.

Despite great interest in allocation of resources and attention in strategy research, authors rarely combine these two perspectives. Nadkarni and Barr present a notable exception. Yet, the latter authors focus on one specific aspect of adaptation of strategic actions, i.e. the timeliness of response. The present study takes a more comprehensive view of adaptation, e.g. the respective changes in slopes of adaptation.

This paper examines binding multi-round commitments (MRCs) to the group account in a repeated voluntary contributions mechanism (VCM) game. Before each five-round interval, subjects in a four-person group are given the option to commit a portion of their endowments to the group account for each of the next five rounds. Decision rounds proceed, with each subject's commitment acting as the binding minimum of his group-account allocation for each round. The opportunity to make MRCs does not increase mean allocations to the group account relative to a control treatment. However, commitments do have implications for reciprocal behavior within groups, leading to higher outcome variances across groups in the MRCs treatment.

Allocation of individuals' resources among multiple goals is an increasingly prominent theoretical and practical issue. Despite several theoretical perspectives that highlight the potential role of affect in this resource allocation process, empirical work on the topic is quite limited with little focus on the activation dimension of affect. This study aimed to provide further insight into this issue.

The current research explored the role of the activation dimension of affect in a multiple-goal environment. Specifically, 118 individuals participated in a 21-day longitudinal study in which they reported on affect and resource allocation related to two real-life goals.

Multilevel-modeling analyses indicated that activation positively relates to allocation of resources (effort, intended effort, and intended time devoted to a goal). The results also illustrate that task-related negative valence is a significant predictor for two of the three indicators of resource allocation (intended effort was the exception).

This research informs theory and practice at the intersection of emotion and work motivation by investigating a relatively understudied dimension of affect and provides results that help clarify the role of affect during the pursuit of multiple, competing goals.

We compare allocation rules in uniform price divisible-good auctions. Theoretically, a “standard allocation rule (STANDARD)” and a “uniform allocation rule (UNIFORM)” admit different types of low-price equilibria, which are eliminated by a “hybrid allocation rule (HYBRID).” We use a controlled laboratory experiment to compare the empirical performances of these allocation rules.

We conduct three-bidder uniform price divisible-good auctions varying the different allocation rules (standard, uniform, or hybrid) and whether or not explicit communication between bidders is allowed. For the case where explicit communication is allowed we also study six-bidder auctions.

We find that prices are similar across allocation rules. Under all three allocation rules, prices are competitive when bidders cannot explicitly communicate. With explicit communication, prices are collusive, and we observe collusive prices even when collusive agreements are broken. Collusive agreements are particularly fragile when the gain from a unilateral deviation is larger, and an implication of this is that collusive agreements are more robust under STANDARD.

We do not find conclusive evidence of differences in performance among allocation rules. However, there is suggestive evidence that STANDARD may be more vulnerable to collusion.

Divisible-good uniform price auctions are used in financial markets, but it is not possible to use naturally occurring data to test how alternatives to the standard format would perform. Using laboratory methods we provide an initial test of alternative allocation rules.

It is widely believed that contrary to standard asset allocation theory, employees irrationally hold concentrated investments in company stock in their 401(k) plans thus bearing firm-specific risk that could otherwise have been diversified away (see e.g., Benartzi, 2001). However, in measuring any such lack of diversification costs, a unique tax benefit associated with such investments (available to those who choose the Net Unrealized Appreciation (NUA) strategy) has been hitherto ignored. We analyze an employee's optimal allocation of retirement assets among alternative investments, including company stock, in the presence of the NUA tax benefit. The employee has a standard power utility function and seeks to maximize expected utility from her after-tax wealth upon retirement. Based on simulations, we find that, even when company stock is stochastically dominated by investments in the market index, the employee will allocate a non-trivial part of her retirement funds to company stock for a wide range of parameter values. Consistent with empirical evidence, the allocation to company stock is greater for employees closer to retirement and when the company's stock has experienced substantial gain in value.

To determine the role of status information conveyance in a negative reward allocation setting.

Using previously published experimental data, we test the relative effects of status information conveyed by expressive and indicative status cues on the allocation of a negative reward. Further, we construct an alternative graph theoretic model of expectation advantage which is also tested to determine its model fit relative to the classic model of Reward Expectations Theory.

Results provide strong support for the conclusion that status information conveyed by expressive status cues influences reward allocations more than information conveyed by indicative cues. We also find evidence that our alternative graph theoretic model of expectation advantage improves model fit.

This research is the first to test the relative impact of expressive versus indicative status cues on the allocation of negative rewards and shows that status characteristics can have differential impacts on these allocations contingent on how characteristics are conveyed. Furthermore, the research suggests a graph theoretic model that allows for this differentiation based on information conveyance and provides empirical support for its structure in a negative reward allocation environment.

Future research is required to validate the results in positive reward situations.

The results show that an individual’s expectations are altered by varying the manner in which status information is presented, thereby influencing the construction and maintenance of status hierarchies and the inequalities those structures generate. Thus, this research has implications for any group or evaluative task where status processes are relevant.

Tooling is a common component of an industrial product’s manufacture. Specific tooling is devised to serve the fabrication of a particular product, while generic tooling can be used in the manufacture of multiple products. In the latter case, companies are confronted with the problem of fairly allocating the indirect costs of the tooling. This article studies how to allocate costs of generic tooling to single production orders.

Ten allocation methods (AMs) are described that are in principle suited to the distribution of generic tooling costs to production orders. Since the presented methods have for the most part been discussed in differing contexts, we apply them to a specified generic tooling problem for comparison. Evaluation of the various methods is based on 16 criteria. Reasoning is supported by a computational Monte Carlo simulation. Furthermore, we suggest using the Analytical Hierarchy Process (AHP) to elaborate one final proposition concerning the most preferable allocation scheme.

The article reports the single allocation rules’ performances for different allocation scenarios. The described characteristics refer to fairness, efficiency, and simplicity as well as to empty-core performance. Using AHP analysis allows for the aggregation of the rules’ criteria ratings. Thus, especially suitable allocation schemes for the problem at hand are identified.

An allocation is required for budgeting reasons and also for the definition of projects’ bottom-up sales prices. Selecting the “right” AM is important, as a suboptimal AM can result in unfair allocation vectors, which will act as incentives to stop using the common resource, potentially leading to higher total costs.

Research on the comparison of AMs is typically performed for certain purposes, such as enterprise networks, horizontal cooperative purchasing scenarios, or municipal service units. This article will augment the research evaluating AMs by introducing a novel set of evaluation criteria and by providing an in-depth comparison of AMs suited for the allocation of generic tooling costs.

This chapter focuses on examining how changes in the liquidity differential between nominal and TIPS yields influence optimal portfolio allocations in U.S. Treasury securities. Based on a nonparametric estimation technique and comparing the optimal allocation decisions of mean-variance and CRRA investor, when investment opportunities are time varying, I present evidence that liquidity risk premium is a significant risk-factor in a portfolio allocation context. In fact, I find that a conditional allocation strategy translates into improved in-sample and out-of-sample asset allocation and performance. The analysis of the portfolio allocation to U.S. government bonds is particularly important for central banks, specially in developing countries, given the fact that, collectively they have accumulate a large holdings of U.S. securities over the last 15 years.