Optimal Award Scheme in Innovation Tournaments

Innovation contests within firms offer the potential to tap latent employee expertise across the organization and expand innovation beyond the core R&D teams. Still, firms undertaking an internal contest, unlike the more commonly studied external contests, incur significant opportunity costs when employees divert their efforts toward the contest (and away from their routine work). Managing this key challenge forms the focus of the current study, with the overarching question being How should firms design internal contests? Motivated by fieldwork in electronics companies, we develop an application‐driven model that explicitly captures the fundamental trade‐off between incurring greater opportunity cost (of lost routine work) and increasing participation and contest effort. Analysis of our model demonstrates that for problem types that do not need significant effort for solution generation, the optimal contest reward is non‐monotonic in both the problem uncertainty and the wage rate of the participating employees. In case of more complex problems that require contestants to exert some minimal effort, the firm uses the reward decision to restrict participation and to ensure that contestants exert the required effort. In this case, the optimal reward increases with problem uncertainty, thereby incentivizing more contestants to enter. While the firm can attempt to mitigate the loss due to opportunity costs by organizing internal contests during employee leisure time, we identify conditions under which it is still optimal to organize these contests during working hours.

Section: Production and Operations Managementsupporting

confidence: 93%

Section: Literature Reviewmentioning

confidence: 99%

Designing internal innovation contests

Nittala

Krishnan

2022

“…2016), feedback mechanism (Mihm and Schlapp 2018, Wooten and Ulrich 2017), and incentive and award structure (Ales et al. 2017, 2018a, Erat and Krishnan 2012, Körpeoğlu and Cho 2018); see Ales et al. (2018b) for a more comprehensive review for this literature.…”

Section: Inclusive Innovation: An Operations Lensmentioning

confidence: 99%

The Role of Inclusive Innovation in Promoting Social Sustainability

Kalkancı

Rahmani

Toktay

2019

This special issue implores us to address sustainability from the lens of emerging economies and the role that innovation can play in this context. We posit that, for sustainable operations research to be relevant in the context of emerging economies, it needs to incorporate social concerns and conditions of underserved populations, with an emphasis on inclusion and equity. Especially important for addressing social concerns of these populations will be product/service innovation, process/business model innovation, and supply chain innovation. We further posit that successful innovation in these areas will require collaboration of for‐profit firms with the public sector, civil society organizations, and communities. In thisstudy, we put forward “inclusive innovation” as a unifying approach that enables the collaborative integration of social issues of relevance to underserved populations in operations management decisions. We then focus on contemporary sectoral challenges in services, manufacturing, and agriculture, highlight the relevant social sustainability issues with an emphasis on those relevant to underserved populations, and point to new opportunities for research.

“…This arises from the fact that such innovation contests are organized by the clients (e.g., firms) who can determine the format of contest; cf. Ales et al (2017), and the projects are highly intellectually demanding (e.g., programming or algorithm development) with the success rate mainly depending on the effort invested by contestants. By comparison to this stream of literature, we study contest-based crowdsourcing from a different perspective by considering multiple projects with relatively simple fixed rules decided by the platforms.…”

Section: Existing Studies On Crowdsourcing Problemsmentioning

confidence: 99%

Stochastic Sequential Allocations for Creative Crowdsourcing

Tian

Shi

2022

C reative crowdsourcing is an innovative online business model in which a platform marshals independent professionals (e.g., designers) to conduct creative work projects. Typically, clients submit project requests stochastically to a platform which possesses a pool of registered designers. For each submitted project, designers decide whether to participate and attempt to submit a design, and the client either chooses a winner among all submissions, or rejects them all, based on subjective criteria. In general, platforms cannot control individual designers directly because of the nature of the freelance market, incurring possible mismatches between designers and arriving projects. To tackle the problem, we present a dynamic control policy applied to the maximum number of participants for each arrived project. Our study reveals that the optimal policy follows an inverted-U-shaped function of the project value, highlighting the importance of applying a stronger restriction on the number of participants for some sufficiently high-valued projects. In addition, the optimal policy we have developed allows the platform to gain higher rewards judiciously even when the market is more volatile. Furthermore, extensive numerical studies have been conducted to glean managerial insights. Specifically, the optimal policy becomes more beneficial even when more designers are available, which is counter-intuitive to the common-sense notion that control should be more valuable when designers are scarcer; and the optimal policy is further shown to be robust when the objective is changed from maximizing the total reward to maximizing the total number of successful projects.