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.

Many knowledge‐intensive projects such as new product and software design, research, and high technology development have flexible scope and involve co‐production between a client and a vendor. In such projects, it is often challenging to estimate how much progress can be achieved within a certain time window or how much time may be needed to achieve a certain degree of progress, especially because the client and vendor often adjust their efforts as a function of the project's progress, the time until the deadline, and the incentives in place. Effective contracts should therefore be flexible in scope and foster collaboration. In this study, we characterize the collaborative work dynamics of a client and a vendor who are engaged in a multi‐state, multi‐period stochastic project with a finite deadline. We show that when the client can verify the vendor's effort, it is optimal that they both exert high effort in one of two situations: when either not enough progress has been made and the deadline is close (deadline effect), or conversely, when so much progress has been made that the project state is close to a completion state set by the client (milestone effect). Hence, in this case, progress will typically be faster when the project is about to be stopped, due to either reaching the deadline or reaching the client's desired completion state. However, when the client cannot verify the vendor's effort, the vendor is prone to free‐riding. Considering a time‐based contract that pays the vendor a per‐period fee and a fixed completion bonus, we show that the equilibrium completion state is decreasing in the per‐period fee and increasing in the bonus, justifying the use of both incentive mechanisms in practice. Moreover, we show that, under such contracts, some form of milestone effect arises in equilibrium, but the deadline effect does not. Hence, in those cases, early progress will typically lead to early project conclusion at a high state; whereas, slow progress will typically make the project drag until the deadline while still at a low state.

In knowledge-intensive projects, one of the challenges project team leaders often face is how to combine their roles of direction and contribution. In this paper, we propose a game-theoretic model of team leadership of coproductive projects and study how team leaders should combine their directing and contributing efforts depending on the team and project characteristics. Our analysis reveals that two types of team leadership approaches arise in equilibrium, namely, “participatory” team leadership, under which the team leader gives the team members full discretion on their choice of effort, and “directive” team leadership, under which the team leader demands team members exert higher effort than what they would choose to exert voluntarily. We find that directive team leadership is optimal when the team members have low incentives, that is, when their rewards are low, the size of the team is large, or failure is not too costly (e.g., continuation is possible); otherwise, participatory team leadership is optimal. Moreover, we show that a higher degree of effort complementarity (as in innovative projects) leads to greater alignment between the team leader’s and team members’ contributing efforts, which, under directive team leadership, also implies greater alignment between the team leader’s directing and contributing efforts. Finally, the team leader should set the team size and team members’ rewards in a way that accentuates the difference between the two team leadership approaches. That is, under directive team leadership, she should set a large team size and offer the team members low rewards whereas under participatory team leadership she should set a small team size and offer the team members high rewards. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2911 . This paper was accepted by Ashish Arora, entrepreneurship and innovation.

Problem definition: Many nonprofit organizations (NPOs) serve distressed individuals who seek relief from hardships such as domestic abuse or homelessness. These NPOs aim to maximize social impact by allocating their limited amount of resources to various activities. Academic/practical relevance: NPOs that serve distressed individuals face a complex task because their clients are often unable to articulate their specific needs. As a result, NPOs are driven to not only offer a variety of services to fulfill different needs, but also engage in advisory activities to minimize mismatches between services clients receive and their true needs. Methodology: We develop a model to study an NPO’s service portfolio and effort allocation decisions under resource constraint. Clients’ progress from distress to resolution is stochastic and depends on the NPO’s efforts in different stages of the service offering. Results: We show that it is optimal for resource-constrained NPOs to offer fewer services and invest more in advisory activities when different types of clients are not evenly mixed in the population, when delays in achieving resolution can significantly blunt the social impact created, when the loss of impact due to not serving a fraction of clients is low, or when there is a limited amount of earmarked funds. Otherwise, it is optimal for NPOs to diversify their service offerings and invest less in advisory activities. Managerial implications: Many NPOs are drawn to maximize the number of clients they serve by increasing the number of services they offer. However, we show that, depending on the characteristics of clients and services, NPOs might be able to generate higher social impact by prioritizing the speed of resolution rather than focusing on the number of clients who achieve resolution. We also present a practical application of our model in the context of domestic abuse.

In many contexts such as product design and development, advertising, and scouting for technical solutions, clients seek the expertise of external providers to generate innovative solutions for their business problems. Because innovation projects are beset with uncertainty, they often require multiple iterations of ideation and evaluation. Although some clients make a commitment to take the first feasible solution from the provider, other clients retain the flexibility to seek more solutions until they decide to stop the project. Which of these policies is the better way to delegate an innovation project? To answer this question, we develop game-theoretic models that capture two salient aspects of delegated innovation projects: a deadline for the project and dynamic effort adjustment by the provider. We show that the flexible stopping policy, despite its intuitive appeal, may not always benefit the client. Specifically, the committed stopping policy is optimal when the provider is highly capable of generating solutions and when the client’s cost of evaluating solutions is in an intermediate range. In such situations, the committed stopping policy provides a stronger incentive to the provider to exert costly effort early on, which improves the quality of initial solutions. Considering endogenous payments, we show that the committed policy not only mitigates the provider’s tendency to postpone effort but also does so with a smaller payment. This paper was accepted by Serguei Netessine, operations management.