Doing Less to Do More? Optimal Service Portfolio of Non-profits That Serve Distressed Individuals

文件夹 业务 服务(商务) 多样性(控制论) 资源(消歧) 营销 财务 计算机科学 计算机网络 人工智能
作者
Priyank Arora,Morvarid Rahmani,Karthik Ramachandran
出处
期刊:Manufacturing & Service Operations Management [Institute for Operations Research and the Management Sciences]
卷期号:24 (2): 883-901 被引量:22
标识
DOI:10.1287/msom.2021.0966
摘要

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.
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