Using trust-based philanthropy with community-based organizations during the COVID-19 pandemic

Community-based organizations (CBOs) fill a critical role in acting as public health partners and trusted resources for their communities, especially in an emergency. The CDC Foundation, an independent, nonprofit organization, used trust-based philanthropy to manage more than 110 COVID-19 grants focused on equitable vaccine information, outreach, and access. The CDC Foundation team uses a trust-based philanthropy paradigm by applying five out of six of the grantmaking practices: do the homework; simplify and streamline paperwork; be transparent and responsive; solicit and act on feedback; and offer support beyond the check. By applying trust-based philanthropy practices, the CDC Foundation is empowering CBOs through flexible grant management and more equitable power dynamics as grantee and grantor. This has been essential to CBOs in their efforts of tackling health inequities during the COVID-19 pandemic and improving community resilience. Lessons learned will inform future collaborations with CBOs where the power dynamics are shared.     

Exploring fundraising executives' careers in arts and culture: The role of tenure and career switching

Fundraisers play a crucial role in helping arts and culture organizations obtain the financial resources they need to carry out their missions and support their causes. However, research on fundraisers' careers is still in its infancy. As the profession gains importance, understanding the main motivating factors of fundraisers' career paths is key. This study investigates the effects of three variables that emerged as relevant motivations for fundraiser careers, that is, education, career promotion and sector experience, on fundraising executives' tenure and career switching. In addition, this research identifies profiles of fundraising executives in the arts and culture organizations in the United States. Moreover, this study explores the role of non-profit orientation as a moderator of the relationship between career switching and tenure, and parallel titles as a moderator of the relationship between sector experience and tenure. Managerial implications are outlined.     

Detection of potential customers’ empathy behavior towards customers' reviews

The aim of the current study is to identify potential customers' empathy behavior and their behavioral reactions based on appraisal and stimulus–organism–response (SOR) theories to customers' reviews of financial services firms using lexicon-based unsupervised learning techniques. After filtering, we obtained 30263 reviews from the Yelp dataset of financial service companies. We examined the connections between several sorts of emotional dimensions and different types of behavioral reactions of potential consumers using lexicon-based unsupervised machine learning methods. Our findings show that the various types of customer sentiment have a significant impact on potential customers' emotional experiences on social media platforms, prompting them to behave differently. Furthermore, potential consumers' reactions to the customers' reviews varied according to their seven emotional aspects. The study is the first to examine the impact of potential customers' empathetic behavioral reactions on customers' evaluations using lexicon-based unsupervised learning techniques.     

A processing fluency perspective on overhead aversion: How much is too much?

Overhead aversion has afflicted the nonprofit sector in recent decades. Yet, questions remain regarding how high is too high from a donor perspective and at what level overhead expenses just “feel right.” Using processing fluency as a theoretical foundation, the central purpose of this research was to investigate whether a nonprofit overhead ratio fluency level exists that significantly reduces both donation likelihood and nonprofit perceptions. Results from two studies show that a 25% overhead ratio appears to be the proximate ceiling regarding what fluently fits within a potential donor's schema for acceptance. Overhead ratios exceeding this threshold tended to decrease donation likelihood and nonprofit perceptions in a relatively stable manner. Moreover, the 25% threshold seems most relevant to human and animal causes and not as relevant to arts and cultural nonprofits such as museums. The results suggest that donors have a preconceived overhead ratio limit. Nonprofits that exceed that threshold are in danger of deterring donors. If nonprofit overhead ratios exceed the donor fluency threshold, nonprofit managers should consider distinct promotional strategies that entice donors and diminish overhead aversion effects.     

Examining the effect of IMF conditionality on natural resource policy

Can International Monetary Fund (IMF) lending improve natural resource governance in borrowing countries? While most IMF agreements mandate policy reforms in exchange for financial support, compliance with these reforms is mixed at best. The natural resource sector should be no exception. After all, resource windfalls enable short-term increases in discretionary spending, and office-seeking politicians are often unwilling to forgo this discretion by reforming the oil, gas, or mining sector. I investigate how and when borrowers go against their political interests and establish natural resource funds—a tool often promoted by the IMF—in the wake of a loan agreement. Using text analysis, statistical models, and qualitative evidence from natural resource policy and IMF conditionality for 74 countries between 1980 and 2019, I show that borrowers under an IMF agreement are more likely to create or regulate a resource fund, particularly if the agreement includes binding conditions that highlight the salience of natural resource reforms. This study contributes to extant research by proposing a new method to extract information from IMF conditions, by introducing a novel dataset on country-level natural resource policy, and by identifying under what circumstances international reform efforts can help combat the resource curse.     

混合型组织的可持续成长：多重紧张的战略响应

本文从混合型组织的“多重紧张识别-多重紧张影响效应-多重紧张的战略响应”这一逻辑链条出发，建构混合型组织紧张表现形式的钻石模型，识别出以使命紧张和制度紧张为表现形式的本源性紧张和以战略紧张、治理紧张、运营紧张和身份紧张为表现形式的引致性紧张。在此基础上，提出紧张度对混合型组织可持续成长影响效应的倒U型关系，认为恶性紧张容易引发单向性使命漂移、内外部合法性冲突、组织治理失灵、扩展性受限等组织脆弱性问题，良性紧张则可以激发组织创新性、促进制度逻辑重构并促进组织身份制度化，有利于组织的可持续成长。针对混合型组织出现的多重紧张，本文结合紧张度和混合元素性质认知两个维度，拓展性地提出针对“紧张”的适度竞争、适当激发、分离战略、整合战略和弹性战略五种响应战略，并基于紧张形式与组织类别建立针对恶性紧张的响应战略适配矩阵。     

关于国际科技组织议题设置的几点思考

本文以中国科协及所属全国学会加入的具有代表性的国际科技组织为研究对象，通过搜集梳理其关注的议题，总结归纳并分析了议题特点。本文认为在国际科技组织中设置长期议题应具备国际视角与专业视野、关注人类福祉与共同利益、围绕组织建设与标准制定，设置短期议题应关注热点事件与全球短期发展目标，长短期议题均应关注跨学科的综合研究问题。     

中国科协英文网国际传播能力提升研究

本文从中央媒体头部效应明显、科技类行业媒体积极探索和高影响力平台渠道较少三方面分析了我国科技创新国际传播能力现状。在此基础上，从受众和访问量分析、栏目设置、内容产品质量和访问体验四个方面分析总结了中国科协英文网国际传播能力现状。进而从提高汉英新闻编审能力、做好主体本位表达、引领全国学会英文网站发展和推出“中国科学家”品牌栏目四个方面对已有成功经验进行总结凝练并确定下阶段着力提升的重点之处。基于以上分析，为提升中国科协英文网国际传播能力、助推中国科协英文网长足发展和让世界了解并理解中国科技群团等目标给出建议。     

Emotional and the normative aspects of customers’ reviews

The goal of the current research is to investigate the link between the emotional aspects of hotel and travel organization customers' reviews and their normative (e.g., star rating) rankings. After filtering, the Yelp dataset generated 3,47,803 hotel and travel company reviews. Following the purification of user reviews, we used an unsupervised machine learning technique-based NRC Emotion Lexicon to study the relationships between various emotional aspects of reviews and their normative values (e.g., star rating) for the review. Customers express different sorts of feelings for different types of emotional aspects, forcing them to assign different stars, according to the study's findings. The study is the first to use a lexicon-based unsupervised learning approach to look into the emotional aspects of hotel and travel organization reviews and associated normative (e.g., star rating) rankings.     

Predictive analytics and centralization of authority

We examine the relation between plant-level predictive analytics use and centralization of authority for more than 25,000 manufacturing plants using proprietary US Census data. We focus on headquarters' authority over plants through delegation of decision-making and design of performance-based incentives. We find that increased predictive analytics use is associated with reduced delegation of decision-rights to local managers, increased centralization of control over data gathering and reduced plant managerial payrolls. In terms of incentives, predictive analytics use is associated with more accurate targets and tighter linkages between rewards to workers (performance-based bonuses, promotions and firings) and measured performance. Overall, our findings suggest that predictive analytics use is associated with increased centralization of authority in headquarters.