More than ever, corporations face pressure to act beyond their fiduciary duties to shareholders and regulatory requirements to reduce their environmental impact and improve social conditions, yet frequently produce empty symbolic measures with no benefit to societal welfare or their own financial performance. This research program examines both external incentives for firms to engage in strategic provision of social and environmental goods and information strategies to harness sustainability motivations and influence perceptions among employees and other stakeholder groups. The dissertation consists of four chapters, each comprising a standalone empirical research study grounded in strategic management, economics, and behavioral theories. The first two studies use field experimental methods to examine the tendency for individuals to alter attitudes and behavior in response to information about relevant peers; the first study in a residential community and the second in a corporate workplace. The third study extends these behavioral phenomena to corporations, evaluating the degree to which more profitable or more rivalrous industry peers influence firms’ engagement in corporate social responsibility initiatives. The final study examines microdata contained within a prominent third-party corporate greenhouse gas emissions disclosure program, finding evidence of widespread reporting inconsistencies that suggest systematic efforts by companies to mislead stakeholders about actual carbon management performance. The outcomes of this research program inform corporate strategies for leveraging social and environmental goods for improved financial performance --- the triple bottom line --- and policy prescriptions to enhance incentives for companies to provide truthful disclosures of environmental performance.

Software for language documentation has a long and successful history, but challenges remain. In this work I describe my efforts to provide a path toward reinvigoration of software design for language documentation, one which equips linguists to participate more directly in designing software for their own workflows. I begin with the description of a simple, extensible data model for all the major data types used in language documentation. I then show how the standardized, well- tested technology that powers modern web browsers can serve as the basis for novel interfaces which are nonetheless closely linked to the terminology and descriptive systems in which linguists are trained.