Robert Owen Briggs

Persuasion can be a complex process. Persuaders may need to use a high degree of sensitivity to understand a persuadee’s states, traits, and values. They must navigate the nuanced field of human interaction. Research on persuasive systems often overlooks the delicate nature of persuasion, favoring "one-size-fits-all" approaches and risking the alienation of certain users. This study examines the considerations made by professional burglary prevention advisors when persuading clients to enhance their home security. It illustrates how advisors adapt their approaches based on each advisee's states and traits. Specifically, the study reveals how advisors deviate from intended and technologically supported practices to accommodate the individual attributes of their advisees. It identifies multiple advisee-specific aspects likely to moderate the effectiveness of persuasive efforts and suggests strategies for addressing these differences. These findings are relevant for designing personalized persuasive systems that rely on conversational modes of persuasion.

Multiorganizational, multistakeholder (MO-MS) collaborations that may span organizational and national boundaries, present design challenges beyond those of smaller-scale collaborations. This study opens an exploratory research stream to discover and document design concerns for MO-MS collaboration systems beyond those of the single-task collaborations that have been the primary focus of collaboration engineering research. We chose the healthcare industry as the first target for this research because it has attributes common to many MO-MS domains, and because it faces significant challenges on a global scale, like the recent COVID-19 pandemic, for which MO-MS collaboration could offer solutions, as, for example, evidenced by the rapid collaborative development and distribution of COVID-19 vaccines. To this end, we reviewed 6,609 articles to find 100 articles that offered insights about the design of MO-MS collaboration systems, then conducted 50 semi-structured interviews in two countries with expert practitioners in the field. From those sources, we derived an eleven-category set of design concerns for MO-MS collaboration systems and argue their generalizability to other MO-MS domains. We offer exemplar probe questions that designers can use to increase the breadth and depth of requirements gathering for MO-MS collaboration systems.

(2020). Special Section: The Growing Complexity of Enterprise Software. Journal of Management Information Systems: Vol. 37, No. 2, pp. 313-315.

Advances in artificial intelligence (AI) technologies have inspired businesses and researchers to identify new ways in which AI can improve our way of life. One such quest lies in giving AIs complex human capabilities-like leadership. We take the first step towards that goal and propose a pattern-based approach to leadership. We argue that leadership best practices are actually a series of mini interventions each of which results in a consistent and desired response from the followers. When codified, these repeatable interventions can serve as foundational blocks for AI algorithms. To this end, we introduce LeadLets: A pattern language that codifies named, scripted, and repeatable leadership techniques that have a predictable influence causing a purposeful effect on one or more individuals. We argue that a pattern-based approach such as LeadLets can create leadership templates that inform programing leadership behavior into AI artifacts and designing leaders development programs.

Collaboration Engineering (CE) is an approach for the design and deployment of repeatable collaborative work practices that can be executed by domain experts without the ongoing support of external collaboration professionals. Since 2001, CE has been an active and productive topic of research that has attracted scientists from different backgrounds and disciplines. CE research started with studies on ways to transfer professional collaboration expertise to novices using a pattern language called thinkLets. Subsequent research focused on the development of theories to explain key phenomena, the development of a structured design methodology, training methods, technology support, design theories, and various field and experimental studies focusing on specific aspects of the CE approach. This paper details the contributions from CE research and practice based on a literature assessment of 331 publications. It extracts the key insights from the body of CE research thus far, identifies significant areas of inquiry that have not yet been explored, and looks ahead at the CE research opportunities that are emerging as our society, organizations, technologies, and the nature of collaboration evolve.

(2019). Special Section: Engineering Artifacts and Processes of Information Systems. Journal of Management Information Systems: Vol. 36, No. 1, pp. 11-13.

California Senate Bill 1953 requires structural and nonstructural upgrades to hospital buildings to enhance resilience to seismic events. This report estimates the costs to hospitals of compliance, with a focus on the 2030 deadline.

Collaboration Engineering (CE) is an approach for the design and deployment of repeatable collaborative work practices that can be executed by practitioners themselves without the ongoing support of external collaboration professionals. A key design activity in CE concerns modeling current and future collaborative work practices. CE researchers and practitioners have used the Facilitation Process Model (FPM) technique. However, this modeling technique suffers from a number of shortcomings to model contemporary collaborative work practices. We use a design science approach to identify the main challenges with the original FPM technique, derive requirements and design a revised modeling technique that is based on the current technique enriched by BPMN 2.0 elements. This paper contributes to the CE literature by offering a revised FPM technique that assists CE-designers to capture new forms of collaborative work practices.