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1. Process Modeling in Humanitarian Settings: A Case Study and Lessons Learned

   Purao, Sandeep; Garfield, Monica (April 2020, Proceedings of the 28th European Conference on Information Systems (ECIS))

   null (Ed.)

   In spite of significant prior work, few scholars have addressed the unique problems of business process modelling in humanitarian settings. We surface and explore these challenges by treating the ‘guest intake process’ at homeless shelters as an exemplar. In most cities, the homeless shelters are a part of the ecosystem of care that includes hospitals, training agencies, housing agencies and others to support homeless individuals. The exemplar we have chosen represents the first line of defence for the homeless guests: the Intake practice at a homeless shelter, a process that remains fairly knowledge-intensive. Our work follows a collaborative research approach, working with the largest homeless shelter in the region. We conduct observations and interviews at the shelter to construct process models with the Petri Net formalism, followed by analytical experimentation. Lessons learned from the work are compared against prior research in modelling of knowledge-intensive processes. We find that process modelling in humanitarian settings such as homelessness remains fraught with problems. We identify new directions, where prior work in knowledge-intensive processes may require extensions in response to the unique nature of work in humanitarian settings. The paper elaborates these findings, illustrates with authentic examples, and outlines possibilities for future research and implications for practice 

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2. Predicting the Slide to Long-Term Homelessness: Model and Validation

   https://doi.org/10.1109/CBI.2019.00011  

   Purao, Sandeep; Garfield, Monica; Gu, Xin; Bhetwal, Prakash (July 2019, 2019 IEEE 21st Conference on Business Informatics (CBI))

   null (Ed.)

   In spite of numerous programs and interventions, homelessness remains a significant societal concern. Long-term homelessness is particularly problematic because it can be increasingly difficult to escape from, and because it represents a continuous drain on societal resources. This paper develops a model for predicting long-term homelessness in response to a simple question: if an individual becomes homeless, what influences the individual's slide to long-term homelessness? The data we analyze to answer the question comes from the City of Boston. The model points to race, veteran status, disability, and age as key factors that predict this slide. The paper describes and illustrates the model along with problems encountered in data preparation and cleansing, prior scholarly work that helped to shape our decisions, and collaboration with participants in the ecosystem for homeless care that complemented the model-building effort. The results are important because they point to possible policy interventions (programs and funding) and process improvements (at homeless shelters) to mitigate this slide. 

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3. Dementia and mild cognitive impairment screening in an emergency homeless shelter

   https://doi.org/10.1002/alz.13763  

   Ross, Heather M; Dzenga, Primrose; Myers, Martha; Squires, Alisa; Duncan, Stephanie; Caradine, Jamilyn; Scharf, Phillip; Bowman, Diana M (May 2024, Alzheimer's & Dementia)

   Abstract INTRODUCTIONOlder adults represent the fastest growing segment of the homeless community. Little is known about the prevalence of dementia and mild cognitive impairment (MCI) in this population. METHODSDementia and MCI screening using the Montreal Cognitive Assessment (MoCA) was incorporated into the standard senior evaluation for adult clients aged ≥ 55 in a large emergency homeless shelter. RESULTSIn a 6‐week period, 104 of 112 (92.9%) assessments were positive for dementia or MCI using a standard cutoff of 26, and 81 (72.3%) were positive using a conservative cutoff of 23. There was no significant difference in MoCA scores based on sex or education level, and no significant correlation between age and MoCA score. DISCUSSIONOlder adults experiencing homelessness may have a high likelihood of dementia or MCI. Routine MoCA screening in older adults experiencing homelessness is feasible and can help to identify services needed to successfully exit homelessness. 

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4. The effects of early rearing experiences on mutual eye gaze among captive olive baboons ( Papio anubis )

   https://doi.org/10.1002/dev.22420  

   Achorn, Angela M.; Mulholland, Michele M.; Hopkins, William D. (September 2023, Developmental Psychobiology)

   Abstract Among human and nonhuman primates, mutual eye gaze (MEG) and gaze following are believed to be important for social cognition and communicative signaling. The goals of this study were to examine how early rearing experiences contribute to individual variation in MEG and to examine the potential role of genetic factors underlying this variation. Subjects included 93 female and 23 male baboons (Papio anubis) ranging from 3 to 20 years of age. Within the sample, there were 55 mother‐reared (MR) and 61 nursery‐reared (NR) baboons. MEG was assessed in four 60‐s test sessions. For each session, the duration, frequency, and bout length were recorded. Mean values were then calculated for each individual from the four sessions. A multivariate analysis of covariance revealed an overall significant main effect for rearing. Subsequent univariate analyses revealed significant rearing effects on mean bout length, but not mean duration or mean frequency, with MR baboons having longer bout lengths compared to NR baboons. Furthermore, mean bout length was found to be significantly heritable. These results indicate that rearing experiences, and to a small extent, genetic factors, affect patterns of mutual eye gaze ‐ in particular, bout length. These results differ from previous findings in MR and NR chimpanzees, further suggesting that rearing may impact MEG in a species‐specific manner that reflects the function of gaze in different primate species. 

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5. Navigating Change: Exploring Gig and Taxi Drivers’ Perceptions of Autonomous Vehicles and Their Influence on Continuance Intentions

   https://doi.org/10.1177/10690727251363579  

   Watson, Gwendolyn Paige; Van_Fossen, Jenna A; Schuster, Amy M; Agrawal, Shubham; Tidwell, Michael L; Cotten, Shelia R (August 2025, Journal of Career Assessment)

   This exploratory sequential mixed-methods paper explores the relationship between gig and taxi drivers’ perceptions of autonomous vehicles (AVs) and their continuance intentions. Drawing from the Career Construction Model of Adaptation, we examined the relationship between drivers’ expectations about AV-related job changes and their intentions to stay or leave their driving role upon the integration of AVs. In Study 1, we collected qualitative data from gig and taxi drivers (N= 69) in 24 focus groups. In Study 2, we administered a survey to gig and taxi drivers (N= 496). The thematic analysis in Study 1 revealed how drivers expected the onset of AVs to positively and negatively impact their job (changes to work stress, safety, job enjoyment, etc.). These expectations influenced their decisions to remain in or leave their jobs. Multivariate regression in Study 2 showed that multiple factors identified in Study 1 were related to continuance intentions, with some being “retention factors” (related to intentions to stay) and others being “turnover factors” (related to intentions to leave). Our findings contribute to the evolving discourse on the impact of new technologies on continuance intentions by offering theoretical and practical implications in careers and vocational behavior. 

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