Exploring Supervisory Needs of First-Generation Professionals Working in Higher Education

As first-generation students enter the workforce and traverse through their careers, their work supervisors are solidly positioned to positively influence their experiences. There is very little literature to be found that addresses the professional experiences of first-generation professionals in relation to their supervisors. The purpose of this exploratory study was to learn, directly from first-generation professionals working in higher education, what they believe they need from their supervisors to support their well-being and success. This research also sought to discover how important participants thought that each need statement was, as well to gain insight to what extent the identified needs are being met. This study utilized a web-based concept mapping methodology that employed both qualitative and quantitative data collection and analysis. The findings of this study indicate that first-generation professionals have identified six need areas that supervisors can address to support their well-being and success. These are (a) Professional Growth and Development; (b) Institutional Onboarding; (c) Guidance and Understanding; (d) Communication and Feedback; (e) Humanity; and (f) Cultural Intelligence. This study contributes to the field of practice in higher education because it has empowered first-generation professionals to identify their unique needs specific to supervision. Equally important, garnering this information from first-generation professionals better informs supervisors on what this population needs, and offers suggestions on how these needs can be met. This dissertation is available in open access at AURA (https://aura.antioch.edu) and OhioLINK ETD Center (https://etd.ohiolink.edu)

Graph Theoretical Analysis of the Dynamic Lines of Collaboration Model for Disruption Response

The Dynamic Lines of Collaboration (DLOC) model was developed to address the Network-to-Network (N2N) service challenge found in e-Work networks with pervasive connectivity. A variant of the N2N service challenge found in emerging Cyber-Physical Infrastructures (CPI) networks is the collaborative disruption response (CDR) operation under cascading failures. The DLOC model has been validated as an appropriate modelling tool to aid the design of disruption responders in CPIs by eliciting the dynamic relation among the service team when handling service requests from clients in the CPI network

The bridge of dreams::Towards a method for operational performance alignment in IT-enabled service supply chains

Concerns on performance alignment, especially on business-IT alignment, have been around for three decades. It is still considered to be one of the most important driving forces for business success, as well as one of the top concerns of many practitioners and organizational researchers. It is also found to be a major issue in two thirds of digital transformation projects. Many attempts from researchers in diverse disciplines have been made to tackle this issue. Unfortunately, they have been working separately and the research appears in various forms and names. This dissertation presents a piece of interdisciplinary research that focuses on identifying operational performance alignment issues, discovering and assessing their root causes with attention to the dynamics in operating IT-enabled service supply chain (SSC). It makes a modest contribution by providing a communication-centred instrument which can modularize complex SSC in terms of a hierarchically-structured set of services and analyze the performance causality between them. With a special focus on the impact of IT, it makes it possible to monitor and tune various performance issues in SSC. This research intends to provide a solution-oriented common ground where multiple service research streams can meet together. Following the framework proposed in this research, services, at different tiers of an SSC, are modelled with a balanced perspective on both business, technical service components and KPIs. It allows a holistic picture of service performances and interactions throughout the entire supply chain to be viewed through a different research lens and permits the causal impact of technology, business strategy, and service operations on supply chain performance to be unveiled

Higher education planning for a strategic goal with a concept mapping process at a small private college

Faculty, staff, and administrators at a small independent college determined that planning with a Concept Mapping process efficiently produced strategic thinking and action plans for the accomplishment of a strategic goal to expand experiential learning within the curriculum. One year into a new strategic plan, the college enjoyed enrollment growth as one indicator of the success of the Strategic Plan. However, no progress on the strategic goal to expand experiential learning was evident. Planning literature cautioned planners to adapt planning techniques to fit the particular traditions and expectations of the individual campus. Should a planner advise administrative intervention as a hierarchical approach to planning might indicate, or would an alternate planning model, such as a Concept Mapping process better engage key leaders to devise strategy? The college opted to invite local experiential learning experts and practitioners to work together in a four meeting structured planning process. The participatory and democratic aspects of the Concept Mapping process (Trochim, 1989) fit the traditions of the campus, as did the group component. Qualitative data (the key leaders' brainstormed ideas) and quantitative data (key leaders' sorting and rating of those ideas) provided input for multivariate analyses (multidimensional scaling and hierarchical cluster analysis). The analyses produced visual displays or maps to show the collective result of the groups' input. The visual displays aided group discussion and decision-making to prioritize actions related to the strategic issue of expanding experiential learning. This process produced a Concept Map of strategic action areas supplemented by specific action plans to address the goal of the expansion of experiential learning for students

Profiling the news spreading barriers using news headlines

News headlines can be a good data source for detecting the news spreading barriers in news media, which may be useful in many real-world applications. In this paper, we utilize semantic knowledge through the inference-based model COMET and sentiments of news headlines for barrier classification. We consider five barriers including cultural, economic, political, linguistic, and geographical, and different types of news headlines including health, sports, science, recreation, games, homes, society, shopping, computers, and business. To that end, we collect and label the news headlines automatically for the barriers using the metadata of news publishers. Then, we utilize the extracted commonsense inferences and sentiments as features to detect the news spreading barriers. We compare our approach to the classical text classification methods, deep learning, and transformer-based methods. The results show that the proposed approach using inferences-based semantic knowledge and sentiment offers better performance than the usual (the average F1-score of the ten categories improves from 0.41, 0.39, 0.59, and 0.59 to 0.47, 0.55, 0.70, and 0.76 for the cultural, economic, political, and geographical respectively) for classifying the news-spreading barriers.Comment: arXiv admin note: substantial text overlap with arXiv:2304.0816

Social and Semantic Contexts in Tourist Mobile Applications

The ongoing growth of the World Wide Web along with the increase possibility of access information through a variety of devices in mobility, has defi nitely changed the way users acquire, create, and personalize information, pushing innovative strategies for annotating and organizing it. In this scenario, Social Annotation Systems have quickly gained a huge popularity, introducing millions of metadata on di fferent Web resources following a bottom-up approach, generating free and democratic mechanisms of classi cation, namely folksonomies. Moving away from hierarchical classi cation schemas, folksonomies represent also a meaningful mean for identifying similarities among users, resources and tags. At any rate, they suff er from several limitations, such as the lack of specialized tools devoted to manage, modify, customize and visualize them as well as the lack of an explicit semantic, making di fficult for users to bene fit from them eff ectively. Despite appealing promises of Semantic Web technologies, which were intended to explicitly formalize the knowledge within a particular domain in a top-down manner, in order to perform intelligent integration and reasoning on it, they are still far from reach their objectives, due to di fficulties in knowledge acquisition and annotation bottleneck. The main contribution of this dissertation consists in modeling a novel conceptual framework that exploits both social and semantic contextual dimensions, focusing on the domain of tourism and cultural heritage. The primary aim of our assessment is to evaluate the overall user satisfaction and the perceived quality in use thanks to two concrete case studies. Firstly, we concentrate our attention on contextual information and navigation, and on authoring tool; secondly, we provide a semantic mapping of tags of the system folksonomy, contrasted and compared to the expert users' classi cation, allowing a bridge between social and semantic knowledge according to its constantly mutual growth. The performed user evaluations analyses results are promising, reporting a high level of agreement on the perceived quality in use of both the applications and of the speci c analyzed features, demonstrating that a social-semantic contextual model improves the general users' satisfactio