A Study of the Internal Restructuring of a Major Organization

This project deals with a study of the internal restructuring of a major organization. It looks at customer service as a whole and how it is effected if internal communication is not at its very best. Chapter one covers the basics of good customer service and establishes that, if done correctly, good customer service positions a company for success. A key point is that good customer service stems from a positive self image within the company, among all segments of the work force; and that this self image depends on good internal communications dynamics. Chapter two reviews the literature of internal communications and how it can effect the outcomes of customer service. Chapter three focuses on two specific books that had a great deal of influence on the project\u27s results and conclusions of this project. One book is The Addictive Or1anization by Anne Wilson Schaef and Diane Fassel which views major corporations as being addictive and their employees as being the addicts . The analogy compares organizational behavior to dysfunctional family situations involving codependency. In such situations. breaking self destructive behavior patterns is difficult, because a certain comfort level of accommodation has been reached even in the face of suffering. This book provocatively develops the analogy, with destructive internal communications dynamics as the corporate drug. Schaef and Fassel\u27s book helps in analyzing the symptoms of the problem. The second book covered in chapter three, Performance Mana1ement by Aubrey C. Daniels, is more prescriptive. Daniels stresses managing people by measuring their performance while giving positive or negative feedback and setting goals along the way. Chapter four shows the results from the research done in chapters one through three and applies them to the restructuring of Brown Group, a footwear company based in Clayton Missouri. The results form a plan that analyzes Brown Group the way that it is currently structured and restructures it into an organization that can run much more smoothly and productively. Chapter five reveals the feedback that was given by the Director of Management and Staff Development at Brown Group. It covers the topics within chapter four that he did or did not agree with and his reasoning for each response. Chapter five also relates the plan to the discussions in the first three chapters

Model Predictive Control of HVAC Systems: Design and Implementation on a Real Case Study

The final aim of this work is to design, implement and test a controller on a real testbed kindly provided by KTH. The control paradigm presented in this thesis is a MPC that aims at saving energy as well as keeping the temperature and the CO2 concentration in a comfort range that guarantees the wellness of room occupants. To improve the knowledge of the plant, we also study the problem of modeling both the dynamics of of the system to be controlled and of the dedicated actuation syste

The unseen and unacceptable face of digital libraries

The social and organisational aspects of digital libraries (DLs) are often overlooked, but this paper reviews how they can affect users' awareness and acceptance of DLs. An analysis of research conducted within two contrasting domains (clinical and academic) is presented which highlights issues of user interactions, work practices and organisational social structures. The combined study comprises an analysis of 98 in-depth interviews and focus groups with lecturers, librarians and hospital clinicians. The importance of current and past roles of the library, and how users interacted with it, are revealed. Web-based DLs, while alleviating most library resource and interaction problems, require a change in librarians' and DL designers' roles and interaction patterns if they are to be implemented acceptably and effectively. Without this role change, users will at best be unaware of these digital resources and at worst feel threatened by them. The findings of this paper highlight the importance of DL design and implementation of the social context and supporting user communication (i.e., collaboration and consultation) in information searching and usage activities. © Springer-Verlag 2004

The Effects of Health Care Chatbot Personas With Different Social Roles on the Client-Chatbot Bond and Usage Intentions: Development of a Design Codebook and Web-Based Study

Background The working alliance refers to an important relationship quality between health professionals and clients that robustly links to treatment success. Recent research shows that clients can develop an affective bond with chatbots. However, few research studies have investigated whether this perceived relationship is affected by the social roles of differing closeness a chatbot can impersonate and by allowing users to choose the social role of a chatbot. Objective This study aimed at understanding how the social role of a chatbot can be expressed using a set of interpersonal closeness cues and examining how these social roles affect clients’ experiences and the development of an affective bond with the chatbot, depending on clients’ characteristics (ie, age and gender) and whether they can freely choose a chatbot’s social role. Methods Informed by the social role theory and the social response theory, we developed a design codebook for chatbots with different social roles along an interpersonal closeness continuum. Based on this codebook, we manipulated a fictitious health care chatbot to impersonate one of four distinct social roles common in health care settings—institution, expert, peer, and dialogical self—and examined effects on perceived affective bond and usage intentions in a web-based lab study. The study included a total of 251 participants, whose mean age was 41.15 (SD 13.87) years; 57.0% (143/251) of the participants were female. Participants were either randomly assigned to one of the chatbot conditions (no choice: n=202, 80.5%) or could freely choose to interact with one of these chatbot personas (free choice: n=49, 19.5%). Separate multivariate analyses of variance were performed to analyze differences (1) between the chatbot personas within the no-choice group and (2) between the no-choice and the free-choice groups. Results While the main effect of the chatbot persona on affective bond and usage intentions was insignificant (P=.87), we found differences based on participants’ demographic profiles: main effects for gender (P=.04, ηp2=0.115) and age (P<.001, ηp2=0.192) and a significant interaction effect of persona and age (P=.01, ηp2=0.102). Participants younger than 40 years reported higher scores for affective bond and usage intentions for the interpersonally more distant expert and institution chatbots; participants 40 years or older reported higher outcomes for the closer peer and dialogical-self chatbots. The option to freely choose a persona significantly benefited perceptions of the peer chatbot further (eg, free-choice group affective bond: mean 5.28, SD 0.89; no-choice group affective bond: mean 4.54, SD 1.10; P=.003, ηp2=0.117). Conclusions Manipulating a chatbot’s social role is a possible avenue for health care chatbot designers to tailor clients’ chatbot experiences using user-specific demographic factors and to improve clients’ perceptions and behavioral intentions toward the chatbot. Our results also emphasize the benefits of letting clients freely choose between chatbots

Understanding Children’s Help-Seeking Behaviors: Effects of Domain Knowledge

This dissertation explores children’s help-seeking behaviors and use of help features when they formulate search queries and evaluate search results in IR systems. This study was conducted with 30 children who were 8 to 10 years old. The study was designed to answer three research questions with two parts in each: 1(a) What are the types of help-seeking situations experienced by children (8-10 years old) when they formulate search queries in a search engine and a kid-friendly web portal?, 1(b) What are the types of help-seeking situations experienced by children (8-10 years old) when they evaluate search results in a search engine and a kid-friendly web portal?, 2(a) What types of help features do children (8-10 years old) use and desire when they formulate search queries in a search engine and a kid-friendly web portal?, 2(b) What types of help features do children (8-10 years old) use and desire when they evaluate search results in a search engine and a kid-friendly web portal?, 3(a) How does children’s (8-10 years old) domain knowledge affect their help seeking and use of help features when they formulate search queries in a search engine and a kid-friendly web portal?, 3(b) How does children’s (8-10 years old) domain knowledge affect their help seeking and use of help features when they evaluate search results in a search engine and a kid-friendly web portal? This study used multiple data collection methods including performance-based domain knowledge quizzes as direct measurement, domain knowledge self-assessments as indirect measurement, pre-questionnaires, transaction logs, think-aloud protocols, observations, and post-interviews. Open coding analysis was used to examine children’s help-seeking situations. Children’s cognitive, physical, and emotional types of help-seeking situations when using Google and Kids.gov were identified. To explore help features children use and desire when they formulate search queries and evaluate results in Google and Kids.gov, open coding analysis was conducted. Additional descriptive statistics summarized the frequency of help features children used when they formulated search queries and evaluated results in Google and Kids.gov. Finally, this study investigated the effect of children’s domain knowledge on their help seeking and use of help features in using Google and Kids.gov based on linear regression. The level of children’s self-assessed domain knowledge affects occurrences of their help-seeking situations when they formulated search queries in Google. Similarly, children’s domain knowledge quiz scores showed a statistically significant effect on occurrences of their help-seeking situations when they formulated keywords in Google. In the stage of result evaluations, the level of children’s self-assessed domain knowledge influenced their use of help features in Kids.gov. Furthermore, scores of children’s domain knowledge quiz affected their use of help features when they evaluated search results in Kids.gov. Theoretical and practical implications for reducing children’s cognitive, physical, and emotional help-seeking situations when they formulate search queries and evaluate search results in IR systems were discussed based on the results

Consumer Health Information Needs, Seeking and Searching Behavior By Rural Residents in the Kachia Grazing Reserve, with a Focus on Vector-borne Diseases

Information is considered the basic material for making decisions. People from all walks of life have information needs for business and personal use. Consumer Health Information (CHI) is an emerging form of information made accessible to the layperson. It is a simplified form of information from the types of information available to medical professionals. This study examines the health information behavior of the residents of one region in the Kachia Grazing Reserve (KGR) located in the North West of the six geopolitical zones of Nigeria. This dissertation explores the health information needs, seeking and searching behavior of the residents of selected communities that are affected by two vector-borne fly diseases in Nigeria. Insects such as flies are responsible for the transmission of diseases to humans, including trypanosomiasis, caused by the tsetse fly, and malaria, caused by mosquitos. These flies are commonly found in and affect mostly rural dwellers in Nigeria. This study investigates some of the broader contextual issues that may influence consumer health care needs as well as seeking-searching behavior. It asks participants whether they believe their health information needs are being met or not. The study applied a qualitative approach to sampling 50 adult participants. It relied on a triangulation data collection method using a questionnaire, interview instrument, and focus group discussion. NVivo version 12 was used in the data analysis to create a coding scheme following the stages of open, axial, and selective coding processes to develop a grounded theory of rural residents’ information behaviors. The findings of the research revealed various health information needs and seeking behavior the rural residents engaged in; it also revealed the factors that influenced their seeking and searching activities. Furthermore, the findings highlighted the information sources they used and the problems associated with the information-seeking and searching process. The model that was inductively derived from the grounded theory data analysis explains further in detail the strategies and processes members of the community use in their health information-seeking and health-searching behavior

Mind Economy: Dynamic Graph Analysis of Communications

Social networks are growing in reach and impact but little is known about their structure, dynamics, or users’ behaviors. New techniques and approaches are needed to study and understand why these networks attract users’ persistent attention, and how the networks evolve. This thesis investigates questions that arise when modeling human behavior in social networks, and its main contributions are: • an infrastructure and methodology for understanding communication on graphs; • identification and exploration of sub-communities; • metrics for identifying effective communicators in dynamic graphs; • a new definition of dynamic, reciprocal social capital and its iterative computation • a methodology to study influence in social networks in detail, using • a class hierarchy established by social capital • simulations mixed with reality across time and capital classes • various attachment strategies, e.g. via friends-of-friends or full utility optimization • a framework for answering questions such as “are these influentials accidental” • discovery of the “middle class” of social networks, which as shown with our new metrics and simulations is the real influential in many processes Our methods have already lead to the discovery of “mind economies” within Twitter, where interactions are designed to increase ratings as well as promoting topics of interest and whole subgroups. Reciprocal social capital metrics identify the “middle class” of Twitter which does most of the “long-term” talking, carrying the bulk of the system-sustaining conversations. We show that this middle class wields the most of the actual influence we should care about — these are not “accidental influentials.” Our approach is of interest to computer scientists, social scientists, economists, marketers, recruiters, and social media builders who want to find and present new ways of exploring, browsing, analyzing, and sustaining online social networks

Effectiveness of Data Enrichment on Categorization: Two Case Studies on Short Texts and User Movements

The widespread diffusion of mobile devices, e.g., smartphones and tablets, has made possible a huge increment in data generation by users. Nowadays, about a billion users daily interact on online social media, where they share information and discuss about a wide variety of topics, sometimes including the places they visit. Furthermore, the use of mobile devices makes available a large amount of data tracked by integrated sensors, which monitor several users’ activities, again including their position. The content produced by users are composed of few elements, such as only some words in a social post, or a simple GPS position, therefore a poor source of information to analyze. On this basis, a data enrichment process may provide additional knowledge by exploiting other related sources to extract additional data. The aim of this dissertation is to analyze the effectiveness of data enrichment for categorization, in particular on two domains, short texts and user movements. We de- scribe the concept behind our experimental design where users’ content are represented as abstract objects in a geometric space, with distances representing relatedness and similarity values, and contexts representing regions close to the each object where it is possibile to find other related objects, and therefore suitable as data enrichment source. Regarding short texts our research involves a novel approach on short text enrichment and categorization, and an extensive study on the properties of data used as enrich- ment. We analyze the temporal context and a set of properties which characterize data from an external source in order to properly select and extract additional knowledge related to textual content that users produce. We use Twitter as short texts source to build datasets for all experiments. Regarding user movements we address the problem of places categorization recognizing important locations that users visit frequently and intensively. We propose a novel approach on places categorization based on a feature space which models the users’ movement habits. We analyze both temporal and spa- tial context to find additional information to use as data enrichment and improve the importance recognition process. We use an in-house built dataset of GPS logs and the GeoLife public dataset for our experiments. Experimental evaluations on both our stud- ies highlight how the enrichment phase has a considerable impact on each process, and the results demonstrate its effectiveness. In particular, the short texts analysis shows how news articles are documents particularly suitable to be used as enrichment source, and their freshness is an important property to consider. User Movements analysis demonstrates how the context with additional data helps, even with user trajectories difficult to analyze. Finally, we provide an early stage study on user modeling. We exploit the data extracted with enrichment on the short texts to build a richer user profile. The enrichment phase, combined with a network-based approach, improves the profiling process providing higher scores in similarity computation where expectedCo-supervisore: Ivan ScagnettoopenDottorato di ricerca in Informaticaope

The drivers of Corporate Social Responsibility in the supply chain. A case study.

Purpose: The paper studies the way in which a SME integrates CSR into its corporate strategy, the practices it puts in place and how its CSR strategies reflect on its suppliers and customers relations. Methodology/Research limitations: A qualitative case study methodology is used. The use of a single case study limits the generalizing capacity of these findings. Findings: The entrepreneur’s ethical beliefs and value system play a fundamental role in shaping sustainable corporate strategy. Furthermore, the type of competitive strategy selected based on innovation, quality and responsibility clearly emerges both in terms of well defined management procedures and supply chain relations as a whole aimed at involving partners in the process of sustainable innovation. Originality/value: The paper presents a SME that has devised an original innovative business model. The study pivots on the issues of innovation and eco-sustainability in a context of drivers for CRS and business ethics. These values are considered fundamental at International level; the United Nations has declared 2011 the “International Year of Forestry”