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Creating a Collaborative Online Project for an MBA Core course

Description: Poster presented as part of the 2012 University Forum on Teaching & Learning at UNT. This poster discusses creating a collaborative online project for an MBA core course. Traditional face-to-face classes offer the rich interactive experience gained through collaborative group projects.
Date: March 28, 2012
Creator: Evangelopoulos, Nicholas & Jayakumar, Jay
Partner: UNT College of Business

Religious Identity and Interreligious Communications: Predicting In-Group and Outgroup Bias with Topic-Sentiment Analysis

Description: Intergroup relations and the factors affecting them constitute a subject of recurring interest within the academic community. Social identity theory suggests that group membership and the value we assign to it drives the expression of in-group favoritism and outgroup prejudice, among other intergroup phenomena. The present study examines how (ir)religious identities are related to topic-sentiment polarization in the form of positive in-group and negative outgroup bias during interreligious debates in YouTube commentaries. Drawing from the propositions of social identity theory, six hypotheses were tested. The data for the study, a product of a natural experiment, are comments posted on YouTube commentary sections featuring videos of interreligious debates between (a) Christian and atheist or (b) Christian and Muslim speakers. Using topic-sentiment analysis, a multistage method of topic modeling with latent semantic analysis (LSA) and sentiment analysis, 52,607 comments, for the Christian - atheist debates, and 24,179 comments, for the Christian - Muslim debates, were analyzed. The results offer support (or partial support) to the hypotheses demonstrating identity-specific instances of topic-sentiment polarization to the predicted direction. The study offers valuable insights for the relevance of social identity theory in real-world interreligious interactions, while the successful application of topic-sentiment analysis lends support for the more systematic utilization of this method in the context of social identity theory.
Date: August 2018
Creator: Grigoropoulou, Nikolitsa
Partner: UNT Libraries

Exploring Teachers’ Constructivist Beliefs Using Talis 2013: Approaches to Training and Development

Description: The changing landscape of demographics, technology, and diversity in the learning environment is challenging schools around the world to rethink their approaches to the implementation of high-quality teaching practices. Classroom practices are becoming more complex because educators have to ensure that their students are well-equipped with 21st century skills (e.g., Darling-Hammond, 2010; Dede, 2010; Griffin, McGaw, & Care, 2012). Educators, curriculum developers, and school administrators need to be more than experts in pedagogy. They are now required to keep up with current ideas, innovative instructional practices, and the results of a variety of educational reform efforts. Believing that teachers’ beliefs are the most important psychological construct with regard to instructional practices (Pajares, 1992) and that teachers’ beliefs are related to their choice of classroom practices and, ultimately, the students’ performance (Bybee, Taylor, Gardner, Van Scotter, Powell, Westbrook, & Landes, 2006; Staub & Stern, 2002), the author of this study utilizes the international data set of the Teaching and Learning International Study (TALIS) 2013 to examine the associations between teachers’ constructivist beliefs, their self-efficacy beliefs, professional activities, and the school principals’ instructional leadership as related to lower secondary school teachers and principals in South Korea, Finland, and Mexico. These three countries represent the high and low performers in the global index of cognitive skills and educational attainment (Pearson, 2014). An account of their educational practices will provide some insights for stakeholders in school systems across nations. Nevertheless, it is important to understand that each country has unique teaching and learning conditions, and that conclusions reached in relation to such conditions do not apply across nations. A series of hierarchical linear modeling (HLM) studies were performed for the present work to provide evidence-based information with practical implications to school administrators and educational policymakers regarding the development and implementation of leadership programs and ...
Date: August 2015
Creator: Angnakoon, Putthachat
Partner: UNT Libraries

Evaluating Semantic Internalization Among Users of an Online Review Platform

Description: The present study draws on recent sociological literature that argues that the study of cognition and culture can benefit from theories of embodied cognition. The concept of semantic internalization is introduced, which is conceptualized as the ability to perceive and articulate the topics that are of most concern to a community as they are manifested in social discourse. Semantic internalization is partly an application of emotional intelligence in the context of community-level discourse. Semantic internalization is measured through the application of Latent Semantic Analysis. Furthermore, it is investigated whether this ability is related to an individual’s social capital and habitus. The analysis is based on data collected from the online review platform yelp.com.
Date: August 2015
Creator: Zaras, Dimitrios
Partner: UNT Libraries

Sociological Applications of Topic Extraction Techniques: Two Case Studies

Description: Limited research has been conducted with regards to the applicability of topic extraction techniques in Sociology. Addressing the modern methodological opportunities, and responding to the skepticism with regards to the absence of theoretical foundations supporting the use of text analytics, I argue that Latent Semantic Analysis (LSA), complemented by other text analysis techniques and multivariate techniques, can constitute a unique hybrid method that can facilitate the sociological interpretations of web-based textual data. To illustrate the applicability of the hybrid technique, I developed two case studies. My first case study is associated with the Sociology of media. It focuses on the topic extraction and sentiment polarization among partisan texts posted on two major news sites. I find evidence of highly polarized opinions on comments posted on the Huffington Post and the Daily Caller. The highest polarizing topic was associated with a commentator’s reference on Hoodies in the context of the Trayvon Martin’s incident. My findings support contemporary research suggesting that media pundits frequently use tactics of outrage to provoke polarization of public opinion. My second case study contributes to the research domain of the Sociology of knowledge. The hybrid method revealed evidence of topical divides and topical “bridges” in the intellectual landscape of the British and the American sociological journals. My findings confirm the theoretical assertions describing Sociology as a fractured field, and partially support the existence of more globalized topics in the discipline.
Date: August 2015
Creator: Zougris, Konstantinos
Partner: UNT Libraries

Enhancing User Search Experience in Digital Libraries with Rotated Latent Semantic Indexing

Description: This study investigates a semi-automatic method for creation of topical labels representing the topical concepts in information objects. The method is called rotated latent semantic indexing (rLSI). rLSI has found application in text mining but has not been used for topical labels generation in digital libraries (DLs). The present study proposes a theoretical model and an evaluation framework which are based on the LSA theory of meaning and investigates rLSI in a DL environment. The proposed evaluation framework for rLSI topical labels is focused on human-information search behavior and satisfaction measures. The experimental systems that utilize those topical labels were built for the purposes of evaluating user satisfaction with the search process. A new instrument was developed for this study and the experiment showed high reliability of the measurement scales and confirmed the construct validity. Data was collected through the information search tasks performed by 122 participants using two experimental systems. A quantitative method of analysis, partial least squares structural equation modeling (PLS-SEM), was used to test a set of research hypotheses and to answer research questions. The results showed a not significant, indirect effect of topical label type on both guidance and satisfaction. The conclusion of the study is that topical labels generated using rLSI provide the same levels of alignment, guidance, and satisfaction with the search process as topical labels created by the professional indexers using best practices.
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Date: August 2015
Creator: Polyakov, Serhiy
Partner: UNT Libraries

Decision Makers’ Cognitive Biases in Operations Management: An Experimental Study

Description: Behavioral operations management (BOM) has gained popularity in the last two decades. The main theme in this new stream of research is to include the human behavior in Operations Management (OM) models to increase the effectiveness of such models. BOM is classified into 4 areas: cognitive psychology, social psychology, group dynamics and system dynamics (Bendoly et al. 2010). This dissertation will focus on the first class, namely cognitive psychology. Cognitive psychology is further classified into heuristics and biases. Tversky and Kahneman (1974) discussed 3 heuristics and 13 cognitive biases that usually face decision makers. This dissertation is going to study 6 cognitive biases under the representativeness heuristic. The model in this dissertation states that cognitive reflection of the individual (Frederick 2005) and training about cognitive biases in the form of warning (Kaufmann and Michel 2009) will help decisions’ makers make less biased decisions. The 6 cognitive biases investigated in this dissertation are insensitivity to prior probability, insensitivity to sample size, misconception of chance, insensitivity to predictability, the illusion of validity and misconception of regression. 6 scenarios in OM contexts have been used in this study. Each scenario corresponds to one cognitive bias. Experimental design has been used as the research tool. To see the impact of training, one group of the participants received the scenarios without training and the other group received them with training. The training consists of a brief description of the cognitive bias as well as an example of the cognitive bias. Cognitive reflection is operationalized using cognitive reflection test (CRT). The survey was distributed to students at University of North Texas (UNT). Logistic regression has been employed to analyze data. The research shows that participants show the cognitive biases proposed by Tversky and Kahneman. Moreover, CRT is significant factor to predict the cognitive bias in two ...
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Date: May 2016
Creator: Alkhars, Mohammed
Partner: UNT Libraries

Factors Influencing BI Data Collection Strategies: An Empirical Investigation

Description: The purpose of this dissertation is to examine the external factors that influence an organizations' business intelligence (BI) data collection strategy when mediated by BI attributes. In this dissertation, data warehousing strategies are used as the basis on which to frame the exploration of BI data collection strategies. The attributes include BI insightfulness, BI consistency, and the organizational transformation attribute of BI. The research population consisted of IT professionals and top level managers involved in developing and managing BI. Data was collected from a range of industries and organizations within the United States. An online survey was used to collect the data to empirically test the proposed relationships. Data was analyzed using partial least square path modeling (PLS). The results of this study suggest that there exists a positive relationship between institutional isomorphism and BI consistency. The results also indicate that there exists a positive relationship between BI consistency and BI comprehensive data collection strategy, and the organizational transformation attribute of BI and BI comprehensive data collection strategy. These findings provide a theoretical lens to better understand the motivators and the success factors related to collecting the huge amounts of data required for BI. This study also provides managers with a mental model on which to base decisions about the data required to accomplish their goals for BI.
Date: August 2010
Creator: Ramakrishnan, Thiagarajan
Partner: UNT Libraries

Creating Value by Enhancing Innovative Capability: the Role of Absorptive Capacity and Institutional Framework

Description: Innovations as a source of economic wellbeing and social prosperity has been well researched, albeit primarily done in the context of developed economies. However, of late, interest in the effect of innovation on economic performance and quality of life has been renewed as the world observes the rise of emerging economies, and at the same time, the prolonged recession in the more developed economies (i.e. North America and European countries). There has been a marked increase in the quantity and quality of research and development, spawn by innovative companies from emerging economies that are making their mark in global marketplace. These phenomena challenge the traditional concept that innovation flows from the resource rich developed countries to less developed countries, and that the latter are at a disadvantage in terms of knowledge, technology and competitiveness. Existing studies on national innovation highlight the relationships between innovative capability and its outcomes; however, few have tried to explain the determinants of a nation’s innovative capabilities. Using a sample of 95 countries and panel data analysis covering 28 years of observation, this study attempts to model the determinants of innovative capability at national level, and focuses on absorptive capacity and institutional framework as the main determinants of innovative capability. Further, this study identifies different aspects of absorptive capacity: creation and exploitation of innovation. Findings offer support on the importance of various sources of external knowledge in the creation of innovation, with FDI inflow and High Technology Export as the strongest sources. Corruption as institutional factor has negative effect on innovative capability, whereas openness shows no effect. National absorptive capacity moderates the effect of external knowledge on innovative capability, except on FDI outflow in which a negative effect on trademark application as a measure of innovative capability. The findings suggest that innovative capability and moderating role ...
Date: August 2014
Creator: Suryandari, Retno Tanding
Partner: UNT Libraries

Comparing Latent Dirichlet Allocation and Latent Semantic Analysis as Classifiers

Description: In the Information Age, a proliferation of unstructured text electronic documents exists. Processing these documents by humans is a daunting task as humans have limited cognitive abilities for processing large volumes of documents that can often be extremely lengthy. To address this problem, text data computer algorithms are being developed. Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are two text data computer algorithms that have received much attention individually in the text data literature for topic extraction studies but not for document classification nor for comparison studies. Since classification is considered an important human function and has been studied in the areas of cognitive science and information science, in this dissertation a research study was performed to compare LDA, LSA and humans as document classifiers. The research questions posed in this study are: R1: How accurate is LDA and LSA in classifying documents in a corpus of textual data over a known set of topics? R2: How accurate are humans in performing the same classification task? R3: How does LDA classification performance compare to LSA classification performance? To address these questions, a classification study involving human subjects was designed where humans were asked to generate and classify documents (customer comments) at two levels of abstraction for a quality assurance setting. Then two computer algorithms, LSA and LDA, were used to perform classification on these documents. The results indicate that humans outperformed all computer algorithms and had an accuracy rate of 94% at the higher level of abstraction and 76% at the lower level of abstraction. At the high level of abstraction, the accuracy rates were 84% for both LSA and LDA and at the lower level, the accuracy rate were 67% for LSA and 64% for LDA. The findings of this research have many strong implications for the ...
Date: December 2011
Creator: Anaya, Leticia H.
Partner: UNT Libraries

The Quest for Perfect Appearance: an Examination of the Role of Objective Self-awareness Theory and Emotions

Description: Quality of appearance is important in nature and individuals have a basic need to establish the normality of appearance to confirm their acceptability to others. In daily inter-relationships of the same species, for instance, normal-appearing members of a species group reject or kill other members who appear abnormal. In human society, appearance is considered as one of the most direct sources of information about other people, and unattractiveness is often accompanied by negative judgments, which can cause emotional distress and isolation. Accordingly, humans tend to pay great attention to their personal appearance and make improvements to enhance their self-representations. The growth of the beauty and cosmetic surgery industries is an indication of an increasing willingness to enhance physical appearance. However, despite the growing demand for cosmetic procedures, the consumer research literature on this topic is extremely sparse. In fact, little is known about the attitudinal and motivational drivers that facilitate undergoing such procedures. This dissertation enriches our understanding of factors that affect consumers’ motivation to pursue cosmetic procedures and examines the role of emotions in such decisions. To that end, objective self-awareness (OSA) theory is applied and the interplay between the state of public OSA, beauty standards, and self-conscious emotions of shame and pride is explored. The results of two experimental studies indicate that access to beauty standards coupled with the state of public OSA generates self-standard comparison thoughts that may yield self-standard discrepancies. Negative emotions experienced due to such discrepancies move individuals into a self-regulatory cycle with the purpose of discrepancy reduction and impact their motivation to undergo cosmetic procedures. Pride and shame, two central self-conscious emotions, influence self-regulatory strategies and differently impact the approach to discrepancy reduction. These findings contribute to the research advocating the role of emotions in decision making and provide more insights about self-conscious emotions ...
Date: August 2012
Creator: Yazdanparast Ardestani, Atefeh
Partner: UNT Libraries

Educational Technology: A Comparison of Ten Academic Journals and the New Media Consortium "Horizon Reports" for the Period of 2000-2017

Description: This exploratory and descriptive study provides an increased understanding of the topics being explored in both published research and industry reporting in the field of educational technology. Although literature in the field is plentiful, the task of synthesizing the information for practical use is a massive undertaking. Latent semantic analysis was used to review journal abstracts from ten highly respected journals and the New Media Consortium Horizon Reports to identify trends within the publications. As part of the analysis, 25 topics and technologies were identified in the combined corpus of academic journals and Horizon Reports. The journals tended to focus on pedagogical issues whereas the Horizon Reports tended to focus on technological aspects in education. In addition to differences between publication types, trends over time are also described. Findings may assist researchers, practitioners, administrators, and policy makers with decision-making in their respective educational areas.
Date: December 2017
Creator: Morel, Gwendolyn
Partner: UNT Libraries

The Evolution of Big Data and Its Business Applications

Description: The arrival of the Big Data era has become a major topic of discussion in many sectors because of the premises of big data utilizations and its impact on decision-making. It is an interdisciplinary issue that has captured the attention of scholars and created new research opportunities in information science, business, heath care, and many others fields. The problem is the Big Data is not well defined, so that there exists confusion in IT what jobs and skill sets are required in big data area. The problem stems from the newness of the Big Data profession. Because many aspects of the area are unknown, organizations do not yet possess the IT, human, and business resources necessary to cope with and benefit from big data. These organizations include health care, enterprise, logistics, universities, weather forecasting, oil companies, e-business, recruiting agencies etc., and are challenged to deal with high volume, high variety, and high velocity big data to facilitate better decision- making. This research proposes a new way to look at Big Data and Big Data analysis. It helps and meets the theoretical and methodological foundations of Big Data and addresses an increasing demand for more powerful Big Data analysis from the academic researches prospective. Essay 1 provides a strategic overview of the untapped potential of social media Big Data in the business world and describes its challenges and opportunities for aspiring business organizations. It also aims to offer fresh recommendations on how companies can exploit social media data analysis to make better business decisions—decisions that embrace the relevant social qualities of its customers and their related ecosystem. The goal of this research is to provide insights for businesses to make better, more informed decisions based on effective social media data analysis. Essay 2 provides a better understanding of the influence of ...
Date: May 2018
Creator: Halwani, Marwah Ahmed
Partner: UNT Libraries

Is It More Advantageous to Administer Libqual+® Lite Over Libqual+®? an Analysis of Confidence Intervals, Root Mean Square Errors, and Bias

Description: The Association of Research Libraries (ARL) provides an option for librarians to administer a combination of LibQUAL+® and LibQUAL+® Lite to measure users' perceptions of library service quality. LibQUAL+® Lite is a shorter version of LibQUAL+® that uses planned missing data in its design. The present study investigates the loss of information in commonly administered proportions of LibQUAL+® and LibQUAL+® Lite when compared to administering LibQUAL+® alone. Data from previous administrations of LibQUAL+® protocol (2005, N = 525; 2007, N = 3,261; and 2009, N = 2,103) were used to create simulated datasets representing various proportions of LibQUAL+® versus LibQUAL+® Lite administration (0.2:0.8, 0.4:0.6. 0.5:0.5, 0.6:0.4, and 0.8:0.2). Statistics (i.e., means, adequacy and superiority gaps, standard deviations, Pearson product-moment correlation coefficients, and polychoric correlation coefficients) from simulated and real data were compared. Confidence intervals captured the original values. Root mean square errors and absolute and relative biases of correlations showed that accuracy in the estimates decreased with increase in percentage of planned missing data. The recommendation is to avoid using combinations with more than 20% planned missing data.
Date: August 2013
Creator: Ponce, Hector F.
Partner: UNT Libraries

Business Intelligence Success: An Empirical Evaluation of the Role of BI Capabilities and the Decision Environment

Description: Since the concept of business intelligence (BI) was introduced in the late 1980s, many organizations have implemented BI to improve performance but not all BI initiatives have been successful. Practitioners and academicians have discussed the reasons for success and failure, yet, a consistent picture about how to achieve BI success has not yet emerged. The purpose of this dissertation is to help fill the gap in research and provide a better understanding of BI success by examining the impact of BI capabilities on BI success, in the presence of different decision environments. The decision environment is a composition of the decision types and the way the required information is processed to aid in decision making. BI capabilities are defined as critical functionalities that help an organization improve its performance, and they are examined in terms of organizational and technological capabilities. An online survey is used to obtain the data and partial least squares path modeling (PLS) is used for analysis. The results of this dissertation suggest that all technological capabilities as well as one of the organizational capabilities, flexibility, significantly impact BI success. Results also indicate that the moderating effect of decision environment is significant for quantitative data quality. These findings provide richer insight in the role of the decision environment in BI success and a framework with which future research on the relationship between BI capabilities and BI success can be conducted. Findings may also contribute to practice by presenting information for managers and users of BI to consider about their decision environment in assessing BI success.
Date: August 2010
Creator: Işik, Öykü
Partner: UNT Libraries

Accuracy and Interpretability Testing of Text Mining Methods

Description: Extracting meaningful information from large collections of text data is problematic because of the sheer size of the database. However, automated analytic methods capable of processing such data have emerged. These methods, collectively called text mining first began to appear in 1988. A number of additional text mining methods quickly developed in independent research silos with each based on unique mathematical algorithms. How good each of these methods are at analyzing text is unclear. Method development typically evolves from some research silo centric requirement with the success of the method measured by a custom requirement-based metric. Results of the new method are then compared to another method that was similarly developed. The proposed research introduces an experimentally designed testing method to text mining that eliminates research silo bias and simultaneously evaluates methods from all of the major context-region text mining method families. The proposed research method follows a random block factorial design with two treatments consisting of three and five levels (RBF-35) with repeated measures. Contribution of the research is threefold. First, the users perceived a difference in the effectiveness of the various methods. Second, while still not clear, there are characteristics with in the text collection that affect the algorithms ability to extract meaningful results. Third, this research develops an experimental design process for testing the algorithms that is adaptable into other areas of software development and algorithm testing. This design eliminates the bias based practices historically employed by algorithm developers.
Date: August 2013
Creator: Ashton, Triss A.
Partner: UNT Libraries

Towards a Dimensional Model for Community Knowledge

Description: Poster paper for the 2017 International Conference on Knowledge Management. This paper proposes a dimensional model with "aspects of a corpus, such as topic or opinion, as derived star schema dimensions." Focusing on a case study on Twitter the paper demonstrates how the derived dimensions, combined with transactional facts and derived facts can uncover "the collective tacit knowledge in Twitter communities."
Date: October 25, 2017
Creator: Shakeri, Shadi & Evangelopoulos, Nicholas
Partner: UNT College of Information

Organizational Identity and Community Values: Determining Meaning in Post-secondary Education Social Media Guideline and Policy Documents

Description: With the increasing use of social media by students, researchers, administrative staff, and faculty in post-secondary education (PSE), a number of institutions have developed guideline and policy documents to set standards for social media use. Social media platforms and applications have the potential to increase communication channels, support learning, enhance research, and encourage community engagement at PSE institutions. As social media implementation and administration has developed in PSE, there has been minimal assessment of the substance of social media guideline and policy documents. The first objective of this research study was to examine an accessible, online database (corpus) comprised of 24, 243 atomic social media guideline and policy text documents from 250 PSE institutions representing 10 countries to identify central attributes. To determine text meaning from topic extraction, a rotated latent semantic analysis (rLSA) method was applied. The second objective of this investigation was to determine if the distribution of topics analyze in the corpus differ by PSE institution geographic location. To analyze the diverging topics, the researcher utilized an iterative consensus-building algorithm.Through the maximum term frequencies, LSA determined a rotated 36-factor solution that identified common attributes and topics shared among the 24,243 social media guideline and policy atomic documents. This initial finding produced a list of 36 universal topics discussed in social media guidelines and policies across all 250 PSE institutions from 10 countries. Continually, the applied chi-squared tests, that measured expected and observed document term counts, identified distribution differences of content related factors between US and Non-US PSE institutions. This analysis offered a concrete analysis for unstructured text data on the topic of social media guidance. This resulted in a comprehensive list of recommendations for developing social media guidelines and policies, and a database of social media guideline and policy documents for the PSE sector and other related ...
Date: August 2014
Creator: Pasquini, Laura Anne
Partner: UNT Libraries

An Analysis of Educational Technology Publications: Who, What and Where in the Last 20 Years

Description: This exploratory and descriptive study examines research articles published in ten of the top journals in the broad area of educational technology during the last 20 years: 1) Educational Technology Research and Development (ETR&D); 2) Instructional Science; 3) Journal of the Learning Sciences; 4) TechTrends; 5) Educational Technology: The Magazine for Managers of Change in Education; 6) Journal of Educational Technology & Society; 7) Computers and Education; 8) British Journal of Educational Technology (BJET); 9) Journal of Educational Computing Research; and 10) Journal of Research on Technology in Education. To discover research trends in the articles published from 1995-2014, abstracts from all contributing articles published in those ten prominent journals were analyzed to extract a latent semantic space of broad research areas, top authors, and top-cited publications. Concepts that have emerged, grown, or diminished in the field were noted in order to identify the most dominant in the last two decades; and the most frequent contributors to each journal as well as those who contributed to more than one of the journals studied were identified.
Date: May 2016
Creator: Natividad Beltran Del Rio, Gloria Ofelia
Partner: UNT Libraries

Using Topic Models to Study Journalist-Audience Convergence and Divergence: The Case of Human Trafficking Coverage on British Online Newspapers

Description: Despite the accessibility of online news and availability of sophisticated methods for analyzing news content, no previous study has focused on the simultaneous examination of news coverage on human trafficking and audiences' interpretations of this coverage. In my research, I have examined both journalists' and commenters' topic choices in coverage and discussion of human trafficking from the online platforms of three British newspapers covering the period 2009–2015. I used latent semantic analysis (LSA) to identify emergent topics in my corpus of newspaper articles and readers' comments, and I then quantitatively investigated topic preferences to identify convergence and divergence on the topics discussed by journalists and their readers. I addressed my research questions in two distinctive studies. The first case study implemented topic modelling techniques and further quantitative analyses on article and comment paragraphs from The Guardian. The second extensive study included article and comment paragraphs from the online platforms of three British newspapers: The Guardian, The Times and the Daily Mail. The findings indicate that the theories of "agenda setting" and of "active audience" are not mutually exclusive, and the scope of explanation of each depends partly on the specific topic or subtopic that is analyzed. Taking into account further theoretical concepts related to agenda setting, four more additional research questions were addressed. Topic convergence and divergence was further identified when taking into account the newspapers' political orientation and the articles' and comments' year of publication.
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Date: August 2016
Creator: Papadouka, Maria Eirini
Partner: UNT Libraries

Organizational Competency Through Information: Business Intelligence and Analytics as a Tool for Process Dynamization

Description: The data produced and collected by organizations represents both challenges and opportunities for the modern firm. Business intelligence and analytics (BI&A) comprises a wide variety of information management technologies and information seeking activities designed to exploit these information resources. As a result, BI&A has been heralded as a source of improved organizational outcomes in both the academic and practitioner literature, and these technologies are among the largest continuous IT expenditures made over the last decade.Despite the interest in BI&A, there is not enough theorizing about its role in improving firm performance. Scholarly investigations of the link between BI&A and organizational benefits are scarce and primarily exploratory in nature. Further, the majority of the extant research on BI&A is techno-centric, conceptualizing BI&A primarily an organizational technical asset. This study seeks to explicate the relationship between BI&A and improved organizational outcomes by viewing this phenomenon through the lens of dynamic capabilities, a promising theoretical perspective from the strategic management discipline. In so doing, this research reframes BI&A as an organizational capability, rather than simply a technical resource. Guided by a comprehensive review of the BI&A and dynamic capabilities literature, as well as a series of semi-structured focus groups with senior-level business practitioners with BI&A experience, this study develops and tests a model of BI&A enabled firm performance. Using a snowball sample, an online survey was administered to 137 business professionals in 24 industries. The data were analyzed using partial least squares (PLS) structural equation modeling (SEM). The findings support the contention that BI&A serve as the sensing and seizing components of an organizational dynamic capability, while transformation is achieved through business process change capability. These factors influence firm financial performance through their impact on the functional performance of the firm’s business processes. Further, this study demonstrates that traditional BI&A success factors are ...
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Date: August 2015
Creator: Torres, Russell
Partner: UNT Libraries