Information Systems & Operations Management

College of Business

 

Chair Gregory Frazier

 

Web wweb.uta.edu/insyopma/

Email insy.om@uta.edu

Phone 817.272.3502

Fax 817.272.5801

 

535 Business Building

Degrees / Certificates

Master’s Degrees

Information Systems, M.S.

Doctoral Degrees

Information Systems (Business Administration), Ph.D.

Mathematical Sciences, Information Systems, Ph.D.

Graduate Faculty

Professor

Revenor Baker

Mark Eakin

Gregory Frazier

Radha Mahapatra

M K Raja

Craig Slinkman

James Teng

Mary Whiteside

Associate Professor

Alan Cannon

Sridhar Nerur

Edmund Prater

Riyaz Sikora

Jingguo Wang

Jie Zhang

Senior Lecturer

Carolyn Davis

Graduate Advisors

Carolyn Davis

Information Systems, M.S.

Radha Mahapatra

Information Systems (Business Administration), Ph.D.

Department Information

Courses

 

Department Information

Objective: Master of Science in Information Systems

Objective: Ph.D. in Business Administration Program

Admission: M.S.I.S. Program

Degree Requirements

 

Objective: Master of Science in Information Systems

The objective of the Master of Science degree in Information Systems is to provide qualified students with both a general knowledge of business and a specialized knowledge of information systems. Students are exposed to the theory, research, and practical applications of numerous information systems areas including management information systems, database management systems, systems analysis and design, and data communications; and may take electives in distributed systems, information resource management, general systems concepts, electronic commerce, ERP, decision support systems, problem formulation, computer science, management sciences, research, and other related fields. The program is designed to prepare students for information systems careers in government and nonprofit organizations as well as in business and industry.

 

Objective: Ph.D. in Business Administration Program

The objective of the Ph.D. degree in Business Administration (with majors in information systems, operations management, or business statistics) is primarily to develop scholars with an ability to teach and conduct independent research. This is accomplished through a combination of rigorous coursework and research activities. This course provides fundamental knowledge in the various areas of information systems, and offers insights into research topics of interest to IS researchers. The research interests of our INSY faculty members encompass technical, managerial, and organizational issues dealing with the development and deployment of information systems.

For a concentration in Operations Management (OPMA), coursework addresses various areas of the field, such as supply chain management, service operations, quality management, and inventory management. The goal of the OPMA Ph.D. program is to provide students with a balanced set of research methods and concepts to better understand and analyze operational problems and issues. Research approaches include empirical methods, conceptual techniques, and modeling.

For a concentration in Business Statistics (STAT), coursework can be taken in a wide variety of statistical areas focusing on different statistical approaches and techniques. Some STAT coursework can be taken from different departments across the university, as appropriate for the student’s interests. The goal of the STAT Ph.D. program is to provide students with fundamental knowledge of common statistical approaches and techniques used in business analysis and research for improved decision-making.

 

Admission: M.S.I.S. Program

Admission to the M.S. in Information Systems (MSIS) program is based upon the completion of the general admission requirements of the Graduate School. For admission into the MSIS program an acceptable score on the Graduate Management Admission Test (GMAT) or Graduate Record Examination (GRE) and acceptable academic undergraduate performance are required. The GMAT is strongly preferred. The GMAT or GRE test may be waived for applicants with an earned graduate degree in an appropriate information systems related discipline or profession. The GMAT or GRE test may also be waived for applicants with five or more years of increasing responsibility in managerial, professional, and/or technical positions in the information systems or related field, and with a 3.0 grade point average on undergraduate work as calculated by the Graduate School; detailed work history required with application. The GMAT or GRE test may also be waived for applicants who have (within the last 3 years) or will receive an undergraduate degree from UT Arlington in a related field with a GPA or 3.0 or higher, as calculated by the graduate school.

Students for whom English is not their native language must take the Test of English as a Foreign Language (TOEFL), TOEFL iBT, Test of Spoken English (TSE) or International English Language Testing System (IELTS). International applicants that score below minimum acceptable levels on the verbal portion of entrance examinations may be admitted under the condition that they pass an English proficiency exam or complete UT Arlington’s Graduate English Skills Program prior to beginning graduate coursework.

A standardized test score (GMAT or GRE) will not be used as the sole or primary criterion for determining an applicant’s admission to the MSIS program. Specifically, multiple criteria are used to make admission decisions. Unconditional acceptance is based on consideration of all the information listed below and the decision to deny admission is not based on any single criterion.

Along with the grade point average and GMAT or GRE scores, admission criteria include the following:

  1. An undergraduate grade point average (GPA) of 3.00 on a 4.0 scale, as calculated by the Graduate School, is typical of a successful candidate. This will be integrated into a formula or index that multiplies the GMAT by 200 and adds the resulting value to the GMAT score. An index score greater than 1080 is typical of a successful candidate. The grade point average is calculated on your undergraduate degree using approximately the last 60 hours. A graduate grade point average is used in the index when it is 3.0 or above and is based on at least 24 hours.
  2. Either the GMAT or the GRE will be considered for an admission decision. Both Quantitative and Verbal percentiles above the 40th percentile on the GRE and the 30th percentile on the GMAT indicate the ability to be successful in the MSIS program.
  3. International applicants must submit a score of at least 550 on the paper-based TOEFL, a score of at least 213 on the computer-based TOEFL, a minimum score of 40 on the TSE, a minimum score of 6.5 on the IELTS, or a minimum TOEFL iBT total score of 79 with sectional scores that meet or exceed 22 for the writing section, 21 for the speaking section, 20 for the reading section, and 16 for the listening section to meet this requirement.
  4. Grades in specified undergraduate business and non-business courses (math, accounting, economics, statistics, for example)
  5. Educational objectives and quality of written expression of the 200 word application essay.
  6. Letters of recommendation from three persons familiar with the applicant’s academic background and/or work experience who can assess the applicant’s potential success in graduate school.
  7. General and specific program accreditation status of degree granting institution.
  8. Professional work experience. Applicants should submit a resume that highlights professional and personal accomplishments, linguistic abilities, computer expertise and leadership experience. In addition, the immediate supervisor should submit a letter confirming work status.
  9. Professional certification or licensure.

Unconditional Admission

For unconditional admission, the applicant’s composite total from the GMAT-based index must be 1080 or higher, and items 1 through 6 above should strongly indicate potential for successful academic performance as a graduate information systems student. If an applicant falls below the GMAT Verbal percentile of 30 and/or the GMAT Quantitative percentile of 30, corroborating evidence of proficiency in that skill will be reviewed.

There is no equivalent index created using GRE scores. For students submitting the GRE, for unconditional admission, GRE Verbal and Quantitative percentiles should be above the 40th percentile, and items 1 through 9 above should strongly indicate potential for success in the MSIS program.

Students who are unconditionally admitted must have a minimum undergraduate grade point average of 3.00 as calculated by the Graduate School (or 3.00 at the graduate level), and enroll for a minimum of six semester credit hours to be eligible for available fellowship and/or scholarship support. A standardized test score will not be used as the sole criterion or the primary criterion for determining fellowship and/or scholarship eligibility.

Probationary Admission

For an applicant with an index score below 1080, probationary admission may be available when at least three items of 1 through 6 above strongly indicate potential for successful academic performance as a graduate information systems student. Items 7 through 10 will also be used to identify positive indicators for admission. When GMAT verbal or quantitative percentiles are below the 30th percentile, probationary admission may be available. For applicants submitting the GRE as part of the application for admission, when GRE verbal or quantitative percentiles are below the 40th percentile, probationary admission may be available. Students admitted on probationary status for low verbal or quantitative percentiles, must satisfactorily complete one or more English and/or math courses in the first two semesters as specified by the Graduate Advisor. Students who are admitted on probation must meet the conditions specified, such as no grade less than ’B’ for the first 12 hours of graduate study and any required undergraduate course.

Provisional, Deferred and Denied Admission

Provisional admission may be granted if an applicant is unable to supply all required documentation prior to the admission deadline but who otherwise appears to meet admission requirements. A student will not be permitted to enroll in the Graduate School with a provisional status for more than one semester. Provisional admission does not guarantee subsequent admission on an unconditional basis.

For an applicant who does not meet minimum acceptable scores on the GMAT, and other evidence indicates lack of potential for academic success as a graduate information systems student, admission will be denied. However, all applicant data will be carefully reviewed before an admission denial is made.

 

Degree Requirements

The Department of Information Systems and Operations Management provides two Master’s tracks: a Thesis Option for those intending to later pursue a Ph.D. in Information Systems, and a Non-Thesis track, a traditional flexible option. The thesis track program provides preparation for entry into a Ph.D. program. The second option is the flexible non-thesis program enabling a degree candidate greater flexibility in designing their program.

The thesis option consists of a minimum of 30 semester hours; BSTAT 5325, INSY 5309, INSY 5335, INSY 5341, INSY 5357, three elective courses approved by the Graduate Advisor, and six hours of thesis work taken in the last semester. The thesis student must be enrolled in six hours of thesis. Once the student is enrolled in the thesis course, continuous enrollment is expected. The student must be enrolled in six hours of thesis during the semester in which the thesis is defended and the final Master’s Examination is unconditionally passed. The degree candidate must defend the thesis in a final oral examination open to all members of the Faculty.

The non-thesis option consists of 33 semester hours; BSTAT 5325, INSY 5309, INSY 5335, INSY 5341, INSY 5357, INSY 5375, and five elective courses approved by the Graduate Advisor.

The non-thesis option electives can be focused in two tracks: systems development and business analytics. The systems development track concentrates on the analysis, design, and implementation of business systems and their management issues. Courses in this track cover such topics as object-oriented technology, data base design, advanced systems design techniques, and project management. The business analytics track concentrates on technologies and skills needed to analyze big data to gain insights which help improve business decisions and planning. Courses in this track would cover such topics as data mining, data warehousing, statistical computing, and selective statistics topics. The student must meet with the MSIS Graduate Advisor to determine the appropriate coursework for the selected track.

When there is equivalent work/course experience, the student must meet with the MSIS Graduate Advisor to select alternate coursework. An approved 3-credit hour graduate internship (INSY 5399) may also be taken as an elective.

Waivers and Transfer Credit

There are three types of required courses: deficiency, core and advanced. Programs of work will normally vary in length from 36 to 45 hours (plus deficiency courses), depending upon waivers granted. The first three waivers of core courses will be used to expand the number of electives in the advanced program rather than shorten the overall program. Additional waivers of core courses may reduce the program to a minimum of 36 hours. Applicants may have both deficiency and core courses waived without the requirement for a substitute course if they have completed, during the last 10 years, a similar course at a recognized college or university and received a "B" or better grade.* Extensions to this 10 year limit may be granted for managers and executives who have completed educational activities to remain current or have extensive related experience. Additionally, a maximum of 9 hours of advanced coursework may be transferred in from other AACSB accredited schools if approved by program advisor. Transfer of graduate classes from other universities will be considered on a case by case basis.

* Note: The University of Texas at Austin offers Business Foundations Programs (BFP) for non-business majors that provide solid foundations in basic business concepts. BFP courses and courses from equivalent programs for non-business majors at other colleges/universities may not be used for course waiver credit.

 

BSTAT Courses

BSTAT5301 – INTRODUCTION TO STATISTICS

3 Lecture Hours  ·  0 Lab Hours

Introduction to statistics, designed to prepare graduate students to become competent consumers of statistical information that they will encounter in their professional and personal lives. Students should be able to perform basic statistical analyses and to think critically when interpreting statistical results. Topics include probability, random variables, sampling distributions, confidence intervals, tests of hypotheses, and simple regression. May not be counted as an MBA foundation course or elective. Prerequisite: MATH 1315.

 

BSTAT5303 – QUANTITATIVE ANALYSIS

3 Lecture Hours  ·  0 Lab Hours

Study of the methods of quantitative analysis used in business administration. Topics include matrix algebra, systems of linear equations, differential and integral calculus, linear programming, classical optimization, and a survey of management science models. Prerequisite: MATH 1315.

 

BSTAT5315 – STATISTICAL METHODS FOR HEALTH CARE ADMINISTRATORS

3 Lecture Hours  ·  0 Lab Hours

Statistical methods designed to prepare graduate students to become competent producers and consumers of data analyses and to use statistical thinking to approach managerial decision making. Students should be familiar with the effectiveness and limitations of various applicable techniques and should be able to recognize when additional statistical expertise is required. Topics include an introduction to evidenced based medicine, probability with an emphasis on the poor predictive value of imperfect diagnostics for rare conditions, standardizing and trending data, graphic and numeric descriptions of data, concepts of inference such as margins of error and significance of results, concepts of quality control including time series analysis and forecasting, and health care applications of discrete random variables with Poisson or binomial probability mass functions. It is recommended that students who have no recent courses in statistics take BSTAT 5301 prior to BSTAT 5315.

 

BSTAT5325 – ADVANCED STATISTICAL METHODS

3 Lecture Hours  ·  0 Lab Hours

Advanced statistical methods designed to prepare graduate students to become competent producers and consumers of statistical methods and to use statistical thinking to approach managerial decision making in their careers. They should be able to recognize the strengths and weaknesses of applicable techniques and when additional statistical expertise is required. Topics include multiple regression, correlation, experimental design and analysis, time series and other statistical methods with emphasis on their application to managerial decision making. It is strongly recommended that students who have no recent courses in statistics take BSTAT 5301 prior to BSTAT 5325.

 

BSTAT5330 – NONPARAMETRIC STATISTICS

3 Lecture Hours  ·  0 Lab Hours

A survey of statistical tools which may be used when the normal assumptions of parametric statistics cannot be made; including procedures for categorical data, methods involving ranks, bootstrapping, and Kolmogorov-Smirnov type techniques. Cross-listed with BSAD 6330. Prerequisite: BSTAT 5325 or equivalent.

 

BSTAT5331 – DATA VISUALIZATION

3 Lecture Hours  ·  0 Lab Hours

Investigation of recent advances in data graphics to support business analytics. Concepts include graphical depiction, analysis of data structure and graphical software. Visualization topics would include exploratory analysis of univariate and multivariate data using graphical software, e.g., Lowess Smoothing and Sunflower Plots. Cross-listed with INSY 5331. Prerequisite: BSTAT 5325 or equivalent.

 

BSTAT5339 – PRINCIPLES OF BUSINESS DATA MINING

3 Lecture Hours  ·  0 Lab Hours

This course provides an overview of the life cycle stages of a data mining project, contexts in which data mining is applied, a survey of data mining techniques, and measuring the effect of the resulting action. Additional topics include communicating with management representatives and IT professionals, ethical issues in data mining, and relationships with reference disciplines such as statistics, artificial intelligence, machine learning and database. Learning is facilitated by a combination of lectures, group projects, and homework assignments. This course is cross-listed with INSY 5339. Prerequisite: BSTAT 5325. May be taken concurrently.

 

BSTAT5360 – COMPUTATIONAL TECHNIQUES FOR BUSINESS ANALYTICS

3 Lecture Hours  ·  0 Lab Hours

Computer software is the primary analytical tool for business analytics and modern research methods. Data analysts, statisticians, and researchers need technologies and skills using the computer as a tool for structuring and cleaning data sets, creating validation samples, conducting analyses, fitting models, simulating stochastic systems, model validation, and model presentation. Emphasis is placed on the use of data analytic software. Cross-listed with INSY 5360. Prerequisite: BSTAT 5325 or equivalent.

 

BSTAT5392 – SELECTED TOPICS IN BUSINESS STATISTICS

3 Lecture Hours  ·  0 Lab Hours

In-depth study of selected topics in business statistics. May be repeated when topics vary.

 

BSTAT5399 – GRADUATE BUSINESS ANALYTICS INTERNSHIP

3 Lecture Hours  ·  0 Lab Hours

Practical training in business statistics. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

INSY Courses

INSY5182 – INDEPENDENT STUDIES IN INFORMATION SYSTEMS

1 Lecture Hour  ·  0 Lab Hours

Extensive analysis of an information systems topic. Prerequisite: permission of instructor.

 

INSY5199 – GRADUATE INFORMATION SYSTEMS INTERNSHIP

1 Lecture Hour  ·  0 Lab Hours

Practical training in information systems. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

INSY5299 – GRADUATE INFORMATION SYSTEMS INTERNSHIP

2 Lecture Hours  ·  0 Lab Hours

Practical training in information systems. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

INSY5309 – OBJECT-ORIENTED BUSINESS PROGRAMMING

3 Lecture Hours  ·  0 Lab Hours

Topics include fundamental programming structures, objects and classes, inheritance, and other basic concepts related to OO programming.

 

INSY5331 – DATA VISUALIZATION

3 Lecture Hours  ·  0 Lab Hours

Investigation of recent advances in data graphics to support business analytics. Concepts include graphical depiction, analysis of data structure and graphical software. Visualization topics would include exploratory analysis of univariate and multivariate data using graphical software, e.g., Lowess Smoothing and Sunflower Plots. Cross-listed with INSY 5331. Prerequisite: BSTAT 5325 or equivalent.

 

INSY5333 – INFORMATION TECHNOLOGIES FOR STRATEGIC MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

A nontechnical, managerially-oriented introduction to information technology applications that enhance an organization's competitive effectiveness. Topics include: Executive Information Systems (EIS), Enterprise Resource Planning (ERP), Supply Chain Management (SCM) systems, data warehousing and mining, business intelligence, knowledge management, e-business, and approaches to integrate these technologies with corporate strategic planning and management. Graded A, B, C, D, F, W.

 

INSY5335 – APPLIED DATABASE MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Concepts, tools, and technologies associated with the design, implementation and management of large databases are presented. Topics include data models (with emphasis on E/R model and relational model), database design and implementation, database query language, transaction management, and distributed databases. Recent advances in data management are also discussed. Use of a commercial DBMS is required. Prerequisite: INSY 5309 or approval of MSIS Graduate Advisor

 

INSY5337 – DATA WAREHOUSING AND BUSINESS INTELLIGENCE

3 Lecture Hours  ·  0 Lab Hours

This course covers concepts, tools, and technologies associated with the design and implementation of data warehousing (DW) and business intelligence (BI) applications. Topics covered include data warehouse architecture and infrastructure, dimensional modeling, Extraction Transformation and Loading (ETL), On Line Analytical Processing (OLAP), data quality, and planning and implementation of a DW & BI application. The course objectives are met through a combination of lectures, class projects and homework assignments. Hands-on experience in developing and deploying a DW & BI application is provided. Prerequisite: INSY 5335

 

INSY5339 – PRINCIPLES OF BUSINESS DATA MINING

3 Lecture Hours  ·  0 Lab Hours

This course provides an overview of the life cycle stages of a data mining project, contexts in which data mining is applied, a survey of data mining techniques, and measuring the effect of the resulting action. Additional topics include communicating with management representatives and IT professionals, ethical issues in data mining, and relationships with reference disciplines such as statistics, artificial intelligence, machine learning and database. Learning is facilitated by a combination of lectures, group projects, and homework assignments. This course is cross-listed with BSTAT 5339. Prerequisite: BSTAT 5325. May be taken concurrently.

 

INSY5340 – MANAGING THE DIGITAL ENTERPRISE

3 Lecture Hours  ·  0 Lab Hours

This course examines a wide variety of topics important to understanding and managing the Digital Enterprise. Topics may include: Internet infrastructure and related technologies; e-business models; security; ethical, legal, global, and social concerns; and managerial and marketing issues.

 

INSY5341 – ANALYSIS AND DESIGN

3 Lecture Hours  ·  0 Lab Hours

Analysis and design phase of systems development life cycle. Topics include systems survey, functional specification, interface specification, data design, program design, system testing, and implementation. Prerequisite: INSY 5335

 

INSY5342 – ADVANCED SYSTEMS DESIGN

3 Lecture Hours  ·  0 Lab Hours

This course provides an understanding of state-of-the-art software development methodologies, including those that are fast emerging. The focus will be on how these new methods differ from traditional practices and what research opportunities they afford to IS researchers. There will be a strong emphasis on technical as well as on socio-technical aspects of software development in the context of these new methodologies. Prerequisite: INSY 5341.

 

INSY5343 – DATA COMMUNICATIONS AND NETWORKING

3 Lecture Hours  ·  0 Lab Hours

Technological and managerial issues related to design, operation and maintenance of computer networks. Topics include communication architectures and protocols, LANs and WANs, ATM and frame relay, cellular and satellite communication, the World Wide Web, the Internet, and electronic commerce.

 

INSY5347 – PRINCIPLES OF INFORMATION SECURITY

3 Lecture Hours  ·  0 Lab Hours

Starting with an introduction to Information Security concepts, this course will address security terminology, history, management, technology and practice based on the Security Domains specified by ISC2. The course will address strategies and tools, managerial, technological, legal, ethical and operational issues related to Information Security. Topics in developing Security Blueprint, Incidence Response, Business Continuity planning and Disaster Recovery will be addressed. Prerequisite: INSY 5343

 

INSY5350 – HEALTH CARE INFORMATION SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Addresses issues in the development, integration, and management of health care information systems. Specifically, topics in financial information systems, patient care systems, and health care delivery applications will be discussed. Both case studies and real life applications will be studied. Prerequisite: Cohort HCAD Major

 

INSY5352 – TOPICS IN OBJECT TECHNOLOGY

3 Lecture Hours  ·  0 Lab Hours

Coverage of current topics in Object Technology to include the study of object-oriented agents, components, object request Brokers, distributed objects and related implementations of object-oriented software. Also includes the study of design patterns in object-oriented software design. Prerequisite: INSY 5309.

 

INSY5354 – ENTERPRISE APPLICATION DEVELOPMENT

3 Lecture Hours  ·  0 Lab Hours

This course will address the architectures, methodologies, tools and techniques used in the development and deployment of enterprise-level information systems applications. The topics covered will include client/server applications, intranet/internet applications, distributed applications, enterprise-level objects and server-side components. Prerequisite: INSY 5341 and 5352.

 

INSY5357 – ENTERPRISE RESOURCE PLANNING

3 Lecture Hours  ·  0 Lab Hours

An introduction to enterprise resource planning (ERP), a business management paradigm that integrates all facets of the business, including planning, manufacturing, sales, finance and marketing. Course will cover both the methodology and practice of ERP using commercial software packages.

 

INSY5360 – COMPUTATIONAL TECHNIQUES FOR BUSINESS ANALYTICS

3 Lecture Hours  ·  0 Lab Hours

Computer software is the primary analytical tool for business analytics and modern research methods. Data analysts, statisticians, and researchers need technologies and skills using the computer as a tool for structuring and cleaning data sets, creating validation samples, conducting analyses, fitting models, simulating stochastic systems, model validation, and model presentation. Emphasis is placed on the use of data analytic software. Cross-listed with INSY 5360. Prerequisite: BSTAT 5325 or equivalent.

 

INSY5363 – INTELLIGENT INFORMATION SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Topics include expert systems, inductive learning, genetic algorithms, neural networks, simulated annealing, etc. Prerequisite: INSY 5309.

 

INSY5365 – COMPUTER FORENSICS AND INVESTIGATIONS

3 Lecture Hours  ·  0 Lab Hours

This course provides an introduction to acquiring and analyzing digital evidence for forensic purposes. The course will cover tools and techniques of forensics investigation of computer crimes. Topics covered include analysis file structures, data recovery, email and network analysis, digital investigations, expert witness testimony, and preserving evidence for law enforcement and legal proceedings. Prerequisite: INSY 5347.

 

INSY5370 – ENTERPRISE APPLICATION ARCHITECTURE

3 Lecture Hours  ·  0 Lab Hours

Enterprise applications typically display, manipulate and store large amounts of complex data and support business processes with that data. Enterprise applications have their own challenges and solutions that is different from desktop systems and embedded systems. This course addresses enterprise application architecture issues such as layering applications, structuring domain logic, specifying user interface, linking memory and relational database, handling session state and the principles of distribution. The course will also address solutions organized as software patterns and their use in application design. Prerequisite: INSY 5341.

 

INSY5373 – INFORMATION SYSTEMS PROJECT MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

This course introduces students to the concepts and practices of project management and their importance to improving the success of information technology projects. Distinct aspects or characteristics of IT projects which cause these projects to behave differently in the corporate world than do other, non-technical, projects will be discussed.

 

INSY5375 – MANAGEMENT OF INFORMATION TECHNOLOGIES

3 Lecture Hours  ·  0 Lab Hours

This course covers topics on the management of information technologies (IT) from the view point of senior managers. Subjects discussed include the strategic role of IT to gain competitive advantage, Internet-based business models, building a lean and agile organization through IT, managing IT security and reliability, evolving models of IT service delivery, such as cloud computing and open source, management of outsourcing, IT governance, and ethical issues in the digital era. In addition to classroom lectures, the course relies heavily on case analysis and discussion to provide a real world perspective of issues related to IT management.

 

INSY5379 – ORGANIZATIONAL RESEARCH PROJECT

3 Lecture Hours  ·  0 Lab Hours

Students conduct a research project at a local organization, focusing on applications of information systems concepts studied in their coursework. Prerequisite: Cohort INSY Major.

 

INSY5382 – INDEPENDENT STUDIES IN INFORMATION SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Extensive analysis of an information systems topic.

 

INSY5392 – SELECTED TOPICS IN INFORMATION SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

In-depth study of selected topics in information systems. May be repeated when topics vary.

 

INSY5398 – THESIS

3 Lecture Hours  ·  0 Lab Hours

Graded F,R,P

 

INSY5399 – GRADUATE INFORMATION SYSTEMS INTERNSHIP

3 Lecture Hours  ·  0 Lab Hours

Practical training in information systems. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

INSY5698 – THESIS

6 Lecture Hours  ·  0 Lab Hours

Graded F, R, P.

 

INSY6182 – INDEPENDENT STUDY IN INFORMATION SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Doctoral level study of information systems topics. Prerequisite: Doctoral standing.

 

INSY6301 – SEMINAR IN RESEARCH FOUNDATIONS

3 Lecture Hours  ·  0 Lab Hours

Integrative analysis of research in information systems, including research philosophies and methodologies, contemporary research topics, dissertation research and future directions for information systems research. Prerequisite: Doctoral standing.

 

INSY6306 – SEMINAR IN INFORMATION TECHNOLOGIES

3 Lecture Hours  ·  0 Lab Hours

Focuses on contemporary technology issues in IS development and deployment. Prerequisite: Doctoral standing and INSY 6301.

 

INSY6307 – SEMINAR IN IS MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Focuses on managerial and organizational issues in IS. Prerequisite: Doctoral standing and INSY 6301

 

INSY6392 – SELECTED TOPICS IN INFORMATION SYSTEMS

3 Lecture Hours  ·  0 Lab Hours

Advanced doctoral level topics in Information Systems. May be repeated when topics vary. Prerequisite: Doctoral standing.

 

MASI Courses

MASI5182 – INDEPENDENT STUDIES IN MANAGEMENT SCIENCES

1 Lecture Hour  ·  0 Lab Hours

Extensive analysis of a management sciences topic.

 

MASI5199 – GRADUATE MANAGEMENT SCIENCES INTERNSHIP

1 Lecture Hour  ·  0 Lab Hours

Practical training in management science. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

MASI5282 – INDEPENDENT STUDIES IN MANAGEMENT SCIENCES

2 Lecture Hours  ·  0 Lab Hours

Extensive analysis of a management sciences topic.

 

MASI5299 – GRADUATE MANAGEMENT SCIENCES INTERNSHIP

2 Lecture Hours  ·  0 Lab Hours

Practical training in management science. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

MASI5332 – ADVANCED DATA COLLECTION

3 Lecture Hours  ·  0 Lab Hours

Surveys, audits, samples and experimental designs contrasted and compared as a basis for statistical inference. Emphasis is on the integration of techniques common to differing areas of business research. Prerequisite: STAT 5325.

 

MASI5382 – INDEPENDENT STUDIES IN MANAGEMENT SCIENCES

3 Lecture Hours  ·  0 Lab Hours

Extensive analysis of a management sciences topic.

 

MASI5399 – GRADUATE MANAGEMENT SCIENCES INTERNSHIP

3 Lecture Hours  ·  0 Lab Hours

Practical training in management science. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

MASI6309 – MULTIVARIATE STATISTICAL METHODS

3 Lecture Hours  ·  0 Lab Hours

Focuses on methods of analyzing mean and covariance structures. Topics include commonly applied multivariate methods such as multiple analysis of variance, repeated measures, discriminant analysis, profile analysis, canonical correlations, and factor analytic methods. The use of matrix algebra and available computer packages will be stressed. Prerequisite: Doctoral standing and BSTAT 5325.

 

OPMA Courses

OPMA5199 – GRADUATE OPERATIONS MANAGEMENT INTERNSHIP

1 Lecture Hour  ·  0 Lab Hours

Practical training in operations management. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

OPMA5299 – GRADUATE OPERATIONS MANAGEMENT INTERNSHIP

2 Lecture Hours  ·  0 Lab Hours

Practical training in operations management. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

OPMA5321 – INTRODUCTION TO MANAGEMENT SCIENCES

3 Lecture Hours  ·  0 Lab Hours

Introduction to optimization and quantitative analysis of business problems. Topics include applications of linear and integer programming, network analysis, simulation, game theory, queuing theory, and other operations research tools.

 

OPMA5361 – OPERATIONS MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Introduction to concepts and problem-solving techniques important in production management and operations management. Topics include demand forecasting, capacity management, resource allocation, inventory management, supply chain management, quality control, and project management.

 

OPMA5363 – OPERATIONS PLANNING AND CONTROL

3 Lecture Hours  ·  0 Lab Hours

Course covers operations planning and control systems in manufacturing and service organizations. Topics include inventory control, material requirements planning, Just-In-Time and lean manufacturing, production scheduling, capacity planning, and operations planning and control software. Previous introductory course in operations management suggested.

 

OPMA5364 – PROJECT MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Course covers concepts and issues important in effectively managing projects. Topics include project selection, project planning, negotiation, budgeting, scheduling, resource allocation, project control, project auditing, and project termination.

 

OPMA5367 – QUALITY MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Course focuses on quality of products and services needed by society. Topics include consideration of quality cost and improvements, designing for quality, process controls, inspections, testing, acceptance sampling, management controls, and quality information systems. Previous introductory course in statistics suggested.

 

OPMA5368 – GLOBAL SUPPLY CHAIN MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Course covers concepts and issues important in managing supply chains. A strategic view is taken of the way companies coordinate their operations with suppliers and customers in a global marketplace. The strategic use of information systems to better manage supply chains is also covered. Previous introductory course in operations management suggested.

 

OPMA5369 – LOGISTICS MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Course covers physical supply, in-plant movement and storage, and physical distribution of materials, which comprise logistics systems in industry. Topics include facility location, transportation, warehousing, inventory control, distribution networks, and logistics information systems. Previous introductory course in operations management suggested.

 

OPMA5377 – HEALTH CARE QUALITY ASSESSMENT

3 Lecture Hours  ·  0 Lab Hours

Covers an integrated case study approach to organizational performance management resulting in the delivery of ever-improving value to patients, improved health care quality and organizational sustainability, improvement of overall organizational effectiveness as a health care provider, and organizational learning.

 

OPMA5379 – ORGANIZATIONAL RESEARCH PROJECT

3 Lecture Hours  ·  0 Lab Hours

Students conduct a research project at a local organization, focusing on applications of business concepts studied in their coursework. Prerequisite: Cohort MBA Major

 

OPMA5382 – INDEPENDENT STUDIES IN OPERATIONS MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Extensive analysis of an Operations Management topic.

 

OPMA5389 – INDEPENDENT STUDIES IN MILITARY ACQUISITION

3 Lecture Hours  ·  0 Lab Hours

This course is reserved for military officers in the Training with Industry or I-Grade programs at UT Arlington. Studies consist of an acquisition practicum with training at an assigned agency and a required seminar at UT Arlington.

 

OPMA5392 – SELECTED TOPICS IN OPERATIONS MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

In-depth study of selected topics in operations management. May be repeated when topics vary.

 

OPMA5399 – GRADUATE OPERATIONS MANAGEMENT INTERNSHIP

3 Lecture Hours  ·  0 Lab Hours

Practical training in operations management. Analysis of theory applied to real life situations. Course counts as an elective and has a pass/fail grade. No credit will be given for previous experience or activities.

 

OPMA5689 – INDEPENDENT STUDIES IN MILITARY ACQUISITION

6 Lecture Hours  ·  0 Lab Hours

This course is reserved for military officers in the Training with Industry or I-GRAD programs at UT Arlington. Studies consist of an acquisition practicum with training at an assigned agency and a required seminar at UT Arlington.

 

OPMA5989 – INDEPENDENT STUDIES IN MILITARY ACQUISITION

9 Lecture Hours  ·  0 Lab Hours

This course is reserved for military officers in the Training with Industry or I-Grade programs at UT Arlington. Studies consist of an acquisition practicum with training at an assigned agency and a required seminar at UT Arlington.

 

OPMA6370 – SEMINAR IN OPERATIONS MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Doctoral seminar that is a comprehensive and integrative study of operations management that focuses on theoretical frameworks, applications of models, and methods of analysis. Prerequisite: Doctoral standing.

 

OPMA6371 – INTEGRATED OPERATIONS STRATEGY AND RESEARCH

3 Lecture Hours  ·  0 Lab Hours

Linkages between the manufacturing and strategy development functions. Research issues within production/operations management. Current techniques/designs for achieving effective research. Prerequisite: Doctoral standing and previous introductory course in operations management suggested.

 

OPMA6380 – RESEARCH IN OPERATIONS MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Independent research under the supervision of a faculty member. May be repeated for credit. Prerequisite: Doctoral standing.

 

OPMA6392 – SPECIAL TOPICS IN OPERATIONS MANAGEMENT

3 Lecture Hours  ·  0 Lab Hours

Advanced doctoral level topics in Operations Management. May be repeated when topics vary. Prerequisite: Doctoral standing.