Discussion Instructions

Discussion Instructions:

· Due 1/14

· Please make sure ALL questions are answered

· Minimum of 2 scholarly sources cited for EACH discussion unless stated in the initial post instructions. Please include a link to EACH scholarly source(s) in your references.

· APA format for in-text citations and list of references

 

Discussion 2: Context, Meaning, and Value

Initial Post Instructions Select one of the following options to research for this discussion:

· Option 1: Google <California Washington mural>. You will find numerous reports concerning a California school district that voted to paint over a mural in the high school. The Life of Washington was painted by Depression-era artist Victor Arnautoff.

· Option 2: Google <Indiana University Thomas Hart Benton mural>. You will find numerous articles on the controversy surround a panel from Benton’s A Social History of Indiana (1933) murals.

· Option 3: Conduct research on a mural or statue or monument in your town that is the subject of controversy.

Before you read the news articles, try to look at the artworks through an image search in Google. Then, read the news articles to see the different viewpoints about the murals.

For the initial post, address at least four (4) of the following questions for the option you selected:

· What do you think should be done with the artwork (e.g., painted over, covered, destroyed, left as is in plain view, etc.)? Why?

· Should the context in which the artwork was created (the Great Depression of the 1930s in the case of the Benton and Arnautoff murals) have an impact on the decision of what to do with the artwork?

· Should the context in which people now view the artwork have an impact on the decision of what to do with it?

· What message do you think the artwork conveys?

· Do you think there is ambiguity in the message?

· Do you think the message is vague?

· Does the artistic value of the artwork require that it be saved regardless of message?

· Does the historic value of the artwork require that it be saved regardless of message?

· Do you think the message of the artwork is sufficiently important that the message alone requires that it be saved?

· Do you think the artists were biased or prejudiced? If yes, explain specifics about the artwork that support your opinion. Do you think viewers might be bringing bias or prejudice to their opinions? Are you?

 

Discussion 3: Evaluating Sources

Introduction “Everyone is entitled to their own opinions – but not their own facts.” (Daniel Patrick Moynihan, cited in Vanity Fair, 2010, para. 2)

We form opinions – and make our judgments – based on facts we observe and values we hold. Our judgments are also influenced by the opinions of others. In the section “An Expert on Hate in America” in Chapter 6, one of the authors, Dr. Peter Facione, renders an opinion on a non-profit civil rights organization: Southern Poverty Law Center (SPLC). Dr. Facione is a leading advocate and one of the most influential voices in the field of critical thinking.

His endorsement of the civil rights organization is unqualified. It is also transparent: Dr. Facione reveals that he is a financial supporter of the organization and has arranged speaking engagements for its founder. This is Dr. Facione’s invitation to you, the reader:

Knowing where you can learn more about the SPLC for yourself, and knowing about Dr. Facione’s endorsement and support of the Center’s work, evaluate this claim made by Dr. Facione: “The SPLC is an expert on hate in America” (p. 124).

The endorsement of the SPLC is contained in the most current edition of the text, whose copyright date is 2016. Since that time Morris Dees, co-founder and former chief trial counsel, has been fired (Hassan, Zraick & Blinder, 2019). Previously, there has been controversy about groups and individuals that are listed by the SPLC as “hate groups” (Graham, 2016; Price, 2018). The organization, which has nearly a half-billion dollars in assets, has also been criticized for how it spends these funds (Robinson, 2019).

Initial Post Instructions For the initial post, address the following:

· Conduct additional researched on the SPLC. Did your opinion alter in any way? Why?

Only after you have done some responsible research should you begin to respond to the discussion prompt. The discussion is not about the SPLC; it is not about Dr. Facione. It is about what you have learned about forming opinions.

Your post MUST answer this question:

· How do you define the term “expert”?

Your post must also discuss at least two (2) of the following questions:

· How important are facts in the process of forming an opinion? Explain what you believe to be the purpose or function of facts in making a judgment.

· How did you respond to the self-assessment question? Since doing further research, have you re-thought the way in which you assess credibility and reliability? What is the importance of factoring the recency of a reference or opinion (i.e., how old is it?) into an assessment of credibility and reliability?

· How would you evaluate Dr. Facione’s claim “The SPLC is an expert on hate in America” (p. 124). Does the SPLC fit your definition of “expert”? Be specific in your answer.

 

Discussion 4: Distinguishing Inductive and Deductive Reasoning

In deductive arguments, the speaker asserts that her premises are true and, therefore, her conclusion must be accepted. Remember that in a deductive argument, logical strength does not depend on the literal truth of the premises. When we test for logical strength, we assume the premises are true. Once we determine that the argument is logically valid, we can then look at the actual – not presumed – truth of the premises.

In inductive arguments, the speaker presents evidence that she claims support the probable truth of her conclusion – that her conclusion is the most likely true – and so you should accept it.

Initial Post Instructions For the initial post, address the following:

· Find and post examples of deductive and inductive arguments.

· For each example, evaluate its logical strength, using the concepts and ideas presented in the textbook readings, the lesson, and any other source you find that helps you to evaluate the validity (deductive) or strength (inductive) of the argument. You can use examples from the text, or you can find examples elsewhere.

· Editorials and opinion columns are a good source, as are letters to the editor. Blogs will also often be based on arguments.

· Use mapping and evaluative techniques to make sure it is an argument.

· Is it inductive or deductive? Explain why.

· Does it pass the tests of validity and strength? Explain.

 

Discussion 5: In My Opinion

Initial Post Instructions Consider one of the following current social issues – or one of your choice:

· Opioid crisis

· Legalization of recreational or medical marijuana

· Vaping

· Immigration

· Elimination of the electoral college

· Gun control

For the initial post, address the following:

· State your position on one of these issues – are you for, against, or neutral? Explain why. Avoid vagueness or ambiguity in your response. Make your position very clear.

· Examine how you have formed that opinion.

· How well do you think you know the facts?

· Do you know and understand statistical information that applies to the issue?

· Do you think you have formed your opinion using only System-1 thinking, or have you applied System-2?

· What part have heuristics, cognitive bias, and dominance structuring played in how you have formed your opinions?

The initial post is not about how “correct” your position is; it is about how you arrived at your position on the issue. This discussion requires application of metacognition – thinking about how you think.

 

Discussion 6: Comparative Reasoning

(only 1 additional scholarly source for this discussion)

Please read/review the following resources for this activity. You must include the following resources in your post.

· The Doctor’s Choice is America’s Choice”: The Physician in US Cigarette Advertisements, 1930 – 1953. Link to article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1470496/

 

· The Opioid Epidemic: Who is to Blame? Link to article: https://www.psychiatrictimes.com/pain/opioid-epidemic-who-blame

 

· The Opioid Epidemic: It’s Time to Place Blame Where It Belongs. Link to article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6140023/

Introduction The medical profession has a muddled and contradictory association with its approach toward the tobacco industry. While the profession now firmly opposes to smoking and vigorously publicizes the serious, even fatal, health hazards associated with smoking, this was not always so. Advertisements for tobacco products, including cigarettes “… became a ready source of income for numerous medical organizations and journals, including the New England Journal of Medicine and the Journal of the American Medical Association (JAMA), as well as many branches and bulletins of local medical associations” (Wolinsky & Brune, 1994). Physicians and reference to doctors and smoking were once common in tobacco industry advertisements. The story of physicians and promotion of smoking can be found in “The Doctors’ Choice Is America’s Choice” (Gardner & Brandt, 2006).

The role of physicians in the current opioid crisis is now under scrutiny on television (Farmer, 2019) by trade publications (King, 2018), peer-reviewed journals (deShazo, et al, 2018), and by physicians themselves (Hirsch, 2019).

Initial Post Instructions For the initial post, research the history of the association of doctors with tobacco companies and tobacco advertising. Read about the association of doctors with the opioid crisis. Then, address the following:

· In what way are the two situations comparable?

· In what way are they different?

· Apply the concept of moral equivalence. Is the conduct of doctors in relation to smoking and the tobacco industry morally equivalent to the conduct of doctors in the opioid crisis? Explain your position and be very specific.

 

Discussion 7: What Do I Value?

Initial Post Instructions For the initial post, address the following:

· What core values would you risk your life and freedom to defend?

· Could a nation going to war be appropriate in certain circumstances – or is war never an appropriate response?

Notice that this exercise requires deductive reasoning. You are stating a position and supporting it with “top down” reasoning. Be sure to review Three Features of Ideological Reasoning. Apply these concepts as you create your own arguments and evaluate those of your peers.

Remember that you are using ideological reasoning here. Is your post structured like an ideological argument, beginning with a general idea (opinion, belief, or principle) and moving down from these abstractions to their specific applications?

The text warns us that ideological arguments often fail the test of Truthfulness of the Premises. Have you tested the truth of your premises?

Discussion 8: When the People You Love Don’t Think Like You

Introduction Facione & Gittens (2016) state, “Strong critical thinking about complex and difficult social policies demands that we respect those with whom we disagree” (p. 344). The authors of your text ask us to take seriously the points of view of those with whom we disagree.

· Should I respect the point of view of a misogynist – a person who dislikes, despises, or is strongly prejudiced against women?

· Should I respect the point of view of a racist?

· How about someone who believes marriage is only between one man and one woman?

· How about someone who does not believe that humans are contributing to the conditions that cause climate change?

· How about someone who denies that the Holocaust occurred?

Initial Post Instructions For the initial post, pick one point of view from the five questions above that you find particularly repugnant – one that you think is completely unjustifiable. If you were in conversation with such a person, how could you ethically respond to the statement of such a point of view? Keep in mind that you are expressing a value opinion, which requires ideological reasoning.

As you form your response, keep in mind the following; these are things you need to think about but not necessarily to write about in your initial post:

· Reflect if you are using System-1 or System-2 thinking? Are your responses tinged with cognitive bias?

· Do you think there is a qualitative difference between believing some races are inferior and the belief that marriage should only be between one man and one woman?

· Do you think there is a qualitative difference between not believing in human contribution to climate change and not believing in the Holocaust?

 

 

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Information Technology and Organizational

Information Technology and Organizational

Learning Managing Behavioral Change

in the Digital Age Third Edition

 

 

 

Information Technology and Organizational

Learning Managing Behavioral Change

in the Digital Age Third Edition

Arthur M. Langer

 

 

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v

Contents

Foreword xi Acknowledgments xiii Author xv IntroductIon xvii

chApter 1 the “rAvell” corporAtIon 1 Introduction 1 A New Approach 3

The Blueprint for Integration 5 Enlisting Support 6 Assessing Progress 7

Resistance in the Ranks 8 Line Management to the Rescue 8 IT Begins to Reflect 9 Defining an Identity for Information Technology 10 Implementing the Integration: A Move toward Trust and Reflection 12 Key Lessons 14

Defining Reflection and Learning for an Organization 14 Working toward a Clear Goal 15 Commitment to Quality 15 Teaching Staff “Not to Know” 16 Transformation of Culture 16

Alignment with Administrative Departments 17 Conclusion 19

 

 

vi Contents

chApter 2 the It dIlemmA 21 Introduction 21 Recent Background 23 IT in the Organizational Context 24 IT and Organizational Structure 24 The Role of IT in Business Strategy 25 Ways of Evaluating IT 27 Executive Knowledge and Management of IT 28 IT: A View from the Top 29

Section 1: Chief Executive Perception of the Role of IT 32 Section 2: Management and Strategic Issues 34 Section 3: Measuring IT Performance and Activities 35 General Results 36

Defining the IT Dilemma 36 Recent Developments in Operational Excellence 38

chApter 3 technology As A vArIAble And responsIve orgAnIzAtIonAl dynAmIsm 41 Introduction 41 Technological Dynamism 41 Responsive Organizational Dynamism 42

Strategic Integration 43 Summary 48

Cultural Assimilation 48 IT Organization Communications with “ Others” 49 Movement of Traditional IT Staff 49 Summary 51

Technology Business Cycle 52 Feasibility 53 Measurement 53 Planning 54 Implementation 55 Evolution 57 Drivers and Supporters 58

Santander versus Citibank 60 Information Technology Roles and Responsibilities 60 Replacement or Outsource 61

chApter 4 orgAnIzAtIonAl leArnIng theorIes And technology 63 Introduction 63 Learning Organizations 72 Communities of Practice 75 Learning Preferences and Experiential Learning 83 Social Discourse and the Use of Language 89

Identity 91 Skills 92

 

 

viiContents

Emotion 92 Linear Development in Learning Approaches 96

chApter 5 mAnAgIng orgAnIzAtIonAl leArnIng And technology 109 The Role of Line Management 109

Line Managers 111 First-Line Managers 111 Supervisor 111

Management Vectors 112 Knowledge Management 116 Ch ange Management 120 Change Management for IT Organizations 123 Social Networks and Information Technology 134

chApter 6 orgAnIzAtIonAl trAnsFormAtIon And the bAlAnced scorecArd 139 Introduction 139 Methods of Ongoing Evaluation 146 Balanced Scorecards and Discourse 156 Knowledge Creation, Culture, and Strategy 158

chApter 7 vIrtuAl teAms And outsourcIng 163 Introduction 163 Status of Virtual Teams 165 Management Considerations 166 Dealing with Multiple Locations 166

Externalization 169 Internalization 171 Combination 171 Socialization 172 Externalization Dynamism 172 Internalization Dynamism 173 Combination Dynamism 173 Socialization Dynamism 173

Dealing with Multiple Locations and Outsourcing 177 Revisiting Social Discourse 178 Identity 179 Skills 180 Emotion 181

chApter 8 synergIstIc unIon oF It And orgAnIzAtIonAl leArnIng 187 Introduction 187 Siemens AG 187

Aftermath 202 ICAP 203

 

 

viii Contents

Five Years Later 224 HTC 225

IT History at HTC 226 Interactions of the CEO 227 The Process 228 Transformation from the Transition 229 Five Years Later 231

Summary 233

chApter 9 FormIng A cyber securIty culture 239 Introduction 239 History 239 Talking to the Board 241 Establishing a Security Culture 241 Understanding What It Means to be Compromised 242 Cyber Security Dynamism and Responsive Organizational Dynamism 242 Cyber Strategic Integration 243 Cyber Cultural Assimilation 245 Summary 246 Organizational Learning and Application Development 246 Cyber Security Risk 247 Risk Responsibility 248 Driver /Supporter Implications 250

chApter 10 dIgItAl trAnsFormAtIon And chAnges In consumer behAvIor 251 Introduction 251 Requirements without Users and without Input 254 Concepts of the S-Curve and Digital Transformation Analysis and Design 258 Organizational Learning and the S-Curve 260 Communities of Practice 261 The IT Leader in the Digital Transformation Era 262 How Technology Disrupts Firms and Industries 264

Dynamism and Digital Disruption 264 Critical Components of “ Digital” Organization 265 Assimilating Digital Technology Operationally and Culturally 267 Conclusion 268

chApter 11 IntegrAtIng generAtIon y employees to AccelerAte competItIve AdvAntAge 269 Introduction 269 The Employment Challenge in the Digital Era 270 Gen Y Population Attributes 272 Advantages of Employing Millennials to Support Digital Transformation 272 Integration of Gen Y with Baby Boomers and Gen X 273

 

 

ixContents

Designing the Digital Enterprise 274 Assimilating Gen Y Talent from Underserved and Socially Excluded Populations 276 Langer Workforce Maturity Arc 277

Theoretical Constructs of the LWMA 278 The LWMA and Action Research 281

Implications for New Pathways for Digital Talent 282 Demographic Shifts in Talent Resources 282 Economic Sustainability 283 Integration and Trust 283

Global Implications for Sources of Talent 284 Conclusion 284

chApter 12 towArd best prActIces 287 Introduction 287 Chief IT Executive 288 Definitions of Maturity Stages and Dimension Variables in the Chief IT Executive Best Practices Arc 297

Maturity Stages 297 Performance Dimensions 298

Chief Executive Officer 299 CIO Direct Reporting to the CEO 305 Outsourcing 306 Centralization versus Decentralization of IT 306 CIO Needs Advanced Degrees 307 Need for Standards 307 Risk Management 307

The CEO Best Practices Technology Arc 313 Definitions of Maturity Stages and Dimension Variables in the CEO Technology Best Practices Arc 314

Maturity Stages 314 Performance Dimensions 315

Middle Management 316 The Middle Management Best Practices Technology Arc 323

Definitions of Maturity Stages and Dimension Variables in the Middle Manager Best Practices Arc 325

Maturity Stages 325 Performance Dimensions 326

Summary 327 Ethics and Maturity 333

chApter 13 conclusIons 339 Introduction 339

glossAry 357 reFerences 363 Index 373

 

 

xi

Foreword

Digital technologies are transforming the global economy. Increasingly, firms and other organizations are assessing their opportunities, develop- ing and delivering products and services, and interacting with custom- ers and other stakeholders digitally. Established companies recognize that digital technologies can help them operate their businesses with greater speed and lower costs and, in many cases, offer their custom- ers opportunities to co-design and co-produce products and services. Many start-up companies use digital technologies to develop new prod- ucts and business models that disrupt the present way of doing busi- ness, taking customers away from firms that cannot change and adapt. In recent years, digital technology and new business models have dis- rupted one industry after another, and these developments are rapidly transforming how people communicate, learn, and work.

Against this backdrop, the third edition of Arthur Langer’ s Information Technology and Organizational Learning is most welcome. For decades, Langer has been studying how firms adapt to new or changing conditions by increasing their ability to incorporate and use advanced information technologies. Most organizations do not adopt new technology easily or readily. Organizational inertia and embed- ded legacy systems are powerful forces working against the adoption of new technology, even when the advantages of improved technology are recognized. Investing in new technology is costly, and it requires

 

 

xii Foreword

aligning technology with business strategies and transforming cor- porate cultures so that organization members use the technology to become more productive.

Information Technology and Organizational Learning addresses these important issues— and much more. There are four features of the new edition that I would like to draw attention to that, I believe, make this a valuable book. First, Langer adopts a behavioral perspective rather than a technical perspective. Instead of simply offering norma- tive advice about technology adoption, he shows how sound learn- ing theory and principles can be used to incorporate technology into the organization. His discussion ranges across the dynamic learning organization, knowledge management, change management, com- munities of practice, and virtual teams. Second, he shows how an organization can move beyond technology alignment to true technol- ogy integration. Part of this process involves redefining the traditional support role of the IT department to a leadership role in which IT helps to drive business strategy through a technology-based learn- ing organization. Third, the book contains case studies that make the material come alive. The book begins with a comprehensive real-life case that sets the stage for the issues to be resolved, and smaller case illustrations are sprinkled throughout the chapters, to make concepts and techniques easily understandable. Lastly, Langer has a wealth of experience that he brings to his book. He spent more than 25 years as an IT consultant and is the founder of the Center for Technology Management at Columbia University, where he directs certificate and executive programs on various aspects of technology innovation and management. He has organized a vast professional network of tech- nology executives whose companies serve as learning laboratories for his students and research. When you read the book, the knowledge and insight gained from these experiences is readily apparent.

If you are an IT professional, Information Technology and Organi­ zational Learning should be required reading. However, anyone who is part of a firm or agency that wants to capitalize on the opportunities provided by digital technology will benefit from reading the book.

Charles C. Snow Professor Emeritus, Penn State University

Co­Editor, Journal of Organization Design

 

 

xiii

Acknowledgments

Many colleagues and clients have provided significant support during the development of the third edition of Information Technology and Organizational Learning.

I owe much to my colleagues at Teachers College, namely, Professor Victoria Marsick and Lyle Yorks, who guided me on many of the the- ories on organizational learning, and Professor Lee Knefelkamp, for her ongoing mentorship on adult learning and developmental theo- ries. Professor David Thomas from the Harvard Business School also provided valuable direction on the complex issues surrounding diver- sity, and its importance in workforce development.

I appreciate the corporate executives who agreed to participate in the studies that allowed me to apply learning theories to actual organizational practices. Stephen McDermott from ICAP provided invaluable input on how chief executive officers (CEOs) can success- fully learn to manage emerging technologies. Dana Deasy, now global chief information officer (CIO) of JP Morgan Chase, contributed enormous information on how corporate CIOs can integrate tech- nology into business strategy. Lynn O’ Connor Vos, CEO of Grey Healthcare, also showed me how technology can produce direct mon- etary returns, especially when the CEO is actively involved.

And, of course, thank you to my wonderful students at Columbia University. They continue to be at the core of my inspiration and love for writing, teaching, and scholarly research.

 

 

xv

Author

Arthur M. Langer, EdD, is professor of professional practice of management and the director of the Center for Technology Management at Columbia University. He is the academic direc- tor of the Executive Masters of Science program in Technology Management, vice chair of faculty and executive advisor to the dean at the School of Professional Studies and is on the faculty of the Department of Organization and Leadership at the Graduate School of Education (Teachers College). He has also served as a member of the Columbia University Faculty Senate. Dr. Langer is the author of Guide to Software Development: Designing & Managing the Life Cycle. 2nd Edition (2016), Strategic IT: Best Practices for Managers and Executives (2013 with Lyle Yorks), Information Technology and Organizational Learning (2011), Analysis and Design of Information Systems (2007), Applied Ecommerce (2002), and The Art of Analysis (1997), and has numerous published articles and papers, relating to digital transformation, service learning for underserved popula- tions, IT organizational integration, mentoring, and staff develop- ment. Dr. Langer consults with corporations and universities on information technology, cyber security, staff development, man- agement transformation, and curriculum development around the Globe. Dr. Langer is also the chairman and founder of Workforce Opportunity Services (www.wforce.org), a non-profit social venture

 

 

xvi Author

that provides scholarships and careers to underserved populations around the world.

Dr. Langer earned a BA in computer science, an MBA in accounting/finance, and a Doctorate of Education from Columbia University.

 

 

xvii

Introduction

Background

Information technology (IT) has become a more significant part of workplace operations, and as a result, information systems person- nel are key to the success of corporate enterprises, especially with the recent effects of the digital revolution on every aspect of business and social life (Bradley & Nolan, 1998; Langer, 1997, 2011; Lipman- Blumen, 1996). This digital revolution is defined as a form of “ dis- ruption.” Indeed, the big question facing many enterprises today is, How can executives anticipate the unexpected threats brought on by technological advances that could devastate their business? This book focuses on the vital role that information and digital technology orga- nizations need to play in the course of organizational development and learning, and on the growing need to integrate technology fully into the processes of workplace organizational learning. Technology personnel have long been criticized for their inability to function as part of the business, and they are often seen as a group outside the corporate norm (Schein, 1992). This is a problem of cultural assimila- tion, and it represents one of the two major fronts that organizations now face in their efforts to gain a grip on the new, growing power of technology, and to be competitive in a global world. The other major

 

 

xviii IntroduCtIon

front concerns the strategic integration of new digital technologies into business line management.

Because technology continues to change at such a rapid pace, the ability of organizations to operate within a new paradigm of dynamic change emphasizes the need to employ action learning as a way to build competitive learning organizations in the twenty-first century. Information Technology and Organizational Learning integrates some of the fundamental issues bearing on IT today with concepts from organizational learning theory, providing comprehensive guidance, based on real-life business experiences and concrete research.

This book also focuses on another aspect of what IT can mean to an organization. IT represents a broadening dimension of business life that affects everything we do inside an organization. This new reality is shaped by the increasing and irreversible dissemination of technology. To maximize the usefulness of its encroaching presence in everyday business affairs, organizations will require an optimal understanding of how to integrate technology into everything they do. To this end, this book seeks to break new ground on how to approach and concep- tualize this salient issue— that is, that the optimization of information and digital technologies is best pursued with a synchronous imple- mentation of organizational learning concepts. Furthermore, these concepts cannot be implemented without utilizing theories of strategic learning. Therefore, this book takes the position that technology liter- acy requires individual and group strategic learning if it is to transform a business into a technology-based learning organization. Technology­ based organizations are defined as those that have implemented a means of successfully integrating technology into their process of organiza- tional learning. Such organizations recognize and experience the real- ity of technology as part of their everyday business function. It is what many organizations are calling “ being digital.”

This book will also examine some of the many existing organi- zational learning theories, and the historical problems that have occurred with companies that have used them, or that have failed to use them. Thus, the introduction of technology into organizations actually provides an opportunity to reassess and reapply many of the past concepts, theories, and practices that have been used to support the importance of organizational learning. It is important, however, not to confuse this message with a reason for promoting organizational

 

 

xixIntroduCtIon

learning, but rather, to understand the seamless nature of the relation- ship between IT and organizational learning. Each needs the other to succeed. Indeed, technology has only served to expose problems that have existed in organizations for decades, e.g., the inability to drive down responsibilities to the operational levels of the organization, and to be more agile with their consumers.

This book is designed to help businesses and individual manag- ers understand and cope with the many issues involved in developing organizational learning programs, and in integrating an important component: their IT and digital organizations. It aims to provide a combination of research case studies, together with existing theories on organizational learning in the workplace. The goal is also to pro- vide researchers and corporate practitioners with a book that allows them to incorporate a growing IT infrastructure with their exist- ing workforce culture. Professional organizations need to integrate IT into their organizational processes to compete effectively in the technology-driven business climate of today. This book responds to the complex and various dilemmas faced by many human resource managers and corporate executives regarding how to actually deal with many marginalized technology personnel who somehow always operate outside the normal flow of the core business.

While the history of IT, as a marginalized organization, is rela- tively short, in comparison to that of other professions, the problems of IT have been consistent since its insertion into business organiza- tions in the early 1960s. Indeed, while technology has changed, the position and valuation of IT have continued to challenge how execu- tives manage it, account for it, and, most important, ultimately value its contributions to the organization. Technology personnel continue to be criticized for their inability to function as part of the business, and they are often seen as outside the business norm. IT employees are frequently stereotyped as “ techies,” and are segregated in such a way that they become isolated from the organization. This book pro- vides a method for integrating IT, and redefining its role in organiza- tions, especially as a partner in formulating and implementing key business strategies that are crucial for the survival of many companies in the new digital age. Rather than provide a long and extensive list of common issues, I have decided it best to uncover the challenges of IT integration and performance through the case study approach.

 

 

xx IntroduCtIon

IT continues to be one of the most important yet least understood departments in an organization. It has also become one of the most significant components for competing in the global markets of today. IT is now an integral part of the way companies become successful, and is now being referred to as the digital arm of the business. This is true across all industries. The role of IT has grown enormously in companies throughout the world, and it has a mission to provide stra- tegic solutions that can make companies more competitive. Indeed, the success of IT, and its ability to operate as part of the learning organization, can mean the difference between the success and failure of entire companies. However, IT must be careful that it is not seen as just a factory of support personnel, and does not lose its justification as driving competitive advantage. We see in many organizations that other digital-based departments are being created, due to frustration with the traditional IT culture, or because they simply do not see IT as meeting the current needs for operating in a digital economy.

This book provides answers to other important questions that have challenged many organizations for decades. First, how can manag- ers master emerging digital technologies, sustain a relationship with organizational learning, and link it to strategy and performance? Second, what is the process by which to determine the value of using technology, and how does it relate to traditional ways of calculating return on investment, and establishing risk models? Third, what are the cyber security implications of technology-based products and services? Fourth, what are the roles and responsibilities of the IT executive, and the department in general? To answer these questions, managers need to focus on the following objectives:

• Address the operational weaknesses in organizations, in terms of how to deal with new technologies, and how to bet- ter realize business benefits.

• Provide a mechanism that both enables organizations to deal with accelerated change caused by technological innovations, and integrates them into a new cycle of processing, and han- dling of change.

• Provide a strategic learning framework, by which every new technology variable adds to organizational knowledge and can develop a risk and security culture.

 

 

xxiIntroduCtIon

• Establish an integrated approach that ties technology account- ability to other measurable outcomes, using organizational learning techniques and theories.

To realize these objectives, organizations must be able to

• create dynamic internal processes that can deal, on a daily basis, with understanding the potential fit of new technologies and their overall value within the structure of the business;

• provide the discourse to bridge the gaps between IT- and non- IT-related investments, and uses, into one integrated system;

• monitor investments and determine modifications to the life cycle;

• implement various organizational learning practices, includ- ing learning organization, knowledge management, change management, and communities of practice, all of which help foster strategic thinking, and learning, and can be linked to performance (Gephardt & Marsick, 2003).

The strengths of this book are that it integrates theory and practice and provides answers to the four common questions mentioned. Many of the answers provided in these pages are founded on theory and research and are supported by practical experience. Thus, evidence of the performance of the theories is presented via case studies, which are designed to assist the readers in determining how such theories and proven practices can be applied to their specific organization.

A common theme in this book involves three important terms: dynamic , unpredictable , and acceleration . Dynamic is a term that rep- resents spontaneous and vibrant things— a motive force. Technology behaves with such a force and requires organizations to deal with its capabilities. Glasmeier (1997) postulates that technology evolution, innovation, and change are dynamic processes. The force then is tech- nology, and it carries many motives, as we shall see throughout this book. Unpredictable suggests that we cannot plan what will happen or will be needed. Many organizational individuals, including execu- tives, have attempted to predict when, how, or why technology will affect their organization. Throughout our recent history, especially during the “ digital disruption” era, we have found that it is difficult, if not impossible, to predict how technology will ultimately benefit or

 

 

xxii IntroduCtIon

hurt organizational growth and competitive advantage. I believe that technology is volatile and erratic at times. Indeed, harnessing tech- nology is not at all an exact science; certainly not in the ways in which it can and should be used in today’ s modern organization. Finally, I use the term acceleration to convey the way technology is speeding up our lives. Not only have emerging technologies created this unpre- dictable environment of change, but they also continue to change it rapidly— even from the demise of the dot-com era decades ago. Thus, what becomes important is the need to respond quickly to technology. The inability to be responsive to change brought about by technologi- cal innovations can result in significant competitive disadvantages for organizations.

This new edition shows why this is a fact especially when examining the shrinking S-Curve. So, we look at these three words— dynamic, unpredictable, and acceleration— as a way to define how technology affects organizations; that is, technology is an accelerating motive force that occurs irregularly. These words name the challenges that organizations need to address if they are to manage technological innovations and integrate them with business strategy and competi- tive advantage. It only makes sense that the challenge of integrating technology into business requires us first to understand its potential impact, determine how it occurs, and see what is likely to follow. There are no quick remedies to dealing with emerging technologies, just common practices and sustained processes that must be adopted for organizations to survive in the future.

I had four goals in mind in writing this book. First, I am inter- ested in writing about the challenges of using digital technologies strategically. What particularly concerns me is the lack of literature that truly addresses this issue. What is also troublesome is the lack of reliable techniques for the evaluation of IT, especially since IT is used in almost every aspect of business life. So, as we increase our use and dependency on technology, we seem to understand less about how to measure and validate its outcomes. I also want to convey my thoughts about the importance of embracing nonmon- etary methods for evaluating technology, particularly as they relate to determining return on investment. Indeed, indirect and non- monetary benefits need to be part of the process of assessing and approving IT projects.

 

 

xxiiiIntroduCtIon

Second, I want to apply organizational learning theory to the field of IT and use proven learning models to help transform IT staff into becoming better members of their organizations. Everyone seems to know about the inability of IT people to integrate with other depart- ments, yet no one has really created a solution to the problem. I find that organizational learning techniques are an effective way of coach- ing IT staff to operate more consistently with the goals of the busi- nesses that they support.

Third, I want to present cogent theories about IT and organiza- tional learning; theories that establish new ways for organizations to adapt new technologies. I want to share my experiences and those of other professionals who have found approaches that can provide posi- tive outcomes from technology investments.

Fourth, I have decided to express my concerns about the valid- ity and reliability of organizational learning theories and practices as they apply to the field of IT. I find that most of these models need to be enhanced to better fit the unique aspects of the digital age. These modified models enable the original learning techniques to address IT-specific issues. In this way, the organization can develop a more holistic approach toward a common goal for using technology.

Certainly, the balance of how technology ties in with strategy is essential. However, there has been much debate over whether tech- nology should drive business strategy or vice versa. We will find that the answer to this is “ yes.” Yes, in the sense that technology can affect the way organizations determine their missions and business strate- gies; but “ no” in that technology should not be the only component for determining mission and strategy. Many managers have realized that business is still business, meaning that technology is not a “ sil- ver bullet.” The challenge, then, is to determine how best to fit tech- nology into the process of creating and supporting business strategy. Few would doubt today that technology is, indeed, the most signifi- cant variable affecting business strategy. However, the most viable approach is to incorporate technology into the process of determin- ing business strategy. I have found that many businesses still formu- late their strategies first, and then look at technology, as a means to efficiently implement objectives and goals. Executives need to better understand the unique and important role that technology provides us; it can drive business strategy, and support it, at the same time.

 

 

xxiv IntroduCtIon

Managers should not solely focus their attention on generating breakthrough innovations that will create spectacular results. Most good uses of technology are much subtler, and longer-lasting. For this reason, this book discusses and defines new technology life cycles that blend business strategy and strategic learning. Building on this theme, I introduce the idea of responsive organizational dynamism as the core theory of this book. Responsive organizational dynamism defines an environment that can respond to the three important terms (dynamic, unpredictable, and acceleration). Indeed, technology requires organizations that can sustain a system, in which individu- als can deal with dynamic, unpredictable, and accelerated change, as part of their regular process of production. The basis of this concept is that organizations must create and sustain such an environment to be competitive in a global technologically-driven economy. I further analyze responsive organizational dynamism in its two subcompo- nents: strategic integration and cultural assimilation, which address how technology needs to be measured as it relates to business strategy, and what related social– structural changes are needed, respectively.

Change is an important principle of this book. I talk about the importance of how to change, how to manage such change, and why emerging technologies are a significant agent of change. I support the need for change, as an opportunity to use many of the learning theories that have been historically difficult to implement. That is, implementing change brought on by technological innovation is an opportunity to make the organization more “ change ready” or, as we define it today, more “ agile.” However, we also know that little is known about how organizations should actually go about modifying existing processes to adapt to new technologies and become digital entities— and to be accustomed to doing this regularly. Managing through such periods of change requires that we develop a model that can deal with dynamic, unpredictable, and accelerated change. This is what responsive organizational dynamism is designed to do.

We know that over 20% of IT projects still fail to be completed. Another 54% fail to meet their projected completion date. We now sit at the forefront of another technological spurt of innovations that will necessitate major renovations to existing legacy systems, requiring that they be linked to sophisticated e-business systems. These e-business systems will continue to utilize the Internet, and emerging mobile

 

 

xxvIntroduCtIon

technologies. While we tend to focus primarily on what technology generically does, organizations need urgently to prepare themselves for the next generation of advances, by forming structures that can deal with continued, accelerated change, as the norm of daily opera- tions. For this edition, I have added new sections and chapters that address the digital transformation, ways of dealing with changing consumer behavior, the need to form evolving cyber security cultures, and the importance of integrating Gen Y employees to accelerate competitive advantage.

 

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Topic: Purchasing Power Parity (PPP)

Discussion Forum Week 9

 

Topic: Purchasing Power Parity (PPP)

 

Discussion Forum Week 9

Once you have completed your research, return to your “initial post” and respond to it; actually past the paper’s body in the text section (for your peers to read). Also, attach the actual paper so the professor can review it for proper APA formatting.

[Your research papaer should be at least  500+ words and in APA format (including Times New Roman with font size 12 and double spaced).]

Submitting your Research Paper : Your research paper should be submitted by  Thursday, 11:59 p.m. EST.

Response to Other Student Postings :  Respond substantively to the post of at least two peers, by  Friday, 11:59 p.m. EST. A peer response such as “I agree with her,” or “I liked what he said about that” or similar comments are not considered substantive and will not be counted for course credit.

[Continue the discussion through  Sunday,11:59 p.m. EST by highlighting differences between your postings and your colleagues’ postings. Provide additional insights or alternative perspectives.]

Evaluation of posts and responses:  Your initial posts and peer responses will be evaluated on the basis of the kind of critical thinking and engagement displayed. The grading rubric evaluates the content based on seven areas:

Content Knowledge & Structure, Critical Thinking, Clarity & Effective Communication, Integration of Knowledge & Articles, Presentation, Writing Mechanics, and Response to Other Students.

 

 

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Report on one of the topics from the list below and explain in your  OWN words its basic operation, and uses.

Report on one of the topics from the list below and explain in your  OWN words its basic operation, and uses.  Identify which basic  operational amplifier configuration is being used in the application  (inverting, non-inverting or voltage divider) and which gain equation is  needed for the application.

  • Comparators
  • Summing Amplifiers
  • Integrators
  • Differentiators

APA Format

Answer the below two Data Analytics questions.

Answer the below two Data Analytics questions.  Attached are documents to help answer the questions. School A is Arizona St. and school B is Boise St.

1. Take a look at the graduation rate of classes with fewer than 20 students and greater than 50 students and determine if the size of the class impacts the graduation rate?

2. Does the graduation rate have a direct impact on the giving rate?

 

Alternative Solutions

 

LT20

Percentage of classes with fewer than 20 students

 

GT50

Percentage of classes with greater than 50 students

 

GRAD

Average six-year graduation rate

 

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health care articles that use quantitative research.

Search the GCU Library and find two new health care articles that use quantitative research. Do not use articles from a previous assignment, or articles that appear in the Topic Materials or textbook.

Complete an article analysis for each using the “Article Analysis: Part 2” template.

Refer to the “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial,” ( https://www-sciencedirect-com.lopes.idm.oclc.org/science/article/pii/S0020748913000941)

in conjunction with the “Article Analysis Example 2,” for an example of an article analysis (Attached).

While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

 

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Project Part 5 – Final Report

Project Part 5 – Final Report

You will submit a final report, written in Word (or similar word processing software), APA format based on your findings and submissions from parts 1-4. It is highly suggested you not submit this paper without first reviewing all the feedback from your instructor on submissions from weeks 1-6. Be sure to ask any questions you may have on your feedback.

This final submission should be three paragraphs and summarize your entire project. It will be submitted through SafeAssign, Liberty’s Plagiarism software on BlackBoard. The project must be submitted in paragraph form and not just a list of the calculations from your project. Be sure your paragraphs flow (not just listing the answers to the questions, but complete sentences with transitions) and are written in third person. You are presenting your results to a nonstatistical audience, do not describe the calculations, describe your results. It should include the following:

  • Paragraph 1:

· Brief summary of the article, including the source

§ Link for article: https://www.usnews.com/higher-education/online-education/articles/2017-04-04/us-news-data-the-average-online-bachelors-student

Link for article

https://www.usnews.com/higher-education/online-education/articles/2017-04-04/us-news-data-the-average-online-bachelors-student

· Define the population, sample, and statistic for the study

· Statement of the two claims in the article that were tested in this project

· Null and alternative hypothesis for both tests run for this project (in words)

  • Paragraph 2 (address the claim about the mean):

· Summary of sample statistics (mean, standard deviation, median, quartiles, sample size)

· Confidence interval, along with interpretation of the confidence interval

· Description of hypothesis test (alpha, test statistic, p-value, conclusion, interpretation)

  • Paragraph 3 (address the claim about the proportion):

· Summary of sample statistics (sample size, successes, proportion)

· Confidence interval, along with interpretation of the confidence interval

· Description of hypothesis test (alpha, test statistic, p-value, conclusion, interpretation)

Project Part 5 – Final Report

Project Part 5 – Final Report

Final Report 3

 

 

 

 

 

Project Part 5 – Final Report

Name

Liberty University

MATH 201 – B11

Dr. xxxxx xxxxx

March 8, 2021

 

 

 

 

 

 

 

 

 

Summary

 

 

 

 

 

 

 

 

 

 

The null hypothesis: (claim about the mean)

 

 

 

 

 

 

 

 

 

The alternative hypothesis: (claim about the proportion)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References

https://www.usnews.com/higher-education/online-education/articles/2017-04-04/us-news-data-the-average-online-bachelors-student.

Ferrão, M. E. (2020). Statistical Methods in Recent Higher Education Research. Journal of College Student Development61(3), 366-371.

Hazra, A. (2017). Using the confidence interval confidently. Journal of thoracic disease9(10), 4125.

Student Instructions BM

Student Instructions BM

Overview – Benchmark
Your group has been given a dataset containing 240 records, located in the Student_BM tab of this spreadsheet..
Each student is only responsible for analyzing 60 of these record records – the specifics of which will be assigned by the instructor.
It is important that each student has a unique 60 records, as the results will be an input into the CLC, and duplication of
results is not helpful. Note that the data have been randomized, so the data given to your group are likely different than the
data given to other groups.
The intent of this assignment is for students to organize their data using a pivot table, get a graphical understanding
of the data through a bar chart, then do hypothesis testing comparing Bo Diddly Tech results versus the national average.
All of your analysis should be done in the Student_BM tab of this spreadsheet and submitted as part of the assignmemt.
The location where the pivot table, bar chart, and relevant information should be placed in the Student_BM tab is
indicated by RED instructions.
Once completed, the Student_BM tab will serve as the basis for writing your management report. It is expected that any
conclusions you draw in the management report will be consistent with the data and analyses contained in the spreadsheet.
Instructions Data Analysis Component:
1. Make a pivot table with: Business Student (Rows), Athlete (Rows), Cheated (Columns), and Cheated (Summed Value).
2. Create a bar chart showing cheating by athletes and business students.
4. Determine if there is a statistical difference between nonathlete BDT business students and the national average for business
students as reported by the Chronicle of Higher Education.
5. Determine if there is a statistical difference between athlete BDT business students and the national average for business
students as reported by the Chronicle of Higher Education.
6. Determine if there is a statistical difference between BDT business students and the national average for business students
as reported by the Chronicle of Higher Education.
7. Determine if there is a statistical difference between BDT nonbusiness students and the national average for nonbusiness
students as reported by the Chronicle of Higher Education.
Instructions Data Interpretation Component:
Utilizing the data you have analyzed, write a managerial report of 500-800 words to the dean. The managerial report needs to
include an introduction, analysis, conclusion, and a minimum of three supporting references.
1. Introduction (Define): Explain in your own words why you are providing this report and the problem(s) you are trying to solve.
2. Collect: Describe the data set you used.
3. Organize: Describe your pivot table.
4. Visualize: Include and describe your bar chart.
5. Analyze: Provide a summary of your conclusions based upon the four population proportion hypothesis tests.
6. The Dean has expressed a concern related to the amount of cheating currently taking place at Bo Diddley Tech and has strongly
suggested that you “tweak” the statistical data such that it favors the image of the university.
Discuss the potential use of unethical manipulation of statistical data to provide a biased outcome as well as the ethical counter
proposal you would offer the dean in this scenario.
7. Conclusion: What advice would you give to the dean based on your analysis of the data?

Student_BM

CollegeAthleteCheated1. Pivot TableNationwide Average% Cheated
Insert pivot table in this cell – F2Business56%
Nonbusiness47%
Insert pivot table in this cell – F2
Bar chart starts in this cell – F20
Bar chart starts in this cell – F20
Insert the appropriate numbers into the hypothesis testing calculations below based upon your pivot table results. Note the results.
3-6 Hypothesis Test
Business Nonathlete vs. National AverageBusiness Athlete vs. National AverageBusiness vs. National AverageNonbusiness vs. National AverageBusiness Athlete vs. Business Nonathlete
ProportionProportionProportionProportionp1 and p2 Proportion
Sample Size (n) =count(range)ERROR:#REF!Sample Size (n) =count(range)ERROR:#REF!Sample Size (n) =count(range)ERROR:#REF!Sample Size (n) =count(range)ERROR:#REF!AthleteNonathlete
Response of Interest (ROI)CheatedResponse of Interest (ROI)CheatedResponse of Interest (ROI)CheatedResponse of Interest (ROI)CheatedSample Size (n1 or n2) =COUNT(range)ERROR:#REF!ERROR:#REF!ERROR:#REF!
Count for Response (CFR) =COUNTIF(range,ROI)ERROR:#REF!Count for Response (CFR) =COUNTIF(range,ROI)ERROR:#REF!Count for Response (CFR) =COUNTIF(range,ROI)ERROR:#REF!Count for Response (CFR) =COUNTIF(range,ROI)ERROR:#REF!Response of Interest (ROI)ERROR:#REF!ERROR:#REF!ERROR:#REF!
Sample Proportion (pbar) =CFR/nERROR:#REF!Sample Proportion (pbar) =CFR/nERROR:#REF!Sample Proportion (pbar) =CFR/nERROR:#REF!Sample Proportion (pbar) =CFR/nERROR:#REF!Count for Response (CFR) =COUNTIF(n1or2,ROI)Did Not CheatDid Not Cheat
Sample Proportion (p1 or p2) =CFR1or2/n1or2ERROR:#REF!ERROR:#REF!
Highlight your H0 and HaTwo Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > poHighlight your H0 and HaTwo Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > poHighlight your H0 and HaTwo Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > poHighlight your H0 and HaTwo Tail H0: p = po Ha: p ≠ po Left Tail H0: p ≥ po Ha: p < po Right Tail H0: p ≤ po Ha: p > po
Hypothesized0.56Hypothesized0.56Hypothesized0.56Hypothesized0.47Highlight your H0 and HaTwo Tail H0: p1-p2=0 Left Tail H0: p1-p2≥0 Right Tail H0: p1-p2≤0Ha: p1-p2≠0 Ha: p1-p2<0 Ha: p1-p2>0
Confidence Coefficient (Coe)0.95Confidence Coefficient (Coe)0.95Confidence Coefficient (Coe)0.95Confidence Coefficient (Coe)0.95Hypothesized Value0
Level of Significance (alpha) =1-Coe0.05Level of Significance (alpha) =1-Coe0.05Level of Significance (alpha) =1-Coe0.05Level of Significance (alpha) =1-Coe0.05Level of Sig. α0.05
Point Estimation of Difference (Point) =p1-p2ERROR:#REF!
Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n)ERROR:#REF!Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n)ERROR:#REF!Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n)ERROR:#REF!Standard Error (StdError) =SQRT(Hypo*(1-Hypo)/n)ERROR:#REF!
Test Statistic (Z-stat) =(pbar-Hypo)/StdErrorERROR:#REF!Test Statistic (Z-stat) =(pbar-Hypo)/StdErrorERROR:#REF!Test Statistic (Z-stat) =(pbar-Hypo)/StdErrorERROR:#REF!Test Statistic (Z-stat) =(pbar-Hypo)/StdErrorERROR:#REF!Pooled Estimation of p (PE) =(n1*p1+n2*p2)/(n1+n2)ERROR:#REF!
Accept or Reject: Left TailERROR:#REF!Accept or Reject: Left TailERROR:#REF!Accept or Reject: Left TailERROR:#REF!Accept or Reject: Left TailERROR:#REF!Standard Error (StdError) =SQRT(PE*(1-PE)*(1/n1+1/n2))ERROR:#REF!
Accept or Reject: Right TailERROR:#REF!Accept or Reject: Right TailERROR:#REF!Accept or Reject: Right TailERROR:#REF!Accept or Reject: Right TailERROR:#REF!Test Statistic Z-stat =(Point-Hypo)/StdErrorERROR:#REF!
Accept or Reject: Two TailERROR:#REF!Accept or Reject: Two TailERROR:#REF!Accept or Reject: Two TailERROR:#REF!Accept or Reject: Two TailERROR:#REF!Accept or Reject: Left TailERROR:#REF!
Accept or Reject: Right TailERROR:#REF!
p-value (Lower Tail) =NORM.S.DIST(z,TRUE)ERROR:#REF!p-value (Lower Tail) =NORM.S.DIST(z,TRUE)ERROR:#REF!p-value (Lower Tail) =NORM.S.DIST(z,TRUE)ERROR:#REF!p-value (Lower Tail) =NORM.S.DIST(z,TRUE)ERROR:#REF!Accept or Reject: Two TailERROR:#REF!
p-value (Upper Tail) =1-LowerTailERROR:#REF!p-value (Upper Tail) =1-LowerTailERROR:#REF!p-value (Upper Tail) =1-LowerTailERROR:#REF!p-value (Upper Tail) =1-LowerTailERROR:#REF!
p-value (Two Tail) =2*MIN(LowerTail,UpperTail)ERROR:#REF!p-value (Two Tail) =2*MIN(LowerTail,UpperTail)ERROR:#REF!p-value (Two Tail) =2*MIN(LowerTail,UpperTail)ERROR:#REF!p-value (Two Tail) =2*MIN(LowerTail,UpperTail)ERROR:#REF!p-value (Lower Tail) =NORM.S.DIST(Zstat,TRUE)ERROR:#REF!
Accept or Reject p-value: Left TailERROR:#REF!Accept or Reject p-value: Left TailERROR:#REF!Accept or Reject p-value: Left TailERROR:#REF!Accept or Reject p-value: Left TailERROR:#REF!p-value (Upper Tail) =1-LowerTailERROR:#REF!
Accept or Reject p-value: Right TailERROR:#REF!Accept or Reject p-value: Right TailERROR:#REF!Accept or Reject p-value: Right TailERROR:#REF!Accept or Reject p-value: Right TailERROR:#REF!p-value (Two Tail) =2*MIN(LowerTail,UpperTail)ERROR:#REF!
Accept or Reject p-value: Two TailERROR:#REF!Accept or Reject p-value: Two TailERROR:#REF!Accept or Reject p-value: Two TailERROR:#REF!Accept or Reject p-value: Two TailERROR:#REF!Accept or Reject p-value: Left TailERROR:#REF!
Accept or Reject p-value: Right TailERROR:#REF!
p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n)ERROR:#REF!p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n)ERROR:#REF!p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n)ERROR:#REF!p-Lower Limit =pbar-CONFIDENCE.NORM(alpha,StdError,n)ERROR:#REF!Accept or Reject p-value: Two TailERROR:#REF!
p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n)ERROR:#REF!p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n)ERROR:#REF!p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n)ERROR:#REF!p-Upper Limit =pbar+CONFIDENCE.NORM(alpha,StdError,n)ERROR:#REF!
Based upon the count of cheaters, categorized into business and nonbusiness students, place the relevant numbers in the purple area of the table below and note the conclusion.
8. Test of Independence – Is cheating independent of college and athletic participation?
Comparing business and nonbusiness students number of cheaters for athletes and nonathletes
Ho: all groups cheat at the same rate
Ha: there is a difference in cheating based upon college or athletic participation
Independent Variable
BusinessNonbusinessCalculations
Dependent variableObsExpObsExpTotalERROR:#REF!ERROR:#REF!
AthleteERROR:#REF!ERROR:#REF!ERROR:#REF!ERROR:#REF!ERROR:#REF!ERROR:#REF!ERROR:#REF!
NonathleteERROR:#REF!ERROR:#REF!ERROR:#REF!ERROR:#REF!ERROR:#REF!
TotalERROR:#REF!ERROR:#REF!ERROR:#REF!
Chi square test statistic =ERROR:#REF!
Level of signicance0.05
# of rows2
# of columns2
df =1df = (rows – 1)(columns – 1)
p-factor =ERROR:#REF!
Chi square critical3.8415
Conclusion:ERROR:#REF!

Data

 

 

 

 

 

 

 

 

 

CollegeAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessAthleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessNonathleteCheated
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessAthleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
BusinessNonathleteDid Not Cheat
NonbusinessAthleteDid Not Cheat
NonbusinessAthleteDid Not Cheat
NonbusinessAthleteDid Not Cheat
NonbusinessAthleteDid Not Cheat
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessAthleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
NonbusinessNonathleteCheated
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Nonbusiness

NonathleteCheated

Chronicle of Higher Education.

During the global recession of 2008 and 2009, there were many accusations of unethical behavior by Wall Street executives, financial managers, and other corporate officers. At that time, an article appeared that suggested that part of the reason for such unethical business behavior may have stemmed from the fact that cheating had become more prevalent among business students, according to a February 10, 2009, article in the Chronicle of Higher Education. The article reported that 56% of business students admitted to cheating at some time during their academic career as compared to 47% of nonbusiness students.

Cheating has been a concern of the dean of the college of business at Bo Diddley Tech (BDT) for several years. Some faculty members in the college believe that cheating is more widespread at BDT than at other universities, whereas other faculty members think that cheating is not a major problem in the college. To resolve some of these issues, the dean commissioned a study to assess the current ethical behavior of business students at BDT. As a former college athlete herself, the dean believed that the spirit of fair play students develop as part of participating in athletics would make them less likely to cheat. As part of this study, an anonymous exit survey was administered to a sample of 240 students from this year’s graduating class, half of whom were business students and half of whom were not. The survey asked various questions, including the student’s college and if the student was an athlete or not. Responses of the various questions were fed into a computer algorithm that made a quantitative determination as to whether the student should be considered a “cheater” or not. The results are in the attached Excel spreadsheet, “Benchmark –  Bo Diddley Tech Data Set.”

Prepare a managerial report as part of your submission to the dean of the college that summarizes your assessment of the nature of cheating at BDT. Be sure to include the following items in your written report.

Utilize the data set provided by the instructor in the Excel spreadsheet, “Benchmark – Bo Diddley Tech Data Set” (60 records per student).

Submit the Excel data calculations (Alpha 0.05).

  1. Make a pivot table with: Business Student (Rows), Athlete (Rows), Cheated (Columns), and Cheated (Summed Value).
  2. Create a bar chart showing cheating by athletes and business students.
  3. Determine if there is a statistical difference between nonathlete BDT business students and the national average for business students as reported by the Chronicle of Higher Education.
  4. Determine if there is a statistical difference between athlete BDT business students and the national average for business students as reported by the Chronicle of Higher Education.
  5. Determine if there is a statistical difference between BDT business students and the national average for business students as reported by the Chronicle of Higher Education.
  6. Determine if there is a statistical difference between BDT nonbusiness students and the national average for nonbusiness students as reported by the Chronicle of Higher Education.

Utilizing the data you have analyzed, write a managerial report of 500-800 words for the dean. The managerial report needs to include an introduction, analysis, conclusion, and a minimum of three supporting references.

  1. Introduction (Define): Explain, in your own words, why you are providing this report and the problem(s) you are trying to solve.
  2. Collect: Describe the data set you used.
  3. Organize: Describe your pivot table.
  4. Visualize: Include and describe your bar chart.
  5. Analyze: Provide a summary of your conclusions based on the four population proportion hypothesis tests.
  6. Ethical Summary: The dean has expressed a concern related to the amount of cheating currently taking place at BDT and has strongly suggested that you “tweak” the statistical data such that they favor the image of the university. Discuss the potential use of unethical manipulation of statistical data to provide a biased outcome as well as the ethical counter proposal you would offer the dean in this scenario.
  7. Conclusion: What advice would you give to the dean based upon your analysis of the data?

You are required to submit your Excel data analysis along with your written report.

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

Benchmark Information

This benchmark assignment assesses the following programmatic competencies:

BS Business Information Systems,

2.2 Use quantitative techniques and tools to analyze data relevant to business decision making. [MC3]

BS Business Administration, BS Business Information Systems, BS Accounting, BS Business Analytics, BS Business Management, BS Entrepreneurial Studies, BS Finance, BS Finance and Economics, BS Hospitality Management, BS Sports Management, BS Supply Chain and Logistics Management

2.3: Use quantitative techniques and tools to analyze data relevant to business decision making. [MC3]

BS Business for Secondary Education

7.3: Use appropriate computer applications to perform mathematical calculations relevant to solving business problems.

 

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